Shaping current European mitochondrial haplogroup frequency in response to infection: the case of SARS-CoV-2 severity

communica ions biology A icle
h ps://doi.o g/10.1038/s42003-024-07314-y
Shaping cu en Eu opean mi ochond ial
haplog oup equency in esponse o
in ec ion: he case o SARS-CoV-2 se e i y
Check o upda es
José Luis Cab e a-Ala con 1,2, Raquel C uz 3,4,Ma inaRosa-Mo eno 1, Ana La o e-Pellice 5,
Sil ia Diz de Almeida 3,4, Scou ge Coho G oup*, José A. Riancho2,6,7,8, Augus o Rojas-Ma inez9,
Ca los Flo es10,11,12, Pablo Lapunzina 3,13, Fá ima Sánchez-Cabo 1, Ángel Ca acedo3,4,14 &
José An onio En iquez 1,2
The equency o mi ochond ial DNA haplog oups (m DNA-HG) in humans is known o be shaped by
mig a ion and epopula ion. Moun ing e idence indica es ha m DNA-HG a e no pheno ypically
neu al, and selec ion may con ibu e o i s dis ibu ion. Haplog oup H, he mos abundan in Eu ope,
imp o ed su i al in sepsis. He e we de eloped a andom o es ained model o mi ochond ial
haplog oup calling using da a p ocu ed om GWAS a ays. Ou esul s e eal ha in he con ex o he
SARS-CoV-2 pandemic, HV b anch we e ound o ep esen p o ec i e ac o s agains he
de elopmen o c i ical SARS-CoV-2 in an analysis o 14,349 pa ien s. These esul s highligh he ole
o m DNA in he esponse o in ec ious diseases and suppo he p oposal ha i s expansion and
popula ion p opo ion has been influenced by selec ion h ough successi e pandemics.
Se e e acu e espi a o y synd ome co ona i us 2 (SARS-CoV-2) disco e ed
in Wuhan, China, in 2019, ep esen ed a global pandemic, esponsible o
a ound 18.2 million dea hs wo ldwide, conside ing only a pe iod be ween
Jan 1s , 2020, and Dec 31s , 20211. Al hough, being SARS-Co -2 he la es
pandemic wi h se e e consequences, h oughou his o y mankind has been
con on ed wi h se e al in ec ious agen s, which ha e shaped ou geno ype.
By ex ension his selec i e p ocess has also shaped he mi ochond ial DNA
(m DNA), and he componen s encoded by i . F om his pe spec i e,
mi ochond ial haplog oup (HG) ma ke s a e a ia ions in m DNA accu-
mula ed in human popula ions due o ma ilineal inhe i ance, ha allows o
ace indi iduals ances y and he classifica ion o indi iduals in o HGs2.
Se e al o hese HG ma ke s de e mine amino acid changes in subuni s
encoded by m DNA o he oxida i e phospho yla ion sys em (OxPhos).
The OxPhos sys em ep esen an ac ual hub o in eg a ion o cell me abo-
lism, ha mus adap o se e al physiological si ua ions3.
Al hough mos gene ic s udies analyzing suscep ibili y and se e i y
o human in ec ious diseases ha e ocused on he immune sys em4, he e
is e idence o he influence o mi ochond ial HG on su i al o sepsis,
ela i e o he deg ees o hea ing ha indi iduals can a o d5.I isknown
ha he se e i y o SARS-CoV-2 is highly co ela ed wi h he como -
bidi ies, age and sex o he pa ien s6,7. The e o e, in ela ion o hese
known isk ac o s, in his s udy we demons a e he ele ance o
mi ochond ial HV b anch (HGs H, V and HV) as p o ec i e ac o o
SARS-CoV-2 se e i y independen o gene al gene ic backg ound,
como bidi ies, age o sex, ein o cing he idea ha mi ochond ia play a
ele an ole in he ou come o in ec ious disease.
Resul s
De elopmen o a machine lea ning model o pe o m HG calling
The mi ochond ial HGs we e iden ified using a andom o es model
ained on he geno ypes o 189 posi ions/p obes om ou GWAS a ay, as
ea u es. These p obes we e selec ed based on wo c i e ia: hey co e HG
ma ke s as defined by MITOMAP, and hey demons a e su ficien p obe
quali y. This model was ini ially ained on 61,134 sequences om he
MITOMAP da abase. These sequences we e p e-labeled using Haplog ep2,
which le e ages HG ma ke s ac oss he en i e mi ochond ial genome,
a he han jus he 189 posi ions ha cons i u ed ou aining da ase . We
subsequen ly alida ed ou andom o es model ex e nally by applying he
same 189 posi ions o indi iduals om he 1000 Genomes P ojec 8,who
we e simila ly labeled using Haplog ep29, based on ull mi ochond ial
sequence da a (Fig. 1, see me hods). This app oach allowed us o de e mine
mi ochond ial HGs wi h a le el o eliabili y de e mined by 3- old c oss-
alida ion (3- old CV) in aining da a-se by Cohen’s kappa coe ficien , κ=
0.98. On he o he hand, he accu acy ob ained in ex e nal alida ion was
κ=0.95. The e o e, his machine lea ning app oach has enough accu acy o
de e mine he HG o ou samples. Thus, using his ad hoc ool, we pe -
o med mi ochond ial HG calling o he 14,349 pa ien s pa icipa ing in his
s udy ob aining he HG dis ibu ion (Table 1).
A ull lis o a filia ions appea s a he end o he pape . *A lis o au ho s and hei a filia ions appea s a he end o he pape . e-mail: [email p o ec ed]
Communica ions Biology | (2025) 8:33 1
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Analysis o HG as independen isk ac o s o COVID-19 se e i y
Then, we e alua ed HGs as independen isk/p o ec i e ac o s o COVID-
19 se e i y om como bidi y, gene ic backg ound, sex, and age. As we only
had como bidi y da a o he SCOURGE coho (cases), he analysis was
pe o med in wo ways, fi s conside ing he SCOURGE coho and hen
including he con ol pa ien s in he analysis. When analyzing he
SCOURGE coho only 8,778 ou o 8,894 ha e como bidi y in o ma ion. In
afi s s ep, eg esso s o be conside ed we e fil e ed ou acco ding o hei
significance in uni a ia e models. This uni a ia e analysis conduc ed using a
logis ic eg ession model as he ini ial s ep, e ealed ha ou o all he
conside ed HGs, only he HV b anch eme ged as a p o ec i e ac o agains
se e e disease (Supplemen a y Table S1). Fu he mo e, he uni a ia e
analysis o como bidi ies indica ed ha a his o y o ascula , diges i e, onco-
hema ologic, and espi a o y diseases we e isk ac o s, while a his o y o
neu ological disease appea ed p o ec i e. Ca diac disease his o y was no
significan in ou coho (Supplemen a y Table S1). Among he 10 p incipal
componen s ep esen ing gene ic backg ound, only PC1 and PC3 we e
significan (Supplemen a y Table S1). As expec ed, age was a isk ac o o
disease se e i y, as well as sex also eme ged as a isk ac o in he same
di ec ion o ha p e iously desc ibed by o he au ho s7. Then, o gene a e a
mo e obus global mul i a ia e model, a oiding possible collinea i ies and
p oblems de i ed om he excessi e complexi y o mul i a ia e models, he
global model was buil based on he e idence collec ed om pa ial mul i-
a ia e models. The e o e, gi en he significan isk ac o s iden ified be o e,
he independence o he HV b anch as a p o ec i e ac o agains se e e
disease was e alua ed ini ially ac oss ou di e en se ings, esul ing in ou
dis inc mul i a ia e models. These models assessed he HV b anch's
independence in ela ion o como bidi ies, gene ic backg ound, age, and sex
(Supplemen a y Table S2). Fi s ly, in mul i a ia e model conside ing sig-
nifican como bidi ies, he HV b anch emained a p o ec i e ac o agains
ascula o espi a o y como bidi ies, while neu ological como bidi ies also
emained p o ec i e. The mul i a ia e model o gene ic backg ound
e ealed ha bo h he HV b anch and PC1 had p o ec i e main e ec s.
