rs115264061 - CARMIL1 - SCGN

Magnitude 2.2 · 2 studies on file

Reported associations

• Combining cross-sectional and longitudinal genomic approaches to identify determinants of cognitive and physical decline - Unknown journal (n.d.) · Unknown authors · PubMed 40374629

  ABSTRACT: Large-scale genomic studies focusing on the genetic contribution to human aging have mostly relied on cross-sectional data. With the release of longitudinally curated aging phenotypes by the UK Biobank (UKBB), it is now possible to study aging over time at genome-wide scale. In this work, we evaluated the suitability of competing models of change in realistic simulation settings, performed genome-wide association scans on simulation-validated measures of age-related deweekcline, and followed up with LD-score regression and Mendelian Randomization (MR) analyses. Focusing on global cognitive and physical function, we observed marked differences between baseline function (θ) and accelerated decline (Δ). Both outcomes showed distinct heritability levels (e.g., 31.38% versus 3.15%

• Identifying missing pieces in color vision defects: a genome-wide association study in Silk Road populations - Unknown journal (n.d.) · Unknown authors · PubMed 37359372

  ABSTRACT: Introduction: Color vision defects (CVDs) are conditions characterized by the alteration of normal trichromatic vision. CVDs can arise as the result of alterations in three genes (OPN1LW, OPN1MW, OPN1SW) or as a combination of genetic predisposition and environmental factors. To date, apart from Mendelian CVDs forms, nothing is known about multifactorial CVDs forms. Materials and Methods: Five hundred and twenty individuals from Silk Road isolated communities were genotyped and phenotypically characterized for CVDs using the Farnsworth D-15 color test. The CVDs traits Deutan-Protan (DP) and Tritan (TR) were analysed. Genome Wide Association Study for both traits was performed, and results were corrected with a False Discovery Rate linkage-based approach (FDR-p). Gene expression o

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