Synergism interaction between genetic polymorphisms in drug metabolizing enzymes and NSAIDs on upper gastrointestinal haemorrhage: a multicenter case-control study

Full Terms & Conditions of access and use can be found at https://www.tandfonline.com/action/journalInformation?journalCode=iann20 Annals of Medicine ISSN: (Print) (Online) Journal homepage: https://www.tandfonline.com/loi/iann20 Synergism interaction between genetic polymorphisms in drug metabolizing enzymes and NSAIDs on upper gastrointestinal haemorrhage: a multicenter case-control study Narmeen Mallah, Maruxa Zapata-Cachafeiro, Carmelo Aguirre, Eguzkiñe Ibarra-García, Itziar Palacios-Zabalza, Fernando Macías-García, María Piñeiro-Lamas, Luisa Ibáñez, Xavier Vidal, Lourdes Vendrell, Luis MartinArias, María Sáinz-Gil, Verónica Velasco-González, Manuel Bacariza-Cortiñas, Angel Salgado, Ana Estany-Gestal & Adolfo Figueirason behalf of the EMPHOGEN Group To cite this article: Narmeen Mallah, Maruxa Zapata-Cachafeiro, Carmelo Aguirre, Eguzkiñe Ibarra-García, Itziar Palacios-Zabalza, Fernando Macías-García, María Piñeiro-Lamas, Luisa Ibáñez, Xavier Vidal, Lourdes Vendrell, Luis Martin-Arias, María Sáinz-Gil, Verónica VelascoGonzález, Manuel Bacariza-Cortiñas, Angel Salgado, Ana Estany-Gestal & Adolfo Figueirason behalf of the EMPHOGEN Group (2022) Synergism interaction between genetic polymorphisms in drug metabolizing enzymes and NSAIDs on upper gastrointestinal haemorrhage: a multicenter case-control study, Annals of Medicine, 54:1, 379-392, DOI: 10.1080/07853890.2021.2016940 To link to this article: https://doi.org/10.1080/07853890.2021.2016940 © 2022 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. Published online: 04 Feb 2022. Submit your article to this journal Article views: 1119 View related articles View Crossmark data ORIGINAL ARTICLE Synergism interaction between genetic polymorphisms in drug metabolizing enzymes and NSAIDs on upper gastrointestinal haemorrhage: a multicenter case-control study Narmeen Mallah a,b,c,d , Maruxa Zapata-Cachafeiro a,e , Carmelo Aguirre f,g,h , Eguzki~ ne Ibarra-Garc ıa f,i , Itziar Palacios-Zabalza f,g , Fernando Mac ıas-Garc ıa j , Mar ıaPi ~ neiro-Lamas e,k , Luisa Ib a~ nez l , Xavier Vidal l , Lourdes Vendrell l , Luis Martin-Arias m , Mar ıaS  ainz-Gil m , Ver onica Velasco-Gonz alez m , Manuel Bacariza-Corti~ nas n , Angel Salgado a , Ana Estany-Gestal k and Adolfo Figueiras a,e,k ; on behalf of the EMPHOGEN Group a Department of Preventive Medicine, University of Santiago de Compostela, Santiago de Compostela, Spain; b WHO Collaborating Centre for Vaccine Safety, Santiago de Compostela, Spain; c Genetics, Vaccines and Pediatric Infectious Diseases Research Group (GENVIP), Instituto de Investigaci on Sanitaria de Santiago de Compostela, Santiago de Compostela, Spain; d Centro de Investigaci on Biom edica en Red de Enfermedades Respiratorias (CIBER-ES), Carlos III Health Institute, Madrid, Spain; e Consortium for Biomedical Research in Epidemiology and Public Health (CIBER en Epidemiolog ıa y Salud P ublica-CIBERESP), Carlos III Health Institute, Madrid, Spain; f Pharmacotherapy Group, Biocruces Bizkaia Health Research Institute, Barakaldo, Spain; g Basque Country Pharmacovigilance Unit, University Hospital of Galdakao-Usansolo, Osakidetza, Spain; h Pharmacology Department, Medicine and Nursing Faculty, University of the Basque Country, Barakaldo, Spain; i Osakidetza Basque Health Service, Pharmacy Department, Urduliz Hospital, Urduliz, Spain; j Department of Gastroenterology and Hepatology, University Hospital of Santiago de Compostela, Santiago de Compostela, Spain; k Health Research Institute of Santiago de Compostela (IDIS), Santiago de Compostela, Spain; l Department of Pharmacology, Therapeutics and Toxicology, Catalonian Institute of Pharmacology, Clinical Pharmacology Service, Vall d’Hebron University Teaching Hospital, Autonomous University, Barcelona, Spain; m Centre for Research on Drug Safety (CESME), Valladolid University, Valladolid, Spain; n Centro de Sa ude de Vite, Santiago de Compostela, Spain ABSTRACT Background: Interindividual genetic variations contribute to differences in patients’response to drugs as well as to the development of certain disorders. Patients who use non-steroidal antiinflammatory drugs (NSAIDs) may develop serious gastrointestinal disorders, mainly