Search for biomarkers related to rhinitis and different asthma phenotypes by serum proteomics and immunoassays

TESIS DE DOCTORADO SEARCH FOR BIOMARKERS RELATED TO RHINITIS AND DIFFERENT ASTHMA PHENOTYPES BY SERUM PROTEOMICS AND IMMUNOASSAYS Juan José Nieto Fontarigo ESCUELA DE DOCTORADO INTERNACIONAL PROGRAMA DE DOCTORADO EN MEDICINA MOLECULAR SANTIAGO DE COMPOSTELA 2019 DECLARACIÓN DO AUTOR/A DA TESE SEARCH FOR BIOMARKERS RELATED TO RHINITIS AND DIFFERENT ASTHMA PHENOTYPES BY SERUM PROTEOMICS AND IMMUNOASSAYS D./Dna. Juan José Nieto Fontarigo Presento a miña tese, seguindo o procedemento axeitado ao Regulamento, e declaro que: 1) A tese abarca os resultados da elaboración do meu traballo. 2) De selo caso, na tese faise referencia ás colaboracións que tivo este traballo. 3) A tese é a versión definitiva presentada para a súa defensa e coincide coa versión enviada en formato electrónico. 4) Confirmo que a tese non incorre en ningún tipo de plaxio doutros autores nin de traballos presentados por min para a obtención doutros títulos. En Santiago de Compostela, 26 de Marzo de 2019. Asdo. Juan José Nieto Fontarigo AUTORIZACIÓN DO DIRECTOR / TITOR DA TESE SEARCH FOR BIOMARKERS RELATED TO RHINITIS AND DIFFERENT ASTHMA PHENOTYPES BY SERUM PROTEOMICS AND IMMUNOASSAYS D./Dna. Francisco Javier Salgado Castro D./Dna. Montserrat Nogueira Álvarez INFORMA/N: Que a presente tese, correspóndese co traballo realizado por D/Dna. Juan José Nieto Fontarigo, baixo a nosa dirección, e a utorizamos a súa presentación , considerando que reúne os r equisitos esixidos no R egulamento de Estudos de Doutoramento da USC, e que como directores desta non incorre nas causas de abstención establecidas na Lei 40/2015. En Santiago de Compostela, 26 de Marzo de 2019. Asdo. Asdo. Francisco Javier Salgado Castro Montserrat Nogueira Álvarez CONFLICTO DE INTERÉS SEARCH FOR BIOMARKERS RELATED TO RHINITIS AND DIFFERENT ASTHMA PHENOTYPES BY SERUM PROTEOMICS AND IMMUNOASSAYS D. Juan José Nieto Fontarigo Declaro no tener ningún tipo de conflicto de intereses, ni ninguna relación económica, personal, política, interés financiero ni académico que pueda influir en este trabajo. En Santiago de Compostela, 26 de Marzo de 2019. Fdo. Juan José Nieto Fontarigo Esta tesis y los trabajos derivados se han realizado en el Centro de Investigación en Biología de la Universidad de Santiago de Compostela (CIBUS) – Facultad de Biología, Campus vida, Universidade de Santiago de Compostela gracias al financiamiento de los proyectos (121/2012) por la Sociedad Española de Neumología y Cirugía Torácica, (SEPAR) y el (PI13/02046) del Instituto de Salud Carlos III, Ministerio de Economía y Competitividad (Fondo de Investigación Sanitaria, FIS; cofinanciado por fondos FEDER de la Unión Europea) El autor de esta tesis, D. Juan José Nieto Fontarigo, ha sido benficiario de la beca predoctoral de la Xunta de Galicia (DOG Núm. 122, Páx. 27453, Mércores, 29 de xuño de 2016), Modalidad B (Cofinanciadas por Fondo Social Europeo, FSE). Todos los trabajos realizados en esta tesis cuentan con la aprobación del Comité de Ética de Investigación Clínica de Galicia (CEIC)(2011/001), y todos los participantes en los mismos han firmado un consentimiento informado. Juan José Nieto Fontarigo AIMS OF THE THESIS ............................................................. 85–87 CHAPTER I ........................................................................................ 89–119 Introduction ............................................................................................................... 91–92 Material and Methods ............................................................................................... 92–96 Results ..................................................................................................................... 96–108 Discussion ............................................................................................................. 108–112 References ............................................................................................................ 112–117 Supplementary Information ................................................................................. 118–119 CHAPTER II .............................................................................. 121–155 Introduction .......................................................................................................... 123–125 Material and Methods .......................................................................................... 125–129 Results .................................................................................................................. 129–139 Discussion ............................................................................................................. 139–146 References ............................................................................................................ 146–153 Supplementary Information ................................................................................. 154–155 CHAPTER III............................................................................. 157–204 Introduction .......................................................................................................... 159–161 Material and Methods .......................................................................................... 161–165 Results .................................................................................................................. 165–180 Discussion ............................................................................................................. 181–185 References ............................................................................................................ 186–194 Supplementary Information ................................................................................. 195–204 CHAPTER IV ............................................................................. 205–258 Introduction .......................................................................................................... 207–210 Material and Methods .......................................................................................... 210–213 Results .................................................................................................................. 213–233 Discussion ............................................................................................................. 233–238 References ............................................................................................................ 239–248 Supplementary Information ................................................................................. 249–258 GENERAL DISCUSSION ...................................................... 259–278 1. INNATE IMMUNE SYSTEM BIOMARKERS OF ALLERGIC ASTHMA (AA) (Chapter I) .................................................................................................. 259–265 2. CD26, ADAPTIVE IMMUNE CELLS, AND ASTHMA PHENOTYPES INDEX (Chapters II and III) ...................................................................................... 265–273 3. SEARCHING FOR BIOMARKERS IN SERUM SAMPLES FROM PATIENTS WITH RHINITIS OR DIFFERENT ASTHMA PHENOTYPES/SEVERITIES (Chapter IV) ..... 273–278 CONCLUSIONS ...................................................................... 279–283 REFERENCES (Introduction and General Discussion) ...... 285–342 APPENDIX I .................................................................................... 343 ABBREVIATIONS I ABBREVIATIONS 2-DE: Two dimension electrophoresis 2D-DIGE: 2D Fluorescence Difference Gel Electrophoresis AA: Allergic asthma ADA: Adenosine deaminase AECs: Airway epithelial cells AHSG: α-2-HS-glycoprotein AHR: Airway hyperresponsiveness APCs: Antigen presenting cells BALF: Bronchoalveolar lavage fluid BB: Bronchial biopsies BCR: B-cell receptor BIM: Bcl-2 interacting mediator CFH: Complement factor H CFI: Complement factor I CPLLs: Combinatorial peptide ligand libraries CSF: Cerebrospinal fluid DAMPs: Damage associated molecular patterns DPP: Dipeptidyl peptidase protein EBC: Exhaled breath condensate ELISAs: Enzyme-linked immunosorbent assays ESI: Electrospray ionisation EU: European Union FeNO: Fractional exhaled nitric oxid GWAS: Genome-wide association studies HDM: House dust mite HSPG2: Heparan sulphate proteoglycan 2 ICS: Inhaled costicosteroids IGFs: Insuline-like growth factors IGFALS: Insulin-like growth factor binding protein, acid labile subunit IGFBPs: Insulin-like growth factor binding proteins Juan José Nieto Fontarigo II ILCs: Innate lymphoid cells iNKT: Invariant natural killer T cells iTRAQ: Isobaric tag for relative and absolute quantitation iTregs: Induced regulatory T cells LAP: Low abundant proteins LBP: Lipopolysaccharide binding protein LC: Liquid chromatography LC-MS/MS: Liquid chromatography coupled to mass spectrometry LMW: Low molecular weight proteins LPS: Lipopolysaccharide LTQ: Linear trap quadrupole MALDI-TOF: Matrix-Assisted Laser Desorption/Ionizationtime-of-flight mCD14: Membrane CD14 MHC: Major histocompatibility complex MS: Mass spectrometry NAA: Non-allergic asthma NB: Nasal brushing NK: Natural killer NLF: Nasal lavage fluid NSE: Neuron-specific enolase nTregs: Natural regulatory T cells ORM1/AGP: Orosomucoid/α-1-acid glycoprotein 1 OVA: Ovalbumin PAMPs: Pathogen associated molecular patterns. Protein AMBP: α-1-microglobulin/bikunin precursor PRRs: Pathogen recognition receptors PCs: Principal components RP: Reverse phase sCD14: Soluble CD14 ABBREVIATIONS III sCD25: Soluble CD25 sCD26: Soluble CD26 SCX: Strong cation exchange SNPs: Single nucleotide polymorphisms TCM: Central-memory T cells TCR: T-cell receptor TEM: Effector-memory T cells TEMRA: Terminally-differentiated effector T cells Teff: Effector T cells TfH: Follicular helper T cells TH: Helper T cells TLRs: Toll-like receptors TN: Naïve T cells Treg: Regulatory T cells TSCM: Stem cell memory T cells UPLC: Ultra performance liquid chromatography US: United States WT: Wild type ABSTRACT 3 sthma is a heterogeneous disease with several clinical phenotypes and molecular endotypes. However, the specific connection between asthma phenotypes and the underlying pathological features is difficult to explain. Thus, the overall aim of the present thesis was to search for biomarkers associated with rhinitis and different phenotypes (allergic and non-allergic) and severities (intermittent-mild and moderate-severe) of asthma, which could have an application in the diagnosis, prognosis or treatment of this disease. The mechanisms underlying asthma are multiple and complex, but the immune system plays a key role in the pathophysiology of this disease. Therefore, we decided to further study the role of the immune system in different phenotypes or severities of asthma through the analysis of certain biomarkers previously related to this disease: CD14 (innate immune system) and CD26/CD126 (adaptive immune system). CD14 is a receptor mainly expressed on monocytes, which participates in the lipopolysaccharide (LPS) signalling. Our results show that both the expression of CD14 on monocytes and the normalized levels of soluble CD14 (sCD14) in serum are reduced in allergic asthma vs. healthy controls. This reduction can be explained by the expansion of CD14low cells, probably non-classical monocytes with a high capacity to differentiate into M2 macrophages. In addition, sCD14 levels are associated with the promoter SNP of CD14 (-159 C/T). Thus, subjects with the C allele and CC genotype have lower levels of sCD14, as well as increased risk of allergic asthma. On the other hand, CD26 is a peptidase mainly expressed by helper T (TH) lymphocytes. Our results evidence a high correlation between the expression of CD26 on those cells and DPP4 activity (~ soluble CD26/sCD26) in vitro. Moreover, the expression of this molecule differentiates subtypes of T cells (TH17>>TH1>TH2>Treg), as well as discriminates between cells with different stages of differentiation: central-memory T cells (TCM, CD26high, CD45RA-CCR7+CD28+), naïve T cells (TN, CD26int, CD45RA+CCR7+CD28+), and terminally differentiated or effector-memory T cells (TEM or TEMRA, CD26low, CD45RA+/-CCR7-CD28-). In addition, there is an A Juan José Nieto Fontarigo 10 biomarcadores séricos en asma (aplicable a otras patologías también), así como la realización de un estudio prospectivo, no dirigido, para identificar nuevos marcadores biológicos asociados con distintos fenotipos y/o severidades de esta enfermedad. Para ello, tras probar diferentes metodologías, se ha desarrollado un protocolo que consiste en una eliminación de lipoproteínas del suero, el enriquecimiento en proteínas de media-baja abundancia mediante librerías de hexapéptidos combinatorios (CPLLs) (compresión del rango dinámico de abundancias), la generación de péptidos trípticos, su marcaje mediante reactivos iTRAQ, y el fraccionamiento, identificación y cuantificación relativa mediante cromatografía líquida en fase reversa acoplada a espectrometría de masas en tándem (LC-MS/MS). Capítulo I El estudio que se expone en el capítulo I tuvo como objetivo el estudio de la expresión de CD14 en la superficie de monocitos, así como el análisis de los niveles de CD14 soluble, su relación con el SNP del promotor de CD14 (-159 C/T) y la susceptibilidad de sufrir asma alérgica. Todo esto en una población bien definida (adultos, caucásicos, bajos niveles de endotoxina) y con un tamaño muestral relativamente elevado (277 pacientes con asma alérgica y 277 controles sanos). Los resultados de este estudio demostraron un aumento del número de monocitos en pacientes con asma alérgica pocas veces descrito previamente. Sin embargo, la expresión de CD14 en la superficie de estas células, así como la concentración de CD14 soluble (normalizado por el número de monocitos) en suero estaban reducidos en los pacientes con asma. Dicha reducción podría deberse a la expansión de monocitos con fenotipo CD14-, probablemente de tipo “no clásico” (CD14-CD16+) y con alta capacidad de diferenciarse a macrófagos tisulares M2. Pero además, a ello se podría sumar el efecto del SNP CD14 (-159 C/T) sobre los niveles de sCD14. De SUMMARY IN SPANISH 11 hecho, nuestros resultados apuntan a mayores niveles de sCD14 en individuos portadores del alelo T y del genotipo TT. Además, tanto el alelo T como el genotipo TT de dicho SNP están asociados a un menor riesgo de sufrir asma alérgica. O dicho de otro modo, nuestros resultados sugieren un papel para el alelo C o el genotipo CC del SNP (-159 C/T) a la hora de generar bajos niveles de CD14 soluble y aumentar el riesgo de desarrollar asma alérgica de mayor gravedad. Los menores niveles de CD14/CD14 soluble en individuos con asma alérgica tienen sentido biológico, ya que esta molécula constituye junto con “Toll-like Receptor 4” (TLR4) un complejo responsable de la señalización del lipopolisacárido bacteriano (LPS) en monocitos/macrófagos. Dicha vía desencadena la producción de citoquinas como IL-12, promoviendo la diferenciación TH1 en detrimento de la TH2. Finalmente, debido al aumento de monocitos circulantes detectado en pacientes con asma alérgica, durante la realización de este estudio también se analizaron los niveles de la enolasa neuronal específica (NSE), una molécula que se ha visto aumentada tras activación de eosinófilos y macrófagos en algunas enfermedades. Nuestros resultados muestran una correlación positiva entra las concentraciones séricas de esta molécula e IgE total, ambas aumentadas en pacientes con asma alérgica. De hecho, la eficiencia diagnóstica evaluada a través de los valores de “area under the curve” AUC de las curvas “Receiver Operating Characteristic” (ROC) demuestran unos valores muy similares de efectividad diagnóstica para NSE e IgE, subrayando un posible uso como biomarcador de este fenotipo asmático. Juan José Nieto Fontarigo 12 Capítulos II y III Del mismo modo que sucede con CD14 en monocitos, CD26 es una peptidasa con actividad DPP4 que muestra una especial abundancia en linfocitos T colaboradores (TCD4+; sistema inmune adaptativo), que presenta una forma soluble, y que también ha sido asociada al asma por diversos autores. Los estudios llevados a cabo en los capítulos II y III tienen como objetivo profundizar en esta última asociación en relación con los distintos fenotipos asmáticos y severidades. CD26/DPP4 es una proteína “pluriempleada” (“moonlighting”), lo que hace que su papel en asma sea complejo de estudiar. Además, la práctica ausencia de estudios de revisión bibliográfica sobre las funciones de esta molécula y sus posibles consecuencias en asma impulsó el trabajo que se muestra en el anexo I de la presente tesis (Anexo I). Este proporciona una visión general y estructurada de las distintas funciones pro- y anti-inflamatorias de CD26, así como de las posibles implicaciones en la fisiopatología asmática. Estudios previos en nuestro grupo habían demostrado una mayor abundancia de CD26 en las células T efectoras que en células T reguladoras. Además, otros autores habían demostrado que los niveles de CD26 dentro de las células efectoras eran bastante variables: TH17>> TH1> TH2> Treg. Con esa idea en mente, nuestro trabajo (Capítulo II) demostró por primera vez en cultivo in vitro un aumento de expresión de CD26 en linfocitos TH efectores humanos tras activación, especialmente en condiciones que promovían una diferenciación TH17, pero también una correlación positiva con la actividad DPP4 soluble (una medida indirecta de CD26 soluble). Por tanto, nuestros resultados sugerían que los niveles de CD26/DPP4 soluble in vitro estaban influenciados por el número de linfocitos T CD4+ así como por su grado de activación y fenotipo (TH1, TH2, o TH17), de modo que los niveles de CD26 soluble en suero podrían estar reflejando, como una “huella dactilar”, la contracción o expansión de unas subpoblaciones TH sobre SUMMARY IN SPANISH 13 otras; dicho de otro modo, podría haber diferencias en la expresión de CD26 en los linfocitos TH y en los niveles de su isoforma soluble dependiendo del fenotipo y severidad asmáticas. Por tanto, esta hipótesis inicial fue examinada en estudios con pacientes. En consonancia con dicha hipótesis de partida y también con los resultados de un estudio previo de 2007 publicado por Samantha Wei-Man Lun y colaboradores, la expresión de CD26 en linfocitos TH fue mayor en pacientes con asma alérgica en comparación con los controles sanos. Sin embargo, los niveles de CD26 estaban, contrariamente, reducidos en el suero de estos mismos pacientes; lo mismo ocurría con CD25 soluble, otro marcador de activación. Dado que no se observaron cambios en los porcentajes de células T reguladoras (una población CD26low), estos menores niveles de CD26/CD25 solubles fueron relacionados con la expansión de una subpoblación TH efectora con fenotipo CD25low/CD26low/CD127low (células “triple low” o Tlow) en asma alérgica. Además, dicha expansión fue confirmada en el Capítulo III, donde además se profundizó en la caracterización fenotípica de esta población. Así, se vio que las células Tlow eran células TH en un avanzado estado de diferenciación, con fenotipo “efector de memoria” (TEM) o “terminalmente diferenciado” (TEMRA), caracterizadas por la pérdida de marcadores de superficie como CD27, CD28, CCR7 o CD127. Por tanto, la expresión de CD26 en células TH y sus niveles en suero son indicativos sobre todo de las distintas etapas de diferenciación naïvememoria: células de memoria central (TCM, CD26high), células naïve (TN, CD26intermediate) y células efectoras de memoria o terminalmente diferenciadas (TEM o TEMRA, CD26-/low). De igual forma que en pacientes con asma alérgica, también hemos visto un descenso de CD26 soluble en pacientes con asma no alérgica. Sin embargo, no se observó una expansión significativa en estos pacientes de poblaciones TH con fenotipo TEM/TEMRA (Tlow). Juan José Nieto Fontarigo 14 Por tanto, decidimos enfocar el análisis sobre los linfocitos T CD4-, que incluyen células B, NK, NKT y linfocitos T-γδ. Además, se analizaron no sólo los niveles de CD26, sino también los de CD126/IL-6Rα, ya que IL-6 tiene un papel importante en la generación de linfocitos TH17, ambos con relevancia en asma no alérgica. En el conjunto de linfocitos T CD4-, se observó una elevada correlación entre la expresión de CD26 y CD126. También se documentó en pacientes con asma no alérgica un aumento del porcentaje de linfocitos T CD4- en avanzado estado de diferenciación (TEM/TEMRA) y con fenotipo CD26- o CD126-. Además, a pesar de no observar cambios en los porcentajes de los distintos tipos celulares dentro de los linfocitos T CD4-, nuestros resultados sí evidenciaron un aumento de la proporción de células T-γδ con bajos niveles de CD26 en estos pacientes. Por tanto, ambos fenotipos asmáticos (asma alérgica y asma no alérgica) presentan un paralelismo en relación con la expansión de células CD26-/low altamente diferenciadas (CD27lowCD28lowCCR7lowCD127low) pertenecientes a diferentes linajes: TH en asma alérgica y CD4- T-γδ en asma no alérgica; la reducción de los niveles de CD26 solubles en ambos fenotipos asmáticos sería una “impronta” de dicha expansión en el suero de los pacientes. La reducción de CD26 de membrana o soluble en asma, especialmente el fenotipo no alérgico, debe tenerse en cuenta a la vista del papel modulador de CD26 sobre citoquinas (p.ej., IL-3, GM-CSF) o quimioquinas (p.ej., RANTES o eotaxina); especialmente teniendo en cuenta el papel inhibidor que dicha función tiene sobre la atracción quimiotáctica de células efectoras importantes en asma, como los linfocitos TH o T-γδ. Por ejemplo, eotaxina es una quimioquina muy potente en la atracción de eosinófilos y células TH2 a lugares de inflamación, cuya función se ve truncada por el corte proteolítico producido por CD26. Lo mismo pasa con SDF-1α/CXCL12 o las SUMMARY IN SPANISH 15 quimioquinas inducidas por IFN-γ (CXCL9-11), que son quimioatrayentes de células TH1 a lugares de inflamación. Estas funciones inhibidoras de CD26 deben sobre todo tenerse en cuenta en pacientes con diabetes tipo-II que están recibiendo o van a recibir gliptinas (inhibidores de la actividad DPP4 de CD26) y que además presentan asma (p.ej., asma no alérgica asociada a obesidad), ya que se podría agravar el estado del paciente. El estudio expuesto en el capítulo III también mostró una reducción de los niveles de CD126/IL-6Rα en monocitos, neutrófilos y linfocitos TH en pacientes con asma moderado-grave en comparación con los pacientes con asma intermitente-leve. Este resultado es indicativo de un papel de CD126/IL-6Rα en la severidad del asma, posiblemente a través de un mecanismo denominado transseñalización en células que son CD126-gp130+. En dicho mecanismo interviene una versión soluble de CD126, que es generada por procesos de procesamiento alternativo del mRNA o mediante proteólisis de la forma anclada a membrana. Finalmente, este estudio también sugiere un defecto funcional (no numérico) en las células T reguladoras de pacientes conforme aumenta la severidad de la enfermedad. Este defecto dependería de una menor producción neta de adenosina, un nucleósido inmunosupresor, como consecuencia de la presencia de mayores niveles de CD26 y menores de CD39 en las células T reguladoras de pacientes con asma moderado-grave comparado con las correspondientes a pacientes con asma intermitente-leve. Capítulo IV En la última parte de esta tesis se planteó como objetivo la identificación de proteínas de baja abundancia de suero que sirviesen como biomarcadores potenciales de fenotipos o severidad asmática. Para ello se desarrolló un método basado la eliminación de Juan José Nieto Fontarigo 16 lipoproteínas del suero y el enriquecimiento de proteínas de baja abundancia mediante el uso de librerías peptídicas aleatorias (CPLLs). Posteriormente, estas muestras enriquecidas en proteínas poco abundantes fueron tripsinizadas, los péptidos fueron etiquetados mediante marcajes isobáricos (iTRAQ) y las proteínas de las distintas muestras (asma alérgica moderado-grave, asma alérgica intermitenteleve, rinitis, asma no alérgica moderado-grave, asma no alérgica intermitente-leve, sanos) fueron identificadas y cuantificadas mediante LC-MS/MS (LTQ-Orbitrap). Para poder tener en cuenta la variabilidad biológica, los sueros de cada uno de los seis grupos muestrales fueron aleatoriamente separados en dos subgrupos y combinados (“pooles biológicos”). A su vez, cada uno de esos “pooles biológicos” fue analizado por triplicado mediante LC-MS/MS. También fue empleado un control interno con el objetivo de normalizar las señales. En conjunto, el estudio proteómico cuantitativo detectó 217 proteínas séricas, dentro de las cuales 26 mostraban una abundancia diferencial entre grupos. Los estudios funcionales (“gene ontology”, GO) han demostrado que estos biomarcadores potenciales desempeñan procesos clave en la patogénesis del asma, tales como activación del complemento, respuesta inmune, respuesta a estímulos bióticos, o respuesta inmune mediada por células B. Los estudios de enriquecimiento (Reactome), por su parte, muestran un enriquecimiento en la vía “Regulación del transporte de factores de crecimiento similares a insulina (IGFs) y captación por proteínas de unión a factores de crecimiento similares a insulina (IGFBPs)” en asma alérgica. A esta vía pertenece IGFALS, un posible biomarcador de asma alérgica (especialmente la moderado-grave) que hemos confirmado ya mediante ELISA. Otras proteínas, en cambio, están pendientes de validación, como por ejemplo HSPG2 o la proteína AMBP, cuya concentración sérica ha sido encontrada aumentada en SUMMARY IN SPANISH 17 pacientes con asma alérgica. Por otro lado, también se han visto cambios en diversas proteínas relacionadas con la activación y regulación de todas las vías del complemento en asma no alérgica. Entre ellas cabe destacar los factores de complemento I (CFI) o H (CFH), así como la proteína MASP1; todas ellas están elevadas en el fenotipo no alérgico, y también pendientes de una posterior validación. Junto con lo anteriormente comentado sobre las células T- γδ, el papel de los factores del complemento habla nuevamente de las implicaciones del sistema inmune innato en el asma no alérgica. Ello asemeja a esta enfermedad a una patología autoinmune y explica, a su vez, su edad más tardía de aparición y la mayor incidencia en mujeres. Por tanto, estos resultados preliminares muestran cambios en un grupo de proteínas séricas que podrían ser útiles para diferenciar diferentes fenotipos asmáticos, servir para pronosticar la severidad de la enfermedad, o ser dianas de futuras terapias dirigidas. Juan José Nieto Fontarigo 26 be found in samples from the left upper lobe of the lung [33]. Interestingly, asthma susceptibility has also been associated with changes in the colonization of lower airways by microbes. Indeed, some works have shown that asthmatics displayed a higher predominance of Proteobacteria (a phylum of gram-negative bacteria) than subjects without asthma, where Bacteriodetes (another phylum of gram-negative bacteria) are more frequent [1, 33, 34]. There is a disagreement about the nature of the underlying mechanism that explains the higher relative abundance of phylum Proteobacteria in asthmatics, but it is broadly accepted that the immune system is implicated. Microbes produce substances such as LPS, flagellin, or lipoteichoic acid. These exogenous and highly conserved molecules are collectively called pathogen-associated molecular patterns (PAMPs). PAMPs are recognized by pattern recognition receptors (PRRs), which are membrane-bound (e.g., Tolllike receptors/TLRs) or cytoplasmic (e.g., NOD-like receptors, RIG-I- like receptors) receptors mainly expressed by innate immune cells (e.g., monocytes, macrophages, dendritic cells, neutrophils, eosinophils, epithelial cells) [35]. PRRs also identify damageassociated molecular patterns (DAMPs) or alarmins, another subset of molecules released this time by host cells during inflammation or when they are damaged or dead. Activation of PRRs leads to innate cells to release soluble factors (e.g., cytokines, chemokines) and express co-stimulatory molecules, which in turn unchain the adaptive immune response. CD14 is a co-receptor that allows the detection of bacterial LPS along with LPS binding protein (LBP), TLR4 and MD2. Triggering of CD14/TLR4 leads to the release of IL-12/IL-18 by monocyte/macrophages, two cytokines that favour the TH1 differentiation, in detriment of the TH2-mediated adaptive responses [36-38]. This shift in the TH1-TH2 axis was the classical explanation INTRODUCTION 27 of the hygiene hypothesis. However, certain helminthic infections (e.g., Schistosomiasis) trigger TH2-type immune responses and prevent asthma [39]. Moreover, TH1 cells could even increase the pathogenicity of TH2 cells, which makes it difficult to explain the hygiene effect through a simple TH1-TH2 cell counterbalance. Nowadays, it is believed that there is a loss of Treg cells in subjects living in “hygiene environments”, which turns into increased TH2 cell immunity and higher susceptibility to develop asthma/allergy [39, 40]. CD14/TLR4 is at the crossroads where naïve lymphocytes have to make the decision between TH1 and TH2 effector responses so that polymorphisms in these genes could impact seriously to asthma development or severity [41]. 