In e es ingly, when examining he HV b anch's independen e ec con-
ce ning sex, he HV b anch was no significan , while he isk e ec o sex
pe sis ed in his popula ion (Supplemen a y Table S2). Howe e , a sig-
nifican emale bias o he HV b anch was obse ed (Fishe es : OR=0.898,
CI=0.825-0.977, p- alue=0.0118). Then, we explo e he uni a ia e analysis
o he in e ac ion be ween he HV b anch and sex, ha showed a simila
end (OR=1.965; CI=1.719-2.242), indica ing ha males wi h he HV
b anch had almos wice p obabili y o de eloping se e e COVID-19.
Las ly, in he mul i a ia e model wi h age, he HV b anch main ained i s
p o ec i e e ec , and he expec ed inc eased isk due o aging was obse ed
(Supplemen a y Table S2).
By combining he findings om all hese mul i a ia e models, he
global mul i a ia e model confi med he same e ec s o all ea u es, wi h
he HV b anch being independen ly p o ec i e agains SARS-CoV-2
se e i y (Table 2). Fu he mo e, we es ed he ele ance o HV b anch,
compa ing nes ed models dele ing he HV b anch om mul i a ia e model,
using ANOVA es , confi med he ele ance and s eng h o mi ochond ial
HV b anch condi ion as p o ec i e ac o (p<0.01**).
Once he eg esso e ec s o mi ochond ial HGs on he se e i y o
COVID-19 in he SCOURGE coho we e analyzed, we p oceeded o hei
e alua ion, also including all he pa ien s (Cases+Con ols=14,379
pa ien s), epea ing he same s a egy. In o ma ion on como bidi ies is los
in his analysis. Addi ionally, he models we e adjus ed o accoun o
po en ial popula ion s a ifica ion a ising om he managemen o di e en
coho s (wi h cases ep esen ed by he SCOURGE coho and con ols).
This was add essed by applying mixed-e ec s models. These mixed models
a e c ucial o ensu ing ha he esul s o HG associa ion a e obus , eliable,
and accu a ely eflec ue biological ela ionships a he han being influ-
enced by popula ion s uc u e a i ac s. Uni a ia e analysis o all conside ed
ea u es, lea e ha HGs HV b anch, I, U, K and J showed co ela ion wi h
disease se e i y, ha ing HV b anch and I a p o ec i e ole, being HGs U, K
and J isk ac o s (Supplemen a y Table S3). Rega ding gene ic backg ound
as p incipal componen s, all PCs we e significan bu PC2 and PC7, ha
we e disca ded o downs eam analysis (Supplemen a y Table S3). Finally,
as obse edwhen analyzing SCOURGE coho , age and sex we e isk ac o s
and in he same di ec ion, (Supplemen a y Table S3). Nex , significan HGs
we e e alua ed in mul i a ia e models o check independen e ec s in 3
ames: ega ding sex, age and gene ic backg ound, (Supplemen a y
Table S4). E alua ing he independen e ec s o HGs and sex on disease
se e i y, only he HV b anch eme ged as a significan p o ec i e ac o ,
independen o sex (Supplemen a y Table S4). Explo ing he exis ence o
significan in e ac ions be ween bo h ea u es, i was ound ha he e we e
no significan in e ac ions (ANOVA o e nes ed models: p- alue=1). In
Fig. 1 | Wo kflow ollowed o ain machine
lea ning model o pe o m mi ochond ial HG
calling. The le panel shows he s a egy o aining
a andom o es model o classi y subjec s in o
mi ochond ial HGs, while he igh panel ou lines
how o pe o m ex e nal alida ion o he ained
andom o es model. *This p ocess o 3- old c oss-
alida ion (3- old CV) is di e en om he 3- old
CV fine- uning sea ch o hype pa ame e s.
h ps://doi.o g/10.1038/s42003-024-07314-y A icle
Communica ions Biology | (2025) 8:33 2
Table 1 | Cha ac e iza ion o he pa ien s pa icipa ing in he s udy
Global Case Con ol Male Female ≥65y <65y Se e e No-Se
N 14,349 8894 5455 6988 7361 4922 9417 1124 13,225
Age mean±sd 58.7 ±17.3 62.2 ±17.9 53.1 ±14.8 58.6 ±16.3 58.8 ±18.3 78.2 ±9.0 48.6 ±10.7 65.4 ±13.0 58.2 ±17.5
Female 7361 4784 2577 ––2478 4883 310 7051
Male 6988 4110 2878 ––2444 4544 814 6174
HV b anch (%) 7731 (53.88) 4792 (53.88) 2939 (53.88) 3680 (52.66) 4051 (55.03) 2648 (53.8) 5083 (53.91) 572 (50.89) 7159 (54.13)
Hg H (%) 6627 (46.18) 4088 (45.96) 2539 (46.54) 3158 (45.19) 3469 (47,12) 2240 (45.51) 4387 (46.54) 488 (43.42) 6139 (46.42)
Hg U (%) 2035 (14.18) 1278 (14.37) 757 (14.37) 1045 (13.45) 990 (14.95) 687 (13.96) 1348 (14.3) 169 (15.03) 1866 (14.11)
Hg K (%) 985 (6.86) 600 (6.75) 385 (7.06) 482 (6.8) 503 (6.9) 357 (7.25) 628 (6.66) 88 (7.83) 897 (6.78)
Hg J (%) 1277 (8.90) 806 (9.06) 471 (8.63) 622 (8.9) 655 (8.9) 435 (8,84) 842 (8.93) 106 (9.43) 1171 (8.85)
Hg T (%) 1159 (8.08) 684 (7.69) 475 (8.71) 575 (8.23) 584 (7.93) 384 (7.8) 775 (8.22) 97 (8.63) 1062 (8.1)
Hg V (%) 633 (4.41) 402 (4.52) 231 (4.23) 299 (4.28) 334 (4,54) 228 (4.63) 405 (4.3) 49 (4.36) 584 (4.42)
Hg HV (%) 471 (3.28) 302 (3.39) 169 (3.1) 223 (3.19) 248 (3.37) 180 (3.66) 291 (3.1) 35 (3.1) 436 (3.3)
Hg X (%) 224 (1.56) 150 (1.69) 74 (1.36) 111 (1.59) 113 (1.54) 93 (1.89) 131 (1.39) 16 (1.42) 208 (1.57)
Hg I (%) 212 (1.48) 120 (1.35) 92 (1.69) 105 (1.45) 107 (1.5) 61 (1.24) 151 (1.6) 15 (1.33) 197 (1.5)
Hg W (%) 152 (1.06) 109 (1.22) 43 (<1%) 85 (1.22) 67 (<1%) 56 (1.14) 96 (1) 12 (1) 140 (1)
Hg M (<1%) 107 60 47 62 45 38 69 7 100
Hg L3 (<1%) 105 64 41 48 57 36 69 8 97
Hg R (<1%) 87 55 32 44 43 24 63 7 80
Hg L2 (<1%) 76 53 23 40 36 32 44 9 67
Hg L1 (<1%) 68 44 24 36 32 28 40 10 58
Hg N (<1%) 66 37 29 26 40 24 42 4 62
Hg B (<1%) 24 16 8 9 15 8 16 2 22
Hg A (<1%) 10 82731919
Hg D (<1%) 10 643755010
Hg P (<1%) 844530817
Hg C (<1%) 422133104
Hg L0 (<1%) 330122103
Hg F (<1%) 312030303
Hg G (<1%) 110100101
Hg E (<1%) 110010101
Hg L4 (<1%) 101010101
Ca diac –1055 –632 423 846 209 154 902
Respi a o y –901 –563 338 598 303 190 711
Vascula –4,081 –2200 1881 2730 1351 682 3394
Ne ous –770 –340 430 655 115 80 690
Onco-Hem. –646 –410 236 479 167 104 542
Diges i e –264 –153 111 172 92 45 219
Mi ochond ial HG de e mined by machine lea ning.
