The goal of this study was to determine whether statistical modeling of population data for a phenotypic marker could reflect a major locus gene defect. Identifying mutations in the HFE gene makes it possible to assess the association between transferrin saturation (TS) subpopulations and HFE mutations. Data were analyzed from 27 895 white patients who attended a health appraisal clinic and who had TS and common mutations of HFE determined. Mixture distribution modeling of TS was performed, and the proportion of HFE mutations in TS subpopulations was assessed on a probability basis. Three subpopulations of TS were identified, consistent with Hardy-Weinberg conditions for major locus effects. For men, 72% of the subpopulation with the highest mean TS had HFE gene mutations; they were primarily homozygotes or compound heterozygotes. Seventy-three percent of the subpopulation with moderate mean TS also had HFE gene mutations; they were predominantly simple heterozygotes. Sixty-seven percent of the subpopulation with the lowest mean TS were wild-type homozygotes. Similar results were observed for women. These results suggest that statistical modeling of population clinical laboratory test data can reveal the influence of a major locus gene defect and perhaps can be applied to other aspects of body metabolism than iron.