Integration of transcriptomes of senescent cell models with multi-tissue patient samples reveals reduced COL6A3 as an inducer of senescence.
Integration of transcriptomes of senescent cell models with multi-tissue patient samples reveals reduced COL6A3 as an inducer of senescence.
复制标题
衰老细胞模型的转录组与多组织患者样本的整合揭示了 COL6A3 作为衰老诱导剂的减少。
DOI：
10.1016/j.celrep.2023.113371
复制
发表时间：
2023
期刊：
影响因子：
8.8
通讯作者：
Stewart,An
中科院分区：
文献类型：
--
作者：
Savić,Radoslav;Yang,Jialiang;Koplev,Simon;An,MahruC;Patel,PriyankaL;O'Brien,RobertN;Dubose,BrittanyN;Dodatko,Tetyana;Rogatsky,Eduard;Sukhavasi,Katyayani;Ermel,Raili;Ruusalepp,Arno;Houten,SanderM;Kovacic,JasonC;Stewart,An
衰老细胞是年龄依赖性心血管组织功能障碍的主要原因，但缺乏对它们在体内细胞标记物和组织背景的了解。为了揭示组织相关的衰老生物学，我们将10个实验性衰老细胞模型的转录组与224个多组织基因共表达网络整合在一起，该网络基于来自600名冠状动脉疾病（CAD）患者的7个组织活检的RNA-seq数据。我们确定了56个与衰老相关的模块，其中许多富含CAD GWAS基因，并与心脏代谢特征相关，这支持了衰老基因程序在组织和CAD中的普遍性。跨组织网络分析揭示了86个候选衰老相关分泌表型（SASP）因子，包括COL 6A 3。COL 6A 3的实验性敲低诱导了与大多数实验性衰老模型重叠的转录变化，细胞周期停滞与DREAM复合物靶向基因的调节有关。我们为细胞衰老提供了转录组学资源，并确定了候选生物标志物，SASP因子和人体组织衰老的潜在驱动因素。
Senescent cells are a major contributor to age-dependent cardiovascular tissue dysfunction, but knowledge of theirin vivocell markers and tissue context is lacking. To reveal tissue-relevant senescence biology, we integrate the transcriptomes of 10 experimental senescence cell models with a 224 multi-tissue gene co-expression network based on RNA-seq data of seven tissues biopsies from ∼600 coronary artery disease (CAD) patients. We identify 56 senescence-associated modules, many enriched in CAD GWAS genes and correlated with cardiometabolic traits—which supports universality of senescence gene programs across tissues and in CAD. Cross-tissue network analyses reveal 86 candidate senescence-associated secretory phenotype (SASP) factors, including COL6A3. Experimental knockdown of COL6A3 induces transcriptional changes that overlap the majority of the experimental senescence models, with cell-cycle arrest linked to modulation of DREAM complex-targeted genes. We provide a transcriptomic resource for cellular senescence and identify candidate biomarkers, SASP factors, and potential drivers of senescence in human tissues.