Dissecting shared genetic architecture between depression and body mass index

• Published in: BMC medicine 2024-10, Vol.22 (1), p.455-13, Article 455
• Main Authors: Zhang, Hengyu, Zheng, Rui, Yu, Binhe, Yu, Yuefeng, Luo, Xiaomin, Yin, Shujuan, Zheng, Yingjun, Shi, Jie, Ai, Sizhi
• Format: Article
• Language: English
• Subjects: Analysis; Annotations; Bivariate analysis; Body Mass Index; Body size; Brain; Brain research; Care and treatment; Comorbidity; Correlation; Cortex (cingulate); Datasets; Depression; Depression - genetics; Depression, Mental; Development and progression; Diagnosis; Gene expression; Gene loci; Genes; Genetic analysis; Genetic aspects; Genetic Predisposition to Disease; Genome-wide association studies; Genome-Wide Association Study; Genomes; Genotype & phenotype; Health aspects; Humans; Linkage Disequilibrium; Mendelian Randomization Analysis; Mental depression; Meta-analysis; Methods; Nucleotides; Nucleus accumbens; Obesity; Obesity - genetics; Overweight; Polymorphism, Single Nucleotide - genetics; Randomization; Regression models; Sensitivity analysis; Share genetic architecture; Single-nucleotide polymorphism
• ISSN: 1741-7015; 1741-7015
• DOI: 10.1186/s12916-024-03681-9

A growing body of evidence supports the comorbidity between depression (DEP) and obesity, yet the genetic mechanisms underlying this association remain unclear. Our study explored the shared genetic architecture and causal associations of DEP with BMI. We investigated the multigene overlap and genetic correlation between DEP (N > 1.3 million) and BMI (N = 806,834) based on genome-wide association studies (GWAS) and using the bivariate causal mixture model and linkage disequilibrium score regression (LDSC). The causal association was explored by bi-directional Mendelian randomization (MR). Common risk loci were identified through cross-trait meta-analyses. Stratified LDSC and multi-marker gene annotation analyses were applied to investigate single-nucleotide polymorphisms enrichment across tissue types, cell types, and functional categories. Finally, we explored shared functional genes by Summary Data-Based Mendelian Randomization (SMR) and further detected differential expression genes (DEG) in brain tissues of individuals with depression and obesity. We found a positive genetic correlation between DEP and BMI (r 0.19, P = 4.07 × 10 ), which was more evident in local genomic regions. Cross-trait meta-analyses identified 16 shared genetic loci, 5 of which were newly identified, and they had influence on both diseases in the same direction. MR analysis showed a bidirectional causal association between DEP and BMI, with comparable effect sizes estimated in both directions. Combined with gene expression information, we found that genetic correlations between DEP and BMI were enriched in 6 brain regions, predominantly in the nucleus accumbens and anterior cingulate cortex. Moreover, 6 specific cell types and 23 functional genes were found to have an impact on both DEP and BMI across the brain regions. Of which, NEGR1 was identified as the most significant functional gene and associated with DEP and BMI at the genome-wide significance level (P