[Analysis of the genetic factors controlling malarial infection in man]

Sante. Jan-Feb 1999;9(1):53-9.
[Article in French]

Abstract

Genetic factors have clearly been shown to play a role in controlling malarial infection in animal models. There is now also increasing evidence for the genetic control of malaria in man. We carried out a segregation analysis based on blood parasite load phenotype for a population of the town of Bobo-Dioulasso (Burkina-Faso). This analysis demonstrated a strong genetic effect. Our results were not consistent with the segregation of a major gene and thus suggest that parasite load is under the control of minor genes. The genetic effect was stronger in children than in adults. We carried out a regression analysis in children and found that there was an association between the phenotype for blood parasite load and the q31-33 region of chromosome 5. We identified a gene in this region, Pfil1 (Plasmodium falciparum infection levels 1), which accounted for almost 50% of the variance in blood parasite load and which played a fundamental role in the control of infection. The 5q31-33 region contains several genes encoding cytokines that regulate T lymphocytes. The identification of genes controlling malarial infection opens up new possibilities for preventive and treatment strategies. It should be possible in the near future to identify individuals at risk of malaria, who would derive the greatest benefit from preventive and therapeutic measures. Finally, a deeper understanding of these genes controlling protective immune responses could be of value for the development of vaccines.

Publication types

  • Comparative Study
  • English Abstract

MeSH terms

  • Adolescent
  • Adult
  • Age Factors
  • Animals
  • Burkina Faso / epidemiology
  • Child
  • Child, Preschool
  • Chromosome Mapping
  • Chromosomes, Human, Pair 5 / genetics
  • Female
  • Humans
  • Infant
  • Infant, Newborn
  • Malaria, Falciparum / epidemiology
  • Malaria, Falciparum / genetics*
  • Malaria, Falciparum / parasitology
  • Male
  • Phenotype
  • Regression Analysis