upper gastrointestinal haemorrhage (UGIH). Studies about the interaction between NSAIDs and genetic variations on the risk of UGIH are scarce. Therefore, we investigated the effect of 16 single nucleotide polymorphisms (SNPs) involved in drug metabolism on the risk of NSAIDs-induced UGIH. Materials and methods: We conducted a multicenter case-control study of 326 cases and 748 controls. Participants were sub-grouped into four categories according to NSAID exposure and genetic profile. We estimated odds ratios (ORs) and their 95% confidence intervals (CI) using generalized linear mixed models for dependent binomial variables and then calculated the measures of interaction, synergism index (S), and relative excess risk due to interaction (RERI). We undertook stratified analyses by the type of NSAID (aspirin, non-aspirin). Results: We observed an excess risk of UGIH due to an interaction between any NSAID, nonaspirin NSAIDs or aspirin and carrying certain SNPs. The greatest excess risk was observed for carriers of: rs2180314:C>G [any NSAID: S¼3.30 (95%CI: 1.24–8.80), RERI ¼4.39 (95%CI: 0.70–8.07); non-aspirin NSAIDs: S¼3.42 (95%CI: 1.12–10.47), RERI ¼3.97 (95%CI: 0.44–7.50)], and rs4809957:A>G [any NSAID: S¼2.11 (95%CI: 0.90–4.97), RERI ¼3.46 (95%CI: 0.40–7.31)]. Aspirin use by carriers of rs6664:C>T is also associated with increased risk of UGIH [OR aspirin(þ),wild-type : 2.22 (95%CI: 0.69–7.17) vs. OR aspirin(þ),genetic-variation : 7.72 (95%CI: 2.75–21.68)], yet larger sample size is needed to confirm this observation. Conclusions: The joint effect of the SNPs s2180314:C>G and rs4809957:A>G and NSAIDs are more than three times higher than the sum of their individual effects. Personalized prescriptions based on genotyping would permit a better weighing of risks and benefits from NSAID consumption. KEY MESSAGES Multicenter case-control study of the effect of genetic variations involved in drug metabolism on upper gastrointestinal haemorrhage (UGIH) induced by NSAIDs (aspirin and non-aspirin). There is a statistically significant additive synergism interaction between certain genetic polymorphisms and NSAIDs on UGIH: rs2180314:C>G and rs4809957:A>G. The joint effect of ARTICLE HISTORY Received 26 August 2021 Revised 24 November 2021 Accepted 5 December 2021 KEYWORDS Aspirin; genetic variation; interaction; non-steroidal anti-inflammatory drugs; upper gastrointestinal haemorrhage CONTACT Narmeen Mallah [email protected] Department of Preventive Medicine, Faculty of Medicine, University of Santiago de Compostela, c/San Francisco s/n., 15 786 Santiago de Compostela, A Coru~ na, Spain ß2022 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. ANNALS OF MEDICINE 2022, VOL. 54, NO. 1, 379–392 https://doi.org/10.1080/07853890.2021.2016940 each of these single nucleotide polymorphisms and NSAIDs on UGIH is more than three times higher than the sum of their individual effects. Genetic profiling and personalized prescriptions would be useful in managing the risks and benefits associated with NSAIDs. 1. Introduction Adverse effects of non-steroidal anti-inflammatory drugs (NSAIDs) were associated with heavy health and economic burdens [1,2]. Upper gastrointestinal haemorrhage (UGIH) is a frequent adverse effect of NSAID treatment that can be life-threatening [3]. Nonetheless, NSAIDs continue to be the most prescribed drugs worldwide [4]. Furthermore, it is well-established that aspirin plays an important prophylactic role against highly incident diseases that are associated with elevated mortality rates, such as several types of cancer and cardiovascular events [5–12]. Nevertheless, the association of aspirin with gastrointestinal bleeding has discouraged the adoption of this drug as a general prophylactic measure against disorders with great public health impact [13]. In addition, gastrointestinal symptoms in patients who used aspirin to protect against cardiovascular events had led to treatment interruption [14], and consequently to an increase in cardiovascular risk [15,16]. Marked interindividual differences with respect to their response to NSAIDs have long been recognized and attributed to many factors including genetic variations in metabolizing enzymes [17–20]. Several studies also reported a possible relationship between genetic variations in users of NSAIDs and gastrointestinal disorders [21–27]. In this context, genetic pharmacokinetic factors are of special importance since variations in genes involved in drug metabolism might alter their expression and thus increase the risk of undesirable effects like bleeding and cardiovascular events. Therefore, identifying patients at risk of UGIH based on their genetic background and personalized NSAID prescriptions might help weigh the risks and benefits associated with each type of NSAIDs and thus avoid adverse effects in susceptible individuals. Currently, there is a lack of knowledge about the effect of variations in genes involved in drug metabolism on the risk of UGIH in general, and in NSAID users in specific. Taking into account the considerable morbidity and mortality rates of UGIH [28,29], and the wide spectrum of NSAID benefits, we carried out a multicenter case-control study that primarily aimed at testing the modification effect of 16 genetic polymorphisms involved in drug metabolism on the risk of NSAIDs-related UGIH. As a secondary objective of this study, we investigated the modification effect of those 16 genetic polymorphisms on the risk of nonaspirin NSAIDs-related UGIH as well as on aspirinrelated UGIH. 2. Materials and methods 2.1. Study settings and design This study represents a continuation of a previous full case-control study (i.e. case-control encompassing exposed and non-exposed patients to NSAIDs, on the contrary to other partial case-control studies that include only exposed patients) [30], published elsewhere, and shares the same protocol [31,32]. Patients were recruited from four hospitals in Spain (Barcelona, Galdakao, Santiago de Compostela, and Valladolid), between January 2004 and November 2007 and between January 2013 and October 2015. The study protocol was approved by the ethics committee of each participating centre (Barcelona: CEIC protocol number: Es38121226Z; Euskadi: CEIC-E protocol number: PI2013101; Galicia: CEIC-G protocol number: 2013/ 263 and Valladolid: CEIC-VA-ESTE-HCUV protocol number: PI-14-142). The participants provided written informed consent before enrolment in the study. 2.2. Definition of cases and controls Cases were patients admitted to the hospital with symptoms of UGIH that were diagnosed surgically or endoscopically. Eligible cases were included irrespective of the grade of UGIH severity. For each case, controls matched by the hospital, gender, and age (±5 years) were selected. To avoid selection bias due to excessive intake of NSAIDs, controls were either outpatients or patients enrolled from the preoperative unit among subjects who were about to undergo any of the following non-painful mild surgeries which were unrelated to the use of NSAIDs: plastic surgery, inguinal or umbilical hernia (strangulated or programmed), lipoma, varicotomy, prostatic adenoma, prostatic hyperplasia, thyroid nodules and thyroglossal cyst (euthyroid), eye cataract, phimosis, 380 N. MALLAH ET AL. ear pinning, vocal cord cyst, tubal ligation, and septoplasty. To ensure that all subjects belong to the same source of population, they were recruited from patients and outpatients attended by the same hospitals. All patients were biologically unrelated. The analysis was restricted to European participants to control for the risk of stratification bias [33]. We used the native language of the participants and their parents as a proxy of ethnicity [34–37]. Patients with a history of neoplasia, liver cirrhosis, or coagulopathy were excluded to control for the risk of Berkson’s bias [38]. The inclusion and exclusion criteria of the cases and controls are specified in more detail in Table 1. 2.3. Data collection Both cases and controls were thoroughly interviewed by trained health personnel, using a questionnaire specifically designed for this study. The collected data include participants’sociodemographic characteristics, clinical antecedents, smoking habits, alcohol and caffeine consumption, the motive for hospital admission, underlying symptomatology (for cases), the motive for Table 1. Motives of the exclusion of cases and controls from the study. Reasons of exclusion † EMPHOGEN I (2004–2007) EMPHOGEN II (2013–2015) CASES (N¼3731) 3120 611 Primary exclusions (N¼2655) 2147 508 Age <18 31 2 Excludable endoscopic diagnosis ‡ 1213 377 History of UGIH 121 18 Intrahospital UGIH 89 5 UGIH without