Prioritization of human well-being spectrum related GWAS-SNVs using ENCODE-based web-tools predict interplay between PSMC3, ITIH4, and SERPINC1 genes in modulating well-being.

Several traits related to positive and negative affect show a high genetic as well as phenotypic correlation with well-being in humans, and are therefore collectively termed as "Well-being spectrum". Genome-Wide Association studies (GWA studies) on "well-being measurement" have led to identification of several genomic variants (Single Nucleotide Variants - SNVs), but very little has been explained with respect to their functionality and mode of alteration of well-being. Utilizing a pool of 1258 GWA studies based SNVs on "well-being measurement", we prioritized the SNVs and tried to annotate well-being related functionality through several bioinformatic tools to predict whether a protein sequence variation affects protein function, as well as experimentally validated datasets available in ENCODE based web-tools namely rSNPBase, RegulomeDB, Haploreg, along with GTEx Portal and STRING based protein interaction networks. Prioritization yielded three key SNVs; rs3781627-A, rs13072536-T and 5877-C potentially regulating three genes, PSMC3, ITIH4 and SERPINC1, respectively. Interestingly, the genes showed well clustered protein-protein interaction (maximum combined confidence score >0.4) with other well-being candidate genes, namely TNF and CRP genes suggesting their important role in modulation of well-being. PSMC3 and ITIH4 genes are also involved in driving acute phase responses signifying a probable cross-talk between well-being and psychoneuroimmunological system. To best of our knowledge this study is the first of its kind where the well-being associated GWA studies-SNVs were prioritized and functionally annotated, majorly based on functional data available in public domain, which revealed PSMC3, ITIH4 and SERPINC1 genes as probable candidates in regulation of well-being spectrum.