Table 2 | Resul s o mul i a ia e logis ic eg ession model o SARS-Co 2 se e i y in SCOURGE coho , including mi ochond ial
HG geno ype in o ma ion
Fea u e Coe ficien S d. e o P- alue OR CI 95%
HV b anch −0.70148 0.21793 <0.01** 0.496 0.324–0.760
Vascula 0.45792 0.07472 <0.001*** 1.581 1.366–1.831
Neu ological −0.47463 0.12947 <0.001*** 0.622 0.480–0.797
Respi a o y 0.40721 0.09315 <0.001*** 1.503 1.24942659–1.800
PC1 −2.15774 0.49375 <0.001*** 0.116 0.044–0.3019
HV b anch x PC1 0.45545 0.66205 <0.001*** 6.714 1.836–24.612
sex 1.14988 0.07176 <0.001*** 3.158 2.746–3.639
age 1.90422 0.22709 <0.05*6.714 1.836–24.612
Le el o significance ep esen ed as ***p< 0.001, **p< 0.01 and *p< 0.05.
h ps://doi.o g/10.1038/s42003-024-07314-y A icle
Communica ions Biology | (2025) 8:33 3
pa ial scena io analyzing HGs and age, again only HV b anch was selec ed
as p o ec i e ea u e in he mul i a ia e model ob ained, no showing
in e ac ion wi h age (ANOVA o nes ed models: p- alue=0.424). Finally, in
mul i a ia e model conside ing gene ic backg ound con ex , again HV
b anch was he only HG explana o y o SARS-Co 2 se e i y, joined wi h
PC1 and PC3, showing in e ac ion wi h PC1 (ANOVA o e nes ed models:
p- alue<0.01**), as also was obse ed when analyzing only SCOURGE
coho (Supplemen a y Table S4). Ga he ing he pe o mance o eg esso s
in hese h ee ames, a global mul i a ia e model was assembled, con-
fi ming p o ec i e ole o HV b anch in his disease, as well as he ac ha i s
e ec is di e en depending on he gene ic backg ound, as obse ed by he
significance o he in e ac ion be ween PC1 and HV b anch (Table 3).
Analysis o ene gy changes in in silico models de e mined by
majo haplog oup ma ke s
Nex , o assess he po en ial s uc u al impac o missense a ian s iden ified
by majo HG ma ke s, we analyzed he ene gy a ia ions hey cause wi hin
in silico models ollowing ose a Flex-ddG p o ocol10. Rega ding hese in
silico esul s calcula ed wi h espec o he e e ence m DNA sequence11,in
HGs J and T espi a o y complex I (CI) showed a significan s abiliza ion,
while HG K p esen ed a significan des abiliza ion, emaining HV b anch
HG U and T unal e ed (Fig. 2, le panel). All analyzed HGs p esen ed
significan le els o des abiliza ion o complex III (CIII
2
), excep o HV
b anch (Fig. 2, middle panel). Finally, in complex V (CV), only HG K
p esen ed a significan des abiliza ion (Fig. 2, igh panel).Nomajo HG
ma ke s causing missense a ia ions a e a ec ing complex IV genes.
Discussion
Since 2019, he global pandemic caused by he SARS-Co -2 i us (COVID-
19) sp ead apidly wi h se ious implica ions all a ound he wo ld. Howe e ,
humans ha e aced nume ous pandemics and epidemics, which likely ac ed
as a selec i e o ce in human e olu ion. By he same oken, HG H (la ges
ep esen a ion o he HV b anch) is he mos equen HG in Eu opean
popula ion, ep esen ing 37–58%12. Howe e , in a s udy pe o med in 54
indi iduals om Uppe Paleoli hic and Ea ly Neoli hic om No he n
Spain, ancien hun e -ga he e samples we e mainly om HG U (50-80%),
while la e Neoli hic samples esul ed mo e he e ogeneous di e ing on hei
p opo ions in HGs J, U and H13. Viewed in his way, since he HG H a i ed
in Eu ope om he Nea Eas (22,000 BP), HG H inc eased i s p opo ion,
being almos 19% in Linea Po e y Cul u e (Neoli hic), inc easing he
equency o a 44% du ing Neoli hic as obse ed in samples om he Basque
Coun y and Na a e13,14. Ne e heless, he HG H has unde gone a mul i-
ace ed and dynamic his o y in Eu ope, shaped by mig a ions, demog aphic
shi s, and possibly selec i e p essu es such diseases. In his s udy we explo e
he hypo he ical con ibu ion o disease linked selec i e p essu es. Thus, in
Eu ope, HG H has become in a ela i ely sho e olu iona y pe iod, he mos
equen one. To p ese e such a high equency, HG H may p o ide some
e olu iona y ad an age, cons i u ing a clea example o e olu iona y
selec ion du ing his o ical ime in human e olu ion. In his p ocess o
selec i e sweep, pandemic/epidemic e en s mus ha e been an impo an
keys one. In his con ex , Ye sinia pes is is one o he deadlies pa hogens o
humans. Du ing he second pandemic (BlackDea h)alone,i wipedou a
leas 30% o he Eu opean popula ion, illus a ing how a pandemic can
influence he gene ic landscape ela ed o immune esponse. Howe e , o
da e, he e is no consis en e idence linking his o mi ochond ial HGs4.