endoscopic or surgical diagnosis from admission to discharge 121 3 Nasogastric or percutaneous tube carrier 75 2 <3 months’residence in study area 42 7 Admission time <24 h 208 8 Admission not due to UGIH 154 80 Death 02 Other 93 4 Secondary exclusions (N¼744) 646 98 Refusal to sign informed consent form 21 0 Occurred at weekend or vacations period 57 21 Death 11 2 Endoscopy performed more than 48 h after admission 83 39 Discharge from hospital or visit to healthcare facility in the 15 days prior to admission 54 20 Severe condition 71 Psychological disorders 12 4 Illiterate 20 Deaf or blind 10 Lives in a residence or closed institution and does not know the drugs taken 7 1 Refusal to answer or failure to complete the interview 12 5 Impossible to conduct interview within the 15-day period preceding admission 6 4 Admission time <24 h 01 Other 373 0 Excluded from analysis (N¼332) 327 5 Non-white patients 40 Unavailable biological material 323 5 CONTROLS (N¼1073) 1071 2 Refused to sign informed consent form 45 0 Age <18 10 History of disease 11 1 Intrahospital UGIH 89 0 Nasogastric or percutaneous tube carrier 2 0 <3 months’residence in study area 1 0 Severe condition 10 Psychological disorders 10 Deaf or blind 30 Refusal to answer or failure to complete the interview 80 0 Impossible to conduct interview within the 15-day period preceding admission 60 0 Date of last admission 01 Other 13 0 Non-white patients 15 0 Unavailable biological material 749 0 † Cases and controls were excluded upon presenting one or more exclusion criteria. ‡ Excludable endoscopic diagnosis included gastritis, esophagitis, oesophageal varices, gastric or duodenal neoplasia, Mallory-Weiss syndrome, angiodysplasia, anastomotic ulcers, diverticulitis, acute alcohol intoxication, hiatal hernia, and papule. Bold values represent the total per reason of exclusion group and study period. ANNALS OF MEDICINE 381 the scheduled surgery (for controls), previous episodes of gastric diseases, and exposure to pharmaceutical drugs (including the medicine’s daily dose and indication). Direct relatives or healthcare assistants, who took care of the patient’s medication, could attend and participate in the interview, but only data confirmed by the patient were considered. When the participant was not able to remember any of the requested information, the interview was repeated on a posterior date, or the patient was contacted by telephone if s/he had been discharged from the hospital. In case the patient doubted or was uncertain about specific information, that information was confirmed later by consulting the medical records of the patient. Index dates were established to ascertain any exposure to NSAIDs. Information on NSAID exposure was extracted from patients’medical records, but the researchers were blind to patients’use of NSAIDs. For the cases, the index date was the day of onset of the first signs or symptoms of UGIH, while for the controls it was the day of the interview. NSAIDs exposure was considered if the consumption took place in the week preceding the index date [39–41]. For ease of recall, a catalog of prompt cards of the most consumed NSAID boxes was shown to the participants during the interview. The reliability of the interview was rated on a scale of 0–10 as perceived by the interviewer, where zero means that the answers provided by the patient were completely unreliable. Patients whose interview was rated by zero were excluded from the study. A 5 ml blood sample was withdrawn from each participant and stored in EDTA tubes or as spots on IsoCode papers at 80 C until genotyping. 2.4. Risk factors associated with UGIH The following co-variables which were known to affect the risk of UGIH were considered: (1) previous infection with Helicobacter pylori; (2) therapeutic groups, such as proton pump inhibitors or oral anticoagulants; (3) digestive system disorders classified according to the patient’s history of ulcer and bleeding (none or dyspepsia; ulcer; or bleeding); and (4) the reliability of the interview. 2.5. Helicobacter pylori determination The presence of anti-H. pylori IgG antibodies in human serum were determined using the commercial ELISA kits: Human Anti-Helicobacter pylori IgG ELISA Kit (ab108736, Abcam, Cambridge, England), and Captia TM H. pylori IgG EIA (ref: 2346400, Trinity Biotech Captia, Co. Wicklaw, Ireland), and following the manufacturer’s protocol. The participants were inquired if they had previously been treated against H. pylori infection to avoid any false-positive results caused by old infections. 