916 resultados para HIV-1 INFECTION


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OBJECTIVES: To assess the prevalence of abnormal testosterone and gonadotropin values in HIV-infected men before and after 2 years of combination antiretroviral therapy (cART). DESIGN: Multicentre cohort of HIV-infected adults. METHODS: We identified 139 Caucasian antiretroviral-naive male patients who started zidovudine/ lamivudine-based cART that was virologically successful over a 2 year period. Ninety-seven were randomly chosen and plasma hormone determinations of free testosterone (fT) and luteinizing hormone (LH) at baseline and after 2 years of cART were evaluated. RESULTS: At baseline 68 patients (70%) had subnormal fT levels. In these, LH levels were low in 44%, normal in 47% and high in 9%. There was a trend for an association between lower CD4+ T-cell counts and hypogonadism. Most participants had normal FSH levels. No significant changes of fT, LH and FSH levels were observed after 2 years of cART. CONCLUSIONS: Low fT levels, mainly with normal or low LH levels and thus indicating secondary hypogonadism, are found in the majority of HIV-infected men and do not resolve during 2 years of successful cART.

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The dynamics of HIV-1 RNA during structured treatment interruptions (STIs) are well established, but little is known about viral proteins like p24. We studied 65 participants of an STI trial. Before the trial, continuous highly active antiretroviral therapy (HAART) had suppressed their viral load to <50 copies/mL during 6 months. They then interrupted HAART during weeks 1 through 2, 11 through 12, 21 through 22, 31 through 32, and 41 through 52. The p24 was measured by boosted enzyme-linked immunosorbent assay of plasma pretreated by efficient virus disruption and heat denaturation. At time point 0, p24 was measurable in 22 patients (34%), who had maintained a viral load <50 copies/mL for 25.4 months (median, range: 6.2-38.9 months) under HAART. Viral rebounds during 2-week STIs led to a mean p24 increase of only 0.08 to 0.19 log10 (ie, 20%-60%). Pre-HAART viral load and p24 at time 0 independently predicted p24 rebounds during the 4 2-week STIs. The p24 at time 0 and HIV-1 RNA rebound during weeks 41 through 52 independently determined the concomitant p24 rebound. An increase of p24 but not viral load during the first 8 weeks of the long STI correlated significantly with concomitant CD4(+) T cell loss. Persisting p24 despite successful HAART may reflect virus replication in reservoirs not represented by plasma viral load and has implications for the concept of therapeutic vaccination.

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OBJECTIVES: We compared androgen and gonadotropin values in HIV-infected men who did and did not develop lipoatrophy on combination antiretroviral therapy (cART). METHODS: From a population of 136 treatment-naïve male Caucasians under successful zidovudine/lamivudine-based cART, the 10 patients developing lipoatrophy (cases) were compared with 87 randomly chosen controls. Plasma levels of free testosterone (fT), dehydroepiandrosterone (DHEA), follicle-stimulating hormone and luteinizing hormone (LH) were measured at baseline and after 2 years of cART. RESULTS: At baseline, 60% of the cases and 71% of the controls showed abnormally low fT values. LH levels were normal or low in 67 and 94% of the patients, respectively, indicating a disturbance of the hypothalamic-pituitary-gonadal axis. fT levels did not significantly change after 2 years of cART. Cases showed a significant increase in LH levels, while controls showed a significant increase in DHEA levels. In a multivariate logistic regression model, lipoatrophy was associated with higher baseline DHEA levels (P=0.04), an increase in LH levels during cART (P=0.001), a lower body mass index and greater age. CONCLUSIONS: Hypogonadism is present in the majority of HIV-infected patients. The development of cART-related lipoatrophy is associated with an increase in LH and a lack of increase in DHEA levels.

