Large-scale cis- and trans-eQTL analyses identify thousands of genetic loci and polygenic scores that regulate blood gene expression

U. Vosa; A. Claringbould; H.J. Westra; M.J. Bonder; P. Deelen; B. Zeng; H. Kirsten; A. Saha; R. Kreuzhuber; S. Yazar; H. Brugge; R. Oelen; D.H. de Vries; M.G.P. van der Wijst; S. Kasela; N. Pervjakova; I. Alves; M.J. Fave; M. Agbessi; M.W. Christiansen; R. Jansen; I. Seppala; L. Tong; A. Teumer; K. Schramm; G. Hemani; J. Verlouw; H. Yaghootkar; R.S. Flitman; A. Brown; V. Kukushkina; A. Kalnapenkis; S. Rueger; E. Porcu; J. Kronberg; J. Kettunen; B. Lee; F.T. Zhang; T. Qi; J.A. Hernandez; W. Arindrarto; F. Beutner; J. Dmitrieva; M. Elansary; B.P. Fairfax; M. Georges; B.T. Heijmans; A.W. Hewitt; BIOS Consortium; i2QTL Consortium; C.D.A. Stehouwer

doi:10.1038/s41588-021-00913-z

Large-scale cis- and trans-eQTL analyses identify thousands of genetic loci and polygenic scores that regulate blood gene expression

U. Vosa^*
, A. Claringbould^*
, H.J. Westra
, M.J. Bonder
, P. Deelen
, B. Zeng
, H. Kirsten
, A. Saha
, R. Kreuzhuber
, S. Yazar
, H. Brugge
, R. Oelen
, D.H. de Vries
, M.G.P. van der Wijst
, S. Kasela
, N. Pervjakova
, I. Alves
, M.J. Fave
, M. Agbessi
, M.W. Christiansen

R. Jansen, I. Seppala, L. Tong, A. Teumer, K. Schramm, G. Hemani, J. Verlouw, H. Yaghootkar, R.S. Flitman, A. Brown, V. Kukushkina, A. Kalnapenkis, S. Rueger, E. Porcu, J. Kronberg, J. Kettunen, B. Lee, F.T. Zhang, T. Qi, J.A. Hernandez, W. Arindrarto, F. Beutner, J. Dmitrieva, M. Elansary, B.P. Fairfax, M. Georges, B.T. Heijmans, A.W. Hewitt, BIOS Consortium, i2QTL Consortium, C.D.A. Stehouwer

^*Corresponding author for this work

Research output: Contribution to journal › Article › Academic › peer-review

Abstract

Trait-associated genetic variants affect complex phenotypes primarily via regulatory mechanisms on the transcriptome. To investigate the genetics of gene expression, we performed cis- and trans-expression quantitative trait locus (eQTL) analyses using blood-derived expression from 31,684 individuals through the eQTLGen Consortium. We detected cis-eQTL for 88% of genes, and these were replicable in numerous tissues. Distal trans-eQTL (detected for 37% of 10,317 trait-associated variants tested) showed lower replication rates, partially due to low replication power and confounding by cell type composition. However, replication analyses in single-cell RNA-seq data prioritized intracellular trans-eQTL. Trans-eQTL exerted their effects via several mechanisms, primarily through regulation by transcription factors. Expression of 13% of the genes correlated with polygenic scores for 1,263 phenotypes, pinpointing potential drivers for those traits. In summary, this work represents a large eQTL resource, and its results serve as a starting point for in-depth interpretation of complex phenotypes.Analyses of expression profiles from whole blood of 31,684 individuals identify cis-expression quantitative trait loci (eQTL) effects for 88% of genes and trans-eQTL effects for 37% of trait-associated variants.

