New "drugs and targets" in the GWAS era of bipolar disorder.

Objective: Due to the phenotypic heterogeneity and etiological complexity of bipolar disorder (BD), many patients do not respond well to the current medications, and developing novel effective treatment is necessary. Whether any BD genome-wide association study (GWAS) risk genes were targets of existing drugs or novel drugs that can be repurposed in the clinical treatment of BD is a hot topic in the GWAS era of BD.

Methods: A list of 425 protein-coding BD risk genes was distilled through the BD GWAS, and 4479 protein-coding druggable targets were retrieved from the druggable genome.

Bidirectional genetic overlap between bipolar disorder and intelligence.

Background: Bipolar disorder (BD) is a highly heritable psychiatric illness exhibiting substantial correlation with intelligence.

Methods: To investigate the shared genetic signatures between BD and intelligence, we utilized the summary statistics from genome-wide association studies (GWAS) to conduct the bivariate causal mixture model (MiXeR) and conjunctional false discovery rate (conjFDR) analyses. Subsequent expression quantitative trait loci (eQTL) mapping in human brain and enrichment analyses were also performed.

Network-based analysis revealed significant interactions between risk genes of severe COVID-19 and host genes interacted with SARS-CoV-2 proteins.

Whether risk genes of severe coronavirus disease 2019 (COVID-19) from genome-wide association study could play their regulatory roles by interacting with host genes that were interacted with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) proteins was worthy of exploration. In this study, we implemented a network-based approach by developing a user-friendly software Network Calculator (https://github.com/Haoxiang-Qi/Network-Calculator.