4. INNATE IMMUNITY IN ASTHMA The innate immunity is the first line of defence against pathogens. This is an immediate and relatively non-specific response in which different cellular populations and soluble factors are implicated. Between them, we are going to put special emphasis on the role of airway epithelial cells (AECs), innate lymphoid cells (ILCs), γδ-T lymphocytes, and monocytes in asthma. 4.1. Airway epithelial cells (AECs) and innate lymphoid cells (ILCs) in asthma. The first cellular component implicated in the pathogenesis of asthma is the airway epithelial barrier. AECs are continuously exposed to different pollutants, particulate matter, allergens and pathogens. PAMPs from microorganisms (e.g., LPS) and enzymes derived from pathogens or allergens (e.g., dust mite allergen Der p1) interact with Juan José Nieto Fontarigo 28 AECs through PRRs (e.g., TLRs) and protease-activated receptors, respectively. This interaction unleashes the potential of epithelial cells to produce a set of cytokines and chemokines implicated in asthma pathogenesis [42, 43], whose best examples are TSLP (thymic stromal lymphopoietin), IL-25 and IL-33. PRRs activation by DAMPs or protease-activated receptors cleavage by endogenous proteinases (e.g., thrombin, plasmin, kallikreins, matrix metalloproteinases, elastases) play a complementary role in AECs activation. As we state above, the genes encoding both IL-33 and its receptor (ST2/IL-1R1L) are asthma susceptibility genes [17, 44, 45]. IL-33 is a member of the IL-1 superfamily of cytokines, but it is also considered an alarmin or DAMP; i.e. an intracellular molecule released in response to cell injury which is discharged to extracellular space after cell damage (necrosis or trauma) [46]. IL-33 is constitutively expressed by alveolar type-II pneumocytes, and its expression is enhanced upon airway inflammation [47, 48], particularly in allergic asthma (AA) [49, 50]. Additionally, macrophages are both the source and target of this cytokine [51]. IL- 33 is involved in the response to both helminths and viral infection [52, 53], through its binding to its receptor (ST2/IL-1R1L). ST2 is expressed by a myriad of immune cells, including mast cells, basophils, eosinophils, dendritic cells, and ILCs [51]. Binding of IL- 33 to transmembrane ST2 triggers different signalling routes. For example, IL-33 induces the activation of the NF-κB pathway in human mast cells stimulating the release of different cytokines (e.g., GM-CSF, TNF-α, IL-1β, IL-6, IL-8, or IL-13) and chemokines (e.g., CXCL8, CCL1) [54]. Similarly, TSLP is a cytokine encoded by a gene associated with a higher risk of AA [17]. TSLP (IL-2 family of cytokines), as well as IL-25 (IL-17 family of cytokines; IL-17E), are released by AECs in response to allergens (e.g., HDM) that possess protease INTRODUCTION 29 activity and are capable of activating protease-activated receptors like PAR2 [55]. Both cytokines display increased levels in asthmatic patients [56, 57]. TSLP is critical for the maintenance of allergic airway inflammation through inducing TH2-type cytokines production, boosting TH9 cells differentiation, inhibiting Treg function, and activating basophils/mast cells [43, 58-60]. Moreover, rhinovirus infection boost levels of TSLP in a mouse model of AA, underlying the potential role of this cytokine in asthma exacerbation [61]. IL-25, for its part, is mainly associated with eosinophils activation. However, it is worth highlighting that the heterodimeric receptor of this cytokine (IL-17RA/IL-17RB) is expressed in many immune cell types such as antigen presenting cells (APCs), invariant natural killer T cells (iNKT), AECs, and ILC2/nuocites [43]. Altogether, IL-25, TSLP, and particularly IL-33 are responsible for the early allergic response in asthma, driving the activation of ILC2 cells [43, 52, 55]. Upon activation by IL-25, TSLP and IL-33, these ILC2 cells become one of the major producers of IL-5 and IL-13 [62], two cytokines with a pivotal role in the induction and maintenance of AA [63]. Recently, several works in both mice and the human system gave support to an important role of this subset in asthma. These studies have shown that activated ILC2 cells not only produce IL-5 and IL-13, but also IL-3, IL-4, IL-6, IL-8, or GM-CSF [reviewed in 62]. Moreover, this function of ILC2 cells is enabled by human mast cells via prostaglandin D2 [64-66]. Therefore, ILC2 lymphocytes might be a bridge between the innate and the adaptive immune system. Apart from ILC2 cells, other innate immune cells are becoming more relevant for asthma pathogenesis, especially in the light of asthma heterogeneity and the presence of different disease phenotypes, such as non-allergic asthma (NAA). For example, alternative ILCs subsets such as natural killer (NK) cells, ILC1, or Juan José Nieto Fontarigo 30 ILC3 cells could be relevant to asthma. Both NK and ILC1 cells have been linked to the pathogenesis of this disorder [67, 68], but more interesting is the role of IL-17-producing ILC3 cells in obesity-related asthma [69]. However, more studies are necessary to ascertain the possible roles of ILC1 and ILC3 in this disease. 4.2. Monocytes in asthma pathogenesis Monocytes represent about 10% of circulating leukocytes and their half-life is around 3 days in human blood [70]. These cells are “circulating macrophages” that can turn into tissular inflammatory cells also capable of generating IL-33. This is illustrated in mouse models, where circulating monocytes are recruited to the lung upon HDM-induction to become active producers of IL-33 [71]. Human blood monocytes have been subdivided into three discrete subpopulations based on the surface expression of CD14 and CD16: “classical” CD14++CD16- cells, representing ~ 90% of circulating monocytes; “non-classical” CD14+CD16++ monocytes; and “intermediate” CD14++CD16+ monocytes [72-74]. However, the last subset is considered a transitional subpopulation more than a true subtype [75]. There is an increase in maturity from classical monocytes, which display an anti-apoptotic and proliferative state, to non-classical subsets, having an anti-proliferative and apoptotic state [75]. CD14++CD16- classical monocytes respond to LPS via TLR2 and TLR4, producing reactive oxygen species and a set of cytokines and chemokines (e.g., IL-6, IL-8 or CCL-3) [76]. Mukherjee et al. have shown that these cells display high levels of CD36 and CD163 (scavenger receptors), which evidence the phagocytic nature of this subset [76]. Additionally, intermediate monocytes and non-classical INTRODUCTION 31 monocytes are characterized by a high co-stimulatory ability, as they express CD80 and CD86 [77]. Non-classical monocytes respond to nucleic acids (damaged cells) and viruses via TLR7 and TLR8, secreting TNF-α and IL-1β [76] and they are also increased during sepsis [77]. All types of monocytes are able to differentiate into monocytederived macrophages or dendritic cells. Indeed, non-classical monocytes display high levels of CD11a and CTSL1, which allow them to infiltrate and differentiate in M2-type macrophages [78]. Macrophage-derived monocytes have both pro-inflammatory and antiinflammatory roles. M1 macrophages or classically-activated macrophages are mainly pro-inflammatory cells which release cytokines and chemokines such as IL-1β, IFN-γ, IL-8, IP-10, IL-23, TNF-α, or RANTES after pathogen infection. These cytokines are potent inducers of TH1 and TH17-driven inflammation [79], which is important in non-allergic lung inflammation. Moreover, higher levels of M1-type macrophages have been described in less severe AA compared to severe allergic disease, highlighting their possible antiallergic role [80]. On the other hand, M2 macrophages consist of four major groups of cells: M2a cells, which secrete IL-4 and IL-13; M2b cells, which secrete pro-inflammatory (IL-6, IL-1β, and TNF) and anti-inflammatory (IL-10 and TGF-β) cytokines; M2c cells, mainly IL-10 producers and Treg cell-inducers; and M2d cells (Figure 3) [80]. M2a-type macrophages have been related to AA in several works. They are IL-13 producers, a cytokine implicated in mucus production, tissue remodelling, and fibrosis that drives the characteristic TH2-type inflammation in AA [81]. These cells are also IL-33 producers (see above) [82], and they express a wide variety of chemokines (CCL-17, CCL-18, CCL-22, and CCL-24), which attract eosinophils and TH2 cells to the inflamed tissue [80, 83]. Juan José Nieto Fontarigo 32 Figure 3. Schematic representation of subtypes of monocyte-derived macrophages during inflammation. In the presence of a different stimulus, monocytes can be differentiated in M2a, M2b, M2c, and M2d cells, which have either proinflammatory or anti-inflammatory roles in asthma through the secretion of different cytokines and chemokines. 4.2.1. CD14 and asthma As commented above, some pathogens display several types of PAMPs, such as LPS in gram-negative bacteria or lipoteichoic acid in gram-positive. These molecules are recognized by PRRs, which are localized on innate immune cells such as monocytes or macrophages. [35]. There are different types of PRRs but the most studied are the TLRs. There are 10 types of TLRs (TLR1 to 10) in humans, each of them capable of recognizing different pathogen components. For INTRODUCTION 33 example, TLR2 recognizes microbial lipopeptides, whereas TLR3 recognizes dsRNA from the viral genome [84]. TLR4 forms part of the receptor for bacterial LPS and is mainly expressed by monocytes, macrophages and dendritic cells [84, 85]. LBP captures LPS monomers and transfers them to CD14, a coreceptor and a susceptibility gene for asthma and allergy [86, 87]. LPS is then delivered to the complex MD2/TLR4, which form a hexamer complex (two LPS/TLR4/MD2). Although there are MyD88- independent TLR-4 signalling pathways, the main route begins with the sequential recruitment of two adaptor proteins: TIRAP (tollinterleukin 1 receptor domain containing adaptor protein) and MyD88 (Myeloid differentiation primary response 88) [85, 88, 89]. Then, IRAK kinases (IRAK4 and IRAK1 or 2) are recruited and phosphorylated, allowing the binding of the ubiquitin protein ligase TRAF6 and the subsequent recruitment of TAK1 and IKK complex. Finally, both MAP kinases and early NF-κB pathways are activated (Figure 4) [90-92]. The hexamer complex (TLR4-MD2-LPS)2 can be internalized via endosomes, which induces a signal transduction pathway dependent on the recruitment of TRIF/TRAM. This pathway ends up with the activation of NF-κB and IRF3 (Figure 4) [91]. Finally, all these signal transduction pathways promote the expression of genes encoding TH1 and TH17-type cytokines and chemokines, such as type-I Interferon, IL-12, IL-1, IL-6, TNF-α, IL-8, or RANTES [90- 92]. This set of cytokines drives the induction of a TH1 and TH17- type inflammation, in detriment of a TH2-type polarization. Indeed, MyD88-deficient mice had a compromised activation of antigenspecific TH1 cells, but not TH2 [93]. Juan José Nieto Fontarigo 34 Figure 4. TLR4-CD14 signalling pathway. The formation of the heterodimer complex (TLR4/MD2/LPS)2 triggers two sequential signalling pathways. The fist of them starts with the recruitment of MyD88 and TIRAP and finish with the earlyphase activation of NFκB, its translocation to the nucleus and the induction of inflammatory cytokines such as IL-12 or IL18. Secondly, the TLR4/MD2/LPS- hexamer complex can be internalized into endosomes, where through the recruitment of TRAM and TRIF, leads to the activation of late-phase NFκB, and thus, the induction of type I IFN. In addition, membrane-anchored CD14 (mCD14) facilitates the response of TLRs (TLR2, TLR3, TLR4) to other PAMPs (e.g., viral nucleic acids and components from Gram-positive and negative INTRODUCTION 35 bacteria) or DAMPs (e.g., endogenous molecules like ceramide, urate crystals, or amyloid peptides) [94]. Hence, changes in the abundance or defects in the function of CD14 (e.g., genetic factors like SNPs) could be relevant for the development of allergen-specific TH2 cells and AA pathogenesis. 4.2.1.1. Soluble CD14 (sCD14) and asthma mCD14 is attached to the cell surface by means of a glycophosphatidylinositol anchorage, but this protein is also detectable as a soluble form (sCD14) in plasma. sCD14 is released by a controlled mechanism (e.g., LPS, CpG, TNF-α) involving either enzymatic cleavage (e.g., elastase, phosphatidylinositol phospholipase C) or direct secretion by exocytosis [94-96]. sCD14 can display opposite functions. On the one hand, sCD14 can mimic the function of the mCD14 by transferring LPS from LBP to TLR4; therefore sCD14 potentiates the induction of type-1 or type-17 proinflammatory cytokines by endotoxin [96]. In addition, sCD14 qualifies CD14- negative cells (e.g., endothelial or epithelial cells) to respond to LPS [97]. Reversely, sCD14 can act as a scavenger receptor transferring LPS to plasma lipoproteins and preventing the activation of TLR4- NF-κB pathway [98]. sCD14 is released from monocytes upon stimulation with TLR ligands (e.g., LPS, CpG, flagellin) or pro-inflammatory cytokines (e.g., IL-6 or IL-1β) [38]. Moreover, plasma sCD14 also behaves as a positive acute phase protein (APP+). This means that sCD14 levels increase during infection, inflammation or upon exposure of hepatocytes to IL-6 [94]. Hence, sCD14 can be considered a non-specific monocyte activation marker [38]. sCD14 features two serum isoforms, with 49 and 55 kDa, and is also cleaved in plasma by proteases like cathepsin D to yield 13 kDa N-terminal Juan José Nieto Fontarigo 42 airways [150, 151] and show a strong association with asthma disease severity [151]. Furthermore, it has also been detected in peripheral blood of asthmatics the expansion of a subset of circulating effector memory IL-6Rα/CD126high CD8+ T cells that produce TH2 cytokines [152]. However, most of the studies in asthma have been focused on CD4+ T cells, especially TH2 cells and AA. 5.1. The role of TH2 cells in asthma TH2 cells have been considered since a long time ago major players in AA. GATA3 and STAT6 are key transcriptions factors for the development of TH2 cells, and their effector type-2 cytokines (IL-4, IL-5, IL-9, IL-13, and IL-25) are important for humoral immune responses, defence against extracellular parasites (e.g., helminths), and AA pathogenesis. IL-4 is cytokine produced, amongst others, by basophils and ILC2 cells, essential for proliferation, survival, and differentiation of TN cells to TH2 lymphocytes [153]. This interleukin induces B-cell proliferation, B-cell class switching to IgE synthesis, and plasma cell differentiation [154]. Therefore, IL-4 plays an important role in the early allergic phase. This cytokine acts via the IL-4Rα, which can be in complex with the common cytokine receptor γ-chain (IL-2Rγc; type-I IL-4 receptor) or with the IL-13Rα1 (type-II IL-4 receptor [154, 155]. The last one is also a receptor for IL-13, which shares some functions with IL-4. However, IL-13 binds to another receptor with higher affinity, IL-13Rα2 [155]. Compared to IL-4, IL-13 is a late-acting (effector phase) pro-inflammatory cytokine that induces mucus production, AHR, and lung fibrosis. Indeed, blockade of IL-13 prevents and reverses mucus secretion [156]. IL-13 is responsible for the transition INTRODUCTION 43 of Clara cells (also known as bronchiolar exocrine cells) to globet cells (metaplasia), whose main role is to secrete a group of glycoproteins called mucins capable of attracting water molecules [157, 158]. IL-13 also leads to goblet cell hyperplasia (cell proliferation) and induces the expression of several genes related to mucus hypersecretion: MUC5AC, MAPK13, GABAA-R, or TMEM16A [159-162]. When the amount and speed involved in mucus production are excessive, this generates a thick secretion in the airways that cannot be easily removed by cilia or cough, driving to an airflow obstruction (together with AHR) characteristic of asthma. Different studies in mice have reported that IL-13 could affect directly to AECs or/and smooth muscle cells to produce AHR [163, 164]. Moreover, the induction of MUC5AC or certain contractile mediators such as nitric oxide by IL-13 appears to contribute to the development of AHR in asthmatics [165, 166]. Another function of IL-13 is the stimulation of myofibroblasts proliferation and their recruitment to airway tissues, leading sub-epithelial fibrosis [167]. IL-5, for its part, promotes the maturation, differentiation, and survival of eosinophils. Moreover, this cytokine act as a chemokine for this leukocyte subset and enhances its effector function [168]. Indeed, the overexpression of IL-5 in mice induces the expansion of eosinophils both in bone marrow and peripheral blood [168, 169], whereas the absence of IL-5Rα abolishes the eosinophilia and AHR compared to wild-type (WT) mice [168, 170]. In addition, some studies have noticed reduced eosinophils influx to the lung epithelium and less AHR after the use of anti-IL-5 antibodies [168]. Recruitment of eosinophils and TH2 cells to lung epithelium drives the late-phase allergic response in asthma due to the release of effector mediators such as the major basic protein, eosinophil-derived neurotoxin or peroxidase [171, 172]. Juan José Nieto Fontarigo 44 5.2. Participation of other effector TH subsets in asthma: TH1 and TH17 lymphocytes TH2 cells have been the most studied CD4+ T subset in asthma over time, particularly in the allergic phenotype. However, other TH subpopulations display important roles in the pathology of this complex disease, such as TH1 or TH17 cells. As we have stated above (see section 3.2), both TH2 and TH1 cells were believed to have opposite roles promoting or inhibiting asthma, respectively. TH1 cells differentiate from TN lymphocytes in response to IL- 12 (an APC-derived cytokine). This subset is characterized by the expression of the transcription factors T-bet and STAT4, and the secretion of IFN-γ and other effector cytokines such as IL-2, TNF, or LT-α [146]. TH1 cells are responsible for the protection against viruses and other intracellular pathogens [146]. The first studies made on the role of TH1 lymphocytes in asthma described this subset as protective. For example, children living on farms and exposed to high endotoxin (LPS) levels were found to be less predisposed to asthma or allergies. Indeed, LPS exposure by means of CD14-TLR4 drives the differentiation towards TH1- instead of TH2-type responses, as stated above. Furthermore, IL-12 prevents the production of IL-4 and inhibits the development of TH2 cells, downmodulating AA inflammation [37]. However, a potential proinflammatory role for TH1 cells in asthma is now emerging. Indeed, some viruses like human rhinoviruses induce the secretion of IL-33 and TSLP, which also trigger TH1 responses and are responsible for acute asthma attacks [173]. Additionally, adults with treatment-refractory severe asthma have increased levels of TH1 cells in their lungs, highlighting the possible role of this subset on the severity of this disorder [174]. INTRODUCTION 45 TH17 keep mucosal barriers fit and facilitate pathogen clearance at mucosal surfaces [175]. In the presence of IL-1β, IL-6, and IL-23, TN cells differentiate into TH17 lymphocytes; TGF-β also appears to play a role in TH17 differentiation [146]. Through its interaction with IL-6R (gp130 + IL-6Rα/CD126), IL-6 induces the upregulation of retinoic acid receptor-related orphan receptor gamma (ROR-γt). ROR-γt and ROR-αt are two transcription factors that drive the development of TH17 cells [176-178]. Moreover, IL-6 can also interact with soluble IL-6Rα, activating CD126-gp130+ cells [179, 180]. Indeed, this process, also known as trans-signalling, is important for the maintenance of several inflammatory diseases such as asthma [181-184]. Apart from ROR-γt, TH17 lymphocytes can be distinguished by the expression of another transcription factor (STAT3) and the surface receptors CCR6 and IL23R. TH17 cells carry out many of their activities by releasing several effector cytokines from the IL-17- (IL-17A, IL-17F), the IL-10- (IL-22), and the IL-12-family (IL-23) [185, 186]. Some IL-17 polymorphisms have been associated with higher asthma risk, like for instance IL-17A rs4711998(A/G), IL-17F rs1889570(C/T), and IL-17A rs3819024(A/G) [187]. IL-17 has been related to airway diseases due to it is directly connected with the production of pro-inflammatory (e.g., IL-8) and pro-fibrotic cytokines (e.g., IL-6, IL-11), as well as matrix metalloproteases from inflammatory cells (e.g., eosinophils), AECs, and fibroblasts [188- 190]. These pro-inflammatory cytokines promote lung inflammation by means of the recruitment of macrophages and neutrophils [191, 192]. Additionally, Chang et al. described that IL17-A, IL-17F, and IL-22 can induce airway smooth muscle cells proliferation and therefore promote airway remodelling [193]. Juan José Nieto Fontarigo 46 Several works have been suggested a possible role of TH17 cells in asthma pathogenesis [194]. For example, the absence of either IL-17A or IL-17F is enough to suppress AA induced by HDM in mice [195]. Both IL-17 and neutrophils levels are augmented in asthmatic subjects with higher body mass index [196], highlighting the role of IL-17 in worse control in obese adults with asthma [69]. On the other hand, Zao et al. reported an increase in both the percentage of TH17 cells and the production of TH17-derived cytokines (IL-17 and IL-25) in peripheral blood from patients with AA and in activated peripheral blood mononuclear cells (PBMCs) from allergic asthmatics compared to healthy controls. Moreover, they also evidenced higher levels of both IL-17 and IL-22 cytokines as disease severity increases (i.e. Controls < Mild asthma < Moderate asthma < Severe asthma), highlighting the possible implication of this subset in asthma severity [197, 198]. Furthermore, TH17 cells have also been implicated in steroid-resistant asthma [199]. Glucocorticoids have been able to induce BIM (Bcl-2 interacting mediator), a pro-apoptotic protein which antagonizes Bcl-2. The predominance of BIM over Bcl-2 induces the activation of BAX, and the subsequent activation of caspases, leading to apoptosis [200, 201]. However, contrary to TH1 lymphocytes, TH17 cells express high levels of Bcl-2, which makes this subset insensitive to glucocorticoids. Indeed, short hairpin RNA (shRNA) mediated silencing of Bcl-2 gene in TH17 cells makes them sensitive to glucocorticoid-induced apoptosis [202]. Furthermore, TH17 cells were augmented in the lungs of a murine model of severe asthma [202]. INTRODUCTION 47 5.3. Other TH subsets implicated in asthma pathogenesis: TH9, TH22 and TfH lymphocytes At least 3 more TH cell subsets have implications in asthma pathogenesis: TH9, TH22 and follicular helper T (TfH) cells. TH9 lymphocytes differentiate from TN cells when IL-4 and TGF-β are present in the media. Both STAT6 and PU.1 are transcription factors important for the development of TH9 cells; they also express GATA3, but to a lesser extent than TH2 cells. Apart from IL-10 and IL-21, TH9 cells are a major source of IL-9, a cytokine which gives them their name. IL-9 has several relevant effects in AA pathogenesis [203]. For example, this interleukin induces the production of histamine, proteases and cytokines from mast cells, promotes TH2- differentiation and eosinophils development, induces IgE classswitching in B cells, and favours bronchoconstriction, globet cell metaplasia, and mucus production [203, 204]. In addition to TH17 cells, TH9 lymphocytes are resistant to glucocorticoids and can be mediators of steroid-resistant asthma [205]. In the presence of IL-6 and TNF-α, TN cells can differentiate into TH22, which are characterized by the secretion of IL-22 and the expression of CCR6, CCR4, and CCR10 [206]. The function of this cytokine is controversial, as it has been implicated in both antiinflammatory and pro-inflammatory processes [207]. Indeed, some works have described higher levels of IL-22 in serum from asthmatics compared to healthy individuals [207], or in severe asthma compared to moderate disease [207-209]. In contrast, other in vitro or in vivo studies suggest that IL-22 have a protective role in the late-phase of allergic induced airway inflammation by decreasing eosinophils levels, IL-5, IL-13, and CXCL10 [207]. TfH cells are another subset of TH cells important for the maintenance of germinal centres and the generation of long-lived Juan José Nieto Fontarigo 48 plasma cells and memory B cell responses [210]. These cells display a high dependency of IL-2 for its generation and are identified by the high expression of ICOS, PD-1, and CXCR5, whose mRNA has been found augmented in asthmatics compared to healthy subjects [211]. The ligand of CXCR5, CXCL13, is produced by follicular stromal cells and helps TfH cell to find the way to germinal centres (B-cell follicles), where somatic hypermutation of BCR and T-B cells interaction leading to class switching and B-cell differentiation takes place [212]. B-cell lymphoma 6 protein (Bcl-6) is a transcription factor expressed by TfH cells that suppresses the expression of transcription factors involved in the differentiation of other TH subsets (e.g., TH1, TH2, TH17) [213]. Moreover, TfH cells release IL-21, which is also increased in asthmatic lungs [211]. Therefore, more studies are needed to clarify the function of the different TH lymphocyte subsets, their relationship and their implication in asthma pathogenesis. 