Expressive

rs116475746 - FOLR1P1 - FOLR1

Magnitude 2.2 · 3 studies on file

Reported associations

  • Efficient candidate drug target discovery through proteogenomics in a Scottish cohort - Unknown journal (n.d.) · Unknown authors · PubMed 40883583

    ABSTRACT: Understanding the genomic basis of human proteomic variability provides powerful tools to probe potential causal relationships of proteins and disease risk, and thus to prioritise candidate drug targets. Here, we investigated 6432 plasma proteins (1533 previously unstudied in large-scale proteomic GWAS) using the SomaLogic (v4.1) aptamer-based technology in a Scottish population from the Viking Genes study. A total of 505 significant independent protein quantitative trait loci (pQTL) were found for 455 proteins in blood plasma: 382 cis- (P < 5×10-8) and 123 trans- (P < 6.6×10-12). Of these, 31 cis-pQTL were for proteins with no previous GWAS. We leveraged these pQTL to perform causal inference using bidirectional Mendelian randomisation and colocalisation against comple

  • 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%

  • Deciphering tissue-specific protein regulation for insights into cardiometabolic disease - Unknown journal (n.d.) · Unknown authors · PubMed 41456820

    ABSTRACT: Understanding tissue-specific mechanisms of protein regulation gives crucial insights into cardiometabolic disease and informs drug discovery. Most proteomic studies have primarily concentrated on plasma, overlooking tissue-specific effects. Utilizing Olink technology, we assessed relative protein levels across plasma and tissue (aortic wall, mammary artery, liver, and skeletal muscle) from the STARNET cohort: 284 individuals with a high prevalence of coronary artery disease (CAD). We identified 608 cis protein quantitative trait loci (pQTLs), primarily in plasma, reflecting greater protein variability. Of 190 proteins with cis-pQTLs in non-plasma tissues, 50% also had plasma pQTLs, validating Olink technology in these tissues while reinforcing the relevance of plasma data for un

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