In his ega d, al hough su i al o in ec ious diseases is a mul i-
ac o ial issue, he ad an age con e ed by HG H in pandemics/epidemics
could be a ele an ac o . As an example, Chinne y e al, desc ibed an
o e come in su i al o sepsis e en in ICU pa ien s by HG H pa ien s
compa ed agains emaining HGs5. They epo ed ha HG H pa ien s could
wi hs and a highe co e empe a u e han he es o he HGs, so hey
p oposed e e as a possible cause o he su i al di e ences.
In e e on elease by i us in ec ed cells is pa o he inna e immune
esponse, ha p omo es se e al pa hways o con ol i us eplica ion/
in ec ion15. Bea ing his in mind, i is known ha e e enhances he
immune esponse agains i us in ec ion, boos ing bo h inna e and adap i e
immune esponse o i us16–20. In he same di ec ion, i is known ha he use
o an ipy e ics is associa ed wi h inc eased mo ali y21–23. The e e p oduces
shi e ing as pa o he s a egy o inc easing co e empe a u e, ha
inc eases me abolic a e six old abo e basal le els24,whe emi ochond ia
ha e a key ole in hea p oduc ion. I is known, ha sus ained high em-
pe a u e abo e he physiological h eshold (hea s ess) can induce pe -
manen mi ochond ial dys unc ion ha leads o cy o oxic ROS p oduc ion
igge ing cell dea h25,26. Fu he mo e, i has been desc ibed ecen ly, ha
espi a o y complexes, especially complex I and s uc u es de i ed om
espi a o y complexes assembly called supe complexes a e uns able a
empe a u es abo e 43ºC, bo h in in ac cells and isola ed mi ochond ia27.
Table 3 | Resul s o mul i a ia e logis ic eg ession model o
SARS-Co 2 se e i y in SCOURGE+Con ol coho , including
mi ochond ial HG geno ype in o ma ion
Fea u e Coe ficien S d. e o P- alue OR CI 95%
HV b anch −0.72041 0.22033 <0.01** 0.487 0.316–0.749
PC1 −2.35113 0.49937 <0.001*** 0.095 0.036–0.25
PC3 −1.62667 0.36593 <0.001*** 0.197 0.096–0.403
HV b anch
x PC1
1.97794 0.67010 <0.01** 7.228 1.944–26.878
sex 1.22007 0.07102 <0.001*** 3.387 2.947–3.893
age 1.05173 0.19806 <0.001*** 2.863 1.942–4.220
Le el o significance ep esen ed as ***p< 0.001, **p< 0.01 and *p< 0.05.
Fig. 2 | S abili y changes by espi a o y complex,
de e mined by majo mi ochond ial HG ma ke s.
All HGs a e compa ed o a e e ence model de e -
mined acco ding o he Camb idge e e ence
sequence (NC_012920). Only mi ochond ial HGs
ha we e significan isk modula o s o SARS-Co 2
se e i y a e ep esen ed. Acco ding o he de el-
ope s o he ose a Flex.ddG p o ocol, significan
ene ge ic changes can be conside ed abo e o below
± 1 Kcal/mol ( ed lines). Al hough CIV also con ains
h ee subuni s encoded by m DNA, his espi a o y
complex is no ep esen ed, as none o he desc ibed
mi ochond ial HG ma ke s p oduce amino acidic
changes.
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Communica ions Biology | (2025) 8:33 4
As a esul , g ea e esilience o sus ained high empe a u es could be e o-
lu iona ily a o ed o comba ing in ec ious diseases, pa icula ly h ough
changes ha educe OxPhos capaci y a igue, such as mu a ions in OxPhos
s uc u es associa ed wi h ce ain HG ma ke s. In his con ex , a ecen
s udy has shown ha ele a ed empe a u e (39 ºC) significan ly influences
he me abolism o he elec on anspo chain (ETC), pa icula ly
impac ing complex I. This leads o inc eased ROS p oduc ion and he
ac i a ion o selec i e apop osis in TH
1
lymphocy es28.TH
1
cells play a
c i ical ole in cellula immuni y agains in acellula pa hogens, especially
h ough he p oduc ion o INF-γin esponse o i al in ec ions. As a esul ,
a ia ions in ole ance o hype he mia, caused by small s uc u al di e -
ences de e mined by mi ochond ial HGs, could di ec ly a ec he e ec-
i eness o TH
1
-media ed an i i al esponses.
In his s udy, we confi med ha HGs significan ly influence he
se e i y o SARS-CoV-2, wi h he HV b anch specifically ha ing a p o ec i e
ole. This emains ele an oday, as i s e ec s a e s ill e iden , despi e
significan medical ad ances in comba ing in ec ious diseases ha ha e
educed he co ela ion be ween suscep ibili y, se e i y, and su i al.
Rega ding he flex-ddG analysis, i is impo an o no e ha he HG
ma ke s analyzed a e highly p e alen in human popula ions, so ha unde
no mal physiological condi ions hey would no ep esen any dec ease in
OxPhos fi ness. Howe e , unde ex eme condi ions such as hype he mia,
ole able di e ences in RCs’s abili y unde no mal physiological condi-
ions, could ep esen a eal dec ease in s abili y and a key ole in disease
ou come. In e es ingly, only he HV b anch shows no significan des abi-
liza ion in any RC induced by op-le el HG ma ke s. I is impo an o
no ice ha Flex-ddG in silico analysis has he limi a ion ha he same
gene ic backg ound is used, making i impossible o ule ou ha he
obse ed e ec s a e due o specific mi o-nuclea in e ac ion wi h his
nuclea en i onmen o he OxPhos sys em. Howe e , his same limi a ion
is accep ed o he use o cyb id models, a echnology widely used o p e-
cisely de e mine mi onuclea in e ac ions. Howe e , he goal o ou Flex-
ddG modeling was o gene a e in silico mechanis ic hypo heses based on
obse a ions o he analyzed popula ion.
In he same line o ou ou comes, i has been desc ibed ha HG
ma ke s linked o HG H as 7028C is p o ec i e agains se e e COVID-19
disease29. The esul s p o ided by ou mul i a ia e model, based on da a
d awn om such a la ge coho o pa ien s, p o ide impo an e idence o
he ole o mi ochond ial HGs as modula ing ac o s in he isk o de el-
oping he se e e o m o he disease, ega dless o he gene ic backg ound,
como bidi ies, age o sex o he pa ien s. In addi ion, om an e olu iona y
pe spec i e, hese ou comes confi m he ele ance o H30 and u he mo e
OxPhos geno ype in he de ense o an in ec ious pa hogen.
Me hods
Sample p ocessing and geno yping
Da a om a o al o 11,977 COVID-19-posi i e cases we e ec ui ed as pa
o he SCOURGE s udy (h ps://www.scou ge-co id.o g) om34hospi al
o esea ch cen e s ac oss Spain be ween Ma ch and Decembe 2020.
