Heritability and genetic correlations of obesity indices with ambulatory and office beat-to-beat blood pressure in the Oman Family Study.

OBJECTIVE: To more precisely and comprehensively estimate the genetic and environmental correlations between various indices of obesity and BP. METHODS: We estimated heritability and genetic correlations of obesity indices with BP in the Oman family study (n = 1231). Ambulatory and office beat-to-beat BP was measured and mean values for SBP and DBP during daytime, sleep, 24-h and 10 min at rest were calculated. Different indices were used to quantify obesity and fat distribution: BMI, percentage of body fat (%BF), waist circumference and waist-to-height ratio (WHtR). SOLAR software was used to perform univariate and bivariate quantitative genetic analyses adjusting for age, age, sex, age-sex and age--sex interactions. RESULTS: Heritabilities of BP ranged from 30.2 to 38.2% for ambulatory daytime, 16.8--21.4% for sleeping time, 32.1--40.4% for 24-h and 22--24.4% for office beat-to-beat measurements. Heritabilities for obesity indices were 67.8% for BMI, 52.2% for %BF, 37.3% for waist circumference and 37.9% for WHtR. All obesity measures had consistently positive phenotypic correlations with ambulatory and office beat-to-beat SBP and DBP (r-range: 0.14--0.32). Genetic correlations of obesity indices with SBP and DBP were higher than environmental correlations (rG: 0.16--0.50; rE: 0.01--0.31). CONCLUSION: The considerable genetic overlap between a variety of obesity indices and both ambulatory and office beat-to-beat BP highlights the relevance of pleiotropic genes. Future GWAS analyses should discover the specific genes both influencing obesity indices and BP to help unravel their shared genetic background.

Heritability and genetic and environmental correlations of heart rate variability and baroreceptor reflex sensitivity with ambulatory and beat-to-beat blood pressure.

This family study from Oman (n = 1231) explored the heritability and genetic and environmental correlations of heart rate variability (HRV) and baroreceptor reflex sensitivity (BRS) with ambulatory and beat-to-beat blood pressure (BP). Ambulatory BP was measured for 24 hours to calculate mean values for daytime and sleep separately. Time and frequency domain HRV indices, BRS, office beat-to-beat BP, and heart rate (HR) were measured for 10 minutes at rest. SOLAR software was used to perform univariate and bivariate quantitative genetic analyses adjusting for age, age2, sex, their interactions and BMI. Heritability of SBP and DBP ranged from 16.8% to 40.4% for daytime, sleeping, 24-hour and office beat-to-beat measurements. HR and BRS showed a heritability of 31.9% and 20.6%, respectively, and for HRV indices heritability ranged from 11.1% to 20.5%. All HRV measurements and BRS were found to be negatively correlated with BP, but phenotypic correlation coefficients were relatively weak; HR was positively correlated with BP. None of the genetic correlations were statistically significant while environmental factors explained most of the correlations for all HRV indices with BP. Our study found consistent but weak correlations among HRV, HR, BRS and ambulatory/office beat-to-beat BP. However, environmental rather than genetic factors contributed most to those correlations.

Heritability and genetic correlations of heart rate variability at rest and during stress in the Oman Family Study.

INTRODUCTION: Individual differences in heart rate variability (HRV) can be partly attributed to genetic factors that may be more pronounced during stress. Using data from the Oman Family Study (OFS), we aimed to estimate and quantify the relative contribution of genes and environment to the variance of HRV at rest and during stress; calculate the overlap in genetic and environmental influences on HRV at rest and under stress using bivariate analyses of HRV parameters and heart rate (HR). METHODS: Time and frequency domain HRV variables and average HR were measured from beat-to-beat HR obtained from electrocardiogram recordings at rest and during two stress tests [mental: Word Conflict Test (WCT) and physical: Cold Pressor Test (CPT)] in the OFS - a multigenerational pedigree consisting of five large Arab families with a total of 1326 participants. SOLAR software was used to perform quantitative genetic modelling. RESULTS: Heritability estimates for HRV and HR ranged from 0.11 to 0.31 for rest, 0.09-0.43 for WCT, and 0.07-0.36 for CPT. A large part of the genetic influences during rest and stress conditions were shared with genetic correlations ranging between 0.52 and 0.86 for rest-WCT and 0.60-0.92 for rest-CPT. Nonetheless, genetic rest-stress correlations for most traits were significantly smaller than 1 indicating some stress-specific genetic effects. CONCLUSION: Genetic factors significantly influence HRV and HR at rest and under stress. Most of the genetic factors that influence HRV at rest also influence HRV during stress tests, although some unique genetic variance emerges during these challenging conditions.

Erratum: Genetic loci associated with heart rate variability and their effects on cardiac disease risk.

This corrects the article DOI: 10.1038/ncomms15805.

Genetic loci associated with heart rate variability and their effects on cardiac disease risk.

