Mapping genomic loci implicates genes and synaptic biology in schizophrenia.
Journal
Nature
ISSN: 1476-4687
Titre abrégé: Nature
Pays: England
ID NLM: 0410462
Informations de publication
Date de publication:
04 2022
04 2022
Historique:
received:
12
08
2020
accepted:
10
01
2022
pubmed:
10
4
2022
medline:
23
4
2022
entrez:
9
4
2022
Statut:
ppublish
Résumé
Schizophrenia has a heritability of 60-80%
Identifiants
pubmed: 35396580
doi: 10.1038/s41586-022-04434-5
pii: 10.1038/s41586-022-04434-5
pmc: PMC9392466
mid: NIHMS1824605
doi:
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
502-508Subventions
Organisme : NIMH NIH HHS
ID : R01 MH116281
Pays : United States
Organisme : NIH HHS
ID : 5R01 MH101519
Pays : United States
Organisme : Wellcome Trust
ID : 085475/B/08/Z
Pays : United Kingdom
Organisme : NIMH NIH HHS
ID : R01 MH124873
Pays : United States
Organisme : NIMH NIH HHS
ID : U01 MH109536
Pays : United States
Organisme : NIMH NIH HHS
ID : R01 MH101519
Pays : United States
Organisme : Medical Research Council
ID : MC_UU_00007/10
Pays : United Kingdom
Organisme : Wellcome Trust
Pays : United Kingdom
Organisme : Medical Research Council
ID : MR/L010305/1
Pays : United Kingdom
Organisme : Medical Research Council
ID : G0901310
Pays : United Kingdom
Organisme : Wellcome Trust
ID : 085475/Z/08/Z
Pays : United Kingdom
Organisme : NIMH NIH HHS
ID : R01 MH119243
Pays : United States
Organisme : Medical Research Council
ID : G0800509
Pays : United Kingdom
Organisme : NIMH NIH HHS
ID : R01 MH106575
Pays : United States
Organisme : NINDS NIH HHS
ID : R37 NS036715
Pays : United States
Organisme : NIMH NIH HHS
ID : K01 MH121659
Pays : United States
Organisme : NIMH NIH HHS
ID : U01 MH109514
Pays : United States
Investigateurs
Nan Dai
(N)
Qin Wenwen
(Q)
D B Wildenauer
(DB)
Feranindhya Agiananda
(F)
Nurmiati Amir
(N)
Ronald Antoni
(R)
Tiana Arsianti
(T)
Asmarahadi Asmarahadi
(A)
H Diatri
(H)
Prianto Djatmiko
(P)
Irmansyah Irmansyah
(I)
Siti Khalimah
(S)
Irmia Kusumadewi
(I)
Profitasari Kusumaningrum
(P)
Petrin R Lukman
(PR)
Martina W Nasrun
(MW)
N S Safyuni
(NS)
Prasetyawan Prasetyawan
(P)
G Semen
(G)
Kristiana Siste
(K)
Heriani Tobing
(H)
Natalia Widiasih
(N)
Tjhin Wiguna
(T)
D Wulandari
(D)
None Evalina
(N)
A J Hananto
(AJ)
Joni H Ismoyo
(JH)
T M Marini
(TM)
Supiyani Henuhili
(S)
Muhammad Reza
(M)
Suzy Yusnadewi
(S)
Alexej Abyzov
(A)
Schahram Akbarian
(S)
Allison Ashley-Koch
(A)
Harm van Bakel
(H)
Michael Breen
(M)
Miguel Brown
(M)
Julien Bryois
(J)
Becky Carlyle
(B)
Alex Charney
(A)
Gerard Coetzee
(G)
Gregory Crawford
(G)
Stella Dracheva
(S)
Prashant Emani
(P)
Peggy Farnham
(P)