Original language	English
Pages (from-to)	1300-1310
Number of pages	22
Journal	Nature Genetics
Volume	53
Issue number	9
Early online date	2021
DOIs	https://doi.org/10.1038/s41588-021-00913-z
Publication status	Published - Sept 2021

Keywords

GENOME-WIDE ASSOCIATION
SERINE BIOSYNTHESIS
HUMAN TRANSCRIPTOME
ARCHITECTURE
DISEASE
DEFICIENCY
RELEVANCE
DISORDER
LINKS
RISK

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10.1038/s41588-021-00913-z

http://hdl.handle.net/1887/3214285Licence: Other

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Vosa, U., Claringbould, A., Westra, H. J., Bonder, M. J., Deelen, P., Zeng, B., Kirsten, H., Saha, A., Kreuzhuber, R., Yazar, S., Brugge, H., Oelen, R., de Vries, D. H., van der Wijst, M. G. P., Kasela, S., Pervjakova, N., Alves, I., Fave, M. J., Agbessi, M., ... Stehouwer, C. D. A. (2021). Large-scale cis- and trans-eQTL analyses identify thousands of genetic loci and polygenic scores that regulate blood gene expression. Nature Genetics, 53(9), 1300-1310. https://doi.org/10.1038/s41588-021-00913-z

@article{e08a1ffc553c477091b16d28af830bc9,

title = "Large-scale cis- and trans-eQTL analyses identify thousands of genetic loci and polygenic scores that regulate blood gene expression",

abstract = "Trait-associated genetic variants affect complex phenotypes primarily via regulatory mechanisms on the transcriptome. To investigate the genetics of gene expression, we performed cis- and trans-expression quantitative trait locus (eQTL) analyses using blood-derived expression from 31,684 individuals through the eQTLGen Consortium. We detected cis-eQTL for 88\% of genes, and these were replicable in numerous tissues. Distal trans-eQTL (detected for 37\% of 10,317 trait-associated variants tested) showed lower replication rates, partially due to low replication power and confounding by cell type composition. However, replication analyses in single-cell RNA-seq data prioritized intracellular trans-eQTL. Trans-eQTL exerted their effects via several mechanisms, primarily through regulation by transcription factors. Expression of 13\% of the genes correlated with polygenic scores for 1,263 phenotypes, pinpointing potential drivers for those traits. In summary, this work represents a large eQTL resource, and its results serve as a starting point for in-depth interpretation of complex phenotypes.Analyses of expression profiles from whole blood of 31,684 individuals identify cis-expression quantitative trait loci (eQTL) effects for 88\% of genes and trans-eQTL effects for 37\% of trait-associated variants.",

keywords = "GENOME-WIDE ASSOCIATION, SERINE BIOSYNTHESIS, HUMAN TRANSCRIPTOME, ARCHITECTURE, DISEASE, DEFICIENCY, RELEVANCE, DISORDER, LINKS, RISK",

author = "U. Vosa and A. Claringbould and H.J. Westra and M.J. Bonder and P. Deelen and B. Zeng and H. Kirsten and A. Saha and R. Kreuzhuber and S. Yazar and H. Brugge and R. Oelen and \{de Vries\}, D.H. and \{van der Wijst\}, M.G.P. and S. Kasela and N. Pervjakova and I. Alves and M.J. Fave and M. Agbessi and M.W. Christiansen and R. Jansen and I. Seppala and L. Tong and A. Teumer and K. Schramm and G. Hemani and J. Verlouw and H. Yaghootkar and R.S. Flitman and A. Brown and V. Kukushkina and A. Kalnapenkis and S. Rueger and E. Porcu and J. Kronberg and J. Kettunen and B. Lee and F.T. Zhang and T. Qi and J.A. Hernandez and W. Arindrarto and F. Beutner and J. Dmitrieva and M. Elansary and B.P. Fairfax and M. Georges and B.T. Heijmans and A.W. Hewitt and \{BIOS Consortium\} and \{i2QTL Consortium\} and C.D.A. Stehouwer",