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OBJECTIVE: To determine the effects of cognitive-behavioral stress management (CBSM) training on clinical and psychosocial markers in HIV-infected persons. METHODS: A randomized controlled trial in four HIV outpatient clinics of 104 HIV-infected persons taking combination antiretroviral therapy (cART), measuring HIV-1 surrogate markers, adherence to therapy and well-being 12 months after 12 group sessions of 2 h CBSM training. RESULTS: Intent-to-treat analyses showed no effects on HIV-1 surrogate markers in the CBSM group compared with the control group: HIV-1 RNA < 50 copies/ml in 81.1% [95% confidence interval (CI), 68.0-90.6] and 74.5% (95% CI, 60.4-85.7), respectively (P = 0.34), and mean CD4 cell change from baseline of 53.0 cells/microl (95% CI, 4.1-101.8) and 15.5 cells/microl (95% CI, -34.3 to 65.4), respectively (P = 0.29). Self-reported adherence to therapy did not differ between groups at baseline (P = 0.53) or at 12 month's post-intervention (P = 0.47). Significant benefits of CBSM over no intervention were observed in mean change of quality of life scores: physical health 2.9 (95% CI, 0.7-5.1) and -0.2 (95% CI, -2.1 to 1.8), respectively (P = 0.05); mental health 4.8 (95% CI, 1.8-7.3) and -0.5 (95% CI, -3.3 to 2.2) (P = 0.02); anxiety -2.1 (95% CI, -3.6 to -1.0) and 0.3 (95% CI, -0.7 to 1.4), respectively (P = 0.002); and depression -2.1 (95% CI, -3.2 to -0.9) and 0.02 (95% CI, -1.0 to 1.1), respectively (P = 0.001). Alleviation of depression and anxiety symptoms were most pronounced among participants with high psychological distress at baseline. CONCLUSION: CBSM training of HIV-infected persons taking on cART does not improve clinical outcome but has lasting effects on quality of life and psychological well-being.

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BACKGROUND: The CD4 cell count at which combination antiretroviral therapy should be started is a central, unresolved issue in the care of HIV-1-infected patients. In the absence of randomised trials, we examined this question in prospective cohort studies. METHODS: We analysed data from 18 cohort studies of patients with HIV. Antiretroviral-naive patients from 15 of these studies were eligible for inclusion if they had started combination antiretroviral therapy (while AIDS-free, with a CD4 cell count less than 550 cells per microL, and with no history of injecting drug use) on or after Jan 1, 1998. We used data from patients followed up in seven of the cohorts in the era before the introduction of combination therapy (1989-95) to estimate distributions of lead times (from the first CD4 cell count measurement in an upper range to the upper threshold of a lower range) and unseen AIDS and death events (occurring before the upper threshold of a lower CD4 cell count range is reached) in the absence of treatment. These estimations were used to impute completed datasets in which lead times and unseen AIDS and death events were added to data for treated patients in deferred therapy groups. We compared the effect of deferred initiation of combination therapy with immediate initiation on rates of AIDS and death, and on death alone, in adjacent CD4 cell count ranges of width 100 cells per microL. FINDINGS: Data were obtained for 21 247 patients who were followed up during the era before the introduction of combination therapy and 24 444 patients who were followed up from the start of treatment. Deferring combination therapy until a CD4 cell count of 251-350 cells per microL was associated with higher rates of AIDS and death than starting therapy in the range 351-450 cells per microL (hazard ratio [HR] 1.28, 95% CI 1.04-1.57). The adverse effect of deferring treatment increased with decreasing CD4 cell count threshold. Deferred initiation of combination therapy was also associated with higher mortality rates, although effects on mortality were less marked than effects on AIDS and death (HR 1.13, 0.80-1.60, for deferred initiation of treatment at CD4 cell count 251-350 cells per microL compared with initiation at 351-450 cells per microL). INTERPRETATION: Our results suggest that 350 cells per microL should be the minimum threshold for initiation of antiretroviral therapy, and should help to guide physicians and patients in deciding when to start treatment.

