Expressive

rs111677020 - CNTN5

Magnitude 4.5 · 2 studies on file

Reported associations

  • Gene-by-environment interactions modulate the infant gut microbiota in asthma and atopy. - The Journal of allergy and clinical immunology (2025) · Stickley SA, Fang ZY, Ambalavanan A, Zhang Y, Zacharias AM, Petersen C, Dai D, Azad MB, Brook JR, Mandhane PJ, Simons E, Moraes TJ, Surette MG, Turvey SE, Subbarao P, Duan Q · PubMed 40187613

    Gut microbiota has been associated with health and susceptibility to childhood diseases, including asthma and allergies. However, the genomic factors contributing to interindividual variations in gut microbiota remain poorly understood. We sought to integrate host genomics with early-life exposures to investigate main and interaction effects on gut microbiota during the first year of life. In addition, we identified gut microbes associated with childhood respiratory (asthma, wheeze) and atopic (atopic dermatitis, food/inhalant sensitization) outcomes. We leveraged microbiome data from infant stool at ages 3 months (N = 779) and 1 year (N = 770) from the CHILD Cohort Study. We identified microbial taxa and co-occurring network clusters associated with asthma and atopy by age 5 years. Genome

  • 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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