Menachem Fromer
(M)
Timur Galeev
(T)
Mike Gandal
(M)
Mark Gerstein
(M)
Gina Giase
(G)
Kiran Girdhar
(K)
Fernando Goes
(F)
Kay Grennan
(K)
Mengting Gu
(M)
Brittney Guerra
(B)
Gamze Gursoy
(G)
Gabriel Hoffman
(G)
Thomas Hyde
(T)
Andrew Jaffe
(A)
Shan Jiang
(S)
Yan Jiang
(Y)
Amira Kefi
(A)
Yunjung Kim
(Y)
Robert Kitchen
(R)
James A Knowles
(JA)
Fides Lay
(F)
Donghoon Lee
(D)
Mingfeng Li
(M)
Chunyu Liu
(C)
Shuang Liu
(S)
Eugenio Mattei
(E)
Fabio Navarro
(F)
Xinghua Pan
(X)
Mette A Peters
(MA)
Dalila Pinto
(D)
Sirisha Pochareddy
(S)
Damon Polioudakis
(D)
Michael Purcaro
(M)
Shaun Purcell
(S)
Henry Pratt
(H)
Tim Reddy
(T)
Suhn Rhie
(S)
Panagiotis Roussos
(P)
Joel Rozowsky
(J)
Stephan Sanders
(S)
Nenad Sestan
(N)
Anurag Sethi
(A)
Xu Shi
(X)
Annie Shieh
(A)
Vivek Swarup
(V)
Anna Szekely
(A)
Daifeng Wang
(D)
Jonathan Warrell
(J)
Sherman Weissman
(S)
Zhiping Weng
(Z)
Kevin White
(K)
Jennifer Wiseman
(J)
Heather Witt
(H)
Hyejung Won
(H)
Shannon Wood
(S)
Feinan Wu
(F)
Xuming Xu
(X)
Lijing Yao
(L)
Peter Zandi
(P)
Maria J Arranz
(MJ)
Steven Bakker
(S)
Stephan Bender
(S)
Elvira Bramon
(E)
David A Collier
(DA)
Benedicto Crepo-Facorro
(B)
Jeremy Hall
(J)
Conrad Iyegbe
(C)
René Kahn
(R)
Stephen Lawrie
(S)
Cathryn Lewis
(C)
Kuang Lin
(K)
Don H Linszen
(DH)
Ignacio Mata
(I)
Andrew McIntosh
(A)
Robin M Murray
(RM)
Roel A Ophoff
(RA)
Jim van Os
(J)
John Powell
(J)
Dan Rujescu
(D)
Muriel Walshe
(M)
Matthias Weisbrod
(M)
Tilmann Achsel
(T)
Maria Andres-Alonso
(M)
Claudia Bagni
(C)
Àlex Bayés
(À)
Thomas Biederer
(T)
Nils Brose
(N)
Tyler C Brown
(TC)
John Jia En Chua
(JJE)
Marcelo P Coba
(MP)
L Niels Cornelisse
(LN)
Arthur P H de Jong
(APH)
Jaime de Juan-Sanz
(J)
Daniela C Dieterich
(DC)
Guoping Feng
(G)
Hana L Goldschmidt
(HL)
Eckart D Gundelfinger
(ED)
Casper Hoogenraad
(C)
Richard L Huganir
(RL)
Steven E Hyman
(SE)
Cordelia Imig
(C)
Reinhard Jahn
(R)
Hwajin Jung
(H)
Pascal S Kaeser
(PS)
Eunjoon Kim
(E)
Frank Koopmans
(F)
Michael R Kreutz
(MR)
Noa Lipstein
(N)
Harold D MacGillavry
(HD)
Robert Malenka
(R)
Peter S McPherson
(PS)
Vincent O'Connor
(V)
Rainer Pielot
(R)
Timothy A Ryan
(TA)
Dnyanada Sahasrabudhe
(D)
Carlo Sala
(C)
Morgan Sheng
(M)
Karl-Heinz Smalla
(KH)
August B Smit
(AB)
Thomas C Südhof
(TC)
Paul D Thomas
(PD)
Ruud F Toonen
(RF)
Jan R T van Weering
(JRT)
Matthijs Verhage
(M)
Chiara Verpelli
(C)
Lieuwe de Haan
(L)
Therese van Amelsvoort
(T)
Ruud van Winkel
(R)
Anna Gareeva
(A)
Pak C Sham
(PC)
Yongyong Shi
(Y)
David St Clair
(D)
Jim van Os
(J)
Commentaires et corrections
Type : CommentIn
Informations de copyright
© 2022. The Author(s), under exclusive licence to Springer Nature Limited.
