Dissecting shared genetic architecture between depression and body mass index
Hengyu Zhang1, Rui Zheng2,3, Binhe Yu4
1Department of Psychiatry, The Affiliated Brain Hospital, Guangzhou Medical University, 36 Mingxin Road, Guangzhou, Guangdong, China.
BMC Medicine
|October 11, 2024
Summary
This study reveals a shared genetic basis between depression and obesity, identifying common genetic loci and causal links. Findings highlight NEGR1 as a key gene, offering new avenues for understanding and treating these comorbidities.
Area of Science:
- Genetics
- Psychiatry
- Metabolic Disorders
Background:
- Comorbidity between depression (DEP) and obesity is recognized, but underlying genetic mechanisms are unclear.
- Understanding shared genetic factors is crucial for addressing the public health burden of these conditions.
Purpose of the Study:
- To explore the shared genetic architecture and causal associations between depression and Body Mass Index (BMI).
- To identify common genetic loci, functional genes, and their enrichment in specific brain regions and cell types.
Main Methods:
- Genome-wide association studies (GWAS) data from over 1.3 million individuals for DEP and 806,834 for BMI.
- Utilized bivariate causal mixture model, linkage disequilibrium score regression (LDSC), and bi-directional Mendelian randomization (MR).
- Cross-trait meta-analyses, SMR, and differential gene expression analyses were performed.
Main Results:
- A significant positive genetic correlation (rg = 0.19) was found between DEP and BMI.
- Identified 16 shared genetic loci, including 5 novel ones, with bidirectional causal associations.
- NEGR1 was identified as a key functional gene, with lower expression in brain tissues of individuals with depression and obesity.
Conclusions:
- Shared genetic underpinnings, including correlations and common genes like NEGR1, connect depression and BMI.
- These findings provide novel insights into the comorbidity of depression and obesity.
- Opens new research avenues for understanding and treating these interconnected conditions.
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