The effect of specific drug mutations on the replication capacity of HIV-1 has been extensively studied, mainly in vitro, through site-directed mutagenesis experiments [1–4]. Nearly all drug mutations studied appear to impair replication capacity to some extent, although this depends on the individual mutation; furthermore, the fitness cost of individual mutations can be decreased or enhanced by the presence of other resistance mutations (mutational interactions) and by other changes in the viral genome that do not directly confer resistance .
Transmitted drug resistance (TDR) is a problem in all settings in which there has been extensive use of antiretroviral therapy (ART). Estimated prevalence rates have varied widely by place and time, although a recent report on European patients suggests the rate may be stabilizing at around 10% . The reduced replication capacity of viruses expressing drug-resistant mutations (particularly M184V) implies that patients with TDR might be expected, on average, to have lower HIV RNA viral load than patients infected with a wild-type virus. The few studies which have examined this issue have generally not confirmed this expected association, although the small sample sizes limit statistical power and have precluded the examination of the effect of specific mutations [7–9].
Our aim was to investigate the association between TDR – both in terms of drug-class specific and individual mutations – and pre-therapy viral load in a large group of HIV-infected patients in the UK.
Pol gene sequences were retrieved from the UK HIV Drug Resistance Database, which collates virtually all genotypic resistance tests conducted as part of routine care in the UK . Demographic and clinical data were obtained via linkage to the UK CHIC study [11,12] and other clinical databases. Eligible patients had a resistance test performed between 1997 and 2007 while ART-naive, were aged 16 years or older, and had a viral load and CD4 cell count measurement within 6 months of their first resistance test and before starting ART; the first resistance test per patient was analysed. Patients with an undetectable viral load (<50 copies/ml) were excluded as it may indicate unrecorded treatment use. TDR was defined using the list of surveillance drug resistance mutations by Shafer et al. . Subtype was inferred from the pol sequences using the REGA HIV subtyping algorithm . The version of viral load assay was inferred from the date of test and the clinical centre when it was not directly recorded.
All analyses were carried out in Stata version 10.1 (StataCorp, College Station, Texas, USA). Interval censored regression (intreg command) was used to account for right censoring of a few (154, 2%) viral load measurements. Adjustment was performed for CD4 cell count (as a surrogate for duration of infection, although imperfect ), viral subtype, ethnicity, risk group, sex, age, calendar year, clinical centre, and viral load assay; many of these factors have been shown to be related to viral load and were thus potential confounders [16–20]. However, as viral load influences the CD4 cell count an additional model was fitted excluding this potential confounder. Finally, we conducted sensitivity analyses limited to patients with a CD4 cell count greater than 400 or 500 cells/μl. The rationale being that a higher CD4 cell count may be regarded as an indicator of a shorter interval between the date of HIV infection and date of the resistance test, and therefore of a lower probability that transmitted mutants might have been overgrown by wild-type virus and escaped detection in the resistance test.
The analysis of individual mutations included those detected in more than 20 patients, and grouped those occurring at lower frequencies (≤20) within class. The model was adjusted for the effect of each mutation as well as for the factors listed above.
A total of 7994 patients were included. The majority of patients (6037; 76%) had a viral load measurement on the same day as the resistance test; for the remaining 1957 patients the median [interquartile range (IQR)] time between the resistance test and viral load measurement was 2.1 (0.4, 5.0) weeks. The date of HIV diagnosis was known for 7603 (95%) patients, whose median (IQR) time between diagnosis and first resistance test was 1.6 (0.2, 30.5) months. Mean (SD) and median (IQR) viral load at the time of resistance testing were 4.60 (0.82) and 4.65 (4.06, 5.18) log10 copies/ml, respectively. The observed distribution of CD4 cell counts [mean (SD) 361 (233); median (IQR) 329 (198, 490) cells/μl] suggests that most patients had an established rather than a recent infection . Five thousand, four hundred and sixty-nine (68%) patients were infected with a subtype B virus and 1072 (13%) with a subtype C virus; other subtypes occurred at a frequency of 5% or less. Main exposure groups were homosexual men (4926, 62%), heterosexual women (1273, 16%), and heterosexual men (820, 10%). The mean age at time of test was 36 years (SD 9). Most viral load measurements were obtained using the Bayer bDNA Quantiplex v2.0 (717, 9%) or v3.0 (3704, 46%), or Roche Amplicor v1.5 (2801, 35%) assays.
