Problematic gaming behaviour and health-related outcomes: a systematic review and meta-analysis

This systematic review and meta-analysis aimed to investigate the interplay between problematic gaming behaviour and health-related outcomes at different developmental stages. A total of 50 empirical studies met the specified inclusion criteria, and a meta-analysis using correlation coefficients was used for the studies that reported adverse health implications regarding the impact of problematic gaming behaviour on depression, anxiety, obsessive–compulsive disorder and somatisation. Overall, the results suggested that problematic gaming behaviour is significantly associated with a wide range of detrimental health-related outcomes. Finally, the limitations of this review alongside its implications were discussed and considered for future research

A family history of type 2 diabetes increases risk factors associated with overfeeding

Aims/hypothesis: The purpose of the study was to test prospectively whether healthy individuals with a family history of type 2 diabetes are more susceptible to adverse metabolic effects during experimental overfeeding. Methods: We studied the effects of 3 and 28 days of overfeeding by 5,200 kJ/day in 41 sedentary individuals with and without a family history of type 2 diabetes (FH+ and FH− respectively). Measures included body weight, fat distribution (computed tomography) and insulin sensitivity (hyperinsulinaemic–euglycaemic clamp). Results: Body weight was increased compared with baseline at 3 and 28 days in both groups (p<0.001), FH+ individuals having gained significantly more weight than FH− individuals at 28 days (3.4±1.6 vs 2.2±1.4 kg, p<0.05). Fasting serum insulin and C-peptide were increased at 3 and 28 days compared with baseline in both groups, with greater increases in FH+ than in FH− for insulin at +3 and +28 days (p<0.01) and C-peptide at +28 days (p<0.05). Fasting glucose also increased at both time points, but without a significant group effect (p=0.1). Peripheral insulin sensitivity decreased in the whole cohort at +28 days (54.8±17.7 to 50.3±15.6 μmol min−1 [kg fat-free mass]−1, p=0.03), and insulin sensitivity by HOMA-IR decreased at both time points (p<0.001) and to a greater extent in FH+ than in FH− (p=0.008). Liver fat, subcutaneous and visceral fat increased similarly in the two groups (p<0.001). Conclusions: Overfeeding induced weight and fat gain, insulin resistance and hepatic fat deposition in healthy individuals. However, individuals with a family history of type 2 diabetes gained more weight and greater insulin resistance by HOMA-IR. The results of this study suggest that healthy individuals with a family history of type 2 diabetes are predisposed to adverse effects of overfeeding.D. Samocha-Bonet, L.V. Campbell, A. Viardot, J. Freund, C.S. Tam, J.R. Greenfield and L.K. Heilbron

A saturated map of common genetic variants associated with human height

Common single-nucleotide polymorphisms (SNPs) are predicted to collectively explain 40-50% of phenotypic variation in human height, but identifying the specific variants and associated regions requires huge sample sizes(1). Here, using data from a genome-wide association study of 5.4 million individuals of diverse ancestries, we show that 12,111 independent SNPs that are significantly associated with height account for nearly all of the common SNP-based heritability. These SNPs are clustered within 7,209 non-overlapping genomic segments with a mean size of around 90 kb, covering about 21% of the genome. The density of independent associations varies across the genome and the regions of increased density are enriched for biologically relevant genes. In out-of-sample estimation and prediction, the 12,111 SNPs (or all SNPs in the HapMap 3 panel(2)) account for 40% (45%) of phenotypic variance in populations of European ancestry but only around 10-20% (14-24%) in populations of other ancestries. Effect sizes, associated regions and gene prioritization are similar across ancestries, indicating that reduced prediction accuracy is likely to be explained by linkage disequilibrium and differences in allele frequency within associated regions. Finally, we show that the relevant biological pathways are detectable with smaller sample sizes than are needed to implicate causal genes and variants. Overall, this study provides a comprehensive map of specific genomic regions that contain the vast majority of common height-associated variants. Although this map is saturated for populations of European ancestry, further research is needed to achieve equivalent saturation in other ancestries.A large genome-wide association study of more than 5 million individuals reveals that 12,111 single-nucleotide polymorphisms account for nearly all the heritability of height attributable to common genetic variants

A saturated map of common genetic variants associated with human height.

Common single-nucleotide polymorphisms (SNPs) are predicted to collectively explain 40-50% of phenotypic variation in human height, but identifying the specific variants and associated regions requires huge sample sizes1. Here, using data from a genome-wide association study of 5.4 million individuals of diverse ancestries, we show that 12,111 independent SNPs that are significantly associated with height account for nearly all of the common SNP-based heritability. These SNPs are clustered within 7,209 non-overlapping genomic segments with a mean size of around 90 kb, covering about 21% of the genome. The density of independent associations varies across the genome and the regions of increased density are enriched for biologically relevant genes. In out-of-sample estimation and prediction, the 12,111 SNPs (or all SNPs in the HapMap 3 panel2) account for 40% (45%) of phenotypic variance in populations of European ancestry but only around 10-20% (14-24%) in populations of other ancestries. Effect sizes, associated regions and gene prioritization are similar across ancestries, indicating that reduced prediction accuracy is likely to be explained by linkage disequilibrium and differences in allele frequency within associated regions. Finally, we show that the relevant biological pathways are detectable with smaller sample sizes than are needed to implicate causal genes and variants. Overall, this study provides a comprehensive map of specific genomic regions that contain the vast majority of common height-associated variants. Although this map is saturated for populations of European ancestry, further research is needed to achieve equivalent saturation in other ancestries

Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis.

BACKGROUND: Genetic variants within nearly 1000 loci are known to contribute to modulation of blood lipid levels. However, the biological pathways underlying these associations are frequently unknown, limiting understanding of these findings and hindering downstream translational efforts such as drug target discovery. RESULTS: To expand our understanding of the underlying biological pathways and mechanisms controlling blood lipid levels, we leverage a large multi-ancestry meta-analysis (N = 1,654,960) of blood lipids to prioritize putative causal genes for 2286 lipid associations using six gene prediction approaches. Using phenome-wide association (PheWAS) scans, we identify relationships of genetically predicted lipid levels to other diseases and conditions. We confirm known pleiotropic associations with cardiovascular phenotypes and determine novel associations, notably with cholelithiasis risk. We perform sex-stratified GWAS meta-analysis of lipid levels and show that 3-5% of autosomal lipid-associated loci demonstrate sex-biased effects. Finally, we report 21 novel lipid loci identified on the X chromosome. Many of the sex-biased autosomal and X chromosome lipid loci show pleiotropic associations with sex hormones, emphasizing the role of hormone regulation in lipid metabolism. CONCLUSIONS: Taken together, our findings provide insights into the biological mechanisms through which associated variants lead to altered lipid levels and potentially cardiovascular disease risk