Transcriptomic Analysis Reveals Novel Transcription Factors Associated With Renin–Angiotensin–Aldosterone System in Human Atheroma. Issue 6 (December 2016)

• Record Type: Journal Article
• Authors: Nehme, Ali; Cerutti, Catherine; Zibara, Kazem
• Is Part Of: Hypertension. Volume 68:Issue 6(2016:Dec.)
• Publication Date: 2016-12
• Subjects: atherosclerosis -- gene expression profiling -- gene expression regulation -- microarray analysis -- transcription factors -- transcriptome; Hypertension -- Periodicals; Hypertension -- Treatment -- Periodicals; 616.132005
• DOI: 10.1161/HYPERTENSIONAHA.116.08070
• Languages: English
• ISSNs: 0194-911X

Abstract

Abstract : Despite the well-known role of the renin–angiotensin–aldosterone system (RAAS) in atheroma, its global local organization is poorly understood. In this study, we used transcriptomic meta-analysis to reveal the local transcriptional organization and regulation of 37 extended RAAS (extRAAS) genes in atheroma. Expression analysis and hierarchical clustering were done on extRAAS genes in 32 paired early and advanced atherosclerotic lesions. Contrary to receptor-coding transcripts, multiple angiotensin-metabolizing enzymes showed higher expression in advance, in comparison to early lesions. Interestingly, similar results were obtained from GEO data sets containing human (n=839) and mouse (n=18) atherosclerotic samples, but different from normal human (n=11) arterial tissues. The expression and coordination patterns were then used to construct transcriptional maps of extRAAS, displaying favored pathways in atheroma. Three coexpression modules (M1, M2, and M3) with >80% reproducibility across human atheroma data sets were identified. M1 and M3 contained angiotensin-metabolizing enzymes transcripts, whereas M2 contained proatherogenic receptor-coding transcripts. Interestingly, M1 and M2 were negatively correlated. A total of 21 transcription factors with enriched binding sites in the promoters of coordinated genes were extracted, among which IRF5, MAX, and ETV5 showed significant positive correlations with M1, but negative correlations with M2. However, ETS1 and SMAD1 transcripts were positively correlated to receptor-coding genes in M2. Despite sharing some similarities in extRAAS organization with kidney and adipose, atheroma showed specific correlations between extRAAS and transcription factors. In conclusion, our transcriptional map helps in designing more efficient treatments for atherosclerosis. In addition, the identified transcription factors provide a basis for the discovery of atheroma-specific modulators of extRAAS. Abstract : Supplemental Digital Content is available in the text.