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重新评估重度抑郁症与血脂之间的关系:一项全面的孟德尔随机化研究。

Reassessing the relationship between major depressive disorder and blood lipids: a comprehensive Mendelian randomisation study.

作者信息

Sun Genmin, Xia Disong, Xue Baiqiang, Jian Xuemin, Peng Lixia, Wang Baokun, Wu Chuanhong, Gao Chengwen, He Lin, Xu Yifeng, Zhao Xiangzhong, Zhang Qian, Cao Hui, Wen Yanqin, Shi Yongyong, Potash James B, Chen Jianhua, Li Zhiqiang

机构信息

Shanghai Mental Health Center, Bio-X Institutes, Shanghai Clinical Research Center for Mental Health, Shanghai Key Laboratory of Psychotic Disorders, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), the Collaborative Innovation Center for Brain Science, Shanghai Jiao Tong University, Shanghai, China.

The Affiliated Hospital of Qingdao University & The Biomedical Sciences Institute of Qingdao University (Qingdao Branch of SJTU Bio-X Institutes), School of Basic Medicine, Qingdao University, Qingdao, Shandong, China.

出版信息

Gen Psychiatr. 2025 Jun 26;38(3):e101900. doi: 10.1136/gpsych-2024-101900. eCollection 2025.

DOI:10.1136/gpsych-2024-101900
PMID:40589629
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12207131/
Abstract

BACKGROUND

Numerous studies have consistently demonstrated that a considerable proportion of patients with major depressive disorder (MDD) frequently exhibit pronounced dyslipidaemia. However, the causal dynamics between MDD and dyslipidaemia remain elusive.

AIMS

To comprehensively disentangle the genetic causality between MDD and various phenotypes of blood lipids, thereby facilitating the advancement of management strategies for these conditions.

METHODS

We conducted a two-sample univariable Mendelian randomisation (MR) analysis using different models, including the inverse variance weighted (IVW) method and causal analysis using the summary effect (CAUSE) estimates, as well as a multivariable MR analysis. This analysis used summary statistics from genome-wide association studies (GWAS) of MDD and five lipid traits: low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, non-high-density lipoprotein cholesterol, total cholesterol and triglycerides (TG), encompassing 5 237 893 individuals of European and East Asian ancestries. For MDD, a total of 598 701 individuals were included, with 500 199 individuals of European ancestry (N=170 756, N=329 443) and 98 502 of East Asian ancestry (N=12 588, N=85 914). Lipid data were collected from 4 639 192 individuals through the Global Lipids Genetics Consortium (European, N=4 096 085; East Asian, N=543 107). Next, we used the two-step MR to explore the mediating factors between MDD and TG, and the risk factors affecting TG through MDD. Finally, we conducted a GWAS meta-analysis and enrichment analysis.

RESULTS

In univariable MR, we observed a negative causal effect of low-density lipoprotein on MDD in both European populations (IVW: odds ratio (OR): 0.972, 95% confidence interval (CI) 0.947 to 0.998, p=0.037) and East Asian populations (IVW: OR: 0.928, 95% CI 0.864 to 0.997, p=0.042). Additionally, we identified a bidirectional causal relationship between TG and MDD, with TG having a causal effect on MDD (IVW: OR: 1.052, 95% CI 1.020 to 1.085, p=0.001) and MDD having a causal effect on TG (IVW: OR: 1.075, 95% CI 1.047 to 1.104, p<0.001). Multivariable MR analysis further supported the role of TG in MDD (OR: 1.205, 95% CI 1.034 to 1.405, p=0.017). CAUSE estimates indicated that the causal model of MDD on TG provided a better fit than the sharing model (p=0.003), while the association of TG on MDD was more likely due to horizontal correlated pleiotropy than causality. Mediation analyses revealed that waist-hip ratio (WHR) mediated 69% of the total causal effect of MDD on TG, while other identified risk factors exhibited lower mediating proportions either mediated through MDD (≤17%) or originating from MDD (≤29%). The GWAS meta-analysis highlighted potential pathways related to lipid processes and nucleosome assembling, with significant cell types identified in brain regions and liver tissues.