Références
Owen, M. J., Sawa, A. & Mortensen, P. B. Schizophrenia. Lancet 388, 86–97 (2016).
pubmed: 26777917
pmcid: 4940219
doi: 10.1016/S0140-6736(15)01121-6
Plana-Ripoll, O. et al. A comprehensive analysis of mortality-related health metrics associated with mental disorders: a nationwide, register-based cohort study. Lancet 394, 1827–1835 (2019).
pubmed: 31668728
doi: 10.1016/S0140-6736(19)32316-5
Momen, N. C. et al. Association between mental disorders and subsequent medical conditions. N. Engl. J. Med. 382, 1721–1731 (2020).
pubmed: 32348643
pmcid: 7261506
doi: 10.1056/NEJMoa1915784
Jääskeläinen, E. et al. A systematic review and meta-analysis of recovery in schizophrenia. Schizophr. Bull. 39, 1296–1306 (2013).
pubmed: 23172003
doi: 10.1093/schbul/sbs130
International Schizophrenia Consortium. Common polygenic variation contributes to risk of schizophrenia and bipolar disorder. Nature 460, 748–752 (2009).
Pocklington, A. J. et al. Novel findings from CNVs implicate inhibitory and excitatory signaling complexes in schizophrenia. Neuron 86, 1203–1214 (2015).
pubmed: 26050040
pmcid: 4460187
doi: 10.1016/j.neuron.2015.04.022
Singh, T. et al. The contribution of rare variants to risk of schizophrenia in individuals with and without intellectual disability. Nat. Genet. 49, 1167–1173 (2017).
pubmed: 28650482
pmcid: 5533219
doi: 10.1038/ng.3903
Rees, E. et al. De novo mutations identified by exome sequencing implicate rare missense variants in SLC6A1 in schizophrenia. Nat. Neurosci 23, 179–184 (2020).
pubmed: 31932766
pmcid: 7007300
doi: 10.1038/s41593-019-0565-2
Lam, M. et al. Comparative genetic architectures of schizophrenia in East Asian and European populations. Nat. Genet. 51, 1670–1678 (2019).
pubmed: 31740837
pmcid: 6885121
doi: 10.1038/s41588-019-0512-x
Bigdeli, T. B. et al. Contributions of common genetic variants to risk of schizophrenia among individuals of African and Latino ancestry. Mol. Psychiatry 25, 2455–2467 (2020).
pubmed: 31591465
doi: 10.1038/s41380-019-0517-y
Biological insights from 108 schizophrenia-associated genetic loci. Nature 511, 421–427 (2014).
Räsänen, S., Pakaslahti, A., Syvälahti, E., Jones, P. B. & Isohanni, M. Sex differences in schizophrenia: a review. Nord. J. Psychiatry 54, 37–45 (2000).
doi: 10.1080/080394800427564
Zeng, J. et al. Widespread signatures of natural selection across human complex traits and functional genomic categories. Nat. Commun. 12, 1164 (2021).
pubmed: 33608517
pmcid: 7896067
doi: 10.1038/s41467-021-21446-3
Aguet, F. et al. Genetic effects on gene expression across human tissues. Nature 550, 204–213 (2017).
doi: 10.1038/nature24277
Genome-wide association study identifies five new schizophrenia loci. Nat. Genet. 43, 969–978 (2011).
Skene, N. G. et al. Genetic identification of brain cell types underlying schizophrenia. Nat. Genet. 50, 825–833 (2018).
pubmed: 29785013
pmcid: 6477180
doi: 10.1038/s41588-018-0129-5
Habib, N. et al. Massively parallel single-nucleus RNA-seq with DroNc-seq. Nat. Methods 14, 955–958 (2017).
pubmed: 28846088
pmcid: 5623139
doi: 10.1038/nmeth.4407
Zeisel, A. et al. Molecular architecture of the mouse nervous system. Cell 174, 999–1014 (2018).
pubmed: 30096314
pmcid: 6086934
doi: 10.1016/j.cell.2018.06.021
Koopmans, F. et al. SynGO: an evidence-based, expert-curated knowledge base for the synapse. Neuron 103, 217–234 (2019).
pubmed: 31171447
pmcid: 6764089
doi: 10.1016/j.neuron.2019.05.002
Benner, C. et al. FINEMAP: efficient variable selection using summary data from genome-wide association studies. Bioinformatics 32, 1493–1501 (2016).
