The genetics of bipolar disorder with obesity and type 2 diabetes

Background: Bipolar disorder (BD) presents with high obesity and type 2 diabetes (T2D) and pathophysiological and phenomenological abnormalities shared with cardiometabolic disorders. Genomic studies may help define if they share genetic liability. This selective review of BD with obesity and T2D will focus on genomic studies, stress their current limitations and guide future steps in developing the field.Methods: We searched electronic databases (PubMed, Scopus) until December 2021 to identify genome-wide association studies, polygenic risk score analyses, and functional genomics of BD accounting for body mass index (BMI), obesity, or T2D.Results: The first genome-wide association studies (GWAS) of BD accounting for obesity found a promising genome-wide association in an intronic gene variant of TCF7L2 that was further replicated. Polygenic risk scores of obesity and T2D have also been associated with BD, yet, no genetic correlations have been demonstrated. Finally, human-induced stem cell studies of the intronic variant in TCF7L2 show a potential biological impact of the products of this genetic variant in BD risk. Limitations: The narrative nature of this review.Conclusions: Findings from BD GWAS accounting for obesity and their functional testing, have prompted potential biological insights. Yet, BD, obesity, and T2D display high phenotypic, genetic, and population-related hetero-geneity, limiting our ability to detect genetic associations. Further studies should refine cardiometabolic phe-notypes, test gene-environmental interactions and add population diversity.

Automated summary

This review focuses on the genomic studies of bipolar disorder (BD) with obesity and type 2 diabetes (T2D), highlighting promising genome-wide associations and potential biological impacts. However, limitations in the research are acknowledged, calling for further studies to refine cardiometabolic phenotypes, test gene-environment interactions, and increase population diversity to enhance our understanding of genetic associations.