Expressive

rs11643654 - SALL1

Magnitude 2.2 · 2 studies on file

Reported associations

  • Genome-wide association study identifies 74 loci associated with educational attainment - Unknown journal (n.d.) · Unknown authors · PubMed 27225129

    ABSTRACT: Summary Educational attainment (EA) is strongly influenced by social and other environmental factors, but genetic factors are also estimated to account for at least 20% of the variation across individuals. We report the results of a genome-wide association study (GWAS) for EA that extends our earlier discovery sample of 101,069 individuals to 293,723 individuals, and a replication in an independent sample of 111,349 individuals from the UK Biobank. We now identify 74 genome-wide significant loci associated with number of years of schooling completed. Single-nucleotide polymorphisms (SNPs) associated with educational attainment are disproportionately found in genomic regions regulating gene expression in the fetal brain. Candidate genes are preferentially expressed in neural tissu

  • Large-scale machine-learning-based phenotyping significantly improves genomic discovery for optic nerve head morphology - Unknown journal (n.d.) · Unknown authors · PubMed 34077760

    ABSTRACT: Summary Genome-wide association studies (GWASs) require accurate cohort phenotyping, but expert labeling can be costly, time intensive, and variable. Here, we develop a machine learning (ML) model to predict glaucomatous optic nerve head features from color fundus photographs. We used the model to predict vertical cup-to-disc ratio (VCDR), a diagnostic parameter and cardinal endophenotype for glaucoma, in 65,680 Europeans in the UK Biobank (UKB). A GWAS of ML-based VCDR identified 299 independent genome-wide significant (GWS; p ≤ 5 × 10−8) hits in 156 loci. The ML-based GWAS replicated 62 of 65 GWS loci from a recent VCDR GWAS in the UKB for which two ophthalmologists manually labeled images for 67,040 Europeans. The ML-based GWAS also identified 93 novel loci, significantl

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