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CSVS, a crowdsourcing database of the Spanish population genetic variability

Abstract

The knowledge of the genetic variability of the local population is of utmost importance in personalized medicine and has been revealed as a critical factor for the discovery of new disease variants. Here, we present the Collaborative Spanish Variability Server (CSVS), which currently contains more than 2000 genomes and exomes of unrelated Spanish individuals. This database has been generated in a collaborative crowdsourcing effort collecting sequencing data produced by local genomic projects and for other purposes. Sequences have been grouped by ICD10 upper categories. A web interface allows querying the database removing one or more ICD10 categories. In this way, aggregated counts of allele frequencies of the pseudo-control Spanish population can be obtained for diseases belonging to the category removed. Interestingly, in addition to pseudo-control studies, some population studies can be made, as, for example, prevalence of pharmacogenomic variants, etc. In addition, this genomic data has been used to define the first Spanish Genome Reference Panel (SGRP1.0) for imputation. This is the first local repository of variability entirely produced by a crowdsourcing effort and constitutes an example for future initiatives to characterize local variability worldwide. CSVS is also part of the GA4GH Beacon network.

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CSVS, a crowdsourcing database of the Spanish population genetic variability

Author: Peña-Chilet, María; Roldán, Gema; Perez-Florido, Javier; Ortuño, Francisco M.; Carmona, Rosario; Antiñolo Gil, Guillermo; Dopazo, Joaquín
Publisher: OXFORD UNIV PRESS
Year: 2021
DOI: 10.1093/nar/gkaa794
Source: https://idus.us.es/bitstreams/bc9005fa-17c5-451f-9959-eebd69b4df31/download
D1130–D1137 Nucleic Acids Resea ch, 2021, Vol. 49, Da abase issue Published online 29 Sep embe 2020
doi: 10.1093/na /gkaa794
CSVS, a c owdsou cing da abase o he Spanish
popula ion gene ic a iabili y
Ma ´
ıa Pe˜
na-Chile 1,2,3, Gema Rold´
an1, Ja ie Pe ez-Flo ido1,3,4, F ancisco M. O u ˜
no1,3,4,
Rosa io Ca mona1, Vi ginia Aquino1, Daniel Lopez-Lopez1,3, Ca los Louce a1,3, Jose
L. Fe nandez-Rueda1, Asunci´
on Gallego5, F ancisco Ga c´
ıa-Ga cia6,
Anna Gonz´
alez-Nei a7, Guille mo Pi a7,Roc
´
ıo N´
u˜
nez-To es7, Ja ie San oyo-L´
opez8,
Ca men Ayuso9, Pablo Minguez9,10, Almudena A ila-Fe nandez9, Ma a Co on9, Miguel
´
Angel Mo eno-Pelayo11,Ma
´
ıas Mo in11, Al a o Gallego-Ma inez12,13, Jose
A. Lopez-Escamez12,13, Salud Bo ego14,15, Guille mo An i˜
nolo14,15, Jo ge Amigo16,
Jose a Salgado-Ga ido17, Sa a Pasalodos-Sanchez17, Bea iz Mo e18, The Spanish Exome
C owdsou cing Conso ium, ´
Angel Ca acedo16,19,´
Angel Alonso17 and
Joaqu´
ın Dopazo 1,2,3,4,*
1Clinical Bioin o ma ics A ea, Fundaci´
on P og eso y Salud (FPS), Hospi al Vi gen del Roc´
ıo, Se illa 41013, Spain,
2Bioin o ma ics in Ra e Diseases (BiER), Cen e o Biomedical Ne wo k Resea ch on Ra e Diseases (CIBERER),
ISCIII, Se illa 41013, Spain, 3Compu a ional Sys ems Medicine g oup, Ins i u e o Biomedicine o Se ille (IBIS)
Hospi al Vi gen del Roc´
ıo, Se illa 41013, Spain, 4Func ional Genomics Node, FPS/ELIXIR-ES, Hospi al Vi gen del
Roc´
ıo, Se illa 41013, Spain, 5Sis emas Genomicos, Pa e na, Valencia 46980, Spain, 6Unidad de Bioin o m´
a ica y
Bioes ad´
ıs ica, Cen o de In es igaci´
on P ´
ıncipe Felipe (CIPF), Valencia 46012, Spain, 7Human Geno yping
Uni –Cen o Nacional de Geno ipado (CEGEN), Human Cance Gene ics P og amme, Spanish Na ional Cance
Resea ch Cen e (CNIO), Mad id 28029, Spain, 8Edinbu gh Genomics, The Uni e si y o Edinbu gh, Edinbu gh EH9
3FL, UK, 9Depa men o Gene ics, Ins i u o de In es igaci´
on Sani a ia-Fundaci´
on Jim´
enez D´
ıaz Uni e si y Hospi al,
Uni e sidad Au ´
onoma de Mad id (IIS-FJD, UAM), Mad id 28040, Spain, 10Cen e o Biomedical Ne wo k Resea ch
on Ra e Diseases (CIBERER), ISCIII, Mad id 28040, Spain, 11Se icio de Gen´
e ica, Ram´
on y Cajal Ins i u e o
Heal h Resea ch (IRYCIS) and Biomedical Ne wo k Resea ch Cen e on Ra e Diseases (CIBERER), Mad id 28034,
Spain, 12O ology & Neu o ology G oup CTS 495, Depa men o Genomic Medicine, Cen e o Genomics and
Oncological Resea ch (GENYO), P ize Uni e si y o G anada, G anada 18016, Spain, 13Depa men o
O ola yngology, Ins i u o de In es igaci´
on Biosani a ia, IBS. GRANADA, Hospi al Uni e si a io Vi gen de las Nie es,
Uni e sidad de G anada, G anada 18016, Spain, 14Depa men o Ma e no e al Medicine, Gene ics and
Rep oduc ion, Ins i u e o Biomedicine o Se ille (IBIS), Uni e si y Hospi al Vi gen del Roc´
ıo/CSIC/Uni e si y o
Se ille, Se ille 41013, Spain, 15Cen e o Biomedical Ne wo k Resea ch on Ra e Diseases (CIBERER), Se ille
41013, Spain, 16Fundaci´
on P´
ublica Galega de Medicina Xen´
omica, SERGAS, IDIS, San iago de Compos ela 15706,
Spain, 17Na a abiomed-IdiSNA, Complejo Hospi ala io de Na a a, Uni e sidad P´
ublica de Na a a (UPNA), IdiSNA
(Na a a Ins i u e o Heal h Resea ch), Pamplona, Na a a 31008, Spain, 18Undiagnosed Ra e Diseases
P og amme (ENoD). Cen e o Biomedical Resea ch on Ra e Diseases (CIBERER), ISCIII, Mad id 28029, Spain
and 19G upo de Medicina Xen´
omica, Cen o de In es igaci´
on Biom´
edica en Red de En e medades Ra as
(CIBERER), CIMUS, Uni e sidade de San iago de Compos ela, San iago de Compos ela, Espa˜
na
Recei ed Augus 13, 2020; Re ised Sep embe 08, 2020; Edi o ial Decision Sep embe 10, 2020; Accep ed Sep embe 10, 2020
ABSTRACT
The knowledge o he gene ic a iabili y o he lo-
cal popula ion is o u mos impo ance in pe son-
alized medicine and has been e ealed as a c i -
ical ac o o he disco e y o new disease a i-
an s. He e, we p esen he Collabo a i e Spanish
Va iabili y Se e (CSVS), which cu en ly con ains
mo e han 2000 genomes and exomes o un ela ed
*To whom co espondence should be add essed. Tel: +34 677910685; Email: [email p o ec ed]
C
The Au ho (s) 2020. Published by Ox o d Uni e si y P ess on behal o Nucleic Acids Resea ch.