2.6. Single nucleotide polymorphisms (SNPs) selection and genotyping A comprehensive list of SNPs involved in gastrointestinal disorders (bleeding or ulcer) was retrieved by reviewing research reports published in MEDLINE until April 2017. The reference numbers (rs number) of the selected SNPs were confirmed using PubMed [42]. Subsequently, the function of the corresponding genes and the clinical significance of the genetic variations were identified through a literature review. Finally, SNPs in genes that may influence drug metabolism were selected for genotyping [25,26]. DNA was extracted from blood stored in EDTA tubes using chemagic TM DNA Buffy Coat 200 Kit H96 (PerkinElmer, reference number CMG-713) and from blood spots using chemagic TM DNA Blood 200 Kit H96 (PerkinElmer, reference number CMG-717). Extracted DNA was then quantified using Quant-iT TM PicoGreen TM dsDNA Assay Kits (ThermoFisher Scientific, reference number P7589). DNA concentration was normalized at 10–20 ng/ml in a minimum total volume of 40 ml. Samples were genotyped in a phonotype-blind process. iPlex V R Gold chemistry and MassARRAY platform were used according to the manufacturer’s instructions (Agena Bioscience, San Diego, USA). Genotyping assays were designed using the Agena Bioscience MassARRAY Assay Designer 4.1 software. All assays were performed in 384-well plates, including negative controls and a trio of Coriell samples for quality control. The reproducibility of 7% of the samples was also checked between and/or within plates. The compliance of the SNPs with Hardy–Weinberg equilibrium was checked using the SNPassoc Library of the R package (Version 1.9-2) [43–45]. In addition, all cluster plots were manually inspected by trained personnel using MassArray Typer software. 2.7. Statistical analysis To determine any interaction between each of the 16 SNPs and NSAID exposure on the risk of UGIH, participants were grouped according to their genotype and NSAID exposure. Stratified analysis by the type of 382 N. MALLAH ET AL. NSAID (any NSAID, non-aspirin NSAIDs, and aspirin) was carried out. In each analysis, the following four groups of participants were obtained: [group 1: drug(þ), wild-type; group 2: drug(þ), genetic-variation; group 3: drug(), genetic-variation; and group 4: drug(), wild-type]. Adjusted odds ratios (ORs) of UGIH were calculated in each group and then checked for any potential interaction between the presence of a genetic variation and drug exposure. The group of subjects who were not exposed to the studied drug category (any NSAID, non-aspirin NSAIDs, or aspirin) and who were carriers of the wild-type genotype of the analyzed SNP (group 4) was used as the reference category for the estimations of the interactions. ORs and their 95% confidence intervals (CI) were estimated by generalized linear mixed models for dependent binomial variables [46]. In the construction of the models, patients were placed at level 1; the strata (each case and its matched controls) at level 2; the hospital at level 3; and the period of patients’ recruitment at level 4. A random-effects model was used to examine the effect of the patients’recruitment period, and a nested random-effects model was applied for the strata of cases and controls and health centre. The lmer function of the lme4 R package (version 1.1-21) was applied in the estimation of the models [47]. Potential confounding variables were introduced in the model if they modified the OR of the main variable by at least 10% and provided that the Schwartz’s Bayesian Information Criterion improved [48]. The recommendations given by Knol and colleagues were followed to explore any potential interaction between NSAIDs and genetic polymorphisms, whereby we estimated the relative excess risk due to interaction (RERI) and the synergism index (S) along with their 95% CI [49–52]. 3. Results 3.1. Clinical data collection One thousand and seventy-four patients (326 cases and 748 controls) fulfilled the inclusion criteria and were included in the final analysis. The flow of subjects and the motives of exclusion are presented in Figure 1 and Table 1. The patients’ demographic and clinical characteristics are presented in Table 2. 