5.4. The role of regulatory T cells (Treg) in asthma The above-mentioned effector functions of human TH lymphocytes are counteracted by Treg cells [214, 215]. There are two major types of Treg cells, with different biological functions: natural Treg cells (nTregs) and induced Treg cells (iTregs). The first subtype is responsible for tolerance to self-antigens. These FoxP3+CD25+CD304/Neuropilin-1+ nTreg cells are generated in the thymus, where they manage to escape the negative selection. Lineagespecific transcription factors like FoxP3, Helios, or RUNX are important regulators of the development of nTregs and their immunosuppressive functions [215, 216]. In contrast, iTregs are generated in the periphery from other TH subsets under tolerogenic conditions: i.e., strong signalling via TCR, low co-stimulation, and INTRODUCTION 49 high levels of TGF-β and retinoic acid [215]. iTregs appear to control immune responses to “non-self” antigens (e.g., allergens, commensal microbiota, diet), and are classically divided into three major subtypes: FoxP3+ iTregs, IL-10+ Tr1 cells, and TGF-β+ TH3 cells [217]. Loss of iTreg cells leads to allergic-type-2 inflammation at mucosal interfaces (for example, in the lung) [218]. Figure 5. Schematic representation of the multitude of regulatory T cells (Treg) functions implicated in asthma pathogenesis. Treg cells control the effector functions of several innate system mediators such as mast cells, basophils, and eosinophils, as well as TH subsets from the adaptive immune system. They also control immunoglobulin (Ig) class switching through the induction of IgG4 production in detriment of IgE production. Stimulatory functions are represented by a solid arrow, whereas inhibitory signals are represented by blunt arrows. Treg cells can be distinguished from Teff cells according to the levels of CD25 (IL-2Rα) and CD127 (IL-7Rα). Thus, contrary to Teff Juan José Nieto Fontarigo 50 cells (CD25lowCD127high), most of Treg lymphocytes display high levels of CD25 and low levels of CD127 (CD25highCD127low) [219]. CD25 is considered an activation marker released by TH lymphocytes during inflammation in the form of soluble CD25 (sCD25) [220-222]. Indeed, sCD25 is augmented in BALF of asthmatics compared to healthy subjects [221, 222]. Moreover, sCD25 is increased in serum during asthma exacerbation [223] and has been correlated with AA severity [224]. On the other hand, CD127 is a subunit of both IL-7 and TSLP receptors [225]. Together with IL-15, IL-7 is cytokine important for homeostatic survival of TH cells, and therefore CD127 is also a marker for naïve and certain memory subpopulations (stemcell memory T cells/TSCM and TCM). Other markers expressed on Treg cells, like CTLA-4 or GITR, are also up-regulated upon activation [215]. Therefore, this means that the Treg phenotype displays characteristics of activated and TEM cells (see below). Treg cells play an important role as negative regulators of inflammatory disorders and tissue repair [215]. This function requires signalling via TCR and IL-2R, and is exercised by means of multiple cell-contact dependent or independent mechanisms involving soluble (e.g., adenosine, granzyme, TGF-β, IL-10, and IL-35) or membraneassociated (e.g., CTLA-4, CD39, CD73, CD25, perforin) molecules [215]. Treg lymphocytes deprive the environment of IL-2, reduce the activation status of dendritic and myeloid cells, and restraint Teff functions by directly inhibit (or killing) TH1, TH2, and TH17 cells. Moreover, this Treg subset switches immunoglobulin isotypes from IgE to IgG4 in B cells and prevents the activation and migration through the airway epithelium of mast cells, eosinophils, and basophils (Figure 5) [1, 217]. Therefore, a functional defect in Treg cells or a change in the effector/regulatory equilibrium may be important in asthma pathogenesis [214]. Indeed, the percentage of IL- 4 producing cells was augmented in allergic subjects, whereas IL-10- INTRODUCTION 51 producing Treg cells were decreased in allergic individuals (in contrast, they were the dominant allergen-specific subset in healthy subjects) [226]. In the same line, children with asthma display low levels of Treg cells in BALF compared to control subjects. Furthermore, contrary to CD4+CD25high T cells isolated from control subjects, Treg cells from asthmatic subjects fail to suppress proliferation and TH2-cytokine production by responder T cells [227]. 5.5. Naïve-memory differentiation of T cells and asthma As stated above, the adaptive immune system is characterized by the generation of long-lived memory cells, even though it has been found recently that ILC2 cells, NK cells, or monocytes display an „innate memory‟ or “trained immunity”; i.e., a long-term improvement of the function of innate immune cells after infection or vaccination due to epigenetic causes [228]. Following Ag encounter, TN cells proliferate and differentiate into cells with different phenotypes and functions following a linear model (Figure 6). These six subsets of T cells (TN, stem cell memory T cells/TSCM, TCM, transitional memory T cells, TEM, and TEMRA) can be characterized according to combinations of 4 markers: CD45RA or CD45RO, CD62L or CCR7, CD27 or CD28, and CD95 (Figure 6) [229]. TN cells display the highest expression of CD45RA and no expression of CD45RO, two splicing variants of the CD45 gene. CD45RO define memory T cells, whereas TEMRA cells re-express the high molecular weight protein CD45RA. CD62L (L-selectin) and CCR7 allow T cells to migrate to secondary lymphoid tissues. Thus, these two molecules are highly expressed in TN, TSCM and TCM cells. TSCM cells retain stem cell properties and they share some genes with TN cells, but they display high expression of CD95 (as the other Juan José Nieto Fontarigo 58 administration [301]. Moreover, a model of OVA-induced experimental asthma in CD26-/- mice showed increased levels of IL-4, IL-5, and IL-13 in BALF, higher circulating levels of eosinophils, enhanced levels of eotaxin and RANTES, as well as augmented expression of TH2 chemokine receptors (CCR3 and CCR5), compared to WT mice, supporting that CD26/DPP4 could play a “braking” role in experimental asthma [281]. From studies in the human system, Lun et al. have shown higher levels of CD26 on total lymphocytes, CD4+ T cells, and iNKT lymphocytes, as well as higher concentrations of sCD26 in adult allergic asthmatics [246]. Moreover, the TH2-cytokine IL-13 has been identified as an important inducer of CD26/DPP4 expression in bronchial epithelial cells [302]. However, other works have shown no changes of sCD26 in asthma [303]. These results could be explained because of many potential confounders: low sample size, male/female proportion, age, or lymphocyte count. For instance, is well-known that both CD26 expression on lymphocytes and circulating sCD26 levels are higher in men than women [303, 304]. Therefore, more studies are needed to assess the relationship between CD26 and asthma, as well as to extend this area of research to different asthma phenotypes (or endotypes) and severity degrees. **For more information see appendix I. 6. ASTHMA PHENOTYPES AND ENDOTYPES Asthma is a heterogeneous disease that groups different clinical phenotypes or “observable properties of an organism that are produced by the interaction of the genotype and the environment”, INTRODUCTION 59 (Merriam-Webster‟s Collegiate Dictionary (© 2019 Merriam- Webster, Incorporated 2019)). Moreover, below this first outer and visible layer of complexity lies a second one, named asthma endotypes, which represent the pathophysiologic and molecular mechanisms that trigger and make this disease worse [2]. However, this connection between specific asthma phenotypes and the underlying pathological features is elusive [2]. Therefore, most of the research is focused on the search for a variety of biomarkers that clearly define the different asthma phenotypes and/or endotypes. Those works are intended to develop new biological drugs, necessary for personalized/precision medicine in asthma and respiratory diseases [45, 305, 306]. The most extended classification of asthma amongst clinicians relies on the presence or absence of allergic triggers: AA and NAA (Figure 7). AA is the most common phenotype (~ 60%) [307]. It is characterized by the presence of allergic sensitization, which is defined by the presence of allergen-specific IgE molecules and a positive skin prick test against common environmental allergens. Compared to the adult onset of NAA, AA often starts in childhood. Moreover, the prevalence of AA is higher in males, whereas nonallergic asthmatics are mostly women. Additionally, AA patients frequently respond well to inhaled corticosteroid (ICS) treatment compared to NAA patients, which are usually more heterogeneous regarding the underlying inflammatory pattern (neutrophilic or paucygranulocytic inflammation) [4, 308, 309]. However, this classification of asthma according to the kind of trigger is an oversimplification, as other asthma phenotypes apart from AA and NAA have been defined by the Asthma Phenotypes Task Force: aspirin-exacerbated respiratory disease, infection-induced asthma, and exercise-induced asthma [307]. Juan José Nieto Fontarigo 60 Figure 7. Cells and molecules implicated in the different asthma phenotypes and endotypes. Two major phenotypes have been described in asthma, the early onset, eosinophilic and atopic/allergic asthma, and the late onset, non-allergic asthma. Allergic asthma mainly fits into the TH2 high asthma, and it is characterized by mast cell and eosinophilic response and a TH2 driven inflammation. On the other hand, non-allergic asthma is more heterogeneous, and it could be neutrophilic or obesity-related. The non-allergic phenotype is characterized by a TH2 low endotype, where type-1 and type-17 cytokines and the cells they come from (ILC1/3, γδ-T cells, or TH1/TH17 cells), as well as neutrophils, have an important role. Underneath the phenotypic classification of AA and NAA, the most common endotype classification is based on the predominant TH-type inflammation: i.e., TH2-high vs TH2-low asthma [310, 311]. The early-onset TH2-high asthma is the most common endotype and almost 100% of patients with this endotype fall into the AA category. The TH2-high endotype is characterized by a TH2- and mast cells- INTRODUCTION 61 driven inflammation, sub-epithelial basement membrane thickening, and a central role for IgE and eosinophils (Figure 7) [2, 312]. This type of asthma is also associated with atopy (i.e., a genetic predisposition to suffer allergic diseases). Indeed, diseases such as allergic rhinitis, eczema, or food and drug allergy are often comorbidities in AA patients [2, 4]. Several biomarkers of TH2-high asthma have been described: elevated sputum eosinophils levels, high fractional exhaled nitric oxide (FeNO), which is a surrogate marker of eosinophilic airway inflammation, and raised levels of periostin and total IgE in serum [311, 313, 314]. However, the main feature of this endotype is the good response to non-specific anti-inflammatory drugs (ICS), resulting in the down-modulation of TH2 cytokines (IL-4, IL-5, and IL-13) and the underlying inflammation [2]. Different biological therapies have emerged in the form of humanised antibodies that target several AA mediators such as IgE or TH2-cytokines [311]. The first humanised monoclonal antibody specifically designed to treat AA was omalizumab (Xolair®). This antibody makes a complex with free IgE and inhibits its binding to the high‐affinity FcϵR1 receptor on mast cells and basophils [314]. As a result of this blockade, the typical mast cell activation/degranulation event that occurs in AA is interrupted, as well as the eosinophilic inflammation [315]. Therefore, severe persistent allergic asthmatic patients treated with omalizumab undergo a reduction of asthma exacerbations [316] and an improvement in their quality of life [317]. Beyond omalizumab therapy, there are other humanised monoclonal antibodies that target several important molecules in asthma: a) TH2- cytokines such as IL-5 (mepolizumab and reslizumab) or IL-13 (lebrikizumab and tralokinumab); b) TH2-cytokine receptors such as IL-4Rα (dupilumab and AMG-317) or IL-5Rα (benralizumab); and c) epithelial cell-derived cytokines such as TSLP (AMG-157) [311, 318]. These alternative biologicals have yielded promising results in terms Juan José Nieto Fontarigo 62 of improvement of lung function and reduction of exacerbations in TH2-high AA [318]. TH2-low asthma, for its part, is more heterogeneous and poorly defined; indeed, there are no specific biomarkers for this asthma endotype. Overall, patients with TH2-low asthma are badlyresponders to ICS and display a more severe disease. In addition, these type of patients are characterized by the absence of a TH2- signature, lower levels of IgE, delayed disease onset (adulthood), and non-allergic/atopic disease usually associated with neutrophilic inflammation (Figure 7) [310, 319-321]. Obesity-related asthma, which is predominant in women, is also included within TH2-low asthma [322]. TH1 and TH17 cells and their derived cytokines seem to be key players in the pathogenesis of this endotype (Figure 7). As commented above, IL-17 is the major mediator of neutrophils recruitment and activation by inducing the production of IL-8 and other chemokines (e.g., CXCL1 or CXCL5) by AECs (Figure 7). IL- 17 has been associated with AHR, remodelling and asthma severity [188, 323, 324]. Although IL-17 is mainly produced by TH17 cells, certain subpopulations of innate lymphocytes also secrete this cytokine. This is the case of ILC3s, which play a central role in obesity-related asthma [69], or γδ-T lymphocytes, which are the major producers of early IL-17 (Figure 7) [134]. On the other hand, IFN-γ, the fingerprint cytokine of TH1 cells, is also implicated in the chemotaxis of neutrophils through the up-regulation of CCR1 and CCR3 on this leukocyte subset (Figure 7) [325]. Given all the above commented, and in the era of biological therapies and personalised/precision medicine, it is more necessary than ever the search for new biological markers, with application in phenotype/endotype refinement and disease diagnosis/prognosis/management. These new biomarkers will enlarge the list of currently available options, which include both cells (e.g., INTRODUCTION 63 eosinophils, neutrophils) and molecules (e.g., total and specific IgE, periostin, FeNO, cytokines) in different kind of samples (e.g., peripheral blood, serum, plasma, IS) [307]. 7. APPLICATION OF BIOFLUID PROTEOMICS FOR ASTHMA-BIOMARKER DISCOVERY The emergence of Proteomics, which is the large-scale study of proteins, has meant a turning point in the world of biomarkers discovery. Proteomic studies often use samples from tissues, in vitro cell cultures, or biofluids such as urine, BALF, exhaled breath condensate (EBC), or cerebrospinal fluid (CSF) [326, 327]. However, the most commonly used samples in clinical studies are those derived from venous peripheral blood: i.e., serum and plasma. This easy to acquire samples are challenging in Proteomics because they are highly dynamic and complex (>10,000 proteins; http://www.plasmaproteomedatabase.org). This is because both serum and plasma samples are an open window to the proteomes of all the tissues in the body. This makes these biofluids ideal for biomarker discovery studies, especially amongst low molecular weight (LMW; < 30-40 kDa) or low abundance protein (LAP) sub-proteomes [328, 329]. Serum/plasma includes proteins that fulfil their function in the extracellular compartment, such as cytokines, hormones, or growth factors. However, they also contain “bystander” molecules such as tissue leakage products; i.e., intracellular proteins released by tissues for multiple reasons (some of them summarized in Figure 8) [328, 330, 331]. LMW cellular proteins (especially the cytosolic ones) reach easily the blood circulation during physiological cell turnover or pathological plasma membrane permeabilization due to their small Juan José Nieto Fontarigo 64 protein size [332]. Despite this ease, the serum/plasma LMW proteome is made of small proteins, protein fragments, or peptides that display a low abundance and elevated complexity. Therefore, LAP and LMW sub-proteomes from serum/plasma are difficult to investigate but represent a partly overlapping rich source of information and novel potential biomarkers related to cancer [333], cardiovascular conditions [334], infectious illnesses [335], or airway diseases [336, 337]. Figure 8. Cell/tissue sources and origin of low abundance serum/plasma proteins. The serum/plasma abundance of disease biomarkers is dependent on the equilibrium between secretions by cells and removal (e.g., kidney or proteolysis). Several reasons are the responsible for the increment or detriment of tissue proteins in plasma: 1) cell damage (necrosis, cell membrane permeabilization), 2) induction of protein synthesis, 3) increment of cellular proliferation/ cell replacement (e.g., cancer), 4) Reduction of protein excretion by exocrine cells (e.g., pancreatic or prostate cells) due to obstruction of the ducts, or 5) less removal of proteins from circulation due to for example renal injury. INTRODUCTION 65 Figure 9. The dynamic range of proteins concentrations in human plasma. Human plasma proteome is composed of thousands of proteins. 22 of them represent the 99.9% and are considered high abundant proteins. Between them, only 10 represent more than 90%, and only albumin constitutes more than 50% of total protein concentration. Low abundance proteins, also called LMW proteome is compound by only the 0.1% of proteins in the human plasma. As above commented, several challenges must be considered when analysing LAP/LMW sub-proteomes from serum/plasma samples. The most important one is the extremely high dynamic range of protein concentrations in those biofluids, of almost 1010 magnitude, and the fact that <0.1% of the total number of species represents almost 99% of the bulk mass of plasma/serum proteins; that is, a set of 22 protein that includes albumin, immunoglobulins, transferrin, α-2 macroglobulin or α1-antitrypsin (Figure 9). Only albumin itself constitutes ~50% of protein content in serum, with concentrations ranging between 35 and 50 mg/mL. In contrast, the low abundance proteome reaches a scarce 0.1% of the bulk mass of proteins, covers a concentration range from ng/mL to fg/mL, and is made up of thousands of LMW proteins with a specific function in plasma (e.g., cytokines, growth factors, and chemokines) or derived from tissues or Juan José Nieto Fontarigo 66 cells (Figure 9) [328, 330, 331, 338, 339]. Therefore, reduction of sample complexity is necessary to ensure access to this potential source of disease biomarkers, coined by certain researchers as the “deep-proteome” [339]. 7.1. Pre-fractioning methods for plasma/serum proteins In the last years, different experimental approaches consisting of either depletion of high-abundance proteins or enrichment of LAP/LMW species in serum/plasma samples have been developed in order to reduce the serum/plasma dynamic range of protein abundances. Ultrafiltration is included in the first group of techniques [340]. This technique consists of centrifugal filter devices whose membranes display a specific cut-off (e.g., 40 kDa cut-off), which means that only low molecular weight proteins will be able to pass through. However, it has been shown that high molecular weight proteins like albumin still appear in the eluted fraction. Other approaches involve the depletion of high abundant protein by affinity chromatography [341]. This is the case of human serum albumin affinity columns (e.g. Cibacron Blue-based affinity chromatography) [342], immunoglobulins depletion (e.g., protein A/G) [343], Proteoprep columns (Merck Millipore) for Albumin/IgG depletion [344], the Pierce™ Top 12 Abundant Protein Depletion Spin Columns (Thermo Scientific™), or the multiple affinity removal system (MARS) (Agilent Technologies). Finally, high-abundance proteins can be depleted from serum by using organic solvent precipitation (e.g., acetonitrile precipitation) [345]. However, it has been described that some LMW proteins are found in association with carrier proteins such as albumin [346]. Therefore, depletion or precipitation of these INTRODUCTION 67 highly-abundant “shipper” proteins can result in the loss of interesting LMW biomarkers. More importantly, removal of the upper-layer of high-abundance proteins from serum/plasma samples only allows researchers to reach the medium abundance sub-proteome. Figure 10. The use of combinatorial peptide ligand libraries (CPLL) as an enrichment method for low abundance proteins in complex samples. The ProteoMinerTM protein enrichment technology (BioRad) is based on the use of combinatorial ligand library of hexapeptides (CPLL) attached to beads. Step 1. The CPLL is added to a complex sample (e.g., serum or plasma) where almost all low abundant proteins bind to their specific ligand hexapeptides, but high abundant proteins saturate their ligands. Step 2. The washing of the sample allows the elimination of high abundant proteins, which had saturated their ligands. Step 3. The proteins attached to the beads are eluted. Therefore, the eluted fraction is enriched in low abundant proteins, whereas high abundant proteins are eliminated in the flowthrough fraction. Apart from depletion methods, several approaches that enrich low-abundance/LMW proteins have been developed. This is the case of affinity capture of low-abundance proteins by means of magnetic beads [347], nanoparticles [348], antibody arrays [349], or the use of combinatorial peptide ligand libraries (CPLLs) (Figure 10) [350]. The last approach, marketed under the name of ProteoMinerTM protein Juan José Nieto Fontarigo 74 Figure 12. iTRAQ labelling. Each label of iTRAQ 8-plex is composed of 3 regions. Tryptic peptides covalently bind to the amine-specific peptide reactive group (NHS). The region next to NHS is the balance group (184- 192 Da) aimed to conserve a constant tag mass of 305.1 in MS1. Finally, the reporter group retains the charge after peptide fragmentation, presents variable mass (113.1-119.1, 121.1 Da), and display an intense signal in MS2. Compared to label-free strategies, which can process an unlimited number of samples in the same experiment, iTRAQ only allows us to label, analyse, and compare up to 8 samples (Figure 13). However, label-free strategies present several challenges [368, 373]: 1) all samples are prepared and analysed separately; 2) it is necessary to use internal standards in order to avoid variations in the peak intensities between different experiments; 3) quantification errors due to close mass signals can be present, so that technical replicates are mandatory (Figure 13). Therefore, label-free quantification results in a huge amount of data, which are difficult and laborious to process (Figure 13). This issue has been solved with iTRAQ technology, which is an easy-to-use method that allows the analysis and INTRODUCTION 75 comparison of all samples (up to 8) in the same MS/MS read out, as all labelled samples are mixed in one common sample (CS) before LC-MS/MS analysis (Figure 13). Figure 13. Comparison of label-free and iTRAQ quantification. In labelfree quantification, all samples are prepared and analysed separately, which results in a huge amount of data difficult to interpret. Stable-isotope labelling by means of iTRAQ allows the comparison of proteins from each sample in the same LC-MS/MS read out. CS, common sample; HAP, high abundant protein; LAP, low abundant protein; LC-MS/MS, liquid chromatography coupled to tandem MS; S, sample; F, fraction. Juan José Nieto Fontarigo 76 7.4. Proteomic studies in asthma As Table 1 shows, several proteomic studies have been carried out in the last years in order to search for specific biomarkers of asthma, asthma exacerbation, and treatment response. The first analysis was carried out by Lindahl et al. in 1999, who used 2-D electrophoresis to show the alteration of several proteins (Lipocalin-1, transthyretin, cystatin S, and IgBF) in both BALF and NLF (nasal lavage fluid) from patients with asthma compared to healthy subjects [374]. Following this initial work, a few more studies in BALF [375, 376] and NLF [377, 378] came to light. For example, Wu et al. in 2005 used affinity depletion of top 6 abundant proteins, 1-DE-LC-MS/MS, and a label-free approach to identify 160 BALF proteins with changes in asthmatics after allergen challenge, some of them with high importance such as IGFBPs, AMBP protein, CD5L or AGP1 [375]. Some years later, Cederfur et al. employed a similar MS approach to identify a set of galectin binding glycoproteins as potential asthma biomarkers (e.g., CD59, keratin 8, HP, RAIG, SBEM, attractin, CD55, AGP, or SERPINA1) [376]. In addition, FABP5 and VEGF were increased in asthmatics compared to healthy controls both in NLF and IS [378]. Apart from BALF and NLF, a few numbers of studies have been performed in BB [357, 379], nasal brushing (NB) [380], or EBC. However, proteomics studies with IS [378, 381-386] or plasma/serum [358, 380, 386-393] samples to look for specific asthma biomarkers have been far more frequent. Moreover, most of these studies have compared asthmatics vs. healthy subjects, coming across significant changes in proteins such as S100A8/9/12, CC16, cystatin s, AAT/SERPINA1, α2M, HP, CP, Hpx, I-TAC, EGF, MMP-9, ITIH4, ORM1, or FGA/B [381, 382, 385, 390, 391]. In contrast, other proteomic studies have compared asthma with COPD [381, 383, 390] or cystic fibrosis [380], aspirin-induced asthma vs. aspirin-tolerant asthma [377, 387], the effect of exercise-induced bronchoconstriction INTRODUCTION 77 [382], the level of asthma control [384, 386, 394] or exacerbation [388], and the effect of different treatments [357, 358, 379]. However, none of them was aimed to compare the differences between asthma phenotypes, and only a handful reported proteomic changes in patients with different asthma severities [384, 386, 388, 394]. Moreover, most of the studies in plasma/serum were performed using 2-DE and MALDI-TOF, only one was carried out by an LC-MS/MS (label-free quantification) approach [391], and none of them used the iTRAQ technology. Therefore, further studies are needed to compare the serum/plasma proteome of different asthma phenotypes (e.g., AA vs. NAA) and severities (intermittent-mild vs. moderate-severe). Juan José Nieto Fontarigo 78 Table 1. Proteomic studies in asthma. Authors Sample Methods Results Ref. Lindahl M, 1999  BALF  NLF 2-DE  LCN1, TTR, cystatin S, and IgBF are altered in asthma. [374] Wu J, 2005  BALF AC and 1DE LC-MS/MS Label-Free  160 proteins were differentially expressed in asthmatic patients afte2r allergen challenge (e.g., IGFBPs, AMBP, CD5L, or AGP1) [375] Lee SH, 2006  Plasma 2-DE MALDI-TOF  C3a and C4a were higher in AIA patients than in patients with ATA. [387] Gray RD, 2008  IS CM10, Q10, or IMACNi SELDI-TOF  105 peaks with changes between asthmatics and controls, and 16 between asthma and COPD.  Proteins identified: S100A8, 9 and 12, CC16, lysosyme c, proline rich salivary peptide, cystatin s, and HBA1. [381] Nishioka T, 2008  Plasma 2-DE (DIGE) MALDI-TOF  19 proteins with changes during asthma exacerbation vs. nonexacerbation: GP1BB, CLU, C7, C1s, AAT/SERPINA1, SERPINA2 and3, F2, FGB, KNG1, A1BG, AZGP1, ALB, HP, AFM, APCS, CD5L, APOA1, APOA4. [388] Continued on next page INTRODUCTION 79 Table 1 (Continued) Rhim T, 2009  Plasma 2-DE MALDI-TOF  C3 increases whereas γfibrinogen decreases in asthma positive responders against Dermatophagoides pteronyssinus inhalation in comparison with negative responders. [389] Gomes- Alves P, 2010  NB  Serum CM10 pH 4 Q10 pH 10 SELDI-TOF  91 peaks with changes between control/asthma/cystic fibrosis  Protein identified: Hemoglobin subunit-beta [380] Bloemen K, 2011  EBC nano-HPLC MALDITOF/TOF  A peak pattern of peptides was identified to discriminate between healthy controls and asthmatics. Only cytokeratin 1 was identified. [395] Gharib SA, 2011  IS LC-MS/MS Label-Free (spectral counting)  70 proteins with differences between asthma and HC (e.g., S100A8/9, AAT/SERPINA1, SMR3B, or SCGB1A1).  