This is an Open Access a icle dis ibu ed unde he e ms o he C ea i e Commons A ibu ion License (h p://c ea i ecommons.o g/licenses/by/4.0/), which
pe mi s un es ic ed euse, dis ibu ion, and ep oduc ion in any medium, p o ided he o iginal wo k is p ope ly ci ed.
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Nucleic Acids Resea ch, 2021, Vol. 49, Da abase issue D1131
Spanish indi iduals. This da abase has been gen-
e a ed in a collabo a i e c owdsou cing e o col-
lec ing sequencing da a p oduced by local genomic
p ojec s and o o he pu poses. Sequences ha e
been g ouped by ICD10 uppe ca ego ies. A web in-
e ace allows que ying he da abase emo ing one
o mo e ICD10 ca ego ies. In his way, agg ega ed
coun s o allele equencies o he pseudo-con ol
Spanish popula ion can be ob ained o diseases be-
longing o he ca ego y emo ed. In e es ingly, in ad-
di ion o pseudo-con ol s udies, some popula ion
s udies can be made, as, o example, p e alence o
pha macogenomic a ian s, e c. In addi ion, his ge-
nomic da a has been used o de ine he i s Spanish
Genome Re e ence Panel (SGRP1.0) o impu a ion.
This is he i s local eposi o y o a iabili y en i ely
p oduced by a c owdsou cing e o and cons i u es
an example o u u e ini ia i es o cha ac e ize local
a iabili y wo ldwide. CSVS is also pa o he GA4GH
Beacon ne wo k.
CSVS can be accessed a : h p://cs s.babelomics.
o g/.
INTRODUCTION
Sequencing echnologies ha e expe ienced an unp ece-
den ed de elopmen du ing he las decade (1) ha esul ed
in di e en in e na ional collabo a i e p ojec s (2–4) which
con ibu ed o an ex ao dina y inc ease in he knowledge
o he mu a ional spec um o diseases. This gene a ion o
knowledge has been especially signi ican in diseases wi h
high mo bidi y and mo ali y, caused by highly pene an
( ypically p o ein-coding) a ian s (5,6). In ac , mo e han
4500 monogenic diseases can nowadays be di ec ly diag-
nosed by pe sonalized genomics (7), a possibili y ha migh
soon be ex ended o he whole spec um o a e diseases
wi h a gene ic backg ound (8). Among he s a egies used
o disco e new disease a ian s, especially in monogenic
diso de s, equency-based il e ing has demons a ed o be
a e yuse ul ool(9). The a ionale is as ollows: a ian s
ha a e ela i ely common in a con ol popula ion (com-
mon a ia ion) a e likely benign (10), while a e a ian s
(especially i hey ha e unc ional consequences) ound in
mul iple a ec ed cases bu absen in he con ol popula ion
a e likely o cause disease (11–13). These il e s sea ch o
genes o a ian s p esen in all (o mos ) a ec ed indi iduals
bu in none (o e y ew) o he una ec ed con ol indi id-
uals. The e o e, i seems clea ha he a ailabili y o heal hy
con ols is a decisi e ac o o he p og ess o disco e y o
new disease de e minan s.
F om an his o ical pe spec i e, he 1000 Genomes P ojec
p oduced he i s comp ehensi e ca alogue o common hu-
man gene ic a ia ion (14). Howe e , i is known ha low
equency (wi h mino allele equencies, MAF, unde 5%)
and a e (MAF unde 0.5%) a ian s, ypically popula ion-
speci ic (15), a e poo ly ep esen ed in such ca alogue (14).
Ac ually, ecen s udies ha e desc ibed a ema kable local
componen (16–18) and a high s a i ica ion le el (19,20)in
many a e a ian s wi h unce ain unc ional consequences.
As a consequence o his, he isk o many diseases di e s in
dis inc human popula ions acco ding o hei gene ic back-
g ounds (21,22). In ac , he knowledge o he gene ic a i-
abili y o he local popula ion has been e ealed as a c i -
ical ac o o he disco e y o new disease a ian s (23).
All hese obse a ions highligh he need o popula ion-
speci ic ca alogues o gene ic a ia ion (24). Howe e , only
a ew ini ia i es o s udy gene ic a ia ion a he popula-
ion le el ha e been ca ied ou o da e, which include a
whole-genome sequence (WGS) s udy o 100 Malays (25),
he Genome o he Ne he lands, wi h low- esolu ion (∼13×)
WGS da a o 250 io- amilies om ac oss he en i e coun-
y (15), he F ench-Canadians s udy o 109 exomes (26),
he Medical Genome P ojec ha p oduced a ca alog o he
heal hy Spanish popula ion wi h almos 270 exomes (23),
he 3000 Finnish genomes (27) and he Icelandic popula ion
s udy o medium esolu ion (∼20×) WGS o 2636 indi idu-
als (28) o he high esolu ion (>30×) WGS o 1070 heal hy
Japanese indi iduals (29) and he ecen gene ic analysis o
he I anian popula ion (30).
