Explore the vast range of titles available.

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. 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. 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. 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.

Background The objective of this study was to derive evidence-based physical activity guidelines for the general Dutch population. Methods Two systematic reviews were conducted of English language meta-analyses in PubMed summarizing separately randomized controlled trials and prospective cohort studies on the relation between physical activity and sedentary behaviour on the one hand and the risk of all-cause mortality and incidence of 15 major chronic diseases and conditions on the other hand. Other outcome measures were risk factors for cardiovascular disease and type 2 diabetes, physical functioning, and fitness. On the basis of these reviews, an expert committee derived physical activity guidelines. In deriving the guidelines, the committee first selected only experimental and observational prospective findings with a strong level of evidence and then integrated both lines of evidence. Results The evidence found for beneficial effects on a large number of the outcome measures was sufficiently strong to draw up guidelines to increase physical activity and reduce sedentary behaviour, respectively. At the same time, the current evidence did not provide a sufficient basis for quantifying how much physical activity is minimally needed to achieve beneficial health effects, or at what amount sedentary behaviour becomes detrimental. A general tenet was that at every level of current activity, further increases in physical activity provide additional health benefits, with relatively larger effects among those who are currently not active or active only at light intensity. Three specific guidelines on (1) moderate- and vigorous-intensity physical activity, (2) bone- and muscle-strengthening activities, and (3) sedentary behaviour were formulated separately for adults and children. Conclusions There is an unabated need for evidence-based physical activity guidelines that can guide public health policies. Research in which physical activity is measured both objectively (quantity) and subjectively (type and quality) is needed to provide better estimates of the type and actual amount of physical activity required for health.

Maladaptive impulsivity is a core symptom in various psychiatric disorders. However, there is only limited evidence available on whether different measures of impulsivity represent largely unrelated aspects or a unitary construct. In a cross-species translational study, thirty rats were trained in impulsive choice (delayed reward task) and impulsive action (five-choice serial reaction time task) paradigms. The correlation between those measures was assessed during baseline performance and after pharmacological manipulations with the psychostimulant amphetamine and the norepinephrine reuptake inhibitor atomoxetine. In parallel, to validate the animal data, 101 human subjects performed analogous measures of impulsive choice (delay discounting task, DDT) and impulsive action (immediate and delayed memory task, IMT/DMT). Moreover, all subjects completed the Stop Signal Task (SST, as an additional measure of impulsive action) and filled out the Barratt impulsiveness scale (BIS-11). Correlations between DDT and IMT/DMT were determined and a principal component analysis was performed on all human measures of impulsivity. In both rats and humans measures of impulsive choice and impulsive action did not correlate. In rats the within-subject pharmacological effects of amphetamine and atomoxetine did not correlate between tasks, suggesting distinct underlying neural correlates. Furthermore, in humans, principal component analysis identified three independent factors: (1) self-reported impulsivity (BIS-11); (2) impulsive action (IMT/DMT and SST); (3) impulsive choice (DDT). This is the first study directly comparing aspects of impulsivity using a cross-species translational approach. The present data reveal the non-unitary nature of impulsivity on a behavioral and pharmacological level. Collectively, this warrants a stronger focus on the relative contribution of distinct forms of impulsivity in psychopathology.

Background The aim of many physical activity interventions is to develop life-long habits of regular exercise and sports activities in leisure time. Previous studies that assessed tracking (i.e. the stability of a trait over the lifespan) of leisure time exercise behaviour across various parts of the life span have treated it as a uniform construct by summing all types of leisure time exercise activities into a single summary score for the total volume of exercise. This study provides new insight by additionally determining tracking across leisure time exercise activities in six different domains: (1) team-based versus solitary activities, (2) competitive versus non-competitive activities, and (3) externally paced versus internally paced activities. We also assessed which of the domains of exercise activities best predicted total volume of exercise at follow-up. Methods A large dataset ( N  = 43,889) from the Netherlands Twin Register (NTR) was used to analyse the tracking of exercise behaviour over time. Using this dataset, we were able to examine tracking as a function of baseline age (8 to 80 years) and tracking duration (2 to 22-year follow-up), taking into account sex differences, using generalized estimating equations. Results Two-year tracking coefficients are moderate to high for total volume of exercise across ages at baseline, ranging from .38 to .77 with a median of .57. Tracking coefficients tend to decrease as the distance to follow-up increases, down to a median of .38 for the 22-year tracking coefficients. The patterns of tracking were largely domain-independent and were largely similar for solitary, competitive, non-competitive, externally and internally paced activities. With the exception of team-based activities, tracking was seen to increase as a function of baseline age. Cross-domain tracking did not favour any specific domain of exercise activity as the best predictor for total volume of exercise behaviour and this was true at all baseline ages. Conclusion We conclude that exercise behaviour is moderately to highly stable across the life span. In particular in adulthood, where the tracking of exercise mimics that of a classical behavioural trait like personality. This stability reinforces existing evidence that exercise habits are hard to change, but at the same time suggests that successful intervention leading to the adoption of exercise habits will tend to last.