Reduced cardiac vagal control reflected in low heart rate variability (HRV) is associated with greater risks for cardiac morbidity and mortality. In two-stage meta-analyses of genome-wide association studies for three HRV traits in up to 53,174 individuals of European ancestry, we detect 17 genome-wide significant SNPs in eight loci. HRV SNPs tag non-synonymous SNPs (in NDUFA11 and KIAA1755), expression quantitative trait loci (eQTLs) (influencing GNG11, RGS6 and NEO1), or are located in genes preferentially expressed in the sinoatrial node (GNG11, RGS6 and HCN4). Genetic risk scores account for 0.9 to 2.6% of the HRV variance. Significant genetic correlation is found for HRV with heart rate (-0.74

Validity of (Ultra-)Short Recordings for Heart Rate Variability Measurements.

OBJECTIVES: In order to investigate the applicability of routine 10s electrocardiogram (ECG) recordings for time-domain heart rate variability (HRV) calculation we explored to what extent these (ultra-)short recordings capture the "actual" HRV. METHODS: The standard deviation of normal-to-normal intervals (SDNN) and the root mean square of successive differences (RMSSD) were measured in 3,387 adults. SDNN and RMSSD were assessed from (ultra)short recordings of 10s(3x), 30s, and 120s and compared to 240s-300s (gold standard) measurements. Pearson's correlation coefficients (r), Bland-Altman 95% limits of agreement and Cohen's d statistics were used as agreement analysis techniques. RESULTS: Agreement between the separate 10s recordings and the 240s-300s recording was already substantial (r = 0.758-0.764/Bias = 0.398-0.416/d = 0.855-0.894 for SDNN; r = 0.853-0.862/Bias = 0.079-0.096/d = 0.150-0.171 for RMSSD), and improved further when three 10s periods were averaged (r = 0.863/Bias = 0.406/d = 0.874 for SDNN; r = 0.941/Bias = 0.088/d = 0.167 for RMSSD). Agreement increased with recording length and reached near perfect agreement at 120s (r = 0.956/Bias = 0.064/d = 0.137 for SDNN; r = 0.986/Bias = 0.014/d = 0.027 for RMSSD). For all recording lengths and agreement measures, RMSSD outperformed SDNN. CONCLUSIONS: Our results confirm that it is unnecessary to use recordings longer than 120s to obtain accurate measures of RMSSD and SDNN in the time domain. Even a single 10s (standard ECG) recording yields a valid RMSSD measurement, although an average over multiple 10s ECGs is preferable. For SDNN we would recommend either 30s or multiple 10s ECGs. Future research projects using time-domain HRV parameters, e.g. genetic epidemiological studies, could calculate HRV from (ultra-)short ECGs enabling such projects to be performed at a large scale.

QCGWAS: A flexible R package for automated quality control of genome-wide association results.

QCGWAS is an R package that automates the quality control of genome-wide association result files. Its main purpose is to facilitate the quality control of a large number of such files before meta-analysis. Alternatively, it can be used by individual cohorts to check their own result files. QCGWAS is flexible and has a wide range of options, allowing rapid generation of high-quality input files for meta-analysis of genome-wide association studies. AVAILABILITY: http://cran.r-project.org/web/packages/QCGWAS CONTACT: i.m.nolte@umcg.nl Supplementary information: Supplementary data are available at Bioinformatics online.

Heritability of ambulatory and beat-to-beat office blood pressure in large multigenerational Arab pedigrees: the 'Oman Family study'.

OBJECTIVE: To estimate the heritability of ambulatory blood pressure (BP), heart rate (HR), and beat-to-beat office BP and HR in an isolated, environmentally and genetically homogeneous Omani Arab population. METHODS: Ambulatory BP measurements were recorded in 1,124 subjects with a mean age of 33.8 ± 16.2 years, using the auscultatory mode of the validated Schiller ambulatory BP Monitor. Beat-to-beat BP and HR were recorded by the Task Force Monitor. Heritability was estimated using quantitative genetic analysis. This was achieved by applying the maximum-likelihood-based variance decomposition method implemented in SOLAR software. RESULTS: We detected statistically significant heritability estimates for office beat-to-beat, 24-hour, daytime, and sleep HR of 0.31, 0.21, 0.20, and 0.07, respectively. Heritability estimates in the above mentioned conditions for systolic BP (SBP)/diastolic BP (DBP)/mean BP (MBP)were all significant and estimated at 0.19/0.19/0.19, 0.30/0.44/0.41, 0.28/0.38/0.39, and 0.21/0.18/0.20,respectively. Heritability estimates for 24-hour and daytime ambulatory SBP, DBP, and MBP ranged from 0.28 to 0.44, and were higher than the heritability estimates for beat-to-beat recordings and sleep periods,which were estimated within a narrow range of 0.18-0.21. CONCLUSION: In this cohort, because shared environments are common to all, the environmental influence that occurs is primarily due to the variation in non-shared environment that is unique to the individual. We demonstrated significant heritability estimates for both beat-to-beat office and ambulatory BP and HR recordings, but 24-hour and daytime ambulatory heritabilities are higher than those from beat-to-beat resting levels and ambulatory night-time recordings.