3.2. Genotyping All genotyped samples were included in the analysis. The reproducibility of the 7% replicated random samples was 100%. All SNPs showed an acceptable genotype call rate: 98%. Both the calculations of the Hardy–Weinberg equilibrium (p<.001) and the manual inspection of the cluster plots confirmed that the controls were in equilibrium in terms of the corresponding polymorphisms (Table 3). 3.3. Risk estimation and modification of effect The odds of UGIH varied according to the genotype and NASID (aspirin or non-apsirin) exposure. 3.3.1. Genotypes associated with high excess of risk of UGIH The presence of certain genetic variations increases the odds of UGIH in users of any NSAID, non-aspirin NSAIDs, or aspirin as compared to users with wildtype genotypes (Table 4). rs2180314:C>G: Any NSAID use by carriers of rs2180314:C>G is associated with substantially higher odds of UGIH in comparison with NSAID users carrying the wild-type genotype [OR drug(þ),wild-type : 3.17 (95%CI: Figure 1. Flow of the cases and the controls throughout the two stages of the project. ANNALS OF MEDICINE 383 1.79–5.63) vs. OR drug(þ),genetic variation : 7.30 (95%CI: 4.27–12.48)]. The measures of interaction showed a statistically significant high excess risk of UGIH from the interaction between NSAID and rs2180314:C>G [S¼3.30 (95%CI: 1.24–8.80), RERI ¼4.39 (95%CI: 0.70–8.07)]. Similar findings were observed when the analysis was stratified by the type of NSAID: nonaspirin NSAIDs [S¼3.42 (95%CI: 1.12–10.47), RERI ¼ 3.97 (95%CI: 0.44, 7.50)] and aspirin [S¼7.65 (95%CI: 0.81, 72.33), RERI ¼8.39 (95%CI: 4.20, 20.99)], though the interaction estimates did not reach statistical significance in aspirin category probably due to the limited number of aspirin users. rs4809957:A>G: Substantially higher ORs of UGIH were observed for patients carrying rs4809957:A>G who are on treatment involving any NSAID [OR wild-type: 4.12 (95%CI: 2.18–7.79) vs. OR genetic-variation :7.57(95%CI:4.43–12.93)], or nonaspirin NSAID [OR wild-type: 3.99 (95%CI: 2.06–7.75) vs. OR genetic-variation : 7.15 (95%CI: 4.10–12.46] in comparison with drug users carriers of the wild type genotype (Table 4). This excess in risk is suggested Table 2. Description of the cases and controls included in the study. Characteristic Cases (N¼326) @(%) Controls (N¼748) @(%) OR (95% CI) p-Value Age <45 41 (12.6%) 95 (12.7%) 1 45–65 117 (35.9%) 271 (36.2%) 1.05 (0.68–1.63) .8327 >65 161 (49.4%) 370 (49.5%) 1.01 (0.66–1.54) .9757 missing 7 (2.1%) 12 (1.6%) BMI Underweight 10 (3.1%) 24 (3.2%) 0.74 (0.33–1.62) .4588 Normal weight 114 (35.0%) 204 (37.3%) 1 Overweight 128 (39.3%) 374 (50.0%) 0.61 (0.45–0.83) .0201 Obese 68 (20.9%) 144 (19.3%) 0.85 (0.58–1.24) .8676 Missing 6 (1.8%) 2 (0.3%) Gender Male 236 (72.4%) 559 (74.7%) 1 Female 87 (26.7%) 189 (25.3%) 1.18 (0.87–1.6) .2852 Missing 3 (0.9%) 0 Arthrosis No 219 (67.2%) 469 (62.7%) 1 Yes 86 (26.4%) 216 (28.9%) 0.86 (0.63–1.17) .3303 Missing 21 (6.4%) 63 (8.4%) Helicobacter pylori No or uncertain 27 (8.3%) 138 (18.4%) 1 Yes 276 (84.7%) 574 (76.7%) 2.54 (1.62–3.99) <.0001 Missing 23 (7.1%) 36 (4.8%) Source of information Patients 259 (79.4%) 672 (89.8%) 1 Healthcare assistant/direct relative 67 (20.6%) 76 (10.2%) 2.35 (1.62–3.42) <.0001 Interview variables Number of interviews conducted 1 274 (84.0%) 644 (86.1%) 1 2 52 (16.0%) 104 (13.9%) 1.27 (0.81–1.99) .2927 Reliability of the interview <5 13 (4.0%) 20 (2.7%) 1 5–7 36 (11%) 78 (10.4%) 0.67 (0.29–1.54) .3466 7–9 134 (41.1%) 310 (41.4%) 0.70 (0.33–1.48) .3540 9 143 (43.9%) 340 (45.5%) 0.67 (0.31–1.41) .2855 Personal history of gastrointestinal disorders None or dyspepsia 208 (63.8%) 647 (86.5%) 1 Ulcer 48 (14.7%) 56 (7.5%) 2.74 (1.79–4.21) <.0001 Bleeding 70 (21.5%) 45 (6.0%) 4.79 (3.15–7.27) <.0001 Co-medications with drugs that are not NSAIDs Analgesics not narcotics No 272 (83.4%) 692 (92.5%) 1 Yes 54 (16.6%) 56 (7.5%) 2.74 (1.81–4.15) <.0001 Inhibitors of the proton pump No 290 (89.0%) 682 (91.2%) 1 Yes 36 (11.0%) 66 (8.8%) 1.2 (0.77–1.88) .4202 Antiaggregant No 261 (80.1%) 662 (88.5%) 1 Yes 65 (19.9%) 86 (11.5%) 1.94 (1.34–2.8) .0005 Anticoagulants No 291 (89.3%) 716 (95.7%) 1 Yes 35 (10.7%) 32 (4.3%) 3.09 (1.85–5.15) <.0001 Inhibitors of COX2 No 323 (99.1%) 742 (99.2%) 1 Yes 3 (0.9%) 6 (0.8%) 0.88 (0.21–3.77) .8659 384 N. MALLAH ET AL. by the interaction estimates which are on the borderline of statistical significance: any NSAID [S¼2.11 (95%CI: 0.9–4.97); RERI ¼3.46 (95%CI: 0.40–7.31)], non-aspirin NSAIDs [S¼2.03 (95%CI: 0.81–5.08); RERI ¼3.11 (95%CI: 0.82–7.05)]. The interaction estimates for aspirin exposure— rs4809957:A>G are inconclusive due to the limited number of observations (Table 4). 