Expressive

rs12135286 - LINC01705

Magnitude 2.2 · 2 studies on file

Reported associations

  • A cross-disorder study to identify causal relationships, shared genetic variants, and genes across 21 digestive disorders - Unknown journal (n.d.) · Unknown authors · PubMed 37965154

    ABSTRACT: Summary Digestive disorders are a significant contributor to the global burden of disease and seriously affect human quality of life. Research has already confirmed the presence of pleiotropic genetic loci among digestive disorders, and studies have explored shared genetic factors among pan-cancers, including various malignant digestive disorders. However, most cross-phenotype studies within the digestive tract system have been limited to a few traits, with no systematic coverage of common benign and malignant digestive disorders. Here, we analyzed data from the UK Biobank to investigate 21 digestive disorders, exploring the genetic correlations and causal relationships between diseases, as well as the common genetic factors and potential biological pathways driving these relatio

  • Investigating the shared genetic architecture between adiposity measures and obesity-related cancers - Unknown journal (n.d.) · Unknown authors · PubMed 40874817

    ABSTRACT: Abstract Fat distribution patterns are increasingly linked to obesity-related cancers; however, their shared genetic determinants remain unclear. To identify shared genetic architecture between adiposity measures and obesity-related cancers. Utilizing large-scale summary statistics from genome-wide association study, we conducted genome-wide cross trait analyses of nine adiposity measures [body mass index (BMI), waist-to-hip (WTH) ratio, waist-to-hip ratio adjusted for BMI, arm fat ratio, trunk fat ratio, leg fat ratio, abdominal subcutaneous adipose tissue, gluteofemoral adipose tissue, and visceral adipose tissue] in five obesity-related cancers (colorectal cancer, esophageal adenocarcinoma, breast cancer, endometrial cancer, and ovarian cancer) to characterize their shared gen

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