https://ogma.newcastle.edu.au/vital/access/ /manager/Index ${session.getAttribute("locale")} 5 https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:48511 n = 321,223) and offspring birth weight (n = 230,069 mothers), we identified 190 independent association signals (129 of which are novel). We used structural equation modeling to decompose the contributions of direct fetal and indirect maternal genetic effects, then applied Mendelian randomization to illuminate causal pathways. For example, both indirect maternal and direct fetal genetic effects drive the observational relationship between lower birth weight and higher later blood pressure: maternal blood pressure-raising alleles reduce offspring birth weight, but only direct fetal effects of these alleles, once inherited, increase later offspring blood pressure. Using maternal birth weight-lowering genotypes to proxy for an adverse intrauterine environment provided no evidence that it causally raises offspring blood pressure, indicating that the inverse birth weight-blood pressure association is attributable to genetic effects, and not to intrauterine programming.]]> Wed 22 Mar 2023 15:25:15 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:50431 Tue 25 Jul 2023 19:01:27 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:50411 Tue 25 Jul 2023 17:30:33 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:41899 PCSK9 locus and compared findings with recent trials of pharmacological inhibitors of PCSK9. Methods: Published and individual participant level data (300,000+ participants) were combined to construct a weighted PCSK9 gene-centric score (GS). Seventeen randomized placebo controlled PCSK9 inhibitor trials were included, providing data on 79,578 participants. Results were scaled to a one mmol/L lower LDL-C concentration. Results: The PCSK9 GS (comprising 4 SNPs) associations with plasma lipid and apolipoprotein levels were consistent in direction with treatment effects. The GS odds ratio (OR) for myocardial infarction (MI) was 0.53 (95% CI 0.42; 0.68), compared to a PCSK9 inhibitor effect of 0.90 (95% CI 0.86; 0.93). For ischemic stroke ORs were 0.84 (95% CI 0.57; 1.22) for the GS, compared to 0.85 (95% CI 0.78; 0.93) in the drug trials. ORs with type 2 diabetes mellitus (T2DM) were 1.29 (95% CI 1.11; 1.50) for the GS, as compared to 1.00 (95% CI 0.96; 1.04) for incident T2DM in PCSK9 inhibitor trials. No genetic associations were observed for cancer, heart failure, atrial fibrillation, chronic obstructive pulmonary disease, or Alzheimer’s disease – outcomes for which large-scale trial data were unavailable. Conclusions: Genetic variation at the PCSK9 locus recapitulates the effects of therapeutic inhibition of PCSK9 on major blood lipid fractions and MI. While indicating an increased risk of T2DM, no other possible safety concerns were shown; although precision was moderate.]]> Tue 16 Aug 2022 08:27:58 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:48599 Tue 04 Apr 2023 19:22:25 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:42033 Drosophila RNAi-knockdowns, we observed a significant increase in the total body triglyceride levels for two genes (DNAH10 and PLXND1). We implicate novel genes in fat distribution, stressing the importance of interrogating low-frequency and protein-coding variants.]]> Mon 22 Aug 2022 10:16:20 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:53055 Fri 17 Nov 2023 11:47:02 AEDT ]]> https://ogma.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 ]]>