Unraveling the cellular characteristics of cardiomyopathy with rare variant-driven gene signatures using multi-omics analysis

利用多组学分析揭示罕见变异驱动的基因特征在心肌病细胞学中的应用

阅读:2

Abstract

Whole-genome sequencing technologies have advanced, leading to an increase in uncharacterized variants with unknown functions. This study focuses on characterizing cardiomyopathy-associated genes harboring theses rare variants and uncovering their cellular contexts using single-cell transcriptomics. We investigated whole genome sequencing on 245 unrelated Korean patients with either dilated (48.2%) and hypertrophic (47.8%) cardiomyopathy. Rare variants were identified and subjected to burden analysis to detect potentially causative candidates. To understand their biological impact, we profiled single-cell transcriptomes from an independent dataset, highlighting cell populations and interactions relevant to disease pathogenesis. A total of 3584 rare variants were discovered, including 50 pathogenic or likely pathogenic variants in 41 patients. Among the remaining 3534 variants of uncertain significance (VUS), burden analysis revealed 144 gene signatures significantly enriched in pathways related to cardiac muscle tissue development, heart morphogenesis, and endocrine system development (FDR < 0.003). These gene signatures were strongly correlated with cardiomyopathy - associated phenotypes, including HCM (HP:0001639) and DCM (HP:0001644) from the Human Phenotype Ontology (HPO) database. Single-cell transcriptomic analysis of 11,664 heart tissue cells demonstrated that the expression of these gene is influenced by cellular heterogeneity, which may contribute to disease manifestation. Further analysis identified five major cell types in heart tissue, revealing dynamic interactions between cardiomyocytes and endothelial cells. Rare genetic variants, including VUS, are closely linked to cardiac developmental processes and the sarcolemma integrity in cardiomyopathy. Our findings underscore the critical involvement of both cardiomyocytes and non-cardiomyocytes in disease etiology, highlighting the utility of integrating genomic and single-cell data for mechanistic insights.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。