Antiretroviral drug resistance in HIV

teaser

Mauro Zaccarelli
MD
Coordinator of the Antiretroviral Therapy Unit
Clinical Department
National Institute for Infectious Diseases “Lazzaro Spallanzani”
Rome, Italy
E:[email protected]

Virological failure is very common in routine HIV treatment, with 30–70% of patients in clinic-based cohorts showing evidence of virological failure during their antiretroviral treatment.(1,2) Thus, the prevalence of mutations associated with HIV resistance is high.(3) Continuing viral replication during the course of therapy leads to accumulation of mutations associated with drug resistance. Increasing risk of disease progression and death in patients harbouring multiple drug resistance has been demonstrated.(4)

Measuring HIV resistance

Phenotypic resistance test
In a way similar to antibiograms, phenotypic assays for drug susceptibility can determine the amount of drug needed to inhibit viral growth in tissue culture. The result is expressed in fold changes in drug concentration, comparing the inhibitory concentration for 50% or 95% (IC(50) and IC(95), respectively) of the patient’s virus to that of the reference control. Although these assays give a direct measure of resistance, they are expensive and only a few laboratories currently carry them out.

Genotypic resistance test
The genotypic resistance test can detect characteristic mutations in HIV genes that are known to be associated with HIV resistance to a particular drug or class of drug. Mutations are indicated by the original amino acid before its position number in the enzyme, followed by the mutated amino acid. For example, the reverse transcriptase (RT) mutation designated as M184V means that at position 184 (in RT) valine has replaced methionine. The RT genome is composed of more than 500 amino acids, and that of the protease (PR) consists of 99 amino acids. There are over 100 mutations that are known to be involved in the development of HIV drug resistance, and the number of mutations continues to grow. The genotypic test is currently the standard in clinical care, and its usefulness has been clearly established.(5–8)

Virtual phenotype
The virtual phenotype simulates phenotypic resistance from the genotype using pattern recognition applied to large relational databases of genotypes and phenotypes. This technique compares the result with other genotypes for which the phenotype has already been identified, providing a quantitative and accurate prediction of phenotypic resistance, and can be helpful for interpreting genotypic resistance.

Use of resistance testing in clinical practice

Guidelines
The most recent treatment guidelines recommend the use of a resistance test in experienced patients both at the time of virological failure during combination antiretroviral therapy and in suboptimal suppression of viral load after antiretroviral therapy initiation.(9) In antiretroviral-naive patients, a resistance test is recommended before starting a first-line therapy only in case of acute or recent infection, particularly if transmission of resistant HIV is suspected. Testing HIV patients with chronic infection might fail to detect drug-resistant species that, with time, have become minor species in the absence of selective drug pressure; thus, testing at this time is not recommended. Testing naive patients before starting therapy is becoming routine due to the increasing occurrence of resistance mutations in these patients (about 10% in Europe).(10) Although there are no specific recommendations for resistance testing during pregnancy, testing is routinely used in clinical practice to prevent perinatal transmission of resistant virus.

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Resistance and possible clinical benefits
Although genotypic mutations are generally associated with different measurable degrees of phenotypic resistance to antiretroviral drugs, in some situations they may confer clinical benefits to the patients. Benefits may occur through two mechanisms: reduction of viral fitness and hypersusceptibility. In this specific context, the term “fitness” indicates the ability of HIV to maintain a high rate of replication capacity in the presence of antiretroviral drugs. Indeed, replication capacity, which is high in the presence of wild-type virus, tends to decrease when HIV needs to adapt its enzymes in order to work in the presence of drugs. The M184V and K65R mutations(11,12) (particularly if they are associated(13)) in RT and all primary mutations (mainly D30N, M46I, V82A, L84V and L90M) in PR are involved in reduced HIV replication capacity.(12,14) Moreover, viral isolates with reduced susceptibility or resistance to some antiretroviral drugs may exhibit significantly increased susceptibility to other drugs acting on the same enzyme. This phenomenon, known as hypersusceptibility, has been demonstrated both in vitro (by phenotypic assays) and in vivo. One of the first examples of enhanced susceptibility was the demonstration that the M184V mutation, associated with high levels of resistance to 3TC, can resensitise AZT-resistant HIV if M41L and 215Y mutations are present.(15) Efavirenz hypersusceptibility has been described in association with selected nucleoside analogous mutations (NAMs) in the presence of M41L, L210W, T215Y and M184V mutations.(16) Hypersusceptibility to some protease inhibitors has also been described in association with mutations conferring resistance to other drugs of the same class.(17,18)

Interpretation
Detection of specific mutations can indicate full resistance to antiretrovirals (see Table 1).(19,20) Full or partial resistance may also be related to single or multiple detection of secondary mutations. Thus, assessing an effective antiretroviral regimen in patients harbouring resistant virus may be complex, especially in patients with extensive patterns of mutations.