3.3.2. Genotypes associated with moderate excess of risk of UGIH An increased odds of UGIH was observed from any NSAID, non-aspirin NSAIDs, or aspirin intake by both the carriers of the genetic variants (rs4715332:C>A and rs4715354:G>A) or their corresponding wild-type genotype (Table 4). However, carriers of the genetic variation were at higher odds of UGIH than carriers of the wild-type genotype. A moderate non-statistically significant excess risk was observed for the presence of these genetic variants: rs4715332:C>A [any NSAID (S¼1.64; RERI ¼2.34), non-aspirin NSAIDs (S¼1.75; RERI ¼2.25) and aspirin (S¼1.61; RERI ¼1.99)] and rs4715354:G>A [any NSAID (S¼1.37; RERI ¼1.53), non-aspirin NSAIDs (S¼1.30; RERI ¼1.16) and aspirin (S¼1.26; RERI ¼0.88)] (Table 4). Similar observations were observed for aspirin users carrying rs6664:C>T. Aspirin users carrying this genetic variant had substantially higher odds of UGIH in comparison with patients carrying the wild-type genotype [OR wild-type : 2.22 (95%CI: 0.69–7.17) vs. OR genetic-variation : 7.72 (95%CI: 2.75–21.68)]. Nonetheless the number of aspirin users in this subgroup was limited which Table 3. Prevalence of the studied genotypes and Hardy–Weinberg equilibrium test. Gene Single nucleotide polymorphism reference number Genotypes Cases N(%) Controls N(%) Hardy–Weinberg equilibrium p-value CYP4F11, cytochrome P450 family 4 subfamily F member 11 rs1060463 CC 64 (19.6) 127 (17.0) 0.03 CT 165 (50.6) 398 (53.2) TT 97 (29.8) 223 (29.8) CYP2A6, cytochrome P450 family 2 subfamily A member 6 rs28399433 AA 288 (88.3) 662 (88.5) Not applicable AC 36 (11.0) 80 (10.7) CYP2B6, cytochrome P450 family 2 subfamily B member 6 rs36079186 TT 326 (100.0) 748 (100.0) Not applicable CYP4F11, cytochrome P450 family 4 subfamily F member 11 rs3765070 AA 65 (19.9) 128 (17.1) 0.03 AG 165 (50.6) 398 (53.2) GG 96 (29.4) 222 (29.7) CYP2A7, cytochrome P450 family 2 subfamily A member 7 rs3869579 AA 94 (28.8) 214 (28.6) 0.05 AG 147 (45.1) 346 (46.3) GG 85 (26.1) 188 (25.1) CYP11B2, cytochrome P450 family 11 subfamily B member 2 rs4536 CT 7 (2.1) 22 (2.9) Not applicable TT 318 (97.5) 725 (96.9) CYP24A1, cytochrome P450 family 24 subfamily A member 1 rs4809957 AA 200 (61.3) 450 (60.2) 0.09 AG 108 (33.1) 271 (36.2) GG 18 (5.5) 27 (3.6) CYP2F1, cytochrome P450 family 2 subfamily F member 1 rs58285195 CC 2 (0.6) 1 (0.1) 0.62 CT 29 (8.9) 51 (6.8) TT 295 (90.5) 696 (93.0) GSTP1, glutathione S-transferase pi 1 rs1695 AA 132 (40.5) 321 (42.9) 0.52 AG 157 (48.2) 332 (44.4) GG 37 (11.3) 95 (12.7) GSTA2, glutathione S-transferase alpha 2 rs2180314 CC 50 (15.3) 104 (13.9) 0.13 CG 139 (42.6) 318 (42.5) GG 129 (39.6) 309 (41.3) GSTA1, glutathione S-transferase alpha 1 rs4715332 AA 104 (31.9) 259 (34.6) 0.29 AC 159 (48.8) 374 (50.0) CC 63 (19.3) 114 (15.2) GSTA5, glutathione S-transferase alpha 5 rs4715354 AA 55 (16.9) 143 (19.1) 0.71 AG 160 (49.1) 362 (48.4) GG 110 (33.7) 243 (32.5) NAT2, N-acetyltransferase 1 rs1799931 AA 1 (0.3) 1 (0.1) 0.45 AG 16 (4.9) 40 (5.3) GG 309 (94.8) 707 (94.5) CHST2, carbohydrate sulfotransferase 2 rs6664 CC 177 (54.3) 419 (56.0) 0.34 CT 128 (39.3) 275 (36.8) TT 21 (6.4) 54 (7.2) ALB_c, albumin rs3756067 AA 37 (11.3) 91 (12.2) 0.33 AG 136 (41.7) 320 (42.8) GG 145 (44.5) 332 (44.4) SLCO3A1, solute carrier organic anion transporter family member 3A1 rs2283458 AA 33 (10.1) 100 (13.4) 1.00 AG 169 (51.8) 348 (46.5) GG 124 (38.0) 300 (40.1) ANNALS OF MEDICINE 385 Table 4. Odds ratios (OR) for UGIH stratified by patients’genotype and NSAID (any NSAID, aspirin, non-aspirin) exposure and their interaction represented by synergism index (S) and relative excess risk due to interaction (RERI). SNP (reference number) Wildtype genotype Genetic variation RERI (95% CI) S (95% CI)N(%) (cases/controls) OR † (95% CI); p-value N(%) (cases/controls) OR † (95% CI); p-value rs2180314:C >G Any NSAID (No) 91 (26.1)/258 (73.9) 1 99 (21.4)/363 (78.6) 0.74 (0.50, 1.09); p¼.1229 4.39 (0.70, 8.07) 