Seven hundred and nine (9%) patients had TDR: 604 (85% of those with TDR) had resistance to one drug class only [350 nucleos(t)ide reverse transcriptase inhibitors (NRTIs), 164 non-nucleoside reverse transcriptase inhibitors (NNRTIs), 90 protease inhibitors (PIs)], 77 (11%) to two classes (42 NRTIs/NNRTIs, 31 NRTIs/PIs, 4 NNRTIs/PIs), and 28 (4%) had resistance to all three classes. Mean (SD) viral load in patients without TDR was 4.60 (0.82) log10 copies/ml (Table 1). Presence of resistance to a single drug class (without consideration of specific mutations being present) was not associated with viral load, in either univariate or multivariate analysis (Table 1). However, patients with resistance to two or three classes had a significantly lower mean viral load [−0.17 log10 copies/ml (95% CI −0.33 to −0.01), 32% lower (95% CI 2 to 53%), P = 0.04]. This effect was slightly strengthened in multivariate analysis [−0.21 log10 copies/ml (95% CI −0.34 to −0.16), 38% lower (95% CI 31 to 54%), P = 0.004] (Table 1). The additional model excluding CD4 cell count as a potential confounder (Table 1), and the sensitivity analyses (data not shown) limited to the 3005 and 1912 patients with CD4 cell count greater than 400 and 500 cells/μl, respectively, showed broadly similar results.
Analysis of individual mutations is shown in Fig. 1. No significant differences were observed for any mutation apart from M184V/I, which was associated with a significantly lower viral load [adjusted mean difference −0.33 log10 copies/ml (95% CI −0.54 to −0.11), 53% lower (95% CI 22 to 71%), P = 0.002] compared to wild-type virus. The mean (SD) CD4 cell count in patients with M184V/I was 304 (235) cells/μl, slightly lower than the overall mean of 361 (P = 0.06). Of the 61 patients with M184V/I (55 V, 4I, 2 V/I), eight (13%) had no other mutations, nine (15%) had it in conjunction with other NRTI mutation(s) only; of the remaining 44 (72%) patients, 27 had NNRTI mutation(s), eight had PI mutation(s), and nine had both NNRTI and PI mutations. Further stratified analyses suggested that the effect of M184V/I on viral load was not influenced by co-existing mutations (data not shown). An additional model which included presence of M184V/I and drug class-specific mutations revealed that the previous association between multiple drug class resistance and viral load was entirely mediated by the M184V/I mutation (Table 1).
It is well established that maintaining the M184V mutation by continued use of lamuvidine in antiretroviral-experienced patients reduces viral load by approximately 0.5 log10 copies/ml [22,23]. However, it has been difficult to disentangle the effect of the mutation per se from a residual drug effect. To our knowledge, this is the first study of the same phenomenon in antiretroviral-naïve patients, with a mean difference of 0.33 log10 copies/ml (53% relative reduction) between patients whose virus contains M184V/I mutation compared with wild-type virus. This finding is consistent with in-vitro data showing that viruses co-expressing M184V have markedly reduced fitness, although the degree of this seems to depend on the co-expression of other mutations . Importantly, a viral load difference of 0.33 log10 copies/ml could translate to a clinically significant reduction in the rate of disease progression and in the probability of viral transmission [24,25].
