Expressive

rs12449061 - WWOX

Magnitude 2.0 · 4 studies on file

Reported associations

  • Multi-trait and multi-ancestry genetic analysis of comorbid lung diseases and traits improves genetic discovery and polygenic risk prediction. - Nature genetics (2026) · He Y, Lu W, Jee YH, Shih MY, Wang Y, Tsuo K, Qian DC, Diao JA, Huang H, Patel CJ, Byun J, Pasaniuc B, Atkinson EG, Amos CI, Feng YA, Moll M, Cho MH, Martin AR · PubMed 41565855

    While respiratory diseases such as chronic obstructive pulmonary disease (COPD) and asthma share many risk factors, most studies investigate them in isolation and in predominantly European-ancestry populations. Here, we conducted the most powerful multi-trait and multi-ancestry genetic analysis of respiratory diseases and auxiliary traits to date, identifying 25 new loci associated with lung function in individuals of East Asian ancestry. Using these results, we developed PRSxtra (cross-trait and cross-ancestry), a multi-trait and multi-ancestry polygenic risk score (PRS) approach that leverages shared components of heritable risk via pleiotropic effects. PRSxtra significantly improved the prediction of asthma, COPD and lung cancer compared to trait- and ancestry-matched PRSs in a multi-an

  • 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%

  • Principled distillation of UK Biobank phenotype data reveals underlying structure in human variation - Unknown journal (n.d.) · Unknown authors · PubMed 38965376

    ABSTRACT: Data within biobanks capture broad yet detailed indices of human variation, but biobank-wide insights can be difficult to extract due to complexity and scale. Here, using large-scale factor analysis, we distill hundreds of variables (diagnoses, assessments and survey items) into 35 latent constructs, using data from unrelated individuals with predominantly estimated European genetic ancestry in UK Biobank. These factors recapitulate known disease classifications, disentangle elements of socioeconomic status, highlight the relevance of psychiatric constructs to health and improve measurement of pro-health behaviours. We go on to demonstrate the power of this approach to clarify genetic signal, enhance discovery and identify associations between underlying phenotypic structure and

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