The 2017 Dutch Physical Activity Guidelines Weggemans, Rianne M; Backx, Frank J G; Borghouts, Lars ...
The international journal of behavioral nutrition and physical activity,
06/2018, Letnik:
15, Številka:
1
Journal Article
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The objective of this study was to derive evidence-based physical activity guidelines for the general Dutch population.
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.
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.
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.
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.
Although common sense suggests that environmental influences increasingly account for individual differences in behavior as experiences accumulate during the course of life, this hypothesis has not ...previously been tested, in part because of the large sample sizes needed for an adequately powered analysis. Here we show for general cognitive ability that, to the contrary, genetic influence increases with age. The heritability of general cognitive ability increases significantly and linearly from 41% in childhood (9 years) to 55% in adolescence (12 years) and to 66% in young adulthood (17 years) in a sample of 11 000 pairs of twins from four countries, a larger sample than all previous studies combined. In addition to its far-reaching implications for neuroscience and molecular genetics, this finding suggests new ways of thinking about the interface between nature and nurture during the school years. Why, despite life's 'slings and arrows of outrageous fortune', do genetically driven differences increasingly account for differences in general cognitive ability? We suggest that the answer lies with genotype-environment correlation: as children grow up, they increasingly select, modify and even create their own experiences in part based on their genetic propensities.
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.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Background and Aims
A strong correlation exists between smoking and the use of alcohol and cannabis. This paper uses polygenic risk scores to explore the possibility of overlapping genetic factors. ...Those scores reflect a combined effect of selected risk alleles for smoking.
Methods
Summary‐level P‐values were available for smoking initiation, age at onset of smoking, cigarettes per day and smoking cessation from the Tobacco and Genetics Consortium (n between 22 000 and 70 000 subjects). Using different P‐value thresholds (0.1, 0.2 and 0.5) from the meta‐analysis, sets of ‘risk alleles’ were defined and used to generate a polygenic risk score (weighted sum of the alleles) for each subject in an independent target sample from the Netherlands Twin Register (n = 1583). The association between polygenic smoking scores and alcohol/cannabis use was investigated with regression analysis.
Results
The polygenic scores for ‘cigarettes per day’ were associated significantly with the number of glasses alcohol per week (P = 0.005, R2 = 0.4–0.5%) and cannabis initiation (P = 0.004, R2 = 0.6–0.9%). The polygenic scores for ‘age at onset of smoking’ were associated significantly with ‘age at regular drinking’ (P = 0.001, R2 = 1.1–1.5%), while the scores for ‘smoking initiation’ and ‘smoking cessation’ did not significantly predict alcohol or cannabis use.
Conclusions
Smoking, alcohol and cannabis use are influenced by aggregated genetic risk factors shared between these substances. The many common genetic variants each have a very small individual effect size.
Twin studies have estimated the relative contribution of genes and the environment to variance in exercise behavior and it is known that parental education positively affects exercise levels. This ...study investigates the role of parental education as a potential modifier of variance in exercise behavior from age 7 to 18 years. The study is based on large datasets from the Netherlands Twin Register (NTR: N = 24 874 twins; surveys around the ages of 7, 10, 12, 14, 16 and 18 years) and two Finnish twin cohorts (FinnTwin12: N = 4399; 12, 14 and 17 years; FinnTwin16: N = 4648; 16, 17 and 18 years). Regular participation in moderate‐to‐vigorous exercise activities during leisure time was assessed by survey. Parental education was dichotomized (“both parents with a low education” vs “at least one parent with a high education”). The mean in exercise behavior tended to be higher and the variance tended to be lower in children of high educated parents. Evidence for gene‐by‐environment interaction was weak. To develop successful interventions that specifically target children of low educated parents, the mechanisms causing the mean and variance differences between the two groups should be better understood.
