Posts Tagged ‘Genetics of Hypertension’

Cardiometabolic Syndrome and the Genetics of Hypertension: The Neuroendocrine Transcriptome Control Points

Reporter: Aviva Lev-Ari, PhD, RN


Integrated Computational and Experimental Analysis of the Neuroendocrine Transcriptome in Genetic Hypertension Identifies Novel Control Points for the Cardiometabolic Syndrome

Ryan S. Friese, PhD, Chun Ye, PhD, Caroline M. Nievergelt, PhD, Andrew J. Schork, BS, Nitish R. Mahapatra, PhD, Fangwen Rao, MD, Philip S. Napolitan, BS, Jill Waalen, MD, MPH, Georg B. Ehret, MD, Patricia B. Munroe, PhD, Geert W. Schmid-Schönbein, PhD, Eleazar Eskin, PhD and Daniel T. O’Connor, MD

Author Affiliations

From the Departments of Bioengineering (R.S.F., G.W.S.-S.), Medicine (R.S.F., A.J.S., F.R., P.S.N., D.T.O.), Pharmacology (D.T.O.), and Psychiatry (C.M.N.), the Bioinformatics Program (C.Y.), and the Institute for Genomic Medicine (D.T.O.), University of California at San Diego; the VA San Diego Healthcare System, San Diego, CA (D.T.O.); the Departments of Computer Science & Human Genetics, University of California at Los Angeles (E.E.); the Department of Biotechnology, Indian Institute of Technology Madras, Chennai, India (N.R.M.); Clinical Pharmacology and The Genome Centre, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, United Kingdom (P.B.M.); Center for Complex Disease Genomics, McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD (G.B.E.); and Scripps Research Institute, La Jolla, CA (J.W.).

Correspondence to Daniel T. O’Connor, MD, Department of Medicine, University of California at San Diego School of Medicine, VASDHS (0838), Skaggs (SSPPS) Room 4256, 9500 Gilman Drive, La Jolla, CA 92093-0838. E-mail doconnor@ucsd.edu


Background—Essential hypertension, a common complex disease, displays substantial genetic influence. Contemporary methods to dissect the genetic basis of complex diseases such as the genomewide association study are powerful, yet a large gap exists betweens the fraction of population trait variance explained by such associations and total disease heritability.

Methods and Results—We developed a novel, integrative method (combining animal models, transcriptomics, bioinformatics, molecular biology, and trait-extreme phenotypes) to identify candidate genes for essential hypertension and the metabolic syndrome. We first undertook transcriptome profiling on adrenal glands from blood pressure extreme mouse strains: the hypertensive BPH (blood pressure high) and hypotensive BPL (blood pressure low). Microarray data clustering revealed a striking pattern of global underexpression of intermediary metabolism transcripts in BPH. The MITRA algorithm identified a conserved motif in the transcriptional regulatory regions of the underexpressed metabolic genes, and we then hypothesized that regulation through this motif contributed to the global underexpression. Luciferase reporter assays demonstrated transcriptional activity of the motif through transcription factors HOXA3, SRY, and YY1. We finally hypothesized that genetic variation at HOXA3SRY, and YY1 might predict blood pressure and other metabolic syndrome traits in humans. Tagging variants for each locus were associated with blood pressure in a human population blood pressure extreme sample with the most extensive associations for YY1 tagging single nucleotide polymorphism rs11625658 on systolic blood pressure, diastolic blood pressure, body mass index, and fasting glucose. Meta-analysis extended the YY1results into 2 additional large population samples with significant effects preserved on diastolic blood pressure, body mass index, and fasting glucose.

Conclusions—The results outline an innovative, systematic approach to the genetic pathogenesis of complex cardiovascular disease traits and point to transcription factor YY1 as a potential candidate gene involved in essential hypertension and the cardiometabolic syndrome.


Circulation: Cardiovascular Genetics.2012; 5: 430-440

Published online before print June 5, 2012,

doi: 10.1161/ CIRCGENETICS.111.962415

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