note = "Funding Information: The cohorts participating in this study list their acknowledgements in the cohort-specific sections of the Supplementary Note. This work is supported by a grant from the European Research Council (ERC, ERC Starting Grant agreement number 637640 ImmRisk), a VIDI grant (917.14.374) and a VICI grant from the Netherlands Organisation for Scientific Research (NWO) to L.F. This work has been supported by the European Regional Development Fund and the program Mobilitas Pluss (MOBTP108) to U.V{\~o}sa. The project was supported by the {\textquoteleft}De Drie Lichten{\textquoteright} foundation in the Netherlands with a grant to A.C. M.G.N. is supported by ZonMw grants 849200011 and 531003014 from the Netherlands Organisation for Health Research and Development, a VENI grant from the NWO (VI.Veni.191G.030) and a Jacobs Foundation research fellowship. H.Y. is funded by a Diabetes UK RD Lawrence fellowship (17/0005594). This project received funding from the ERC under the European Union{\textquoteright}s Horizon 2020 research and innovation program (grant agreement no. 772376 (EScORIAL)) to J.H.V. T.E. and A.K. were supported by the Estonian Research Council grant PRG (PRG1291). A.Battle was supported by NIH grant R01MH109905, NIH grant R01HG008150 (NHGRI; Non-Coding Variants Program) and NIH grant R01MH101814 (NIH Common Fund; GTEx Program). M.G.P.v.d.W. was funded by the Nederlandse Organisatie voor Wetenschappelijk onderzoek, NWO-Veni 192.029. This work was supported by NIH grants R21ES024834 (B.Pierce), R01ES020506 (B.Pierce), R01ES023834 (B.Pierce), R35ES028379 (B.Pierce) and R01CA107431 (H.A.). This work was supported by the Sigrid Juselius Foundation (J.Kettunen) and funds from the Academy of Finland (grant numbers 297338 and 307247) (J.Kettunen) and the Novo Nordisk Foundation (grant number NNF17OC0026062) (J.Kettunen). S.Ripatti was supported by the Academy of Finland Centre of Excellence in Complex Disease Genetics (grant no. 312062). M.G. was supported by EU Horizon 2020 (grant 733100 for SYSCID) and a grant from the Excellence of Science (FNRS and FWO) (grant no. 30770923). We acknowledge support from the BBMRI-NL (Biobanking and Biomolecular Resources Research Infrastructure 184.021.007 and 184.033.111), Spinozapremie (NWO 56-464-14192), the ERC (ERC Advanced 230374) and the KNAW Academy Professor Award (PAH/6635) to D.I.B. G.H. works in a unit that receives funding from the UK MRC (MC\_UU\_12013/1\&2\&5) and the University of Bristol. S.B. was supported by the Swiss National Science Foundation (310030-152724). B.M.P. was supported by CHARGE infrastructure grant number HJ105756 for the HVH cohort. This work was supported by the German Federal Ministry of Education and Research (BMBF) within the framework of the e:Med research and funding concept (grant 01ZX1906B) and by LIFE (Leipzig Research Center for Civilization Diseases), Universit{\"a}t Leipzig (which is funded by the European Union, by the European Regional Development Fund and by the Free State of Saxony within the framework of the excellence initiative to H.K. and M.Scholz). We thank the UMCG Genomics Coordination Center, the MOLGENIS team, the UG Center for Information Technology and the UMCG research IT program and their sponsors, in particular the BBMRI-NL for data storage, high-performance computing and web hosting infrastructure. The BBMRI-NL is a research infrastructure financed by the NWO (grant number 184.033.111). We thank K. McIntyre for editing the manuscript text. Publisher Copyright: {\textcopyright} 2021, The Author(s), under exclusive licence to Springer Nature America, Inc.",

year = "2021",

month = sep,

doi = "10.1038/s41588-021-00913-z",

language = "English",

volume = "53",

pages = "1300--1310",

journal = "Nature Genetics",

issn = "1061-4036",

publisher = "Nature Research",

number = "9",

}

Vosa, U, Claringbould, A, Westra, HJ, Bonder, MJ, Deelen, P, Zeng, B, Kirsten, H, Saha, A, Kreuzhuber, R, Yazar, S, Brugge, H, Oelen, R, de Vries, DH, van der Wijst, MGP, Kasela, S, Pervjakova, N, Alves, I, Fave, MJ, Agbessi, M, Christiansen, MW, Jansen, R, Seppala, I, Tong, L, Teumer, A, Schramm, K, Hemani, G, Verlouw, J, Yaghootkar, H, Flitman, RS, Brown, A, Kukushkina, V, Kalnapenkis, A, Rueger, S, Porcu, E, Kronberg, J, Kettunen, J, Lee, B, Zhang, FT, Qi, T, Hernandez, JA, Arindrarto, W, Beutner, F, Dmitrieva, J, Elansary, M, Fairfax, BP, Georges, M, Heijmans, BT, Hewitt, AW, BIOS Consortium, i2QTL Consortium & Stehouwer, CDA 2021, 'Large-scale cis- and trans-eQTL analyses identify thousands of genetic loci and polygenic scores that regulate blood gene expression', Nature Genetics, vol. 53, no. 9, pp. 1300-1310. https://doi.org/10.1038/s41588-021-00913-z

TY - JOUR

T1 - Large-scale cis- and trans-eQTL analyses identify thousands of genetic loci and polygenic scores that regulate blood gene expression

AU - Vosa, U.

