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Alexander Gusev, Bogdan Pasaniuc and colleagues present a strategy that integrates gene expression measurements with summary statistics from large-scale genome-wide association studies to identify genes whose cis -regulated expression is associated with complex traits. They identify 69 new genes significantly associated with obesity-related traits and illustrate how this approach can provide insights into the genetic basis of complex traits. Many genetic variants influence complex traits by modulating gene expression, thus altering the abundance of one or multiple proteins. Here we introduce a powerful strategy that integrates gene expression measurements with summary association statistics from large-scale genome-wide association studies (GWAS) to identify genes whose cis -regulated expression is associated with complex traits. We leverage expression imputation from genetic data to perform a transcriptome-wide association study (TWAS) to identify significant expression-trait associations. We applied our approaches to expression data from blood and adipose tissue measured in ∼3,000 individuals overall. We imputed gene expression into GWAS data from over 900,000 phenotype measurements to identify 69 new genes significantly associated with obesity-related traits (BMI, lipids and height). Many of these genes are associated with relevant phenotypes in the Hybrid Mouse Diversity Panel. Our results showcase the power of integrating genotype, gene expression and phenotype to gain insights into the genetic basis of complex traits.

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.

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.

We introduce two novel methods for multivariate genome-wide-association meta-analysis (GWAMA) of related traits that correct for sample overlap. A broad range of simulation scenarios supports the added value of our multivariate methods relative to univariate GWAMA. We applied the novel methods to life satisfaction, positive affect, neuroticism, and depressive symptoms, collectively referred to as the well-being spectrum ( N obs  = 2,370,390), and found 304 significant independent signals. Our multivariate approaches resulted in a 26% increase in the number of independent signals relative to the four univariate GWAMAs and in an ~57% increase in the predictive power of polygenic risk scores. Supporting transcriptome- and methylome-wide analyses (TWAS and MWAS, respectively) uncovered an additional 17 and 75 independent loci, respectively. Bioinformatic analyses, based on gene expression in brain tissues and cells, showed that genes differentially expressed in the subiculum and GABAergic interneurons are enriched in their effect on the well-being spectrum. New methods for multivariate genome-wide-association meta-analysis (GWAMA) applied to four well-being spectrum traits identifies 304 association loci, representing a 26% increase in the number of signals, as compared with four univariate analyses.

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.

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.

Introduction Early motor development has been found to be a predictor of exercise behavior in children and adolescents, but whether this reflects a causal effect or confounding by genetic or shared environmental factors remains to be established. Methods For 20,911 complete twin pairs from the Netherlands Twin Register a motor development score was obtained from maternal reports on the timing of five motor milestones. During a 12-year follow-up, subsamples of the mothers reported on the twins’ ability to perform seven gross motor skills ability ( N  = 17,189 pairs), and weekly minutes of total metabolic equivalents of task (MET) spent on sports and exercise activities at age 7 ( N  = 3632 pairs), age 10 ( N  = 3735 pairs), age 12 ( N  = 7043 pairs), and age 14 ( N  = 3990 pairs). Multivariate phenotypic and genetic regression analyses were used to establish the predictive strength of the two motor development traits for future exercise behavior, the contribution of genetic and shared environmental factors to the variance in all traits, and the contribution of familial confounding to the phenotypic prediction. Results Significant heritability (h 2 ) and shared environmental (c 2 ) effects were found for early motor development in boys and girls (h 2  = 43-65%; c 2  = 16-48%). For exercise behavior, genetic influences increased with age (boys: h 2 age7  = 22% to h 2 age14  = 51%; girls: h 2 age7  = 3% to h 2 age14  = 18%) paired to a parallel decrease in the influence of the shared environment (boys: c 2 age7  = 68% to c 2 age14  = 19%; girls: c 2 age7  = 80% to c 2 age14  = 48%). Early motor development explained 4.3% ( p  < 0.001) of the variance in future exercise behavior in boys but only 1.9% ( p  < 0.001) in girls. If the effect in boys was due to a causal effect of motor development on exercise behavior, all of the factors influencing motor development would, through the causal chain, also influence future exercise behavior. Instead, only the genetic parts of the regression of exercise behavior on motor development were significant. Shared and unique environmental parts of the regression were largely non-significant, which is at odds with the causal hypothesis. Conclusion No support was found for a direct causal effect in the association between rapid early motor development on future exercise behavior. In boys, early motor development appears to be an expression of the same genetic factors that underlie the heritability of childhood and early adolescent exercise behavior.

The Netherlands Twin Register (NTR) is a national register in which twins, multiples and their parents, siblings, spouses and other family members participate. Here we describe the NTR resources that were created from more than 30 years of data collections; the development and maintenance of the newly developed database systems, and the possibilities these resources create for future research. Since the early 1980s, the NTR has enrolled around 120,000 twins and a roughly equal number of their relatives. The majority of twin families have participated in survey studies, and subsamples took part in biomaterial collection (e.g., DNA) and dedicated projects, for example, for neuropsychological, biomarker and behavioral traits. The recruitment into the NTR is all inclusive without any restrictions on enrollment. These resources — the longitudinal phenotyping, the extended pedigree structures and the multigeneration genotyping — allow for future twin-family research that will contribute to gene discovery, causality modeling, and studies of genetic and cultural inheritance.

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.