[[HPE20_table1_46]]

To help clinicians (who may fail to interpret the complex results of a genotypic test even if they are experienced), several interpretation systems are available on the internet. These systems use large databases and several published algorithms to interpret the set of mutations obtained from a genotypic test. The result is an immediate report in which the sensitivity of each antiretroviral drug is indicated. Unfortunately, the algorithms lack standardisation, and different systems may lead to different interpretations.(21)

The most widely use interpretation system is the Stanford sequence analysis programme, freely available online (see Resource). Although the virtual phenotype is an advanced interpretation system, it is expensive and not directly available. In our research centre, genotype results are discussed weekly within a panel including clinicians and virologists. This “expert advice” approach is effective in interpreting genotype and improving the effectiveness of a genotype-guided therapy.(5,6)

Management of different possible resistance scenarios in treatment-failing patients are summarised in Table 2.

[[HPE20_table2_47]]

References

1. Lucas GM, Chaisson RE, Moore RD. Ann Intern Med 1999;131:81-7.
2. Mocroft A, Devereux H, Kinloch-de-Loes S, et al. AIDS 2000;14:1545-52.
3. Richman DD, Morton SC, Wrin T, et al. AIDS 2004;18:1393-401.
4. Zaccarelli M, Tozzi V, Lorenzini P, et al. XV International AIDS Conference, Bangkok Thailand, 11–16 July 2004. Abstract WePeB5706.
5. Durant J, Clevenbergh P, Garraffo R, et al. Lancet 1999;353:2195-9.
6. Baxter JD, Mayers DL, Wentworth DN, et al. AIDS 2000;14:F83-93.
7. Tural C, Ruiz L, Holtzer C, et al. AIDS 2002;16:209-18.
8. Meynard JL, Vray M, Morand-Joubert L, et al. AIDS 2002;16:727-36.
9. Department of Health and Human Services (DHHS). Guidelines for the use of antiretroviral agents in HIV-1-infected adults and adolescents. 2004.
10. Wensing AMJ, van de Vijver DAMC, Asjo B. 2nd IAS Conference on HIV Pathogenesis and Treatment; 13–16 July 2003; Paris, France. Abstract LB1.
11. Wei X, Liang C, Gotte M, et al. Virology 2003;311:202-12.
12. Weber J, Rangel HR, Chakraborty B, et al. J Acquir Immune Defic Syndr 2003;33:448-60.
13. White KL, Margot NA, Wrin T, et al. Antimicrob Agents Chemother 2002;46:3437-46.
14. Devereux HL, Emery VC, Johnson MA, et al. J Med Virol 2001;65:218-24.
15. Whitcomb JM, Huang W, Limoli K, et al. AIDS 2002;16:F41-7.
16. Tozzi V, Zaccarelli M, Narciso P, et al. J Infect Dis 2004;189:1688-95.
17. Obry V, Race E, Vray M, Meynard L, et al. 9th Conference on Retroviruses and Opportunistic Infections; 24–28 February 2002; Seattle, Washington, USA. Abstract 557-T.
18. Colonno R, Rose R, Cianci C, et al. 10th Conference on Retroviruses and Opportunistic Infections; 10–14 February 2003; Boston, Massachusetts, USA. Abstract 597.
19. Shafer RW. Genotypic testing for HIV-1 drug resistance. Available at: hivdb.stanford.edu
20. Johnson V, Brun-Vézinet F, Clotet B, et al. Update of the drug resistance mutations in HIV-1: 2004. Top HIV Med 2004;12:119-24. Available at: www.iasusa.org
21. De Luca A, Perno CF. Curr Opin Infect Dis 2003;16:573-80.

Resource
HIV Drug Resistance Database
W:hivdb.stanford.edu