rs12452590 - MRC2

Magnitude 2.0 · 8 studies on file

Reported associations

  • Sex-specific genetic architecture of blood pressure. - Nature medicine (2024) · Yang ML, Xu C, Gupte T, Hoffmann TJ, Iribarren C, Zhou X, Ganesh SK · PubMed 38459180

    The genetic and genomic basis of sex differences in blood pressure (BP) traits remain unstudied at scale. Here, we conducted sex-stratified and combined-sex genome-wide association studies of BP traits using the UK Biobank resource, identifying 1,346 previously reported and 29 new BP trait-associated loci. Among associated loci, 412 were female-specific (P ≤ 5 × 10 ; P > 5 × 10 ) and 142 were male-specific (P ≤ 5 × 10 ; P > 5 × 10 ); these sex-specific loci were enriched for hormone-related transcription factors, in particular, estrogen receptor 1. Analyses of gene-by-sex interactions and sexually dimorphic effects identified four genomic regions, showing female-specific associations with diastolic BP or pulse pressure, including the chromosome 13q34-COL4A1/

  • Genetic Correlation, Shared Loci, and Causal Association Between Sex Hormone-Binding Globulin and Bone Mineral Density: Insights From a Large-Scale Genomewide Cross-Trait Analysis. - Journal of bone and mineral research : the official journal of the American Society for Bone and Mineral Research (2023) · Qu Y, Xiao C, Wu X, Zhu J, Qin C, He L, Cui H, Zhang L, Zhang W, Yang C, Yao Y, Li J, Liu Z, Zhang B, Wang W, Jiang X · PubMed 37615194

    Although the impact of sex hormones on bone metabolism is well-documented, effect of their primary modulator, sex hormone-binding globulin (SHBG), remains inconclusive. This study aims to elucidate the genetic overlap between SHBG and heel estimated bone mineral density (eBMD), a widely-accepted tool for osteoporosis management and fracture risk assessment. Using summary statistics from large-scale genomewide association studies conducted for SHBG (N = 370,125), SHBG adjusted for body mass index (SHBGa, N = 368,929), and eBMD (N = 426,824), a comprehensive genomewide cross-trait approach was performed to quantify global and local genetic correlations, identify pleiotropic loci, and infer causal associations. A significant overall inverse genetic correlation was found for SHBG a

  • Leveraging Polygenic Functional Enrichment to Improve GWAS Power. - American journal of human genetics (2019) · Kichaev G, Bhatia G, Loh PR, Gazal S, Burch K, Freund MK, Schoech A, Pasaniuc B, Price AL · PubMed 30595370

    Functional genomics data has the potential to increase GWAS power by identifying SNPs that have a higher prior probability of association. Here, we introduce a method that leverages polygenic functional enrichment to incorporate coding, conserved, regulatory, and LD-related genomic annotations into association analyses. We show via simulations with real genotypes that the method, functionally informed novel discovery of risk loci (FINDOR), correctly controls the false-positive rate at null loci and attains a 9%-38% increase in the number of independent associations detected at causal loci, depending on trait polygenicity and sample size. We applied FINDOR to 27 independent complex traits and diseases from the interim UK Biobank release (average N = 130K). Averaged across traits, we attaine

  • Combining cross-sectional and longitudinal genomic approaches to identify determinants of cognitive and physical decline - Unknown journal (n.d.) · Unknown authors · PubMed 40374629

    ABSTRACT: Large-scale genomic studies focusing on the genetic contribution to human aging have mostly relied on cross-sectional data. With the release of longitudinally curated aging phenotypes by the UK Biobank (UKBB), it is now possible to study aging over time at genome-wide scale. In this work, we evaluated the suitability of competing models of change in realistic simulation settings, performed genome-wide association scans on simulation-validated measures of age-related deweekcline, and followed up with LD-score regression and Mendelian Randomization (MR) analyses. Focusing on global cognitive and physical function, we observed marked differences between baseline function (θ) and accelerated decline (Δ). Both outcomes showed distinct heritability levels (e.g., 31.38% versus 3.15%

  • A scalable variational inference approach for increased mixed-model association power - Unknown journal (n.d.) · Unknown authors · PubMed 39789286

    ABSTRACT: The rapid growth of modern biobanks is creating new opportunities for large-scale genome-wide association studies (GWASs) and the analysis of complex traits. However, performing GWASs on millions of samples often leads to trade-offs between computational efficiency and statistical power, reducing the benefits of large-scale data collection efforts. We developed Quickdraws, a method that increases association power in quantitative and binary traits without sacrificing computational efficiency, leveraging a spike-and-slab prior on variant effects, stochastic variational inference and graphics processing unit acceleration. We applied Quickdraws to 79 quantitative and 50 binary traits in 405,088 UK Biobank samples, identifying 4.97% and 3.25% more associations than REGENIE and 22.71%

  • Multi-ancestry genome-wide association analyses improve resolution of genes and pathways influencing lung function and chronic obstructive pulmonary disease risk - Unknown journal (n.d.) · Unknown authors · PubMed 36914875

    ABSTRACT: Lung-function impairment underlies chronic obstructive pulmonary disease (COPD) and predicts mortality. In the largest multi-ancestry genome-wide association meta-analysis of lung function to date, comprising 588,452 participants, we identified 1,020 independent association signals implicating 559 genes supported by ≥2 criteria from a systematic variant-to-gene mapping framework. These genes were enriched in 29 pathways. Individual variants showed heterogeneity across ancestries, age and smoking groups, and collectively as a genetic risk score showed strong association with COPD across ancestry groups. We undertook phenome-wide association studies for selected associated variants as well as trait and pathway-specific genetic risk scores to infer possible consequences of interve

  • A Genomics England haplotype reference panel and imputation of UK Biobank - Unknown journal (n.d.) · Unknown authors · PubMed 39134668

    ABSTRACT: We built a reference panel with 342 million autosomal variants using 78,195 individuals from the Genomics England (GEL) dataset, achieving a phasing switch error rate of 0.18% for European samples and imputation quality of r2 = 0.75 for variants with minor allele frequencies as low as 2 × 10−4 in white British samples. The GEL-imputed UK Biobank genome-wide association analysis identified 70% of associations found by direct exome sequencing (P < 2.18 × 10−11), while extending testing of rare variants to the entire genome. Coding variants dominated the rare-variant genome-wide association results, implying less disruptive effects of rare non-coding variants. A Genomics England haplotype reference panel constructed using sequence data from 78,195 individuals

  • Bidirectional relationship between type 2 diabetes mellitus and coronary artery disease: Prospective cohort study and genetic analyses - Unknown journal (n.d.) · Unknown authors · PubMed 38062574

    ABSTRACT: Abstract Background: While type 2 diabetes mellitus (T2DM) is considered a putative causal risk factor for coronary artery disease (CAD), the intrinsic link underlying T2DM and CAD is not fully understood. We aimed to highlight the importance of integrated care targeting both diseases by investigating the phenotypic and genetic relationships between T2DM and CAD. Methods: We evaluated phenotypic associations using data from the United Kingdom Biobank (N = 472,050). We investigated genetic relationships by leveraging genomic data conducted in European ancestry for T2DM, with and without adjustment for body mass index (BMI) (T2DM: Ncase/Ncontrol = 74,124/824,006; T2DM adjusted for BMI [T2DMadjBMI]: Ncase/Ncontrol = 50,409/523,897) and for CAD (Ncase/Ncontrol = 181,522/984,168). We


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