Genome wide association studies (GWAS) have focused on elucidating the genetic architecture of complex traits by assessing single variant effects in additive genetic models, albeit explaining a fraction of the trait heritability. Epistasis has recently emerged as one of the intrinsic mechanisms that could explain part of this missing heritability. We conducted epistasis analysis for genome-wide body mass index (BMI) associated SNPs in Alzheimer's Disease Neuroimaging Initiative (ADNI) and followed up top significant interacting SNPs for replication in the UK Biobank imputed genotype dataset. We report two pairwise epistatic interactions, between rs2177596 (RHBDD1) and rs17759796 (MAPK1), rs1121980 (FTO) and rs6567160 (MC4R), obtained from a consensus of nine different epistatic approaches. Gene interaction maps and tissue expression profiles constructed for these interacting loci highlights co-expression, co-localisation, physical interaction, genetic interaction, and shared pathways emphasising the neuronal influence in obesity and implicating concerted expression of associated genes in liver, pancreas, and adipose tissues insinuating to metabolic abnormalities characterized by obesity. Detecting epistasis could thus be a promising approach to understand the effect of simultaneously interacting multiple genetic loci in disease aetiology, beyond single locus effects.
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http://dx.doi.org/10.1038/s41598-022-11270-0 | DOI Listing |
Mol Genet Genomics
December 2024
Department of Plant Sciences, North Dakota State University, Fargo, 58108, USA.
Detecting genome-wide SNP-SNP interactions (epistasis) efficiently is essential to harnessing the vast data now available from modern biobanks. With millions of SNPs and genetic information from hundreds of thousands of individuals, researchers are positioned to uncover new insights into complex disease pathways. However, this data scale brings significant computational and statistical challenges.
View Article and Find Full Text PDFFront Biosci (Schol Ed)
December 2024
Laboratory of Genomic Research, Research Institute for Genetic and Molecular Epidemiology, Kursk State Medical University, 305041 Kursk, Russia.
Background: Uterine fibroids (UF) is the most common benign tumour of the female reproductive system. We investigated the joint contribution of genome-wide association studies (GWAS)-significant loci and environment-associated risk factors to the UF risk, along with epistatic interactions between single nucleotide polymorphisms (SNPs).
Methods: DNA samples from 737 hospitalised patients with UF and 451 controls were genotyped using probe-based PCR for seven common GWAS SNPs: rs117245733 , rs547025 rs2456181 , rs7907606 , , rs58415480 , rs7986407 , and rs72709458 .
BioData Min
December 2024
School of Computing, Queen's University, 557 Goodwin Hall, 21-25 Union St, Kingston, K7L 2N8, Ontario, Canada.
Background: Epistasis, the phenomenon where the effect of one gene (or variant) is masked or modified by one or more other genes, significantly contributes to the phenotypic variance of complex traits. Traditionally, epistasis has been modeled using the Cartesian epistatic model, a multiplicative approach based on standard statistical regression. However, a recent study investigating epistasis in obesity-related traits has identified potential limitations of the Cartesian epistatic model, revealing that it likely only detects a fraction of the genetic interactions occurring in natural systems.
View Article and Find Full Text PDFDatabase (Oxford)
December 2024
The Morris Kahn Laboratory of Human Genetics at the National Institute of Biotechnology in the Negev and Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer Sheva 84105, Israel.
Originally developed to meet the challenges of genomic data deluge, GeniePool emerged as a pioneering platform, enabling efficient storage, accessibility, and analysis of vast genomic datasets, enabled due to its data lake architecture. Building on this foundation, GeniePool 2.0 advances genomic analysis through the integration of cutting-edge variant databases, such as CHM13-T2T, AlphaMissense, and gnomAD V4, coupled with the capability for variant co-occurrence queries.
View Article and Find Full Text PDFbioRxiv
December 2024
Department of Ecology and Evolution, University of Chicago, Chicago, IL, USA.
We recently reanalyzed 20 combinatorial mutagenesis datasets using a novel reference-free analysis (RFA) method and showed that high-order epistasis contributes negligibly to protein sequence-function relationships in every case. Dupic, Phillips, and Desai (DPD) commented on a preprint of our work. In our published paper, we addressed all the major issues they raised, but we respond directly to them here.
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