Integrative network analysis reveals molecular mechanisms of blood pressure regulation.

Autor: Huan T; The National Heart Lung and Blood Institute's Framingham Heart Study, Framingham, MA, USA The Population Sciences Branch and the Division of Intramural Research, National Heart, Lung and Blood Institute, Bethesda, MD, USA., Meng Q; Department of Integrative Biology and Physiology, University of California, Los Angeles, CA, USA., Saleh MA; Department of Medicine, Division of Clinical Pharmacology, Vanderbilt University, Nashville, TN, USA Department of Pharmacology and Toxicology, Faculty of Pharmacy, Mansoura University, Mansoura, Egypt., Norlander AE; Department of Medicine, Division of Clinical Pharmacology, Vanderbilt University, Nashville, TN, USA., Joehanes R; The National Heart Lung and Blood Institute's Framingham Heart Study, Framingham, MA, USA The Population Sciences Branch and the Division of Intramural Research, National Heart, Lung and Blood Institute, Bethesda, MD, USA Mathematical and Statistical Computing Laboratory, Center for Information Technology National Institutes of Health, Bethesda, MD, USA Harvard Medical School, Boston, MA, USA Hebrew SeniorLife, Boston, MA, USA., Zhu J; Institute of Genomics and Multiscale Biology, New York, NY, USA Graduate School of Biological Sciences Mount Sinai School of Medicine, New York, NY, USA., Chen BH; The National Heart Lung and Blood Institute's Framingham Heart Study, Framingham, MA, USA The Population Sciences Branch and the Division of Intramural Research, National Heart, Lung and Blood Institute, Bethesda, MD, USA., Zhang B; Institute of Genomics and Multiscale Biology, New York, NY, USA Graduate School of Biological Sciences Mount Sinai School of Medicine, New York, NY, USA., Johnson AD; The National Heart Lung and Blood Institute's Framingham Heart Study, Framingham, MA, USA Cardiovascular Epidemiology and Human Genomics Branch, Division of Intramural Research, National Heart, Lung and Blood Institute, Bethesda, MD, USA., Ying S; Mathematical and Statistical Computing Laboratory, Center for Information Technology National Institutes of Health, Bethesda, MD, USA., Courchesne P; The National Heart Lung and Blood Institute's Framingham Heart Study, Framingham, MA, USA The Population Sciences Branch and the Division of Intramural Research, National Heart, Lung and Blood Institute, Bethesda, MD, USA., Raghavachari N; Division of Geriatrics and Clinical Gerontology, National Institute on Aging, Bethesda, MD, USA., Wang R; Genomics Core facility Genetics & Developmental Biology Center, The National Heart, Lung and Blood Institute, Bethesda, MD, USA., Liu P; Genomics Core facility Genetics & Developmental Biology Center, The National Heart, Lung and Blood Institute, Bethesda, MD, USA., O'Donnell CJ; The National Heart Lung and Blood Institute's Framingham Heart Study, Framingham, MA, USA Cardiovascular Epidemiology and Human Genomics Branch, Division of Intramural Research, National Heart, Lung and Blood Institute, Bethesda, MD, USA., Vasan R; The National Heart Lung and Blood Institute's Framingham Heart Study, Framingham, MA, USA., Munson PJ; Mathematical and Statistical Computing Laboratory, Center for Information Technology National Institutes of Health, Bethesda, MD, USA., Madhur MS; Department of Medicine, Division of Clinical Pharmacology, Vanderbilt University, Nashville, TN, USA., Harrison DG; Department of Medicine, Division of Clinical Pharmacology, Vanderbilt University, Nashville, TN, USA., Yang X; Department of Integrative Biology and Physiology, University of California, Los Angeles, CA, USA xyang123@ucla.edu levyd@nih.gov., Levy D; The National Heart Lung and Blood Institute's Framingham Heart Study, Framingham, MA, USA The Population Sciences Branch and the Division of Intramural Research, National Heart, Lung and Blood Institute, Bethesda, MD, USA xyang123@ucla.edu levyd@nih.gov.
Jazyk: angličtina
Zdroj: Molecular systems biology [Mol Syst Biol] 2015 Apr 16; Vol. 11 (1), pp. 799. Date of Electronic Publication: 2015 Apr 16.
DOI: 10.15252/msb.20145399
Abstrakt: Genome-wide association studies (GWAS) have identified numerous loci associated with blood pressure (BP). The molecular mechanisms underlying BP regulation, however, remain unclear. We investigated BP-associated molecular mechanisms by integrating BP GWAS with whole blood mRNA expression profiles in 3,679 individuals, using network approaches. BP transcriptomic signatures at the single-gene and the coexpression network module levels were identified. Four coexpression modules were identified as potentially causal based on genetic inference because expression-related SNPs for their corresponding genes demonstrated enrichment for BP GWAS signals. Genes from the four modules were further projected onto predefined molecular interaction networks, revealing key drivers. Gene subnetworks entailing molecular interactions between key drivers and BP-related genes were uncovered. As proof-of-concept, we validated SH2B3, one of the top key drivers, using Sh2b3(-/-) mice. We found that a significant number of genes predicted to be regulated by SH2B3 in gene networks are perturbed in Sh2b3(-/-) mice, which demonstrate an exaggerated pressor response to angiotensin II infusion. Our findings may help to identify novel targets for the prevention or treatment of hypertension.
(© 2015 The Authors. Published under the terms of the CC BY 4.0 license.)
Databáze: MEDLINE
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