It is important to stress that as most patients in this analysis were likely to have an established infection, some patients may have been infected by a resistant virus which subsequently reverted to wild-type prior to resistance testing. The M184V/I mutation, in particular, does not persist effectively in the newly infected host [3,26], and is greatly under-represented in treatment-naïve populations compared with treatment-experienced populations . We are therefore likely to have observed a selected group of patients among those originally infected with M184V/I-containing viruses and to have underestimated the extent to which this mutation reduces replication capacity. These patients may have been infected with viruses which were fitter in other regions of the genome viruses (which also facilitated its transmission) or have acquired compensatory changes during early rounds of viral replication.
Apart from M184V/I, no other resistance mutation, either individually or collectively within drug class, was found to have an impact on viral load. As discussed for the M184V/I mutation, initially resistant viruses may have reverted to wild-type and masked a genuine effect of TDR on viral load. However, our sensitivity analyses restricted to patients with high CD4 cell counts partly alleviate this concern and there is increasing evidence that some important mutations may persist for several years [3,26,28]. One exception to this is the T215F/Y mutation, which has a severe fitness cost and rapidly mutates to other 215 variants in untreated individuals [28–30]. It is possible that patients harbouring T215F/Y were sampled unusually close to the time of seroconversion or that compensatory changes in pol or other genetic regions occur relatively easily for TAMs.
Our findings of no effect of TDR on pre-therapy viral load (M184V/I aside) are generally consistent with other reports, but the number of patients analysed with TDR (n = 709) was a factor of magnitude higher than other studies (range 9–77 patients) [7–9,31]. Intriguingly, one study of recently infected patients found higher viral loads among patients who harboured NNRTI-resistant viruses , although the same study group found no relationship with reduced replication capacity . Our results suggest this is likely to be a chance finding.
The authors do not have any association that might pose a conflict of interest.
H.C., D.P., L.H. and D.D. designed the study. L.H. did the data analysis. L.H. and D.D. wrote the first draft of the manuscript. All authors made substantive comments on the different revisions of the manuscript.
UK Collaborative Group on HIV Drug Resistance: Steering Committee: Jane Anderson, Homerton University Hospital, London; David Asboe, Anton Pozniak, Chelsea & Westminster Hospital, London; Sheila Burns, Royal Infirmary of Edinburgh; Sheila Cameron, Gartnavel General Hospital, Glasgow; Patricia Cane, Health Protection Agency, Porton Down; Ian Chrystie, Guy's and St. Thomas' NHS Foundation Trust, London; Duncan Churchill, Brighton and Sussex University Hospitals NHS Trust; Duncan Clark, St Bartholomew's and The London NHS Trust; Valerie Delpech, Deenan Pillay, Health Protection Agency, Centre for Infections, London; Linda Lazarus, Expert Advisory Group on AIDS Secretariat, Health Protection Agency, London; David Dunn, Esther Fearnhill, Hannah Castro (nee Green), Kholoud Porter, MRC Clinical Trials Unit, London; Mark Zuckerman, King's College Hospital, London; Anna Maria Geretti, Royal Free NHS Trust, London; Paul Kellam, Deenan Pillay, Andrew Phillips, Caroline Sabin, Royal Free and University College Medical School, London; David Goldberg, Health Protection Scotland, Glasgow; Mark Gompels, Southmead Hospital, Bristol; Antony Hale, Leeds Teaching Hospitals NHS Trust; Steve Kaye, St. Mary's Hospital, London; Svilen Konov, Community Advisory Board; Andrew Leigh-Brown, University of Edinburgh; Nicola Mackie, St. Mary's Hospital, London; Chloe Orkin, St. Bartholomew's Hospital, London; Erasmus Smit, Health Protection Agency, Birmingham Heartlands Hospital; Peter Tilston, Manchester Royal Infirmary; Ian Williams, Mortimer Market Centre, London; Hongyi Zhang, Addenbrooke's Hospital, Cambridge