5 differential proteins between EIB+ and EIB- (e.g., C3a and HPX). [382] Continued on next page Juan José Nieto Fontarigo 80 Table 1 (Continued) Ko YC, 2011  CD4+ T cells 2-DE MALDI-TOF  13 proteins with differential expression between controlled and uncontrolled asthmatics: HSP-70, FGB, TPM3, ATP- dependent DNA helicase II, HSP-90, ACTB, VIM, ARHGDIB, ENO1, CALR precursor, YWHAZ, PRDX2. [394] O'Neil SE, 2011  BB SCX LC-MS/MS iTRAQ  7 differential proteins between asthma patients and HC (ANXA5, DPT, HIST1H2AH, LMNA, PPIA, RPL7 and 8).  7 modified proteins between budesonide pre and post-treated asthmatics (α2M, ALDOA, ATP5B, DPYSL5, RPS20, SERPINB3, and VIM) [379] Terracciano R, 2011  IS MSB MALDI TOF/TOF  HNP1, HNP2, HNP3, and three C-terminal amidated peptides with changes between asthma, COPD, and healthy volunteers. [383] Verrills NM, 2011  Plasma 2-DE MALDI-TOF  20 proteins with differences between asthma, COPD, and controls. 4 of them able to discriminate between the three groups: α2M, HP, CP, and Hpx. [390] Continued on next page INTRODUCTION 81 Table 1 (Continued) Cederfur C, 2012  BALF LC-MS/MS Label-Free (spectral counting)  Some galectin-binding glycoproteins were found only in asthma compared to controls: CD59, keratin 8, HP, RAIG, SBEM, attractin, CD55, AGP, and SERPINA1 [376] Izbicka E, 2012  Plasma LCMS/MS Label-Free  I-TAC, EGF, and MMP-9 were higher in asthmatics than in controls. [391] Choi GS, 2013  NLF 2-DE (DIGE) MALDI-TOF  ApoA1, α2M, and CP were increased in aspirininduced nasal responders compared to nonresponders. [377] Lee TH, 2013  IS 2-DE MALDI-TOF  HNP-2, S100A9, βamylase, NGAL, 4- aminobutyrate transaminase, and cystatin SA were increased whereas plunc precursor, C3, GFAP, IgM κIIIb SON, MLL-AF4 der(11) fusion protein, CK-8, and IgG4 heavy chain were decreased in severe uncontrolled asthma compared to controlled asthma. [384] Continued on next page Juan José Nieto Fontarigo 82 Table 1 (Continued) Mauri P, 2014  BB SCX-LC- MS/MS Label-Free (Spectral count)  23 proteins were unregulated in omalizumab responders and 84 in omalizumab non-responders after treatment.  LGALS3, HSPG2, ELN, TGFB1, VCL, EZR, MYH9, Myl6, MYH11, actin, ACTG2, FBLN5, and FBLN2 were only identified in omalizumab responders. [357] Suojalehto H, 2015  IS  NLF 2D-DIGE LC-MS/MS  FABP5 and VEGF were increased in asthmatics compared to healthy controls [378] Hamsten C, 2016  Plasma Suspension bead array  Children with asthma display less CL5 and HPGDS levels and high NPSR1 levels. [392] Jiang H, 2016  Serum 2-DE (DIGE) MALDI-TOF  7 proteins were differentially expressed in SRA vs. SSA: Up (MTMR9, VDBP, HP precursor, C4a) Down (ALB precursor, MASP2, ApoA1) [358] Xu H, 2016  Plasma Antibody array  EPO and sGP130 were found augmented in childhood asthma compared to controls. [393] Continued on next page INTRODUCTION 83 Table 1 (Continued) Cao C, 2017  IS LC-MS/MS  23 proteins increased in asthma compared to controls: A2M, ANXA1, APOA2, ELANE, GPI, S100A8/9/12, AGT, C5, FGA, FGB, APOA1, SERPINF2, CHI3L1, HPX, ITIH4, ORM1, ILRN, PRG2, B2M, CTSB, FN1. [385] Kasaian MT, 2018  Serum  IS Olink multiplex arrays  27 proteins with changes between controlled and uncontrolled asthma.  Serum: CCL11, CCL19, CCL25, CDCP1, FGF21, FGF23, Flt3L, IL-6, IL- 10Rβ.  IS: ADA, AZU1, tPA, DNER, KLK6, MMP9, Chit1, GRN, PGLYRP1, MPO, HGF, PRTN3, RETN, PI3, Chi3L1, and OPG. [386] AC, affinity chromatography; AIA, aspirin-induced asthma; ATA, aspirin-tolerant asthma; BALF, bronchoalveolar lavage fluid; BB, bronchial biopsy; EBC, exhaled breath condensate; EIB, exercise-induced bronchoconstriction; IS, induced sputum; MSB, mesoporous silica beads; NB, nasal brushing; NLF, nasal lavage fluid; SRA, steroid-resistant asthma; SSA, steroid-sensitive asthma. CHAPTER I 91 INTRODUCTION During asthma attacks allergens trigger lung epithelial cells to release cytokines (e.g., Thymic stromal lymphopoietin (TSLP), Interleukin (IL)-33, IL-25) that activate innate leukocytes and drive the differentiation of allergen-specific T helper (TH)2 lymphocytes.1 Innate defences also rely on pattern recognition receptors, such as tolllike receptors (TLRs), capable of detecting pathogen-associated molecular patterns (PAMPs). Lipopolysaccharide (LPS) is a PAMP that interacts with CD14 (monocytes, macrophages, and neutrophils),2 a receptor whose gene has been linked to asthma/allergy.3 CD14 transfers LPS to the TLR4-MD2 complex, which induces the secretion of a set of cytokines (IL-12/IL-18) that act as an innate-adaptive bridge and favour the TH1 differentiation.4 In addition, IL-12 also prevents the development of allergen-specific TH2 cells, which ameliorates airway inflammation in allergic asthma.4 Therefore, a functional defect in CD14 could alter TH2 differentiation and IgE- mediated allergic diseases.5 Membrane-bound CD14 (mCD14) is released to the medium as soluble CD14 (sCD14),2,6,7 which either potentiates the response to LPS in macrophages by inducing the release of proinflammatory cytokines,8 or has a protective role by transferring LPS to lipoproteins.9 sCD14 is released from monocytes through a process enhanced by LPS, IL-6 and IL-1β,6 but decreased by interferon-γ (IFN-γ) and IL-4.10 sCD14 inversely correlates with IL-4,11 but positively with the number of sputum eosinophils.12 Moreover, plasma sCD14 is a biomarker of ongoing or acute immune responses.2,13 Thus, children with asthma exacerbations display augmented sCD14 levels compared to the recovery phase,14,15 whereas adult asthmatics have higher amounts in sputum than healthy subjects.12 An increased sCD14 concentration has also been detected in bronchoalveolar lavage Juan José Nieto Fontarigo 92 fluid (BALF) upon allergen exposure.16 However, other works reported unaltered sCD14 levels, like for example in asthmatic children.7,15 Single-nucleotide polymorphisms (SNPs) also constitute modulatory agents for CD14 levels that could influence the risk factors for developing asthma or aggravate disease symptoms.17 Baldini et al. found an association between CD14 (-159 C/T) SNP (rs2569190) and sCD14 in atopic children, showing TT homozygotes higher levels than CT/CC genotypes11 in line with the enhanced CD14 transcriptional activity in the T allele.6 Since those landmark studies, different works have confirmed these results,18,19 while the C allele has been associated with high IgE levels, atopy and asthma.15,17,20 However, this association has not been consistently replicated.3,13,21-24 These different results may be attributed to a number of factors, like the low sample size, asthma phenotype (atopic, non-atopic or mixed asthma), age of study population (children or adults), ethnicity (African, Caucasian or Asiatic population) or gene-environment interactions (e.g., endotoxin levels).21,25 Therefore, it seems necessary to undertake new works aimed to the simultaneous measurement of both membrane and soluble forms of CD14 as well as the CD14 (-159 C/T) SNP in adult Caucasian subjects with allergic asthma and different degrees of severity (intermittent-mild and moderate-severe). MATERIAL AND METHODS Subjects The study population was recruited from January 2009 to December 2012, at the Unit of Pneumology and Allergy of the USC University Hospital Complex of Santiago de Compostela (CHUS) and the Pontevedra Hospital Complex (CHOP). This study population CHAPTER I 93 included 277 healthy controls (HC) and 277 allergic asthmatics (AA), consisting of 108 intermittent-mild allergic asthmatics (IMAA) and 169 moderate-severe allergic asthmatics (MSAA). Asthma and allergy diagnosis was confirmed according to the Global Strategy for Asthma Management and Prevention criteria (GINA 2006, http://www.seicap.es/documentos/archivos/GINA2006general.pdf). All patients were in a stable phase for at least 4 weeks before the study initiation. Forced vital capacity (FVC), forced expiratory volume in 1 second (FEV1), and the FEV1/FVC ratio, were measured. Asthma diagnosis was confirmed by a positive bronchodilator test (>12% of FEV1 change after salbutamol) or methacholine challenge. Allergic sensitization was confirmed through a skin prick test or serum IgE specific to frequent allergens. Other variables were measured: smoking, pets at home, residence (rural/urban), profession, comorbidities, the age of symptoms onset, asthma control, or number of visits to emergency units, family doctors or hospitals during the year prior to the study initiation. HC were selected from patients scheduled in the hospital for minor surgeries such as orthopedic surgery or inguinal hernia, and smoke and systemic diseases or allergies were used as exclusion criteria. The research was carried out according to The Code of Ethics of the World Medical Association (Declaration of Helsinki). The project was also approved by the Ethics Committee of Clinical Research of Galicia (2011/001), Spain, and all subjects signed informed consent statements. Flow cytometry assays Venous peripheral blood was collected in ethylenediaminetetraacetic acid (EDTA) treated tubes (BD Vacutainer K2E). To analyse the expression of CD14 on peripheral blood leukocytes, CD14-FITC (Mouse IgG2a κ; BD Biosciences) or Isotype-FITC (Mouse IgG2a; BD Biosciences) were added to 100 μL of whole blood (30 min, room Juan José Nieto Fontarigo 94 temp.). Then, red cells were lysed (BD FACSTM Lysing Solution). Finally, 10 000 events were collected and analysed by means of a BD FACSCalibur flow cytometer. Data were examined using WinMDI 2.9 software (Joseph Trotter, La Jolla, CA. USA). Biochemical determinations Biochemical determinations were carried out by an ADVIA®1650 analyser (SIEMENS Healthcare Diagnostics S.L., Berlin, Germany) while neuron-specific enolase (NSE) was measured with electrochemiluminescence analyser (MODULAR ANALYTICS Cobas E-601, Roche Diagnostics; Mannheim, Germany). The nucleated cell counting was performed using an ADVIA®2120 hematology counter (SIEMENS Healthcare Diagnostics S.L., Berlin, Germany). Serum sCD14 levels were measured by means of an enzymelinked immunosorbent assay (ELISA) with the Quantikine®Human sCD14 Immunoassay kit (R&D Systems, MN, USA). Optical densities were recorded at 450 nm and protein concentration was calculated from standard curves. Genomic DNA purification and CD14 (-159 C/T) promoter SNP (rs2569190) studies Genomic DNA was purified from whole blood (200 µL) with the QIAamp® DNA Mini Kit (QIAGEN, Melbourne, Australia). The subsequent study of the rs2569190 SNP in the CD14 promoter was conducted by the CEGEN-PRB2 USC node using the iPlex® Gold chemistry and MassARRAY platform, according to manufacturer‟s instructions (Agena Bioscience, San Diego, CA). Genotyping assay (Polymerase chain reaction/PCR primers and single-base- extension/SBE primers) were designed using the Agena Bioscience MassARRAY Assay Designer 4.1 software. To avoid confusion in the CHAPTER I 95 mass spectrum, a tag (5-ACGTTGGATG-3) was added to the 5´ end of each PCR primer. Both SBE and PCR primer sequences are shown in Supplementary Table 1. PCR reaction was set up in a 5 µL volume and contained template DNA (20 ng), 1× PCR buffer, MgCl2 (2 mM), dNTPs (500 µM) and PCR enzyme (1 U/reaction). A pool of PCR primers was made at a final concentration of each primer of 100 nM (Metabion International AG, Germany). The thermal cycling conditions for the reaction consisted of an initial denaturation step at 95°C for 2 minutes, followed by 45 cycles of 95°C for 30 seconds, 56°C for 30 seconds and 72°C for 1 minute, and a final extension step of 72°C for 5 minutes. PCR products were treated with shrimp alkaline phosphatase (1.5 U) by incubation at 37°C for 40 min, followed by enzyme inactivation by heating at 85°C for 5 min to neutralize unincorporated dNTPs. The iPLEX GOLD reactions were set up in a final 9 µL volume and contained 0.222x iPLEX buffer Plus, 0.222x iPLEX termination mix and iPLEX enzyme (1.35 U/reaction). An SBE primer mix was made to give a final concentration of each primer between 0.52 µM and 1.57 µM (Metabion International AG, Germany). The thermal cycling conditions for the reaction included an initial denaturation step at 95°C for 30 seconds, followed by 40 cycles of 95°C for 5 seconds, with an internal 5 cycles loop at 52°C for 5 seconds and 80°C for 5 seconds, followed by a final extension step of 72°C for 3 minutes. The next step is to desalt the iPLEX Gold reaction products with Clean Resin following the manufacturer‟s protocol. The desalted products were dispensed onto a 384 Spectrochip II using an RS1000 Nanodispenser and spectra were acquired using the MA4 mass spectrometer, followed by manual inspection of spectra by trained personnel using MassARRAY Typer software, version 4.0. All assays were performed in 384-well plates, including negative controls and a trio of Coriell samples (Na10830, Na10831 and Na12147) for Juan José Nieto Fontarigo 96 quality control. 10% of random samples were tested in duplicate and the reproducibility was 100%. Statistics Descriptive data are presented as either median (interquartile range; IQR1-3) or percentages. To assess the significance of changes between AA and HC, Mann–Whitney U two-tailed test or Kruskal– Wallis One Way Analysis of Variance on Ranks followed by Dunn‟s multiple comparison test were used. Receiver Operating Characteristic (ROC) curves and Spearman´s association test were also employed, while differences in proportions were assayed by the χ2 test. To evaluate the association between CD14 (-159 C/T) SNP and the risk of allergic asthma, Odd´s ratios (ORs) and 95% confidence intervals (CIs) were calculated according to different models: TT+TC vs. CC (dominant model), TT vs. TC+CC (recessive model), TT vs. CC, TC vs. CC, and T vs. C (allelic model). Hardy–Weinberg equilibrium (HWE) was calculated by using Pearson χ2 test. All analyses and graphs were conducted using GraphPad Prism version 6.0 (GraphPad Software, Inc., San Jose, California, USA). Data are presented in box and whisker plots, where median, 25 and 75 quartiles, 5-95 percentiles (error bars) and anomalous values are shown. The statistical signification was defined as P < 0.05. RESULTS Demographic and clinical characteristics of the study population In this work a case-control study was performed, where adult patients with both intermittent-mild and moderate-severe allergic asthma were recruited. These patients were in a clinically stable state, had a well- CHAPTER I 97 controlled disease, and the majority were non-smokers under treatment with inhaled corticosteroids (Table 1). FEV1 (%) and FEV1/FVC ratio (%) values are described in Table 1, showing decreased levels in MSAA (moderate-severe allergic asthmatics) compared to IMAA (intermittent-mild allergic asthmatics) (Table 1). Although 66.4% of AA came from rural areas, most of them had no animals or just dogs/cats; only 11% had farm animals. Table 1. Characteristics of the study population. AA HC ALL IMAA MSAA N 277 108 169 277 Agea 32 (25-42) 31 (22-38) 33 (26-46) 46 (31-60) Sex (M/F) 119/158 42/66 77/92 105/172 Smokers (%) 21.3 15.7 24.8 0 Control: Good 219 98 121 - Partial 36 8 28 - Bad 22 2 20 - Treatment: No 66 66 0 - Inhaled Corticosteroids 196 34 162 - Oral Corticosteroids 15 0 15 - Antileukotrienes 63 6 57 - Omalizumab 4 0 4 - FEV1 (%) 97.2 (83.7- 108.0) 105.0 (95.3- 115.7)# 93 (74.5- 102.2)# - FEV1/FVC (%) 78.0 (70.7- 85.4) 82.9 (75.9- 88.4)# 74.7 (67.6- 81.9)# - Neutrophils (103 cells/μL)a 3.67 (2.77- 4.50) 3.53 (2.99- 4.27) 3.71 (2.90- 4.96) 3.54 (2.77- 4.50) Lymphocytes (103 cells/μL )a 2.22 (1.85- 2.71)* 2.20 (1.86- 2.79)& 2.23 (1.80- 2.71)& 2.02 (1.62- 2.45) Monocytes (103 cells/μL )a 0.47 (0.38- 0.59)* 0.47 (0.39- 0.56)& 0.46 (0.37- 0.62)& 0.35 (0.28- 0.43) Continued on next page Juan José Nieto Fontarigo 98 According to their allergic disease state, patients had significantly augmented levels of eosinophils and total IgE compared to HC, but there were no significant changes regarding disease severity (Table 1). IgE showed a positive correlation with eosinophil, monocyte and, to a lesser extent, lymphocyte blood count, underlying the relevance of these subsets in allergic asthma pathogenesis (Table 2). Since activation of eosinophils and macrophages has been associated with enhanced NSE levels under some pathological conditions,26,27 we also undertook the measurement of this enzyme in serum samples. As table 2 shows, it was found a positive correlation of IgE, eosinophils and monocytes with NSE (Table 2), which prompted us to examine the utility of this parameter as an additional marker of allergic asthma. As shown in Figure 1a, NSE levels were augmented in AA compared to HC and tend to be around 14.6% higher in men than in women (Figure 1a). Moreover, the area under the curve (AUC) of the ROC plot for NSE levels was close to AUC of total IgE and higher than AUC of blood eosinophils (absolute values) (Figure 1b). Table 1 (Continued) Eosinophils (103 cells/μL )a 0.33 (0.19- 0.51)* 0.29 (0.20- 0.51)& 0.34 (0.18- 0.51)& 0.16 (0.11- 0.23) Basophils ((103 cells/μL )a 0.04 (0.03- 0.05) 0.04 (0.03- 0.05) 0.04 (0.02- 0.06) 0.04 (0.03- 0.06) IgE (IU/mL)a 272 (116- 533)* 270 (111- 485)& 276 (122- 668)& 34 (11-102) AA, allergic asthmatics; HC, healthy controls; IMAA, intermittent-mild allergic asthmatics; MSAA, moderate-severe allergic asthmatics. a Median value (IQR1-3); * AA vs HC: Mann-Witney U Statistic, P < 0.001; # IMAA vs MSAA: Mann-Witney U Statistic, P < 0.001; & IMAA vs MSAA vs HC: Kruskal-Wallis One Way Analysis of Variance on Ranks (P < 0.001), IMAA/MSAA vs HC P < 0.05 Dunn's Method. CHAPTER I 99 Table 2. Spearman correlation matrix of the study population. VARIABLES NSE CRP IgE mCD14# sCD14 Age Leucocyte count 0.163* 0.221*** 0.192*** -0.021 -0.035 -0.165*** Neutrophil count 0.003 0.190*** -0.027 -0.027 -0.034 -0.052 Lymphocyte count 0.077 0.107* 0.143*** -0.020 -0091 -0.152*** Monocyte count 0.303*** 0.154*** 0.336*** 0.234***P -0.021 -0.182*** Eosinophil count 0.279*** 0.054 0.459*** -0.199*** -0.071 -0.273*** Basophil count 0.149*** -0.024 0.057 -0.034 -0.005 -0.113* FEV1% 0.099P -0.088P -0.057P 0.140P -0.177P -0.209***P FEV1/FVC 0.106P -0.071P -0.051P 0.151 -0.146P -0.375***P TNF -0.022 0.179*** -0.011 0.082 0.119** 0.198*** NSE -0.004 0.322*** -0.215*** 0.087 -0.128** CRP -0.033 -0.000 0.158** * 0.119** IgE -0.264*** -0.054 -0.296*** mCD14# -0.079 0.177*** sCD14 0.102* CRP, C-reactive protein; IgE, immunoglobulin E; NSE, neuron specific enolase; P, patient population; TNF, tumour necrosis factor. *P<0.05, **P<0.01, ***P<0.001. # % of CD14+ monocytes. No alterations were appreciated for C-reactive protein (CRP), IgG, IgA, IgM, or tumour necrosis factor (TNF) in AA. The influence of age was also taken into consideration, with a negative correlation with FEV1%, FEV1/FVC, IgE and leukocyte subtypes (mostly eosinophils), but a small positive association with TNF, CRP, mCD14 and sCD14 (Table 2). Juan José Nieto Fontarigo 106 Table 4. Association between CD14 (-159 C/T) SNP and allergic asthma risk. OR (95% CI) χ2 (Yate´s correction) P AA (ALL) TT+TC vs CC 0.67 (0.45- 0.98)* 3.805 0.0511 TT vs TC+CC 0.68 (0.46- 1.00) 3.484 0.0620 TT vs CC 0.55 (0.34- 0.89)* 5.449 0.0196* TC vs CC 0.74 (0.49- 1.11) 1.180 0.1704 T vs C 0.74 (0.59- 0.94)* 5.776 0.0162* IMAA TT+TC vs CC 0.72 (0.43- 1.20) 1.300 0.2543 TT vs TC+CC 0.79 (0.48- 1.33) 0.566 0.4517 TT vs CC 0.66 (0.35- 1.23) 1.346 0.2460 TC vs CC 0.75 (0.44- 1.30) 0.781 0.3768 T vs C 0.81 (0.59- 1.11) 1.531 0.2159 MSAA TT+TC vs CC 0.64 (0.42- 0.99)* 3.630 0.0547 TT vs TC+CC 0.61 (0.38- 0.96)* 4.029 0.0442* TT vs CC 0.49 (0.28- 0.85)* 5.767 0.0163* TC vs CC 0.72 (0.46- 1.15) 1.572 0.2100 T vs C 0.70 (0.54- 0.92)* 6.091 0.0136* AA, allergic asthmatics; CI, confidence interval; IMAA, intermittent-mild allergic asthmatics; MSAA, moderate-severe allergic asthmatics; OR, odds ratio; TC vs CC, heterozygote; TT vs CC, homozygote; TT vs TC+CC, recessive model; TT+TC vs CC, dominant model. ∗Significant difference. CHAPTER I 107 Regarding to the other genetic models, a significant association of CD14 (-159 C/T) and allergic asthma risk was found between the homozygotes TT vs. CC (OR = 0.55, 95% CI = 0.34-0.89, P = 0.0196), and almost reached significance in a dominant model (TT+TC vs. CC: OR = 0.67, 95% CI = 0.45–0.98, P = 0.0511) (Table 4). Furthermore, after segregating by disease severity, it was found an association of allergic asthma risk with this SNP only in MSAA according to a recessive model (TT vs. TC+CC: OR = 0.61, 95% CI = 0.38-0.96, P = 0.0442) or TT vs. CC genotype comparisons (OR = 0.49, 95% CI = 0.28-0.85, P = 0.0163). Therefore, the results suggested that T allele and TT homozygote individuals have decreased risk of allergic asthma compared with C allele and CC homozygote carriers, respectively. The influence of the CD14 (-159 C/T) SNP on CD14 levels Although we have shown augmented peripheral blood monocyte count and decreased levels of mCD14 (Figures 2a-c), the number of monocytes was not influenced by the CD14 (-159 C/T) SNP genotype. We also failed to detect any change in mCD14 related to the SNP genotype (data not shown). In contrast (and regardless of whether they belong to the control group or to the asthmatic population), CC genotypes and to a lesser extent TC genotypes had lower concentrations of sCD14 (absolute values) than TT carriers, while no significant differences were observed between TC and CC subjects (Figure 3a). This association was maintained between TT and CC carriers when sCD14 levels were normalised by the absolute count of monocytes (Figure 3b). Therefore, this SNP could be partially responsible for the reduction of normalised sCD14 levels in AA and influence the severity of this disease (Figure 2e). Juan José Nieto Fontarigo 108 Figure 3. Impact of the CD14 (-159 C/T) SNP (rs2569190) on sCD14 levels in serum. Absolute (ng/mL) (a) and relative (ng/1 x 103 monocytes) (b) sCD14 levels in serum samples from TT, TC and CC donors (healthy and asthmatics). *Kruskal- Wallis One Way Analysis of Variance on Ranks, P < 0.001; Dunn's Method was used for multiple comparisons (numbers on the graph represent P-values). DISCUSSION In the current study, we report data supporting an increase of NSE and monocytes and a down-modulation of their mCD14 expression in allergic asthma regardless of disease severity. In addition, we detect a decrease of normalised sCD14 values in serum samples from asthmatics, suggesting the expansion of a CD14low monocyte subset and the influence of the CD14 (-159 C/T) SNP genotype. Indeed, we evidence an association of the T allele and TT genotype of CD14 (- 159 C/T) polymorphism with reduced risk of moderate-severe allergic asthma. AA in our study have an atopic disease with eosinophilia, monocytosis and elevated IgE levels. NSE is the neuronal isomer of the glycolytic enzyme 2-phospho-D-glycerate hydrolase, and a typical biomarker of small cell lung cancer.28 Nevertheless, changes in nonmalignant inflammatory lung diseases have also been found,27,29-32 CHAPTER I 109 since this enzyme can translocate towards the cell surface upon proper stimulatory signals to enhance a proinflammatory response.33 Our results support the presence of higher NSE levels in men, as previously reported by Collazos et al.,29 but contrary to this work our asthma patient cohort displays above-normal NSE levels in serum. Monocytes/macrophages appear to be a possible source of NSE,27,33 and increased numbers of monocytes as well as a correlation of them with NSE levels were demonstrated in our study. However, other plausible sources of NSE are eosinophils or injured epithelial cells during pulmonary infiltration,26 while the neuronal distress or hypoxia occurring in the lung also could play a role during the disease.29 Apart from other cells as T and B lymphocytes, eosinophils, basophils or neutrophils, monocytes are gaining importance as regulators of inflammation in asthma and as key players in the pathogenesis.34-36 Our results show the expansion of this subset in AA regardless of the severity of the symptoms (i.e., IMAA and MSAA), as well as a reduction of mCD14, a monocyte marker associated to asthma.3 In contrast, some authors have described no differences in the staining for mCD14,37,38 even though these could be the result of a low statistical sample size. Reduced levels of mCD14 or TLR4 in AA makes biological sense,39 as signal transduction through CD14/TLR4 leads to IL-12 secretion, a powerful inducer of TH1 polarization.13 Therefore, attenuated mCD14 levels on antigen presenting cells (APCs) could favour TH2-driven allergic asthma.4,5,13,16 This diminished number of mCD14 molecules on monocytes could arise as a result of several, and not mutually exclusive, mechanisms: a) altered transcription/translation rates affecting protein abundance; b) expansion of CD14low monocyte subsets; c) a vesicle- or enzymaticmediated mechanism that release mCD14 from monocytes and should also affect sCD14 concentration. Juan José Nieto Fontarigo 110 The degree of mCD14 down-modulation on monocytes suggests the preferential expansion of a small CD14low subset and not a globally altered transcription/translation rate. This, for example, is in line with the increased percentage of CD14low/- monocytes upon in vitro culture in the presence of TSLP, a cytokine important in allergic asthma.40 Monocytes are heterogeneous, with major (CD14high) and minor (CD14low) subsets.33 CD14high (“classical”) monocytes display a CD16/FcγRIII- phenotype, while the less frequent CD16+ subset consists of both intermediate (CD14highCD16+) and non-classical (CD14lowCD16+) subpopulations.34 CD16+ monocytes, particularly the intermediate subset, are expanded in inflammation, severe asthma or upon allergen challenge,34,36 in line with their pro-inflammatory nature.41 A major constraint of our study is that we have not analysed CD16, but our results show a significant down-modulation of mCD14 in allergic asthma, which appears to rather support the expansion of CD14lowCD16+ monocytes. These cells (non-classical subset) express high levels of CD80, CD86, and CD163, suggesting a high antigen presenting capability.42 Furthermore, non-classical monocytes are in an advanced differentiation stage and they evidence high invading ability to infiltrate and differentiate into M2-type macrophages,43 a subset related to allergic inflammation.44 CD14 can be released to medium from hepatocytes as an acute phase protein.45 Although we saw a small correlation between sCD14 and CRP or TNF, the levels of these two last molecules had no changes between AA and HC, and our patients were in a steady-state of the disease. Excluding the hepatocyte origin, monocytes are the most likely cell source of sCD14. Down-modulation of mCD14 in monocytes from AA does not fit with either its shedding2,6,7 or the release of mCD14-enriched vesicles [http://exocarta.org/gene_summary?gene_id=12475] from these cells, because both processes should lead to a higher number of sCD14 CHAPTER I 111 molecules in the extracellular compartment, as happen during the acute phase.15,16,46,47 However, patients in our study are in a chronic phase, where there is no relationship between monocyte counts and sCD14 or mCD14-sCD14 correlation.16 Therefore, our results only make sense considering a puzzling scenery with an elevation of monocyte numbers and enhanced frequencies of both CD14high,34 but also CD14low (our results) subsets of monocytes in asthma. Indeed, in our study only normalised serum levels of sCD14 were significantly reduced in patients. In agreement, sCD14 levels have been inversely correlated with IL-4-production,11 total IgE,11 or asthma severity.46 However, some authors have detected higher levels12 or no differences7,15 of baseline sCD14 in peripheral blood from asthmatics. Hence, we cannot rule out the contribution of many potential confounding factors that explain these different results, like gene-gene or gene-environment interactions.11,15 One of the most studied CD14 polymorphisms in asthma is the CD14 (-159 C/T) SNP (rs2569190).11 Previous studies investigating the association of this SNP with allergic asthma yielded variable results regarding the strength and direction of the association.3,17,24 These contradictory results can be explained by differences in ethnicity, low sample size, the age of patients or gene-environment interaction.21,25 We performed our study in a well-defined population (Caucasian, adults, allergic asthmatics and mostly non-farmers), with a high sample size (277 AA vs. 277 HC), and two different disease severity grades (IMAA and MSAA). In agreement with others,11,17 we show an association of the frequency of the C allele and the CC genotype with allergic asthma (whole asthmatics). More interesting, this association is also related to the disease severity, as it is only maintained in MSAA and within this group, in severe asthmatics. Moreover, the risk of having moderate-severe allergic asthma (but not intermittent-mild asthma) is lower in carriers of the T allele (T vs. C) Juan José Nieto Fontarigo 112 and TT genotype, following either a recessive model (TT vs. TC+CC) or after comparing TT vs. CC homozygotes. As other works have shown,5,11,12,18,19 we evidence augmented sCD14 levels in subjects carrying the TT genotype but no association of this polymorphism with mCD14 levels on monocytes. This suggests an adverse role for the C allele, the CC genotype and the presence of low levels of sCD14/mCD14 in allergic asthma or atopy,11,46 especially among adult and atopic subjects exposed to low levels of endotoxin, like our cohort.13 In summary, our findings show an increment in the serum levels of NSE, which could be used as a novel biomarker of allergic asthma. On the other hand, we also found a decrease in the expression of CD14 on monocytes from allergic asthmatic patients, probably related to an increase of CD14low monocyte subset. Moreover, we evidence an association of the (-159 C/T) SNP in the CD14 promoter with allergic asthma, and a decreased risk of having moderate-severe allergic asthma in carriers of T allele and TT genotype. Furthermore, TT genotype is associated with higher levels of sCD14, pointing out a protective role for the T allele in this disease. REFERENCES 1. Martinez, F. D. & Vercelli, D. Asthma. Lancet 382, 1360-1372 (2013). 