Cited by 322Genetic Associations and EpidemiologyGenetic Mapping and Diversity in Plants and AnimalsGenetic and phenotypic traits in livestock

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

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Porcu, Eleonora, Rüeger, Sina, Lepik, Kaido, eQTLGen Consortium, Agbessi, Mawussé, Ahsan, Habibul, Alves, Isabel, Andiappan, Anand +129 more·2019·Nature Communications

Published version of a preprint

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.

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  • The median-based method assumes that less than half of the variants are invalid instruments (majority valid assumption).

    “Specifically, the median-based method assumes that less than half of the variants are invalid instruments (majority valid assumption)”
  • The mode-based method assumes more variants estimate the true causal effect than estimate any other quantity (plurality valid assumption).

    “and the mode-based method assumes more variants estimate the true causal effect than estimate any other quantity (plurality valid assumption).”

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Authors
Porcu, E., Rüeger, S., Lepik, K., eQTLGen Consortium, Agbessi, M., Ahsan, H., Alves, I., Andiappan, A., Arindrarto, W., Awadalla, P., Battle, A., Beutner, F., Jan Bonder, M., Boomsma, D., Christiansen, M., Claringbould, A., Deelen, P., Esko, T., Favé, M.-J., Franke, L., Frayling, T., Gharib, S. A., Gibson, G., Heijmans, B. T., Hemani, G., Jansen, R., Kähönen, M., Kalnapenkis, A., Kasela, S., Kettunen, J., Kim, Y., Kirsten, H., Kovacs, P., Krohn, K., Kronberg-Guzman, J., Kukushkina, V., Lee, B., Lehtimäki, T., Loeffler, M., Marigorta, U. M., Mei, H., Milani, L., Montgomery, G. W., Müller-Nurasyid, M., Nauck, M., Nivard, M., Penninx, B., Perola, M., Pervjakova, N., Pierce, B. L., Powell, J., Prokisch, H., Psaty, B. M., Raitakari, O. T., Ripatti, S., Rotzschke, O., Saha, A., Scholz, M., Schramm, K., Seppälä, I., Slagboom, E. P., Stehouwer, C. D. A., Stumvoll, M., Sullivan, P., ‘t Hoen, P. A. C., Teumer, A., Thiery, J., Tong, L., Tönjes, A., van Dongen, J., van Iterson, M., van Meurs, J., Veldink, J. H., Verlouw, J., Visscher, P. M., Völker, U., Võsa, U., Westra, H.-J., Wijmenga, C., Yaghootkar, H., Yang, J., Zeng, B., Zhang, F., BIOS Consortium, Arindrarto, W., Beekman, M., Boomsma, D. I., Bot, J., Deelen, J., Deelen, P., Franke, L., Heijmans, B. T., ’t Hoen, P. A. C., Hofman, B. A., Hottenga, J. J., Isaacs, A., Bonder, M. J., Jhamai, P. M., Jansen, R., Kielbasa, S. M., Lakenberg, N., Luijk, R., Mei, H., Moed, M., Nooren, I., Pool, R., Schalkwijk, C. G., Slagboom, P. E., Stehouwer, C. D. A., Suchiman, H. E. D., Swertz, M. A., Tigchelaar, E. F., Uitterlinden, A. G., van den Berg, L. H., van der Breggen, R., van der Kallen, C. J. H., van Dijk, F., van Dongen, J., van Duijn, C. M., van Galen, M., van Greevenbroek, M. M. J., van Heemst, D., van Iterson, M., van Meurs, J., van Rooij, J., van’t Hof, P., van Zwet, E. W., Vermaat, M., Veldink, J. H., Verbiest, M., Verkerk, M., Wijmenga, C., Zhernakova, D. V., Zhernakova, S., Santoni, F. A., Reymond, A., & Kutalik, Z.
Affiliations
  • SIB Swiss Institute of Bioinformatics (CH)
  • University of Tartu (EE)
  • Ontario Institute for Cancer Research (CA)
  • University of Chicago (US)
  • Agency for Science, Technology and Research (SG)
  • Johns Hopkins University (US)
  • Leipzig University (DE)
  • University of Washington (US)
  • University Medical Center Groningen (NL)
  • University of Exeter (GB)
  • Georgia Institute of Technology (US)
