Detecting genome-wide directional effects of transcription factor binding on polygenic disease risk
Open accessPublished version of a preprint
Abstract
Biological interpretation of genome-wide association study data frequently involves assessing whether SNPs linked to a biological process, for example, binding of a transcription factor, show unsigned enrichment for disease signal. However, signed annotations quantifying whether each SNP allele promotes or hinders the biological process can enable stronger statements about disease mechanism. We introduce a method, signed linkage disequilibrium profile regression, for detecting genome-wide directional effects of signed functional annotations on disease risk. We validate the method via simulations and application to molecular quantitative trait loci in blood, recovering known transcriptional regulators. We apply the method to expression quantitative trait loci in 48 Genotype-Tissue Expression tissues, identifying 651 transcription factor-tissue associations including 30 with robust evidence of tissue specificity. We apply the method to 46 diseases and complex traits (average n = 290 K), identifying 77 annotation-trait associations representing 12 independent transcription factor-trait associations, and characterize the underlying transcriptional programs using gene-set enrichment analyses. Our results implicate new causal disease genes and new disease mechanisms.
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The SLDP regression method provides additional evidence of biologically relevant effects for Neanderthal variants and has the benefit over simple GWAS intersections because directional effects are less confounded by genomic co-localization of Neanderthal ancestry with other functional elements and can have more power when applied to rare variation or diverse populations.
“This provides additional evidence of biologically relevant effects for Neanderthal variants and has the benefit over simple GWAS intersections because directional effects are less confounded by genomic co-localization of Neanderthal ancestry with other functional elements and can have more power when applied to rare variation or diverse populations58.”
From Quantifying the contribution of Neanderthal introgression to the heritability of complex traits (2021) · cites this paper as [58]
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References 182 · Cited by 68
Research works printed but not linked: 1
- [109]Verbanck M, Chen C-Y, Neale B & Do R Widespread pleiotropy confounds causal relationships between complex traits and diseases inferred from Mendelian randomization. bioRxiv 157552 (2017). doi: 10.1101/157552 · DOI
- Authors
- Reshef, Y. A., Finucane, H. K., Kelley, D. R., Gusev, A., Kotliar, D., Ulirsch, J. C., Hormozdiari, F., Nasser, J., O’Connor, L., van de Geijn, B., Loh, P.-R., Grossman, S. R., Bhatia, G., Gazal, S., Palamara, P. F., Pinello, L., Patterson, N., Adams, R. P., & Price, A. L.
- Affiliations
- Broad Institute (US)
- Calico Life Sciences (US)
- Dana-Farber Cancer Institute (US)
- Harvard University (US)
- Google (United States) (US)
- Corresponding author
- Reshef, Yakir A.
- Price, Alkes L
- ORCID
- Venue
- Nature Genetics
- Published
- 2018-09-03
- Volume
- 50
- Issue
- 10
- Pages
- 1483-1493
- ISSN
- 1061-4036 (ISSN-L)
- 1546-1718
- PMC
- PMC6202062
- OpenAlex
- W2951544440
- Cited by
- 68
- References
- 182
- Citations by year
- 2026: 4 · 2025: 7 · 2024: 7 · 2023: 9 · 2022: 6 · 2021: 10 · 2020: 12 · 2019: 11 · 2018: 2
- FWCI
- 5.35
- Type
- journal article
- Language
- en
- Open access
- green
- doi.org
- Licence
- cc-by-nd
- www.springer.com/tdm (tdm)
- Locations
- Nature Genetics (publishedVersion)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nd)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Science Foundation (1421780)
- National Institutes of Health (1s10rr028832-01, MH101244, MH107649)
- National Institute of Mental Health (R01MH107649, R01MH109978, R01MH101244)
- National Human Genome Research Institute (R00HG008399, F32HG009987, U01HG009379)
- National Institute of General Medical Sciences (T32GM007753)
- National Institute of Diabetes and Digestive and Kidney Diseases (T32DK110919)
- National Center for Research Resources (S10 RR028832, 1S10RR028832-01)
- 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 › Molecular Biology › Bioinformatics and Genomic Networks
- Keywords
- transcription factor binding, expression quantitative trait loci, tissue specificity, gene set enrichment analysis, disease mechanisms
- MeSH terms
- Binding Sites, Blood Cells, Blood Chemical Analysis, Disease, Gene Expression Regulation, Humans, Phenotype, Protein Binding, Risk Factors, Transcription Factors, Linkage Disequilibrium, Genetic Predisposition to Disease, Multifactorial Inheritance, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Genome-Wide Association Study
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