Estimating frequencies of minority nevirapine-resistant strains in chronically HIV-1-infected individuals naive to nevirapine by using stochastic simulations and a mathematical model.
Nevirapine forms the mainstay of our efforts to curtail the pediatric AIDS epidemic through prevention of mother-to-child transmission of HIV-1. A key limitation, however, is the rapid selection of HIV-1 strains resistant to nevirapine following the administration of a single dose. This rapid selection of resistance suggests that nevirapine-resistant strains preexist in HIV-1 patients and may adversely affect outcomes of treatment. The frequencies of nevirapine-resistant strains in vivo, however, remain poorly estimated, possibly because they exist as a minority below current assay detection limits. Here, we employ stochastic simulations and a mathematical model to estimate the frequencies of strains carrying different combinations of the common nevirapine resistance mutations K103N, V106A, Y181C, Y188C, and G190A in chronically infected HIV-1 patients naïve to nevirapine. We estimate the relative fitness of mutant strains from an independent analysis of previous competitive growth assays. We predict that single mutants are likely to preexist in patients at frequencies ( approximately 0.01% to 0.001%) near or below current assay detection limits (>0.01%), emphasizing the need for more-sensitive assays. The existence of double mutants is subject to large stochastic variations. Triple and higher mutants are predicted not to exist. Our estimates are robust to variations in the recombination rate, cellular superinfection frequency, and the effective population size. Thus, with 10(7) to 10(8) infected cells in HIV-1 patients, even when undetected, nevirapine-resistant genomes may exist in substantial numbers and compromise efforts to prevent mother-to-child transmission of HIV-1, accelerate the failure of subsequent antiretroviral treatments, and facilitate the transmission of drug resistance.
Gadhamsetty
Saikrishna
S
Department of Chemical Engineering, Indian Institute of Science, Bangalore 560012, India.
Dixit
Narendra M
NM
D024882:Drug Resistance, Viral / Q000235:genetics; D019143:Evolution, Molecular; D005260:Female; D016679:Genome, Viral; D015658:HIV Infections / Q000188:drug therapy* / Q000517:prevention & control / Q000635:transmission / Q000821:virology*; D015497:HIV-1 / Q000187:drug effects* / Q000235:genetics*; D006801:Humans; D007231:Infant, Newborn; D018445:Infectious Disease Transmission, Vertical / Q000517:prevention & control; D055641:Mathematical Concepts; D008954:Models, Biological; D019829:Nevirapine / Q000494:pharmacology*; D011247:Pregnancy; D018894:Reverse Transcriptase Inhibitors / Q000494:pharmacology; D013269:Stochastic Processes
D018894:Reverse Transcriptase Inhibitors; D019829:Nevirapine