Sequence Analysis of Drug Target Genes with Suicidal Behavior in Bipolar Disorder Patients

Abstract

Background: A number of genes have been implicated in recent genome-wide association studies of suicide attempt in bipolar disorder. More focused investigation of genes coding for protein targets of existing drugs may lead to drug repurposing for the treatment and/or prevention of suicide. Methods: We analyzed 2,457 DNA variants across 197 genes of interest to GlaxoSmithKline across the pipeline in our sample of European patients suffering from bipolar disorder (N = 219). We analyzed these variants for a possible association with the suicide severity score (ranging from suicidal ideation/plan to serious suicide attempt) from the Schedule for Clinical Assessment in Neuropsychiatry. We conducted tests of individual variants and gene-based tests. Results: We found a number of DNA variants in the transforming growth factor beta receptor 1 gene (TGFBR1) to be suggestively associated with suicide severity scores (p < 0.005). The gene-based tests also pointed to TGFBR1 to be associated with suicide severity (p = 0.0001). However, these findings were not replicated in an independent bipolar disorder sample. Conclusions: We report no significant association between DNA sequences of drug target genes and suicidal behavior. Additional larger sequencing studies could further interrogate associations between variants in drug target genes and suicidal behavior.

Drug targets for COVID-19 therapeutics: Ongoing global efforts

“…Kuang et al 2019; Luscher Dias et al 2020;Nabirotchkin et al 2020). Huge data generated by High-throughput Next Gen Sequencing (NGS) from numerous patients when combined with disease characteristics and treatment options can lead to the identification of new disease biomarkers and drug targets(Stupnikov et al 2018;Zai et al 2018). AI-driven supervised machine learning algorithms can implement multiomics and multitask learning to facilitate drug response elicited by engagement of multiple drug targets(Nascimento et al 2019;Nath et al 2018;Saberian et al 2019;Zhao and So 2019).…”