Mendelian randomization integrating GWAS and eQTL data reveals genetic determinants of complex and clinical traits

Eleonora Porcu; Sina Rueger; Kaido Lepik; Mawusse Agbessi; Habibul Ahsan; Isabel Alves; Anand Andiappan; Wibowo Arindrarto; Philip Awadalla; Alexis Battle; Frank Beutner; Marc Jan Bonder; Dorret Boomsma; Mark Christiansen; Annique Claringbould; Patrick Deelen; Tonu Esko; Marie-Julie Fave; Lude Franke; Timothy Frayling; Sina A. Gharib; Gregory Gibson; Bastiaan T. Heijmans; Gibran Hemani; Rick Jansen; Mika Kahonen; Anette Kalnapenkis; Silva Kasela; Johannes Kettunen; Yungil Kim; Holger Kirsten; Peter Kovacs; Knut Krohn; Jaanika Kronberg-Guzman; Viktorija Kukushkina; Bernett Lee; Terho Lehtimaki; Markus Loeffler; Urko M. Marigorta; Hailang Mei; Lili Milani; Grant W. Montgomery; Martina Mueler-Nurasyid; Matthias Nauck; Coen D. A. Stehouwer; Aaron Isaacs; Casper G. Schalkwijk; Carla J. H. van der Kallen; Marleen M. J. van Greevenbroek; eQTLgen Consortium; BIOS Consortium; Zoltan Kutalik

doi:10.1038/s41467-019-10936-0

Mendelian randomization integrating GWAS and eQTL data reveals genetic determinants of complex and clinical traits

Eleonora Porcu^*, Sina Rueger, Kaido Lepik, Mawusse Agbessi, Habibul Ahsan, Isabel Alves, Anand Andiappan, Wibowo Arindrarto, Philip Awadalla, Alexis Battle, Frank Beutner, Marc Jan Bonder, Dorret Boomsma, Mark Christiansen, Annique Claringbould, Patrick Deelen, Tonu Esko, Marie-Julie Fave, Lude Franke, Timothy FraylingSina A. Gharib, Gregory Gibson, Bastiaan T. Heijmans, Gibran Hemani, Rick Jansen, Mika Kahonen, Anette Kalnapenkis, Silva Kasela, Johannes Kettunen, Yungil Kim, Holger Kirsten, Peter Kovacs, Knut Krohn, Jaanika Kronberg-Guzman, Viktorija Kukushkina, Bernett Lee, Terho Lehtimaki, Markus Loeffler, Urko M. Marigorta, Hailang Mei, Lili Milani, Grant W. Montgomery, Martina Mueler-Nurasyid, Matthias Nauck, Coen D. A. Stehouwer, Aaron Isaacs, Casper G. Schalkwijk, Carla J. H. van der Kallen, Marleen M. J. van Greevenbroek, eQTLgen Consortium, BIOS Consortium, Zoltan Kutalik^*

^*Corresponding author for this work

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

Abstract

Genome-wide association studies (GWAS) have identified thousands of variants associated with complex traits, but their biological interpretation often remains unclear. Most of these variants overlap with expression QTLs, indicating their potential involvement in regulation of gene expression. Here, we propose a transcriptome-wide summary statistics-based Mendelian Randomization approach (TWMR) that uses multiple SNPs as instruments and multiple gene expression traits as exposures, simultaneously. Applied to 43 human phenotypes, it uncovers 3,913 putatively causal gene-trait associations, 36% of which have no genome-wide significant SNP nearby in previous GWAS. Using independent association summary statistics, we find that the majority of these loci were missed by GWAS due to power issues. Noteworthy among these links is educational attainment-associated BSCL2, known to carry mutations leading to a Mendelian form of encephalopathy. We also find pleiotropic causal effects suggestive of mechanistic connections. TWMR better accounts for pleiotropy and has the potential to identify biological mechanisms underlying complex traits.

Original language	English
Article number	3300
Number of pages	12
Journal	Nature Communications
Volume	10
Issue number	1
DOIs	https://doi.org/10.1038/s41467-019-10936-0
Publication status	Published - 24 Jul 2019

Keywords

INSTRUMENTAL VARIABLES
VARIANTS
DISEASE
ASSOCIATION
MUTATION
STATISTICS
EXPRESSION
PLEIOTROPY
OBESITY
FAMILY

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Porcu, E., Rueger, S., Lepik, K., Agbessi, M., Ahsan, H., Alves, I., Andiappan, A., Arindrarto, W., Awadalla, P., Battle, A., Beutner, F., Bonder, M. J., Boomsma, D., Christiansen, M., Claringbould, A., Deelen, P., Esko, T., Fave, M.-J., Franke, L., ... Kutalik, Z. (2019). Mendelian randomization integrating GWAS and eQTL data reveals genetic determinants of complex and clinical traits. Nature Communications, 10(1), Article 3300. https://doi.org/10.1038/s41467-019-10936-0