AU - Claringbould, A.

AU - Westra, H.J.

AU - Bonder, M.J.

AU - Deelen, P.

AU - Zeng, B.

AU - Kirsten, H.

AU - Saha, A.

AU - Kreuzhuber, R.

AU - Yazar, S.

AU - Brugge, H.

AU - Oelen, R.

AU - de Vries, D.H.

AU - van der Wijst, M.G.P.

AU - Kasela, S.

AU - Pervjakova, N.

AU - Alves, I.

AU - Fave, M.J.

AU - Agbessi, M.

AU - Christiansen, M.W.

AU - Jansen, R.

AU - Seppala, I.

AU - Tong, L.

AU - Teumer, A.

AU - Schramm, K.

AU - Hemani, G.

AU - Verlouw, J.

AU - Yaghootkar, H.

AU - Flitman, R.S.

AU - Brown, A.

AU - Kukushkina, V.

AU - Kalnapenkis, A.

AU - Rueger, S.

AU - Porcu, E.

AU - Kronberg, J.

AU - Kettunen, J.

AU - Lee, B.

AU - Zhang, F.T.

AU - Qi, T.

AU - Hernandez, J.A.

AU - Arindrarto, W.

AU - Beutner, F.

AU - Dmitrieva, J.

AU - Elansary, M.

AU - Fairfax, B.P.

AU - Georges, M.

AU - Heijmans, B.T.

AU - Hewitt, A.W.

AU - BIOS Consortium

AU - i2QTL Consortium

AU - Stehouwer, C.D.A.

N1 - Funding Information: The cohorts participating in this study list their acknowledgements in the cohort-specific sections of the Supplementary Note. This work is supported by a grant from the European Research Council (ERC, ERC Starting Grant agreement number 637640 ImmRisk), a VIDI grant (917.14.374) and a VICI grant from the Netherlands Organisation for Scientific Research (NWO) to L.F. This work has been supported by the European Regional Development Fund and the program Mobilitas Pluss (MOBTP108) to U.Võsa. The project was supported by the ‘De Drie Lichten’ foundation in the Netherlands with a grant to A.C. M.G.N. is supported by ZonMw grants 849200011 and 531003014 from the Netherlands Organisation for Health Research and Development, a VENI grant from the NWO (VI.Veni.191G.030) and a Jacobs Foundation research fellowship. H.Y. is funded by a Diabetes UK RD Lawrence fellowship (17/0005594). This project received funding from the ERC under the European Union’s Horizon 2020 research and innovation program (grant agreement no. 772376 (EScORIAL)) to J.H.V. T.E. and A.K. were supported by the Estonian Research Council grant PRG (PRG1291). A.Battle was supported by NIH grant R01MH109905, NIH grant R01HG008150 (NHGRI; Non-Coding Variants Program) and NIH grant R01MH101814 (NIH Common Fund; GTEx Program). M.G.P.v.d.W. was funded by the Nederlandse Organisatie voor Wetenschappelijk onderzoek, NWO-Veni 192.029. This work was supported by NIH grants R21ES024834 (B.Pierce), R01ES020506 (B.Pierce), R01ES023834 (B.Pierce), R35ES028379 (B.Pierce) and R01CA107431 (H.A.). This work was supported by the Sigrid Juselius Foundation (J.Kettunen) and funds from the Academy of Finland (grant numbers 297338 and 307247) (J.Kettunen) and the Novo Nordisk Foundation (grant number NNF17OC0026062) (J.Kettunen). S.Ripatti was supported by the Academy of Finland Centre of Excellence in Complex Disease Genetics (grant no. 312062). M.G. was supported by EU Horizon 2020 (grant 733100 for SYSCID) and a grant from the Excellence of Science (FNRS and FWO) (grant no. 30770923). We acknowledge support from the BBMRI-NL (Biobanking and Biomolecular Resources Research Infrastructure 184.021.007 and 184.033.111), Spinozapremie (NWO 56-464-14192), the ERC (ERC Advanced 230374) and the KNAW Academy Professor Award (PAH/6635) to D.I.B. G.H. works in a unit that receives funding from the UK MRC (MC_UU_12013/1&2&5) and the University of Bristol. S.B. was supported by the Swiss National Science Foundation (310030-152724). B.M.P. was supported by CHARGE infrastructure grant number HJ105756 for the HVH cohort. This work was supported by the German Federal Ministry of Education and Research (BMBF) within the framework of the e:Med research and funding concept (grant 01ZX1906B) and by LIFE (Leipzig Research Center for Civilization Diseases), Universität Leipzig (which is funded by the European Union, by the European Regional Development Fund and by the Free State of Saxony within the framework of the excellence initiative to H.K. and M.Scholz). We thank the UMCG Genomics Coordination Center, the MOLGENIS team, the UG Center for Information Technology and the UMCG research IT program and their sponsors, in particular the BBMRI-NL for data storage, high-performance computing and web hosting infrastructure. The BBMRI-NL is a research infrastructure financed by the NWO (grant number 184.033.111). We thank K. McIntyre for editing the manuscript text. Publisher Copyright: © 2021, The Author(s), under exclusive licence to Springer Nature America, Inc.