Samples and da a we e collec ed by he pa icipa ing cen e s h ough hei
espec i e biobanks a e in o med consen . The whole p ojec was
app o ed by he Galician E hical Commi ee, e .: 2020/197. Addi ionally,
5,943 people wi h unknown COVID-19 s a us we e included as popula ion
con ols: 3,437 samples om he Spanish DNA biobank (h ps://www.
bancoadn.o g) and 2,506 samples om he GR@CE conso ium. All e hical
egula ions ele an o human esea ch pa icipan s we e ollowed.
Genomic DNA was ob ained om pe iphe al blood and isola ed using
he Chemagic DNA blood100 ki (Pe kinElme Chemagen Technologies
GmbH), ollowing he manu ac u e 's ecommenda ions. Geno yping was
pe o med using he Axiom Spain Biobank A ay (The mo Fishe scien ific,
Wal ham, MA, USA) acco ding o he manu ac u e 's ins uc ions in he
San iago de Compos ela Node o he Na ional Geno yping Cen e (CeGen-
ISCIII). This a ay con ains 757,836 ma ke s and is en iched in a e a ian s
selec ed in he Spanish popula ion.
De ails conce ning he sample p ocessing and quali y con ol can be
ound in he fi s epo desc ibing he Eu opean GWAS o his
conso ium31. All indi iduals included in he analysis we e o Eu opean
ances y. Ances y was in e ed wi h Admix u e32 using defined 1KGP
supe popula ions. Those indi iduals wi h an es ima ed p obabili y >80% o
pe aining o Eu opean ances y we e defined as Eu opean (N=15,571)31.
A e down-sampling indi iduals wi h missing alues o disease se e i y,
sex o age, we ob ained an e ec i e da ase o 14,349 indi iduals (8,894
COVID-19 posi i e cases and 5,455 popula ion con ols). In hese indi i-
duals’genomic p incipal componen s (PCs) we e compu ed using a LD-
p uned ( 2< 0.1 wi h a window size o 1000 ma ke s) subse o geno yped
SNPs passing quali y check o con olling he popula ion s uc u e in he
pos e io analyses (Fig. 3).
HG calling using machine lea ning
We de elopedan ad hoc me hod o pe o m mi ochond ial HG calling om
GWAS a ay da a, based in machine lea ning (Fig. 1). The Axiom Spain
Biobank A ay co e s up o 231 mi ochond ial confiden posi ions. A ound
189 ou o hese 231 posi ions we e posi ions linked o HG ma ke s and he
p obes ha define hegeno ypeinou a ayha eenoughquali y.Ou goal
was o ain a andom o es classifie using 189 posi ions (which define he
a iables o he andom o es ) om 61,134 HG-labeled sequences
ob ained om he Mi omap da abase. We employed 3- old c oss- alida ion
o fine- une he model's hype pa ame e s (Fig. 1, le panel). The hype -
pa ame e s we e es ic ed o he numbe o a iables andomly sampled as
candida es a each spli (5, 10, 20, 40, o 60). Model e o was fi s assessed
using a 3- old c oss- alida ion loop on he aining da ase , wi h hype -
pa ame e fine- uning conduc ed wi hin each cycle (ob ained by nes ed
cycles o 3- old CV, men ioned be o e). Thus, he e o was measu ed as he
mean o Cohen’s kappa calcula ed o each c oss- alida ion cycle. Nex ,
ex e nal alida ion o his model was unde ook using Publicly a ailable da a
om he hi d phase o 1,000 genome p ojec 8. In his samples, he SNPs
collec ed om ull leng h m DNA we e used o call HG using haplog ep29.
Finally, we use ou model o p edic HGs in ou 14,749 pa ien s, based on
geno ype in o ma ion o he 189 posi ions. (Fig. 1, igh panel).Anapp
powe ed by shiny (h ps://shiny.posi .co/) will be a ailable a h ps://gi hub.
com/Cab e a-ala con/GENOXPHOS.
Analysis o HGs as independen isk ac o s
To assess he alue o HGs as independen isk ac o o he se e i y o
SARS-CoV-2, we analyzed only HGs wi h equencies >1% (H, HV, V, J, T,
Fig. 3 | P incipal componen (PC) analysis summa izing gene ic a iabili y Cases
Vs Con ols. A plo depic ing he wo main PC, cases (n=8894) Vs con ols
(n=5455), ha ga he s ha main amoun o o e all gene ic a iabili y based in
GWAS a ay.
h ps://doi.o g/10.1038/s42003-024-07314-y A icle
Communica ions Biology | (2025) 8:33 5

U, K, I, W and X). Se e e disease de elopmen was conside ed o pa ien s
wi h a al ou come, admission o he ICU o he need o mechanical en-
ila ion (in asi e o nonin asi e). Addi ionally, HGs we e connec ed by
b anches based on op-le el MITOMAP HG ma ke s (p esen in ≥80% o
HGs) ha esul in amino acid changes in mi ochond ial DNA encoded
OxPhos subuni s. The missense s a us o hese op-le el HG ma ke s was
p edic ed using he a ian e ec p edic o 33 (Supplemen a y Da a 1). As a
esul , HGs H, V, and HV we e g ouped oge he unde he HV b anch.
Then we assessed explana o y meaning o HGs o SARS-Co 2 se e i y
in wo g oups, he SCOURGE coho ( hose a e ou case g oup, o which
we ha e como bidi y in o ma ion o 8,778 ou o 8,894) and he global
g oup o pa ien s ep esen ed by he SCOURGE+Con ol pa ien s
(8,894+5,455).
Ini ially, we examined he impac o po en ial explana o y a iables by
fi ing a uni a ia e logis ic eg ession model o s udy hese e ec s in he
SCOURGE coho . Fo he analysis ac oss all pa ien s, we employed a
mixed-e ec s logis ic eg ession model o accoun o he popula ion s a-
ifica ion in o cases and con ols as a andom e ec . To fi suchmixed-
e ec s models we used lme4 -1.-35.3 R-package34. Fi e g oups o ea u es
we e conside ed, HGs, como bidi ies, gene ic backg ound, sex and age. The
como bidi ies we e ep esen ed by he pa ien 's ca diac his o y (ischemic
hea disease, hea ailu e, ca diac a hy hmia o pe iphe al ascula dis-
ease), ascula his o y (a e ial hype ension, hype choles e olemia,
uncomplica ed diabe es melli us, diabe es melli us wi h isce al epe cus-
sions, obesi y), diges i e an eceden s (Pep ide ulce , Ch onic li e disease
wi hou po al hype ension, Ch onic li e disease wi h po al hype en-
sion), ne ous sys em an eceden s (Ce eb o ascula disease such as
in a c ion o hemo hage wi hou sequelae o minimal sequelae, wi h
hemiplegia o pa aplegia, demen ia o o he neu ological disease), espi a-
o y his o y (Ch onic Obs uc i e Pulmona y Disease o o he ch onic
espi a o y disease) and oncological o oncohema ological his o y (localized
solid umo , me as a ic solid umo , leukemia, lymphoma o bone ma ow/
hema opoie ic p ecu so ansplan ). The gene ic backg ound was es i-
ma ed as o summa ize gene ic a iabili y as he 10 p incipal componen s
de e mined om geno ype ma ix. Since many o hese a iables we e
dicho omous and he quan i a i e a iables (gene ic backg ound and age)
we e on e y di e en scales, a min-max no maliza ion o he da a was
pe o med.