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OBJECTIVES: CD4 cell count and plasma viral load are well known predictors of AIDS and mortality in HIV-1-infected patients treated with combination antiretroviral therapy (cART). This study investigated, in patients treated for at least 3 years, the respective prognostic importance of values measured at cART initiation, and 6 and 36 months later, for AIDS and death. METHODS: Patients from 15 HIV cohorts included in the ART Cohort Collaboration, aged at least 16 years, antiretroviral-naive when they started cART and followed for at least 36 months after start of cART were eligible. RESULTS: Among 14 208 patients, the median CD4 cell counts at 0, 6 and 36 months were 210, 320 and 450 cells/microl, respectively, and 78% of patients achieved viral load less than 500 copies/ml at 6 months. In models adjusted for characteristics at cART initiation and for values at all time points, values at 36 months were the strongest predictors of subsequent rates of AIDS and death. Although CD4 cell count and viral load at cART initiation were no longer prognostic of AIDS or of death after 36 months, viral load at 6 months and change in CD4 cell count from 6 to 36 months were prognostic for rates of AIDS from 36 months. CONCLUSIONS: Although current values of CD4 cell count and HIV-1 RNA are the most important prognostic factors for subsequent AIDS and death rates in HIV-1-infected patients treated with cART, changes in CD4 cell count from 6 to 36 months and the value of 6-month HIV-1 RNA are also prognostic for AIDS.

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The human immunodeficiency virus-1 reverse transcriptase inhibitory activity of 2-(2,6-disubstituted phenyl)-3-(substituted pyrimidin-2-yl)-thiazolidin-4-ones have been analyzed using combinatorial protocol in multiple linear regression (CP-MLR) with several electronic and molecular surface area features of the compounds obtained from Molecular Operating Environment (MOE) software. The study has indicated the role of different charged molecular surface areas in modeling the inhibitory activity of the compounds. The derived models collectively suggested that the compounds should be compact without bulky substitutions on its peripheries for better HIV-1 RT inhibitory activity. It also emphasized the necessity of hydrophobicity and compact structural features for their activity. The scope of the descriptors identified for these analogues have been verified by extending the dataset with different 2-(disubstituted phenyl)-3-(substituted pyridin-2-yl)-thiazolidin-4-ones. The joint analysis of extended dataset highlighted the information content of identified descriptors in modeling the HIV-1 RT inhibitory activity of the compounds.

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HIV-1 sequence diversity is affected by selection pressures arising from host genomic factors. Using paired human and viral data from 1071 individuals, we ran >3000 genome-wide scans, testing for associations between host DNA polymorphisms, HIV-1 sequence variation and plasma viral load (VL), while considering human and viral population structure. We observed significant human SNP associations to a total of 48 HIV-1 amino acid variants (p<2.4 × 10−12). All associated SNPs mapped to the HLA class I region. Clinical relevance of host and pathogen variation was assessed using VL results. We identified two critical advantages to the use of viral variation for identifying host factors: (1) association signals are much stronger for HIV-1 sequence variants than VL, reflecting the ‘intermediate phenotype’ nature of viral variation; (2) association testing can be run without any clinical data. The proposed genome-to-genome approach highlights sites of genomic conflict and is a strategy generally applicable to studies of host–pathogen interaction.

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The success of combination antiretroviral therapy is limited by the evolutionary escape dynamics of HIV-1. We used Isotonic Conjunctive Bayesian Networks (I-CBNs), a class of probabilistic graphical models, to describe this process. We employed partial order constraints among viral resistance mutations, which give rise to a limited set of mutational pathways, and we modeled phenotypic drug resistance as monotonically increasing along any escape pathway. Using this model, the individualized genetic barrier (IGB) to each drug is derived as the probability of the virus not acquiring additional mutations that confer resistance. Drug-specific IGBs were combined to obtain the IGB to an entire regimen, which quantifies the virus' genetic potential for developing drug resistance under combination therapy. The IGB was tested as a predictor of therapeutic outcome using between 2,185 and 2,631 treatment change episodes of subtype B infected patients from the Swiss HIV Cohort Study Database, a large observational cohort. Using logistic regression, significant univariate predictors included most of the 18 drugs and single-drug IGBs, the IGB to the entire regimen, the expert rules-based genotypic susceptibility score (GSS), several individual mutations, and the peak viral load before treatment change. In the multivariate analysis, the only genotype-derived variables that remained significantly associated with virological success were GSS and, with 10-fold stronger association, IGB to regimen. When predicting suppression of viral load below 400 cps/ml, IGB outperformed GSS and also improved GSS-containing predictors significantly, but the difference was not significant for suppression below 50 cps/ml. Thus, the IGB to regimen is a novel data-derived predictor of treatment outcome that has potential to improve the interpretation of genotypic drug resistance tests.

