rs12224337 - ASS1P13 - CWF19L2

Magnitude 2.2 · 2 studies on file

Reported associations

  • Trans-ethnic association study of blood pressure determinants in over 750,000 individuals - Unknown journal (n.d.) · Unknown authors · PubMed 30578418

    ABSTRACT: In this trans-ethnic multi-omic study we reinterpret the genetic architecture of blood pressure to identify genes, tissues, phenome, and medication contexts of blood pressure homeostasis. We discovered 208 novel common blood pressure SNPs and 53 rare variants in GWASs of systolic, diastolic and pulse pressure in up to 776,078 participants from the Million Veteran Program (MVP) and collaborating studies, with analysis of the blood pressure clinical phenome in MVP. Our transcriptome-wide association study detected 4,043 blood pressure associations with genetically-predicted gene expression of 840 genes in 45 tissues, and murine renal single-cell RNA sequencing identified upregulated blood pressure genes in kidney tubule cells. Editorial summary: Analysis of blood pressure data from

  • 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.