pubmed: 26773131
pmcid: 4866522
doi: 10.1093/bioinformatics/btw018
Sakuntabhai, A. et al. Mutations in ATP2A2, encoding a Ca
pubmed: 10080178
doi: 10.1038/6784
Cederlöf, M. et al. The association between Darier disease, bipolar disorder, and schizophrenia revisited: a population-based family study. Bipolar Disord. 17, 340–344 (2015).
pubmed: 25213221
doi: 10.1111/bdi.12257
Pardiñas, A. F. et al. Common schizophrenia alleles are enriched in mutation-intolerant genes and in regions under strong background selection. Nat. Genet. 50, 381–389 (2018).
pubmed: 29483656
pmcid: 5918692
doi: 10.1038/s41588-018-0059-2
Zhu, Z. et al. Integration of summary data from GWAS and eQTL studies predicts complex trait gene targets. Nat. Genet. 48, 481–487 (2016).
pubmed: 27019110
doi: 10.1038/ng.3538
Gandal, M. J. et al. Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder. Science 362, eaat8127 (2018).
pubmed: 30545856
pmcid: 6443102
doi: 10.1126/science.aat8127
O’Brien, H. E. et al. Expression quantitative trait loci in the developing human brain and their enrichment in neuropsychiatric disorders. Genome Biol. 19, 194 (2018).
pubmed: 30419947
pmcid: 6231252
doi: 10.1186/s13059-018-1567-1
Võsa, U. et al. Large-scale cis- and trans-eQTL analyses identify thousands of genetic loci and polygenic scores that regulate blood gene expression. Nat. Genet. 53, 1300–1310 (2021).
pubmed: 34475573
pmcid: 8432599
doi: 10.1038/s41588-021-00913-z
Wang, D. et al. Comprehensive functional genomic resource and integrative model for the human brain. Science 362, eaat8464 (2018).
pubmed: 30545857
pmcid: 6413328
doi: 10.1126/science.aat8464
Galvan, L. et al. The striatal kinase DCLK3 produces neuroprotection against mutant huntingtin. Brain 141, 1434–1454 (2018).
pubmed: 29534157
pmcid: 5917821
doi: 10.1093/brain/awy057
Singh, T. et al. Rare coding variants in 10 genes confer substantial risk for schizophrenia. Nature https://doi.org/10.1038/s41586-022-04556-w (2022).
Rees, E. et al. Analysis of intellectual disability copy number variants for association with schizophrenia. JAMA Psychiatry 73, 963–969 (2016).
pubmed: 27602560
pmcid: 5014093
doi: 10.1001/jamapsychiatry.2016.1831
Fromer, M. et al. De novo mutations in schizophrenia implicate synaptic networks. Nature 506, 179–184 (2014).
pubmed: 24463507
pmcid: 4237002
doi: 10.1038/nature12929
Kaplanis, J. et al. Evidence for 28 genetic disorders discovered by combining healthcare and research data. Nature 586, 757–762 (2020).
Satterstrom, F. K. et al. Large-scale exome sequencing study implicates both developmental and functional changes in the neurobiology of autism. Cell 180, 568–584 (2020).
pubmed: 31981491
pmcid: 7250485
doi: 10.1016/j.cell.2019.12.036
Luo, Y. et al. Exploring the genetic architecture of inflammatory bowel disease by whole-genome sequencing identifies association at ADCY7. Nat. Genet. 49, 186–192 (2017).
pubmed: 28067910
pmcid: 5289625
doi: 10.1038/ng.3761
Cheng, Y. et al. Rare genetic variants affecting urine metabolite levels link population variation to inborn errors of metabolism. Nat. Commun. 12, 964 (2021).
pubmed: 33574263
pmcid: 7878905
doi: 10.1038/s41467-020-20877-8
Singh, T., Neale, B. M. & Daly, M. J. Exome sequencing identifies rare coding variants in 10 genes which confer substantial risk for schizophrenia. Preprint at https://doi.org/10.1101/2020.09.18.20192815 (2020).
