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HIV-1 genetic diversity and transmitted resistance in health care settings in Maputo, Mozambigue
Global Health Sciences Literature Digest
Published January 4, 2010
Journal Article

Bartolo I, Casanovas J, Bastos R, et al. HIV-1 genetic diversity and transmitted resistance in health care settings in Maputo, Mozambigue. J Acquir Immune Def Syndr 2009;51:323-31.

In Context

Widespread use of antiretroviral therapy (ART) without sufficient infrastructure can lead to drug-resistant strains of HIV circulating in the population because access to ART may be intermittent and programs to reduce transmission of HIV may be lacking, allowing greater mutations to occur. Although ART programs became widely available in Mozambique in 2004,(1) among patients able to pay for treatment, ART use without infrastructure began as early as 1996. Understanding the characteristics of drug-resistant mutations prior to 2004 can provide a baseline for monitoring resistance patterns as the use of ART expands.

Objective

To measure and describe the genetic diversity of HIV infections among drug-naïve HIV-infected patients.

Setting

Four hospitals and three public clinics in Maputo, Mozambique.

Study Design

Retrospective observational study.

Participants

Participants were 144 drug-naïve patients seen between 2002 and 2004.

Outcome

HIV drug-resistant mutations and natural polymorphisms.

Methods

Stored plasma from patients referred to hospitals and clinics in Maputo was tested for CD4 counts and viral load. Viral RNA was extracted, amplified by polymerase chain reaction, and sequenced. Sequences were aligned with reference strains collected from the Los Alamos Sequence Database(2) using ClustalX 1.8 interface.(3) Maximum likelihood phylogenetic analyses(4) were performed using the best-fit model of molecular evolution estimated by Modeltest v3.7 under the Akaike information criterion.(5) The chosen model was General time reversible 1 Gamma + Proportion Invariant (GTR + G + I) model of evolution for both genes. Tree searches were conducted in Phylogenetic Analysis Using Parsimony (and other method) (PAUP) v4.0b10 using a nearest neighbor interchange heuristic search strategy(6) and bootstrap resampling.(7) Bootstrap values of ≥70% were considered definitive for significant clustering.(8) Recombination analysis was performed by bootscanning using SimPlot 3.5.1.(9) A maximum likelihood phylogenetic analysis of a dataset containing the Mozambican sequences and subtype G, CRF02_AG, CRF37_cpx, and A3 sequences collected from the Los Alamos Sequence Database to examine the provenience of subtype G and CRF37-cpx viruses circulating in Mozambique.(2) Resistance mutation analysis was performed using the Stanford Genotypic Resistance Interpretation Algorithm.(10).

Results

The mean patient age was 41 years and 57% of the sample was male. The mean viral load was 5.0 log10 copies/mL and median CD4 count was 260 cells/µL. The amplification, sequencing and phylogenetic analysis of the protease region (PR) and/or reverse transcriptase (RT) regions were completed successfully for 104 (72%) samples. The PR sequences were obtained from 99 (95%) patients and RT sequences were obtained from 68 (65%) patients. Both PR and RT sequences were obtained from 63 (61%) patients. Sequences were obtained significantly more often in older patients and patients with a greater viral load. Phylogenetic analysis revealed that 84 (80.8%) viral isolates were subtype C, 12 (11.5%) were non-C (7 [58%] CRF37_cpx, 4 [33%] subtype G, and 1 (8%) untypable [U] strain), and 8 (7.7%) were recombinants between the C subtype and 3 other subtypes or U strains (3 C [PR]/A1 [RT], 1 C/D, 1 C/F1, 2 C/U, and 1 U/C). No major mutations were associated with protease inhibitor resistance. One of the patients also carried the K103N mutation that confers resistance to nevirapine and efavirenz. Phylogenetic analysis revealed that patients 04MZUNIV87 and 04MZUNIV15 clustered together in the RT region, which could be an indication of epidemiological linkage. Patients with drug-resistant virus had a significantly lower viral load compared with the rest of the patients. The most frequent PR polymorphisms in subtype C viruses, as compared with the B subtype, were T12S, I15V, L19I, M36I, R41K, L63P, H69K, L89M, and I93L. The prevalence of the V35T, D177E, V245Q, E291D, and V292I polymorphisms was significantly lower in the C sequences from Maputo compared with the worldwide C and B sequences available from untreated patients. The prevalence of R211K was significantly higher in our patients. The RT polymorphisms whose frequency in non-C sequences differed significantly from clade C viruses from Mozambique and worldwide were E36A, T39E, S48T, K122E,A272P, and V292I.

Conclusions

There is a large degree of genetic diversity of HIV-1 in Maputo, including representation of all major subtypes and recombinant forms.

Quality Rating

This is a high-quality descriptive analysis. The sample is adequately representative and the methods employed are appropriate.

Programmatic Implications

This study is important because it demonstrates the feasibility of conducting surveillance for drug-resistance in a resource constrained country and because it demonstrates substantial genetic diversity and the presence of drug resistance. Monitoring HIV drug-resistant strains is important to ensure that first-line ART is routinely prescribed.

References

  1. Gilks CF, Crowley S, Ekpini R, et al. The WHO public-health approach to antiretroviral treatment against HIV in resource-limited settings. Lancet 2006;368:505-10.
  2. Database LAS. Los Alamos, et al. New Mexico: Los Alamos National Laboratory; 2008. Accessed September 2008.
  3. Thompson JD, Gibson TJ, Plewniak F, et al. The CLUSTAL_X windows interface: flexible strategies for multiple sequence alignment aided by quality analysis tools. Nucleic Acids Res 1997;25:4876-82.
  4. Felsenstein J. Evolutionary trees from DNA sequences: a maximum likelihood approach. J Mol Evol 1981;17:368-76.
  5. Posada D, Crandall KA. MODELTEST: testing the model of DNA substitution. Bioinformatics 1998;14:817-8.
  6. Wilgenbusch J, Swofford D. PAUP* Phylogenetic Analysis Using Parsimony (*and Other Methods) [computer program]. Version 4. Sunderland, MA: Sinauer-associates; 2001. Abstract not available.
  7. Felsenstein J. Confidence limits on phylogenies: an approach using the bootstrap. Evolution. 1985;39:783-791. Abstract not available.
  8. Hillis D, Bull J. An empirical test for bootscanning as a method for assessing viral sequence relatedness. Syst Biol. 1993;42:182-192. Abstract not available.
  9. Lole KS, Bollinger RC, Paranjape RS, et al. Full-length human immunodeficiency virus type 1 genomes from subtype C-infected seroconverters in India, with evidence of intersubtype recombination. J Virol 1999;73:152-160.
  10. Shafer R. Database SHDR. Stanford University, California; 2008.