The association between depression and metabolic syndrome and its components: a bidirectional two-sample Mendelian randomization study

Min Zhang,Jing Chen, Zhiqun Yin, Lanbing Wang,Lihua Peng

TRANSLATIONAL PSYCHIATRY(2021)

引用 40|浏览2
暂无评分
摘要
Observational studies suggested a bidirectional correlation between depression and metabolic syndrome (MetS) and its components. However, the causal associations between them remained unclear. We aimed to investigate whether genetically predicted depression is related to the risk of MetS and its components, and vice versa. We performed a bidirectional two-sample Mendelian randomization (MR) study using summary-level data from the most comprehensive genome-wide association studies (GWAS) of depression ( n = 2,113,907), MetS ( n = 291,107), waist circumference ( n = 462,166), hypertension ( n = 463,010) fasting blood glucose (FBG, n = 281,416), triglycerides ( n = 441,016), high-density lipoprotein cholesterol (HDL-C, n = 403,943). The random-effects inverse-variance weighted (IVW) method was applied as the primary method. The results identified that genetically predicted depression was significantly positive associated with risk of MetS (OR: 1.224, 95% CI: 1.091–1.374, p = 5.58 × 10 −4 ), waist circumference (OR: 1.083, 95% CI: 1.027–1.143, p = 0.003), hypertension (OR: 1.028, 95% CI: 1.016–1.039, p = 1.34 × 10 −6 ) and triglycerides (OR: 1.111, 95% CI: 1.060–1.163, p = 9.35 × 10 −6 ) while negative associated with HDL-C (OR: 0.932, 95% CI: 0.885–0.981, p = 0.007) but not FBG (OR: 1.010, 95% CI: 0.986–1.034, p = 1.34). No causal relationships were identified for MetS and its components on depression risk. The present MR analysis strength the evidence that depression is a risk factor for MetS and its components (waist circumference, hypertension, FBG, triglycerides, and HDL-C). Early diagnosis and prevention of depression are crucial in the management of MetS and its components.
更多
查看译文
关键词
Depression,Medical genetics,Psychology,Medicine/Public Health,general,Psychiatry,Neurosciences,Behavioral Sciences,Pharmacotherapy,Biological Psychology
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要