Expressive

rs10110651 - KCNU1 - SMARCE1P4

Magnitude 2.2 · 3 studies on file

Reported associations

  • Japanese GWAS identifies variants for bust-size, dysmenorrhea, and menstrual fever that are eQTLs for relevant protein-coding or long non-coding RNAs - Unknown journal (n.d.) · Unknown authors · PubMed 29855537

    ABSTRACT: Traits related to primary and secondary sexual characteristics greatly impact females during puberty and day-to-day adult life. Therefore, we performed a GWAS analysis of 11,348 Japanese female volunteers and 22 gynecology-related phenotypic variables, and identified significant associations for bust-size, menstrual pain (dysmenorrhea) severity, and menstrual fever. Bust-size analysis identified significant association signals in CCDC170-ESR1 (rs6557160; P = 1.7 × 10−16) and KCNU1-ZNF703 (rs146992477; P = 6.2 × 10−9) and found that one-third of known European-ancestry associations were also present in Japanese. eQTL data points to CCDC170 and ZNF703 as those signals' functional targets. For menstrual fever, we identified a novel association in OPRM1 (rs171

  • Genome-Wide Association Study of Breast Density among Women of African Ancestry - Unknown journal (n.d.) · Unknown authors · PubMed 37345113

    ABSTRACT: Simple Summary In the US, Black women are disproportionately affected by higher breast cancer mortality rates and later-stage tumor diagnoses compared with White women. Breast density, the ratio of dense fibroglandular breast tissue to overall breast tissue area, has previously been identified as an important breast cancer risk factor. Most current genome-wide association studies for breast density have been performed in participants of European ancestry, which have yielded important insights into genetic etiology of breast density. However, little is known about the influence of common genetic variants on breast density in African ancestry populations. Our study aimed to determine genetic factors associated with breast density in African ancestry populations using a Genome-Wide

  • Detection and interpretation of shared genetic influences on 42 human traits - Unknown journal (n.d.) · Unknown authors · PubMed 27182965

    ABSTRACT: We performed a scan for genetic variants associated with multiple phenotypes by comparing large genome-wide association studies (GWAS) of 42 traits or diseases. We identified 341 loci (at an FDR of 10%) associated with multiple traits. Several loci are associated with a large number of phenotypes; for example, a nonsynonymous variant in the zinc transporter SLC39A8 influences seven of these traits, including risk of schizophrenia (rs13107325: log-odds ratio = 0.15, P = 2 × 10−12) and Parkinson's disease (log-odds ratio = −0.15, P = 1.6 × 10−7), among others. Second, we used these loci to identify traits that share multiple genetic causes in common. For example, variants that increase risk of schizophrenia also tend to increase risk of inflammatory bowel disease. Finally,

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