2. White, A. F. & Demchenko, A. V. Modulating LPS signal transduction at the LPS receptor complex with synthetic Lipid A analogues. Adv. Carbohydr. Chem. Biochem. 71, 339-389 (2014). 3. Wang, D., Yang, Y., Xu, J., Zhou, Z. K. & Yu, H. Y. Association of CD14 -159 (-260C/T) polymorphism and CHAPTER I 113 asthma risk: an updated genetic meta-analysis study. Medicine (Baltimore) 95, e4959 (2016). 4. Vignali, D. A. & Kuchroo, V. K. IL-12 family cytokines: immunological playmakers. Nat. Immunol. 13, 722-728 (2012). 5. Tesse, R., Pandey, R. C. & Kabesch, M. Genetic variations in toll-like receptor pathway genes influence asthma and atopy. Allergy 66, 307–316 (2011). 6. Shive, C. L., Jiang, W., Anthony, D. D. & Lederman, M. M. Soluble CD14 is a nonspecific marker of monocyte activation. AIDS 29, 1263-1265 (2015). 7. Marcos, V. et al. Expression, regulation and clinical significance of soluble and membrane CD14 receptors in pediatric inflammatory lung diseases. Respir. Res. 11, 32 (2010). 8. Lévêque, M. et al. Soluble CD14 acts as a DAMP in human macrophages: origin and involvement in inflammatory cytokine/chemokine production. FASEB J. 31, 1891-1902 (2017). 9. Kitchens, R. L., Thompson, P. A., Viriyakosol, S., O‟Keefe, G. E. & Munford, R. S. Plasma CD14 decreases monocyte responses to LPS by transferring cell-bound LPS to plasma lipoproteins. J. Clin. Invest. 108, 85-93 (2001). 10. Landmann, R., Fisscher, A. E. & Obrecht, J. P. Interferongamma and interleukin-4 down-regulate soluble CD14 release in human monocytes and macrophages. J. Leukoc. Biol. 52, 323-330 (1992). 11. Baldini, M. et al. A Polymorphism* in the 5‟ flanking region of the CD14 gene is associated with circulating soluble CD14 levels and with total serum immunoglobulin E. Am. J. Respir. Cell Mol. Biol. 20, 976-983 (1999). Juan José Nieto Fontarigo 114 12. Alexis, N., Eldridge, M., Reed, W., Bromberg, P. & Peden, D. B. CD14-dependent airway neutrophil response to inhaled LPS: role of atopy. J. Allergy Clin. Immunol. 107, 31-35 (2001). 13. Simpson, A. & Martinez, F. D. The role of lipopolysaccharide in the development of atopy in humans. Clin. Exp. Allergy 40, 209-223 (2010). 14. Garty, B. Z., Monselise, Y. & Nitzan, M. Soluble CD14 in children with status asthmaticus. Isr. Med. Assoc. J. 2, 104-107 (2000). 15. Klaassen, E. M., Thönissen, B. E., van Eys, G., Dompeling, E. & Jöbsis, Q. 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Racial differences in the association of CD14 polymorphisms with serum total IgE levels and allergen skin test reactivity. J. Asthma Allergy 6, 81-92 (2013). CHAPTER I 115 22. Lau, M. Y. et al. CD14 polymorphisms, microbial exposure and allergic diseases: a systematic review of gene-environment interactions. Allergy 69, 1440-1453 (2014). 23. Zhang, Y. N., Li, Y. J., Li, H., Zhou, H. & Shao, X. J. Association of CD14 C159T polymorphism with atopic asthma susceptibility in children from Southeastern China: a casecontrol study. Genet. Mol. Res. 14, 4311-4317 (2015). 24. Zhang, R., Deng, R., Li, H. & Chen, H. No Association Between -159C/T Polymorphism of the CD14 Gene and Asthma Risk: a Meta-Analysis of 36 Case-Control Studies. Inflammation 39, 457-466 (2016). 25. Zhang, G., Goldblatt, J. & LeSouëf, P. N. Does the relationship between IgE and the CD14 gene depend on ethnicity? Allergy 63, 1411-1417 (2008). 26. Sakito, O. et al. 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CHAPTER II 123 INTRODUCTION Asthma is influenced by genetic factors (eg, dipeptidyl peptidase 10 [DPP10] and ADAM metallopeptidase domain 33 [ADAM33]) and environmental factors [1]. Its management should be based on endotypes [1,2]. During asthma attacks, allergens trigger lung epithelial cells to release cytokines, which in turn activate innate leukocytes and drive type 2 helper T cell (TH2) lymphocyte differentiation [1]. These cells release interleukins (IL-4, IL-5, and IL- 13), stimulate IgE production and favor the activation of eosinophils, mast cells, and basophils [1]. This effector role is counteracted by regulatory T cells (Tregs) [3], whose number and/or function may be altered in asthma [4]. Both CD4+ T subsets express differential levels of interleukin receptor 2 (IL-2R). Thus, CD25 (IL-2Rα) is mainly expressed by Tregs [4], while a CD25–/low phenotype is present in effector CD4+ T lymphocytes (Teff). T-cell receptor (TCR)–triggered Teff cells release soluble CD25 (sCD25), an activation marker [5] that is elevated in serum/plasma during asthma exacerbations [6] and that correlates positively with the severity of allergic asthma [7]. In addition, Tregs are thought to be another source of sCD25 [4,8,9]. sCD25 is also increased in bronchoalveolar lavage fluid from asthma patients [8,9]. Another interesting protein in the pathogenesis of asthma is CD26/DPP4, a surface glycoprotein enriched in CD4+ T cells [10]. In the form of dipeptidyl peptidase 4 (DPP4; EC 3.4.14.5), the enzyme belongs to the serine peptidase subfamily S9B, which includes an asthma susceptibility locus (DPP10 [11]), dipeptidyl peptidase 8 (DPP8), dipeptidyl peptidase 9 (DPP9), and fibroblast activation protein alpha (FAP) [12-16]. Dipeptidyl peptidase 2 (DPP2, DPP7) from serine peptidase subfamily S28 also displays DPP4-like activity at acidic pH. As CD26, the glycoprotein interacts with adenosine deaminase, CD45, caveolin-1, and C-X-C chemokine receptor type 4 Juan José Nieto Fontarigo 124 (CXCR4), thereby fulfilling either inhibitory or enhancing roles upon association [17]. CD26 is an activation marker known to be upregulated on lymphocytes (especially CD4+) in adults with allergic asthma [18]. CD4+ T cells are major actors in the pathogenesis of asthma; however, unlike CD25, Treg cells display lower CD26 levels than Teff lymphocytes. Indeed, CD26 is a negative marker of Treg cells and a marker of the remaining TH subsets. Thus, expression of CD26 on TH follows the order of TH17>>TH1>TH2>Treg [19,20]. Hence, an elevated presence of CD26 on CD4+ T cells in adult allergic asthma suggests an activated status [18,21] and may point to a specific T-cell phenotype. Moreover, a soluble form of CD26 (sCD26/sDPP4) is released from T cells into the bloodstream, either shed by metalloproteases [22] or secreted by CD26+ vesicles (http://www.exocarta.org). In plasma/serum, sCD26 accounts for >90% of total sDPP4-like activity [23,24], and the remaining 10% is derived from the intracellular peptidases DPP2, DPP8, and DPP9. These DPP4 homologs are also involved in the pathogenesis of asthma [13] and show differential expression in leukocytes [14,15] and eosinophils [25]. Moreover, both DPP8 and DPP9 enzymes are upregulated in activated macrophages and trimmed for antigen presentation [14,15]. Besides, DPP2 is necessary for maintaining the quiescence of lymphocytes and is downmodulated upon activation [15]. CD26/DPP4 cleaves X-Pro or X-Ala amino terminal dipeptides from chemokines (eg, CXCL12a [stromal cell-derived factor-1α, SDF-1α], CCL11 [eotaxin], and CCL5 [regulated on activation, normal T cell expressed and secreted, RANTES]), thereby modulating their biological activity and immunological function, as recently reviewed [17,26,27]. Other substrates include neuropeptides and peptide hormones such as incretins [28,29], whose half-life is prolonged by the DPP4 inhibitors currently used as antidiabetic drugs CHAPTER II 125 [30]. Vascular substrates of DPP4 may be cleaved by sDPP4, DPP4 expressed on leukocytes, and endothelial DPP4 [31]. Increased DPP4- like activity has been observed in bronchoalveolar lavage fluid from asthmatic rat lungs and is due mostly to sDPP4 and, to some extent, DPP8, DPP9, and DPP2 [13,32]. CD4+ T lymphocytes are the main source of sCD26, as this subpopulation displays the highest percentage of CD26+ cells [10,23,33]. Therefore, this molecule could be used as a “fingerprint” to test the activation status or differentiation status of CD4+ T cells in asthma. However, the few studies that have been undertaken show augmented levels of sCD26 in allergic asthma that were positively correlated with eosinophils and IgE [18]. In contrast, sCD26 was inversely associated with inflammation in chronic eosinophilic pneumonia, a disease linked to asthma [34], while no changes were observed for sCD26 in children with asthma or atopy [35]. To date, few studies have monitored sCD26 in asthma, and none consider the potential roles of CD26 in the pathogenesis of asthma or take into account the possibility that abnormalities of circulating biomarkers (sCD25 and sCD26) may reflect changes in leukocyte phenotype such as CD25–/lowCD26+ Teff cells and CD25+/highCD26low Treg cells. Therefore, in the present study, a comprehensive analysis was carried out to assess the aforementioned immune biomarkers in patients with moderate-severe allergic asthma. MATERIAL AND METHODS Subjects The study was conducted between 2009 and 2012 and included patients from hospital consultations for Pneumology and Allergy in Juan José Nieto Fontarigo 126 Galicia (Spain). Patients had confirmed diagnosis of asthma and allergy for at least one year according to Global Strategy for Asthma Management and Prevention (GINA 2006, http://www.seicap.es/documentos/archivos/GINA2006general.pdf) criteria. The research project was approved by the Ethics Committee of Clinical Research of Galicia (2011/001), Spain, and informed consent was obtained from all individual participants included in the study. A validation cohort was also recruited from 2014 to 2016 (Neumology Service, University Hospital of Santiago de Compostela, Spain). All patients were in a stable phase for at least 4 weeks before sample collection. Healthy Controls (HC) were selected from patients scheduled in the hospital for minor surgeries such as inguinal hernia or orthopedic surgery; they were non-smokers and systemic diseases or allergies were absent. None of the patients or healthy controls were on DPP4 inhibitors treatment. Sensitization in allergic asthmatic patients (AAP) was confirmed through a skin prick test or serum IgE specific to frequent allergens. Other variables were also accounted: body mass index (BMI), rural-urban residence, profession, smoking or comorbidities. Biochemical determinations were performed using an ADVIA®1650 analyzer (SIEMENS Healthcare Diagnostics S.L., Berlin, Germany). The nucleated cells number was measured using an ADVIA®2120 hematology counter (SIEMENS Healthcare Diagnostics S.L., Berlin, Germany). Magnetic purification of CD4+ T cell subsets and in vitro culture Buffy coats from healthy subjects were donated by “Axencia Galega de Sangue, Órganos e Tecidos” (Santiago de Compostela, Spain) and used to isolate peripheral blood mononuclear cells (PBMCs) by Ficoll® density gradients. Teff and Treg cells were prepared from PBMCs by means of the Dynabeads® Regulatory CD4+CD25+ T cell CHAPTER II 127 Kit (Life-Technologies, Spain). Viability was always >90% (trypan blue exclusion). Teff (CD4+CD25-) and Treg (CD4+CD25+) cells were cultured in vitro for 4 days in 96-microwell U-bottom plates with ImmunoCult™-XF T Cell Expansion Medium (StemCell, Grenoble, France) supplemented (or not) with soluble tetrameric antibody complexes (ImmunoCult™ Human CD3/CD28 T Cell Activator; StemCell). To promote a partial Teff differentiation, the following cytokines (PeproTech, London, UK) were added: 10 ng/mL IL-12 (TH1-like), 10 ng/mL IL-4 (TH2-like), or IL-1β (100 ng/mL), IL-6 (30 ng/ml) and IL-23 (100 ng/mL) (TH17-like). In addition, 800 ng/mL of IL-2 was used for Treg cells maintenance. Flow cytometry assays Venous peripheral blood was collected (BD Vacutainer K2E) ir order to examine the proportion of Teff and Treg cells. Leukocytes from 100 μL of whole blood were stained (30 min, room temp.) with mouse IgG1 ĸ isotype antibodies (BD Biosciences) labelled with FITC, PE- Cy7, AlexaFluor-647 and PE as negative controls. Alternatively, cells were stained with mouse IgG1 ĸ specific antibodies (BD Biosciences) against CD4 (FITC), CD25 (PE-Cy7) or CD127 (Alexa Fluor-647) and a mouse IgG2b antibody specific for CD26 (PE; Immunostep); then, red cells were lysed (BD FACSTM Lysing Solution). The purity of Teff/Treg lymphocytes prior (or after) in vitro cell culture was also assayed with the same specific (CD4-FITC, CD25-PE-Cy7, CD26- PE) or isotype antibodies (Isotype-FITC, Isotype-PE-Cy7, Isotype- PE). Finally, samples were analysed (BD FACSCalibur and FACSort) and a number of 10,000-200,000 events collected. Data were examined using WinMDI 2.9 software (Joseph Trotter, La Jolla, CA. USA). Juan José Nieto Fontarigo 128 DPP4 activity measurement Total DPP4 enzymatic activity was colourimetrically assayed by means of a flat-bottom 96-well microplate-adapted and end-point protocol. Cell culture supernatants (50 μL) were diluted with 50 μL reaction buffer (0.05 M Tris(hydroxymethyl)aminomethane (TRIS)- HCl pH 8.0 buffer) and 100 μL of 2 mM glycyl-prolyl- paranitroanilide (Gly-Pro-pNA). Plates were incubated at 37ºC and absorbance sequentially (30-120 min) recorded at 405 nm (Labsystems Multiscan MS microtiter plate reader). The concentration of pNA was calculated from a standard curve, ranging from 0 – 2000 μM. One international unit (IU) was defined as the amount of enzyme that processes 1 μmol Gly-Pro-pNA (or releases 1 μmol pNA from this substrate) per minute. Assays were performed in duplicate for each sample. Determination of sCD25 and sCD26 Serum sCD25 levels were measured through enzyme-linked immunosorbent assay (ELISA) from R&D Systems, MN, USA (Quantikine® Human IL-2Rα Immunoassay), and sCD26 was quantified with ELISAs plates from eBioscience®, Vienna, Austria (Human sCD26 Platinum ELISA). Optical densities were recorded at 450 nm and protein concentration calculated from standard curves. Statistics Descriptive data are presented as either median (interquartile range; IQR1-3) or percentages. To assess the changes between AAP and HC in non-normally distributed variables we used Mann–Whitney U twotailed test, or the Kruskal–Wallis test followed by Dunn‟s multiple comparison test for more than 2 groups. Spearman´s test was used to measure the association between variables. All analyses were conducted using GraphPad Prism 6.0 (GraphPad Software, Inc., San CHAPTER II 129 Jose, California, USA). The statistical significance was defined as P < 0.05. RESULTS Characteristics of the First Cohort of Allergic Asthmatic Patients Table 1. Characteristics of the Study Populationa Allergic Asthmatic Patientsb Healthy Controls Male Female All Male Female All No. (%) 33 (40.7) 48 (59.3) 81 (100) 36 (37.1) 61 (62.9) 97 (100) Age 33 (21-45) 36 (28-48) 35 (26-47) 35 (27-49) 37 (29-52) 35 (29-51) Smokers, %c 45.5 18.75 29.6 0 0 0 BMI, kg/m2 26.4 (23.8- 29) 26.7 (22.6- 28) 26 (23.1- 28.4) - - - Asthma Severity: Mild 2 4 6 - - - Moderate/High 31 44 75 - - - Control: Good 23 37 60 - - - Bad 10 11 21 - - - Treatment: No 1 2 3 - - - Inhaled corticosteroids 32 46 78 - - - Oral corticosteroids 5 3 8 - - - Antileukotrienes 6 19 25 - - - Omalizumab 0 1 1 - - - Continued on next page Juan José Nieto Fontarigo 130 Table 1 (Continued) FEV1 (%) 93 (74- 101) 91.8 (73- 102) 93 (74- 102) - - - FEV1/FVC (%) 74.5 (64- 83) 73.5 (65- 81) 74.2 (65- 82) - - - Lymphocytes, cells/μL 2480 (1935- 2835) 2150 (1770- 2680) 2310 (1848- 2765) d 1941.5 (1615- 2372) 1892.3 (1585- 1892) 1912.7 (1594- 2362) d Eosinophils, cells/μL 327 (154- 502)d 326 (182- 492)d 327 (175- 494)d 173 (110- 268)d 133 (97- 198) d 152 (103- 218) d Monocytes, cells/μL 501 (414- 658) 420 (306- 518)d 444 (349- 575)d 425 (350- 528) 318.8 (231-399)d 361 (271- 451)d Neutrophils, cells/μL 4458 (3202- 5617) 3851 (2814- 4859) 4045 (3003- 5232) 3286 (2645- 5685) 3399 (2812- 4472) 3395 (2776- 4809) IgE, IU/mL 355 (87- 707)d 204 (89- 680)d 241 (90- 682) d 78 (19- 195) d 22 (7-55) d 34 (10- 95) d CRP, mg/dL 0.09 (0.07- 0.42) 0.16 (0.07- 0.32) 0.15 (0.07- 0.34) 0.19 (0.1- 0.69) 0.16 (0.05- 0.39) 0.17 (0.07- 0.57) TNF, pg/mL 9.4 (6.6- 12.0) 9.5 (7.6- 12.9) 9.4 (7.2- 12.3) 8.6 (7.3- 10.4) 10.5 (7.6- 13.2) 9.7 (7.4- 12.9) Leptin, ng/mL 2.9 (1.3- 7.2)e 18.1 (11.2- 27.9)e 11.2 (3.1- 23.9) 2.9 (1.0- 8.0)e 13.0 (5.35- 26.9)e 8.1 (3.3- 20.0) Abbreviations: BMI, body mass index; CRP, C-reactive protein; FEV1, forced expiratory volume in the first second; FVC, forced vital capacity; TNF, tumor necrosis factor. aValues are expressed as median (IQR), unless otherwise specified. bWe recorded the professional activity of ~70% of patients, distributed according to the following order: students (14.8%), construction professionals (9.9%), housewives (8.6%), administrative officers (7.4%), cleaning service (6.2%), health professionals (6.2%), waiters (4.9%), educators (4.9%), farmers (2.5%), salespersons (2.5%), and textile workers (2.5%). cApart from the nonregistered (8.6%), formerly smoker (11.1%) and current smoker (29.6%) patients, they were mostly nonsmokers (50.6%). dDifferences between AAPs and HCs (Mann-Whitney, P<.05). eDifferences between male and female (Mann-Whitney, P<.05). CHAPTER II 131 The characteristics of this first cohort of patients are summarized in Table 1. In AAPs, the median forced expiratory volume in the first second (FEV1) (%) was 93 (74.5-102.2), while the FEV1/forced vital capacity (FVC) ratio (%) was 74.2 (65.2-81.9). Asthma was mainly moderate-persistent (71.6%), and patients had an allergic disease, with positive skin prick test reactions against common allergens. In addition, most patients lived in rural areas (72%), although only a small percentage of them were farmers (Table 1). As expected, a significant group of AAPs had peripheral blood eosinophilia (45% had >350/μL) and elevated total IgE (Table 1). There was a positive correlation between eosinophils and IgE, but not between FEV1 and serum IgE in AAPs (Table 2). Patients were under different treatments, were mostly nonsmokers, and had wellcontrolled asthma (Table 1). Given the well-known association between leptin and body mass index (BMI) and the assumed correlation between the development/worsening of asthma and BMI, we also studied these parameters. First, BMI in AAPs was positively correlated with leptin and C-reactive protein (CRP), but negatively associated with IgE and both FEV1% and FEV1/FVC (Table 2). Second, leptin levels were generally 4 to 6–fold higher in women, although no differences were detected between HCs and AAPs (Figure S1, Table 1). These findings underline the lack of association between BMI and asthma. In contrast, some parameters were more elevated in men, including IgE, basophil counts, and sCD26 (data not shown). The influence of age was also taken into consideration, indicating a positive correlation between BMI and TNF and a negative interdependence with IgE, FEV1%, and FEV1/FVC; no association with age was detected for sCD26 or sCD25 (Table 2). Juan José Nieto Fontarigo 234 relevant as candidate biomarkers for asthma phenotypes diagnosis or assessment of asthma severity. This is the case, for example, of IGFALS, protein AMBP, and HSPG2 in the case of AA, and CFI, or CFH for NAA. IGFALS belongs to a family of proteins previously linked to asthma pathogenesis that includes IGF1 and IGF2 [40]. IGF1 is a key factor in asthma pathogenesis, through the promotion of subepithelial fibrosis, inflammation, hyperresponsiveness, and smooth muscle cell hyperplasia in the airways [40]. Indeed, omalizumab (an anti-IgE antibody) [41], as well as oral glucocorticoids [42], decrease the levels of IGF-I. Both IGF1 and IGF2 exert their biological effects through the binding to IGF1R, but IGF2 can be also sequestrated by IGF2R/cation-independent mannose-6-phosphate receptor, a highaffinity inhibitory protein that attenuates IGF2 signalling [43]. Strikingly, this last receptor has been related to CD26/DPP4 [44, 45], a serine peptidase involved in asthma pathogenesis [46]. Therefore, there are many lines of evidence pointing to an important role of IGF family in allergic asthma. The IGF system is completed with several binding proteins (IGFBPs: 1-6) [47], a novel IGFBP3-specific receptor (IGFBP3R) [48], and IGFALS [47, 49]. Both IGFBPs and IGFALS appear to influence free-IGF concentration in the extracellular compartment, playing a role on the bioavailability of IGFs [40]. The formation of a high molecular weight complex (IGFALS-IGF1-IGFBP) prevents the extravasation of IGF-1, the IGF-1/IGFBPs proteolysis, and the renal elimination of IGF-1 [50]. Indeed, IGFALS deficiency results in a dramatic decrease in IGF-1, IGF-2, and IGFBP3 levels [50, 51]. Apart from IGF1 [40] and IGFBP3 [40], the present results show that IGFALS is elevated in AA, especially moderate-severe forms, but not in NAA. Regarding IGFBP3, this protein controls AA inflammation through IGF-dependent and IGF-independent (IGFBPR-mediated) CHAPTER IV 235 mechanisms that target the HIF/VEGF axis, TGFβ1 and TH2 cytokines production, and NF-kB activation [40]. Veraldi et al. also described a role in AA for IGFBP-3 through the promotion of subepithelial fibrosis [52]. Regarding the role of IGFALS in asthma, this remains mostly unknown, but together with IGFs and IGFBPs this protein could be an additional therapeutic target for asthma management. Other possible biomarkers for AA are protein AMBP and HSPG2. Although the first one has not been extensively studied in asthma or airway-related diseases, a study of serum proteome from patients with idiopathic pulmonary fibrosis (IPF) has shown decreased levels of AMBP in IPF patients compared to HC, and the same decrease was observed for AHSG, a protein with a similar pattern of changes as AMBP in our study [38]. Although the possible function of protein AMBP in AA is not known, this protein shares the same chromosomal region (9q32) as ORM1/AGP, a positive acute phase protein increased in AA (Table 3). Thus, it is probable that both proteins coordinate their levels and that AMBP participates in the acute inflammatory response. Indeed, AMBP and ORM1 levels, as well as other proteins augmented in AA and R in our study (e.g., AHSG or CD5L), have been found increased in BALF of asthmatic individuals 24 h after segmental allergen challenge [53], highlighting the possible role of these set of proteins in AA. On the other hand, together with hyaluronan (HA) or vesicant (VCAN), HSPG2/perlecan is an extracellular matrix molecule which is deposited in the lamina reticularis and generates subepithelial fibrosis in the airways [54]. Basement membrane thickening has been reported in asthma [55-58] and even allergic rhinitis [58, 59]. Moreover, HSPG2 is an upstream regulator of genes (ACAN, COL10A1, and FGFR3) containing asthma-associated differentially methylated regions [60]. There is a negative correlation between the Juan José Nieto Fontarigo 236 levels of HSPG2 and airway hyperresponsiveness (PC20) [61], and this protein has been linked to fibrosis as well. Indeed, mature fibrocytes [62] constitutively produce VCAN, HA, COL3/5/6, fibronectin, and HSPG2 [63, 64] and contribute to the subepithelial fibrosis in asthma [63]. Aligned with these results and our own data showing higher levels of HSPG2 in serum samples from AA and R patients, fibrocytes from asthmatic patients exposed to TH2- (IL-4, IL-13) but not TH17 (IL-17A) cytokines show an enhanced expression of HSPG2 and a profibrotic phenotype (i.e., elevated expression of HA, COL315, VCAN and HSPG2) [65]. Changes in HSPG2 deposition could have mechanistic effects, but also modulate the bioability of growth factors (e.g., bFGF) or cytokines (e.g., IL-4, TGF-β, or GM-CSF). Taken together, these results could explain the increase of HSPG2 and protein AMBP in our group of MSAA and R patients and their potential as atopic disease biomarkers. Asthma and especially its NAA phenotype share certain characteristics with autoimmune disorders, like their prevalence in female the presence of autoantibodies in higher frequency than HC [66-68]. It is well known that the complement system plays an important role in autoimmune diseases [69], but also appear to have a proinflammatory role in asthma [70-72]. However, the complement factors involved remain unclear. According to the initial stimuli, three pathways (classical, alternative, and lectin) have been described for complement activation. Our results support that complement factors I and H, two regulatory proteins that control the excessive activation of the alternative complement pathway [73, 74], are upregulated in NAA. CFI is a serine protease that favours the degradation of C4b, diminishes the levels of C3-convertase (C4bC2a) and prevents inflammation arising from complement activation [75]. Complement factor H, for its part, is a cofactor for CFI [73, 76] and it is also known as adrenomedullin binding protein (AMBP-1) [77, 78]. CHAPTER IV 237 Adrenomedullin is an anti-inflammatory peptide that suppresses TH2 inflammation and maintains tissue integrity in an OVA-induced model of asthma [79]. Moreover, Weiszhár et al. have found augmented levels of CFH in asthmatic sputum and a correlation with severity and the loss of lung function [80]. The increase of CFI and CFH in our group of NAA patients could be related to a mechanism to evade the immune response, as it happens with some pathogens [81-83], which could also explain the higher severity of NAA. Additionally, the levels of the serine protease MASP1 are also increased in NAA. MASP1 participate in the lectin pathway of complement activation, but this protease has also substrates that belong to the coagulation cascade [84]; we have found some of them altered in asthma as well, such as kininogen, FXIII, or F2. Moreover, another substrate of MASP1 is the protease activation receptor 4 (PAR4) in endothelial cells, whose activation leads to the production of IL-6 and IL-8, the last one a chemotactic molecule for neutrophils [84]. This is relevant, as neutrophils have been related to some NAA endotypes [85] and higher disease severity [86, 87]. Besides, C1r and C1s proteins (classical complement pathway) are also modified in our group of asthma patients. Therefore, our results point out that all the complement activation pathways (classical, alternative, and lectin) appear to be involved in asthma, especially in the NAA phenotype. Like other studies, the present work has also some limitations. First, not all the proteins were detected in all the groups since it is known that in LC-MS/MS assays is necessary to perform more than 3 technical replicates in order to detect all proteins in a sample (completeness of analysis issue) [88]. A second problem is related to the "pooled sample" analysed with the isobaric label 121. This sample has been introduced in all analytical series to allow the normalization of the signals and the adjustment of the interserial variability. However, the use of this type of reference samples makes difficult to Juan José Nieto Fontarigo 238 detect low abundance proteins, which in addition makes the normalization process difficult. Third, another issue is the whole number of proteins detected, especially low abundance species, despite the use of lipoprotein-depletion, CPLLs-based enrichment, and reverse phase LC. Therefore, an additional step of peptidesfractionation using strong cation exchange (SCX) chromatography before LC-MS/MS analysis would be of benefit. Finally, some of our results are still preliminary, especially those referring to the proteins detected with differential abundance by LS-MS/MS which have not been validated by ELISA yet. In conclusion, a shotgun/bottom-up/non-targeted methodology has been developed for the quantitative analysis of the proteome of medium-low abundance in serum samples from patients with rhinitis and various asthmatic phenotypes. This protocol is based on the elimination of lipoproteins by the LRA resin, protein enrichment of medium and low abundance by CPLLs application, labelling with iTRAQ 8plex reagents, and analysis by LC-MS/MS. 