Nex , he eg esso s ha we e significan in uni a ia e models we e
e alua ed by assembling mul i a ia e models. Ini ially, we assessed he
significan HGs om he uni a ia e models ac oss ou di e en scena ios,
esul ing in ou dis inc mul i a ia e models. These models es ed he
independen e ec s o he HGs: one conside ing only como bidi ies (in he
SCOURGE coho ), one accoun ing o gene ic backg ound, ano he
checking o independen e ec s wi h sex and age. Du ing his p ocess,
ea u e selec ion was conduc ed using a s epwise backwa d s a egy, edu-
cing he Akaike in o ma ion c i e ion (AIC) o he main e ec s. Once he
ea u es we e selec ed, po en ial in e ac ions be ween HGs and o he ea-
u es we e explo ed by analyzing he ele ance o hei inclusion in he
model h ough ANOVA es s compa ing nes ed models. The same s a egy
was applied o e alua e he impo ance o including HGs in he final models.
Finally, based on he in o ma ion ob ained om hese pa ial mul i a ia e
models, a global model was fi ed, bo h when conside ing only SCOURGE
coho and when s udying SCOURGE+Con ols. In hese models, s a i-
fica ion o analyzed popula ion was conside ed as alea o y e ec . In all
models a h eshold o significance o 0.05 was adop ed.
Analysis o ene gy changes in in silico models de e mined by
majo HG ma ke s
Fu he analyses we e pe o med o e alua e in ou in-silico models (Cab-
e a-Ala con & En iquez, manusc ip submi ed), o assess whe he
obse ed esul s o significan HGs om mul i a ia e mixed e ec logis ic
eg ession co ela e wi h changes in OxPhos complexes s abili y by ana-
lyzing esidue changes de e mined by majo HG ma ke s ga he ed om
MITOMAP. S uc u al consequences oh HG ma ke s we e de e mined
using Va ian E ec P edic o 33. Fo his pu pose, changes in he s eng h
ha bind subuni s assembled in OxPhos complexes due o esidue changes
we e s udied ollowing he ose a Flex-ddG p o ocol10. Acco ding o
de elope s o his ool significan ene gy changes can be conside ed om ±1
Kcal/mol.
Da a a ailabili y
All da a used o de elop machine lea ning models a e publicly a ailable in
Mi omap: (h ps://www.mi omap.o g/ oswiki/bin/ iew/Main/WebHome)
and The In e na ional Genome Sample Resou ce (h ps://www.
in e na ionalgenome.o g), and ma e ials ha a e no a ailable in he main
ex , he supplemen a y ma e ials o gi hub eposi o y will be a ailable upon
eques . Summa y s a is ics om he SCOURGE La in-Ame ican GWAS
will be a ailable a h ps://gi hub.com/CIBERER/Scou ge-COVID19.Raw
geno ype o pheno ype da a canno be made a ailable due o es ic ions
imposed by he e hics app o al.
Code a ailabili y
Code use in his s udy will be a ailable a h ps://gi hub.com/Cab e a-
ala con/GENOXPHOS.
Recei ed: 18 Ap il 2024; Accep ed: 22 No embe 2024;
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Acknowledgemen s
The au ho s hank M. M. Muñoz-He nandez, R. Ma ínez de Mena and E.R.
Ma ínez Jiménez, o echnical assis ance. Scheme figu es we e made wi h
BioRende . We pa icula ly acknowledge all he pa ien s, BancoNacional de
ADN, Biobanco del Sis ema de Salud de A agón, Biobanc Fundació Ins i u
d'In es igació Sani à ia Illes Balea s, Biobanco del Complexo Hospi ala io
Uni e si a io de San iago, Biobanco Vasco, o hei collabo a ion and
p o iding ma e ials. JAE labo a o y is suppo ed by: RTI2018-099357-B-I00
and PID2021-1279880B-and TED2021-131611B-I00 unded by MCIN/AEI/
10.13039/501100011033 and he, and CIBERFES (CB16/10/00282),
Human F on ie Science P og am (g an RGP0016/2018), and Leducq
T ansa lan ic Ne wo ks (17CVD04). MR-M is suppo ed by a FPI/PRE2021-
097721 ellowship. JAE and FSC a e suppo ed by TED2021-131611B-I00
unded by MCIN/AEI/10.13039/501100011033 and he Eu opean Union
“Nex Gene a ionEU”/Plan de Recupe ación T ans o mación y Resiliencia
-PRTR. FSC ecei ed unding [g an no. PID2022-141527OB-I00] by he
MCIN/AEI/10.13039/501100011033/ and by FEDER Una mane a de hace
Eu opa. This wo k was suppo ed by Fundación Amancio O ega Gaona,
Banco de San ande S.A. and Ins i u o de Salud Ca los III (COV20/00622)
and he Eu opean Regional De elopmen Fund. Geno yping se ice was
ca ied ou a CEGEN-PRB3-ISCIII, suppo ed by g an PT17/0019, o he
PE I+D+i 2013-2016, unded by ISCIII and ERDF. The CNIC is suppo ed by
he Ins i u o de Salud Ca losIII (ISCIII), he Minis e io de Ciencia e Inno ación
(MCIN) and he P o CNIC Founda ion) and is a Se e o Ochoa Cen e o
Excellence (g an CEX2020-001041-S unded by MICIN/AEI/10.13039/
501100011033).
Au ho con ibu ions
Concep ualiza ion: J.L.C.-A., R.C., F.S.-C., A.C., J.A.E. Me hodology:
J.L.C.-A., M.R.-M., R.C., A.L.-P. In es iga ion: J.L.C.-A., M.R.-M.
Visualiza ion: J.L.C.-A., J.A.E. Funding acquisi ion: F.S.-C., J.A.E. P ojec
adminis a ion: S.D.A., J.A.R., A.R.M., C.F., P.L. Sample P o ide s: S.C.G.
Supe ision: A.C., J.A.E. W i ing—o iginal d a : J.L.C.-A., F.S.-C., J.A.E.
W i ing— e iew and edi ing: All Au ho s
Compe ing in e es s
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Addi ional in o ma ion
Supplemen a y in o ma ion The online e sion con ains
supplemen a y ma e ial a ailable a
h ps://doi.o g/10.1038/s42003-024-07314-y.
Co espondence and eques s o ma e ials should be add essed o
José An onio En iquez.
Pee e iew in o ma ion Communica ions Biology hanks he anonymous
e iewe s o hei con ibu ion o he pee e iew o his wo k. P ima y
Handling Edi o s: Ani Manichaikul and Tobias Go is. [A pee e iew file is
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Communica ions Biology | (2025) 8:33 7
1
Cen o Nacional de In es igaciones Ca dio ascula es Ca los III (CNIC), Mad id E-28029, Spain.