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Context: In virologically suppressed, antiretroviral-treated patients, the effect of switching to tenofovir (TDF) on bone biomarkers compared to patients remaining on stable antiretroviral therapy is unknown. Methods: We examined bone biomarkers (osteocalcin [OC], procollagen type 1 amino-terminal propeptide, and C-terminal cross-linking telopeptide of type 1 collagen) and bone mineral density (BMD) over 48 weeks in virologically suppressed patients (HIV RNA < 50 copies/ml) randomized to switch to TDF/emtricitabine (FTC) or remain on first-line zidovudine (AZT)/lamivudine (3TC). PTH was also measured. Between-group differences in bone biomarkers and associations between change in bone biomarkers and BMD measures were assessed by Student's t tests, Pearson correlation, and multivariable linear regression, respectively. All data are expressed as mean (SD), unless otherwise specified. Results: Of 53 subjects (aged 46.0 y; 84.9% male; 75.5% Caucasian), 29 switched to TDF/FTC. There were reductions in total hip and lumbar spine BMD in those switching to TDF/FTC (total hip, TDF/FTC, −1.73 (2.76)% vs AZT/3TC, −0.39 (2.41)%; between-group P = .07; lumbar spine, TDF/FTC, −1.50 (3.49)% vs AZT/3TC, +0.25 (2.82)%; between-group P = .06), but they did not reach statistical significance. Greater declines in lumbar spine BMD correlated with greater increases in OC (r = −0.28; P = .05). The effect of TDF/FTC on bone biomarkers remained significant when adjusted for baseline biomarker levels, gender, and ethnicity. There was no difference in change in PTH levels over 48 weeks between treatment groups (between-group P = .23). All biomarkers increased significantly from weeks 0 to 48 in the switch group, with no significant change in those remaining on AZT/3TC (between-group, all biomarkers, P < .0001). Conclusion: A switch to TDF/FTC compared to remaining on a stable regimen is associated with increases in bone turnover that correlate with reductions in BMD, suggesting that TDF exposure directly affects bone metabolism in vivo.

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Objectives: To determine HIV-1 RNA in cerebrospinal fluid (CSF) of successfully treated patients and to evaluate if combination antiretroviral treatments with higher central nervous system penetration-effectiveness (CPE) achieve better CSF viral suppression. Methods: Viral loads (VLs) and drug concentrations of lopinavir, atazanavir, and efavirenz were measured in plasma and CSF. The CPE was calculated using 2 different methods. Results: The authors analyzed 87 CSF samples of 60 patients. In 4 CSF samples, HIV-1 RNA was detectable with 43–82 copies per milliliter. Median CPE in patients with detectable CSF VL was significantly lower compared with individuals with undetectable VL: CPE of 1.0 (range, 1.0–1.5) versus 2.3 (range, 1.0–3.5) using the method of 2008 (P = 0.011) and CPE of 6 (range, 6–8) versus 8 (range, 5–12) using the method of 2010 (P = 0.022). The extrapolated CSF trough levels for atazanavir (n = 12) were clearly above the 50% inhibitory concentration (IC50) in only 25% of samples; both patients on atazanavir/ritonavir with detectable CSF HIV-1 RNA had trough levels in the range of the presumed IC50. The extrapolated CSF trough level for lopinavir (n = 42) and efavirenz (n = 18) were above the IC50 in 98% and 78%, respectively, of samples, including the patients with detectable CSF HIV-1 RNA. Conclusions: This study suggests that treatment regimens with high intracerebral efficacy reflected by a high CPE score are essential to achieve CSF HIV-1 RNA suppression. The CPE score including all drug components was a better predictor for treatment failure in the CSF than the sole concentrations of protease inhibitor or nonnucleoside reverse transcriptase inhibitor in plasma or CSF.