CONCLUSIONS

The findings indicate that genetic proxies of MDD are associated with elevated levels of TG, with WHR serving as a clinical indicator of the association. This suggests that interventions targeting WHR may be effective in reducing TG levels in patients with MDD.

摘要

背景

大量研究一致表明,相当一部分重度抑郁症(MDD)患者经常表现出明显的血脂异常。然而,MDD与血脂异常之间的因果动态关系仍不明确。

目的

全面厘清MDD与各种血脂表型之间的遗传因果关系,从而推动这些病症管理策略的发展。

方法

我们使用不同模型进行了两样本单变量孟德尔随机化(MR)分析,包括逆方差加权(IVW)方法和使用汇总效应(CAUSE)估计的因果分析,以及多变量MR分析。该分析使用了MDD和五种脂质性状的全基因组关联研究(GWAS)的汇总统计数据:低密度脂蛋白胆固醇、高密度脂蛋白胆固醇、非高密度脂蛋白胆固醇、总胆固醇和甘油三酯(TG),涵盖了5237893名欧洲和东亚血统的个体。对于MDD,总共纳入了598701名个体,其中500199名欧洲血统个体(N = 170756,N = 329443)和98502名东亚血统个体(N = 12588,N = 85914)。脂质数据通过全球脂质遗传学联盟从4639192名个体中收集(欧洲人,N = 4096085;东亚人,N = 543107)。接下来,我们使用两步MR来探索MDD和TG之间的中介因素,以及通过MDD影响TG的危险因素。最后,我们进行了GWAS荟萃分析和富集分析。

结果

在单变量MR中,我们在欧洲人群(IVW:比值比(OR):0.972,95%置信区间(CI)0.947至0.998,p = 0.037)和东亚人群(IVW:OR:0.928,95%CI 0.864至0.997,p = 0.042)中均观察到低密度脂蛋白对MDD有负向因果效应。此外,我们确定了TG与MDD之间存在双向因果关系,TG对MDD有因果效应(IVW:OR:1.052,95%CI 1.020至1.085,p = 0.001),MDD对TG也有因果效应(IVW:OR:1.075,95%CI 1.047至1.104,p < 0.001)。多变量MR分析进一步支持了TG在MDD中的作用(OR:1.205,95%CI 1.034至1.405,p = 0.017)。CAUSE估计表明,MDD对TG的因果模型比共享模型拟合更好(p = 0.003),而TG对MDD的关联更可能是由于水平相关的多效性而非因果关系。中介分析显示,腰臀比(WHR)介导了MDD对TG总因果效应的69%,而其他确定的危险因素通过MDD介导的比例较低(≤17%)或源自MDD的比例较低(≤29%)。GWAS荟萃分析突出了与脂质过程和核小体组装相关的潜在途径,并在脑区和肝组织中鉴定出了重要的细胞类型。

结论

研究结果表明,MDD的遗传代理与TG水平升高有关,WHR是这种关联的临床指标。这表明针对WHR的干预措施可能有效降低MDD患者的TG水平。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1ffd/12207131/bbe1396f1982/gpsych-38-3-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1ffd/12207131/f1648e90cffd/gpsych-38-3-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1ffd/12207131/848fc74ac669/gpsych-38-3-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1ffd/12207131/6440a4bdab05/gpsych-38-3-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1ffd/12207131/bbe1396f1982/gpsych-38-3-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1ffd/12207131/f1648e90cffd/gpsych-38-3-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1ffd/12207131/848fc74ac669/gpsych-38-3-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1ffd/12207131/6440a4bdab05/gpsych-38-3-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1ffd/12207131/bbe1396f1982/gpsych-38-3-g005.jpg

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