Objective:
Genome-wide association studies (GWASs) of the Alcohol Use Disorders Identification Test (AUDIT), a 10-item screen for alcohol use disorder (AUD), have elucidated novel loci for alcohol ...consumption and misuse. However, these studies also revealed that GWASs can be influenced by numerous biases (e.g., measurement error, selection bias), which may have led to inconsistent genetic correlations between alcohol involvement and AUD, as well as paradoxically negative genetic correlations between alcohol involvement and psychiatric disorders and/or medical conditions. The authors used genomic structural equation modeling to elucidate the genetics of alcohol consumption and problematic consequences of alcohol use as measured by AUDIT.
Methods:
To explore these unexpected differences in genetic correlations, the authors conducted the first item-level and the largest GWAS of AUDIT items (N=160,824) and applied a multivariate framework to mitigate previous biases.
Results:
The authors identified novel patterns of similarity (and dissimilarity) among the AUDIT items and found evidence of a correlated two-factor structure at the genetic level (“consumption” and “problems,” rg=0.80). Moreover, by applying empirically derived weights to each of the AUDIT items, the authors constructed an aggregate measure of alcohol consumption that was strongly associated with alcohol dependence (rg=0.67), moderately associated with several other psychiatric disorders, and no longer positively associated with health and positive socioeconomic outcomes. Lastly, by conducting polygenic analyses in three independent cohorts that differed in their ascertainment and prevalence of AUD, the authors identified novel genetic associations between alcohol consumption, alcohol misuse, and health.
Conclusions:
This work further emphasizes the value of AUDIT for both clinical and genetic studies of AUD and the importance of using multivariate methods to study genetic associations that are more closely related to AUD.
Human behavior is imperfect. This is notably clear during repetitive tasks in which sequences of errors or deviations from perfect performance result. These errors are not random, but show patterned ...fluctuations with long-range temporal correlations that are well described using power-law spectra P(f)∝1/f(β), where β is the power-law scaling exponent describing the decay in temporal correlations. The neural basis of temporal correlations in such behaviors is not known. Interestingly, long-range temporal correlations are a hallmark of amplitude fluctuations in resting-state neuronal oscillations. Here, we investigated whether the temporal dynamics in brain and behavior are related. Thirty-nine subjects' eyes-open rest EEG was measured. Next, subjects reproduced without feedback a 1 s interval by tapping with their right index finger. In line with previous reports, we found evidence for the presence of long-range temporal correlations both in the amplitude modulation of resting-state oscillations in multiple frequency bands and in the timing-error sequences. Frequency scaling exponents of finger tapping and amplitude modulation of oscillations exhibited large individual differences. Neuronal dynamics of resting-state alpha-band oscillations (9-13 Hz) recorded at precentral sites strongly predicted scaling exponents of tapping behavior. The results suggest that individual variation in resting-state brain dynamics offer a neural explanation for individual variation in the error dynamics of human behavior.
Intelligence in childhood, as measured by psychometric cognitive tests, is a strong predictor of many important life outcomes, including educational attainment, income, health and lifespan. Results ...from twin, family and adoption studies are consistent with general intelligence being highly heritable and genetically stable throughout the life course. No robustly associated genetic loci or variants for childhood intelligence have been reported. Here, we report the first genome-wide association study (GWAS) on childhood intelligence (age range 6-18 years) from 17,989 individuals in six discovery and three replication samples. Although no individual single-nucleotide polymorphisms (SNPs) were detected with genome-wide significance, we show that the aggregate effects of common SNPs explain 22-46% of phenotypic variation in childhood intelligence in the three largest cohorts (P=3.9 × 10(-15), 0.014 and 0.028). FNBP1L, previously reported to be the most significantly associated gene for adult intelligence, was also significantly associated with childhood intelligence (P=0.003). Polygenic prediction analyses resulted in a significant correlation between predictor and outcome in all replication cohorts. The proportion of childhood intelligence explained by the predictor reached 1.2% (P=6 × 10(-5)), 3.5% (P=10(-3)) and 0.5% (P=6 × 10(-5)) in three independent validation cohorts. Given the sample sizes, these genetic prediction results are consistent with expectations if the genetic architecture of childhood intelligence is like that of body mass index or height. Our study provides molecular support for the heritability and polygenic nature of childhood intelligence. Larger sample sizes will be required to detect individual variants with genome-wide significance.
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