We aimed at enhancing the accuracy of diagnosing bipolar disorder (BD), a challenge in clinical settings due to its symptomatic overlap with major depressive disorder (MDD). Using genome-wide association analyses (GWAS) and polygenic risk scores (PRS) from the Psychiatric Genomics Consortium's case-control cohorts, we sought to discern genetic distinctions between BD and MDD.
While our GWAS is not well-powered to identify genome-wide significant loci, our study revealed significant SNP-heritability, enabling our PRS to effectively differentiate BD from MDD, including BD cases initially presenting with depression. This differentiation was further validated in an independent Danish cohort.
Leveraging the dataset currently available, we provide an approach to carefully match and compile case-case-control cohorts from existing case-control cohorts, which enable more comprehensive analyses of underlying genetic architecture such as the one provided here.