单细胞转录组学结合孟德尔分析探讨扩张性心肌病潜在治疗靶点

Combined analysis of single-cell transcriptomics and clinical data for the prognosis of dilated cardiomyopathy

目的 在通过分析多组转录组和单细胞数据集,深入探究扩张性心肌病(DCM)的分子机制,并寻找潜在的治疗靶点。方法 (1)数据获取与预处理。从GEO数据库获取多个转录组和单细胞数据集,并利用SVA软件去除批次效应。(2)差异基因分析。通过PCA和差异分析,筛选出与DCM相关的关键基因。(3)功能富集分析。利用GO和KEGG富集分析,探讨这些基因在生物学过程中的功能。(4)关键基因筛选。采用共识聚类、LASSO和随机森林等算法,从差异基因中筛选出关键基因。(5)因果关系分析。进行孟德尔随机化分析,验证关键基因与DCM之间的因果关系。(6)细胞类型分析。利用单细胞数据分析确定关键基因在不同细胞类型中的表达情况。结果 (1)鉴定出788个与DCM相关的关键基因。(2)GO和KEGG分析揭示了这些基因在多个生物学通路中发挥重要作用。(3)筛选出FGFR3、RTKN2和SLC9A3R1三个关键基因。(3)孟德尔随机化分析证实SLC9A3R1与DCM存在因果关系。(4)单细胞数据分析显示SLC9A3R1在心肌细胞中高表达。结论 本研究通过多组学分析,深入解析了DCM的分子机制。SLC9A3R1作为新发现的关键基因在DCM的发病过程中可能扮演重要角色,有望成为新的治疗靶点。这些研究结果为DCM的诊疗提供了新的思路和方向。

Objective This study aimed to delve into the molecular mechanisms underlying dilated cardiomyopathy(DCM)by analyzing multiple transcriptomic and single-cell datasets,and to identify potential therapeutic targets.Method(1)Data acquisition and preprocessing:Multiple transcriptomic and single-cell datasets were obtained from the GEO database,and batch effects were removed using the SVA package.(2)Differential gene analysis:PCA and differential analysis were performed to identify key genes associated with DCM.(3)Functional enrichment analysis:GO and KEGG enrichment analyses were conducted to explore the biological functions of these genes.(4)Key gene screening:Consensus clustering,LASSO,and random forest algorithms were employed to screen for key genes from the differential genes.(5)Causal relationship analysis:Mendelian randomization analysis was performed to verify the causal relationship between key genes and DCM.(6)Cell type analysis:Single-cell data analysis was used to determine the expression of key genes in different cell types.Result(1)A total of 788 key genes associated with DCM were identified.(2)GO and KEGG analyses revealed that these genes played important roles in multiple biological pathways.(3)Three key genes,FGFR3,RTKN2,and SLC9A3R1,were screened out.(4)Mendelian randomization analysis confirmed the causal relationship between SLC9A3R1 and DCM.(5)Single-cell data analysis showed that SLC9A3R1 was highly expressed in cardiomyocytes. Conclusion Through multi-omics analysis, this study has deeply explored the molecular mechanisms of DCM. SLC9A3R1, as a newly discovered key gene, may play a crucial role in the pathogenesis of DCM and holds promise as a novel therapeutic target. These findings provide new insights and directions for the diagnosis and treatment of DCM.