rs11724690 - SORBS2

Magnitude 2.2 · 4 studies on file

Reported associations

  • Genome-wide meta-analysis of insomnia prioritizes genes associated with metabolic and psychiatric pathways. - Nature genetics (2022) · Watanabe K, Jansen PR, Savage JE, Nandakumar P, Wang X, Hinds DA, Gelernter J, Levey DF, Polimanti R, Stein MB, Van Someren EJW, Smit AB, Posthuma D · PubMed 35835914

    Insomnia is a heritable, highly prevalent sleep disorder for which no sufficient treatment currently exists. Previous genome-wide association studies with up to 1.3 million subjects identified over 200 associated loci. This extreme polygenicity suggested that many more loci remain to be discovered. The current study almost doubled the sample size to 593,724 cases and 1,771,286 controls, thereby increasing statistical power, and identified 554 risk loci (including 364 novel loci). To capitalize on this large number of loci, we propose a novel strategy to prioritize genes using external biological resources and functional interactions between genes across risk loci. Of all 3,898 genes naively implicated from the risk loci, we prioritize 289 and find brain-tissue expression spec

  • Gene discovery and polygenic prediction from a 1.1-million-person GWAS of educational attainment - Unknown journal (n.d.) · Unknown authors · PubMed 30038396

    ABSTRACT: We conduct a large-scale genetic association analysis of educational attainment in a sample of ~1.1 million individuals and identify 1,271 independent genome-wide-significant SNPs. For the SNPs taken together, we found evidence of heterogeneous effects across environments. The SNPs implicate genes involved in brain-development processes and neuron-to-neuron communication. In a separate analysis of the X chromosome, we identify 10 independent genome-wide-significant SNPs and estimate a SNP heritability of ~0.3% in both men and women, consistent with partial dosage compensation. A joint (multi-phenotype) analysis of educational attainment and three related cognitive phenotypes generates polygenic scores that explain 11-13% of the variance in educational attainment and 7-10% of

  • Genome-wide association studies identify susceptibility loci for epithelial ovarian cancer in east Asian women - Unknown journal (n.d.) · Unknown authors · PubMed 30898391

    ABSTRACT: Objective. Genome-wide association studies (GWASs) for epithelial ovarian cancer (EOC) have focused largely on populations of European ancestry. We aimed to identify common germline variants associated with EOC risk in Asian women. Methods. Genotyping was performed as part of the OncoArray project. Samples with >60% Asian ancestry were included in the analysis. Genotyping was performed on 533,631 SNPs in 3238 Asian subjects diagnosed with invasive or borderline EOC and 4083 unaffected controls. After imputation, genotypes were available for 11,595,112 SNPs to identify associations. Results. At chromosome 6p25.2, SNP rs7748275 was associated with risk of serous EOC (odds ratio [OR] = 1.34, P = 8.7 × 10−9) and high-grade serous EOC (HGSOC) (OR = 1.34, P = 4.3 × 10−9). SNP rs6

  • Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals - Unknown journal (n.d.) · Unknown authors · PubMed 35361970

    ABSTRACT: We conduct a genome-wide association study (GWAS) of educational attainment (EA) in a sample of ~3 million individuals and identify 3,952 approximately uncorrelated genome-wide-significant single-nucleotide polymorphisms (SNPs). A genome-wide polygenic predictor, or polygenic index (PGI), explains 12-16% of EA variance and contributes to risk prediction for ten diseases. Direct effects (i.e., controlling for parental PGIs) explain roughly half the PGI's magnitude of association with EA and other phenotypes. The correlation between mate-pair PGIs is far too large to be consistent with phenotypic assortment alone, implying additional assortment on PGI-associated factors. In an additional GWAS of dominance deviations from the additive model, we identify no genome-wide-significan


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