| Title: | Evidence of epistasis in regions of long-range linkage disequilibrium across five complex diseases in the UK Biobank and eMERGE datasets |
| Journal: | American Journal of Human Genetics |
| Published: | 1 Apr 2023 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/37028392/ |
| DOI: | https://doi.org/10.1016/j.ajhg.2023.03.007 |
| Citations: | 10 (10 in last 2 years) as of 8 Aug 2024 |
Publication 7885
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Abstract
Leveraging linkage disequilibrium (LD) patterns as representative of population substructure enables the discovery of additive association signals in genome-wide association studies (GWASs). Standard GWASs are well-powered to interrogate additive models; however, new approaches are required for invesigating other modes of inheritance such as dominance and epistasis. Epistasis, or non-additive interaction between genes, exists across the genome but often goes undetected because of a lack of statistical power. Furthermore, the adoption of LD pruning as customary in standard GWASs excludes detection of sites that are in LD but might underlie the genetic architecture of complex traits. We hypothesize that uncovering long-range interactions between loci with strong LD due to epistatic selection can elucidate genetic mechanisms underlying common diseases. To investigate this hypothesis, we tested for associations between 23 common diseases and 5,625,845 epistatic SNP-SNP pairs (determined by Ohta's D statistics) in long-range LD (>0.25 cM). Across five disease phenotypes, we identified one significant and four near-significant associations that replicated in two large genotype-phenotype datasets (UK Biobank and eMERGE). The genes that were most likely involved in the replicated associations were (1) members of highly conserved gene families with complex roles in multiple pathways, (2) essential genes, and/or (3) genes that were associated in the literature with complex traits that display variable expressivity. These results support the highly pleiotropic and conserved nature of variants in long-range LD under epistatic selection. Our work supports the hypothesis that epistatic interactions regulate diverse clinical mechanisms and might especially be driving factors in conditions with a wide range of phenotypic outcomes.</p>
19 Authors
- Pankhuri Singhal
- Yogasudha Veturi
- Scott M Dudek
- Anastasia Lucas
- Alex Frase
- Kristel van Steen
- Steven J Schrodi
- David Fasel
- Chunhua Weng
- Rion Pendergrass
- Daniel J Schaid
- Iftikhar J Kullo
- Ozan Dikilitas
- Patrick M A Sleiman
- Hakon Hakonarson
- Jason H Moore
- Scott M Williams
- Marylyn D Ritchie
- Shefali S Verma
1 Application
| Application ID | Title |
|---|---|
| 32133 | Integration of multi-organ imaging phenotypes, clinical phenotypes, and genomic data |
Enabling scientific discoveries that improve human health