| 徐佳庆,徐辰,谷晓楚,庞丽俊,沈静,叶莉雅.心律失常与强迫症的遗传共病机制：基于多组学整合分析的心脑轴研究[J].四川精神卫生杂志,2026,(2):149-157.Xu Jiaqing,Xu Chen,Gu Xiaochu,Pang Lijun,Shen Jing,Ye Liya,Shared genetic architecture between arrhythmia and obsessive-compulsive disorder： a heart-brain axis study based on multi-omics integration[J].SICHUAN MENTAL HEALTH,2026,(2):149-157 |
| 心律失常与强迫症的遗传共病机制：基于多组学整合分析的心脑轴研究 |
| Shared genetic architecture between arrhythmia and obsessive-compulsive disorder： a heart-brain axis study based on multi-omics integration |
| 投稿时间：2026-01-15 |
| DOI：10.11886/scjsws20260115001 |
| 中文关键词: 心律失常 强迫症 遗传相关性 多效性 心脑轴 多组学整合 |
| 英文关键词:Arrhythmia Obsessive-compulsive disorder Genetic correlation Pleiotropy Heart-brain axis Multi-omics integration |
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| 中文摘要: |
| 背景 心律失常与强迫症在临床和流行病学研究中常呈现共病现象，但其潜在的共享遗传基础及心脑轴机制尚不清楚。目的 系统评估心律失常与强迫症之间的遗传相关性，并解析其潜在的分子遗传机制，从多组学角度验证“心脑轴”的遗传基础，为二者的风险预测及临床协同干预提供分子层面的支持。方法 整合英国生物银行（UK Biobank）心律失常全基因组关联研究（GWAS）汇总数据（包括7 207例病例和477 391例对照）与精神病基因组学联合会发布的强迫症GWAS数据（包括2 688例病例和7 037例对照），均限于欧洲血统个体。采用连锁不平衡回归分析（LDSC）和高精度似然法（HDL）估计全基因组遗传相关性；利用局部方差分析注释法（LAVA）进行局部遗传相关性分析；通过多性状GWAS整合分析（MTAG）识别多效性位点；结合汇总数据孟德尔随机化（SMR）与转录组关联分析（TWAS）鉴定共享风险基因；并基于功能定位与注释（FUMA）平台进行功能富集分析。结果 LDSC（rg=0.248，95% CI：0.159~0.336，P=4.82×10-3）与HDL（rg=0.294，95% CI：0.237~0.351，P=5.87×10-4）均显示心律失常与强迫症存在正向遗传相关性。LAVA在全基因组中识别出23个显著的局部相关区域（P<2.0×10-5）。MTAG识别出11个达到全基因组显著性水平的共享SNP，其中rs12754189（KCNN3内含子）具有潜在功能有害性（CADD>12.37）。SMR与TWAS共鉴定出20个共享基因，这些基因富集于大脑皮层、杏仁核、左心室等神经-心血管组织，并参与DNA损伤应答、RNA代谢、转录调控及FAS信号通路（FDR<0.05）。结论 心律失常与强迫症具有共享的遗传基础，其共病机制可能涉及神经元与心肌细胞在基因表达调控和应激响应方面的共同脆弱性，支持心脑轴在二者病理生理中的作用。 |
| 英文摘要: |
| Background Arrhythmia and obsessive-compulsive disorder （OCD） frequently co-occur in clinical and epidemiological settings， yet their shared genetic basis and potential heart-brain axis mechanisms remain unclear.Objective To systematically evaluate the genetic correlation between arrhythmia and OCD， and to elucidate their underlying molecular genetic mechanisms， so as to provide molecular evidence for the "heart-brain axis" to support risk assessment and integrated clinical strategies for these comorbidities.Methods The aggregated data from the genome-wide association study （GWAS） of arrhythmia in the UK Biobank （7 207 cases and 477 391 controls） and the GWAS data of OCD released by the Psychiatric Genomics Consortium （2 688 cases and 7 037 controls） were integrated， all of which were limited to individuals of European ancestry. The genome-wide genetic correlations were estimated using the linkage disequilibrium score regression （LDSC） and the high-definition likelihood （HDL）. Local genetic correlation analysis was conducted using the local analysis of variance annotation （LAVA）. Multi-trait analysis of GWAS （MTAG） was employed to identify pleiotropic loci. Shared risk genes were identified by combining summary-data based Mendelian randomization （SMR） and transcriptome-wide association study （TWAS）. Functional enrichment analysis was performed based on the functional mapping and annotation （FUMA） platform.Results Both LDSC （rg=0.248， 95% CI： 0.159–0.336， P=4.82×10-3） and HDL （rg=0.294， 95% CI： 0.237–0.351， P=5.87×10-4） revealed significant positive genetic correlation between arrhythmia and OCD. LAVA identified 23 significantly local correlated regions in the genome （P<2.0×10-5）. MTAG discovered 11 genome-wide significant pleiotropic SNPs， among which rs12754189 （intron of KCNN3） had potential functional harmfulness （CADD>12.37）. SMR and TWAS jointly identified 20 shared genes， enriched in neural-cardiovascular tissues such as the cerebral cortex， amygdala， and left ventricle， and involved in DNA damage response， RNA metabolism， transcriptional regulation， and FAS signaling pathway （FDR<0.05）.Conclusion Arrhythmia and OCD share a common genetic basis. The co-morbidity mechanism may involve the common vulnerability of neurons and cardiac muscle cells in terms of gene expression regulation and stress response， supporting the role of the brain-heart axis in the pathophysiology of both conditions. |
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