Familial Correlations,Segregation Analysis,and Nongenetic Correlates of Soy Isoflavone–Metabolizing Phenotypes

Abstract

Particular intestinal bacteria metabolize the soy isoflavone daidzein to equol and O-desmethylangolensin (O-DMA), metabolites that can be identified in urine. Individuals that harbor bacteria capable of producing equol or O-DMA are known as equol producers (approximately 30%-50% of the population) and O-DMA producers (approximately 80%-90% of the population), respectively. The equol-producer phenotype has been associated with sex hormone-related outcomes in several studies. However, the bacteria responsible for these phenotypes have not yet been identified and factors that influence the manifestation of these phenotypes are not well understood. To evaluate familial clustering of and nongenetic factors associated with these phenotypes, 410 individuals from 112 families participated in phenotyping (3-day soy challenge and Day 4 spot urine collection). In segregation analyses of the equol-producer phenotype, the Mendelian dominant model provided the most parsimonious fit to the data, suggesting that the pattern of inheritance of the equol-producer phenotype is consistent with an autosomal dominant trait. This phenotype was positively associated with education (p trend = 0.01), but not with sex, smoking, or several dietary factors. Results of the segregation analyses of the O-DMA-producer phenotype were inconclusive; no other models provided a more parsimonious fit to the data than the general model. This phenotype was inversely associated with age in a nonlinear model (p = 0.01), positively associated with age- and sex-adjusted height (odds ratio [OR] 10-cm increase = 0.38, 95% confidence interval [CI] = 0.15, 0.95) and body mass index (kg/m²) (OR = 0.91, 95% CI = 0.85, 0.96), but not with sex, education, smoking, or several dietary factors. These results suggest the equol-producer phenotype may be under some degree of genetic control and that there are likely other environmental factors not evaluated in the present analysis that contribute to both of these phenotypes. These results provide a foundation for further work to refine our understanding of heritable and environmental determinants of daidzein-metabolizing phenotypes.