In spi e o i s ecognized use ulness, la ge-scale sequenc-
ing p ojec s o coho s o local ‘heal hy’ popula ions equi e
expensi e conso ium-based p ojec s o ob ain a ep esen-
a i e sample o he popula ion a ge ed. Un o una ely,
unding bodies ha a e p one o suppo esea ch on dis-
eases, end o be, howe e , eluc an o und p ojec s ha
in ol e sys ema ic sequencing o heal hy indi iduals. In his
scena io, a c owdsou cing s a egy can p o ide a easible
al e na i e o adi ional wo king schemas by o ganizing
conso ia ha collec da a om di e en g oups ha ul i-
ma ely a e collec i ely bene i ed o he sample size coope -
a i ely ob ained. C owdsou cing is becoming a e y popu-
la s a egy in biomedicine (31) and can be de ined as ‘ he
p ocess o ge ing se ices, in o ma ion, labo o ideas by
ou sou cing h ough an open call, especially h ough he
In e ne ’ (32). Recen ly some examples o c owdsou ced e-
sea ch ha e demons a ed an inc eased accu acy in p edic -
ing b eas cance su i al (33), esponse o d ugs (34)o
o oxic compounds (35) om bo h, clinical and genomic
da a, and show how ‘c owdsou ced da a science challenges
can achie e in mon hs wha would ake yea s h ough con-
en ional esea ch app oaches’ (36).
MATERIALS AND METHODS
Subjec s
The da abase con ains de ailed allelic equencies co -
esponding o The MGP popula ion, sequenced in he
con ex o he Medical Genome P ojec (h p://www.
clinbioin osspa.es/con en /medical-genome-p ojec ),
which includes 267 heal hy, un ela ed samples o Spanish
o igin (EGA, accession: EGAS00001000938), o he heal hy
con ols, pa ien s o di e en diseases, accompanied in
some cases o un ela ed pheno ypically heal hy ca ie s.
The sequences we e con ibu ed by di e en conso iums
and p ojec s, including g oups om he Spanish Ne wo k
o Resea ch in Ra e Diseases, CIBERER, esul s om
he EnoD, (Undiagnosed Ra e Diseases p og amme; h ps:
//www.cibe e .es/en/ ans e sal-p og ammes/scien i ic-
p ojec s/undiagnosed- a e-diseases-p og amme-enod),
he P ojec Genome 1000 Na a a (NAGEN 1000;
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D1132 Nucleic Acids Resea ch, 2021, Vol. 49, Da abase issue
(h ps://www.nagen1000na a a.es/en), The Ra eGenomics
(h ps://www. a e-genomics.com/) om Mad id, and o he
esea ch g oups and ini ia i es ac oss Spain (37,38), which
cu en ly sum up a o al o 2027 genomic and exomic
sequences o un ela ed Spanish indi iduals.
Tes ing sample locali y
Ensu ing he Spanish locali y o he samples uploaded in
he CSVS is key o he p ojec . He e, we speci ically de-
eloped a me hodology o double-check he o igin o each
sample. Sequences belonging o di e en popula ions in
he 1000 genomes p ojec (14)we eused o ainaMa-
chine Lea ning based decision model o disc imina e Span-
ish samples om he es o popula ions. Fi s ly, SNPs co -
esponding o he genomic egions sha ed by all he sam-
ples ha ing a MAF >0.01 we e selec ed. Then, indi idual
ances y in 1000 genomes was es ima ed o 26 subpopu-
la ions using ADMIXTURE (39). The e o e, each indi id-
ual is desc ibed by a ec o o 26 ea u es ha co espond
o he p obabili ies o belonging o any o he 26 subpopu-
la ions o 1000 genomes. Then, a machine lea ning bina y
classi ica o y was buil using a well-known a ian o he
g adien boos ing machine: ex eme g adien boos ing (XG-
Boos )(40) (see Supplemen a y Me hods o de ails).
Tes ing sample kinship and ou lie sample de ec ion
A es o de e mine undesi ed samples based on hei pe -
cen age o no el a ian s in oduced in he da abase, ei he
by excess (po en ial noisy sample) o by de ec (close el-
a i e o indi idual al eady in he da abase), has also been
used o popula e he CSVS da abase. A lea e-one-ou c oss-
alida ion (LOOCV) s a egy was o build a dis ibu ion o
pe cen ages o a ian s con ibu ed by any single sample o
he pool o a ian s p esen in he es o he da abase. Sam-
ples we e conside ed po en ial ou lie s i o e pass 1.5 imes
he in e qua ile ange om i s and hi d qua ile in he
dis ibu ion ob ained (see Supplemen a y Me hods o de-
ails).
Cons uc ion o he e e ence impu a ion panel
Two al e na i e e e ence panels we e c ea ed o compa -
ison pu poses ha include he CSVS WGS a ian panel
composed o 228 samples plus: (i) he en i e 1000G e e -
ence panel (CSVS+1000G) and (ii) exclusi ely he Span-
ish popula ion (IBS subpopula ion) con ained in he 1000G
panel (CSVS+IBS), using he Minimac3 impu a ion ool
(41). The ou longes ch omosomes (ch omosome 1–4)
we e used o es ima e he co ela ion be ween eal and im-
pu ed geno ypes ( 2pa ame e ) and assess he impu a ion
accu acy (see Supplemen a y Me hods o de ails).
RESULTS
The CSVS da abase
Figu e 1A shows how da a con ibu ed by di e en ge-
nomic p ojec s unde go di e en quali y con ol s eps, in-
cluding an a i ac and kinship de ec ion es s and local-
i y es , desc ibed abo e. Then he o iginal VCFs a e ag-
g ega ed as coun s o a ian s, binned by ICD10 (h ps:
//www.icd10da a.com/) disease ca ego ies, and inse ed in
he CSVS da abase.
The CSVS in e ace
The ini ial sc een (Figu e 1B) equi es he accep-
ance o he ‘Te ms and condi ions o he use o he
CSVS da abase’ (h p://cs s.babelomics.o g/downloads/
CSVSTe msAndCondi ions use.pd ) be o e s a ing any
ope a ion. Once accep ed, di e en op ions can be used.
The sea ch op ion. This is he main op ion and allows
que ying he CSVS da abase. In he le panel (Figu e 1C)
que ies can be done by gene symbol o by ch omosomal
egions. Also, one o se e al disease ca ego ies can be ex-
cluded, and a ian s can be highligh ed using di e en ypes
o sco es (e.g. SIFT (42), Polyphen (43), CADD (44), Ge p
(45)) as well as Sequence On ology e ms o he a ia ion
consequences.
The esul s o he que y (Figu e 1D) include a lis o he
posi ions o which a ia ion has been ound in he Span-
ish popula ion along wi h complemen a y da a as: ch omo-
some, posi ion, e e ence allele and al e na i e allele, allelic
equencies in he Spanish popula ion, allelic equencies in
he 1000 genomes popula ions and in he EVS popula ions,
impac and conse a ion indexes (SIFT, Polyphen, CADD,
Ge p), he wo o he consequence ypes assigned o he
mu a ion and he pheno ypes, co esponding o known clin-
ical in o ma ion o he a ian s, ex ac ed om ClinVa
(46), COSMIC (47) and a e anno a ed in e ac i ely on each
que y using he CellBase (48) webse ices. Also a isualiza-
ion o he a ian in he genomic con ex is p o ided, based
on he Genome Maps b owse (49). Addi ionally, some ex-
a de ailed in o ma ion can be ound on he popula ion e-
quencies obse ed o he a ian , he pheno ype o he e -
ec .
