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Biological interpretation of genome-wide association studies using predicted gene functions
Open accessAbstract
The main challenge for gaining biological insights from genetic associations is identifying which genes and pathways explain the associations. Here we present DEPICT, an integrative tool that employs predicted gene functions to systematically prioritize the most likely causal genes at associated loci, highlight enriched pathways and identify tissues/cell types where genes from associated loci are highly expressed. DEPICT is not limited to genes with established functions and prioritizes relevant gene sets for many phenotypes. Identifying which genes and pathways explain genetic associations is challenging. Here, the authors present DEPICT, a tool for gene prioritization, pathway analysis and tissue/cell-type enrichment analysis that can be used to generate testable hypotheses from genetic association studies.
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“At the standard false discovery rate (FDR) threshold of 5%, the bioinformatics tool DEPICT19 prioritizes 1,838 genes (Supplementary Table 7), a tenfold increase relative to the DEPICT results from an earlier GWAS of EduYears10.”
From Gene discovery and polygenic prediction from a genome-wide association study of educational attainment in 1.1 million individuals (2018) · cites this paper as [19]
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“we applied the bioinformatics tool DEPICT19 and found that, relative to other genes, genes near our lead SNPs are overwhelmingly enriched for expression in the central nervous system (Fig. 3A, Supplementary Table 6).”
From Gene discovery and polygenic prediction from a genome-wide association study of educational attainment in 1.1 million individuals (2018) · cites this paper as [19]
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“On the other hand, CLECL1 represents a simpler case of a known susceptibility effect that has previously been linked to altered CLECL1 RNA expression in monocytes (26, 32); its enrichment in microglial cells, which share many molecular pathways with other myeloid cells, is more straightforward to understand.”
From Multiple sclerosis genomic map implicates peripheral immune cells and microglia in susceptibility (2019) · cites this paper as [32]
Experimental — accuracy not yet measuredIn the citing paper
“Additionally, suggestive evidence for enrichment (FDR≤0.2) was observed for ten tissues, including female genitalia, uterus, endocrine glands, endometrium, ovary and Fallopian tubes (Supplementary Data 16).”
From Meta-analysis identifies five novel loci associated with endometriosis highlighting key genes involved in hormone metabolism (2017) · cites this paper as [32]
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“However, when using results with evidence of genome-wide suggestive association (P<1 × 10−5) in either all or Grade B meta-analysis, DEPICT provided evidence for significant enrichment (FDR≤0.05) of COPB1 PPI subnetwork gene set (Supplementary Data 16).”
From Meta-analysis identifies five novel loci associated with endometriosis highlighting key genes involved in hormone metabolism (2017) · cites this paper as [32]
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“DEPICT32 analysis provided little support for potential genes, pathways, tissues or cell types reaching multiple testing threshold (FDR≤0.05).”
From Meta-analysis identifies five novel loci associated with endometriosis highlighting key genes involved in hormone metabolism (2017) · cites this paper as [32]
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Metadata
- Authors
- Pers, T. H., Karjalainen, J. M., Chan, Y., Westra, H.-J., Wood, A. R., Yang, J., Lui, J. C., Vedantam, S., Gustafsson, S., Esko, T., Frayling, T., Speliotes, E. K., Genetic Investigation of ANthropometric Traits (GIANT) Consortium, Boehnke, M., Raychaudhuri, S., Fehrmann, R. S. N., Hirschhorn, J. N., & Franke, L.
- Affiliations
- Broad Institute (US)
- University Medical Center Groningen (NL)
- Brigham and Women's Hospital (US)
- University of Exeter (GB)
- The University of Queensland (AU)
- National Institutes of Health (US)
- Uppsala University (SE)
- University of Michigan (US)
- Corresponding author
- Pers, Tune H.
- Hirschhorn, Joel N.