Increasing amounts of genetic data have led to the development of polygenic risk scores (PRSs) for a variety of diseases. These scores, built from the summary statistics of genome-wide association studies (GWASs), are able to stratify individuals based on their genetic risk of developing various common diseases and could potentially be used to optimize the use of screening and preventative treatments and improve personalized care for patients. Many challenges are yet to be overcome, including PRS validation, healthcare professional and patient education, and healthcare systems integration. Ethical challenges are also present in how this information is used and the current lack of diverse populations with PRSs available. In this review, we discuss the topics above and cover the nature of PRSs, visualization schemes, and how PRSs can be improved. With these tools on the horizon for multiple diseases, scientists, clinicians, health systems, regulatory bodies, and the public should discuss the uses, benefits, and potential risks of PRSs.

Many cardiocirculatory mechanisms are involved in the adaptation to orthostatic stress. While these mechanisms may be impaired in Fontan patients. However, it is yet unclear how Fontan patients, who exhibit a critical fluid balance, respond to orthostatic stress. Angiotensin converting enzyme inhibitors are often prescribed to Fontan patients, but they may negatively influence orthostatic tolerance. Therefore, we evaluated the response to orthostatic stress in pediatric Fontan patients before and after treatment with enalapril. Thirty-five Fontan patients (aged 14 years) with moderate-good systolic ventricular function without pre-existent enalapril treatment were included. Before and after a three-month enalapril treatment period, the hemodynamic response to head-up tilt test was evaluated by various parameters including cardiac index, blood pressure, cerebral blood flow, aortic stiffness and cardiac autonomous nervous activity. Thirty-four healthy subjects (aged 13 years) served as controls. Fontan patients had a decreased cerebral blood flow and increased aortic stiffness in the supine position compared to controls, while all other factors did not differ. Patients and controls showed a comparable response to head-up tilt test for most parameters. Twenty-seven patients completed the enalapril study with a mean dosage of 0.3±0.1mg/kg/day. Most parameters were unaffected by enalapril, only the percent decrease in cardiac index to tilt was higher after treatment, but the cardiac index during tilt was not lower (3.0L/min/m.sup.2 pre-enalapril versus 2.8L/min/m.sup.2 after treatment; P = 0.15). Pediatric Fontan patients adequately respond to orthostasis with maintenance of blood pressure and cerebral blood flow and sufficient autonomic response. Enalapril treatment did not alter the response.

High levels of liver enzymes GGT, ALT and AST are predictive of disease and all-cause mortality and can reflect liver injury, fatty liver and/or oxidative stress. Variation in GGT, ALT and AST levels is heritable. Moderation of the heritability of these liver enzymes by age and sex has not often been explored, and it is not clear to what extent non-additive genetic and shared environmental factors may play a role. To examine the genetic architecture of GGT, ALT and AST, plasma levels were assessed in a large sample of twins, their siblings, parents and spouses ( N  = 8,371; age range 18–90). For GGT and ALT, but not for AST, genetic structural equation modeling showed evidence for quantitative sex differences in the genetic architecture. There was no evidence for qualitative sex differences, i.e. the same genes were expressed in males and females. Both additive and non-additive genetic factors were important for GGT in females (total heritability h 2 60 %) and AST in both sexes (total h 2 43 %). The heritability of GGT in males and ALT for both sexes was due to additive effects only (GGT males 30 %; ALT males 40 %, females 22 %). Evidence emerged for shared environmental factors influencing GGT in the male offspring generation (variance explained 28 %). Thus, the same genes influence liver enzyme levels across sex and age, but their relative contribution to the variation in GGT and ALT differs in males and females and for GGT across age. Given adequate sample sizes these results suggest that genome-wide association studies may result in the detection of new susceptibility loci for liver enzyme levels when pooling results over sex and age.

