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CLINICAL SCIENCE: CONCISE COMMUNICATION

CD4+ cell count, viral load, and drug resistance patterns among heterosexual breakthrough HIV infections in a study of oral preexposure prophylaxis

Chirwa, Lovemore I.a; Johnson, Jeffrey A.b; Niska, Richard W.b; Segolodi, Tebogo M.a; Henderson, Faith L.b; Rose, Charles E.b; Li, Jin-fenb; Thigpen, Michael C.b; Matlhaba, Onkabetsea; Paxton, Lynn A.b; Brooks, John T.b

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doi: 10.1097/QAD.0000000000000102
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Abstract

Introduction

Antiretroviral therapy for HIV-1 infection reduces HIV RNA viral load and thereby increases CD4+ cell count, leading to reduced incidence of opportunistic infections, decreased mortality, and improved well being and functioning [1]. We and others have recently demonstrated that preexposure prophylaxis (PrEP) using antiretroviral agents significantly reduces HIV acquisition among persons at high risk for HIV infection, including both MSM [2] and young heterosexual men and women [3,4].

Data from animal modeling demonstrated that the level of viremia after HIV infection was blunted in macaques administered PrEP compared with those given placebo [5], suggesting the potential for a degree of immune preservation and reduced acute pathologic effects. Here we evaluated plasma HIV RNA viral loads and absolute CD4+ cell counts (CD4+ cell count) following the estimated date of seroconversion among participants in the TDF/FTC Oral HIV Prophylaxis Trial (TDF2 study) [4]. We compared values from seroconverters who had been assigned to receive the combination of oral tenofovir (TDF) and emtricitabine (FTC) with seroconverters assigned to receive placebo. We also examined for evidence of HIV-1 drug resistance in participants with breakthrough infections.

Methods

After enrollment, HIV-negative study participants were tested monthly for incident HIV infection. Study medication was stopped when HIV infection was diagnosed. Seroconverters were referred for clinical care and followed an additional year with scheduled quarterly viral load and CD4+ cell count assessments. We used log10 transformed viral loads and CD4+ cell counts to conduct all analyses; values were backtransformed to the original scale if necessary. We estimated the Pearson correlation between viral loads and CD4+ cell counts, and then modeled viral load and CD4+ cell count individually using linear mixed-effects models with the participant treated as a random effect. These models were used to obtain the geometric means for viral load and CD4+ cell count following seroconversion; a type III F-test was used to test whether there were treatment differences. To estimate treatment differences and trends across time since seroconversion, our final analysis used a bivariate random-effects model with the participant treated as a random effect to account for correlation between viral load and CD4+ cell count. Our base bivariate model included separate intercepts and slopes for each combination of treatment group (i.e. TDF-FTC and placebo) and outcome (i.e. viral load and CD4+ cell count) and accounted for the correlation between viral load and CD4+ cell count. For our bivariate model, we plotted the regression lines over the scatterplot of observed values and included 95% confidence bands.

Drug resistance mutations have the potential to lessen virus replicative capacity, aside from their impact on subsequent therapy. Therefore, to document any evidence of antiretroviral drug resistance, we assessed HIV resistance mutations in seroconverters utilizing both bulk sequencing and a sensitive mutation-specific PCR assay that can identify FTC (M184V) and TDF (K65R, K70E) resistance mutations in reverse transcriptase at frequencies below what is detectable by bulk sequencing [6,7].

Results

Among the 1203 participants who were provided drug in the TDF2 study, there were 36 HIV infections of which 33 occurred during the study (three seroconverters were retrospectively found to be acutely HIV infected at study entry): nine were among the 601 participants assigned to receive TDF-FTC and 24 infections among the 599 participants assigned to receive placebo [4]. The nine participants in the TDF-FTC arm contributed 12 CD4+ cell counts and 16 viral loads to our analysis, whereas the 24 participants in the placebo arm contributed 45 CD4+ cell counts and 61 viral loads. No patients had initiated antiretroviral therapy at the time these CD4+ cell count and viral load values were measured.

The model-estimated geometric mean of the CD4+ cell counts was 500 cells/μl [95% confidence interval (CI) 378–661] for the TDF-FTC group and 466 cells/μl (CI 396–549) for the placebo group (P = 0.66). The model-estimated viral load geometric mean was 9394 copies/ml (CI 3455–25 541) for the TDF-FTC group and 26 393 copies/ml (CI 15 012–46 403) for the placebo group (P = 0.08). The Pearson's correlation for CD4+ cell count and viral load values on the log10 scale showed only a slight negative correlation of −0.27. Although the base model fitted line for the TDF-FTC group's viral load values appeared slightly lower than the viral load values for the placebo group (Fig. 1), the difference between the slopes and intercepts of TDF-FTC and placebo group for viral load was not significant.

Fig. 1
Fig. 1:
Scatterplots of the log10 of plasma HIV RNA viral loads and CD4+ cell counts since HIV seroconversion for TDF/FTC Oral HIV Prophylaxis Trial (TDF2) participants separately for the tenofovir-emtricitabine group (n = 9) in red and placebo group (n = 24) in blue.The solid lines are the fitted regression lines and the dashed lines are the 95% confidence limits of the corresponding fitted line. The data points of the two individuals who had trace levels of antiretroviral drug around the time of seroconversion are indicated by large red diamonds. TDF-FTC, tenofovir-emtricitabine.