@article{5cc4e1065ad941b689b95647e9e9a57d,

title = "Mendelian randomization integrating GWAS and eQTL data reveals genetic determinants of complex and clinical traits",

abstract = "Genome-wide association studies (GWAS) have identified thousands of variants associated with complex traits, but their biological interpretation often remains unclear. Most of these variants overlap with expression QTLs, indicating their potential involvement in regulation of gene expression. Here, we propose a transcriptome-wide summary statistics-based Mendelian Randomization approach (TWMR) that uses multiple SNPs as instruments and multiple gene expression traits as exposures, simultaneously. Applied to 43 human phenotypes, it uncovers 3,913 putatively causal gene-trait associations, 36% of which have no genome-wide significant SNP nearby in previous GWAS. Using independent association summary statistics, we find that the majority of these loci were missed by GWAS due to power issues. Noteworthy among these links is educational attainment-associated BSCL2, known to carry mutations leading to a Mendelian form of encephalopathy. We also find pleiotropic causal effects suggestive of mechanistic connections. TWMR better accounts for pleiotropy and has the potential to identify biological mechanisms underlying complex traits.",

keywords = "INSTRUMENTAL VARIABLES, VARIANTS, DISEASE, ASSOCIATION, MUTATION, STATISTICS, EXPRESSION, PLEIOTROPY, OBESITY, FAMILY",

author = "Eleonora Porcu and Sina Rueger and Kaido Lepik and Mawusse Agbessi and Habibul Ahsan and Isabel Alves and Anand Andiappan and Wibowo Arindrarto and Philip Awadalla and Alexis Battle and Frank Beutner and Bonder, {Marc Jan} and Dorret Boomsma and Mark Christiansen and Annique Claringbould and Patrick Deelen and Tonu Esko and Marie-Julie Fave and Lude Franke and Timothy Frayling and Gharib, {Sina A.} and Gregory Gibson and Heijmans, {Bastiaan T.} and Gibran Hemani and Rick Jansen and Mika Kahonen and Anette Kalnapenkis and Silva Kasela and Johannes Kettunen and Yungil Kim and Holger Kirsten and Peter Kovacs and Knut Krohn and Jaanika Kronberg-Guzman and Viktorija Kukushkina and Bernett Lee and Terho Lehtimaki and Markus Loeffler and Marigorta, {Urko M.} and Hailang Mei and Lili Milani and Montgomery, {Grant W.} and Martina Mueler-Nurasyid and Matthias Nauck and Stehouwer, {Coen D. A.} and Aaron Isaacs and Schalkwijk, {Casper G.} and {van der Kallen}, {Carla J. H.} and {van Greevenbroek}, {Marleen M. J.} and {eQTLgen Consortium} and {BIOS Consortium} and Zoltan Kutalik",

note = "Funding Information: This work was supported by grants from the Swiss National Science Foundation (31003A_143914 and 32003B_173092 to ZK and 31003A_160203 to AR) and the Horizon2020 Twinning project ePerMed (692145 to AR). This research has been conducted using the UK Biobank Resource (#16389). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Publisher Copyright: {\textcopyright} 2019, The Author(s).",

year = "2019",

month = jul,

day = "24",

doi = "10.1038/s41467-019-10936-0",

language = "English",

volume = "10",

journal = "Nature Communications",

issn = "2041-1723",

publisher = "Nature Publishing Group",

number = "1",

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Porcu, E, Rueger, S, Lepik, K, Agbessi, M, Ahsan, H, Alves, I, Andiappan, A, Arindrarto, W, Awadalla, P, Battle, A, Beutner, F, Bonder, MJ, Boomsma, D, Christiansen, M, Claringbould, A, Deelen, P, Esko, T, Fave, M-J, Franke, L, Frayling, T, Gharib, SA, Gibson, G, Heijmans, BT, Hemani, G, Jansen, R, Kahonen, M, Kalnapenkis, A, Kasela, S, Kettunen, J, Kim, Y, Kirsten, H, Kovacs, P, Krohn, K, Kronberg-Guzman, J, Kukushkina, V, Lee, B, Lehtimaki, T, Loeffler, M, Marigorta, UM, Mei, H, Milani, L, Montgomery, GW, Mueler-Nurasyid, M, Nauck, M, Stehouwer, CDA, Isaacs, A , Schalkwijk, CG , van der Kallen, CJH , van Greevenbroek, MMJ, eQTLgen Consortium, BIOS Consortium & Kutalik, Z 2019, 'Mendelian randomization integrating GWAS and eQTL data reveals genetic determinants of complex and clinical traits', Nature Communications, vol. 10, no. 1, 3300. https://doi.org/10.1038/s41467-019-10936-0

TY - JOUR

T1 - Mendelian randomization integrating GWAS and eQTL data reveals genetic determinants of complex and clinical traits