Participating laboratories: Addenbooke's Hospital, Cambridge (Hongyi Zhang); Department of Virology, St Bartholomew's and The London NHS Trust (Duncan Clark, Ines Ushiro-Lumb, Tony Oliver, David Bibby); Belfast Health and Social Care Trust (Suzanne Mitchell); HPA Birmingham Public Health Laboratory (Erasmus Smit); Chelsea and Westminster Hospital, London (Adrian Wildfire); King's College Hospital, London (Melvyn Smith); Royal Infirmary of Edinburgh (Jill Shepherd); West of Scotland Specialist Virology Lab Gartnavel, Glasgow (Alasdair MacLean); Guy's and St. Thomas' NHS Foundation Trust, London (Ian Chrystie); Leeds Teaching Hospitals NHS Trust (Diane Bennett); Specialist Virology Centre, Liverpool (Mark Hopkins) and Manchester (Peter Tilston); Department of Virology at Royal Free Hospital, London (Clare Booth, Ana Garcia-Diaz); St Mary's Hospital, London (Steve Kaye); University College London Hospitals (Stuart Kirk)
Funding: The UK HIV Drug Resistance Database is partly funded by the Department of Health; the views expressed in the publication are those of the authors and not necessarily those of the Department of Health. Additional financial support is provided by Boehringer Ingelheim; Bristol-Myers Squibb; Gilead; Roche; Tibotec, a division of Janssen-Cilag Ltd.
The UK Collaborative HIV Cohort (UK CHIC) Study Group: Steering Committee: Jonathan Ainsworth, Jane Anderson, Abdel Babiker, David Dunn, Martin Fisher, Brian Gazzard (Chair), Richard Gilson, Mark Gompels, Teresa Hill, Margaret Johnson, Clifford Leen, Chloe Orkin, Andrew Phillips, Deenan Pillay, Kholoud Porter, Frank Post, Caroline Sabin, Tariq Sadiq, Achim Schwenk, John Walsh, Valerie Delpech.
Central Co-ordination: Royal Free NHS Trust and RFUCMS, London (Loveleen Bansi, Teresa Hill, Andrew Phillips, Caroline Sabin); Medical Research Council Clinical Trials Unit (MRC CTU), London (David Dunn, Adam Glabay, Kholoud Porter).
Participating Centres: Barts and The London NHS Trust, London (Chloe Orkin, Kevin Jones, Claudio Fassio, James Hand, Carl de Souza); Brighton and Sussex University Hospitals NHS Trust (Martin Fisher, Nicky Perry, Stuart Tilbury, Duncan Churchill); Chelsea and Westminster Hospital NHS Trust, London (Brian Gazzard, Ben Hodgkinson, Sundhiya Mandalia); Health Protection Agency – Centre for Infections London (HPA) (Valerie Delpech); Homerton University Hospital NHS Trust, London (Jane Anderson, Meaghan Kall); King's College Hospital, London (Frank Post, Hardik Korat, Lucy Campbell, Fowzia Ibrahim, Chris Taylor, Mary Poulton).
Medical Research Council Clinical Trials Unit (MRC CTU), London (Abdel Babiker, David Dunn, Adam Glabay, Kholoud Porter); Mortimer Market Centre, Royal Free and University College Medical School (RFUCMS), London (Richard Gilson, Emmanuel Mubwandarikwa, Annie Wilkinson, Ian Williams); North Middlesex University Hospital NHS Trust, London (Achim Schwenk); Royal Free NHS Trust and RFUCMS, London (Margaret Johnson, Mike Youle, Fiona Lampe, Colette Smith, Helen Grabowska, Clinton Chaloner, Dewi Ismajani Puradiredja, Loveleen Bansi, Teresa Hill, Andrew Phillips, Caroline Sabin); St. Mary's Hospital, London (John Walsh, Jonathan Weber, Joceline Cook, Mark Carder); The Lothian University Hospitals NHS Trust, Edinburgh (Clifford Leen, Alan Wilson); North Bristol NHS Trust (Mark Gompels, Debbie Dooley).
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