Con ac eques . An in e es ing op ion is he Con ac e-
ques bu on, o e ed o any a ian in he que y esul s
panel, which is a local equi alen o a Ma chmake ex-
change se ice (50), ex ensi ely used o con ac he o iginal
con ibu o o a speci ic sequence.
Sa u a ion plo s. Sa u a ion plo s (Figu e 1F) p o ide an
in e es ing pe spec i e on he gene al conse a ion o he
gene s udied and, consequen ly on he possibili ies o dis-
co e ing new a ian s in o i . Genes highly cons ained o
change will sa u a e soon and a ela i ely low numbe o
indi iduals will cap u e mos o he ole a ed mu a ion he
gene can handle, while uncons ained genes will p esen a
s ill g owing slope, meaning ha he e a e s ill many a i-
an s ha can po en ially be disco e ed. Disco e ing a new
a ian in a sa u a ed gene (cons ained o change) can be
mo e ele an han he same inding in a non-sa u a ed gene
(uncons ained). Sa u a ion has a clea unc ional compo-
nen , ha can easily be e ealed by en ichmen analysis
o he genes anked by sa u a ion. Thus, when genes a e
anked by hei ela i e sa u a ion, en ichmen analysis us-
ing en ichR (51) shows how highly sa u a ed genes (con-
s ained) a e en iched in unc ional e ms ela ed o meio-
sis, cell signaling, p oli e a ion and homeos asis, while he
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Nucleic Acids Resea ch, 2021, Vol. 49, Da abase issue D1133
Figu e 1. (A) da a is con ibu ed by di e en genomic p ojec s and pass h ough di e en quali y con ol s eps including an a e ac and kinship es
( ha de ec s uppe ou lie s, wi h an unexpec ed high a io o p i a e a ian s, mos likely e o s, and lowe ou lie s, ha a e duplica es o close kinship
indi iduals) and locali y es be o e being inse ed in he da abase. (B) Ini ial CSVS page. (C) Que y panel in he Sea ch op ion. (D) Lis o a ian s ound
in he Spanish popula ion wi hin he selec ed egion along wi h complemen a y in o ma ion on impac , conse a ion, o he ’s popula ion equencies and
pheno ype. (E) genomic b owse ha displays he selec ed a ian in i s genomic con ex . (F) Sa u a ion plo . (G) Upda ed con en s o he da abase.
less sa u a ed (uncons ained) a e mo e ela ed o senso y
pe cep ion, immune esponse and simila unc ionali ies
(see Supplemen a y Resul s and Supplemen a y Figu e S1).
Figu e 2depic s how genes wi h high and low sa u a ion a e
dis ibu ed along he ch omosomes. In e es ingly, sex ch o-
mosomes seem o be en iched in low sa u a ed genes.
Downloads and s a is ics. Pa ial o o al downloads o he
agg ega ed da a a e possible upon he ecep ion o he co -
esponding da a download ag eemen duly signed.
The S a s op ion p o ides an upda ed iew o he con en
o he CSVS da abase.
The Spanish Genome Re e ence Panel (SGRP1.0)
Supplemen a y Figu e S2 shows he accu acy o he wo e -
e ence panels de i ed o impu a ion in he Spanish popula-
ion. Bo h e e ence panels including he CSVS WGS e e -
ence ou pe o med he 1000 genomes e e ence. The impu-
a ion accu acy inc eases when a ian s in a e si es we e in-
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D1134 Nucleic Acids Resea ch, 2021, Vol. 49, Da abase issue
Figu e 2. Ci cos plo showing he di e en genes wi h high sa u a ion (o ange) and low sa u a ion (g een) along he ch omosomes, which we e signi ican ly
en iched in unc ional e ms in Supplemen a y Figu e S1.
cluded (MAF >0.005). The mos ealis ic impu a ion panel
includes CSVS and he IBS popula ion o he 1000 genomes.
Va ian s o pha macogenomic in e es
In e indi idual gene ic a iabili y in genes in ol ed in d ug-
me abolizing enzymes and anspo e s ha e been linked
o di e ences in he e icacy and oxici y o many medica-
ions: Mo eo e , gene ic di e ences be ween human popu-
la ions a e becoming inc easingly ecognized as impo an
ac o s accoun ing o in e indi idual a ia ions in d ug e-
sponsi eness (52,53). App oxima ely one- i h o new d ugs
app o ed in he pas yea s demons a ed di e ences in e-
sponse ac oss e hnic g oups, leading o popula ion-speci ic
p esc ibing ecommenda ions (54). In spi e o he consen-
sus abou he exis ence o a ela i e homogenei y wi hin
Eu opean popula ions, popula ion-speci ic di e ences in
he Spanish popula ion we e ecen ly epo ed (23). Using
he indi iduals o he CSVS eposi o y, we add essed how
popula ion-speci ic di e ences in hose genes in ol ed in
d ug Abso p ion, Dis ibu ion, Me abolism, Exc e ion and
Toxici y (ADMET) could a ec in he a es and isks o
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Nucleic Acids Resea ch, 2021, Vol. 49, Da abase issue D1135
d ug ine icacy and/o ad e se d ug eac ions in he Span-
ish popula ion. We es ima ed he allele equencies o a o-
al o 142 pha macogene ic a ian s desc ibed in he Pha -
mGKB da abase (55) wi h pha macogene ic clinical ecom-
menda ions (Pha mGKB a ian s le el 1A and 1B) and a
o al o 40 o hese we e ound o be polymo phic in he
CSVS. When compa ed wi h he allele equencies calcu-
la ed om gene ic da a o 30 000 Eu opean non-Finnish
indi iduals (gnomAD (56)), no ele an equency di e -
ences be ween he gene al Eu opean popula ion and he
Spanish popula ion we e obse ed, being he mos di e -
en s2228001 (le el 1B) in XPC gene, s2108622 (le el 1A)
in CYP4F2 gene and s3892097 (le el 1A) In CYP2D6 gene
(P- alue ≤1×10−10). Rega ding he non-polymo phic
a ian s, we obse ed ha all o hem a e low- equency
a ian s (lowe han 0.00065) and we do no expec o ind a
he e ozygous indi idual due o he sample size in ou epos-
i o y (Supplemen a y Table S1).
