Investigation of genetic loci shared between bipolar disorder and risk-taking propensity: potential implications for pharmacological interventions

Abstract

Patients with bipolar disorder (BD) often show increased risk-taking propensity, which may contribute to poor clinical outcome. While these two phenotypes are genetically correlated, there is scarce knowledge on the shared genetic determinants. Using GWAS datasets on BD (41,917 BD cases and 371,549 controls) and risk-taking (n = 466,571), we dissected shared genetic determinants using conjunctional false discovery rate (conjFDR) and local genetic covariance analysis. We investigated specificity of identified targets using GWAS datasets on schizophrenia (SCZ) and attention-deficit hyperactivity disorder (ADHD). The putative functional role of identified targets was evaluated using different tools and GTEx v. 8. Target druggability was evaluated using DGIdb and enrichment for drug targets with genome for REPositioning drugs (GREP). Among 102 loci shared between BD and risk-taking, 87% showed the same direction of effect. Sixty-two were specifically shared between risk-taking propensity and BD, while the others were also shared between risk-taking propensity and either SCZ or ADHD. By leveraging pleiotropic enrichment, we reported 15 novel and specific loci associated with BD and 22 with risk-taking. Among cross-disorder genes, CACNA1C (a known target of calcium channel blockers) was significantly associated with risk-taking propensity and both BD and SCZ using conjFDR (p = 0.001 for both) as well as local genetic covariance analysis, and predicted to be differentially expressed in the cerebellar hemisphere in an eQTL-informed gene-based analysis (BD, Z = 7.48, p = 3.8E−14; risk-taking: Z = 4.66, p = 1.6E−06). We reported for the first time shared genetic determinants between BD and risk-taking propensity. Further investigation into calcium channel blockers or development of innovative ligands of calcium channels might form the basis for innovative pharmacotherapy in patients with BD with increased risk-taking propensity.

Bidirectional genetic overlap between bipolar disorder and intelligence

“…Indeed, mixed directions of allelic effects between phenotypes with overlapped genetic basis are commonly seen [18][19][20], and Frei et al described a novel statistical method, MiXeR, for precisely estimating the overall shared polygenic architecture regardless of allelic effect directions [21]. In addition, the conjunctional false discovery rate (conjFDR) analyses, which are built on an empirical Bayesian statistical framework and leverages the combined power of both GWASs, are believed to increase the opportunity of discovering novel risk loci based on GWAS summary statistics [22][23][24][25][26][27].…”