Background The gut microbiota composition is known to be influenced by a myriad of factors including the host genetic profile and a number of environmental influences. Here, we focus on the environmental influence of cohabitation on the gut microbiota as well as whether these environmentally influenced microorganisms are associated with cardiometabolic and inflammatory burden. We perform this by investigating the gut microbiota composition of various groups of related individuals including cohabitating monozygotic (MZ) twin pairs, non-cohabitating MZ twin pairs and spouse pairs. Results A stronger correlation between alpha diversity was found in cohabitating MZ twins (45 pairs, r = 0.64, p  = 2.21 × 10 − 06 ) than in non-cohabitating MZ twin pairs (121 pairs, r = 0.42, p  = 1.35 × 10 − 06 ). Although the correlation of alpha diversity did not attain significance between spouse pairs (42 pairs, r = 0.23, p  = 0.15), the correlation was still higher than those in the 209 unrelated pairs (r = − 0.015, p  = 0.832). Bray-Curtis (BC) dissimilarity metrics showed cohabitating MZ twin pairs had the most similar gut microbiota communities which were more similar than the BC values of non-cohabitating MZ twins (empirical p -value = 0.0103), cohabitating spouses (empirical p-value = 0.0194), and pairs of unrelated non-cohabitating individuals (empirical p-value< 0.00001). There was also a significant difference between the BC measures from the spouse pairs and those from the unrelated non-cohabitating individuals (empirical p -value< 0.00001). Intraclass correlation coefficients were calculated between the various groups of interest and the results indicate the presence of OTUs with an environmental influence and one OTU that appeared to demonstrate genetic influences. One of the OTUs (Otu0190) was observed to have a significant association with both the cardiometabolic and inflammatory burden scores (p’s < 0.05). Conclusions Through the comparison of the microbiota contents of MZ twins with varying cohabitation status and spousal pairs, we showed evidence of environmentally influenced OTUs, one of which had a significant association with cardiometabolic and inflammatory burden scores.

Summary Microbiome influences multiple human systems, but its effects on gene methylation is unknown. We investigated the relations between gene methylation in blood and the abundance of common gut bacteria profiled by 16s rRNA gene sequencing in two population-based Dutch cohorts: LifeLines-Deep (LLD, n  = 616, discovery) and the Netherlands Twin Register (NTR, n  = 296, replication). In LLD, we also explored microbial pathways using data generated by shotgun metagenomic sequencing ( n  = 683). Methylation in both cohorts was profiled in blood samples using the Illumina 450K array. Discovery and replication analysis identified two independent CpGs associated with the genus Eggerthella : cg16586104 (P meta−analysis = 3.21 × 10 −11 ) and cg12234533 (P meta−analysis = 4.29 × 10 −10 ). We also show that microbiome can mediate the effect of environmental factors on host gene methylation. In this first association study linking epigenome to microbiome, we found and replicated the associations of two CpGs to the abundance of genus Eggerthella and identified microbiome as a mediator of the exposome. These associations are observational and suggest further investigation in larger and longitudinal set-ups.

Background The influence of genetics and environment on the association of the plasma proteome with body mass index (BMI) and changes in BMI remains underexplored, and the links to other omics in these associations remain to be investigated. We characterized protein–BMI trajectory associations in adolescents and adults and how these connect to other omics layers. Methods Our study included two cohorts of longitudinally followed twins: FinnTwin12 ( N  = 651) and the Netherlands Twin Register (NTR) ( N  = 665). Follow-up comprised 4 BMI measurements over approximately 6 (NTR: 23–27 years old) to 10 years (FinnTwin12: 12–22 years old), with omics data collected at the last BMI measurement. BMI changes were calculated in latent growth curve models. Mixed-effects models were used to quantify the associations between the abundance of 439 plasma proteins with BMI at blood sampling and changes in BMI. In FinnTwin12, the sources of genetic and environmental variation underlying the protein abundances were quantified by twin models, as were the associations of proteins with BMI and BMI changes. In NTR, we investigated the association of gene expression of genes encoding proteins identified in FinnTwin12 with BMI and changes in BMI. We linked identified proteins and their coding genes to plasma metabolites and polygenic risk scores (PRS) applying mixed-effects models and correlation networks. Results We identified 66 and 14 proteins associated with BMI at blood sampling and changes in BMI, respectively. The average heritability of these proteins was 35%. Of the 66 BMI-protein associations, 43 and 12 showed genetic and environmental correlations, respectively, including 8 proteins showing both. Similarly, we observed 7 and 3 genetic and environmental correlations between changes in BMI and protein abundance, respectively. S100A8 gene expression was associated with BMI at blood sampling, and the PRG4 and CFI genes were associated with BMI changes. Proteins showed strong connections with metabolites and PRSs, but we observed no multi-omics connections among gene expression and other omics layers. Conclusions Associations between the proteome and BMI trajectories are characterized by shared genetic, environmental, and metabolic etiologies. We observed few gene-protein pairs associated with BMI or changes in BMI at the proteome and transcriptome levels.