Computational protocol: Ancestry-informative markers on chromosomes 2, 8 and 15 are associated with insulin-related traits in a racially diverse sample of children

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Protocol publication

[…] Differences in mean values for phenotypes between racial/ethnic groups were examined using analysis of variance. Multiple linear regression analyses were used to test the association between European admixture and total fat and the four insulin-related phenotypes, and to examine the association between each of 142 SNPs and four insulin-related phenotypes. For SI, FI and HOMA-IR, the model was defined by age, Tanner stage, sex, SES, European admixture, Amerindian admixture, total fat and height. By controlling for two of three admixture estimates, we prevented the introduction of co-linearity in the statistical models, since the three admixture estimates add up to 1. For AIRg, the model was additionally adjusted for SI. To conform to the assumptions of regression, all models were evaluated for residual normality; logarithmic transformation was performed when appropriate. Outliers were removed based on whether residuals were greater than three standard deviations away from the mean.Genotyped SNPs were tested for association with the four insulin-related phenotypes using linear regression under additive, dominant, recessive and two-degrees-of-freedom genotypic models. Considering each phenotype and each genetic model separately, we applied a Bonferroni multiple correction to the marker association tests; a p-value cut-off of 3.6 × 10-4 keeps the nominal type I error rate at 0.05. To determine the extent to which measurement error in admixture estimates could skew the results, we applied the method described by Divers et al. [] Basically, we obtained an estimate of the measurement error covariance and applied the simulation extrapolation (SimEx) algorithm [] to retest for association between each marker and phenotype, for each mode of inheritance model. Analyses were carried out with PLINK,[] SAS 9.1 software (SAS Institute, Cary, NC, USA) and R []. […]

Pipeline specifications

Software tools ADMIXTURE, PLINK
Applications Population genetic analysis, GWAS
Organisms Homo sapiens
Diseases Diabetes Mellitus, Machado-Joseph Disease
Chemicals Glucose