Expressive

rs1011728 - ALX1 - LINC02820

Magnitude 2.2 · 2 studies on file

Reported associations

  • Genome-wide association meta-analyses identified 1q43 and 2q32.2 for hip Ward's triangle areal bone mineral density - Unknown journal (n.d.) · Unknown authors · PubMed 27397699

    ABSTRACT: Aiming to identify genomic variants associated with osteoporosis, we performed a genome-wide association meta-analysis of bone mineral density (BMD) at Ward's triangle of the hip in 7,175 subjects from 6 samples. We performed in silico replications with femoral neck, trochanter, and inter-trochanter BMDs in 6,912 subjects from the Framingham heart study (FHS), and with forearm, femoral neck and lumbar spine BMDs in 32,965 subjects from the GEFOS summary results. Combining the evidence from all samples, we identified 2 novel loci for areal BMD: 1q43 (rs1414660, discovery p=1.20×10−8, FHS p=0.05 for trochanter BMD; rs9287237, discovery p=3.55×10−7, FHS p=9.20×10−3 for trochanter BMD, GEFOS p=0.02 for forearm BMD, nearest gene FMN2) and 2q32.2 (rs56346965, discovery p=7.48

  • 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%

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