Objectives: Blood pressure variability (BPV) and its reduction in response to antihypertensive treatment are predictors of clinical outcomes; however, little is known about its heritability. In this study, we examined the relative influence of genetic and environmental sources of variance of BPV and the extent to which it may depend on race or sex in young twins.
Methods: Twins were enrolled from two studies. One study included 703 white twins (308 pairs and 87 singletons) aged 18–34 years, whereas another study included 242 white twins (108 pairs and 26 singletons) and 188 black twins (79 pairs and 30 singletons) aged 12–30 years. BPV was calculated from 24-h ambulatory blood pressure recording.
Results: Twin modeling showed similar results in the separate analysis in both twin studies and in the meta-analysis. Familial aggregation was identified for SBP variability (SBPV) and DBP variability (DBPV) with genetic factors and common environmental factors together accounting for 18–40% and 23–31% of the total variance of SBPV and DBPV, respectively. Unique environmental factors were the largest contributor explaining up to 82–77% of the total variance of SBPV and DBPV. No sex or race difference in BPV variance components was observed. The results remained the same after adjustment for 24-h blood pressure levels.
Conclusions: The variance in BPV is predominantly determined by unique environment in youth and young adults, although familial aggregation due to additive genetic and/or common environment influences was also identified explaining about 25% of the variance in BPV.
aDepartment of Pediatrics, Georgia Prevention Institute, Georgia Health Sciences University, Augusta
bJiann-Ping Hsu College of Public Health, Georgia Southern University, Statesboro, Georgia
cCollege of Nursing, Medical University of South Carolina, Charleston, South Carolina
dDepartment for Human Genetics, University Hospital Gasthuisberg
eHypertension and Cardiovascular Rehabilitation Unit, Department of Cardiovascular Diseases, KU Leuven, Leuven, Belgium
fResearch School for Nutrition, Toxicology and Metabolism (NUTRIM)
gCluster of Genetics and Cell Biology, Department of Complex Genetics, Maastricht University Medical Centre, Maastricht, The Netherlands
hMedical Research Council Epidemiology Unit, Institute of Metabolic Science, Addenbrooke's Hospital, Cambridge, UK
iFaculty of Kinesiology and Rehabilitation Sciences, Department of Biomedical Kinesiology, University Hospital Gasthuisberg, KU Leuven, Leuven, Belgium
jGenetic of Obesity and Related Metabolic Traits Program, Institute for Personalized Medicine, Child Health and Development Institute, Department of Preventive Medicine, Mount Sinai School of Medicine, New York, New York, USA
kDepartment of Epidemiology, Unit of Genetic Epidemiology and Bioinformatics, University of Groningen, University Medical Center Groningen, The Netherlands
Correspondence to Dr Xiaoling Wang, MD, PhD, Department of Pediatrics, Georgia Prevention Institute, Georgia Health Sciences University, HS-1640, Augusta, GA 30912, USA. Tel: +1 706 721 6139; fax: +1 706 721 7150; e-mail: firstname.lastname@example.org
Abbreviations: ABP, ambulatory blood pressure; AIC, Akaike's information criterion; BP, blood pressure; BPV, blood pressure variability; CI, confidence intervals; DBPV, DBP variability; EFPTS, East Flanders Prospective Twin Survey; GEE, generalized estimating equations; MZm, onozygotic; SBPV, SBP variability
Received 7 September, 2012
Revised 12 November, 2012
Accepted 20 December, 2012
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