rs1046411 - CNNM2

Magnitude 2.0 · 2 studies on file

Reported associations

  • Leveraging Polygenic Functional Enrichment to Improve GWAS Power. - American journal of human genetics (2019) · Kichaev G, Bhatia G, Loh PR, Gazal S, Burch K, Freund MK, Schoech A, Pasaniuc B, Price AL · PubMed 30595370

    Functional genomics data has the potential to increase GWAS power by identifying SNPs that have a higher prior probability of association. Here, we introduce a method that leverages polygenic functional enrichment to incorporate coding, conserved, regulatory, and LD-related genomic annotations into association analyses. We show via simulations with real genotypes that the method, functionally informed novel discovery of risk loci (FINDOR), correctly controls the false-positive rate at null loci and attains a 9%-38% increase in the number of independent associations detected at causal loci, depending on trait polygenicity and sample size. We applied FINDOR to 27 independent complex traits and diseases from the interim UK Biobank release (average N = 130K). Averaged across traits, we attaine

  • Genome-wide meta-analyses of cross substance use disorders in diverse populations - Unknown journal (n.d.) · Unknown authors · PubMed 41057643

    ABSTRACT: Substance use disorders (SUDs, including alcohol, cannabis, opioids, and tobacco) represent significant public health challenges. The estimated heritability of SUDs is ~50% and many individuals experience multiple SUDs concurrently. Studies have demonstrated the existence of genes shared across multiple SUDs, and identifying these SUD-shared genes is critical to developing novel prevention and treatment strategies. Here, we conducted the largest cross SUD meta-analysis to date to identify SUD-shared genes using samples genetically similar to 1000 Genomes Project European (1kg-EUR-like), African (1kg-AFR-like), and American mixed (1kg-AMR-like) populations. We defined variants that had the same direction of effects across different SUDs (i.e., concordant variants) as SUD-shared. I


Auto-generated from study metadata. AI-synthesised commentary is added when this entry is regenerated through content-service's LLM mode.