Priya, A., Johar, K. & Wong-Riley, M. T. T. Specificity protein 4 functionally regulates the transcription of NMDA receptor subunits GluN1, GluN2A, and GluN2B. Biochim. Biophys. Acta 1833, 2745–2756 (2013).
pubmed: 23871830
doi: 10.1016/j.bbamcr.2013.07.002
Ripke, S. et al. Genome-wide association analysis identifies 13 new risk loci for schizophrenia. Nat. Genet. 45, 1150–1159 (2013).
pubmed: 23974872
pmcid: 3827979
doi: 10.1038/ng.2742
Kirov, G. et al. De novo CNV analysis implicates specific abnormalities of postsynaptic signalling complexes in the pathogenesis of schizophrenia. Mol. Psychiatry 17, 142–153 (2012).
pubmed: 22083728
doi: 10.1038/mp.2011.154
Lek, M. et al. Analysis of protein-coding genetic variation in 60,706 humans. Nature 536, 285–291 (2016).
pubmed: 27535533
pmcid: 5018207
doi: 10.1038/nature19057
Fagerberg, L. et al. Analysis of the human tissue-specific expression by genome-wide integration of transcriptomics and antibody-based proteomics. Mol. Cell. Proteomics 13, 397–406 (2014).
pubmed: 24309898
doi: 10.1074/mcp.M113.035600
Stephens, R. et al. Gene organisation, sequence variation and isochore structure at the centromeric boundary of the human MHC. J. Mol. Biol. 291, 789–799 (1999).
Lam, M. et al. RICOPILI: Rapid Imputation for COnsortias PIpeLIne. Bioinformatics 36, 930–933 (2019).
pmcid: 7868045
doi: 10.1093/bioinformatics/btz633
Purcell, S., Neale, B., Todd-Brown, K., Thomas, L. & Ferreira, M. A. PLINK: a toolset for whole-genome association and population-based linkage analysis. Am. J. Hum. Genet. 81, 559–575 (2007).
pubmed: 17701901
pmcid: 1950838
doi: 10.1086/519795
Devlin, B. & Roeder, K. Genomic control for association studies. Biometrics 55, 997–1004 (1999).
pubmed: 11315092
doi: 10.1111/j.0006-341X.1999.00997.x
Reference-based phasing using the Haplotype Reference Consortium panel. Nat. Genet. 48, 1443–1448 (2016).
Das, S. et al. Next-generation genotype imputation service and methods. Nat. Genet. 48, 1284–1287 (2016).
pubmed: 27571263
pmcid: 5157836
doi: 10.1038/ng.3656
The Haplotype Reference Consortium. A reference panel of 64,976 haplotypes for genotype imputation. Nat. Genet. 48, 1279–1283 (2016).
O’Connell, J. et al. Haplotype estimation for biobank-scale data sets. Nat. Genet. 48, 817–820 (2016).
pubmed: 27270105
pmcid: 4926957
doi: 10.1038/ng.3583
Bycroft, C. et al. The UK Biobank resource with deep phenotyping and genomic data. Nature 562, 203–209 (2018).
pubmed: 30305743
pmcid: 6786975
doi: 10.1038/s41586-018-0579-z
Chang, C. C. et al. Second-generation PLINK: rising to the challenge of larger and richer datasets. Gigascience 4, 7 (2015).
pubmed: 25722852
pmcid: 4342193
doi: 10.1186/s13742-015-0047-8
Lee, J. J. et al. Gene discovery and polygenic prediction from a genome-wide association study of educational attainment in 1.1 million individuals. Nat. Genet. 50, 1112–1121 (2018).
pubmed: 30038396
pmcid: 6393768
doi: 10.1038/s41588-018-0147-3
Vittinghoff, E. & McCulloch, C. E. Relaxing the rule of ten events per variable in logistic and cox regression. Am. J. Epidemiol. 165, 710–718 (2007).
pubmed: 17182981
doi: 10.1093/aje/kwk052
Heinze, G. & Ploner, M. A SAS macro, S-PLUS library and R package to perform logistic regression without convergence problems. Technical report 2/2004 https://cemsiis.meduniwien.ac.at/fileadmin/user_upload/_imported/fileadmin/msi_akim/CeMSIIS/KB/programme/tr2_2004.pdf (Medical University of Vienna, 2004).
