Clinical and Molecular Studies of Drug-Resistant Malaria [II]

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Investigator: Matthew G. Dorsey, MD
Sponsor: NIH John F. Fogarty International Center

Location(s): Uganda

Description

Anti-malarial drug resistance is a serious international health problem and a major obstacle for malaria control efforts in Africa. In 2002, a collaborative project was established to expand an existing surveillance system for the monitoring of anti-malarial drug resistance at seven sentinel sites in Uganda with a focus on combination anti-malarial therapy. The overall goal of my project is to utilize data collected from these surveillance sites, molecular tools, and cutting-edge analytical techniques to best characterize anti-malarial drug resistance in Uganda and further our understanding of the determinants of drug resistance. The specific aims of the project are as follows: 1) To optimize the results of a large national drug surveillance study by evaluating the impact of extended follow-up and genotyping on estimates of the efficacies of combination regimens for the treatment of uncomplicated malaria in Uganda. 2) To evaluate molecular markers of sulfadoxine-pyrimethamine and chloroquine resistance as predictors of clinical treatment outcomes. 3) To identify individual and community level risk factors for anti-malarial drug resistance. Data will come from ongoing randomized clinical trials comparing sulfadoxine/pyrimethamine (SP) + chloroquine (CQ) to SP + amodiquine (AQ) for the treatment of uncomplicated falciparum malaria at each of the seven sentinel sites. An AQ + artesunate (AS) treatment arm will be included at three of the sites. Of note, SP+CQ is the new national first-line therapy for uncomplicated malaria, SP+AQ was superior in our prior studies, and AQ+AS is a promising new regimen of great international interest. Estimates of treatment efficacy using the standard 14-day WHO protocol will be compared with those using a 28-day follow-up protocol including molecular genotyping to distinguish recrudescence from new infections. Parasite DNA will be used to determine whether polymorphisms in key parasite genes (dhfr, dhps, pfcrt) predict clinical response to therapy. Multivariate analysis will be used to identify population and individual risk factors for markers of anti-malarial drug resistance and clinical treatment failure. The results of these investigations will provide key information for the formulation of rational malaria treatment policies and contribute to our understanding of the mechanisms of anti-malarial drug resistance.