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

Abstract

The frequency of mitochondrial DNA haplogroups (mtDNA-HG) in humans is known to be shaped by migration and repopulation. Mounting evidence indicates that mtDNA-HG are not phenotypically neutral, and selection may contribute to its distribution. Haplogroup H, the most abundant in Europe, improved survival in sepsis. Here we developed a random forest trained model for mitochondrial haplogroup calling using data procured from GWAS arrays. Our results reveal that in the context of the SARS-CoV-2 pandemic, HV branch were found to represent protective factors against the development of critical SARS-CoV-2 in an analysis of 14,349 patients. These results highlight the role of mtDNA in the response to infectious diseases and support the proposal that its expansion and population proportion has been influenced by selection through successive pandemics.

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

Author: Cabrera Alarcón, José Luis; Cruz, Raquel; Rosa-Moreno, Marina; Latorre-Pellicer, Ana; Diz de Almeida, Silvia; SCOURGE cohort group; Medrano Ortega, Francisco Javier; Rodríguez Hernández, María A.; Morilla Romero de la Osa, Rubén; Valido Morales, Agustín
Publisher: Nature Briefing
Year: 2025
DOI: 10.1038/s42003-024-07314-y
Source: https://idus.us.es/bitstreams/2f931eac-5ac6-4a41-8888-1c87dbabfc7d/download
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.
h ps://doi.o g/10.1038/s42003-024-07314-y A icle
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
The au ho s decla e no compe ing in e es s.
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
a ailable].
Rep in s and pe missions in o ma ion is a ailable a
h p://www.na u e.com/ ep in s
Publishe ’s no e Sp inge Na u e emains neu al wi h ega d o
ju isdic ional claims in published maps and ins i u ional a filia ions.
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h ps://doi.o g/10.1038/s42003-024-07314-y A icle
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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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
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pez-Ruz188,189,190,
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42,43, Alicia Ma in-
Cando
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Amalia Ma inez199,O
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O
sca Ma inez-Nie o64,182,Icia Ma inez-Lo
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F ancisco J. Med ano14,91,92,XoseM.Meijome
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A al180,181,221,Ge ma
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Ma iaJazmi
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 ez147,Alexand aPe
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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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Lisbe h A. Picha do25, Ad iana P. Ribei o36,37,214, Mel·lina Pinsach-Abuin80,82, Luz Ad iana Pinzo
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241,242, And ea Rome o-Co onado34,Rube
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Ga cia25, An onio Rosales-Cas illo244, Cladelis Rubio245,Ma i
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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
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nchez-Pablo133,Ma i
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nchez-
P ados32,Ja ie Sa
nchez-Real25,Jo geSa
nchez-Redondo15,254,C is inaSancho-Sainz
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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
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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
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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