Threat of resistant HIVJanuary 14, 2019
Global and large-scale use of anti-retroviral therapy (ART) is helping reduce relative rates of morbidity and mortality from acquired immunodeficiency syndrome. However, clinical benefits are soon becoming outweighed by the emergence of drug-resistant HIV-1 strains. At present, ART is directed against virus-specific enzymes as well as the processes of attachment and entry into cells. These therapies are neither curative nor eradicative, as latent HIV infection is established through the integration of double-stranded proviral DNA into the host cell. In India and elsewhere, the use of ARTs is leading to a rapid evolution of the virus and an increase in individuals presenting with HIV drug resistance (HIVDR) mutations. Monitoring of HIVDR mutations are needed for proper management and ensuring optimal therapy to patients. As patients with acquired drug resistance are increasing, so are newly infected patients with transmitted drug resistance.
This clearly suggests that the 21 million people receiving ART are at risk as also the target of eliminating HIV as a public health threat by 2030. More than 1 patient in 10 are becoming ART-resistant in low and middle income countries with respect to non-nucleoside reverse transcriptase inhibitors (NNRTIs). Pretreatment drug resistance is associated with an increased risk of virological failure, impaired immune recovery, accumulation of drug resistance, increased risk of treatment switches and death. WHO recommends a shift to alternative, non-NNRTI-based first-line ART (i.e., based on integrase inhibitors or protease inhibitors) or individualised pretreatment drug resistance testing to guide the choice of an appropriate
first-line treatment. Additionally, continuous resistance surveillance is recommended as a part of the WHO Global Action Plan on HIV drug resistance. One technological breakthrough has led to the development of highly robust next generation sequencing (NGS) technologies with the ability to detect low-frequency, minority HIV variants at increasingly affordable prices.
Importance of HIV-1 genotyping
A recent case-control study nested within a prospective multicountry cohort by Seth C Inzaule et al (The Lancet HIV, http://dx.doi.org/10.1016/S2352-3018(18)30177-2), studied the International Antiviral Society (IAS)-USA mutation list or the Stanford HIV Drug Resistance Database (HIVDB) using Illumina MiSeq next-generation sequencing technology. They compared the conventional pretreatment drug resistance detection threshold of 20% or more for Sanger-based sequencing to diagnostic accuracy measurements and the odds of virological failure using conditional logistic regression for 1%, 5% and 10%. A 12-month follow-up of 1896 participants suggested that virological failure had an odds ratio (OR) of 9.2 (95% CI 4·2–20·1) at a detection threshold of 20% or more, for patients with pretreatment resistance compared to without pretreatment drug resistance. Lowering the threshold to 10% resulted in an odds ratio of 6.8 (95% CI 3·3–13·9), 5% to 7·6 (3·4–17·1) and 1% to 4·5 (2·0–10·2). This suggests that lowering the threshold does improve the ability to identify at-risk participants, but a slight reduction of specificity from 98% to 96% was observed. This suggests that
in the era of ARTs, HIV-1 genotyping is very important for both clinical management and public health surveillance for anyone living with HIV-1 anywhere in world.
Detecting low-frequency mutations
Ultrasensitive genotyping tests can improve the clinical evaluation and identification of low-frequency drug resistance mutations (LFDRM). LFDRMs, if detected robustly, can impact the efficacy of treatment protocols of ART and the outcomes. Furthermore, the level at which each drug resistance mutation is present in the virus population can play an important role. Several studies (Simen et al., 2009b, Li et al., 2011 and Cozzi-Lepri et al., 2015) evaluated the dose-dependent association between LFDRMs and the risk of virological failure of first-line NMRTI therapy. The mutational load (ie., the mutant frequency multiplied by the total HIV-1 RNA levels) may be a better predictor of virological failure (Gupta et al 2014, Goodaman et al 2011). It is well known that 1% of viruses have K103N mutation and patients carrying these mutant viruses respond to first-line Efavirenz (EFV)-based therapy if they have 100,000 copies/mL versus 1,000 copies/mL. A review (Barth et al 2010) analyzing 89 studies with 12,288 patients suggested that the most common mutations are M184V (65%) and K103N (52%). Thymidine-analog mutations (TAMs: M41L, D67N, K70R, L210W, T215Y/F, and K219Q/E) were less common, ranging from 5%–20% of patients, whereas K65R was found in 5% patients. A larger cohort study, PharmAccess African Studies to Evaluate Resistance (PASER), where 37% of the cohort received ZDV, 27% received d4T and 33.5% received TDF. Majority of patients (96%) acquired resistance during the therapy was also carried out. The most common mutations were M184V (53.5%) and K103N (28.9%). TAMs occurred in 12.7% of subjects receiving ZDV, 5% in d4T and 4.3% in TDF.
Viral tropism is another factor to be considered, as it has been demonstrated (Raymond et al., 2011; Archer et al., 2010, 2009; Tsibris et al., 2009; Westby et al., 2006) that in case of maraviroc prescription, which is a selective CCR5 co-receptor antagonist, approximately 10-15% of treatment-naïve subjects and 50% of experienced subjects have viruses that can also use a CXCR4 co-receptor. It was also shown that V3-loop 454 sequencing was a better predictor than the first version of Monogram’s phenotypic Trofile Assay in a retrospective analysis of two clinical trials of maraviroc (Swenson et al., 2011a). Deep sequencing by NGS was shown to also have better results from MERIT trial reanalysis and to be cost effective too.
In India, it was feared that the lack of resources, coupled with tuberculosis, would lead to very high HIV transmission. However, with ART rollout, transmission has been reduced by 54%. With increased levels of first-line ART comes the challenge of drug resistance. It has been reported that (Hosseinipour et al. 2013) there are predictable mutation patterns at 12 month ART in resource-limited settings. Till date, the majority of Indian national programmes have relied on clinic-immunological monitoring for the diagnosis of treatment failure, especially CD4 cell count every 6 months. An NGS based pretreatment and clinical management of HIV using the knowledge of known mutations can lead to improvements in clinical care. Meanwhile, more studies can help in better understanding acquired disease mutations for better outcomes in the future.
The author is medical scientist and former director of SGRF, Bangalore