Expressive

rs1167311 - AGBL4

Magnitude 2.0 · 6 studies on file

Reported associations

  • A scalable variational inference approach for increased mixed-model association power - Nature genetics (2025) · Loya H, Kalantzis G, Cooper F, Palamara PF · 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%

  • Genome-wide association studies in a large Korean cohort identify quantitative trait loci for 36 traits and illuminate their genetic architectures - Nature communications (2025) · Jee YH, Wang Y, Jung KJ, Lee JY, Kimm H, Duan R, Price AL, Martin AR, Kraft P · PubMed 40436827

    ABSTRACT: Genome-wide association studies (GWAS) have predominantly focused on European ancestry populations, limiting biological discoveries across diverse populations. Here we report GWAS findings from 153,950 individuals across 36 quantitative traits in the Korean Cancer Prevention Study-II (KCPS2) Biobank. We discovered 301 previously unreported genetic loci in KCPS2, including an association between thyroid-stimulating hormone and CD36. Meta-analysis with the Korean Genome and Epidemiology Study, Biobank Japan, Taiwan Biobank, and UK Biobank identified 4588 loci that were not significant in any contributing GWAS. We describe differences in genetic architectures across these East Asian and European samples. We also highlight East Asian specific associations, including a known pleiotrop

  • Tissue-specific genetic variation suggests distinct molecular pathways between body shape phenotypes and colorectal cancer - Science advances (2024) · Peruchet-Noray L, Sedlmeier AM, Dimou N, Baurecht H, Fervers B, Fontvieille E, Konzok J, Tsilidis KK, Christakoudi S, Jansana A, Cordova R, Bohmann P, Stein MJ, Weber A, Bézieau S, Brenner H, Chan AT, Cheng I, Figueiredo JC, Garcia-Etxebarria K, Moreno V, Newton CC, Schmit SL, Song M, Ulrich CM, Ferrari P, Viallon V, Carreras-Torres R, Gunter MJ, Freisling H · PubMed 38640244

    ABSTRACT: It remains unknown whether adiposity subtypes are differentially associated with colorectal cancer (CRC). To move beyond single-trait anthropometric indicators, we derived four multi-trait body shape phenotypes reflecting adiposity subtypes from principal components analysis on body mass index, height, weight, waist-to-hip ratio, and waist and hip circumference. A generally obese (PC1) and a tall, centrally obese (PC3) body shape were both positively associated with CRC risk in observational analyses in 329,828 UK Biobank participants (3728 cases). In genome-wide association studies in 460,198 UK Biobank participants, we identified 3414 genetic variants across four body shapes and Mendelian randomization analyses confirmed positive associations of PC1 and PC3 with CRC risk (52,77

  • Genetic evidence that high BMI in childhood has a protective effect on intermediate diabetes traits, including measures of insulin sensitivity and secretion, after accounting for BMI in adulthood - Diabetologia (2023) · Hawkes G, Beaumont RN, Tyrrell J, Power GM, Wood A, Laakso M, Fernandes Silva L, Boehnke M, Yin X, Richardson TG, Smith GD, Frayling TM · PubMed 37280435

    ABSTRACT: Aims/hypothesis Determining how high BMI at different time points influences the risk of developing type 2 diabetes and affects insulin secretion and insulin sensitivity is critical. Methods By estimating childhood BMI in 441,761 individuals in the UK Biobank, we identified which genetic variants had larger effects on adulthood BMI than on childhood BMI, and vice versa. All genome-wide significant genetic variants were then used to separate the independent genetic effects of high childhood BMI from those of high adulthood BMI on the risk of type 2 diabetes and insulin-related phenotypes using Mendelian randomisation. We performed two-sample MR using external studies of type 2 diabetes, and oral and intravenous measures of insulin secretion and sensitivity. Results We found tha

  • Use of genetic variation to separate the effects of early and later life adiposity on disease risk: mendelian randomisation study - BMJ (Clinical research ed.) (2020) · Richardson TG, Sanderson E, Elsworth B, Tilling K, Davey Smith G · PubMed 32376654

    ABSTRACT: Abstract Objective To evaluate whether body size in early life has an independent effect on risk of disease in later life or whether its influence is mediated by body size in adulthood. Design Two sample univariable and multivariable mendelian randomisation. Setting The UK Biobank prospective cohort study and four large scale genome-wide association studies (GWAS) consortiums. Participants 453 169 participants enrolled in UK Biobank and a combined total of more than 700 000 people from different GWAS consortiums. Exposures Measured body mass index during adulthood (mean age 56.5) and self-reported perceived body size at age 10. Main outcome measures Coronary artery disease, type 2 diabetes, breast cancer, and prostate cancer. Results Having a larger genetically predicted body

  • 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

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