3.3 (1.24, 8.8) Any NSAID (Yes) 48 (44.4)/60 (55.6) 3.17 (1.79, 5.63); p¼.0001 80 (61.5)/50 (38.5) 7.30 (4.27, 12.48); p<.0001 Non-aspirin NSAID (No) 100 (27.2)/267 (72.8) 1 110 (22.9)/370 (77.1) 0.75 (0.52, 1.09); p¼.1343 3.97 (0.44, 7.50) 3.42 (1.12, 10.47) Non-aspirin NSAID (Yes) 39 (43.3)/51 (56.7) 2.89 (1.57, 5.31); p¼.0006 69 (61.6)/43 (38.4) 6.61 (3.82, 11.46); p<.0001 Aspirin intake (No) 115 (30.4)/263 (69.6) 1.0 142 (28.4)/358 (71.6) 0.92 (0.66–1.30); p¼.6481 8.39 (4.20, 20.99) 7.65 (0.81–72.33) Aspirin intake (Yes) 10 (47.6)/11(52.4) 2.34 (0.84–6.49); p¼.1031 14 (70.0)/6 (30.0) 10.65 (3.27–34.71); p¼.0001 rs4809957:A >G Any NSAID (No) 68 (23.4)/222 (76.6) 1 127 (23.5)/414 (76.5) 0.99 (0.66, 1.47); p¼.9515 3.46 (0.40, 7.31) 2.11 (0.9, 4.97) Any NSAID (Yes) 40 (44.9)/49 (55.1) 4.12 (2.18, 7.79); p<.0001 91 (59.1)/63 (40.9) 7.57 (4.43, 12.93); p<.0001 Non-aspirin NSAID (No) 74 (24.3)/230 (75.7) 1 141 (25.0)/422 (75.0) 1.04 (0.71, 1.53); p¼.8433 3.11 (0.82, 7.05) 2.03 (0.81, 5.08) Non-aspirin NSAID (Yes) 34 (45.3)/41 (54.7) 3.99 (2.06, 7.75); p<.0001 77 (58.3)/55 (41.7) 7.15 (4.10, 12.46); p<.0001 Aspirin intake (No) 92 (28.8)/227 (71.2) 1.0 170 (29.4)/409 (70.6) 1.09 (0.76–1.54); p¼.6474 6.04 (1.89, 13.98) 7.72 (0.38–158.17) Aspirin intake (Yes) 6 (40.0)/9 (60.0) 1.81 (0.45–7.37); p¼.4045 18 (69.2)/8 (30.8) 7.94 (2.99–21.13); p<.0001 rs6664:C >T Any NSAID (No) 75 (24.4)/233 (75.6) 1 120 (22.9)/403 (77.1) 1.13 (0.76, 1.68); p¼.5438 1.45 (6.05, 3.15) 0.78 (0.37, 1.65) Any NSAID (Yes) 53 (55.8)/42 (44.2) 7.47 (4.02, 13.88); p<.0001 78 (52.7)/70 (47.3) 6.15 (3.60, 10.50); p<.0001 Non-aspirin NSAID (No) 83 (25.6)/241 (74.4) 1 132 (24.3)/411 (75.7) 1.16 (0.79, 1.70); p¼.4486 3.37 (8.77, 2.03) 0.55 (0.24, 1.25) Non-aspirin NSAID (Yes) 45 (57.0)/34 (43.0) 8.38 (4.33, 16.18); p<.0001 66 (51.6)/62 (48.4) 5.16 (3.00, 8.90); p<.0001 Aspirin intake (No) 104 (31.0)/231 (69.0) 1.0 158 (28.1)/405 (71.9) 0.95 (0.67–1.34); p¼.7793 5.55 (2.60, 13.70) 5.74 (0.49–67.83) Aspirin intake (Yes) 8 (47.1)/9 (52.9) 2.22 (0.69–7.17); p¼.1829 16 (66.7)/8 (33.3) 7.72 (2.75–21.68); p¼.0001 rs2283458:A >G Any NSAID (No) 107 (26.7)/294 (73.3) 1 88 (20.5)/342 (79.5) 0.69 (0.47, 1.01); p¼.0532 0.56 (2.62, 3.73) 1.15 (0.50, 2.64) Any NSAID (Yes) 62 (53.4)/54 (46.6) 4.92 (2.83, 8.58); p<.0001 69 (54.3)/58 (45.7) 5.17 (3.07, 8.70); p<.0001 Non-aspirin NSAID (No) 117 (28.1)/300 (71.9) 1 98 (21.8)/352 (78.2) 0.71 (0.49, 1.03); p¼.068 0.77 (2.41, 3.96) 1.24 (0.5, 3.09) Non-aspirin NSAID (Yes) 52 (52.0)/48 (48.0) 4.46 (2.51, 7.93); p<.0001 59 (55.1)/48 (44.9) 4.95 (2.86, 8.57); p<.0001 Aspirin intake (No) 134 (31.7)/289 (68.3) 1.0 128 (26.9)/347 (73.1) 0.78 (0.56–1.08); p¼.1369 0.02 (6.07, 6.10) 1.01 (0.14–7.55) Aspirin intake (Yes) 13 (65.0)/7 (35.0) 4.24 (1.38–13.06); p¼.0118 11 (52.4)/10 (47.6) 4.03 (1.46–11.15); p¼.0072 rs1060463:C >G/C >T Any NSAID (No) 98 (22.5)/337 (77.5) 1 97 (24.5)/299 (75.5) 1.36 (0.93, 1.99); p¼.1143 0.73 (3.88, 5.33) 1.12 (0.55, 2.29) Any NSAID (Yes) 67 (52.3)/61 (47.7) 6.67 (3.94, 11.28); p<.0001 64 (55.7)/51 (44.3) 7.75 (4.41, 13.62); p<.0001 Non-aspirin NSAID (No) 103 (22.9)/346 (77.1) 1 112 (26.8)/306 (73.2) 1.42 (0.98, 2.05); p¼.0603 0.019 (4.65, 4.69) 1 (0.46, 2.19) Non-aspirin NSAID (Yes) 62 (54.4)/52 (45.6) 6.53 (3.81, 11.19); p<.0001 49 (52.7)/44 (47.3) 6.97 (3.81, 12.74); p<.0001 Aspirin intake (No) 138 (28.8)/342 (71.3) 1.0 124 (29.7)/294 (70.3) 1.28 (0.91–1.79); p¼.1542 2.07 (5.66, 9.79) 1.62 (0.27–9.83) Aspirin intake (Yes) 8 (50.0)/8 (50.0) 4.05 (1.26–12.98); p¼.0186 16 (64.0)/9 (36.0) 6.39 (2.35–17.38); p¼.0003 rs1695:A >G Any NSAID (No) 94 (24.5)/289 (75.5) 1 101 (22.5)/347 (77.5) 0.82 (0.56, 1.20); p¼.3084 0.11 (3.67, 3.46) 0.98 (0.44, 2.18) Any NSAID (Yes) 63 (59.4)/43 (40.6) 5.70 (3.27, 9.92); p<.0001 68 (49.6)/69 (50.4) 5.41 (3.19, 9.18); p<.0001 Non-aspirin NSAID (No) 101 (25.4)/297 (74.6) 1 114 (24.3)/355 (75.7) 0.90 (0.62, 1.30); p¼.5776 1.24 (5.08, 2.60) 0.75 (0.32, 1.77) Non-aspirin NSAID (Yes) 56 (61.5)/35 (38.5) 6.08 (3.40, 10.88); p<.0001 55 (47.4)/61 (52.6) 4.74 (2.72, 8.27); p<.0001 Aspirin intake (No) 133 (31.4)/290 (68.6) 1.0 129 (27.2)/346 (72.8) 0.83 (0.59–1.17); p¼.2858 1.14 (5.04, 7.31) 1.44 (0.18–11.37) Aspirin intake (Yes) 9 (56.3)/7 (43.8) 3.73 (1.14–12.21); p¼.0295 15 (60.0)/10 (40.0) 4.70 (1.76–12.52); p¼.0020 rs3756067:G >A (continued) 386 N. MALLAH ET AL.