Viechtbauer, W. Conducting meta-analyses in R with the metafor package. J. Stat. Softw. 36, 1–48 (2010).
doi: 10.18637/jss.v036.i03
Lee, S. H., Goddard, M. E., Wray, N. R. & Visscher, P. M. A better coefficient of determination for genetic profile analysis. Genet. Epidemiol. 36, 214–224 (2012).
pubmed: 22714935
doi: 10.1002/gepi.21614
Martínez-Camblor, P. Fully non-parametric receiver operating characteristic curve estimation for random-effects meta-analysis. Stat. Methods Med. Res. 26, 5–20 (2017).
pubmed: 24872352
doi: 10.1177/0962280214537047
Bryois, J. et al. Genetic identification of cell types underlying brain complex traits yields insights into the etiology of Parkinson’s disease. Nat. Genet. 52, 482–493 (2020).
pubmed: 32341526
pmcid: 7930801
doi: 10.1038/s41588-020-0610-9
de Leeuw, C. A., Mooij, J. M., Heskes, T. & Posthuma, D. MAGMA: generalized gene-set analysis of GWAS data. PLoS Comput. Biol. 11, e1004219 (2015).
pubmed: 25885710
pmcid: 4401657
doi: 10.1371/journal.pcbi.1004219
Finucane, H. K. et al. Heritability enrichment of specifically expressed genes identifies disease-relevant tissues and cell types. Nat. Genet. 50, 621–629 (2018).
pubmed: 29632380
pmcid: 5896795
doi: 10.1038/s41588-018-0081-4
Durinck, S., Spellman, P. T., Birney, E. & Huber, W. Mapping identifiers for the integration of genomic datasets with the R/ Bioconductor package biomaRt. Nat. Protoc. 4, 1184–1191 (2009).
pubmed: 19617889
pmcid: 3159387
doi: 10.1038/nprot.2009.97
Maston, G. A., Evans, S. K. & Green, M. R. Transcriptional regulatory elements in the human genome. Annu. Rev. Genomics Hum. Genet. 7, 29–59 (2006).
pubmed: 16719718
doi: 10.1146/annurev.genom.7.080505.115623
A reference panel of 64,976 haplotypes for genotype imputation. Nat. Genet. 48, 1279–1283 (2016).
Genovese, G. et al. Increased burden of ultra-rare protein-altering variants among 4,877 individuals with schizophrenia. Nat. Neurosci. 19, 1433–1441 (2016).
pubmed: 27694994
pmcid: 5104192
doi: 10.1038/nn.4402
Merico, D., Isserlin, R., Stueker, O., Emili, A. & Bader, G. D. Enrichment map: a network-based method for gene-set enrichment visualization and interpretation. PLoS One 5, e13984 (2010).
pubmed: 21085593
pmcid: 2981572
doi: 10.1371/journal.pone.0013984
Benner, C. et al. Prospects of fine-mapping trait-associated genomic regions by using summary statistics from genome-wide association studies. Am. J. Hum. Genet 101, 539–551 (2017).
pubmed: 28942963
pmcid: 5630179
doi: 10.1016/j.ajhg.2017.08.012
Võsa, U. et al. Large-scale cis- and trans-eQTL analysis identify thousands of genetic loci and polygenic scores that regulate blood gene expression. Nat. Genet. 53, 1300–1310 (2021).
pubmed: 34475573
pmcid: 8432599
doi: 10.1038/s41588-021-00913-z
Sonnega, A. et al. Cohort profile: The Health and Retirement Study (HRS). Int. J. Epidemiol. 43, 576–585 (2014).
pubmed: 24671021
pmcid: 3997380
doi: 10.1093/ije/dyu067
Yang, J., Lee, S. H., Goddard, M. E. & Visscher, P. M. GCTA: a tool for genome-wide complex trait analysis. Am. J. Hum. Genet. 88, 76–82 (2011).
pubmed: 21167468
pmcid: 3014363
doi: 10.1016/j.ajhg.2010.11.011
Yang, J. et al. Conditional and joint multiple-SNP analysis of GWAS summary statistics identifies additional variants influencing complex traits. Nat. Genet. 44, 369–375 (2012).
pubmed: 22426310
pmcid: 3593158
doi: 10.1038/ng.2213
Gusev, A. et al. Integrative approaches for large-scale transcriptome-wide association studies. Nat. Genet. 48, 245–252 (2016).
pubmed: 26854917
pmcid: 4767558
doi: 10.1038/ng.3506
Zhang, W. et al. Integrative transcriptome imputation reveals tissue-specific and shared biological mechanisms mediating susceptibility to complex traits. Nat. Commun. 10, 3834 (2019).
pubmed: 31444360
pmcid: 6707297
doi: 10.1038/s41467-019-11874-7