2
Cen o de In es igación Biomédica en Red de F agilidad y En eje-
cimien o Saludable.(CIBERFES) Ins i u o de Salud Ca los III, Mad id E-28029, Spain.
3
Cen o de In es igación Biomédica en Red en En e medades Ra as (CIBERER),
Ins i u o deSaludCa los III, Mad id E-28029, Spain.
4
G upo de Medicina Xenómica-CIMUS-Uni e sidade de San iago de Compos ela, San iagode Compos ela, Spain.
5
G upo de Gené ica Clínica y Genómica Funcional, Facul ad de Medicina, Uni e sidad de Za agoza, IIS A agón, CIBERER-GCV02, E-50009 Za agoza, Spain.
6
Uni-
e sidad de Can ab ia, Can ab ia, Spain.
7
Hospi al U M Valdecilla, Can ab ia, Spain.
8
DIVAL, Can ab ia, Spain.
9
Tecnológico de Mon e ey, Escuela de Medicina y
Ciencias de la Salud, Mon e ey, México.
10
Cen e o Biomedical Ne wo k Resea ch on Respi a o y Diseases (CIBERES), Ins i u o de Salud Ca los III, Mad id, Spain.
11
Genomics Di ision, Ins i u o Tecnológico y de Ene gías Reno ables, San a C uz de Tene i e, Spain.
12
Resea ch Uni , Hospi al Uni e si a io Nues a Seño a de
Candela ia, San a C uz de Tene i e, Spain.
13
Ins i u o de Gené ica Médica y Molecula (INGEMM), Hospi al Uni e si a io La Paz-IDIPAZ, ERN-ITHACA-Eu opean
Re e ence Ne wo k, Mad id, Spain.
14
Fundación Pública Galega de Medicina Xenómica (SERGAS), Heal h Resea ch Ins i u e o San iago de Compos ela (IDIS),
San iago de Compos ela, Spain. e-mail: [email p o ec ed]
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Ma ia A. Cas illo93,Wal e G.Cha es-San iago
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113, Ma ia C. C. Ca alho114, Da id Dalmau62,76,RaquelC.S.Dan as-Koma su
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M. Te esa Da naude116, Raimundo de And es117,Ca mendeJuan
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nguez-Ga ido129, Lidia S. Rosa130, And e D. Luchessi131, Jose Echa e-
Sus ae a132,Roci
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Ana Fe nandez-C uz139, Sil ia Fe nandez-Fe e o25, Yolanda Fe nandez Ma inez25,Ma i
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Lacides Fuenmayo -He na
ndez34, Ma a Fue es-Nu
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Manuela Gago-Dominguez7,10, Na alia Gallego11, C is ina Galoppo147,AnaGa ci
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n148, Ca los Ga cia-Ce ada15,16,
Ai o Ga cia-de-Vicuna48,98,Josefina Ga cia-Ga cia68, I ene Ga cia-Ga cia77, Ca men Ga cia-Iba bia59,60,137,And e
sC.Ga ci
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a3,40, Elisa Ga cia-Vazquez68,
Emiliano Ga za-F ias94, Angela Gen ile147,Bele
n Gil-Fou nie 151,Je
ssicaN.G.deA au
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mez-Duque54,103,
Ja ie Go
mez-A ue121,122, Luis Go
mez Ca e a32,Ma i
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mez Ga cia6,A
ngela Go
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Anna Gonzalez-Nei a41, Bea iz Gonza
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l a ez121,122,Fe na
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lez Be naldo de Qui o
s154, Ra aela Gonza
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Mon elongo155,Ja ie Gonza
lez-Penas20,45,52, Manuel Gonzalez-Sag ado104, Hugo Gonzalo-Beni o156, Osca Go gojo-Galindo157,
Miguel Go
 golas86, Flo encia Gua agna147, Jessica G. Chaux54, Enca na Guillen-Na a o68,158,159,160, Bea iz Guille
n-Guio109,
Pablo Guisado-Vasco132, Luz D. Gu ie ez-Cas aneda54,161,JuanF.Gu ie
 ez-Bau is a162,Sa aHeili-F ades
163,
Ra aelH. Jacomo164,Es e aniaHe nandez165,C is inaHe na
ndez-Mo o25,Luis D.He nandez-O ega166,167,Guille moHe na
ndez-
Pe ez42, Rebeca He na
ndez-Vaque o168,Bele
n He aez41,M.Te esaHe anz
68,Ma i
a He e a50,51,Ma i
aJose
He e o169,170,
An onio He e o-Gonzalez171, Juan P. Ho cajada28,172,173,174,Na aleImaz-Ayo
48, Maide In xaus i-U u ibeaskoa175,An onioI
nigo-
h ps://doi.o g/10.1038/s42003-024-07314-y A icle
Communica ions Biology | (2025) 8:33 8
Campos155,Ma i
aI
niguez176,Rube
nJa a
68,A
ngelJime
nez50,51,177,Pila Jime
nez162,Ma i
aA.Jime
nez-Sousa81, Iolanda Jo dan14,178,
Ignacio Jimenez-Al a o179,Roci
o Laguna-Goya180,181, Daniel Lao den32,Ma i
a Lasa-Laza o180,181,Ma i
a Claudia La ig93,182,
Ailen Lau ien e147, Anabel Lige Bo ja183, LuciaLlanos
184,Ampa oLo
pez-Be nus42,43,MiguelLo
pez de He edia3,Es he Lopez-
Ga cia14,119,120,185, Edua do Lo
pez-G anados3,186,187, Rosa io Lopez-Rod iguez3,40,MiguelA.Lo
pez-Ruz188,189,190,
Leona do Lo en e191,Jose
M. Lo enzo-Salaza 155,Jose
E. Lozano192,Ma i
a Lozano-Espinosa183, Ignacio Mahillo10,193,194,
Es he Mancebo180,181, Ca men Ma 135, C is ina Ma celo Cal o102, Alba Ma cos-Delgado195,MiguelMa cos
42,43, Alicia Ma in-
Cando
n77, Pablo Ma iscal-Aguila 32, Lau a Ma in-Ped aza74, Ma a Ma in-Fe nandez196,Ca idadMa i
n-Lo
pez183,Jose
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A
ngel Ma in-O e ino42,43,Ma i
a Dolo es Ma in197, Vicen e Ma in14,195,Ma i
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n198,Ma i
aMa i
n-Vicen e81,
Amalia Ma inez199,O
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nez165, Ped o Ma inez-Paz156, Co adonga M. Diaz-Caneja20,45,52,
O
sca Ma inez-Nie o64,182,Icia Ma inez-Lo
pez200,201,MichelF.Ma inez-Resendez94,Sil iaMa inez59,137,JuanJose
