Cited by 134Genetic Associations and EpidemiologyBioinformatics and Genomic NetworksGenetic Mapping and Diversity in Plants and Animals

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Predicting gene targets from integrative analyses of summary data from GWAS and eQTL studies for 28 human complex traits

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Pavlides, Jennifer M. Whitehead, Zhu, Zhihong, Gratten, Jacob, McRae, Allan F., Wray, Naomi R., Yang, Jian·2016·Genome Medicine

DOI 10.1186/s13073-016-0338-4PMC PMC4979185

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Abstract

Genome-wide association studies (GWAS) have identified hundreds of genetic variants associated with complex traits and diseases. However, elucidating the causal genes underlying GWAS hits remains challenging. We applied the summary data-based Mendelian randomization (SMR) method to 28 GWAS summary datasets to identify genes whose expression levels were associated with traits and diseases due to pleiotropy or causality (the expression level of a gene and the trait are affected by the same causal variant at a locus). We identified 71 genes, of which 17 are novel associations (no GWAS hit within 1 Mb distance of the genes). We integrated all the results in an online database ( http://www.cnsgenomics/shiny/SMRdb/ ), providing important resources to prioritize genes for further follow-up, for example in functional studies.

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Additional file 10 of A systems genetics approach reveals PbrNSC as a regulator of lignin and cellulose biosynthesis in stone cells of pear fruit
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Additional file 1 of A systems genetics approach reveals PbrNSC as a regulator of lignin and cellulose biosynthesis in stone cells of pear fruit
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Additional file 5 of Genome-wide analysis of expression QTL (eQTL) and allele-specific expression (ASE) in pig muscle identifies candidate genes for meat quality traits
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Additional file 3 of Genome-wide analysis of expression QTL (eQTL) and allele-specific expression (ASE) in pig muscle identifies candidate genes for meat quality traits
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Authors: Pavlides, J. M. W., Zhu, Z., Gratten, J., McRae, A. F., Wray, N. R., & Yang, J.
Affiliations: The University of Queensland (AU)
Corresponding author: Yang, Jian
ORCID: Pavlides, Jennifer M. Whitehead
Zhu, Zhihong
Gratten, Jacob
McRae, Allan F.
Wray, Naomi R.
Yang, Jian
Venue: Genome Medicine
Publisher: Springer Science and Business Media LLC
Published: 2016-08-09
Volume: 8
Issue: 1
Pages: 84-84
ISSN: 1756-994X (ISSN-L)
DOI: 10.1186/s13073-016-0338-4
PMC: PMC4979185
OpenAlex: W2499155228
Cited by: 109
References: 36
Citations by year: 2026: 11 · 2025: 6 · 2024: 8 · 2023: 10 · 2022: 12 · 2021: 16 · 2020: 15 · 2019: 11 · 2018: 11 · 2017: 5 · 2016: 3
FWCI: 8.07
Type: journal article
Language: en
Open access: gold
doi.org
Licence: cc-by
Locations: Genome Medicine (publishedVersion, cc-by)
Europe PMC (PubMed Central) (publishedVersion, cc-by)
PubMed Central (publishedVersion, cc-by)
PubMed (publishedVersion)
Funders: Medical Research Council (1107258, 1078901)
National Health and Medical Research Council (1083656, 1078901, 1087889, 1107258)
Topics: Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Mapping and Diversity in Plants and Animals
Keywords: expression quantitative trait loci, summary-data-based Mendelian randomization, complex traits, causal gene identification, pleiotropy, gene expression, gene prioritization
MeSH terms: Autism Spectrum Disorder, Alzheimer Disease, Coronary Artery Disease, Gene Expression Regulation, Genotype, Humans, Phenotype, Inflammatory Bowel Diseases, Models, Statistical, Genome, Human, Quantitative Trait, Heritable, Genetic Predisposition to Disease, Gene Expression Profiling, Databases, Genetic, Quantitative Trait Loci, Genome-Wide Association Study, Genetic Pleiotropy

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Predicting gene targets from integrative analyses of summary data from GWAS and eQTL studies for 28 human complex traits

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