Cited by 926Genetic Associations and EpidemiologyBioinformatics and Genomic NetworksGenetic Mapping and Diversity in Plants and Animals

Leveraging Polygenic Functional Enrichment to Improve GWAS Power

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Kichaev, Gleb, Bhatia, Gaurav, Loh, Po-Ru, Gazal, Steven, Burch, Kathryn, Freund, Malika K., Schoech, Armin, Pasaniuc, Bogdan +1 more·2019·The American Journal of Human Genetics

Published version of a preprint

Abstract

Functional genomics data has the potential to increase GWAS power by identifying SNPs that have a higher prior probability of association. Here, we introduce a method that leverages polygenic functional enrichment to incorporate coding, conserved, regulatory, and LD-related genomic annotations into association analyses. We show via simulations with real genotypes that the method, functionally informed novel discovery of risk loci (FINDOR), correctly controls the false-positive rate at null loci and attains a 9%-38% increase in the number of independent associations detected at causal loci, depending on trait polygenicity and sample size. We applied FINDOR to 27 independent complex traits and diseases from the interim UK Biobank release (average N = 130K). Averaged across traits, we attained a 13% increase in genome-wide significant loci detected (including a 20% increase for disease traits) compared to unweighted raw p values that do not use functional data. We replicated the additional loci in independent UK Biobank and non-UK Biobank data, yielding a highly statistically significant replication slope (0.66-0.69) in each case. Finally, we applied FINDOR to the full UK Biobank release (average N = 416K), attaining smaller relative improvements (consistent with simulations) but larger absolute improvements, detecting an additional 583 GWAS loci. In conclusion, leveraging functional enrichment using our method robustly increases GWAS power.

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Crossref · 10.1016/j.ajhg.2018.11.008

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Authors
Kichaev, G., Bhatia, G., Loh, P.-R., Gazal, S., Burch, K., Freund, M. K., Schoech, A., Pasaniuc, B., & Price, A. L.
Affiliations
  • University of California, Los Angeles (US)
  • Harvard University (US)
  • Broad Institute (US)
Corresponding author
  • Kichaev, Gleb
  • Price, Alkes L.
Venue
The American Journal of Human Genetics
Publisher
Elsevier BV
Published
2019-01
Volume
104
Issue
1
Pages
65-75
ISSN
0002-9297 (ISSN-L)
OpenAlex
W2777667999
Cited by
926
References
52
Citations by year
2026: 60 · 2025: 93 · 2024: 107 · 2023: 138 · 2022: 183 · 2021: 164 · 2020: 147 · 2019: 29 · 2018: 1 · 2013: 1
FWCI
53.85
Type
journal article
Language
en
Open access
Locations
  • The American Journal of Human Genetics (publishedVersion)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc-nd)
  • Europe PMC (PubMed Central) (publishedVersion)
  • PubMed Central (publishedVersion)
  • PubMed (publishedVersion)
  • eScholarship (California Digital Library) (submittedVersion)
Funders
NIH (U01 HG009379, R01 MH101244, R01 MH107649, R01 HG009120)
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
functional genomic annotation, regulatory annotation, conserved non-coding elements, linkage disequilibrium, complex traits, disease genetics, replication, UK Biobank
MeSH terms
Calibration, False Positive Reactions, United Kingdom, Humans, Probability, Reproducibility of Results, Multifactorial Inheritance, Polymorphism, Single Nucleotide, Databases, Genetic, Genome-Wide Association Study, Datasets as Topic

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