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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., (© The Author 2015. Published by Oxford University Press on behalf of the Society of Toxicology. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.)

Hyperuricemia is associated with the metabolic syndrome, gout, renal and cardiovascular disease (CVD). American Indians have high rates of CVD and 25% of individuals in the strong heart family study (SHFS) have high serum uric acid levels. The aim of this study was to investigate the genetic determinants of serum uric acid variation in American Indian participants of the SHFS. A variance component decomposition approach (implemented in SOLAR) was used to conduct univariate genetic analyses in each of three study centers and the combined sample. Serum uric acid was adjusted for age, sex, age x sex, BMI, estimated glomerular filtration rate, alcohol intake, diabetic status and medications. Overall mean +/- SD serum uric acid for all individuals was 5.14 +/- 1.5 mg/dl. Serum uric acid was found to be significantly heritable (0.46 +/- 0.03 in all centers, and 0.39 +/- 0.07, 0.51 +/- 0.05, 0.44 +/- 0.06 in Arizona, Dakotas and Oklahoma, respectively). Multipoint linkage analysis showed significant evidence of linkage for serum uric acid on chromosome 11 in the Dakotas center [logarithm of odds score (LOD) = 3.02] and in the combined sample (LOD = 3.56) and on chromosome 1 (LOD = 3.51) in the combined sample. A strong positional candidate gene in the chromosome 11 region is solute carrier family22, member 12 (SLC22A12) that encodes a major uric acid transporter URAT1. These results show a significant genetic influence and a possible role for one or more genes on chromosomes 1 and 11 on the variation in serum uric acid in American Indian populations.

Background: Body fat mass distribution and deposition are determined by multiple environmental and genetic factors. Obesity is associated with insulin resistance, hyperinsulinemia, and type 2 diabetes. We previously identified evidence for genotype-by-diabetes interaction on obesity traits in Strong Heart Family Study (SHFS) participants. To localize these genetic effects, we conducted genome-wide linkage scans of obesity traits in individuals with and without type 2 diabetes, and in the combined sample while modeling interaction with diabetes using maximum likelihood methods (SOLAR 2.1.4)., Methods: SHFS recruited American Indians from Arizona, North and South Dakota, and Oklahoma. Anthropometric measures and diabetes status were obtained during a clinic visit. Marker allele frequencies were derived using maximum likelihood methods estimated from all individuals and multipoint identity by descent sharing was estimated using Loki. We used variance component linkage analysis to localize quantitative trait loci (QTLs) influencing obesity traits. We tested for evidence of additive and QTL-specific genotype-by-diabetes interactions using the regions identified in the diabetes-stratified analyses., Results: Among 245 diabetic and 704 non-diabetic American Indian individuals, we detected significant additive gene-by-diabetes interaction for weight and BMI (P < 0.02). In analysis accounting for QTL-specific interaction (P < 0.001), we detected a QTL for weight on chromosome 1 at 242 cM (LOD = 3.7). This chromosome region harbors the adiponectin receptor 1 gene, which has been previously associated with obesity., Conclusion: These results suggest distinct genetic effects on body mass in individuals with diabetes compared to those without diabetes, and a possible role for one or more genes on chromosome 1 in the pathogenesis of obesity.