Quantitative genetic analysis of susceptibility to hookworm infection in a population from rural Zimbabwe

Hum Biol. 1997 Apr;69(2):201-8.

Abstract

Overdispersion is a common feature of population distribution patterns for hookworm infection in humans. Genetic factors may be partially responsible for this observed increased susceptibility in a fraction of the exposed population. However, the hypothesis that there are genetic components to susceptibility to this infectious disease has not been tested explicitly. The purpose of this study is to quantify the influence of genetic factors on patterns of hookworm infection in a rural population in Zimbabwe. A quantitative measure of hookworm load, number of hookworm eggs per gram of feces, as determined by the Kato thick smear technique, was available for 289 individuals. Of these, 279 individuals were members of 62 nuclear families and 10 were independent individuals. We analyzed the hookworm data in combination with the pedigree structure of the sampled individuals using quantitative genetic analysis techniques. Using this variance decomposition approach, we estimated the heritability of hook worm load to be 0.37 +/- 0.09 (p < 0.0001). This significant heritability indicates that 37% of the variation (after correcting for the effects of covariates) in hookworm eggs per gram observed in this population is attributable to genetic factors. The results suggest that further investigation and characterization of the genetic components influencing susceptibility to hookworm infection are warranted.

Publication types

  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Adolescent
  • Adult
  • Child
  • Child, Preschool
  • Developing Countries
  • Disease Susceptibility
  • Feces / parasitology
  • Female
  • Hookworm Infections / epidemiology
  • Hookworm Infections / genetics*
  • Humans
  • Incidence
  • Likelihood Functions
  • Male
  • Middle Aged
  • Models, Genetic
  • Pedigree
  • Phenotype
  • Rural Population
  • Sampling Studies
  • Zimbabwe / epidemiology