Apa om he gene ic a ian s al eady ecommended o
be implemen ed in he clinical se ing, i was ound ha ge-
ne ic a iabili y wi h unc ional impac was go e ned by
ew high- equency a ian s o some genes, bu he unc-
ionali y o he majo i y o pha macogenes is domina ed
by a e gene ic a ian s (57). In addi ion, local a iabil-
i y in hese ADMET genes could also be e y ele an
o explaining a subs an ial pa o he unexplained in e -
indi idual di e ences in d ug esponse and oxici ies a
he popula ion-speci ic le el, so ha i is manda o y o
ha e a ailable popula ion-speci ic ca alogs o hese pha ma-
a ian s (mainly a e) o explo e hei con ibu ion o p e-
dic ions o d ug esponse. To examine his, we s udied he
a iabili y o he Spanish popula ion cap u ed by ou epos-
i o y in a o al o 421 well-known pha macogenes in ol ed
in d ug pha macokine ics and/o d ug esponse (Supple-
men a y Table S2). High-impac a ian s wi hin hose pha -
macogenes we e de ined acco ding o he Va ian E ec
P edic o (58) as hose ha ing ha ing he ollowing con-
sequence ypes: ameshi , splice accep o , splice dono ,
s a los , s op gained, s op los , ansc ip abla ion and
ansc ip ampli ica ion. Addi ionally, dele e ious missense
a ian s ca ego ized as dele e ious by CONDEL (59)o
ha ing a LoF ool sco e (60) lowe han he i s qua ile co -
esponding o he mos in ole an a ian s.
As be o e, he same compa ison wi h he co espond-
ing Eu opean non-Finnish a ian s ende ed a o al o 318
high impac a ian s and 235 likely dele e ious missense sin-
gle nucleo ide a ian s in he pha macogenes s udied. In-
e es ingly, 18 (5.6%) high impac a ian s and 18 (7.6%)
missense a ian s iden i ied we e p esen in ou Spanish
popula ion while no he e ozygo es we e obse ed in hese
posi ions ac oss ∼30 000 heal hy indi iduals o he Eu o-
pean non-Finnish popula ion. Also, a non-negligible pe -
cen age o p i a e a ia ion was obse ed in hese genes
encoding p o eins in ol ed in d ug me abolism, anspo ,
and esponse, and his in o ma ion can be used o pin-
poin ele an p i a e gene ic a ian s o be included in he
design o popula ion-speci ic pha macogene ic geno yping
a ays o be u ilized in he implemen a ion o pha maco-
gene ic diagnos ics in he clinical se ing (Supplemen a y
Table S3).
CSVS Beacon
Since 2017, CSVS makes i s genomic in o ma ion disco e -
able h ough he GA4GH Beacon ne wo k (h ps://beacon-
ne wo k.o g/). In o de o imp o e he pe o mance o he
CSVS Beacon API we se up an SQLi e da abase speci ic o
his pu pose. Al hough CSVS s o es da a in 1-base i can e-
spond o que ies in bo h 1-base o 0-base (Beacon eques s
da a in 0-base). A o m o di ec ly make Bacon-s yle que ies
is also a ailable (h p://ucscbeacon.clinbioin osspa.es/).
DISCUSSION
The gene ic a iabili y o he local popula ion is ecognized
as one o he mos ele an ac o s in he disco e y o new
disease a ian s, especially in mendelian diseases (6,8,23).
Howe e , genomic da a o heal hy indi iduals belonging
o he local popula ion o in e es a e o en sca ce when
no una ailable. The CSVS p o ides an o iginal solu ion o
his p oblem. The CSVS is a con inuously g owing esou ce
ha collec s genomic o exomic sequences o he Span-
ish local popula ion, no ma e whe he hese come om
heal hy o diseased indi iduals. The main objec i e is us-
ing he eposi o y as a pseudo-con ol popula ion o ind-
ing new disease-causing a ian s and genes, wi h he idea
ha ‘disease A is a heal hy con ol o disease B’. Despi e
gene pleio opy canno be comple ely uled ou , da a a e
binned a highe disease ICD10 ca ego ies, whe e his gene
p ope y can be conside ed negligible. Ac ually, esou ces
like Disgene (61) can be used in case o doub , and will
be inco po a ed o au oma ically exclude he p ope disease
ca ego ies, in u u e CSVS e sions. Since he collec ion o
popula ion-speci ic genomic da a om indi iduals wi h di -
e en diseases a e easie o collec han hose om heal hy
dono s, CSVS p o ides an example o he cons uc ion o
popula ion-speci ic pseudo-con ol eposi o ies by means
o c owdsou cing (31). Mo eo e , he CSVS Beacon and he
Con ac eques op ion makes o CSVS a ool wi h high po-
en ial o disco e abili y. Thus, CSVS se s he g ound and i
is an example o u u e ede a ed Eu opean in as uc u es
(62).
DATA AVAILABILITY
CSVS is an open esou ce a ailable a h p://cs s.
babelomics.o g/.
The CSVS code, as well as he code o he di e en es s
used is a ailable in he co esponding gi hub eposi o y:
h ps://gi hub.com/babelomics/CSVS.
SUPPLEMENTARY DATA
Supplemen a y Da a a e a ailable a NAR Online.
ACKNOWLEDGEMENTS
The Spanish Exome C owdsou cing Conso ium is a de
ac o conso ium cu en ly composed by: F´
a ima Al-
Shah ou , Ra ael A uch, Ja ie Beni ez, Luis An onio
Cas a˜
no, Ignacio del Cas illo, Ai o Delmi o, Ca mina
Espinos, Rose Gonz´
alez, Daniel G inbe g, Enca naci´
on
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D1136 Nucleic Acids Resea ch, 2021, Vol. 49, Da abase issue
Guill´
en, Pablo Lapunzina, Es he Lopez, Ram´
on Ma ´
ı,
Mon se a Mil´
a, Jos´
eMªMill´
an, Vi ginia Nunes, F ancesc
Palau, Belen Pe ez, Luis P´
e ez Ju ado, Rosa io Pe ona, Au-
o a Pujol, Feliciano Ramos, An onia Ribes, Jo di Rosell,
Eulalia Ro i a, Jo di Su all´
es, Isabel Tejada and Mag-
dalena Uga e.
FUNDING
Spanish Minis y o Economy and Compe i i eness
[SAF2017-88908-R, PT17/0009/0006 o J.D.; PI19/00321
and CIBERER ACCI-06/07/0036 o C.A., PI14-948, PI17-
1659 and CIBERER ACCI-06/07/0036 o M.A.M.P.];
Regional Go e nmen o Mad id, RAREGenomics-
CM [B2017/BMD-3721 o C.A. and B2017/BMD3721
o M.A.M.P.]; all co- unded wi h Eu opean Regional
De elopmen Funds (ERDF) as well as EU H2020-
INFRADEV-1-2015-1 ELIXIR-EXCELERATE [676559];
Uni e si y Chai UAM-IIS-FJD o Genomic Medicine
and he Ramon A eces Founda ion also suppo ed his
wo k. Funding o open access cha ge: Spanish Minis y
o Economy and Compe i i eness [SAF2017-88908-R].
