We decided to use the statistic SCORE.MAX, which is recommended in most circumstances, and selleck chem inhibitor which has been shown to work well even on non-randomly ascertained data. The current version of QTL-ALL can handle only nuclear family pedigrees. So the Mega2 program was used to convert the multi-generation families to single generation nuclear families [33]. Results Family Structure Error, Gender Error and Genotype Error Checking Family structure data and X-linked genotypes at 27 markers were combined to detect possible gender errors by looking for males who are more heterozygous than expected and females who are more homozygous than expected. Five males were heterozygous at more than two markers; 16 women were more than 80% homozygous. All suspect participants were rechecked to ensure there was no misreporting of gender.

We used RELPAIR and PREST to check the accuracy of self-reported family relationships. Misclassification of relationship for half-siblings as full-sibling, and unrelated as cousins, were detected and resolved. Participants with unresolved relationship errors were removed from families before analysis. We also used PEDCHECK to check Mendelian inconsistencies at each marker and erroneous data were omitted from further analysis. Table 1 shows the clinical and physical characteristics of the SDS participants used in the analysis. Linkage Analysis for T2D As shown in online Figure S1, non-parametric multipoint linkage analysis did not show any chromosomal region to be significantly associated with T2D in this Sikh cohort.

Adjusting for age, BMI, and gender did not alter linkage signal significantly and consequently were not included as covariates in the results presented. We found little evidence of linkage with T2D with maximum LOD of 1.24 reached on chromosome 2p24 near microsatellite markers SRAP and X130YG9P. No other region revealed any signal (LOD >1.00) associated with T2D in these families. Influence of Environmental Factors on Lipid Traits Univariate analysis of the lipid traits showed some individuals with very high or very low outlier values, which were removed from the analysis. As needed a Box-Cox transformation was used to make the error distribution of the data more normal (online Figure S2). Regression models were then fitted for the transformed traits. In the variable selection step, in most cases forward stepwise-regression and backward elimination agreed with each other.

Table 3 shows the final models selected after detecting the significant covariates for each lipid trait analyzed. Total serum cholesterol levels were influenced by economic status. The correlation between VLDL cholesterol and triglycerides was very high (0.98) and level of Cilengitide alcohol consumption was a significant factor for influencing both serum triglycerides and VLDL-cholesterol levels.