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J Biochem Biophys Methods. 2004;60(3):265-80. 33. Zhu MZ, Li N, Wang YT, Liu N, Guo MQ, Sun BQ, et al. Acid/Salt/pH Gradient Improved Resolution and Sensitivity in Proteomics Study Using 2D SCX-RP LC-MS. J Proteome Res. 2017;16(9):3470-5. 34. Durr E, Yu J, Krasinska KM, Carver LA, Yates JR, Testa JE, et al. Direct proteomic mapping of the lung microvascular endothelial cell surface in vivo and in cell culture. Nat Biotechnol. 2004;22(8):985-92. 35. Terracciano R, Pelaia G, Preianò M, Savino R. Asthma and COPD proteomics: current approaches and future directions. Proteomics Clin Appl. 2015;9(1-2):203-20. 36. Izbicka E, Streeper RT, Michalek JE, Louden CL, Diaz A 3rd, Campos DR. Plasma biomarkers distinguish non-small cell lung cancer from asthma and differ in men and women. Cancer Genomics Proteomics. 2012;9(1):27-35. 37. Tan HT, Ling LH, Dolor-Torres MC, Yip JW, Richards AM, Chung MC. Proteomics discovery of biomarkers for mitral regurgitation caused by mitral valve prolapse. J Proteomics. 2013;94:337-45. CHAPTER IV 243 38. Niu R, Liu Y, Zhang Y, Zhang Y, Wang H, Wang Y, et al. iTRAQ-Based Proteomics Reveals Novel Biomarkers for Idiopathic Pulmonary Fibrosis. PLoS One. 2017;12(1):e0170741. 39. O'Neil SE, Sitkauskiene B, Babusyte A, Krisiukeniene A, Stravinskaite-Bieksiene K, Sakalauskas R, et al. Network analysis of quantitative proteomics on asthmatic bronchi: effects of inhaled glucocorticoid treatment. Respir Res. 2011;12:124. 40. Lee H, Kim SR, Oh Y, Cho SH, Schleimer RP, Lee YC. Targeting insulin-like growth factor-I and insulin-like growth factor-binding protein-3 signaling pathways. A novel therapeutic approach for asthma. Am J Respir Cell Mol Biol. 2014;50(4):667-77. 41. Bulut I, Ozseker ZF, Coskun A, Serteser M, Unsal I. Pregnancyassociated plasma protein-A (PAPP-A) levels in patients with severe allergic asthma are reduced by omalizumab. J Asthma. 2017;55(10):1116-21. 42. Frystyk J, Schou AJ, Heuck C, Vorum H, Lyngholm M, Flyvbjerg A, et al. Prednisolone reduces the ability of serum to activate the IGF1 receptor in vitro without affecting circulating total or free IGF1. Eur J Endocrinol. 2012;168(1):1-8. 43. Brown J, Jones EY, Forbes BE. Interactions of IGF-II with the IGF2R/cation-independent mannose-6-phosphate receptor mechanism and biological outcomes. Vitam Horm. 2009;80:699-719. 44. Ikushima H, Munakata Y, Ishii T, Iwata S, Terashima M, Tanaka H, et al. Internalization of CD26 by mannose 6- phosphate/insulin-like growth factor II receptor contributes to T cell activation. Proc Natl Acad Sci U S A. 2000;97(15):8439-44. 45. Ikushima H, Munakata Y, Iwata S, Ohnuma K, Kobayashi S, Dang NH, et al. Soluble CD26/dipeptidyl peptidase IV enhances transendothelial migration via its interaction with mannose 6- Juan José Nieto Fontarigo 250 Enrichment of low abundance proteins: ProteominerTM. To enrich samples in low abundance proteins, ProteoMiner™ Protein Enrichment Large-Capacity Kit (Bio-Rad, cat163-3007) was used following commercial guidelines. In brief, 1 mL from each serum sample was loaded in each column and subsequently incubated under stirring conditions (2 h, RT). After incubation, the samples were washed 4 times and then eluted by using a buffer provided by the kit. All centrifugations were performed at 1000 xg, 1 min, RT. Three fractions were collected and mixed in a single sample. Then, in order to eliminate contaminants such as the salts of the Proteominer elution buffer, the 2-D Cleanup Kit (GE Healthcare, Cat No. 80-6484-51) was used also following commercial guidelines. Finally, the pellet obtained was diluted into 30 μL of 0.5M TEAB 6M urea for ulterior analysis. Protein quantification Two methodologies were used according to the manufacturer's protocol. The first one, PierceTM BCA Protein Assay Kit (Thermo Fisher, # 23225), was used for protein quantification after the delipidation process. A calibration line was generated using different concentrations of bovine serum albumin (BSA) in phosphate buffer (10 mM, pH 7.0): 0-2 mg/mL. The test samples were also diluted in phosphate buffer (1:60 dilution). In a 96-well plate, 25 μL of the blank (PBS), samples and standards were added. Each condition was analysed at least in duplicate. Subsequently, 200 μL of working reagent (50 A: 1 B) was added and incubated at 37 °C, 20 min. Finally, the reading was made at 550 nm in a plate reader (model 680, Bio-Rad). The quantification after Clean-up required using the CB-X kit (786-12X, G-Biosciences). Firstly, to precipitate proteins from CHAPTER IV 251 samples, 1 mL of previously cooled (-20 ° C) CB-X ™ reagent was added to 50 µL of each sample (diluted 1:10 in TEAB buffer) and mixed by vortexing. The samples were then centrifuged at 16,000 xg for 5 min, the supernatant was removed, and 50 μL of CB-X ™ I and 50 μL CB-X ™ II solubilization buffers were sequentially added. The proteins were dissolved by vortex, and 1 mL/sample of CB-X ™ test dye was added. After vortexing and incubation for 5 min at RT, the samples were transferred to 96-well plates and the absorbance was read at 595 nm on a microplate reader (Labsystems Multiskan MS). A standard line with BSA (0.2-1 mg/mL) diluted in 0.5M TEAB buffer containing 6M urea was used to determine the protein concentration. Reduction, alkylation, and trypsinization Fifty μg of protein from each sample in 20 μL of 0.5M TEAB 6M urea were reduced and alkylated. For this purpose, 2 μL of reducing agent (TCEP) were added to each tube, followed by 1 h incubation at RT. Next, the samples were alkylated by adding 1 μL/sample of MMTS, followed by 10 min incubation at RT. Subsequently, 123 μL of 1M TEAB were added to reduce the urea concentration, and trypsinization was performed (1 μg/µL trypsin; 4326682, Sciex) at 37 ° C overnight. To stop the reaction (pH < 6.0), 4 μL of acetic acid was added. Finally, all samples were lyophilized. iTRAQ labelling The iTRAQ® Reagent-8PLEX Multiplex Kit (Sigma-Aldrich) was used according to the manufacturer's protocol. First of all, the samples were dissolved in 30 μL of 0.5M TEAB. Half of the contents of each vial (10 μL) were diluted in 25 μL of isopropanol, and then added to each peptide samples with the following labels: MSAA, 113; IMAA, 114; R, 115; MSNAA, 116; IMNAA, 117; HC, 119; PS, 121. PS sample is a pool of all the serum samples used to normalize the data Juan José Nieto Fontarigo 252 between the different MS analytical series. After 2h incubation, the seven labelled peptide samples were collected in a single tube and lyophilized. This procedure was performed twice, one for each biological replicate (pool A and pool B). nanoLC/MS-MS identification and quantification of peptides The samples were analysed in the Structural, Proteomic and Genomic Determination Service, Cacti Mass Spectrometry Unit, University of Vigo. Firstly, the peptide samples were reconstituted in solution A (0.1% formic acid (FA) in water) and desalted by Zip-Tips C18 (Millipore). Secondly, peptides were dispensed to nano-reverse phase EASY-Spray Columns (PepMap® RSLC, C18, 2µm, 100 Å, 75µm x 500mm, Thermo Fisher Scientific) mounted in the Proxeon EASY- nLC 1000 UHPLC (Thermo Fisher Scientific), and were eluted with a gradient of solution B (ACN) of 5-30% (240 min), 30%-90% (10min), and 90%-5% (17min). The nanoLC system is coupled online to an LTQ-Orbitrap ELITE (Thermo Fisher Fisher) used in a data dependent and positive ion mode. A full MS scan was carried out from 380−1600 m/z with a resolution at 12000. HCD-fragmentation was used and the MS/MS scan was accomplished with top 15, at 28% normalized collision energy, with a resolution at 30000, a dynamic exclusion time at 30 s, a minimum signal required at 1000, and an isolation width at 1.50 Da. Three technical replicates were performed from each biological replicate. MS data analysis Proteome Discoverer (version 2.1.1.21) was used for protein identification and iTRAQ quantification. HCD spectra were analysed using Sequest HT with Percolator validation. Spectra were searched against the latest UniProtKB Release and common contaminant sequences (e.g., trypsin, or keratins). The peptide mass tolerance was CHAPTER IV 253 10 ppm and the fragment mass tolerance 0.020 Da. As static modifications, the iTRAQ 8-plex N-terminus, and carbamidomethylation of cysteine were specified, and as variable modifications, the oxidation of methionine, the iTRAQ 8-plex of tyrosine and lysine, the carbamylation of lysine, and the N-terminus acetylation. The intensities acquired in MS/MS were globally normalized on protein median. Then, all reporter intensities were normalized by the reporter intensity of the pooled sample (PS, 121). The abundance of each protein was calculated as an average abundance of all its detected peptides. A 1.3 fold change (downregulation, < 0.77; up-regulation, ≥1.3) in iTRAQ ratios, as well as a p-value less than 0.05, was used to identify differentially expressed proteins between the different groups of study. Statistical and bioinformatic analysis of the data Statistical data analyses were carried out using GraphPad Prism version 6.00 for Windows (GraphPad Software, La Jolla California USA, www.graphpad.com). Quantitative data comparisons between the different sample groups were performed by Kruskal–Wallis oneway analysis of variance followed by Dunn's multiple comparison tests. The receiver operating characteristic (ROC) analysis was also performed with GraphPad Prism. A p < 0.05 was considered of statistical significance. Bioinformatic analysis: GO annotation, GO terms overrepresentation test, and Reactome pathway overrepresentation analyses against the plasma proteome database (Version 2015-02-02) (www.plasmaproteomedatabase.org/) were performed in PANTHER Classification System (PANTHER version 13.1. Released 2018-02-03). A prospective study of all the potential physical or functional protein-protein interactions was also performed by means of the Search Tool for the Retrieval of Interacting Genes (STRING) (Version: 11.0, www.string-db.org) Juan José Nieto Fontarigo 254 SUPPLEMENTARY TABLES Supplementary Table 1. Characteristics of the subjects from pool A. MSAA IMAA MSNAA IMNAA R HC N 25 26 22 24 22 16 Age (mean (range)) 39 (21- 64) 37 (20- 64) 53 (24- 68) 53 (29- 72) 31 (18- 46) 45 (22- 58) Sex (M/F) 11/14 15/11 6/16 2/22 12/10 5/11 Disease control: Yes 18 26 13 22 22 - No 7 0 9 2 0 - Baseline treatment: ICS-LABA 24 16 18 17 0 - ICS 0 7 1 0 0 - OCS 0 0 0 0 0 - Antileukotrienes 14 8 10 5 3 - Anticholinergic 5 3 13 2 0 - Roflumilast 0 0 0 0 0 - Prednisone 0 0 2 0 0 - FEV1 (%) 97.0 (85.5- 111.5)$ 102.5 (94.5- 110.5) 70.6 (60.0- 88.8)#& 112.0 (98.0- 120.5) 109.5 (99.5- 121.5) - FEV1/FVC (%) 76.5 (70.7- 79.6)# 79.6 (72.6- 82.7) 67.6 (58.1- 77.1)# 76.6 (73.7- 80.6)# 84.6 (79.1- 88.3) - Neutrophils (103 cells/μL) 3.14 (2.28- 4.19) 3.94 (3.21- 4.45) 3.61 (2.98- 4.77) 3.16 (2.49- 3.53) 3.73 (2.86- 4.90) 3.68 (2.25- 4.34) Lymphocytes (103cells/μL) 1.89 (1.37- 2.12) 1.98 (1.74- 2.21) 2.07 (1.64- 2.50) 1.87 (1.49- 2.16) 2.20 (1.95- 2.71) 2.04 (1.48- 2.45) Continued on next page CHAPTER IV 255 Supplementary Table 1 (Continued) Monocytes (103 cells/μL) 0.33 (0.29- 0.42) 0.41 (0.31- 0.46) 0.37 (0.32- 0.50) 0.32 (0.29- 0.43) 0.40 (0.34- 0.50) 0.42 (0.33- 0.62) Eosinophils (103 cells/μL) 0.36 (0.22- 0.55)* 0.24 (0.16- 0.34) 0.31 (0.18- 0.46) 0.25 (0.13- 0.37) 0.22 (0.13- 0.38) 0.20 (0.09- 0.30) Basophils (103 cells/μL) 0.04 (0.03- 0.05) 0.04 (0.03- 0.05) 0.03 (0.02- 0.05) 0.03 (0.02- 0.04) 0.03 (0.02- 0.06) 0.03 (0.02- 0.05) ESR (1h; mm) 10.0 (6.5- 17.5) 5.5 (2.0- 17.2) 15.0 (9.7- 25.5)*# 12.0 (7.2- 20.5) 4.5 (2.0- 14.8) 10.0 (7.0- 11.0) IgE (IU/mL) 122.0 (62.5- 316.0)*$ 174 (79- 241)*$ 38 (10- 96) 17 (5- 32) 76 (24- 283) 11 (3- 45) IgG (mg/dL) 1100 (951- 1260) 1075 (952- 1195) 1045 (951- 1313) 1030 (794- 1140) 1005 (943- 1288) 980 (842- 1090) IgG1 (mg/dL) 630 (548- 807) 681 (594- 732) 658 (495- 761) 550 (447- 605)# 673 (546- 775) - IgG2 (mg/dL) 374 (285- 448) 365 (276- 469) 293 (213- 459) 338 (246- 426) 337 (268- 405) - IgG3 (mg/dL) 32 (22- 45) 32 (21- 48) 42 (22- 55) 33 (28- 57) 39 (29- 59) - IgG4 (mg/dL) 50 (27- 87) 47 (23- 96) 65 (39- 125) 28 (10- 60) 23 (14- 51) - IgA (mg/dL) 223 (159- 270) 226 (176- 295) 204 (147- 262) 209 (162- 251) 166 (100- 262) 250 (121- 333) IgM (mg/dL) 113 (76- 166) 97 (64- 153) 115 (93- 172) 101 (70- 133) 109 (67- 171) 88 (71- 118) HC, healthy controls; IMAA, intermittent-mild allergic asthmatics; IMNAA, intermittentmild non-allergic asthmatics;MSAA, moderate-severe allergic asthmatics; MSNAA, moderate-severe non-allergic asthmatics; R, rhinitis patients. Data are presented as median value (IQR1-3), unless otherwise expressed. Statistical significance is shown: *Disease vs HC; #Asthma vs R; $AA vs NAA; &Moderatesevere vs Intermittent-mild asthma. Kruskal-Wallys test followed by Dunn´s multiple comparison test. p < 0.05 Juan José Nieto Fontarigo 256 Supplementary Table 2. Characteristics of the subjects from pool B. MSAA IMAA MSNAA IMNAA R HC N 24 27 21 23 21 16 Age (mean (range)) 39 (18- 68) 36 (21- 66) 54 (28- 67) 51 (34- 72) 39 (24- 55) 41 (27- 61) Sex (M/F) 12/12 10/17 7/14 6/17 8/13 9/7 Disease control: Yes 12 27 17 23 21 - No 12 0 4 0 0 - Baseline treatment: ICS-LABA 23 17 21 18 18 - ICS 1 8 0 3 0 - OCS 1 0 0 0 0 - Antileukotrienes 11 10 10 4 7 - Anticholinergic 8 0 12 0 0 - Roflumilast 0 0 1 0 0 - Prednisone 0 0 3 0 0 - FEV1 (%) 89.5 (65.7- 99.2)# 100.0 (92.0- 108.0) 77.0 (66.0- 96.0)#& 105.0 (97.0- 113.0) 102.5 (96.2- 115.0) - FEV1/FVC (%) 69.8 (55.9- 78.6)# 78.9 (72.3- 80.7) 67.2 (61.0- 76.9)# 77.0 (72.5- 80.1) 83.2 (78.1- 86.1) - Neutrophils (103 cells/μL) 3.90 (2.93- 4.61) 3.55 (3.14- 4.06) 3.56 (3.31- 4.31) 3.78 (3.19- 4.53) 3.54 (2.97- 3.86) 3.02 (2.40- 3.69) Lymphocytes (103cells/μL) 1.94 (1.81- 2.81) 2.02 (1.59- 2.29) 1.83 (1.51- 2.67) 1.96 (1.67- 2.28) 2.13 (1.65- 2.48) 1.95 (1.53- 2.57) Monocytes (103 cells/μL) 0.31 (0.30- 0.47) 0.31 (0.40- 0.50) 0.43 (0.32- 0.52) 0.37 (0.30- 0.51) 0.34 (0.28- 0.46) 0.39 (0.32- 0.47) Continued on next page CHAPTER IV 257 Supplementary Table 2 (Continued) Eosinophils (103 cells/μL) 0.35 (0.22- 0.50)* 0.29 (0.20- 0.45)* 0.28 (0.15- 0.42)* 0.24 (0.17- 0.35) 0.22 (0.14- 0.28) 0.12 (0.10- 0.22) Basophils (103 cells/μL) 0.04 (0.03- 0.06) 0.04 (0.03- 0.05) 0.04 (0.02- 0.06) 0.03 (0.02- 0.05) 0.04 (0.02- 0.05) 0.04 (0.03- 0.05) ESR (1h; mm) 7.0 (4.0- 13.7) 7.0 (4.0- 12.0) 9.0 (4.0- 20.0) 11.0 (8.0- 20.0)* 11.0 (2.5- 15.5) 3.0 (2.0- 8.5) IgE (IU/mL) 209.0 (72.5- 523.3)*$ 122 (50- 304)$ 44 (16- 104) 25 (11- 43) 59 (27- 99) 15 (12- 144) IgG (mg/dL) 1030 (898- 1100) 1100 (923- 1250) 1065 (915- 1203) 1010 (880- 1175) 1045 (879- 1180) 1080 (904- 1290) IgG1 (mg/dL) 644 (555- 725) 651 (538- 768) 607 (474- 733) 549 (455- 654) 603 (521- 692) - IgG2 (mg/dL) 333 (257- 383) 331 (279- 409) 345 (318- 436) 347 (273- 393) 312 (258- 426) - IgG3 (mg/dL) 30 (20- 43) 39 (31- 56) 36 (27- 64) 36 (32- 62) 31 (26- 38) - IgG4 (mg/dL) 52 (38- 86) 47 (23- 68) 37 (21- 64) 32 (17- 67) 41 (29- 54) - IgA (mg/dL) 200 (170- 279) 254 (172- 315) 238 (170- 296) 197 (147- 270) 214 (135- 275) 332 (148- 375) IgM (mg/dL) 93 (65- 143) 106 (85- 133) 111 (72- 149) 123 (79- 154) 112 (78- 160) 102 (86- 103) HC, healthy controls; IMAA, intermittent-mild allergic asthmatics; IMNAA, intermittentmild non-allergic asthmatics;MSAA, moderate-severe allergic asthmatics; MSNAA, moderate-severe non-allergic asthmatics; R, rhinitis patients. Data are presented as median value (IQR1-3), unless otherwise expressed. Statistical significance is shown: *Disease vs HC; #Asthma vs R; $AA vs NAA; &Moderatesevere vs Intermittent-mild asthma. Kruskal-Wallys test followed by Dunn´s multiple comparison test. p < 0.05 Juan José Nieto Fontarigo 258 SUPPLEMENTARY FIGURES Supplementary Figure 1. Treatment with LRA resin reduces serum lipoprotein levels. A volume of 300 μL of serum was treated with different concentrations of LRA resin (0-100 mg / mL) overnight at 4 ° C in rotation. An SDS-PAGE (15% T separating gel) is shown in which 30 μg of protein belonging to the fraction not retained by the resin (channels 2-7) has been loaded. Channel 1 corresponds to molecular weight markers, and channel 9 to the retained fraction (R). Juan José Nieto Fontarigo 266 like mCD14, this glycoprotein presents a membrane and a soluble (sCD26) isoform. Moreover, even though CD26 does not anchor to the plasma membrane through a glycophosphatidylinositol linkage as CD14 does, this molecule presents an extremely short cytoplasmic region of 6 residues that requires the participation of other molecules (e.g., CARMA1) to downstream signal transduction [252]. Likewise, CD26 expression is rather confined to CD4+ T lymphocytes in a manner comparable to CD14 and monocytes. Finally, CD26/DPP4 belongs to a subfamily of serine proteases (the S9B) with several members showing an association with asthma: CD26/DPP4 itself and DPP10. Based on all these points, Chapters II and III were aimed to study the expression pattern of CD26 in different lymphocyte subpopulations and their implications in both AA and NAA, as well as disease severity. Because of the complexity of this issue, we carried out a comprehensive review (see appendix I) aimed to provide a structured overview of the numerous functions of CD26 and its implications in asthma pathogenesis and progression. Up until that time, there was only one review paper specifically covering the relationship between CD26, T cells, and asthma [412]. CD26 is a prolyl oligopeptidase that belongs to the serine protease family (S9B) [243]. CD26 is widely distributed over several cell types and tissues. However, expression of CD26 is especially associated with immune cells, such as granulocytes, monocytes, B cells, and T lymphocytes (particularly CD4+ T cells) [251]. Within CD4+ T lymphocytes, its expression is higher in Teff cells compared to Treg cells [258]. In addition, Bengsch et al. used flow cytometry data and FACS sorting to shown that the expression of CD26 amongst Teff cells is quite variable, according to the following order: TH17>> TH1> TH2 [259, 413, 414]. These results have been confirmed in vitro in Chapter II, where CD4+CD25- Teff cells were activated and differentiated towards a TH1-like (IL-12), TH2-like (IL-4), and TH17- GENERAL DISCUSSION 267 like (IL-1β, IL-6, and IL-23) phenotypes. Our results show the same differential expression for CD26 in Teff cells (TH17>> TH1> TH2) that Bengsch et al. described previously. As above commented, CD26 can also be found in the extracellular space (e.g., serum/plasma, BALF, CSF) as sCD26 [286]. This soluble version of CD26 is released by CD26+ cells through enzymatic-shedding [291] or production of CD26+ vesicles (http://www.exocarta.com). It has been shown that visceral fat release sCD26 as an adipokine [415], but CD4+ T cells remain as the most likely source [286, 293, 294]. Indeed, our in vitro assays (Chapter II) reveal a strong positive correlation between the expression of CD26 (mean fluorescent intensity/MFI) on different TH lymphocyte subsets (TH17>>TH1>TH2>Treg) and the soluble DPP4 activity (a bona fide indicator of sCD26 levels) in culture supernatants. Therefore, if this was happening in vitro, it was expected that serum sCD26 levels were influenced by the number of CD4+ T cells or mirror the predominant subpopulation of CD4+ T cells (e.g., TH1, TH2, TH17) in the different asthma phenotypes/endotypes. In other words, we were expecting a coordinated and variable elevation of both CD26 and sCD26 in asthma, higher or lower depending on the disease phenotype and the prevailing TH subset. With this in mind, we undertook a systematic analysis of the expression of CD26 on TH lymphocytes from AA, NAA, rhinitis, and healthy individuals, as well as an evaluation of sCD26 levels in serum samples (Chapters II and III). Firstly, as Lun and coworkers [246] previously showed in AA (and as expected from an activation marker) [252, 416, 417], there was an increase in the expression of CD26 on CD4+ lymphocytes from AA an NAA patients (Chapters II and III). However, inconsistently with the higher sCD26 levels detected by Lun et al. in AA [246], in the first study (Chapter II) it was shown a diminished concentration of sCD26 in serum samples from two Juan José Nieto Fontarigo 268 cohorts of AA patients compared to healthy subjects. Moreover, the same happened for sCD25 (Chapter II), another soluble isoform of an activation marker: CD25/IL-2Rα [220-224]. A similar downmodulation of sCD26 was found in NAA patients (Chapter III) and eosinophilic pneumonia [418], whereas other authors did not detect any difference in sCD26 levels in children with asthma [303]. The different results reported by Lun and coworkers [246] regarding sCD26 levels in AA as compared with our findings in Chapter II may have several explanations. On the one hand, the different male/female proportions between AA patients and controls in the paper of Samantha Lun, as sCD26 concentration is higher in males. On the other hand, the more active disease status of patients in these studies compared to our cohort of AA patients, which were in a stable phase. Our in vitro experiments (Chapter II) support that CD4+CD25- Teff cells primarily secrete CD26 upon TCR triggering. In the same line, Teff cells up-regulate and release CD25 after being activated [419]. Therefore, the small reduction detected for both soluble markers (sCD26 and sCD25) in serum samples from AA patients may be indicative of the expansion of a CD25-/lowCD26-/low TH subpopulation in this disease. Indeed, in Chapter II we describe, for AA patients, a significant increase in the percentage of a small population of CD4+CD25-/lowCD26-/lowCD127-/low TH cells; we have called this subset “triple low” or Tlow cells. These results have been confirmed in Chapter III, showing that CD26-/low TH cells belong to a group of CD4+ T lymphocytes that have lost the expression of several markers: CD27, CD28, CCR7, and CD127. This fact highlights the advanced differentiation stage (TEM or TEMRA) of this subset. Thus, in line with other works [262], the number of CD26 molecules on TH cells allows describing lymphocytes with a TN (CD26int; CD45RA+CCR7+CD28+), a TCM (CD26high; CD45RA-CCR7+CD28+), or a highly differentiated phenotype (CD26-/low; CD45RA+/-CCR7- GENERAL DISCUSSION 269 CD28-): i.e., TEM or TEMRA. Perhaps some of these cells stop recirculating between blood/lymphatic system and non-lymphoid tissues and enter the lung tissues to become tissue-resident memory T cells [420, 421]. Research in asthma is mostly focused on CD4+ T cells and the AA phenotype. However, CD4- lymphocytes (i.e., B cells, CD8+ T cells, NKT, γδ-T lymphocytes, and NK cells) could have an active role in asthma pathogenesis and be relevant for asthma immunephenotyping. Along with this line of reasoning, the work shown in Chapter III has focused on the possibility that CD4- subpopulations may be altered amongst patients with rhinitis or different asthma phenotypes (AA and NAA) or severities. In this way, that study draws a parallel between CD4+ T cells in AA and CD4- lymphocytes in NAA, as it was also found an expansion of CD26-/low subpopulations in CD4- lymphocytes from NAA patients that explains why serum sCD26 levels are also reduced in this phenotype. Moreover, in Chapter III it was also shown that this expansion in NAA (compared to AA) can be mostly ascribed to CD26-CD4- γδ-T lymphocytes. Most of circulating γδ-T cells are V𝛿2/Vγ9+ cells [119], which display a similar distribution of naïve-memory populations as CD4+ αβ T cells: TN (CD45RA+CD27+), TCM (CD45RA-CD27+), TEM (CD45RA-CD27-), and TEMRA (CD45RA+CD27-) [122, 135]. Therefore, these findings are compatible with the description in Chapter III of CD26- (TEM/TEMRA), CD26int (TN), and CD26high (TCM) γδ-T subsets. Furthermore, γδ-T cells are the major producers of early IL-17 [134]. Therefore, the increase of a population of CD26- γδ-T lymphocytes with a TEM/TEMRA phenotype in NAA (Chapter III) with preferential production of TH17 or TH1 cytokines [422] might explain the inverse relationship between γδ-T cells and B cells (Chapter III) and the enhanced airway inflammation in NAA [309]. The number of peripheral blood γδ-T cells was previously found decreased in AA Juan José Nieto Fontarigo 270 [119, 133, 423], whereas no changes or even an increase was found in BALF or bronchial biopsies from AA patients [142, 143]. We did not measure the number of γδ-T cells in healthy subjects, but we found in AA a slightly lower percentage (2.9%) than the one previously described in the literature for healthy subjects (4.1%) [119]. In any case, more studies are needed to validate these findings because, to our knowledge, this is the first work addressing the levels of CD26 in γδ-T cells in patients with NAA. To summarize, data from the studies shown in Chapter II and III provide evidence that both asthma phenotypes share common immunopathological