Expressive

rs11751024 - HLA-DRB1 - HLA-DQA1

Magnitude 4.5 · 8 studies on file

Reported associations

  • GWAS and multi-omics integrative analysis reveal novel loci and their molecular mechanisms for circulating fatty acids. - HGG advances (2025) · Sun Y, Xu H, Ye K · PubMed 40545721

    Previous genome-wide association studies (GWAS) have identified genetic loci associated with the circulating levels of fatty acids (FAs), but the biological mechanisms of these genetic associations remain largely unexplored. Here, we conducted GWAS to identify additional genetic loci for 19 circulating FA traits in UK Biobank participants of European ancestry (n = 239,268) and five other ancestries (n = 508-4,663). We leveraged the GWAS findings to characterize genetic correlations and colocalized regions among FAs, explore sex differences, examine FA loci influenced by lipoprotein metabolism, and apply statistical fine-mapping to pinpoint putative causal variants. We integrated GWAS signals with multi-omics quantitative trait loci (QTL) to reveal intermediate molecular phenotypes mediatin

  • A genetic map of human metabolism across the allele frequency spectrum. - Nature genetics (2025) · Zoodsma M, Beuchel C, Yasmeen S, Kohleick L, Nepal A, Koprulu M, Kronenberg F, Mayr M, Williamson A, Pietzner M, Langenberg C · PubMed 41044249

    Genetic studies of human metabolism have been limited in scale and allelic breadth. Here we provide a data-driven map of the genetic regulation of circulating small molecules and lipoprotein characteristics (249 traits) measured using proton nuclear magnetic resonance spectroscopy across the allele frequency spectrum in ~450,000 individuals. Trans-ancestral meta-analyses identify 29,824 locus-metabolite associations mapping to 753 regions with effects largely consistent between men and women and large ancestral groups represented in UK Biobank. We observe and classify extreme genetic pleiotropy, identify regulators of lipid metabolism, and assign effector genes at >100 loci through rare-to-common allelic series. We propose roles for genes less established in metabolic control (for example,

  • A scalable variational inference approach for increased mixed-model association power. - Nature genetics (2025) · Loya H, Kalantzis G, Cooper F, Palamara PF · PubMed 39789286

    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% and 7.07%

  • Exploring the genetic architecture of multiple long-term conditions using a genome-wide association study in the UK Biobank population. - Scientific reports (2025) · Nair ATN, Witham M, Sayer AA, Cordell HJ, Pearson ER · PubMed 41353206

    The prevalence of multiple long-term conditions (MLTC) is increasing. It is essential to develop strategies to prevent and manage MLTC; however, the biological mechanisms underlying MLTC are not yet clearly understood. We used UK Biobank data as part of the ADMISSION research collaborative to identify genetic drivers for MLTC. We used the UK Biobank (UKBB) self-reported illness data to characterise MLTC (defined as two or more long-term conditions) using 51 common disease labels. A genome-wide association study (GWAS) was conducted for MLTC and complex MLTC (complex MLTC was defined as having three or more diseases from the 51 self-reported diseases, with these three diseases additionally belonging to different body systems), and post-GWAS analyses were conducted to explore the genomic loc

  • Genome-wide characterization of circulating metabolic biomarkers. - Nature (2024) · Karjalainen MK, Karthikeyan S, Oliver-Williams C, Sliz E, Allara E, Fung WT, Surendran P, Zhang W, Jousilahti P, Kristiansson K, Salomaa V, Goodwin M, Hughes DA, Boehnke M, Fernandes Silva L, Yin X, Mahajan A, Neville MJ, van Zuydam NR, de Mutsert R, Li-Gao R, Mook-Kanamori DO, Demirkan A, Liu J, Noordam R, Trompet S, Chen Z, Kartsonaki C, Li L, Lin K, Hagenbeek FA, Hottenga JJ, Pool R, Ikram MA, van Meurs J, Haller T, Milaneschi Y, Kähönen M, Mishra PP, Joshi PK, Macdonald-Dunlop E, Mangino M, Zierer J, Acar IE, Hoyng CB, Lechanteur YTE, Franke L, Kurilshikov A, Zhernakova A, Beekman M, van den Akker EB, Kolcic I, Polasek O, Rudan I, Gieger C, Waldenberger M, Asselbergs FW, Hayward C, Fu J, den Hollander AI, Menni C, Spector TD, Wilson JF, Lehtimäki T, Raitakari OT, Penninx BWJH, Esko T, Walters RG, Jukema JW, Sattar N, Ghanbari M, Willems van Dijk K, Karpe F, McCarthy MI, Laakso M, Järvelin MR, Timpson NJ, Perola M, Kooner JS, Chambers JC, van Duijn C, Slagboom PE, Boomsma DI, Danesh J, Ala-Korpela M, Butterworth AS, Kettunen J · PubMed 38448586