PY - 2021/9

Y1 - 2021/9

N2 - Trait-associated genetic variants affect complex phenotypes primarily via regulatory mechanisms on the transcriptome. To investigate the genetics of gene expression, we performed cis- and trans-expression quantitative trait locus (eQTL) analyses using blood-derived expression from 31,684 individuals through the eQTLGen Consortium. We detected cis-eQTL for 88% of genes, and these were replicable in numerous tissues. Distal trans-eQTL (detected for 37% of 10,317 trait-associated variants tested) showed lower replication rates, partially due to low replication power and confounding by cell type composition. However, replication analyses in single-cell RNA-seq data prioritized intracellular trans-eQTL. Trans-eQTL exerted their effects via several mechanisms, primarily through regulation by transcription factors. Expression of 13% of the genes correlated with polygenic scores for 1,263 phenotypes, pinpointing potential drivers for those traits. In summary, this work represents a large eQTL resource, and its results serve as a starting point for in-depth interpretation of complex phenotypes.Analyses of expression profiles from whole blood of 31,684 individuals identify cis-expression quantitative trait loci (eQTL) effects for 88% of genes and trans-eQTL effects for 37% of trait-associated variants.

AB - Trait-associated genetic variants affect complex phenotypes primarily via regulatory mechanisms on the transcriptome. To investigate the genetics of gene expression, we performed cis- and trans-expression quantitative trait locus (eQTL) analyses using blood-derived expression from 31,684 individuals through the eQTLGen Consortium. We detected cis-eQTL for 88% of genes, and these were replicable in numerous tissues. Distal trans-eQTL (detected for 37% of 10,317 trait-associated variants tested) showed lower replication rates, partially due to low replication power and confounding by cell type composition. However, replication analyses in single-cell RNA-seq data prioritized intracellular trans-eQTL. Trans-eQTL exerted their effects via several mechanisms, primarily through regulation by transcription factors. Expression of 13% of the genes correlated with polygenic scores for 1,263 phenotypes, pinpointing potential drivers for those traits. In summary, this work represents a large eQTL resource, and its results serve as a starting point for in-depth interpretation of complex phenotypes.Analyses of expression profiles from whole blood of 31,684 individuals identify cis-expression quantitative trait loci (eQTL) effects for 88% of genes and trans-eQTL effects for 37% of trait-associated variants.

KW - GENOME-WIDE ASSOCIATION

KW - SERINE BIOSYNTHESIS

KW - HUMAN TRANSCRIPTOME

KW - ARCHITECTURE

KW - DISEASE

KW - DEFICIENCY

KW - RELEVANCE

KW - DISORDER

KW - LINKS

KW - RISK

U2 - 10.1038/s41588-021-00913-z

DO - 10.1038/s41588-021-00913-z

M3 - Article

C2 - 34475573

SN - 1061-4036

VL - 53

SP - 1300

EP - 1310

JO - Nature Genetics

JF - Nature Genetics

IS - 9

ER -

Large-scale cis- and trans-eQTL analyses identify thousands of genetic loci and polygenic scores that regulate blood gene expression

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Keywords

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