- Franke, Lude
- ORCID
- Venue
- Nature Communications
- Published
- 2015-01-19
- Volume
- 6
- Issue
- 1
- Pages
- 5890-5890
- ISSN
- 2041-1723 (ISSN-L)
- PMC
- PMC4420238
- OpenAlex
- W2125972459
- Cited by
- 787
- References
- 40
- Citations by year
- 2026: 32 · 2025: 46 · 2024: 53 · 2023: 69 · 2022: 76 · 2021: 106 · 2020: 77 · 2019: 100 · 2018: 87 · 2017: 66 · 2016: 49 · 2015: 26
- FWCI
- 33.02
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Nature Communications (publishedVersion)
- PubMed (publishedVersion)
- Research Publications (Maastricht University) (publishedVersion, cc-by-nc-nd)
- University of Groningen research database (University of Groningen / Centre for Information Technology) (publishedVersion, cc-by)
- SERVAL (Université de Lausanne) (publishedVersion, other-oa)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Edinburgh Research Explorer (University of Edinburgh) (acceptedVersion, other-oa)
- QUT ePrints (Queensland University of Technology) (submittedVersion)
- UEF eRepo (University of Eastern Finland) (submittedVersion, cc-by)
- IRIS (submittedVersion)
- Pure Amsterdam UMC (submittedVersion, other-oa)
- UWA Profiles and Research Repository (UWA) (submittedVersion)
- Data Archiving and Networked Services (DANS) (submittedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- BOA (University of Milano-Bicocca) (submittedVersion, other-oa)
- Discovery Research Portal (University of Dundee) (submittedVersion)
- Utrecht University Repository (Utrecht University) (submittedVersion, other-oa)
- UCL Discovery (University College London) (submittedVersion)
- Figshare (submittedVersion)
- Työväentutkimus Vuosikirja (submittedVersion)
- Archivio Istituzionale della Ricerca - Università Vita-Salute San Raffaele (submittedVersion)
- Research Portal (King's College London) (submittedVersion)
- Site cant be reached (submittedVersion)
- Open Research Exeter (University of Exeter) (submittedVersion)
- Research Explorer (The University of Manchester) (submittedVersion)
- Royal Devon and Exeter Research Repository (Royal Devon and Exeter) (submittedVersion)
- Radboud Repository (Radboud University) (submittedVersion)
- Open Research (University of Surrey) (submittedVersion)
- Radboud Repository (Radboud University) (submittedVersion, other-oa)
- University of Groningen research database (University of Groningen / Centre for Information Technology) (submittedVersion, cc-by)
- Utrecht University Repository (Utrecht University) (submittedVersion)
- Funders
- Wellcome Trust (098395)
- National Institute for Health and Care Research (NF-SI-0611-10170, NF-SI-0611-10219, NF-SI-0514-10027, NF-SI-0513-10059)
- European Commission (259867)
- Nederlandse Organisatie voor Wetenschappelijk Onderzoek (FP7 2007-2013, 916·10·135, 14374, 10135)
- Lundbeckfonden (R190 2014-3904)
- Danmarks Frie Forskningsfond
- Alfred Benzon Foundation
- Novo Nordisk Fonden (NNF14OC0010513, NNF13OC0005785)
- National Institutes of Health (5r01ar063759-07, FP7/2007-2013)
- Medical Research Council (MR/K013351/1, MR/K006584/1, MR/N01104X/1)
- National Heart, Lung, and Blood Institute (R01HL117078)
- National Cancer Institute (P30CA071789)
- National Institute of General Medical Sciences (U01GM092691)
- National Institute of Diabetes and Digestive and Kidney Diseases (R01DK075787, P30DK020572)
- National Institute of Arthritis and Musculoskeletal and Skin Diseases (UH2AR067677, R01-AR063759)
- National Institute of Child Health and Human Development
- Eunice Kennedy Shriver National Institute of Child Health and Human Development
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Health Sciences › Medicine › Health Informatics › Biomedical Text Mining and Ontologies
- Keywords
- genome-wide association study, gene prioritization, pathway enrichment, causal genes, hypothesis generation
- MeSH terms
- Software, Genome-Wide Association Study
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