ObjectivesIn 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.MethodsThe 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.ResultsAgreement 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.ConclusionsOur 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.

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

Objectives To describe the normal appearance and study the biometry of the fetal cerebellar vermis by threedimensional (3D) volume contrast imaging in the coronal (C-) plane (VCI-C). Methods

Genome-wide association studies have detected many loci underlying susceptibility to disease, but most of the genetic factors that contribute to disease susceptibility remain unknown. Here we provide evidence that part of the missing heritability can be explained by an overestimation of heritability. We estimated the heritability of twelve complex human diseases using family history of disease in 1,555,906 white European individuals from the UK Biobank. Estimates using simple family-based statistical models were inflated on average by ~47% comparing with those from Structural Equation Models (SEM) that specifically accounted for shared familial environmental factors. In addition, heritabilities using SNP data explained an average of 44.2% of the simple family-based estimates across diseases and an average of 57.3% of SEM estimated heritability and accounted for almost all of the SEM heritability for hypertension. Our results show that both genetics and familial environment make substantial contributions to familial clustering of disease.

Objective To compare sonographic visualization of midline cerebral structures obtained by two-dimensional (2D) imaging and three-dimensional (3D) multiplanar and volume contrast imaging in the coronal plane (VCI-C), with transfrontal 3D acquisition.Methods Sixty consecutive healthy fetuses in vertex presentation at a mean gestational age of 24 (range, 20-33)

http://cran.r-project.org/web/packages/QCGWAS CONTACT: i.m.nolte@umcg.nl Supplementary information: Supplementary data are available at Bioinformatics online.

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 abovementioned 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.

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