mechanisms, with expansion of CD26-/low subsets in AA (CD4+ Tlow) and NAA (CD4- T cells; γδ-T lymphocytes) and down-modulation of additional surface molecules (CD27, CD28, IL- 7Rα/CD127, CCR7) to produce differentiated effector subsets and extracellular sCD26 reduction. Decline in sCD26 and CD26 expression in different lymphocyte populations must be considered in the light of different findings such as the reduction of caveolin-1 (a CD26 ligand) in monocytes and bronchial epithelial cells from asthmatics [424], or the role of CD26 controlling the bioavailability of soluble factors such as cytokines (e.g., IL-3, GM-CSF) [425] and chemokines (e.g., eotaxin 1/CCL11, RANTES/CCL5, MDC/CCL22) [274, 286]. Thus, the cleavage by CD26/DPP4 of chemokines that are potent chemoattractant for eosinophils and TH cells such as RANTES [282] and eotaxin [275, 277, 278] plays a key role in asthma pathogenesis. For example, the treatment with CD26 inhibitors or the use of CD26-/- animals results in higher levels of eosinophils, higher infiltration of these cells into the airways, and higher disease severity [275, 281]. In the same way, CD26 mediated cleavage of SDF- 1α/CXCL12 [426] or IFN-γ induced chemokines (CXCL9-11) [279, 427, 428] reduce the chemotaxis of TH1 cells towards the epithelial barrier. Therefore, CD26 forms part of a homeostatic mechanism GENERAL DISCUSSION 271 aimed to the down-modulation of airways inflammation. Thus, the immunomodulatory potential of CD26/DPP4 should be considered in light of the clinical usage of CD26 inhibitors (gliptins) (see appendix I). Another area of attention in Chapter III was the CD126/IL-6Rα molecule. Together with gp130, CD126 composes the receptor of IL- 6, a molecule with a key role in the differentiation of TN lymphocytes towards a TH17 (i.e., CD26high) phenotype [176]. IL-6 signalling is also essential for the generation of functionally active memory CD4+ T cells [429], while CD126 expression on CD8+ T cells defines diverse naïve-memory differentiation stages in these cells [152], in the same way that CD26 [261]. Indeed, we report a highly positive correlation between the levels of these two markers on circulating lymphocytes, but no differences in CD126 expression between the different groups of patients (healthy controls, rhinitis, AA, NAA). As well, this paper describes that CD4- lymphocytes can be segregated in different subpopulations based on the expression of CD126. Therefore, this molecule could be useful for naïve-memory characterization as well. Moreover, CD126-CD4- lymphocytes (augmented in NAA vs. AA) downmodulate the levels of CCR7, CD28, and CD27, but retain a high abundance of CD45RA molecules, highlighting their advanced differentiation stage (TEMRA-like). As CD26, CD126 can be released from the membrane of CD126+ cells as sIL-6Rα. This soluble receptor retains the capacity to bind IL-6, leading to the activation of CD126- gp130+ cells. This process is known as trans-signalling [179, 180], and might be important for asthma through the maintenance of TH17 cells or the inhibition of T cell apoptosis [430]. For example, it has been described that CD126 is down-modulated upon inflammation on CD4+ T cells, but these cells retain the IL-6 response capacity through transsignalling events [431]. Indeed, the release of sIL6Rα has been Juan José Nieto Fontarigo 272 described in asthma, and sIL-6Rα levels have been directly associated with IgE levels. Furthermore, sIL-6Rα in serum is negatively correlated with lung function [432]. Therefore, the down-modulation of the number of CD126 molecules on monocytes, neutrophils, and CD4+ cells from moderate-severe patients reported in Chapter III highlights the potential role of IL-6 trans-signalling in asthma severity. The effector function of human TH lymphocytes is counteracted by the immunosuppressive branch of this subset, called Treg cells [214]. Therefore, a defect in their biological function or a reduction in their number could result in higher inflammation levels in asthma. Although some authors have described a reduction of the frequency of Treg cells in asthmatics, in Chapter II and III we fail to detect such a numerical alteration. Nevertheless, women did show an increased Teff/Treg ratio compared to men (Chapter II), and this could be behind the greater susceptibility of this gender to adult asthma. Our results also suggest an impaired function of Treg cells in asthma (Chapter III). Thus, it appears that Treg lymphocytes from asthmatic patients display higher levels of CD26 than those from healthy subjects. Moreover, the percentage of CD26+ Treg cells was higher in moderate-severe patients compare to intermittent-mild nonallergic asthmatics. Why are CD26 levels so important for Treg function? CD26 is a glycoprotein that anchors ADA to the cellsurface, and ADA is an ecto-enzyme involved in the catabolism of adenosine [264]. Moreover, CD39 is another ecto-enzyme expressed by CD26- Treg lymphocytes involved in adenosine production [258, 433]. Therefore, a CD26high phenotype in Tregs from asthmatics could cause higher asthma severity through a decreased local concentration of adenosine, a purine nucleoside with immunomodulatory functions [434]. On the other hand, the percentage of CD127+ Treg cells was increased in our asthmatic cohort compared to healthy and rhinitis, a GENERAL DISCUSSION 273 parameter negatively correlated with the suppressive capacity of these cells according to others [435]. Therefore, future studies including the assessment of Treg function in NAA and AA will be necessary. 3. SEARCHING FOR BIOMARKERS IN SERUM SAMPLES FROM PATIENTS WITH RHINITIS OR DIFFERENT ASTHMA PHENOTYPES/SEVERITIES (Chapter IV) Because of the absence of studies of this kind, the last chapter of the present thesis is devoted to the search of serum biomarkers associated to asthma phenotypes (AA vs. NAA) or severities (intermittent-mild and moderate-severe) by means of modern proteomic techniques. The first serum/plasma proteomic studies were only able to “scratch” the first layer of the proteome (i.e., the high-abundance proteins) as a result of the high dynamic range of protein concentrations in serum. Since then, several techniques have been developed to deal with this problem, such as ultrafiltration, targeted protein-depletion, or low abundant protein enrichment. At the same time, analytical methods have evolved from classical procedures with a low sensitivity, precision, and throughput (e.g. 2-DE), to more modern and highperformance technologies (e.g., LC-MS/MS). However, despite these refinements, most of the current proteomic approaches are not yet capable to reach with ease the medium-low abundant proteome (the so-called “deep proteome”). Therefore, the first aim of the work accomplished in Chapter IV was to develop a protocol for the quantitative study of the medium-low abundance proteome of serum samples, which combines lipoproteins-depletion, CPLL-based enrichment of low abundant proteins (ProteoMiner®), and iTRAQ-LC- MS/MS analysis. The second aim was to apply this protocol to different serum samples from rhinitis, allergic asthmatics, non-allergic asthmatics, and healthy subjects, in order to discover novel biomarkers capable of predicting different asthma phenotypes or severities. Juan José Nieto Fontarigo 274 In the last years, a high number of proteomic studies have been carried out in asthma (summarized in Table 1 from introduction). In all these pieces of work, different types of samples (e.g., BALF, EBC, NLF, BB, NB, IS, serum/plasma) were used, and several types of biomarkers pursued (e.g., diagnosis, exacerbation, treatment response) [337, 436-438]. However, none of them was aimed to analyse the serum proteome of different asthma phenotypes (AA vs. NAA) or severities, as above commented. Additionally, most of the studies in serum samples used 2-DE, and just a handful was carried out by LCMS/MS [391]. Moreover, one single proteomic study used iTRAQ- LC-MS/MS to evaluate bronchial brushing samples from asthmatics [379]. Therefore, the first part of Chapter IV addresses the development of a new quantitative proteomic approach based on lipoproteins-depletion, low abundant protein enrichment (ProteoMiner), iTRAQ peptides labelling, and subsequent LC-MS/MS and iTRAQ quantification, with applications in a diverse set of pathologies. On the other hand, the second part of the work accomplished in Chapter IV undertakes the identification of the serum proteome signature in different groups of donors: moderate-severe AA, intermittent-mild AA, rhinitis, moderate-severe NAA, intermittentmild NAA, and healthy controls (HC; reference group). Due to a large number of serum specimens and the ability of iTRAQ reagents to label up to 8 biological samples, each group of patients was split into two subgroups to generate two biological replicates. In turn, these biological samples were analysed in triplicate (technical replicates), together with a pooled serum sample formed by all the samples (internal pool; 121 reporter ion), which was used for normalization. After LC-MS/MS analysis, a set of 217 proteins was identified with high confidence, of which 26 presented changes between the groups of study. Principal Component Analysis of the differentially abundant GENERAL DISCUSSION 275 proteins revealed the presence of 5 principal components (PCs) explaining 81.6% of the variation. PC1 is made up of proteins related to allergy (AA and rhinitis), most of them implicated in metabolic (e.g., protein AMBP/alpha-1-microglobulin/bikunin precursor; HSPG2/Heparan sulphate proteoglycan 2/Perlecan; IGFALS/Insulinlike growth factor binding protein, acid labile subunit; or AHSG/alpha-2-HS-glycoprotein) or immune system processes (e.g., HSPG2, AHSG, ORM1/AGP1/Alpha-1-acid glycoprotein 1, or CD5L). Moreover, PC1 has an enrichment of the Reactome pathway “Regulation of Insulin-like Growth Factor (IGF) transport and uptake by Insulin-like Growth Factor Binding Proteins (IGFBPs)” to which calumenin, IGFALS, AHSG, and prothrombin belong. Amongst proteins in PC1, IGFALS, protein AMBP, and HSPG2 were chosen for further confirmation by Enzyme-Linked ImmunoSorbent Assays (ELISAs). So far, only IGFALS ELISA was performed with identical results. IGFALS is a protein produced by hepatocytes, but also expressed in other tissues, including thymus and lungs [439]. This protein can be found in plasma or as a free molecule or forming a complex with IGF1-IGFBP (3 or 5 proteins) [440]. IGFALS has an important role on the bioavailability of IGFs [441], preventing the extravasation, proteolysis or renal elimination of IGF-1 [442]. For this reason, IGFALS deficiency results in a dramatic decrease of IGF-1 levels, but also affects the IGF-2 and IGFBP3 proteins [442, 443]. IGF1 is important for asthma pathogenesis through the promotion of inflammation, sub-epithelial fibrosis, hyperresponsiveness, and smooth muscle cell hyperplasia in the lungs [441]. Apart from the previously reported elevation of IGF1 [441] and IGFBP3 [441] in AA, the work presented in Chapter IV shows that IGFALS is also augmented in this kind of patients, especially those displaying a high disease severity. IGFBP3 controls AA inflammation through Juan José Nieto Fontarigo 282 resemble memory/effector cells with an advanced differentiation stage: TEM or TEMRA lymphocytes. 4. The TEM/TEMRA subsets expanded in asthma patients belong to different lymphocyte lineages: CD4+ TH cells in AA and CD4- γδ-T lymphocytes in NAA. 5. Serum sCD26 levels are decreased in both AA and NAA patients; therefore, they probably reflect the “fingerprint” in serum proteome of the expansion of CD26-/lowCD4+ TH in AA and CD26-/lowCD4- γδ-T subsets in NAA. 6. The reduction of circulating sCD26 levels as well as CD26 expression on effector TH lymphocytes from asthmatics might be important to improve their migratory and proliferative capabilities. This finding should be considered in light of the current clinical usage of DPP4 inhibitors and anti-CD26 antibodies. 7. There is a strong correlation between the expression of CD26 and CD126/IL-6Rα on Teff lymphocytes, particularly those lacking the CD4 marker. Therefore, the TEM/TEMRA subsets expanded in asthma (especially amongst the NAA patients) are also CD126-/low cells. 8. The down-modulation of CD126/IL-6Rα in moderate-severe patients compared to intermittent-mild asthmatics is a widespread event, taking place on monocytes, neutrophils, and CD4+ cells. This highlights the potential role of IL-6 transsignalling in asthma severity. 9. Although the number of Treg cells remains unchanged in asthma, their suppressive capacity could be impaired according to their higher CD26 levels compared to healthy controls. Chapter IV 1. A “shotgun” proteomics methodology has been developed for the quantitative analysis of medium-low abundance serum CONCLUSIONS 283 proteins. 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J Immunol. 2003;171(1):380-9. ABSTRACT Asthma is a heterogeneous and chronic inflammatory family of disorders of the airways with an increasing prevalence that results in recurrent and reversible bronchial obstruction and expiratory airflow limitation. These diseases arise from the interaction between environmental and genetic factors, which collaborate to cause increased susceptibility and severity. Many asthma susceptibility genes are linked to the immune system or encode enzymes like metalloproteases (e.g., ADAM-33) or serine proteases. The S9 family of serine proteases (prolyl oligopeptidases) is capable to process peptide bonds adjacent to proline, a kind of cleavage-resistant peptide bonds present in many growth factors, chemokines or cytokines that are important for asthma. Curiously, two serine proteases within the S9 family encoded by genes located on chromosome 2 appear to have a role in asthma: CD26/dipeptidyl peptidase 4 (DPP4) and DPP10. The aim of this review is to summarize the current knowledge about CD26, and to provide a structured overview of the numerous functions and implications that this versatile enzyme could have in this disease, especially after the detection of some secondary effects (e.g., viral nasopharyngitis) in type II diabetes mellitus patients (a subset with a certain risk of developing obesity-related asthma) upon CD26 inhibitory therapy. KEYWORDS: CD26, DPP4, asthma, cytokines and chemokines, sCD26, CD26 inhibitors. 1.- DEFINITION AND GENETIC FACTORS IMPLICATED IN ASTHMA Asthma is a heterogeneous and chronic disease characterized by reversible expiratory airflow limitation, bronchial hyperresponsiveness, mucous cell hyperplasia, higher vasculature permeability, airway remodelling with fibrosis and inflammatory cell infiltration [1, 2]. Asthma is a major concern, with 334 million people worldwide affected, increasing prevalence [3] and a high economic charge [4]. It is more frequent and severe in boys until the age of 13 years, but both prevalence and severity of asthma rise in women after puberty, becoming even more prevalent in women [3, 5, 6]. 5-10% of cases display a highly severe and treatment-refractory disease, suffering from recurrent exacerbations that threaten patient´s life and increase the health care costs. This is a complex pathology, with both genetic and environmental factors causing increased susceptibility and severity. Great efforts have been made to discover the genetic bases (mostly GWAS), revealing the influence of several genes encoding proteins with an important role in the immune system (HLA-DQ, HLA-G, IL1RL1, IL18R, TSLP, PDE, IL-33, LRRC32, SMAD3, IL2RB, IL6R, IL13) and also proteases (ADAM33, and DPP10) [7-9]. 2.- ASTHMA AND THE PROLYL OLIGOPEPTIDASE FAMILY OF PROTEASES: DIPEPTIDYL PEPTIDASE 10 (DPP10) AND CD26/DPP4 As commented above, proteases are involved in many physiological and pathological processes, including chronic respiratory conditions like asthma. Amongst all proteases, there are only a few prolinespecific enzymes, as peptide bonds adjacent to proline (present in some growth factors, chemokines or cytokines) are resistant to cleavage [10]. These enzymes include serine proteases, with a serine residue in their catalytic region (sequence consensus Gly-Xaa-Ser- Xaa-Gly) [11] and covering different families (S1-S81) and subfamilies. Thus, the S9 family (prolyl oligopeptidases) includes from S9A to S9D, all with the catalytic triad Ser, Asp, His but with slightly different sequence consensus around the catalytic Ser. For example, most of members of the S9B subfamily (EC 3.4.14.5; CD26/DPP4, DPP8, DPP9, and fibroblast activation protein/FAP/Seprase) (http://merops.sanger.ac.uk/) present the sequence Gly-Trp-Ser-Tyr-Gly-Gly, while the other additional two members, DPP6 (DPPX; Gly-Lys-Asp-Tyr-Gly-Gly) and DPP10 (Gly-Lys-Gly-Tyr-Gly-Gly), do not possess the catalytic serine and, therefore, DPP4 activity [12]. Curiously, four of these peptidases (CD26, FAP, DPP6, and DPP10) are type II membrane proteins released to the extracellular medium, three are encoded by genes located on chromosome 2 (CD26, FAP and DPP10), and only two (CD26, DPP10) appear to have a role in asthma [13-16]. For example, DPP10 have been linked to asthma susceptibility in different populations [7, 13, 15], and this protein (as well as DPP8 and DPP9) has been primarily located in the trachea and the bronchi of the airways in rats [17]. For its part, the protease CD26 is the major member of the S9B family and also a receptor for the Middle-East respiratory syndrome coronavirus (MERS-CoV) [18, 19], a new coronavirus that causes severe lower respiratory tract infections that could lead to asthma exacerbations. CD26 has been found elevated in both plasma samples (sCD26) and the surface of peripheral CD4+ T cells from adult patients with allergic asthma [20, 21], and different animal models [14, 16, 22] suggest a role of this peptidase in the pathogenesis of this disease. 3.- STRUCTURE AND DISTRIBUTION OF CD26 3.1.- Structure of the CD26 molecule CD26 is a single-pass type II integral membrane glycoprotein of 105- 110 kDa [23]. Only the homodimeric form of CD26 is biologically active [24-27]. Homodimerization takes place in both the Golgi apparatus [28] and the endoplasmic reticulum [29]. Each monomer displays a highly conserved and short (6 amino acids) cytoplasmic tail at the N-terminus, a 22 amino acid hydrophobic transmembrane region and a long extracellular domain of 738 amino acids. The heavily N-glycosylated extracellular domain can be subdivided, in turn, in several regions. The closest to the amino-terminal part starts with a flexible stalk region and contains 8 out of 10 possible N- glycosylation sites, while the intermediate region is highly enriched in cysteines (9 out of 12). Finally, the active centre is located towards the carboxyl-terminal end and is another highly conserved region [30-34]. 3.2.- Tissue and cell distributions of CD26 Human CD26 is broadly distributed in a variety of cell types, tissues, and organs [35-39]. Lungs display the second highest CD26 activity amongst organs, especially in lung parenchyma [17, 22]. Contrary to DPP8/9 and DPP10, bronchi almost no express CD26 [17], but can be found in the apical membrane of epithelial cells, capillary endothelial cells, fibroblasts and serosal submucosal glands of human bronchi [40-42]. In most of these places, CD26 levels are constitutive and highly correlated with the mRNA content (http://www.proteinatlas.org/ENSG00000197635-DPP4/tissue) [43]. However, IL-13 causes a strong proinflammatory upregulation of CD26 in the airway epithelial cells [44]. Moreover, both DPP4 activity and CD26 protein (but not mRNA) increase after allergen exposure in lung parenchyma in a rat model of allergic airway inflammation [17], suggesting that CD26 on lung epithelium could be important in asthma pathogenesis [45]. CD26 is also expressed in the Immune System, being detected in medullar thymocytes, T cell areas of spleen and lymph nodes, peripheral blood T cells and, at a lesser extent, B cells, NK cells, monocytes/macrophages and granulocytes [24, 25, 30, 41, 46, 47]. CD26 density in these cells is heavily controlled and augments upon cell activation and acquisition of a memory phenotype, especially in the T cell lineage [33, 41, 48]. Human T lymphocytes display variable basal expression of CD26 (CD4+ T >> CD8+ T cells), which depends on the individual and the mAb used. Despite not all resting T cells are CD26+, most of them contain CD26 mRNA and display CD26 molecules on the surface 4-8 hours after stimulation [49-51]. However, only a certain regulation on CD26 mRNA levels has been detected by either northern blot [36, 50, 52-54] or gene arrays [55] upon activation. Additionally, CD26 is upregulated by IFNγ on renal epithelial cells [56] and B-CLL [57] through the modification of mRNA levels. Despite the above-described adjustment of CD26 expression through mRNA levels, several pieces of evidence support the presence of upstream control levels. Thus, CD26 is strongly regulated at protein level by several soluble factors. For example, the TH1 cytokine IL-12 (and to a lesser extent IL-2) enhances the expression of CD26 on both activated T cells [58, 59] and NK cells (together with IL-15) [47, 60]. On the contrary, IFNγ (another TH1 cytokine) has no effect on CD26 levels in these lymphocytes [47, 58]. Regarding TH2 cytokines, IL-4 promotes the expression of CD26 on human B lymphocytes activated with Staphylococcus aureus cowan I [61, 62], while this cytokine moves from a lack of effect [63] or a certain downmodulation of CD26 levels in T cells at high concentrations [unpublished results]. In addition, in vitro exposure to regulatory T cells (Treg)-derived soluble factors like TGFβ1 [64, 65] or Ado (adenosine) [66] leads to diminished CD26 levels. Most of peripheral blood Treg lymphocytes display an “activated-like” (e.g., CD25high), “memory” (CD45RO+) and “anergic/apoptosis-prone” phenotype [67] and were expected to express other activation/memory markers such as CD26. This seems to be the case for rats, where CD25+ (Treg) and CD25- (effector T cells or Teff) subsets of peripheral CD4+ T cells show equivalent CD26 expression [68]. In contrast, human Treg cells (CD4+CD25high or CD4+FoxP3high) display lower levels of CD26 compared to Teff lymphocytes (CD4+CD25-/low or CD4+FoxP3-/low) [69-72]. This likely explains why cytokines that favour “effector” responses (e.g., IL-12) cause a strong upregulation of CD26 on “bulk” TH cell cultures, while others important for the Treg homeostasis (e.g., IL-2, IL-15) only induce a slight increase on CD26 levels [58, 73]. It also gives a clue on why CD26 is downmodulated upon exposure of T cells to TGF-β1 [64, 65]. CD26 expression amongst Teff lymphocytes is also variable, and TH17 cells appear to display the highest levels of CD26 according to the following order: TH17>>TH1>TH2 [72, 74-77]. Furthermore, two subsets were reported amongst TH17 cells on the base of CCR4 expression [78], but only the CCR4- TH17 subset (and not the TGF-β- secreting CCR4+ TH17 subpopulation) has a CD26high phenotype [79]. This finding likely indicates that the degree of phenotypic diversity found in Teff cells for CD26 levels is also probably present in Tregs and reflects the presence of functionally different subsets that mirror the corresponding Teff subsets [80]. The different expression levels of CD26 in Treg and Teff lymphocytes could depend on a variation in CD26 mRNA levels as it happens with “regulatory-like” CD4+ T cells in classical Hodgkin´s lymphoma [81]. However, it is worth to mention that, apart from regulating this set of CD26 mRNA molecules, there is an intracellular pool of CD26 protein maintained by continuous translation in human T cells (regardless their CD26+ or CD26- phenotype) [50] that can be mobilized towards the plasma membrane [54] or released into the extracellular space. Therefore, there could be a number of additional mechanisms leading to a CD26-/low phenotype in human Treg cells. 3.3.- Body fluid compartments and distribution of soluble CD26 CD26 can be found in the extracellular space, with autocrine, paracrine or endocrine effects. The soluble version of CD26 (sCD26) has been described in many biological fluids (e.g., serum, plasma, synovial fluid, cerebrospinal fluid) from different organisms [82]. Bronchoalveolar lavage contains DPP4 enzymatic activity in rats [17] and humans [83]. In serum or plasma at least 90% of this activity is associated to a heavily glycosylated 110 kDa CD26 isoform [84, 85], whose concentration displays a normal distribution [86] and high biological variability [87, 88] that seems to depend on pre-analytical variables, like age or gender. Thus, serum sCD26 concentration increased in up to 10-12 years in children, after which the values start decreasing [89]. In adults, it has been also detected a slight decrease of sCD26 or DPP4 activity in serum with age [87, 88], but other studies did not describe such correlation [86, 90]. In addition, no differences were detected regarding gender in some studies [90], while different authors did find a higher sCD26 concentration in serum/plasma samples [86-89, 91] but a lower CD26 expression on CD4+ T cells (our unpublished results) from males. Several studies have found a positive correlation between sDPP4 activity and sCD26 in humans [91-93], but others have reported a low correlation instead, with different explanations like the presence of hypersialylated CD26 isoforms or alternative proteins with DPP4 activity [82]. Thus, plasma samples contain a soluble glycoprotein named DPPT-L or attractin without homology with CD26 but with DPP4 activity [94-96], although this activity has been questioned more recently [97]. Attractin is accumulated in the plasma membrane upon T cell receptor (TCR) triggering (~24h) [95, 96], especially in CD26high Teff cells (our unpublished results), and released into the plasma at 48-72h [95, 96]. Curiously, linkage disequilibrium studies show an association of asthma with a region including the attractin (ATRN) gene, which is upstream of the gene encoding the secretase/sheddase ADAM-33 (an asthma susceptibility gene) [97]. Release of CD26 could be accomplished by a classical or nonclassical pathway, and either by a constitutive or induced mechanism. The classical pathway requires vesicular traffic from the endoplasmic reticulum/Golgi towards the plasma membrane. Intravesicular proteins are liberated in the extracellular medium after membranes merging (exocytosis), while transmembrane proteins appear in the secretome through proteolysis mediated by “secretases”/“sheddases”. This last process ("shedding") delivers growth factors, cytokines, receptors and probably molecules like CD26 [98]. This is additionally supported by the lack of posttranscriptional splicing in CD26 mRNA, the absence of cytoplasmic and transmembrane domains in sCD26, or results from pulse chase and transfection experiments [25, 82]. However, CD26 has been detected in microvesicles and exosomes from lymphocytes (http://www.exocarta.org). Therefore, constitutive or induced release of CD26+ vesicles (exosomes, microvesicles or apoptotic bodies) into the medium could also contribute to the pool of sCD26 in the circulation and reflect the cell subset of origin (“cell lineage fingerprint"). The cell source of sCD26 is still controversial [25, 82]. Visceral fat, at least in obese patients, overexpresses CD26 and releases this “adipokine” into the circulation [88], and there are data supporting the presence of a positive correlation between fasting sCD26 levels and body mass indexes/BMI >25 [88, 99]. sCD26 may also originate from other sources, such as endothelial cells (e.g. lung) or epithelial cells from liver (bile canaliculi) or kidney. However, immune cells are also a likely source [25, 82, 100]. Thus, a transplantation model in rats has determined that, under healthy conditions, bone marrow-derived cells represent a significant source for sCD26 [101]. Therefore, the concentration of sCD26 could also be influenced by the number of lymphocytes [102] or mirror the predominant phenotype of circulating CD4+ T lymphocytes in a pathological situation. 