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Wild, P.S.* ; Felix, J.F.* ; Schillert, A.* ; Teumer, A.* ; Chen, M.* ; Leening, M.J.G.* ; Voelker, U.* ; Grossmann, V.* ; Brody, J.A.* ; Irvin, M.R.* ; Shah, S.J.* ; Pramana, S.* ; Lieb, W.* ; Schmidt, R.* ; Stanton, A.V.* ; Malzahn, D.* ; Smith, A.V.* ; Sundström, J.* ; Minelli, C.* ; Ruggiero, D.* ; Lyytikäinen, L.-P.* ; Tiller, D.* ; Smith, J.G.* ; Monnereau, C.* ; Di Tullio, M.R.* ; Musani, S.K.* ; Morrison, A.C.* ; Pers, T.H.* ; Morley, M.* ; Kleber, M.E.* ; Aragam, J.* ; Benjamin, E.J.* ; Bis, J.C.* ; Bisping, E.* ; Broeckel, U.* ; Cheng, S.* ; Deckers, J.W.* ; Del Greco, F.* ; Edelmann, F.* ; Fornage, M.* ; Franke, L.* ; Friedrich, N.* ; Harris, T.B.* ; Hofer, E.* ; Hofman, A.* ; Huang, J.* ; Hughes, A.D.* ; Kähönen, M.* ; Kruppa, J.* ; Lackner, K.J.* ; Lannfelt, L.* ; Laskowski, R.A.* ; Launer, L.J.* ; Leosdottir, M.* ; Lin, H.* ; Lindgren, C.M.* ; Loley, C.* ; MacRae, C.A.* ; Mascalzoni, D.* ; Mayet, J.* ; Medenwald, D.* ; Morris, A.P.* ; Mueller, C.* ; Müller-Nurasyid, M. ; Nappo, S.* ; Nilsson, P.M.* ; Nuding, S.* ; Nutile, T.* ; Peters, A. ; Pfeufer, A. ; Pietzner, D.* ; Pramstaller, P.P.* ; Raitakari, O.T.* ; Rice, K.M.* ; Rivadeneira, F.* ; Rotter, J.I.* ; Ruohonen, S.T.* ; Sacco, R.L.* ; Samdarshi, T.E.* ; Schmidt, H.* ; Sharp, A.S.P.* ; Shields, D.C.* ; Sorice, R.* ; Sotoodehnia, N.* ; Stricker, B.H.* ; Surendran, P.* ; Thom, S.* ; Toeglhofer, A.M.* ; Uitterlinden, A.G.* ; Wachter, R.* ; Voelzke, H.* ; Ziegler, A.* ; Muenzel, T.* ; Maerz, W.* ; Cappola, T.P.* ; Hirschhorn, J.N.* ; Mitchell, G.F.* ; Smith, N.L.* ; Fox, E.R.* ; Dueker, N.D.* ; Jaddoe, V.W.V.* ; Melander, O.* ; Russ, M.* ; Lehtimäki, T.* ; Ciullo, M.* ; Hicks, A.A.* ; Lind, L.* ; Gudnason, V.* ; Pieske, B.* ; Barron, A.J.* ; Zweiker, R.* ; Schunkert, H.* ; Ingelsson, E.* ; Liu, K.* ; Arnett, D.K.* ; Psaty, B.M.* ; Blankenberg, S.* ; Larson, M.G.* ; Felix, S.B.* ; Franco, O.H.* ; Zeller, T.* ; Vasan, R.S.* ; Doerr, M.*

Large-scale genome-wide analysis identifies genetic variants associated with cardiac structure and function.

J. Clin. Invest. 127, 1798-1812 (2017)
Verlagsversion DOI PMC
Open Access Gold
BACKGROUND. Understanding the genetic architecture of cardiac structure and function may help to prevent and treat heart disease. This investigation sought to identify common genetic variations associated with inter-individual variability in cardiac structure and function. METHODS. A GWAS meta-analysis of echocardiographic traits was performed, including 46,533 individuals from 30 studies (EchoGen consortium). The analysis included 16 traits of left ventricular (LV) structure, and systolic and diastolic function. RESULTS. The discovery analysis included 21 cohorts for structural and systolic function traits (n = 32,212) and 17 cohorts for diastolic function traits (n = 21,852). Replication was performed in 5 cohorts (n = 14,321) and 6 cohorts (n = 16,308), respectively. Besides 5 previously reported loci, the combined meta-analysis identified 10 additional genome-wide significant SNPs: rs12541595 near MTSS1 and rs10774625 in ATXN2 for LV end-diastolic internal dimension; rs806322 near KCNRG, rs4765663 in CACNA1C, rs6702619 near PALMD, rs7127129 in TMEM16A, rs11207426 near FGGY, rs17608766 in GOSR2, and rs17696696 in CFDP1 for aortic root diameter; and rs12440869 in IQCH for Doppler transmitral A-wave peak velocity. Findings were in part validated in other cohorts and in GWAS of related disease traits. The genetic loci showed associations with putative signaling pathways, and with gene expression in whole blood, monocytes, and myocardial tissue. CONCLUSION. The additional genetic loci identified in this large meta-analysis of cardiac structure and function provide insights into the underlying genetic architecture of cardiac structure and warrant follow-up in future functional studies.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Schlagwörter Reduced Ejection Fraction; Coronary-artery-disease; Heart-failure; Myocardial-infarction; Suppressor Gene; Blood-pressure; Risk; Metaanalysis; Epidemiology; Replication
Sprache englisch
Veröffentlichungsjahr 2017
HGF-Berichtsjahr 2017
ISSN (print) / ISBN 0021-9738
e-ISSN 1558-8238
Zeitschrift Journal of Clinical Investigation
Quellenangaben Band: 127, Heft: 5, Seiten: 1798-1812 Artikelnummer: , Supplement: ,
Verlag American Society of Clinical Investigation
Verlagsort Ann Arbor
Begutachtungsstatus Peer reviewed
Institut(e) Institute of Genetic Epidemiology (IGE)
Institute of Epidemiology (EPI)
Institute of Bioinformatics and Systems Biology (IBIS)
POF Topic(s) 30501 - Systemic Analysis of Genetic and Environmental Factors that Impact Health
30202 - Environmental Health
30505 - New Technologies for Biomedical Discoveries
Forschungsfeld(er) Genetics and Epidemiology
Enabling and Novel Technologies
PSP-Element(e) G-504100-001
G-504000-001
G-503700-001
DOI 10.1172/JCI84840
WOS ID WOS:000400381000022
Scopus ID 85018974417
PubMed ID 28394258
Erfassungsdatum 2017-05-30
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