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It is widely held that a substantial genetic component underlies BipolarDisorder (BD) and other neuropsychiatric disease traits. Recent efforts havebeen aimed at understanding the genetic basis of disease susceptibility, withgenome-wide association studies (GWAS) unveiling some promising associations.Nevertheless, the genetic etiology of BD remains elusive with a substantialproportion of the heritability - which has been estimated to be 80% based ontwin and family studies - unaccounted for by the specific genetic variantsidentified by large-scale GWAS. Furthermore, functional understanding ofassociated loci generally lags discovery. Studies we report here provideconsiderable support to the claim that substantially more remains to be gainedfrom GWAS on the genetic mechanisms underlying BD susceptibility, and that alarge proportion of the variation in disease risk may be uncovered throughintegrative functional genomic approaches. We combine recent analytic advancesin heritability estimation and polygenic modeling and leverage recenttechnological advances in the generation of -omics data to evaluate the natureand scale of the contribution of functional classes of genetic variation to arelatively intractable disorder. We identified cis eQTLs in cerebellum andparietal cortex that capture more than half of the total heritabilityattributable to SNPs interrogated through GWAS and showed that eQTL-basedheritability estimation is highly tissue-dependent. Our findings show that amuch greater resolution may be attained than has been reported thus far on thenumber of common loci that capture a substantial proportion of the heritabilityto disease risk and that the functional nature of contributory loci may beclarified en masse.

The Convergence of eQTL Mapping, Heritability Estimation and Polygenic Modeling: Emerging Spectrum of Risk Variation in Bipolar Disorder