Expressive

rs12455952 - HMGN1P31 - CDH20

Magnitude 2.2 · 2 studies on file

Reported associations

  • Multitrait genome association analysis identifies new susceptibility genes for human anthropometric variation in the GCAT cohort - Unknown journal (n.d.) · Unknown authors · PubMed 30166351

    ABSTRACT: Background Heritability estimates have revealed an important contribution of SNP variants for most common traits; however, SNP analysis by single-trait genome-wide association studies (GWAS) has failed to uncover their impact. In this study, we applied a multitrait GWAS approach to discover additional factor of the missing heritability of human anthropometric variation. Methods We analysed 205 traits, including diseases identified at baseline in the GCAT cohort (Genomes For Life- Cohort study of the Genomes of Catalonia) (n=4988), a Mediterranean adult population-based cohort study from the south of Europe. We estimated SNP heritability contribution and single-trait GWAS for all traits from 15 million SNP variants. Then, we applied a multitrait-related approach to study genome-

  • Genome-wide genetic analyses highlight mitogen-activated protein kinase (MAPK) signaling in the pathogenesis of endometriosis - Unknown journal (n.d.) · Unknown authors · PubMed 28333195

    ABSTRACT: Abstract STUDY QUESTION Do genome-wide association study (GWAS) data for endometriosis provide insight into novel biological pathways associated with its pathogenesis? SUMMARY ANSWER GWAS analysis uncovered multiple pathways that are statistically enriched for genetic association signals, analysis of Stage A disease highlighted a novel variant in MAP3K4, while top pathways significantly associated with all endometriosis and Stage A disease included several mitogen-activated protein kinase (MAPK)-related pathways. WHAT IS KNOWN ALREADY Endometriosis is a complex disease with an estimated heritability of 50%. To date, GWAS revealed 10 genomic regions associated with endometriosis, explaining <4% of heritability, while half of the heritability is estimated to be due to common risk v

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