Ma inez3,97,
A
ngel Ma inez-Pe ez202,And eaMa i
nez-Ramas3,40, Viole a Ma inez-Robles25, Lau a Ma zal3,40, Juliana F. Mazzeu203,204,205,
F ancisco J. Med ano14,91,92,XoseM.Meijome
206,207, Na alia Meju o-Mon e o208,Ing idMendes
3,AliceL.Dua e
111,AnaMe
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Eche a ia209, Humbe o Mendoza Cha is34,78, Eleu e io Me ayo Macias210,Fa
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Pablo Minguez3,40, Elena Molina-Roldan212, An onio J. J. Molina195,JuanJose
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Pa icia Mo ei a-Esc iche118, Xenia Mo elos-A nedo34,78,Roci
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38,39,E aO ega-Paino
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Conejo25, Sonia Panade o-Faja do95, Ma a Pa ellada20,45,52, Robe o Pa ien e-Rod iguez148, Vicen e F iaza14,92, Es ela Paz-
A al180,181,221,Ge ma
nPeces-Ba ba10,222, Miguel S. Ped omingo Kus223,CeliaPe ales146,NeyP.C.San os224,GenilsonP. Guegel225,
Ma iaJazmi
nPe
 ez147,Alexand aPe
 ez80,82, Pa icia Pe
 ez-Ma u e176,Ce
sa Pe ez226,Gus a oPe
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Felipe Pe ez-Ga cia227,228, Pa icia Pe ez229, Luis A. Pe ez-Ju ado1,2,3,87,M.ElenaPe
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s68, Te esa Pe ucho230,
Lisbe h A. Picha do25, Ad iana P. Ribei o36,37,214, Mel·lina Pinsach-Abuin80,82, Luz Ad iana Pinzo
n54,103, Jeane F. P. Medei os231,
Guille mo Pi a41, F ancesc Pla-Junca3,232, Lau a Planas-Se a3,97,E ickaN.Pompa-Me a
233, Glo ia L. Po as-Hu ado165,
Au o a Pujol3,97,234,Ma i
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n151,
Ped o Rascado Sedes236, Joana F. R. Nunes56, Delia Recalde121,122, Emma Recio-Fe na
ndez176, Sal ado Resino81,
Rena a R. Sousa214, Ca los S. Ri adenei a-Chamo o54, Diana Roa-Agudelo64, Mon se a Robelo Pa do236,
Ma ianne R. Fe nandes224,237,Ma i
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Ma ilyn Johanna Rod iguez54, Fe nando Rod iguez-A alejo14,119,120,185,Ma enaRod i
guez-Fe e 34,Ca losRod i
guez-
Gallego239,240,Jose
A. Rod iguez-Ga cia25,Bele
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guez-
No oa147, Paula A. Rod iguez-U ego64,Fede icoRojo
241,242, And ea Rome o-Co onado34,Rube
n Mo illa92,243, Filomeno Rondo
n-
Ga cia25, An onio Rosales-Cas illo244, Cladelis Rubio245,Ma i
aRubioOli e a
50,51, F ancisco Ruiz-Cabello162,189,246,E aRuiz-
Casa es230,JuanJ.Ruiz-Cubillan
59,137, Ja ie Ruiz-Ho nillos51,247,248, Mon se a Ruiz3,97,PabloRyan
249,250,251,
Hec o D. Salamanca53,54, Lo ena Salaza -Ga cia93, Gio gina Gab iela Salguei o-O iglia102, Anna Sangil76,OlgaSa
nchez-
Pe nau e252, Ped o-Luis Sanchez43,133,An onioJ.Sa
nchez Lo
pez253,Cla aSa
nchez-Pablo133,Ma i
a Concepcio
nSa
nchez-
P ados32,Ja ie Sa
nchez-Real25,Jo geSa
nchez-Redondo15,254,C is inaSancho-Sainz
175,Es he Sande
226, A noldo San os226,
Aga ha Schlü e 3,97, Sonia Sego ia232,255,256, Alex Se a-Llo ich62, Fe nando Se il-Pu as22, Ma a Se illa-Po as3,11,
Miguel A. Sicolo257,258, C is ina Sil an-Fuen es3,Vi o M.S.Mo aes
259, Vanessa S. Souza105,Jo diSole
-Violan10,260,
Jose
ManuelSo ia202,JoseV.So li
107,108,Naya aS.Sil a
261,JuanCa losSou o17, John J. Sp ockel54,103,Jose
Ja ie Sua ez-Rama6,
Da id A. Sua ez-Zamo a64, Xiana Taboada-F aga208, Edua do Tamayo157,262, Al a o Tamayo-Velasco263, Juan Ca los Ta acido-
Fe nandez171, Rome o H. T. Vasconcelos113, Ca los Telle ia121,122,Tha
ssia M. T. Ca a o259, Jai An onio Teno io-Cas ano3,11,12,
Alejand o Tepe 147,IzabelM.T.A aujo
111, Juan To es-Macho264, Lilian To es-Toba 265, Ronald P. To es-Gu ie ez223,
Jesu
sT oya
249,MiguelU ios e
211, Juan Valencia-Ramos266,Agus i
n Valido35,267, Juan Pablo Va gas-Gallo268,269,Bele
nVa o
n270,
Tomas Vega271, San iago Velasco-Qui ce272, Valen ina Velez-San ama ia96,97,Vi giniaVi
c o 50,51,JuliaVida
n-Es e ez25,
Gab iela V. Sil a111, Mi iam Viei ez-San iago59,137, Ca los Vilches273, La inia Villalobos25, Felipe Villa 222, Judi Villa -Ga cia274,275,276,
C is ina Villa e de3,40, Pablo Villoslada-Blanco176, Ana Vi seda-Be dices81,Ta ianaX.Cos a
277,ZuleimaYa
nez34,
An onio Zapa e o-Ga i ia278, Ru h Za a e279,Sand aZazo
241,Ca losFlo es
10,109,155,240,Jose
A. Riancho59,60,137, Augus o Rojas-
Ma inez280, Pablo Lapunzina3,11,12 &A
ngel Ca acedo3,6,7,9,10
15
Hospi al Uni e si a io Mos oles, Medicina In e na, Mad id, Spain.
16
Uni e sidad F ancisco de Vi o ia, Mad id, Spain.
17
Haemos asis and Th ombosis Uni , Hospi alde
la San a C eu I San Pau, IIB San Pau, Ba celona, Spain.
18
Uni o In ec ious Diseases, Hospi al Uni e si a io 12 de Oc ub e, Ins i u o de In es igacio
n Sani a ia Hospi al
12 de Oc ub e (imas12), Mad id, Spain.
19
Spanish Ne wo k o Resea ch in In ec ious Diseases (REIPI RD16/0016/0002), Ins i u o de Salud Ca los III, Mad id, Spain.
20
School o Medicine, Uni e sidad Complu ense, Mad id, Spain.
21
Cen e o Biomedical Ne wo k Resea ch on In ec ious Diseases, Ins i u o de Salud Ca los III,
Mad id, Spain.
22
Hospi al Gene al San a Ba
 ba a de So ia, So ia, Spain.
23
Pedia ic Neu ology Uni , Depa men o Pedia ics, Na a a Heal h Se ice Hospi al,
h ps://doi.o g/10.1038/s42003-024-07314-y A icle
Communica ions Biology | (2025) 8:33 9