rs11172086 - MYO1A - NEMP1

Magnitude 2.2 · 3 studies on file

Reported associations

• Shared genetics of asthma and mental health disorders: a large-scale genome-wide cross-trait analysis. - The European respiratory journal (2020) · Zhu Z, Zhu X, Liu CL, Shi H, Shen S, Yang Y, Hasegawa K, Camargo CA, Liang L · PubMed 31619474

  Epidemiological studies demonstrate an association between asthma and mental health disorders, although little is known about the shared genetics and causality of this association. Thus, we aimed to investigate shared genetics and the causal link between asthma and mental health disorders.We conducted a large-scale genome-wide cross-trait association study to investigate genetic overlap between asthma from the UK Biobank and eight mental health disorders from the Psychiatric Genomics Consortium: attention deficit hyperactivity disorder (ADHD), anxiety disorder (ANX), autism spectrum disorder, bipolar disorder, eating disorder, major depressive disorder (MDD), post-traumatic stress disorder and schizophrenia (sample size 9537-394 283).In the single-trait genome-wide association analysis,

• Diversity and scale: Genetic architecture of 2068 traits in the VA Million Veteran Program - Unknown journal (n.d.) · Unknown authors · PubMed 39024449

  ABSTRACT: INTRODUCTION: Findings from genome-wide association studies (GWASs) have provided foundational knowledge of the genetic basis of disease, facilitating precision approaches for prevention and treatment. Current GWAS results are limited by underrepresentation of individuals from diverse populations, leading to concerns with generalizability regarding our knowledge of the relationships between genes, traits, and disease. The Department of Veterans Affairs (VA) Million Veteran Program (MVP), one of the largest US-based biobanks, addresses this need; 29% of MVP comprises individuals genetically similar to African (AFR), Admixed American (AMR), and East Asian (EAS) reference populations. With over 635,000 participants and more than 44.3M genotyped variants linked with detailed phenotyp

• 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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