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Differential associations of depression‐related phenotypes with cardiometabolic risks: Polygenic analyses and exploring shared genetic variants and pathways

共病 全基因组关联研究 神经质 重性抑郁障碍 萧条(经济学) 遗传建筑学 连锁不平衡 心理学 临床心理学 单核苷酸多态性 遗传学 精神科 数量性状位点 生物 基因 人格 基因型 心情 宏观经济学 经济 社会心理学
作者
Bel Wong,Carlos Kwan‐Long Chau,Fu‐Kiu Ao,Cheuk‐Hei Mo,Sze‐Yung Wong,Yui‐Hang Wong,Hon‐Cheong So
出处
期刊:Depression and Anxiety [Wiley]
卷期号:36 (4): 330-344 被引量:25
标识
DOI:10.1002/da.22861
摘要

Numerous studies have suggested associations between depression and cardiometabolic (CM) diseases. However, little is known about the mechanism underlying this comorbidity, and whether the relationship differs by depression subtypes.Using polygenic risk scores (PRS) and linkage disequilibrium (LD) score regression, we investigated the genetic overlap of various depression-related phenotypes with a comprehensive panel of 20 CM traits. GWAS results for major depressive disorder (MDD) were taken from the PGC and CONVERGE studies, with the latter focusing on severe melancholic depression. GWAS results on general depressive symptoms (DS) and neuroticism were also included. We identified the shared genetic variants and inferred enriched pathways. We also looked for drugs over-represented among the top-shared genes, with an aim to finding repositioning opportunities for comorbidities.We found significant genetic overlap between MDD, DS, and neuroticism with cardiometabolic traits. In general, positive polygenic associations with CM abnormalities were observed except for MDD-CONVERGE. Counterintuitively, PRS representing severe melancholic depression was associated with reduced CM risks. Enrichment analyses of shared SNPs revealed many interesting pathways such as those related to inflammation that underlie the comorbidity of depressive and CM traits. Using a gene-set analysis approach, we also revealed several repositioning candidates with literature support (e.g., bupropion).Our study highlights shared genetic bases of depression with CM traits, and suggests the associations vary by depression subtypes, which may have implications in targeted prevention of cardiovascular events for patients. Identification of shared genetic factors may also guide drug discovery for the comorbidities.

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