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Dynamics of seminal plasma HIV-1 decline after antiretroviral treatment

2001· article· en· W1975601959 on OpenAlexaff
Stephen Taylor, Neil M. Ferguson, Patricia A. Cane, Roy M. Anderson, Deenan Pillay

Bibliographic record

VenueAIDS · 2001
Typearticle
Languageen
FieldImmunology and Microbiology
TopicHIV Research and Treatment
Canadian institutionsInstitute of Infection and Immunity
Fundersnot available
KeywordsHuman immunodeficiency virus (HIV)Antiretroviral therapyMedicineANTIRETROVIRAL AGENTSAntiretroviral treatmentVirologyViral load

Abstract

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High levels of extracellular and cellular HIV-1 can be detected in the semen of infected men, and are implicated in the sexual transmission of this virus. Cross-sectional studies have demonstrated the presence of semen virus at all stages of infection, although the level of extracellular viral RNA is generally lower (approximately 1 log10) than blood plasma levels [1,2]. The semen viral load, like plasma virus, is reduced by highly active antiretroviral therapy (HAART). Antiviral therapy appears to be the most significant determinant of the presence of detectable extracellular virus in the male genital tract [1,3–5]. This is likely to be the key mechanism by which HAART reduces HIV-1 transmission, although proviral DNA may continue to be detectable in both the semen and blood during HAART [6,7], despite cell-free virus being below the level of detection. Analysis of the dynamics of viral suppression after the initiation of antiviral therapy has yielded important quantitative measures of the parameters determining viral production in the blood compartment. However, there are no data available on the dynamics of HIV-1 in the male genital tract. This is partly due to the difficulties in obtaining multiple sequential samples from appropriate volunteers. In order to explore the potential of this approach, we undertook frequent sampling of semen from two HIV-1-infected patients initiating HAART, both of whom had high levels of seminal plasma viral RNA at baseline, in order to determine the short-term kinetics of virus suppression in semen compared with blood. One patient had taken a 16 month drug holiday after the failure of previous therapy with multiple resistance-associated mutations, also allowing an assessment of the efficacy of salvage therapy on semen virus in this context. HIV-1-infected patients attending Birmingham Heartlands Hospital Department of Sexual Medicine were assessed for seminal plasma viral load in parallel with routine blood viral load monitoring. Two patients were identified with high viral loads in both compartments, in which the initiation of antiretroviral therapy was indicated. Patient 1 had previously received multiple antiviral therapies, but had stopped all medication 16 months previously. The therapy chosen for re-initiation was guided by the genotypic drug resistance results available from the time of previous antiretroviral failure. He started on didanosine (400 mg a day), lamivudine (150 mg twice a day), adefovir (60 mg a day), efavirenz (600 mg a day) and hydroxyurea (500 mg twice a day). Patient 2 was antiretroviral drug naive (less than 7 days therapy previously) at entry into the study, and was initiated on zidovudine (300 mg twice a day), lamivudine (150 mg twice a day) and nevirapine (200 mg a day – increasing after 2 weeks). Blood and semen samples were obtained just before starting therapy and then at 2–3 day intervals for the first 14 days. Approximately 1–2 weekly samples were obtained thereafter for patient 1, whereas patient 2 did not provide any further samples. HIV-1-RNA quantitation was undertaken by nucleic acid sequence-based amplification, previously shown to be most appropriate for assessing viral load in semen samples [8]. Taking into account the volume of sample required in the assay, the limit of detection was 400 copies/ml for blood plasma and 800 copies/ml for seminal plasma. The patients enrolled in this study provided written, informed consent, and the study protocol was approved by the Ethics Committee of Birmingham Heartlands Hospital. A simple biphasic exponential decay model was fitted to the plasma and semen viral load data, of the following form:EQUATION Therefore A and B represent the approximate log10 viral load from which the first and second phases of the decay begin (the starting conditions), whereas a and b are the slopes of these decay phases (in units of log10 virions/ml per day). These slopes can be interpreted as reflecting the average half-lives of the actively infected and persistently/latently infected CD4 cell reservoirs, which can be calculated from the slope parameters thus:t1/2 = ln 2/(a ln 10). A non-mechanistic two-phase model was used because the limited volume of data available makes robust parameter estimation of more complex dynamical models problematical [9]. Maximum likelihood methods were used to estimate parameters, assuming viral load measurements are log-normally distributed with a ± 0.5 log10 measurement error. The most parsimonious biphasic decay model describing all the data for both patients is the five parameter form given below:EQUATION The parameter C represents the mean number of logs semen viral load is below plasma viral load in patient 2. Viral decay in patient 1 was distinctly biphasic in both blood and semen (Fig. 1a), whereas the shorter period of sampling for patient 2 only allowed the demonstration of the first phase of decay (Fig. 1b). No significant differences between viral decay in blood and blood and semen for either patient were observed, and a first phase decay of 0.27 log10/ml per day and second phase decay (only for patient 1) of 0.027 log10/ml per day were determined. These parameters translate into virus halflives of 1.1 and 12.1 days for first and second phase decay, respectively. The fit of this model to the four viral load time series is illustrated in Fig. 1, which shows the parallel decay profiles of plasma and semen viral load in both patients.Fig. 1.: Blood plasma and seminal plasma viral load reductions after the initiation of antiretroviral therapy for patients 1 (a) and 2 (b). Viral load at each time point is given as copies/ml with a variation of 0.5 log10. The model described in the methods was also applied to these data. (a) —&◆— Plasma; —░— semen; —□— model. (b) —&◆— Plasma; —░— semen; —□— plasma model; —▵— semen model.We have demonstrated the feasibility of the frequent sampling of semen in order to investigate the dynamics of HIV replication in the male genital tract. We show potent inhibition of extracellular viral shedding in the semen in both a drug-naive patient, and an antiretroviral-experienced patient. This further illustrates the potential of HAART to reduce the sexual transmission of HIV infection. However, this observation must be tempered by the possibility that cellular provirus represents the major source of transmitted virus. The estimates of first and second phases of virus decline in blood plasma and semen plasma suggest that similar dynamics of virus replication are at play within these two compartments, at least for the two patients investigated. Future studies on viral kinetics in the genital tract should assess the impact of different antiretroviral regimens, and monitor changes in cellular proviral DNA and replication-competent virus over a longer period of time. Stephen Taylora Neil M. Fergusonb Patricia A. Canea Roy M. Andersonb Deenan Pillaya

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.357
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.002

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.010
GPT teacher head0.261
Teacher spread0.251 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations16
Published2001
Admission routes1
Has abstractyes

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