Con lic o in e es s a emen . None decla ed.
REFERENCES
1. Ma dis,E.R. (2017) DNA sequencing echnologies: 2006–2016. Na .
P o oc.,12, 213.
2. Du bin,R.M., Abecasis,G.R., Al shule ,D.L., Au on,A.,
B ooks,L.D., Gibbs,R.A., Hu les,M.E. and McVean,G.A. (2010) A
map o human genome a ia ion om popula ion-scale sequencing.
Na u e,467, 1061–1073.
3. Dunham,I., Kundaje,A., Ald ed,S.F., Collins,P.J., Da is,C.A.,
Doyle,F., Eps ein,C.B., F ie ze,S., Ha ow,J., Kaul,R. e al. (2012) An
in eg a ed encyclopedia o DNA elemen s in he human genome.
Na u e,489, 57–74.
4. Fu,W., O’Conno ,T.D., Jun,G., Kang,H.M., Abecasis,G., Leal,S.M.,
Gab iel,S., Riede ,M.J., Al shule ,D., Shendu e,J. e al. (2013)
Analysis o 6,515 exomes e eals he ecen o igin o mos human
p o ein-coding a ian s. Na u e,493, 216–220.
5. Boyco ,K.M., Ra h,A., Chong,J.X., Ha ley,T., Alku aya,F.S.,
Baynam,G., B ookes,A.J., B udno,M., Ca acedo,A., den
Dunnen,J.T. e al. (2017) In e na ional coope a ion o enable he
diagnosis o all a e gene ic diseases. Am. J. Hum. Gene .,100,
695–705.
6. Boyco ,K.M., Vans one,M.R., Bulman,D.E. and MacKenzie,A.E.
(2013) Ra e-disease gene ics in he e a o nex -gene a ion sequencing:
disco e y o ansla ion. Na . Re . Gene .,14, 681–691.
7. Wenge ,A.M., Gu u u,H., Be ns ein,J.A. and Beje ano,G. (2017)
Sys ema ic eanalysis o clinical exome da a yields addi ional
diagnoses: implica ions o p o ide s. Gene . Med.,19, 209.
8. Boyco ,K.M., Ha ley,T., Biesecke ,L.G., Gibbs,R.A., Innes,A.M.,
Riess,O., Belmon ,J., Dunwoodie,S.L., Jojic,N., Lassmann,T. e al.
(2019) A diagnosis o all a e gene ic diseases: he ho izon and he
nex on ie s. Cell,177, 32–37.
9. Rehm,H.L., Bale,S.J., Bay ak-Toydemi ,P., Be g,J.S., B own,K.K.,
Deignan,J.L., F iez,M.J., Funke,B.H., Hegde,M.R. and Lyon,E.
(2013) ACMG clinical labo a o y s anda ds o nex -gene a ion
sequencing. Gene . Med.,15, 733.
10. Lek,M., Ka czewski,K.J., Minikel,E.V., Samocha,K.E., Banks,E.,
Fennell,T., O’Donnell-Lu ia,A.H., Wa e,J.S., Hill,A.J.,
Cummings,B.B. e al. (2016) Analysis o p o ein-coding gene ic
a ia ion in 60,706 humans. Na u e,536, 285.
11. Ng,S.B., Tu ne ,E.H., Robe son,P.D., Flyga e,S.D., Bigham,A.W.,
Lee,C., Sha e ,T., Wong,M., Bha acha jee,A. and Eichle ,E.E.
(2009) Ta ge ed cap u e and massi ely pa allel sequencing o 12
human exomes. Na u e,461, 272–276.
12. Ng,S.B., Buckingham,K.J., Lee,C., Bigham,A.W., Tabo ,H.K.,
Den ,K.M., Hu ,C.D., Shannon,P.T., Jabs,E.W., Nicke son,D.A.
e al. (2010) Exome sequencing iden i ies he cause o a mendelian
diso de . Na . Gene .,42, 30–35.
13. Ng,S.B., Bigham,A.W., Buckingham,K.J., Hannibal,M.C.,
McMillin,M.J., Gilde slee e,H.I., Beck,A.E., Tabo ,H.K.,
Coope ,G.M., Me o d,H.C. e al. (2010) Exome sequencing
iden i ies MLL2 mu a ions as a cause o Kabuki synd ome. Na .
Gene .,42, 790–793.
14. Abecasis,G.R., Au on,A., B ooks,L.D., DeP is o,M.A.,
Du bin,R.M., Handsake ,R.E., Kang,H.M., Ma h,G.T. and
McVean,G.A. (2012) An in eg a ed map o gene ic a ia ion om
1,092 human genomes. Na u e,491, 56–65.
15. The Genome o he Ne he lands Conso ium. (2014)
Whole-genome sequence a ia ion, popula ion s uc u e and
demog aphic his o y o he Du ch popula ion. Na . Gene .,46,
818–825.
16. Nelson,M.R., Wegmann,D., Ehm,M.G., Kessne ,D., S Jean,P.,
Ve zilli,C., Shen,J., Tang,Z., Bacanu,S.A., F ase ,D. e al. (2012) An
abundance o a e unc ional a ian s in 202 d ug a ge genes
sequenced in 14,002 people. Science,337, 100–104.
17. K yuko ,G.V., Pennacchio,L.A. and Sunyae ,S.R. (2007) Mos a e
missense alleles a e dele e ious in humans: implica ions o complex
disease and associa ion s udies. Am. J. Hum. Gene .,80, 727–739.
18. Ma h,G.T., Yu,F., Indap,A.R., Ga imella,K., G a el,S., Leong,W.F.,
Tyle -Smi h,C., Bainb idge,M., Blackwell,T., Zheng-B adley,X. e al.
(2011) The unc ional spec um o low- equency coding a ia ion.
Genome Biol.,12, R84.
19. Ma hieson,I. and McVean,G. (2012) Di e en ial con ounding o a e
and common a ian s in spa ially s uc u ed popula ions. Na .
Gene .,44, 243–246.
20. Mo eno-Es ada,A., G a el,S., Zakha ia,F., McCauley,J.L.,
By nes,J.K., Gignoux,C.R., O iz-Tello,P.A., Ma inez,R.J.,
Hedges,D.J., Mo is,R.W. e al. (2013) Recons uc ing he popula ion
gene ic his o y o he Ca ibbean. PLoS Gene .,9, e1003925.
