Transcriptome-Wide Analysis Identifies Novel Associations With Blood Pressure. Issue 4 (October 2017)

• Record Type: Journal Article
• Authors: Zeller, Tanja; Schurmann, Claudia; Schramm, Katharina; Müller, Christian; Kwon, Soonil; Wild, Philipp S.; Teumer, Alexander; Herrington, David; Schillert, Arne; Iacoviello, Licia; Kratzer, Adelheid; Jagodzinski, Annika; Karakas, Mahir; Ding, Jingzhong; Neumann, Johannes T.; Kuulasmaa, Kari; Gieger, Christian; Kacprowski, Tim; Schnabel, Renate B.; Roden, Michael; Wahl, Simone; Rotter, Jerome I.; Ojeda, Francisco; Carstensen-Kirberg, Maren; Tregouet, David-Alexandre; Dörr, Marcus; Meitinger, Thomas; Lackner, Karl J.; Wolf, Petra; Felix, Stephan B.; Landmesser, Ulf; Costanzo, Simona; Ziegler, Andreas; Liu, Yongmei; Völker, Uwe; Palmas, Walter; Prokisch, Holger; Guo, Xiuqing; Herder, Christian; Blankenberg, Stefan; Homuth, Georg;
• Is Part Of: Hypertension. Volume 70:Issue 4(2017:Oct.)
• Publication Date: 2017-10
• Subjects: blood pressure -- gene expression -- genome-wide association study -- hypertension -- transcriptome; Hypertension -- Periodicals; Hypertension -- Treatment -- Periodicals; 616.132005
• DOI: 10.1161/HYPERTENSIONAHA.117.09458
• Languages: English
• ISSNs: 0194-911X

Abstract

Abstract : Hypertension represents a major cardiovascular risk factor. The pathophysiology of increased blood pressure (BP) is not yet completely understood. Transcriptome profiling offers possibilities to uncover genetics effects on BP. Based on 2 populations including 2549 individuals, a meta-analyses of monocytic transcriptome-wide profiles were performed to identify transcripts associated with BP. Replication was performed in 2 independent studies of whole-blood transcriptome data including 1990 individuals. For identified candidate genes, a direct link between long-term changes in BP and gene expression over time and by treatment with BP-lowering therapy was assessed. The predictive value of protein levels encoded by candidate genes for subsequent cardiovascular disease was investigated. Eight transcripts ( CRIP1, MYADM, TIPARP, TSC22D3, CEBPA, F12, LMNA, and TPPP3 ) were identified jointly accounting for up to 13% (95% confidence interval, 8.7–16.2) of BP variability. Changes in CRIP1, MYADM, TIPARP, LMNA, TSC22D3, CEBPA, and TPPP3 expression associated with BP changes—among these, CRIP1 gene expression was additionally correlated to measures of cardiac hypertrophy. Assessment of circulating CRIP1 (cystein-rich protein 1) levels as biomarkers showed a strong association with increased risk for incident stroke (hazard ratio, 1.06; 95% confidence interval, 1.03–1.09; P =5.0×10 –5 ). Our comprehensive analysis of global gene expression highlights 8 novel transcripts significantly associated with BP, providing a link between gene expression and BP. Translational approaches further established evidence for the potential use of CRIP1 as emerging disease-related biomarker. Abstract : Supplemental Digital Content is available in the text.