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Sample Preparation to Bioinformatics Analysis of DNA Methylation: Association Strategy for Obesity and Related Trait Studies
Published on: May 6, 2022
Genome-wide analysis of epistasis in body mass index using multiple human populations
Wen-Hua Wei1, Gib Hemani, Attila Gyenesei
1MRC Human Genetics Unit, MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, UK. Wenhua.Wei@igmm.ed.ac.uk
None:
We surveyed gene-gene interactions (epistasis) in human body mass index (BMI) in four European populations (n<1200) via exhaustive pair-wise genome scans where interactions were computed as F ratios by testing a linear regression model fitting two single-nucleotide polymorphisms (SNPs) with interactions against the one without. Before the association tests, BMI was corrected for sex and age, normalised and adjusted for relatedness. Neither single SNPs nor SNP interactions were genome-wide significant in either cohort based on the consensus threshold (P=5.0E-08) and a Bonferroni corrected threshold (P=1.1E-12), respectively. Next we compared sub genome-wide significant SNP interactions (P<5.0E-08) across cohorts to identify common epistatic signals, where SNPs were annotated to genes to test for gene ontology (GO) enrichment. Among the epistatic genes contributing to the commonly enriched GO terms, 19 were shared across study cohorts of which 15 are previously published genome-wide association loci, including CDH13 (cadherin 13) associated with height and SORCS2 (sortilin-related VPS10 domain containing receptor 2) associated with circulating insulin-like growth factor 1 and binding protein 3. Interactions between the 19 shared epistatic genes and those involving BMI candidate loci (P<5.0E-08) were tested across cohorts and found eight replicated at the SNP level (P<0.05) in at least one cohort, which were further tested and showed limited replication in a separate European population (n>5000). We conclude that genome-wide analysis of epistasis in multiple populations is an effective approach to provide new insights into the genetic regulation of BMI but requires additional efforts to confirm the findings.
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