  • University of Bristol (GB)
  • Tampere University (FI)
  • University of Oulu (FI)
  • IFB Adiposity Diseases (DE)
  • Leiden University Medical Center (NL)
  • The University of Queensland (AU)
  • Universitätsmedizin Greifswald (DE)
  • Vrije Universiteit Amsterdam (NL)
  • University of Helsinki (FI)
  • Garvan Institute of Medical Research (AU)
  • Helmholtz Munich (DE)
  • Kaiser Permanente Washington Health Research Institute (US)
  • University of Turku (FI)
  • Karolinska Institutet (SE)
  • Erasmus MC (NL)
  • SURFsara (Netherlands) (NL)
  • University of Lausanne (CH)
  • Maastricht University Medical Centre (NL)
  • Centre Hospitalier Universitaire Vaudois (CH)
Corresponding author
  • Porcu, Eleonora
  • Kutalik, Zoltán
Venue
Nature Communications
Published
2019-07-24
Volume
10
Issue
1
Pages
3300-3300
ISSN
2041-1723 (ISSN-L)
OpenAlex
W2963404097
Cited by
322
References
64
Citations by year
2026: 44 · 2025: 47 · 2024: 67 · 2023: 47 · 2022: 45 · 2021: 32 · 2020: 31 · 2019: 9
FWCI
17.78
Type
journal article
Language
en
Open access
Locations
  • Nature Communications (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Research Publications (Maastricht University) (publishedVersion, cc-by)
  • Pure Amsterdam UMC (publishedVersion, cc-by)
  • Amsterdam UMC (VU Amsterdam) - Institutional Repository (publishedVersion, other-oa)
  • EUR Research Repository (Erasmus University Rotterdam) (publishedVersion, other-oa)
  • SERVAL (Université de Lausanne) (publishedVersion, cc-by)
  • IRIS (submittedVersion, cc-by)
  • PuSH - Publication Server of Helmholtz Zentrum München (submittedVersion, cc-by)
  • EUR Research Repository (Erasmus University Rotterdam) (submittedVersion, other-oa)
  • RePub (Erasmus University Rotterdam) (submittedVersion, other-oa)
  • Data Archiving and Networked Services (DANS) (submittedVersion)
  • Leiden Repository (Leiden University) (submittedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • Utrecht University Repository (Utrecht University) (submittedVersion, other-oa)
  • Open access LMU (Ludwid Maxmilian's Universitat Munchen) (submittedVersion, cc-by)
  • Työväentutkimus Vuosikirja (submittedVersion)
  • mediaTUM (Technical University of Munich) (submittedVersion, other-oa)
  • Site cant be reached (submittedVersion, cc-by)
  • University of Groningen research database (University of Groningen / Centre for Information Technology) (submittedVersion, cc-by)
  • Bristol Research (University of Bristol) (submittedVersion, cc-by)
  • VU Research Portal (submittedVersion, other-oa)
  • Research Publications (Maastricht University) (submittedVersion, other-oa)
  • Data Archiving and Networked Services (DANS) (submittedVersion, other-oa)
Funders
  • Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (31003A-160203, 32003B_173092)
  • Horizon2020 Twinning project ePerMed
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Mapping and Diversity in Plants and Animals
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic and phenotypic traits in livestock
Keywords
Mendelian randomization, expression QTL, gene-trait association, pleiotropy, complex traits, clinical traits, educational attainment, BSCL2, encephalopathy, causal inference, gene expression regulation
MeSH terms
Brain Diseases, Humans, Phenotype, Genetic Variation, Genetic Predisposition to Disease, Polymorphism, Single Nucleotide, Gene Expression Profiling, Quantitative Trait Loci, GTP-Binding Protein gamma Subunits, Genome-Wide Association Study, Mendelian Randomization Analysis, Transcriptome

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