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(Hypertension. 2009;53:35.)
© 2009 American Heart Association, Inc.
Original Articles |
From the Divisions of Biostatistics (G.S., C.C.G., D.C.R.) and Statistical Genomics (A.T.K.) and the Departments of Genetics and Psychiatry (D.C.R.), Washington University School of Medicine, Saint Louis, MO; Department of Epidemiology (D.K.A.), School of Public Health, University of Alabama at Birmingham; Department of Neurology (R.H.M.), Boston University School of Medicine, Massachusetts; Division of Epidemiology and Community Health (J.S.P.), University of Minnesota, Minneapolis; and Cardiovascular Genetics Division (S.C.H.), University of Utah School of Medicine, Salt Lake City.
Correspondence to Dr Gang Shi, Division of Biostatistics, Washington University School of Medicine, Campus Box 8067, 660 S Euclid Ave, St. Louis, MO 63110-1093. E-mail gang{at}wubios.wustl.edu
Genome-wide linkage analysis was performed for systolic and diastolic blood pressures in the Hypertension Genetic Epidemiology Network. We investigated the role of gene–age interactions using a recently developed variance components method that incorporates age variation in genetic effects. Substantially improved linkage evidence, in terms of both the number of linkage peaks and their significance levels, was observed. Twenty-six linkage peaks were identified with maximum logarithm of odds scores ranging between 3.0 and 4.6, 15 of which were cross-validated by the literature. The chromosomal region 1p36 that showed the highest logarithm of odds score in our study was found to be supported by evidence from 3 studies. The new method also led to vastly improved validation across ethnic groups. Ten of the 15 supported linkage peaks were cross-validated between 2 different ethnic groups, and 2 peaks on chromosomal region 1q31 and 16p11 were validated in 3 ethnic groups. In conclusion, this investigation demonstrates that genetic effects on blood pressure vary by age. The improved genetic linkage results presented here should help to identify the specific genetic variants that explain the observed results.
Key Words: blood pressure genetics hypertension linkage gene–age interactions QTL effect
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