Genetic predictors of susceptibility to cutaneous fungal infections: a pilot genome wide association study to refine a candidate gene search

Abstract

Background: Trichophyton tonsurans is the foremost fungal pathogen of minority children in the U.S. Despite overwhelming infection rates, it does not appear that this fungus infects children in a non-specific manner.

Objective: This study was designed to identify genes that may predispose or protect a child from T. tonsurans infection.

Methods: Children participating in an earlier longitudinal study wherein infection rates could be reliably determined were eligible for inclusion. DNA from a subset (n=40) of these children at the population extremes underwent whole genome genotyping (WGG). Allele frequencies between cases and controls were examined and significant SNPs were used to develop a candidate gene list for which the remainder of the cohort (n=115) were genotyped. Cumulative infection rate was examined by genotype and the ability of selected genotypes to predict the likelihood of infection explored by multivariable analysis.

Results: 23 genes with a putative mechanistic role in cutaneous infection were selected for evaluation. Of these, 21 demonstrated significant differences in infection rate between genotypes. A risk index assigned to genotypes in the 21 genes accounted for over 60% of the variability observed in infection rate (adjusted r(2)=0.665, p<0.001). Among these, 8 appeared to account for the majority of variability that was observed (r(2)=0.603, p<0.001). These included genes involved in: leukocyte activation and migration, extracellular matrix integrity and remodeling, epidermal maintenance and wound repair, and cutaneous permeability.

Conclusions: Applying WGG to individuals at the extremes of phenotype can help to guide the selection of candidate genes in populations of small cohorts where disease etiology is likely polygenic in nature.

Figure 1

Box plots of risk index vs. infection phenotype with all genes considered (left), with the subset of genes demonstrating the greatest impact on phenotype (center) and with the subset of genes demonstrating the greatest impact on phenotype based on β-coefficient (right).