4.- CD26 AND ASTHMA 4.1.- Asthma phenotypes, disease severity and CD26 levels in CD4+ T cells. CD4+ TH cells play a central role in adaptive immune responses and the induction/persistence of asthma and other allergic/atopic diseases. They are plastic and heterogeneous lymphocytes, with four main lineages (TH1, TH2, TH17 and Treg cells) and different roles. For example, TH2 (GATA-3+) cells infiltrate airways in allergic asthma and produce a set of cytokines (IL-4, IL-5, IL-13) important for airway remodelling, leucocytosis, eosinophilia, macrophages/mast cells activation, and B-cell dependent IgE elevation [103, 104]. In the same way that TH lymphocytes are heterogeneous, there are also a number of asthma phenotypes as a likely reflection of the TH cells heterogeneity itself, with both TH2high and TH2low phenotypes sharing different clinical signs: a) the early allergic asthma, with a strong familial background and mediated by TH2 cytokines (TH2high) and allergen-specific IgE (atopy); b) the less-allergic late-onset asthma (TH2high), which is characterized by eosinophilic inflammation, absence of specific IgE (i.e., non-atopic) and worse response to corticosteroids; c) neutrophilic asthma, a TH2low phenotype refractory to corticosteroids and linked to TH17-responses, sputum neutrophilia, and augmented levels of IL-8 and IL-17; d) and the obesity-related asthma, a TH2low phenotype predominant in obese women, with higher levels of TNFα, IL-6 and leptin but low numbers of eosinophils [1] (Table 1). Therefore, alternative CD26+/high effector TH subpopulations are gaining importance in asthma, particularly as the disease becomes chronic and refractory to treatment. In this context, even though it was initially described that CD26+ TH1 cells were protective (“hygiene hypothesis”), now it is considered that these cells could be favouring the inflammation of the airways [105]. In addition, proinflammatory CD26high TH17 cells have been detected in biopsies from asthma patients, and their cytokines (e.g., IL-17, IL-6, IL-21, IL-22) involved in eosinophilia/neutrophilia and higher severity during acute attacks [106]. On the other hand, Treg cells (FoxP3+, CD26-/low) also seem to play a relevant role in controlling exaggerated TH2 responses and asthma development [9, 107, 108]. Treg cells exert their suppressor activity by using both soluble (e.g., adenosine, TGFβ, IL-10) and membrane-associated (e.g., TGFβ, CTLA-4) molecules [67], and a number of GWAS in asthma have identified some genes (e.g., IL2RB, SMAD3, GARP/LRRC32) linked to this suppressor activity. Thus, the lower or higher prevalence of different Teff subsets and/or the distortion of the Teff/Treg balance could also alter the phenotype and severity of asthma [104, 109, 110], Moreover, depending on the asthma phenotype or the severity of this disease, the levels and functions of CD26 on the surface of immune cells and biofluids could be rather different and be a factor influencing disease development. lymphocytes, eosinophils, neutrophils, endothelial and mast, epithelial, endothelial, and smooth muscle cells) [161, 162]. This role of Ado in asthma is affected by binding affinity, receptor density and local levels of this nucleoside, which are influenced by a delicate balance where different mechanisms are involved (e.g., extracellular/intracellular Ado metabolism) [161, 162]. Amongst these mechanisms, the Ado catabolism mediated by ADA molecules anchored to CD26 is the major regulated pathway that influences the local concentration and biological effects of Ado. In this respect, relevant TH2 cytokines in allergic asthma (IL-4, IL-13) reduce ADA activity in the lung [161] and ecto-ADA levels on TH lymphocytes [63]. These findings suggest that low levels of CD26/ecto-ADA on the TH2 subset in TH2high (allergic/atopic) asthma could favour the local accumulation of Ado, the activation of A1AR, and the participation of proinflammatory ARs that require Ado concentrations over the physiological levels (e.g., the low-affinity A2BAR) in order to neutralize the off-signals provided by the engagement of high-affinity and asthma-protective A2AARs. Therefore, it is likely that ARstargeted therapy is more effective in TH2high asthma than in TH2low or severe asthma, wherein CD26/ecto-ADAhigh TH1 and TH17 cells are more frequent. However, additional studies are needed to clarify what could be exactly the role of Treg cells in asthma, a lymphocyte subset with a CD26/ecto-ADAlow phenotype that should favour the high production of Ado [70]. On the other hand, CD45 has been involved in Janus kinases dephosphorylation [163]. Therefore, the CD26-CD45 association could have a negative and DPP4-independent role important to restrain the signal transduction of cytokine receptors [122] (Fig. 1). In this sense, the low PTPase activity in human naïve CD4+CD45RA+CD26-/low T cells makes them susceptible to small amounts of IL-4, as mentioned an important cytokine in allergic asthma, while memory/effector CD4+CD45RO+CD26+/high T cells secrete this soluble factor upon activation, but are less sensitive to its effects [164]. Indeed, high levels of CD26 in memory/effector TH lymphocytes might act as a “brake” for the proliferative responses to cytokines (for example, IL-12; our unpublished results). The protective function of CD26 in asthma could also be linked to the DPP4 activity (Fig. 1). Some CD26 substrates fall outside the scope of the immune system and are beyond the scope of this review, like incretins (GIP/glucose-dependent insulinotropic peptide, GLP-1/glucagon-like peptide-1, GLP-2/ glucagon-like peptide-2) [10, 165, 166], glucagon, PACAP (pituitary adenylate cyclase-activating polypeptide), GRP (gastrin-releasing peptide), peptide YY, vasoactive peptides (bradykinin and VIP/vasoactive intestinal peptide), natriuretic peptides (BNP/B-type natriuretic peptide), and neuropeptides (NPY/neuropeptide Y, betacasomorphins, endomorphins, substance P) [41, 82, 166, 167] (Table 2). However, some others have an important immunomodulatory role, such as cytokines (e.g., IL-3, G-CSF, GM-CSF) [168] or chemokines (e.g., RANTES/CCL5, eotaxin/CCL11, MDC/CCL22) [82, 166]. CD26 enzymatic activity down-modulates the biological function of most of these chemokines and cytokines (Table 3). Consistent with this observation, it has been found that CD26 inhibitors can enhance some in vivo immune responses depending on the dose, application route, timing or predominant Teff subset [45, 169], which could be explained by the presence of off-targets effects as well [25, 170]. However, animal models of rheumatoid arthritis [93], multiple sclerosis [171], and inflammatory bowel disease [172] in CD26 KO mice do support an immunosuppressive role of both CD26 and DPP4 activity. This immunosuppressive function has also been observed for sCD26 during strong in vitro proliferative responses of immune cells [143, 145]. Moreover, CD26 has been even regarded as a tumour suppressor gene in melanomas or neuroblastomas [173, 174]. For this reason, we will focus this part of this review on the CD26 substrates with a direct connection with the immune system like chemokines. Table 2. Known substrates processed by CD26/DPP4 out of the immune system Substrate name and family N-terminal sequence Effect of DPP4 processing In vitro / in vivo evidence Reference β-casomorphins (neuropeptide) Tyr-ProPhe Inhibitory Yes/Yes [10] [82] [156] BNP (natriuretic peptide) Ser-ProLys Inhibitory Change in receptor preference Yes/Yes [82] [233] Bradykinin (vasoactive) Arg-ProPro Inhibitory Change in receptor preference Yes/Yes [10] [82] [156] Endormorphins (neuropeptide) Tyr-ProPhe Inhibitory Change in receptor preference Yes/Yes [10] [41] [82] [156] Enterostatin (grastointestinal hormone) Val-ProAsp Inhibitory Yes/Yes [10] [41] [156] GIP (incretin) Tyr-AlaGlu Inhibitory Yes/Yes [10] [41] [82] [154] [156] GLP (GLP-1 [7- 36]amide, GLP-1 [7-37]& and GLP-2) (incretin) His-AlaGlu (GLP-1) His-AlaAsp (GLP-2) Inhibitory Yes/Yes [10] [41] [82] [154] [156] Glucagon (gastrointestinal hormone)* His-SerGln Inhibitory Yes/Yes [82] [156] GRH (GRH[1-29] and GRH[1-44] (hypothalamic hormone) Tyr-AlaAsp Inhibitory Yes/No [10] Continued on next page Table 1 (Continued) GRP (hormone bombesin family) Val-ProLeu Not known Yes/Yes [82] NPY (neuropeptide) Tyr-ProSer Receptor Y1 Inactivation Change in receptor preference Yes/Yes [10] [41] [82] [156] PACAP (PACAP27 and PACAP38)* His-SerAsp Probably inhibitory Yes/Yes [82] [234] Peptide YY (Pancreatic peptide) Tyr-ProIle Receptor Y1 Inactivation Change in receptor preference Yes/Yes [10] [41] [82] [156] Substance P (neuropeptide) Arg-ProLys Inhibitory Questionable Yes/Yes [10] [41] [82] [156] VIP peptides (VIP, PHV42, PHM27) (vasoactive)* His-AlaAsp (PHV, PHM) His-SerAsp (VIP) Probably inhibitory Yes/Yes [10] [41] [82] [154] [156] BNP: B-type natriuretic peptide; GIP: glucagon inhibitory peptide; GLP: glucagon like peptide; GRH: growth hormone-releasing hormone; GRP: gastrin releasing peptide; NPY: neuropeptide Y; PCAP: pituitary adenylate cyclase-activating polypeptide; VIP: vasoactive intestinal peptide; PHV42: peptide histidine valine 42; PHM27: peptide histidine methionine 27 *: Glucagon, PACAP and VIP have a Ser in position 2 and, with less efficiency that Pro or Ala, also can be DPP4 potential substrate; &: GLP-1 [7-36] amide and [7-37] are the active forms of GLP-1 and substrates of DPP4. 4.3.1.- CD26, TH2-related chemokines and TH2high asthma. Even though cytokines like IL-1β or IL-2 contain an appropriate N- terminal sequence, the molecular weight precludes their N-terminal clipping, with exceptions like IL-3, G-CSF (granulocyte colonystimulating factor), GM-CSF (granulocyte-macrophage colonystimulating factor), or Epo (erythropoietin) [168]. In contrast, CD26- dependent processing of chemokines (8-10 kDa) like RANTES (regulated on activation, normal T cell expressed and secreted) is one of the most interesting aspects of CD26 biology [175]. Moreover, this function is mostly dependent on CD26 levels, which is influenced by the T cell subset or disease, as we have just seen. Chemokines are proinflammatory cytokines with a role in leukocyte activation and migration. They are classified according to the position of two N-terminal cysteine residues (CC, CXC, C and CX3C) [176], but can also be divided as a function of the cells they attract or the receptor they recognize. As table 3 shows, the major branches of effector (TH1, TH2, and TH17) and regulatory T cells express characteristic (but not totally selective) chemokine receptors [76, 103]. For example, TH2 lymphocytes and other leukocytes important in asthma (basophils, mast cells, and eosinophils) express CCR3, CCR4, CCR8, CXCR4 and, in humans, CRTH2 [103]. CCR3, CCR4, and CXCR4 interact with CD26-substrates, but only CCR3 and CCR4 are actually specific for TH2 cells. Regarding CXCR4, TH2 cells seem to display a slight overexpression compared to TH1 lymphocytes [177], but other authors describe CXCR4 as a merely trafficking marker [178-180]. Ligation of CCR3 with eotaxin/CCL11, RANTES/CCL5, and MCP-1/CCL2, MCP-2/CCL8, MCP-3/CCL7, MCP-4/CCL13 participates in the recruitment of basophils, eosinophils and mast cells [103, 181, 182] (Table 3). Eotaxin is an important chemokine in allergic asthma produced by endothelial cells and monocytes in response to IFNγ and TNFα, respectively. This chemokine is recognized by CCR3 (eosinophils, basophils, mast cells and TH2) and a lesser extent by CCR5, a putative TH1-marker (see later) [183]. Eotaxin is a chemoattractant for eosinophils that facilitates their mobilization from bone marrow [184]. Truncation of eotaxin by CD26 is characterized by an intermediate-low efficiency (kcat/Km: SDF-1α > MDC > I-TAC > IP-10 > MIG > eotaxin > RANTES > LD78β) [185]. Despite this, N-terminal clipping by CD26 results in an isoform (3-74) with a reduced chemotactic activity that causes CCR3-desensitization [183, 186, 187]. Indeed, administration of eotaxin to F344 rats leads to a mobilization of eosinophils, an effect enhanced in CD26-deficient animals or with CD26 inhibitors [187]. Additionally, CD26-/- mice challenged with ovalbumin/OVA show higher levels of CCR3 and CCR3-ligands (eotaxin, RANTES) and stronger eosinophils infiltration in lungs [16]. Another ligand of CCR3 is CCL14 (Table 3), a chemokine processed by plasmin and urokinase plasminogen activator (UPA) to yield CCL14 (9-74). This isoform binds to CCR3 (and also CCR1 and CCR5) to efficiently attract eosinophils, monocytes and TH2 cells, a process also dampened by CD26 [188]. Therefore, a CD26-/low phenotype in both eosinophils and TH2 cells (CCR3+) seems to favour the inflammatory response in TH2high-asthma. CXCR4 is found in monocytes and B/T (preferentially TH2) cells [177, 189] and promotes the recruitment of T-cells in the lungs during allergic airway diseases [178, 190]. CXCR4 recognizes macrophage migration inhibitory factor (MIF) and stromal cellderived factor 1 (SDF1/CXCL12) [189] (Table 3), the last one a small chemokine synthesized by endothelial cells and fibroblasts that induces T/B cells activation [142] and regulates the traffic of lymphocytes, monocytes and dendritic cells toward inflamed epithelia [179, 189, 191, 192]. Amongst the several SDF1 isoforms, at least two (SDF1α and SDF1β) are efficiently processed by CD26 in vitro [185, 193-195] and in vivo [93]. The SDF-1α (3-67) isoform is unable to activate CXCR4 and displays antagonistic activity [185, 193-198]. Moreover, both CD26 and CXCR4 have similar expression kinetics upon activation [58, 199] and interact in lymphocytes [114]. Binding of SDF1α to CXCR4 initiates the CXCR4-CD26 complex endocytosis [114], a process disrupted by N-terminal clipping of SDF1α [195]. This finding could not explain however the preferential expression of CXCR4 in CD26low cells (e.g., TH2 or naïve TH) [76, 199], or why TGFβ (a cytokine that induces CD26 downmodulation) leads to augmented expression of CXCR4 and a potentiated SDF1α-CXCR4 axis [200-202]. This CD26-/lowCXCR4+ phenotype also facilitates a vigorous response to SDF1α in the recruitment of T cells and eosinophils in a mouse model of lung allergic inflammation [178]. On the other hand, CD26 has also been positively correlated with the in vitro invasive capacity of T cell lines in response to SDF1α, and this positive effect is mediated by CD45 [203], a tyrosine phosphatase that enhances cell migration in response to SDF-1α [204]. CCR4 is present on monocytes, dendritic cells, NK cells and TH cells (TH2, TH17, Treg). CCR4 recognizes both CCL17/TARC and CCL22/MDC (Table 3), the last chemokine produced by macrophages, dendritic cells, NK cells, and B/T lymphocytes [205]. TARC and MDC are expressed by epithelial cells in the airways, and their levels are upregulated after allergen challenge [103]. TH2 cytokines (e.g., IL-4 and IL-13), LPS, IL-1 and TNFα stimulate the secretion of MDC, whereas TH1 cytokines (e.g., IFNα, IL-12) inhibit MDC production [205, 206]. Moreover, MDC generates and amplifies TH2 responses and recruits TH2 lymphocytes [205-207], being important in diseases with a TH2-cytokine profile (e.g., asthma) or equivalent models in mice [207]. In these models, CCR4-MDC has a dominant role in later and chronic stages of the disease as compared with CCR3-Eotaxin [181]. Furthermore, CD26 processes very efficiently MDC (half-life: 2-5 min) to generate MDC(3-69) and, subsequently, MDC(5–69) [185]. This last isoform preserves the attractant power for monocytes, but displays reduced chemotactic activity for lymphocytes and dendritic cells [150], two subsets important in asthma. As Tregs, TH2 and CCR4+ TH17 cells are CD26- /low cells, while CCR4- TH17 cells are CD26high [72, 79], the CD26-/low phenotype of these CCR4+ subsets should apparently facilitates their recruitment to inflammatory sites. 4.3.2.- CD26, TH1/TH17-related chemokines and TH2low asthma Most of asthma patients present a TH2high disease, but there are other two types (obesity-associated and neutrophilic asthma) linked to a TH2low (i.e., TH1/TH17) profile [1]. The CD26high T cell subset displays a CD45RO+CCR7low effector-memory phenotype and produces TH1/TH17 cytokines [72, 77, 208]. TH1 cells are CCR5+CXCR3A+ lymphocytes [72, 208], are essential for the production of IgM, IgG, and IgA (but not IgE) by B-cells, and orchestrate the response against intracellular microbes [103]. A few CCR5 ligands and all the CXCR3A-specific chemokines are CD26 substrates (Table 3). For example, CCL5/RANTES is produced by endothelial and epithelial cells, platelets, macrophages, eosinophils and T cells [209]. RANTES activates CCR1, CCR3 (TH2) and preferentially CCR5 (TH1), thereby attracting monocytes, eosinophils and T cells to inflammatory sites [209]. This chemokine is cleaved with low efficiency (half-life of 400 min) by CD26 [100, 185], leading to RANTES(3-68), a chemokine that loses its capacity to bind CCR1 and CCR3 (monocytes, eosinophils and TH2 cells), but not CCR5 [197]. As CCR5 is expressed on TH1 and CD45RA-CD45R0+CCR7low effector-memory CD4+ T cells (both CD26+/high) [76, 103, 199], this means that RANTES(3-68) favours their attraction toward inflammatory sites [175, 197, 198, 210]. Another TH1-chemokine and CD26-substrate that binds CCR5 is LD78β/CCL3L1 [211]. Macrophage inflammatory protein–1α (MIP-1α) is encoded by 2 different loci: LD78α and LD78β [212]. Both chemokines are agonists of CCR1, CCR3 and CCR5, but LD78β binds with high affinity to CCR5 [213], regulating the traffic/activation of macrophages/monocytes, NK cells, eosinophils, basophils, immature dendritic cells, and T lymphocytes. Strikingly, the inefficient (half-life ~ 5 h) [185, 211] clipping of LD78β by CD26 generates LD78β(3-70) enhances the chemotactic activity for TH1 cells already been highlighting throughout this review, with proinflammatory or anti-inflammatory effects depending on the processed substrate: incretins or chemokines/substance P, respectively. Obese persons are at risk of a number of co-morbidities like type 2 diabetes mellitus (T2DM), a disease characterized by impair production of incretins, with subsequently hyperglycaemia. Incretins (GIP, GLP-1, GLP-2) are well-known CD26 substrates that lose their function when they are processed. Inhibition of CD26 enzymatic activity avoids the degradation of these hormones, enhances the incretin effect, improves both the insulin secretion and the glucose uptake and lowers the glycosylated haemoglobin A1c levels. To achieve these goals, a new group of anti-hyperglycaemic drugs (CD26 inhibitors or gliptins) have come on the market, with sitagliptin, (Januvia®; Merck Sharp & Dohme Ltd) and vildagliptin (Galvus®; Novartis Europharm Ltd) (both approved by European Medicines Agency/EMA in 2007) as the first outpost (Table 4). Currently, there are several orally administered CD26 inhibitors that have been approved by agencies like the Food and Drug Administration (FDA) or EMA and are being used with satisfactory results as a second or third line medication in combination with other oral antidiabetic drugs. Commercially available gliptins include the above-mentioned sitagliptin (Januvia®, Ristaben®), but also saxagliptin (Onglyza®), linagliptin (Trajenta®), alogliptin (Vipidia®), and vildagliptin (Galvus®, Jalra®, Xiliarx®) (Table 4). However, there is a controversial debate about the secondary effects on co-morbidities (e.g., cardiovascular outcome, renal impairment, acute pancreatitis) that the long-term treatment with these long half-life inhibitors may have. These concerns are as a result of several issues related to the great number of CD26 substrates linked or not to the immune system. Thus, the SAVOR TIMI-53 (saxagliptin) [235] trial detected a significantly increased rate for hospitalization due to heart failure, and a more recent study based on FAERS (US-FDA Adverse Even Reporting System) [236] is also consistent with this finding. In clear contrast, the TECOS trial (sitagliptin) [237] did not find an increased risk of heart failure. Table 4. DPP4 inhibitors registered for clinical use in EMA and adverse drugs reactions identified during both the clinical and post-marketing surveillance stage Active substance used as monotherapy Proprietary Name (Company; Date of EMA authorization) Immune system & Respiratory disorders, infections (Frequency)** Skin and subcutaneous tissue disorders (Frequency)** Sitagliptin Januvia® (Merck Sharp & Dohme Ltd; 2007) Ristaben® (Merck Sharp & Dohme Ltd; 2010)  Hypersensitivity, including anaphylactic responses (not known)*  Interstitial lung disease (not known)  Pruritus (uncommon)*  Angioedema (not known) *  Rash (not known) *  Urticaria (not known) *  Cutaneous vasculitis (not known) *  Exfoliative skin conditions including Stevens-Johnson syndrome (not known) *  Bullous pemphigoid (not known) * Vildagliptin Galvus® (Novartis Europharm Ltd; 2007) Jalra® (Novartis Europharm Ltd; 2008) Xiliarx® (Novartis Europharm Ltd; 2008)  Upper respiratory infection (very rare)  Nasopharyngitis (very rare)  Urticaria (not known) *  Bullous pemphigoid (not known)*  Exfoliative skin conditions (not known)* Continued on next page Table 4 (Continued) Saxagliptin Onglyza® (AstraZeneca AB; 2009)  Small decrease in the absolute count of peripheral blood lymphocytes  Upper respiratory infection (common)  Sinusitis (common)  Pruritus (uncommon) *  Angioedema (rare) *  Rash (common) *  Urticaria (uncommon) *  Dermatitis (uncommon) Linagliptin Trajenta® (Boehringer Ingelheim International GmbH; 2011)  Nasopharyngitis (uncommon)  Hypersensitivity (e.g. bronchial hyperreactivity) (not known)  Cough (uncommon)  Angioedema (rare) *  Rash (uncommon) *  Urticaria (rare)*  Bullous pemphigoid (not known)* Alogliptin Vipidia® (Takeda Pharma A/S; 2013)  Upper respiratory infection (common)  Nasopharyngitis (common)  Hypersensitivity reactions (not known) *  Pruritus (common)  Rash (common)  Exfoliative skin conditions, including Stevens-Johnson syndrome, Erythema multiforme, Angioedema and Urticaria (not known) * *Adverse drug reactions (ADRs) identified based on post-marketing surveillance **Absolute frequencies of ADRs; very common (≥ 1/10), common (≥ 1/100 to < 1/10), uncommon (≥ 1/1,000 to 1/100), rare (≥ 1/10,000 to 1/1,000), very rare (< 1/10,000), or not known (i.e., not estimated). More in accordance with the scope of this review, CD26 reversible inhibitors seem to increase the frequency of risk factors for asthma development/exacerbation like atopic sensitization, rhinitis, or rhinovirus infection in T2DM patients [232]. Thus, a rapid review of clinical and data published on the EMA web page (http://www.ema.europa.eu) supports increased risk of nonserious upper respiratory tract infections (e.g., viral nasopharyngitis, rhinitis, sinusitis) (Table 4), which would be in line with the costimulatory role of CD26. As Willemen and co-authors sustain, this increased risk of infections with CD26 inhibitors (~3% cases) cannot be compared with the magnitude of the effects seen with biological agents like tumour necrosis factor inhibitors [238]. However, this effect should not be underestimated and must be added to the immune impairment caused by T2DM itself to increase the overall asthma development/exacerbation risk in these patients. Other adverse drug reactions (ADRs) reported in association with gliptins and more associated with an inhibitory role of CD26 would be interstitial lung disease, hypersensitivity reactions (including anaphylactic responses or bronchial hyperreactivity), and skin and subcutaneous tissue disorders such as pruritus, angioedema, rash, urticaria, cutaneous vasculitis, or more severe and rare skin conditions (Table 4). For example, Bullous pemphigoid [187, 239-241] is an autoimmune subepidermal disease with overproduction of eotaxin and eosinophilia that affects skin and mucosae. Therefore, the association between gliptins and Bullous pemphigoid is in tune with in vivo studies in F344 rats showing that CD26 limits the eotaxin-mediated recruitment of eosinophils [187], or with the finding that oral administration of CD26 inhibitors promotes the allergic inflammation of the airways [45]. This means that CD26 could be part of a homeostatic mechanism to downmodulate airways inflammation mediated by TH2 and especially TH17/TH1 cells important in some TH2low asthma phenotypes such as obesity-related asthma. Nevertheless, it should be noted that besides chemokines there are other CD26 substrates with implications on obesity and asthma-like the substance P. Inhaled substance P, but not bradykinin enhances the airway response to bronchoconstricting agents in guinea-pigs [242]. Substance P also favours allergen sensitization and bronchial inflammation, as observed in a mouse model of diet-induced obesity sensitized and challenged with OVA and treated with an antagonist of the substance P receptor (NK1-R) [243]. Therefore, expanded half-life in substance P caused by treatment with CD26 inhibitors in T2DM patients could increase certain obesity-related co-morbidities such as asthma. In the same way, administration of sitagliptin in T2DM generates a temporary decrease in the percentage of peripheral blood Tregs that also could favour asthma prevalence in these patients [244]. In clear contrast, GLP-1-based therapies have anti-inflammatory effects in chronic inflammatory diseases including T2DM and asthma [245]. For example, in vitro studies have described that CD26 inhibitors induce a decrease of NLRP3 inflammasome, toll-like receptor 4 (TLR4) signalling and IL-1β in macrophages via GLP-1 receptor [160]. Therefore, more studies are needed to clarify whether gliptins have an overall positive or negative role in T2DM patients with obesity-related asthma. 6.- CONCLUDING REMARKS CD26 is a relevant molecule in asthma for several reasons. The first one because of its potential utility together with periostin to test the efficacy of the treatment with interleukin-13 neutralising monoclonal antibodies (e.g., Tralokinumab) in patients with severe uncontrolled asthma [246, 247]. Secondly, because of its multifunctionality nature, with both costimulatory and inhibitory roles in the immune system, apart from the high (but variable) CD26 levels in a subset of lymphocytes central to asthma: the CD4+ T cells. Different authors have highlighted the inhibitory functions of this molecule relative to signalling mediated by cytokines and chemokines. A handful of chemokines important for CD26+ TH2 cells during early-onset allergic or late-onset eosinophilic asthma includes chemotactic factors whose biological activity is reduced with low-intermediate (eotaxin) or high (MDC, SDF-1α) efficiency, whereas important chemokines for CD26+ TH1 (I-TAC, IP-10, Mig) and CD26high TH17 cells (MDC), two Teff subsets relevant in obesity-related asthma, late-onset neutrophilic asthma or severe asthma, are inactivated with intermediate-high effectiveness. Therefore, CD26 could act as a “biological brake” by reducing the attraction of Teff cells at sites of inflammation (e.g., the bronchi). This means that CD26 inhibitors used in T2DM patients could lead to a higher persistence of unprocessed substance P or chemokines and exacerbation of TH2high and especially TH2low asthma. 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