21. Co ona,E., Chen,R., Siko a,M., Mo gan,A.A., Pa el,C.J.,
Ramesh,A., Bus aman e,C.D. and Bu e,A.J. (2013) Analysis o he
gene ic basis o disease in he con ex o wo ldwide human
ela ionships and mig a ion. PLoS Gene .,9, e1003447.
22. Fe nandez,R.M., Bleda,M., Luzon-To o,B., Ga cia-Alonso,L.,
A nold,S., S ibudiani,Y., Besmond,C., Lan ie i,F., Doan,B.,
Cecche ini,I. e al. (2013) Pa hways sys ema ically associa ed o
Hi schsp ung’s disease. O phane . J. Ra e. Dis.,8, 187.
23. Dopazo,J., Amadoz,A., Bleda,M., Ga cia-Alonso,L., Alem´
an,A.,
Ga c´
ıa-Ga c´
ıa,F., Rod iguez,J.A., Daub,J.T., Mun an´
e,G. and
Rueda,A. (2016) 267 Spanish exomes e eal popula ion-speci ic
di e ences in disease- ela ed gene ic a ia ion. Mol. Biol. E ol.,33,
1205–1218.
24. Bus aman e,C.D., Bu cha d,E.G. and De la Vega,F.M. (2011)
Genomics o he wo ld. Na u e,475, 163–165.
25. Wong,L.P., Ong,R.T., Poh,W.T., Liu,X., Chen,P., Li,R., Lam,K.K.,
Pillai,N.E., Sim,K.S., Xu,H. e al. (2013) Deep whole-genome
sequencing o 100 sou heas Asian Malays. Am. J. Hum. Gene .,92,
52–66.
26. Casals,F., Hodgkinson,A., Hussin,J., Idaghdou ,Y., B ua ,V., de
Mailla d,T., G enie ,J.C., Gbeha,E., Hamdan,F.F., Gi a d,S. e al.
(2013) Whole-exome sequencing e eals a apid change in he
equency o a e unc ional a ian s in a ounding popula ion o
humans. PLos Gene .,9, e1003815.
27. Lim,E.T., Wu z,P., Ha ulinna,A.S., Pal a,P., Tukiainen,T.,
Rehns om,K., Esko,T., Magi,R., Inouye,M., Lappalainen,T. e al.
(2014) Dis ibu ion and medical impac o loss-o - unc ion a ian s
in he Finnish ounde popula ion. PLoS Gene .,10, e1004494.
28. Gudbja sson,D.F., Helgason,H., Gudjonsson,S.A., Zink,F.,
Oddson,A., Gyl ason,A., Besenbache ,S., Magnusson,G.,
Halldo sson,B.V., Hja a son,E. e al. (2015) La ge-scale
whole-genome sequencing o he Icelandic popula ion. Na . Gene .,
47, 435–444.
29. Nagasaki,M., Yasuda,J., Ka suoka,F., Na iai,N., Kojima,K.,
Kawai,Y., Yamaguchi-Kaba a,Y., Yokozawa,J., Danjoh,I., Sai o,S.
e al. (2015) Ra e a ian disco e y by deep whole-genome
sequencing o 1,070 Japanese indi iduals. Na . Commun.,6, 8018.
30. Fa ahi,Z., Behesh ian,M., Mohseni,M., Pous chi,H., Sella s,E.,
Nezhadi,S.H., Amini,A., A zhangi,S., Jalal and,K. and Jamali,P.
(2019) I anome: a ca alog o genomic a ia ions in he I anian
popula ion. Hum. Mu a .,40, 1968–1984.
Downloaded om h ps://academic.oup.com/na /a icle/49/D1/D1130/5912819 by Uni e sidad de Se illa use on 08 Sep embe 2022
Nucleic Acids Resea ch, 2021, Vol. 49, Da abase issue D1137
31. Kha e,R., Good,B.M., Leaman,R., Su,A.I. and Lu,Z. (2015)
C owdsou cing in biomedicine: challenges and oppo uni ies. B ie .
Bioin o m.,17, 23–32.
32. Es ell´
es-A olas,E. and Gonz´
alez-Lad ´
on-de-Gue a a,F. (2012)
Towa ds an in eg a ed c owdsou cing de ini ion. J In Sci,38,
189–200.
33. Ma golin,A.A., Bilal,E., Huang,E., No man,T.C., O es ad,L.,
Mecham,B.H., Saue wine,B., Kellen,M.R., Mang a i e,L.M.,
Fu ia,M.D. e al. (2013) Sys ema ic analysis o challenge-d i en
imp o emen s in molecula p ognos ic models o b eas cance . Sci.
T ansl. Med.,5, 181 e1.
34. Plenge,R.M., G eenbe g,J.D., Mang a i e,L.M., De y,J.M.,
S ahl,E.A., Coenen,M.J., Ba on,A., Padyuko ,L., Kla eskog,L.,
G ege sen,P.K. e al. (2013) C owdsou cing gene ic p edic ion o
clinical u ili y in he heuma oid a h i is esponde challenge. Na .
Gene .,45, 468–469.
35. Edua i,F., Mang a i e,L.M., Wang,T., Tang,H., Ba e,J.C., Huang,R.,
No man,T., Kellen,M., Menden,M.P., Yang,J. e al. (2015) P edic ion
o human popula ion esponses o oxic compounds by a
collabo a i e compe i ion. Na . Bio ech.,33, 933–940.
36. Da is,S., Bu on-Simons,K., Bensellak,T., Ahsen,E.M., Checkley,L.,
Fos e ,G.J., Su,X., Moussa,A., Mapiye,D., Khoo,S.K. e al. (2019)
Le e aging c owdsou cing o accele a e global heal h solu ions. Na .
Bio echnol.,37, 848–850.
37. Gallego-Ma inez,A. and Lopez-Escamez,J.A. (2019) Gene ic
a chi ec u e o Menie e’s disease. Hea . Res., 107872.
38. Gui,H., Sch ieme ,D., Cheng,W.W., Chauhan,R.K., An iˇ
nolo,G.,
Be ios,C., Bleda,M., B ooks,A.S., B ouwe ,R.W. and Bu ns,A.J.
(2017) Whole exome sequencing coupled wi h unbiased unc ional
analysis e eals new Hi schsp ung disease genes. Genome Biol.,18, 48.
39. Alexande ,D.H., No emb e,J. and Lange,K. (2009) Fas model-based
es ima ion o ances y in un ela ed indi iduals. Genome Res.,19,
1655–1664.