AU - Porcu, Eleonora

AU - Rueger, Sina

AU - Lepik, Kaido

AU - Agbessi, Mawusse

AU - Ahsan, Habibul

AU - Alves, Isabel

AU - Andiappan, Anand

AU - Arindrarto, Wibowo

AU - Awadalla, Philip

AU - Battle, Alexis

AU - Beutner, Frank

AU - Bonder, Marc Jan

AU - Boomsma, Dorret

AU - Christiansen, Mark

AU - Claringbould, Annique

AU - Deelen, Patrick

AU - Esko, Tonu

AU - Fave, Marie-Julie

AU - Franke, Lude

AU - Frayling, Timothy

AU - Gharib, Sina A.

AU - Gibson, Gregory

AU - Heijmans, Bastiaan T.

AU - Hemani, Gibran

AU - Jansen, Rick

AU - Kahonen, Mika

AU - Kalnapenkis, Anette

AU - Kasela, Silva

AU - Kettunen, Johannes

AU - Kim, Yungil

AU - Kirsten, Holger

AU - Kovacs, Peter

AU - Krohn, Knut

AU - Kronberg-Guzman, Jaanika

AU - Kukushkina, Viktorija

AU - Lee, Bernett

AU - Lehtimaki, Terho

AU - Loeffler, Markus

AU - Marigorta, Urko M.

AU - Mei, Hailang

AU - Milani, Lili

AU - Montgomery, Grant W.

AU - Mueler-Nurasyid, Martina

AU - Nauck, Matthias

AU - Stehouwer, Coen D. A.

AU - Isaacs, Aaron

AU - Schalkwijk, Casper G.

AU - van der Kallen, Carla J. H.

AU - van Greevenbroek, Marleen M. J.

AU - eQTLgen Consortium

AU - BIOS Consortium

AU - Kutalik, Zoltan

N1 - Funding Information: This work was supported by grants from the Swiss National Science Foundation (31003A_143914 and 32003B_173092 to ZK and 31003A_160203 to AR) and the Horizon2020 Twinning project ePerMed (692145 to AR). This research has been conducted using the UK Biobank Resource (#16389). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Publisher Copyright: © 2019, The Author(s).

PY - 2019/7/24

Y1 - 2019/7/24

N2 - Genome-wide association studies (GWAS) have identified thousands of variants associated with complex traits, but their biological interpretation often remains unclear. Most of these variants overlap with expression QTLs, indicating their potential involvement in regulation of gene expression. Here, we propose a transcriptome-wide summary statistics-based Mendelian Randomization approach (TWMR) that uses multiple SNPs as instruments and multiple gene expression traits as exposures, simultaneously. Applied to 43 human phenotypes, it uncovers 3,913 putatively causal gene-trait associations, 36% of which have no genome-wide significant SNP nearby in previous GWAS. Using independent association summary statistics, we find that the majority of these loci were missed by GWAS due to power issues. Noteworthy among these links is educational attainment-associated BSCL2, known to carry mutations leading to a Mendelian form of encephalopathy. We also find pleiotropic causal effects suggestive of mechanistic connections. TWMR better accounts for pleiotropy and has the potential to identify biological mechanisms underlying complex traits.

AB - Genome-wide association studies (GWAS) have identified thousands of variants associated with complex traits, but their biological interpretation often remains unclear. Most of these variants overlap with expression QTLs, indicating their potential involvement in regulation of gene expression. Here, we propose a transcriptome-wide summary statistics-based Mendelian Randomization approach (TWMR) that uses multiple SNPs as instruments and multiple gene expression traits as exposures, simultaneously. Applied to 43 human phenotypes, it uncovers 3,913 putatively causal gene-trait associations, 36% of which have no genome-wide significant SNP nearby in previous GWAS. Using independent association summary statistics, we find that the majority of these loci were missed by GWAS due to power issues. Noteworthy among these links is educational attainment-associated BSCL2, known to carry mutations leading to a Mendelian form of encephalopathy. We also find pleiotropic causal effects suggestive of mechanistic connections. TWMR better accounts for pleiotropy and has the potential to identify biological mechanisms underlying complex traits.

KW - INSTRUMENTAL VARIABLES

KW - VARIANTS

KW - DISEASE

KW - ASSOCIATION

KW - MUTATION

KW - STATISTICS

KW - EXPRESSION

KW - PLEIOTROPY

KW - OBESITY

KW - FAMILY

U2 - 10.1038/s41467-019-10936-0

DO - 10.1038/s41467-019-10936-0

M3 - Article

C2 - 31341166

SN - 2041-1723

VL - 10

JO - Nature Communications

JF - Nature Communications

IS - 1

M1 - 3300

ER -

Mendelian randomization integrating GWAS and eQTL data reveals genetic determinants of complex and clinical traits

Abstract

Keywords

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