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. Author manuscript; available in PMC: 2012 Feb 7.
Published in final edited form as: HIV Seq Compend. 2001;2001:1–51.

Table 10.

Sources of Data on HIV Drug Resistance Mutations

Source A. Correlation between genotype and phenotype based on laboratory isolates
The pre-clinical evaluation of a new drug often involves culturing a wildtype laboratory HIV-1 isolate in the presence of increasing drug concentrations, and identifying mutations that allow the virus to continue to replicate. Site-directed mutagenesis experiments are done to confirm that the mutations arising during virus passage in the presence of the drug confer drug resistance when introduced into a wildtype virus. Drug resistance mutations identified by this process acquire widespread acceptance, are referred to as “canonical” resistance mutations, and are often considered the predominant mutations responsible for resistance to the drug under evaluation.
Source B. Correlation between genotype and phenotype based on clinical isolates
Laboratory isolates often contain only one or two drug-resistance mutations and rarely reflect the more complicated patterns of mutations observed in clinical isolates from patients receiving combination drug therapy. The complexity of sequences obtained on clinical isolates often precludes site-directed mutagenesis. Instead statistical associations between drug resistance mutations and in vitro resistance are required to elucidate the role of specific mutations or mutation patterns in causing drug resistance.
Source C. Correlation between genotype and treatment history
Sequences of HIV-1 isolates from patients failing antiretroviral therapy are crucial observations of HIV evolution that show which virus mutations are most significant in vivo. Such data are also essential for elucidating the genetic mechanisms of resistance to drugs that are difficult to test in vitro.
Source D. Correlation between genotype and clinical outcome
Data correlating genotype and clinical response to subsequent antiretroviral therapy are the most clinically relevant and the most useful for clinicians who must select anti-HIV drugs for their patients. However, data of this type generally lags several years behind data from sources A–C.