Expressive

rs10746387 - ZC3H11B - SLC30A10

Magnitude 2.2 · 2 studies on file

Reported associations

  • Identification of fifty-seven novel loci for abdominal wall hernia development and their biological and clinical implications: results from the UK Biobank. - Hernia : the journal of hernias and abdominal wall surgery (2022) · Wei J, Attaar M, Shi Z, Na R, Resurreccion WK, Haggerty SP, Zheng SL, Helfand BT, Ujiki MB, Xu J · PubMed 34382107

    Familial aggregation is known for both hernia development and recurrence. To date, only one genome-wide association study (GWAS) limited to inguinal hernia has been reported that identified four risk-associated loci. We aim to investigate polygenic architecture of abdominal wall hernia development and recurrence. A GWAS was performed in 367,394 subjects from the UK Biobank to investigate the polygenic architecture of abdominal wall hernia subtypes (inguinal, femoral, umbilical, ventral) and identify specific single nucleotide polymorphisms (SNPs) that are associated with their risk. Expression quantitative trait loci (eQTL) analysis was performed to identify genes whose expression levels are associated with these SNPs. A genetic risk score (GRS) was used to assess the cumulative effect of

  • A saturated map of common genetic variants associated with human height - Unknown journal (n.d.) · Unknown authors · PubMed 36224396

    ABSTRACT: Common single-nucleotide polymorphisms (SNPs) are predicted to collectively explain 40-50% of phenotypic variation in human height, but identifying the specific variants and associated regions requires huge sample sizes. Here, using data from a genome-wide association study of 5.4 million individuals of diverse ancestries, we show that 12,111 independent SNPs that are significantly associated with height account for nearly all of the common SNP-based heritability. These SNPs are clustered within 7,209 non-overlapping genomic segments with a mean size of around 90 kb, covering about 21% of the genome. The density of independent associations varies across the genome and the regions of increased density are enriched for biologically relevant genes. In out-of-sample estimation

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