Bulk sequencing and sensitive PCR assays of plasma virus from the 33 participants who acquired HIV infection during the study identified no resistance mutations in their first RNA-positive samples or in any of their samples from subsequent study visits. One participant in the placebo group had low levels (<1%) of the K65R mutation, a level of expression attributable to replication error at and around codon 65 that has been observed with antiretroviral-naive HIV subtype C infections [7]. Three participants with acute wild-type HIV infection tested falsely negative at entry screening and were enrolled in the study; one was assigned to receive TDF-FTC and continued receiving medication until HIV infection was diagnosed at the month 7 study visit. Retrospective testing of stored specimens indicated that this participant developed the M184V mutation 1 month after study entry and the A62V and K65R mutations between 4 and 7 months after study entry; all mutations were at high levels.

Discussion

We observed no differences in viral load or CD4+ cell count set points or trajectories up to 120 weeks after estimated date of seroconversion among TDF2 study participants assigned to receive TDF-FTC compared with participants assigned to receive placebo. Although the viral load geometric mean was lower for the TDF-FTC group, this difference was not statistically significant. We found that exclusion of the four placebo data points which occurred after the period of TDF-FTC sampling, when further viral load decline might have influenced the slope for placebos, in fact did not significantly alter the viral load trend for the placebo group. A study comparing breakthrough SIV/HIV chimeric virus (SHIV) infections in macaques exposed to either subcutaneous FTC alone (n = 3) or oral TDF-FTC (n = 3) with infections in untreated macaques observed a blunted viremia in the breakthrough infections of animals known to have drug [5]. Thus, the statistically insignificant lower viremia we observed in TDF-FTC seroconverters may imply insufficient antiviral activity, possibly reflecting low adherence to daily PrEP dosing in those participants. However, the number of observations was few and may also have been insufficient to detect a small but potentially significant difference in viral load set points.

In this study with few breakthrough infections and monthly monitoring for infection, seroconversion on daily oral TDF-FTC did not induce detectable resistance to these antiretrovirals. Moreover, the absence or trace levels of antiretrovirals in the breakthroughs would have made emergence of drug resistance unlikely. Hence, the viral load and CD4+ cell counts of seroconverters assigned TDF-FTC were not influenced by viral replicative capacity that was diminished due to drug resistance. Whether longer drug exposures following infection as a result of less-frequent infection monitoring might provide greater opportunities for resistance to emerge is not known; however, our findings suggest that acquiring infection while provided PrEP does not necessarily promote rapid selection of drug resistance.

As noted, the primary limitation to our analyses is the few seroconverters in the TDF-FTC arm. Although the study demonstrated the efficacy of this oral intervention, it did not provide sufficient data to detect significant differences in viral load or CD4+ cell count for persons who seroconverted while receiving TDF-FTC PrEP compared with persons receiving placebo. Likewise, although it is reassuring that few persons receiving TDF-FTC seroconverted after enrollment and among those no drug resistance was identified, the outcomes must be interpreted cautiously in light of the fact that only four of the nine TDF-FTC participants were on the study drug at the time of seroconversion.

Initiating PrEP in persons with undiagnosed acute infection remains a concern vis-à-vis antiretroviral resistance, as was seen in the infected participant who was nonreactive at baseline and continued PrEP for 7 months. Although the numbers of acute seroconverters enrolled in our study and others were small, an emphasis on repeat preintervention HIV testing may help prevent exposure of HIV-infected person to suboptimal antiretroviral therapy and the risk of developing antiretroviral resistance. It is worth noting that the participant who was undiagnosed at baseline and selected for drug resistance in our study responded well to protease inhibitor-based alternative therapy. Finally, additional studies, such as larger demonstration projects of PrEP administered outside of a randomized clinical trial, are needed to better quantify the risk of developing antiretroviral resistance among persons who seroconvert while prescribed PrEP. Such studies will also help to more fully elucidate whether persons who seroconvert while taking PrEP experience blunted peak viremia and viral load set points, and subsequently have reduced morbidity and decreased risk of onward HIV transmission, compared with persons who become HIV-infected while not taking PrEP.

Acknowledgements

L.I.C., T.M.S., and J.A.J. conceived and designed this substudy; R.W.N. and J.T.B. provided critical review; L.I.C., T.M.S., O.M., J.L., J.A.J., and C.E.R. acquired data; J.A.J., C.E.R., and F.L.H. analyzed data; C.E.R. performed the statistical analyses; L.I.C., J.A.J., T.M.S., F.L.H., C.E.R., J.L., O.M., M.C.T., J.T.B., and L.A.P. aided in drafting the article and approved the final version.

The findings and conclusions of this article are those of the authors and do not necessarily represent the official views of the Centers for Disease Control and Prevention.

This work was supported by the Centers for Disease Control and Prevention and the National Institutes of Health; TDF2 ClinicalTrials.gov number, NCT00448669.

Conflicts of interest

J.A.J. is an author on patents for the mutation-specific PCR assays. All other authors have no conflicts to declare.

References

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Keywords:

CD4+ cell; HIV drug resistance; HIV seroconversion; oral preexposure prophylaxis; viral load

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