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Publication Detail

Title: Linkage Analysis of Urine Arsenic Species Patterns in the Strong Heart Family Study.

Authors: Gribble, Matthew O; Voruganti, Venkata Saroja; Cole, Shelley A; Haack, Karin; Balakrishnan, Poojitha; Laston, Sandra L; Tellez-Plaza, Maria; Francesconi, Kevin A; Goessler, Walter; Umans, Jason G; Thomas, Duncan C; Gilliland, Frank; North, Kari E; Franceschini, Nora; Navas-Acien, Ana

Published In Toxicol Sci, (2015 Nov)

Abstract: Arsenic toxicokinetics are important for disease risks in exposed populations, but genetic determinants are not fully understood. We examined urine arsenic species patterns measured by HPLC-ICPMS among 2189 Strong Heart Study participants 18 years of age and older with data on ~400 genome-wide microsatellite markers spaced ~10 cM and arsenic speciation (683 participants from Arizona, 684 from Oklahoma, and 822 from North and South Dakota). We logit-transformed % arsenic species (% inorganic arsenic, %MMA, and %DMA) and also conducted principal component analyses of the logit % arsenic species. We used inverse-normalized residuals from multivariable-adjusted polygenic heritability analysis for multipoint variance components linkage analysis. We also examined the contribution of polymorphisms in the arsenic metabolism gene AS3MT via conditional linkage analysis. We localized a quantitative trait locus (QTL) on chromosome 10 (LOD 4.12 for %MMA, 4.65 for %DMA, and 4.84 for the first principal component of logit % arsenic species). This peak was partially but not fully explained by measured AS3MT variants. We also localized a QTL for the second principal component of logit % arsenic species on chromosome 5 (LOD 4.21) that was not evident from considering % arsenic species individually. Some other loci were suggestive or significant for 1 geographical area but not overall across all areas, indicating possible locus heterogeneity. This genome-wide linkage scan suggests genetic determinants of arsenic toxicokinetics to be identified by future fine-mapping, and illustrates the utility of principal component analysis as a novel approach that considers % arsenic species jointly.

PubMed ID: 26209557 Exiting the NIEHS site

MeSH Terms: Adult; Arizona; Arsenic Poisoning/enzymology; Arsenic Poisoning/genetics*; Arsenic Poisoning/urine; Arsenicals/urine*; Biomarkers/urine; Biotransformation; Cohort Studies; Female; Genetic Linkage; Genetic Predisposition to Disease*; Genome-Wide Association Study; Humans; Linkage Disequilibrium; Logistic Models; Male; Methylation; Methyltransferases/genetics*; Methyltransferases/metabolism; Microsatellite Repeats*; Midwestern United States; Polymorphism, Single Nucleotide; Principal Component Analysis; Toxicokinetics

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