    Genome-wide association analyses using high-throughput metabolomics platforms have led to novel insights into the biology of human metabolism . This detailed knowledge of the genetic determinants of systemic metabolism has been pivotal for uncovering how genetic pathways influence biological mechanisms and complex diseases . Here we present a genome-wide association study for 233 circulating metabolic traits quantified by nuclear magnetic resonance spectroscopy in up to 136,016 participants from 33 cohorts. We identify more than 400 independent loci and assign probable causal genes at two-thirds of these using manual curation of plausible biological candidates. We highlight the importance of sample and participant characteristics that can have significant effects on genetic associations. W

  • Comprehensive genetic study of the insulin resistance marker TG:HDL-C in the UK Biobank. - Nature genetics (2024) · Oliveri A, Rebernick RJ, Kuppa A, Pant A, Chen Y, Du X, Cushing KC, Bell HN, Raut C, Prabhu P, Chen VL, Halligan BD, Speliotes EK · PubMed 38200128

    Insulin resistance (IR) is a well-established risk factor for metabolic disease. The ratio of triglycerides to high-density lipoprotein cholesterol (TG:HDL-C) is a surrogate marker of IR. We conducted a genome-wide association study of the TG:HDL-C ratio in 402,398 Europeans within the UK Biobank. We identified 369 independent SNPs, of which 114 had a false discovery rate-adjusted P value < 0.05 in other genome-wide studies of IR making them high-confidence IR-associated loci. Seventy-two of these 114 loci have not been previously associated with IR. These 114 loci cluster into five groups upon phenome-wide analysis and are enriched for candidate genes important in insulin signaling, adipocyte physiology and protein metabolism. We created a polygenic-risk score from the high-confidence

  • Decreased Circulating Very Small Low-Density Lipoprotein is Likely Causal for Age-Related Macular Degeneration. - Ophthalmology science (2024) · Farashi S, Bonelli R, Jackson VE, Ansell BRE, Guymer RH, Bahlo M · PubMed 39091897

    Abnormal changes in metabolite levels in serum or plasma have been highlighted in several studies in age-related macular degeneration (AMD), the leading cause of irreversible vision loss. Specific changes in lipid profiles are associated with an increased risk of AMD. Metabolites could thus be used to investigate AMD disease mechanisms or incorporated into AMD risk prediction models. However, whether particular metabolites causally affect the disease has yet to be established. A 3-tiered analysis of blood metabolites in the United Kingdom (UK) Biobank cohort to identify metabolites that differ in AMD patients with evidence for a putatively causal role in AMD. A total of 72 376 donors from the UK Biobank cohort including participants with AMD (N = 1353) and non-AMD controls (N = 71 02

  • Phage display sequencing reveals that genetic, environmental, and intrinsic factors influence variation of human antibody epitope repertoire. - Immunity (2023) · Andreu-Sánchez S, Bourgonje AR, Vogl T, Kurilshikov A, Leviatan S, Ruiz-Moreno AJ, Hu S, Sinha T, Vich Vila A, Klompus S, Kalka IN, de Leeuw K, Arends S, Jonkers I, Withoff S, Brouwer E, Weinberger A, Wijmenga C, Segal E, Weersma RK, Fu J, Zhernakova A · PubMed 37164013

    Phage-displayed immunoprecipitation sequencing (PhIP-seq) has enabled high-throughput profiling of human antibody repertoires. However, a comprehensive overview of environmental and genetic determinants shaping human adaptive immunity is lacking. In this study, we investigated the effects of genetic, environmental, and intrinsic factors on the variation in human antibody repertoires. We characterized serological antibody repertoires against 344,000 peptides using PhIP-seq libraries from a wide range of microbial and environmental antigens in 1,443 participants from a population cohort. We detected individual-specificity, temporal consistency, and co-housing similarities in antibody repertoires. Genetic analyses showed the involvement of the HLA, IGHV, and FUT2 gene regions in antibody-bou

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