https://ogma.newcastle.edu.au/vital/access/ /manager/Index ${session.getAttribute("locale")} 5 https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:38111 [BI] = 9.38 × 10^-25; p_[SSBI] = 5.23 × 10-14 for hypertension), smoking (p_[BI]= 4.4 × 10^-10; p_[SSBI] = 1.2 × 10^-4), diabetes (p_[BI] = 1.7 × 10 -8; p_[SSBI] = 2.8 × 10^-3), previous cardiovascular disease (p_[BI] = 1.0 × 10^-18; p_[SSBI] = 2.3 × 10^-7), stroke (p_[BI] = 3.9 × 10^-69; p_[SSBI] = 3.2 × 10^-24), and MRI-defined white matter hyperintensity burden (p_[BI]=1.43 × 10^-157; p_[SSBI] = 3.16 × 10^-106), but not with body mass index or cholesterol. GRS of BP traits were associated with BI and SSBI (p = 0.0022), without indication of directional pleiotropy. Conclusion: In this multiethnic GWAS meta-analysis, including over 20,000 population-based participants, we identified genetic risk loci for BI requiring validation once additional large datasets become available. High BP, including genetically determined, was the most significant modifiable, causal risk factor for BI.]]> Wed 04 Aug 2021 10:54:18 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:30822 50 loci at which common variants with minor allele frequency >5% are associated with kidney function. GWAS using more complete reference sets for imputation, such as those from The 1000 Genomes project, promise to identify novel loci that have been missed by previous efforts. To investigate the value of such a more complete variant catalog, we conducted a GWAS meta-analysis of kidney function based on the estimated glomerular filtration rate (eGFR) in 110,517 European ancestry participants using 1000 Genomes imputed data. We identified 10 novel loci with p-value < 5 × 10−8 previously missed by HapMap-based GWAS. Six of these loci (HOXD8, ARL15, PIK3R1, EYA4, ASTN2, and EPB41L3) are tagged by common SNPs unique to the 1000 Genomes reference panel. Using pathway analysis, we identified 39 significant (FDR < 0.05) genes and 127 significantly (FDR < 0.05) enriched gene sets, which were missed by our previous analyses. Among those, the 10 identified novel genes are part of pathways of kidney development, carbohydrate metabolism, cardiac septum development and glucose metabolism. These results highlight the utility of re-imputing from denser reference panels, until whole-genome sequencing becomes feasible in large samples.]]> Tue 04 Apr 2023 19:09:51 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:41379 Tue 04 Apr 2023 19:08:51 AEST ]]>