Drug resistance is the major obstacle to control of malaria and the spread of resistance has increased malaria mortality over recent decades. Identification of parasite genes that influence drug response would improve our ability to monitor resistance spread, provide tools for better understanding the mode of action of antimalarials, and allow rational redesign of existing drugs. In Thailand the problem is particularly severe with high levels of resistance to all classes of antimalarials except for the artemisinin derivatives. In the initial funding period of this project we measured response to eight drugs in 825 parasite isolates from a single clinic on the Thailand-Burma border, and then genotyped 323 single-clone parasites using 426 di-nucleotide microsatellite markers spaced at 50kb (~3cM) intervals throughout the genome. This work resulted in identification of a number of candidate regions that show association with response to one or more drugs. This renewal application capitalizes on these findings. We propose to (1) identify candidate genes and alleles that influence drug response using comparative sequencing and fine-scale association mapping, (2) use rapid transfection approaches to confirm which of the candidate genes identified are involved in resistance, and (3) examine whether specific alleles in these genes can predict drug treatment failure using clinical samples collected from patients in Thailand. Relevance of this research to public health. Malaria kills over one million people each year. The mainstay of malaria control is drug treatment, but treatment options are rapidly running out due to the evolution of resistance.
We aim to locate parasite genes underlying resistance. This will allow us to track the spread of resistance, to better understand how antimalarial drugs work, and to redesign drugs to restore their effectiveness.

Agency
National Institute of Health (NIH)
Institute
National Institute of Allergy and Infectious Diseases (NIAID)
Type
Research Project (R01)
Project #
5R01AI048071-08
Application #
7364133
Study Section
Special Emphasis Panel (ZRG1-DDR (01))
Program Officer
Joy, Deirdre A
Project Start
2000-09-01
Project End
2011-01-31
Budget Start
2008-02-01
Budget End
2009-01-31
Support Year
8
Fiscal Year
2008
Total Cost
$461,133
Indirect Cost
Name
Texas Biomedical Research Institute
Department
Type
DUNS #
007936834
City
San Antonio
State
TX
Country
United States
Zip Code
78245
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Anderson, Tim J C; Patel, Jigar; Ferdig, Michael T (2009) Gene copy number and malaria biology. Trends Parasitol 25:336-43

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