Zhang Wenqiang, Qiu Lingli, Liu Yunjie, Wang Yutong, Tang Mingshuang, Chen Lin, Zhang Ben, Jiang Xia
Jiangxi Provincial Key Laboratory of Molecular Medicine, The Second Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, China.
Department of Medical Genetics, The Second Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, China.
Depress Anxiety. 2025 Sep 5;2025:5250758. doi: 10.1155/da/5250758. eCollection 2025.
The coexistence of depression and stroke has long been observed; however, their intrinsic link has not been fully understood. We aimed to inform the importance of depression intervention as a primary prevention of stroke by investigating shared genetic etiology and causal relationship underlying depression and stroke. Leveraging summary statistics from the hitherto largest genome-wide association studies (GWAS) in European-ancestry individuals for depression ( / = 294,322/741,438) and stroke ( / = 73,652/1,234,808), we performed cross-trait linkage-disequilibrium (LD) score regression and SUPERGNOVA to quantify global and local genetic correlations, cross-trait meta-analysis to identify shared genetic loci, transcriptome-wide association study (TWAS) to detect shared tissue-specific gene expression, and Mendelian randomization (MR) analysis to make causal inference between the two conditions. We observed a significant positive global genetic correlation between depression and stroke (rg = 0.18, =2.92 ×10). Partitioning the whole genome, we observed one genomic region (11q23.2) presenting a significant local genetic correlation. Cross-trait meta-analysis and TWAS identified two shared genetic loci ( and ) revealing potential shared biological mechanisms involving lysosome localization. MR identified a putative causal association of genetically predicted depression on stroke (odds ratio [OR] = 1.13, 95% confidence interval [CI] = 1.07-1.19, =1.12 ×10). A considerable proportion of this association was mediated through smoking initiation (proportion-mediated [PM] = 44.0%, 95% CI = 19.9%-68.1%, =3.42 ×10), hypertension (PM = 34.0%, 95% CI = 14.5%-53.5%, =6.46 ×10), type 2 diabetes (PM = 19.0%, 95% CI = 8.5%-29.5%, =3.78 ×10), and atrial fibrillation (PM = 10.9%, 95% CI = 0.7%-21.1%, =3.61 ×10), respectively. MR in the reverse direction identified a putative association of genetically predicted stroke on depression (OR = 1.05, 95% CI = 1.01-1.09, =1.73 ×10), which attenuated to nonsignificant when correcting for both correlated and uncorrelated pleiotropy (OR = 1.00, 95% CI = 0.98-1.03, =0.88). Drug target MR identified causal associations of genetically predicted level on depression (OR = 0.92, 95% CI = 0.90-0.94, =2.04 ×10) and stroke (OR = 0.90, 95% CI = 0.86-0.95, =3.53 ×10). Our work highlights a shared genetic basis and a putative causal relationship between depression and stroke, providing novel insights into the primary prevention of stroke by depression intervention.
抑郁症与中风的共存早已被观察到；然而，它们之间的内在联系尚未完全明了。我们旨在通过研究抑郁症和中风潜在的共同遗传病因及因果关系，来揭示抑郁症干预作为中风一级预防措施的重要性。利用欧洲裔个体中迄今为止最大规模的全基因组关联研究（GWAS）的汇总统计数据，分别针对抑郁症（病例数/对照数=294,322/741,438）和中风（病例数/对照数=73,652/1,234,808），我们进行了跨性状连锁不平衡（LD）评分回归和SUPERGNOVA分析，以量化全局和局部遗传相关性；进行跨性状荟萃分析以识别共同的遗传位点；进行全转录组关联研究（TWAS）以检测共同的组织特异性基因表达；并进行孟德尔随机化（MR）分析以推断这两种疾病之间的因果关系。我们观察到抑郁症和中风之间存在显著的正全局遗传相关性（rg = 0.18，P = 2.92×10⁻⁶）。对整个基因组进行划分时，我们观察到一个基因组区域（11q23.2）呈现出显著的局部遗传相关性。跨性状荟萃分析和TWAS识别出两个共同的遗传位点（基因1和基因2），揭示了涉及溶酶体定位的潜在共同生物学机制。MR分析确定了遗传预测的抑郁症对中风的假定因果关联（优势比[OR]=1.13，95%置信区间[CI]=1.07 - 1.19，P = 1.12×10⁻⁵）。这种关联的很大一部分分别通过开始吸烟（中介比例[PM]=44.0%，95% CI = 19.9% - 68.1%，P = 3.42×10⁻³）、高血压（PM = 34.0%，95% CI = 14.5% - 53.5%，P = 6.46×10⁻⁴）、2型糖尿病（PM = 19.0%，95% CI = 8.5% - 29.5%，P = 3.78×10⁻³）和心房颤动（PM = 10.9%，95% CI = 0.7% - 21.1%，P = 3.61×10⁻²）介导。反向的MR分析确定了遗传预测的中风对抑郁症的假定关联（OR = 1.05，95% CI = 1.01 - 1.09，P = 1.73×10⁻²），在校正相关和不相关的多效性后，这种关联减弱至不显著（OR = 1.00，95% CI = 0.98 - 1.03，P = 0.88）。药物靶点MR分析确定了遗传预测的[某种物质]水平对抑郁症（OR = 0.92，95% CI = 0.90 - 0.94，P = 2.04×10⁻⁶）和中风（OR = 0.9个，95% CI = 0.86 - 0.95，P = 3.53×10⁻⁵）的因果关联。我们的研究突出了抑郁症和中风之间共同的遗传基础及假定的因果关系，为通过抑郁症干预进行中风的一级预防提供了新的见解。
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