https://nova.newcastle.edu.au/vital/access/ /manager/Index ${session.getAttribute("locale")} 5 https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:47731 g| ~ 0.25 to 0.50) with a range of risky behaviors. Bioinformatics analyses imply that genes near SNPs associated with general risk tolerance are highly expressed in brain tissues and point to a role for glutamatergic and GABAergic neurotransmission. We found no evidence of enrichment for genes previously hypothesized to relate to risk tolerance.]]> Wed 25 Jan 2023 14:39:42 AEDT ]]> https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:41782  0.05). Our findings suggest that the inverse association of birthweight with hypertension risk from observational studies was not supported by large Mendelian randomization analyses.]]> Wed 22 Mar 2023 14:30:25 AEDT ]]> https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:53295 Tue 21 Nov 2023 11:54:41 AEDT ]]> https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:48483 LCT-13910 C/T, rs4988235) associated with dairy intake as an instrumental variable (IV). The causal effects of dairy intake on body composition and cardiometabolic traits (lipids, glycemic traits, and inflammatory factors) were quantified by IV estimators among 182041 participants from 18 studies. Results: Each 1 serving/day higher dairy intake was associated with higher lean mass [β (SE) = 0.117 kg (0.035); P = 0.001], higher hemoglobin A1c [0.009% (0.002); P < 0.001], lower LDL [-0.014 mmol/L (0.006); P = 0.013], total cholesterol (TC) [-0.012 mmol/L (0.005); P = 0.023], and non-HDL [-0.012 mmol/L (0.005); P = 0.028]. The LCT-13910 C/T CT + TT genotype was associated with 0.214 more dairy servings/day (SE = 0.047; P < 0.001), 0.284 cm higher waist circumference (SE = 0.118; P = 0.017), 0.112 kg higher lean mass (SE = 0.027; P = 3.8 x 10-5), 0.032 mmol/L lower LDL (SE = 0.009; P = 0.001), and 0.032 mmol/L lower TC (SE = 0.010; P = 0.001). Genetically higher dairy intake was associated with increased lean mass [0.523 kg per serving/day (0.170); P = 0.002] after correction for multiple testing (0.05/18). However, we find that genetically higher dairy intake was not associated with lipids and glycemic traits. Conclusions: The present study provides evidence to support a potential causal effect of higher dairy intake on increased lean mass among adults. Our findings suggest that the observational associations of dairy intake with lipids and glycemic traits may be the result of confounding.]]> Mon 20 Mar 2023 10:41:47 AEDT ]]> https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:50952 overall) detected no genome-wide significant hits and showed low single nucleotide polymorphism (SNP) heritability (1.66%, 95% CI = 0.84-2.48%, n_effective = 132,260). Stratified analyses indicated rater-based heterogeneity in genetic effects, with self-reported internalizing symptoms showing the highest heritability (5.63%, 95% CI = 3.08%-8.18%). The contribution of additive genetic effects on internalizing symptoms appeared to be stable over age, with overlapping estimates of SNP heritability from early childhood to adolescence. Genetic correlations were observed with adult anxiety, depression, and the well-being spectrum (|r_g| > 0.70), as well as with insomnia, loneliness, attention-deficit/hyperactivity disorder, autism, and childhood aggression (range |r_g| = 0.42-0.60), whereas there were no robust associations with schizophrenia, bipolar disorder, obsessive-compulsive disorder, or anorexia nervosa. Conclusion: Genetic correlations indicate that childhood and adolescent internalizing symptoms share substantial genetic vulnerabilities with adult internalizing disorders and other childhood psychiatric traits, which could partially explain both the persistence of internalizing symptoms over time and the high comorbidity among childhood psychiatric traits. Reducing phenotypic heterogeneity in childhood samples will be key in paving the way to future GWAS success.]]> Mon 14 Aug 2023 14:36:09 AEST ]]> https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:50392 0.49), but not with autism or the less common adult disorders (schizophrenia, bipolar disorder, or eating disorders) (rG < 0.01). Importantly, the total psychiatric problem score also showed at least a moderate genetic correlation with intelligence, educational attainment, wellbeing, smoking, and body fat (rG > 0.29). The results suggest that many common genetic variants are associated with childhood psychiatric symptoms and related phenotypes in general instead of with specific symptoms. Further research is needed to establish causality and pleiotropic mechanisms between related traits.]]> Mon 13 May 2024 11:16:33 AEST ]]> https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:54727 Mon 11 Mar 2024 14:11:41 AEDT ]]> https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:55383 Fri 24 May 2024 10:35:40 AEST ]]> https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:41061 HHIP) gene and was previously associated with lung function and HHIP lung expression. We found HHIP expression was significantly different between the sexes (P=6.90x10⁻⁶), but we could not detect sex differential effects of rs7697189 on expression. Conclusions: We identified a novel genotype-by-sex interaction at a putative enhancer region upstream of the HHIP gene. Establishing the mechanism by which HHIP SNPs have different effects on lung function in males and females will be important for our understanding of lung health and diseases in both sexes.]]> Fri 22 Jul 2022 13:18:47 AEST ]]> https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:46943 METTL15). The variant was nominally associated with only the European subgroup analysis but had a consistent direction of effect in other ethnicities. We then utilized trans-ancestral Bayesian analysis to narrow down the location of the probable causal variant at each genome-wide significant signal. Of all the fine-mapped loci, we were able to narrow down the causative variant at four known loci to fewer than 10 single nucleotide polymorphisms (SNPs) (FAIM2, GNPDA2, MC4R and SEC16B loci). In conclusion, an ethnically diverse setting has enabled us to both identify an additional pediatric obesity locus and further fine-map existing loci.]]> Fri 09 Dec 2022 14:01:32 AEDT ]]>