rs10493326 - DOCK7

Magnitude 2.2 · 3 studies on file

Reported associations

• Genetic Prediction of Smoking Cessation Medication Side Effects: A Genome-Wide Investigation of Abnormal Dreams on Varenicline. - Clinical pharmacology and therapeutics (2024) · Chenoweth MJ, Kim YJ, Nollen NL, Hawk LW, Mahoney MC, Lerman C, Knight J, Tyndale RF · PubMed 38369951

  Varenicline, the most efficacious smoking cessation monotherapy, produces abnormal dreams. Although genetic contributions to varenicline-associated nausea and cessation have been identified, the role of genetics in abnormal dreams is unknown. We conducted a genomewide association study (GWAS) of abnormal dreams in 188 European ancestry smokers treated with varenicline (NCT01314001). Additive genetic models examined the likelihood of experiencing abnormal dreams 2 weeks following varenicline initiation. For the top locus, we tested for selectivity to varenicline, effects on cessation, replication, and generalizability to African ancestry (AA) individuals. The top GWAS variant associated with abnormal dreams was rs901886, mapping to intron 2 of ICAM5 on chromosome 19. The prevalence of abn

• 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%

• Multi-trait GWAS for diverse ancestries: mapping the knowledge gap - Unknown journal (n.d.) · Unknown authors · PubMed 38627641

  ABSTRACT: Background Approximately 95% of samples analyzed in univariate genome-wide association studies (GWAS) are of European ancestry. This bias toward European ancestry populations in association screening also exists for other analyses and methods that are often developed and tested on European ancestry only. However, existing data in non-European populations, which are often of modest sample size, could benefit from innovative approaches as recently illustrated in the context of polygenic risk scores. Methods Here, we extend and assess the potential limitations and gains of our multi-trait GWAS pipeline, JASS (Joint Analysis of Summary Statistics), for the analysis of non-European ancestries. To this end, we conducted the joint GWAS of 19 hematological traits and glycemic traits acro

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