40. Chen,T. and Gues in,C. (2016) In: P oceedings o he 22nd ACM
Sigkdd In e na ional Con e ence on Knowledge Disco e y and Da a
Mining. ACM, pp. 785–794.
41. Das,S., Fo e ,L., Sch¨
onhe ,S., Sido e,C., Locke,A.E., Kwong,A.,
V ieze,S.I., Chew,E.Y., Le y,S. and McGue,M. (2016)
Nex -gene a ion geno ype impu a ion se ice and me hods. Na .
Gene .,48, 1284.
42. Ng,P.C. and Heniko ,S. (2003) SIFT: P edic ing amino acid changes
ha a ec p o ein unc ion. Nucleic Acids Res.,31, 3812–3814.
43. Adzhubei,I., Jo dan,D.M. and Sunyae ,S.R. (2013) P edic ing
unc ional e ec o human missense mu a ions using PolyPhen-2.
Cu . P o oc. Hum. Gene .,76, 7.20.21–27.20.41.
44. Ki che ,M., Wi en,D.M., Jain,P., O’Roak,B.J., Coope ,G.M. and
Shendu e,J. (2014) A gene al amewo k o es ima ing he ela i e
pa hogenici y o human gene ic a ian s. Na . Gene .,46, 310–315.
45. Da ydo ,E.V., Goode,D.L., Si o a,M., Coope ,G.M., Sidow,A. and
Ba zoglou,S. (2010) Iden i ying a high ac ion o he human genome
o be unde selec i e cons ain using GERP++. PLoS Compu . Biol.,
6, e1001025.
46. Land um,M.J., Lee,J.M., Benson,M., B own,G.R., Chao,C.,
Chi ipi alla,S., Gu,B., Ha ,J., Ho man,D., Jang,W. e al. (2017)
ClinVa : imp o ing access o a ian in e p e a ions and suppo ing
e idence. Nucleic Acids Res.,46, D1062–D1067.
47. Ta e,J.G., Bam o d,S., Jubb,H.C., Sondka,Z., Bea e,D.M., Bindal,N.,
Bou selakis,H., Cole,C.G., C ea o e,C., Dawson,E. e al. (2018)
COSMIC: he Ca alogue O Soma ic Mu a ions In Cance . Nucleic
Acids Res.,47, D941–D947.
48. Bleda,M., Ta aga,J., de Ma ia,A., Sala e ,F., Ga cia-Alonso,L.,
Celma,M., Ma in,A., Dopazo,J. and Medina,I. (2012) CellBase, a
comp ehensi e collec ion o REST ul web se ices o e ie ing
ele an biological in o ma ion om he e ogeneous sou ces. Nucleic
Acids Res.,40, W609–W614.
49. Medina,I., Sala e ,F., Sanchez,R., de Ma ia,A., Alonso,R.,
Escoba ,P., Bleda,M. and Dopazo,J. (2013) Genome Maps, a new
gene a ion genome b owse . Nucleic Acids Res.,41, W41–W46.
50. Philippakis,A.A., Azza i i,D.R., Bel an,S., B ookes,A.J.,
B owns ein,C.A., B udno,M., B unne ,H.G., Buske,O.J., Ca ey,K.
and Doll,C. (2015) The Ma chmake Exchange: a pla o m o a e
disease gene disco e y. Hum. Mu a .,36, 915–921.
51. Kulesho ,M.V., Jones,M.R., Rouilla d,A.D., Fe nandez,N.F.,
Duan,Q., Wang,Z., Kople ,S., Jenkins,S.L., Jagodnik,K.M.,
Lachmann,A. e al. (2016) En ich : a comp ehensi e gene se
en ichmen analysis web se e 2016 upda e. Nucleic Acids Res.,44,
W90–W97.
52. Kubo,K., Oha a,M., Tachikawa,M., Ca alla i,L., Lee,M., Wen,M.,
Sco do,M., Nu escu,E., Pe e a,M. and Miyajima,A. (2017)
Popula ion di e ences in S-wa a in pha macokine ics among
A ican Ame icans, Asians and whi es: hei in luence on
pha macogene ic dosing algo i hms. Pha macogenomics J.,17,
494–500.
53. Meye ,U.A. (2004) Pha macogene ics– i e decades o he apeu ic
lessons om gene ic di e si y. Na . Re . Gene .,5, 669–676.
54. Ramamoo hy,A., Pacanowski,M., Bull,J. and Zhang,L. (2015)
Racial/e hnic di e ences in d ug disposi ion and esponse: e iew o
ecen ly app o ed d ugs. Clin. Pha macol. The .,97, 263–273.
55. Ba ba ino,J.M., Whi l-Ca illo,M., Al man,R.B. and Klein,T.E.
(2018) Pha mGKB: A wo ldwide esou ce o pha macogenomic
in o ma ion. Wiley In e discip. Re . Sys . Biol. Med.,10, e1417.
56. Koch,L. (2020) Explo ing human genomic di e si y wi h gnomAD.
Na . Re . Gene .,21, 448–448.
57. Ingelman-Sundbe g,M., Mk chian,S., Zhou,Y. and Lauschke,V.M.
(2018) In eg a ing a e gene ic a ian s in o pha macogene ic d ug
esponse p edic ions. Hum. Genomics,12, 26.
58. McLa en,W., Gil,L., Hun ,S.E., Ria ,H.S., Ri chie,G.R.,
Tho mann,A., Flicek,P. and Cunningham,F. (2016) The ensembl
a ian e ec p edic o . Genome Biol.,17, 122.
59. Gonz´
alez-P´
e ez,A. and L´
opez-Bigas,N. (2011) Imp o ing he
assessmen o he ou come o nonsynonymous SNVs wi h a
consensus dele e iousness sco e, Condel. Am. J. Hum. Gene .,88,
440–449.
60. Fadis a,J., Oskolko ,N., Hansson,O. and G oop,L. (2017) LoF ool: a
gene in ole ance sco e based on loss-o - unc ion a ian s in 60 706
indi iduals. Bioin o ma ics,33, 471–474.
61. Pi˜
ne o,J., Que al -Rosinach,N., B a o, `
A., Deu-Pons,J.,
Baue -Meh en,A., Ba on,M., Sanz,F. and Fu long,L.I. (2015)
DisGeNET: a disco e y pla o m o he dynamical explo a ion o
human diseases and hei genes. Da abase,2015, ba 028.
62. Saunde s,G., Baudis,M., Becke ,R., Bel an,S., B´
e oud,C., Bi ney,E.,
B ooksbank,C., B unak,S., Van den Bulcke,M. and D ysdale,R.
(2019) Le e aging Eu opean in as uc u es o access 1 million
human genomes by 2022. Na . Re . Gene .,20, 693–701.
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