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Objectives: Etravirine (ETV) is metabolized by cytochrome P450 (CYP) 3A, 2C9, and 2C19. Metabolites are glucuronidated by uridine diphosphate glucuronosyltransferases (UGT). To identify the potential impact of genetic and non-genetic factors involved in ETV metabolism, we carried out a two-step pharmacogenetics-based population pharmacokinetic study in HIV-1 infected individuals. Materials and methods: The study population included 144 individuals contributing 289 ETV plasma concentrations and four individuals contributing 23 ETV plasma concentrations collected in a rich sampling design. Genetic variants [n=125 single-nucleotide polymorphisms (SNPs)] in 34 genes with a predicted role in ETV metabolism were selected. A first step population pharmacokinetic model included non-genetic and known genetic factors (seven SNPs in CYP2C, one SNP in CYP3A5) as covariates. Post-hoc individual ETV clearance (CL) was used in a second (discovery) step, in which the effect of the remaining 98 SNPs in CYP3A, P450 cytochrome oxidoreductase (POR), nuclear receptor genes, and UGTs was investigated. Results: A one-compartment model with zero-order absorption best characterized ETV pharmacokinetics. The average ETV CL was 41 (l/h) (CV 51.1%), the volume of distribution was 1325 l, and the mean absorption time was 1.2 h. The administration of darunavir/ritonavir or tenofovir was the only non-genetic covariate influencing ETV CL significantly, resulting in a 40% [95% confidence interval (CI): 13–69%] and a 42% (95% CI: 17–68%) increase in ETV CL, respectively. Carriers of rs4244285 (CYP2C19*2) had 23% (8–38%) lower ETV CL. Co-administered antiretroviral agents and genetic factors explained 16% of the variance in ETV concentrations. None of the SNPs in the discovery step influenced ETV CL. Conclusion: ETV concentrations are highly variable, and co-administered antiretroviral agents and genetic factors explained only a modest part of the interindividual variability in ETV elimination. Opposing effects of interacting drugs effectively abrogate genetic influences on ETV CL, and vice-versa.

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Alpha interferon (IFN-α) suppresses human immunodeficiency virus type 1 (HIV-1) replication in vitro by inducing cell-intrinsic retroviral restriction mechanisms. We investigated the effects of IFN-α/ribavirin (IFN-α/riba) treatment on 34 anti-HIV-1 restriction factors in vivo. Expression of several anti-HIV-1 restriction factors was significantly induced by IFN-α/riba in HIV/hepatitis C virus (HCV)-coinfected individuals. Fold induction of cumulative restriction factor expression in CD4+ T cells was significantly correlated with viral load reduction during IFN-α/riba treatment (r2 = 0.649; P < 0.016). Exogenous IFN-α induces supraphysiologic restriction factor expression associated with a pronounced decrease in HIV-1 viremia.

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Next-generation sequencing (NGS) is a valuable tool for the detection and quantification of HIV-1 variants in vivo. However, these technologies require detailed characterization and control of artificially induced errors to be applicable for accurate haplotype reconstruction. To investigate the occurrence of substitutions, insertions, and deletions at the individual steps of RT-PCR and NGS, 454 pyrosequencing was performed on amplified and non-amplified HIV-1 genomes. Artificial recombination was explored by mixing five different HIV-1 clonal strains (5-virus-mix) and applying different RT-PCR conditions followed by 454 pyrosequencing. Error rates ranged from 0.04-0.66% and were similar in amplified and non-amplified samples. Discrepancies were observed between forward and reverse reads, indicating that most errors were introduced during the pyrosequencing step. Using the 5-virus-mix, non-optimized, standard RT-PCR conditions introduced artificial recombinants in a fraction of at least 30% of the reads that subsequently led to an underestimation of true haplotype frequencies. We minimized the fraction of recombinants down to 0.9-2.6% by optimized, artifact-reducing RT-PCR conditions. This approach enabled correct haplotype reconstruction and frequency estimations consistent with reference data obtained by single genome amplification. RT-PCR conditions are crucial for correct frequency estimation and analysis of haplotypes in heterogeneous virus populations. We developed an RT-PCR procedure to generate NGS data useful for reliable haplotype reconstruction and quantification.