Expressive

rs10425377 - KLK10

Magnitude 2.0 · 2 studies on file

Reported associations

  • Genetic determinants of plasma protein levels in the Estonian population - Scientific reports (2024) · Kalnapenkis A, Jõeloo M, Lepik K, Kukuškina V, Kals M, Alasoo K, Mägi R, Esko T, Võsa U · PubMed 38565889

    ABSTRACT: The proteome holds great potential as an intermediate layer between the genome and phenome. Previous protein quantitative trait locus studies have focused mainly on describing the effects of common genetic variations on the proteome. Here, we assessed the impact of the common and rare genetic variations as well as the copy number variants (CNVs) on 326 plasma proteins measured in up to 500 individuals. We identified 184 cis and 94 trans signals for 157 protein traits, which were further fine-mapped to credible sets for 101 cis and 87 trans signals for 151 proteins. Rare genetic variation contributed to the levels of 7 proteins, with 5 cis and 14 trans associations. CNVs were associated with the levels of 11 proteins (7 cis and 5 trans), examples including a 3q12.1 deletion acting

  • A fully joint Bayesian quantitative trait locus mapping of human protein abundance in plasma - PLoS computational biology (2020) · Ruffieux H, Carayol J, Popescu R, Harper ME, Dent R, Saris WHM, Astrup A, Hager J, Davison AC, Valsesia A · PubMed 32492067

    ABSTRACT: Molecular quantitative trait locus (QTL) analyses are increasingly popular to explore the genetic architecture of complex traits, but existing studies do not leverage shared regulatory patterns and suffer from a large multiplicity burden, which hampers the detection of weak signals such as trans associations. Here, we present a fully multivariate proteomic QTL (pQTL) analysis performed with our recently proposed Bayesian method LOCUS on data from two clinical cohorts, with plasma protein levels quantified by mass-spectrometry and aptamer-based assays. Our two-stage study identifies 136 pQTL associations in the first cohort, of which >80% replicate in the second independent cohort and have significant enrichment with functional genomic elements and disease risk loci. Moreover, 78%

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