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The individualized genetic barrier predicts treatment response in a large cohort of HIV-1 infected patients.

ABSTRACT: 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.

SUBMITTER: Beerenwinkel N

PROVIDER: S-EPMC3757085 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

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The individualized genetic barrier predicts treatment response in a large cohort of HIV-1 infected patients.

Beerenwinkel Niko N Montazeri Hesam H Schuhmacher Heike H Knupfer Patrick P von Wyl Viktor V Furrer Hansjakob H Battegay Manuel M Hirschel Bernard B Cavassini Matthias M Vernazza Pietro P Bernasconi Enos E Yerly Sabine S Böni Jürg J Klimkait Thomas T Cellerai Cristina C Günthard Huldrych F HF

PLoS computational biology 20130829 8

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 genet ...[more]

PMID: 24009493

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Project description:IntroductionResponse to antiretroviral therapy (ART) among individuals infected with HIV-2 is poorly described. We compared the immunological response among patients treated with three nucleoside reverse-transcriptase inhibitors (NRTIs) to boosted protease inhibitor (PI) and unboosted PI-based regimens in West Africa.MethodsThis prospective cohort study enrolled treatment-naïve HIV-2-infected patients within the International Epidemiological Databases to Evaluate AIDS collaboration in West Africa. We used mixed models to compare the CD4 count response to treatment over 12 months between regimens.ResultsOf 422 HIV-2-infected patients, 285 (67.5%) were treated with a boosted PI-based regimen, 104 (24.6%) with an unboosted PI-based regimen and 33 (7.8%) with three NRTIs. Treatment groups were comparable with regard to gender (54.5% female) and median age at ART initiation (45.3 years; interquartile range 38.3 to 51.8). Treatment groups differed by clinical stage (21.2%, 16.8% and 17.3% at CDC Stage C or World Health Organization Stage IV for the triple NRTI, boosted PI and unboosted PI groups, respectively, p=0.02), median length of follow-up (12.9, 17.7 and 44.0 months for the triple NRTI, the boosted PI and the unboosted PI groups, respectively, p<0.001) and baseline median CD4 count (192, 173 and 129 cells/µl in the triple NRTI, the boosted PI and the unboosted PI-based regimen groups, respectively, p=0.003). CD4 count recovery at 12 months was higher for patients treated with boosted PI-based regimens than those treated with three NRTIs or with unboosted PI-based regimens (191 cells/µl, 95% CI 142 to 241; 110 cells/µl, 95% CI 29 to 192; 133 cells/µl, 95% CI 80 to 186, respectively, p=0.004).ConclusionsIn this observational study using African data, boosted PI-containing regimens had better immunological response compared to triple NRTI combinations and unboosted PI-based regimens at 12 months. A randomized clinical trial is still required to determine the best initial regimen for treating HIV-2 infected patients.

Project description:BackgroundInfection with human immunodeficiency virus type 1 (HIV) typically results from transmission of a small and genetically uniform viral population. Following transmission, the virus population becomes more diverse because of recombination and acquired mutations through genetic drift and selection. Viral intrahost genetic diversity remains a major obstacle to the cure of HIV; however, the association between intrahost diversity and disease progression markers has not been investigated in large and diverse cohorts for which the majority of the genome has been deep-sequenced. Viral load (VL) is a key progression marker and understanding of its relationship to viral intrahost genetic diversity could help design future strategies for HIV monitoring and treatment.MethodsWe analysed deep-sequenced viral genomes from 2,650 treatment-naive HIV-infected persons to measure the intrahost genetic diversity of 2,447 genomic codon positions as calculated by Shannon entropy. We tested for associations between VL and amino acid (AA) entropy accounting for sex, age, race, duration of infection, and HIV population structure.ResultsWe confirmed that the intrahost genetic diversity is highest in the env gene. Furthermore, we showed that mean Shannon entropy is significantly associated with VL, especially in infections of >24 months duration. We identified 16 significant associations between VL (p-value<2.0x10-5) and Shannon entropy at AA positions which in our association analysis explained 13% of the variance in VL. Finally, equivalent analysis based on variation in HIV consensus sequences explained only 2% of VL variance.ConclusionsOur results elucidate that viral intrahost genetic diversity is associated with VL and could be used as a better disease progression marker than HIV consensus sequence variants, especially in infections of longer duration. We emphasize that viral intrahost diversity should be considered when studying viral genomes and infection outcomes.Trial registrationSamples included in this study were derived from participants who consented in the clinical trial, START (NCT00867048) (23), run by the International Network for Strategic Initiatives in Global HIV Trials (INSIGHT). All the participant sites are listed here: http://www.insight-trials.org/start/my_phpscript/participating.php?by=site.

Project description:OBJECTIVE:An epidemic of acute hepatitis C virus (HCV) infection in HIV-positive men-who-have-sex-with-men (MSM) is emerging in Europe, Australia and the USA. The aim of this study was to characterise the natural history of primary HCV in this setting and to assess host and viral factors which predict spontaneous clearance. METHODS:This prospective longitudinal cohort study was carried out in 112 HIV-positive patients who were followed in a single centre (the St Mary's Acute HCV Cohort). Plasma and peripheral blood mononuclear cells (PBMCs) were obtained at monthly intervals for 3 months and at 3-monthly intervals thereafter for a median of 45 months (IQR = 29-69 months). The primary end point was spontaneous clearance of HCV. Cox regression was used to assess the impact of clinical and virological variables on outcome, including liver function, CD4 count, rate of HCV RNA decline, T cell response and clonal sequence evolution within the HCV E2 envelope gene. RESULTS:15% of patients cleared HCV spontaneously, while 85% progressed towards chronicity. The latter group included a significant proportion of 'fluctuating' progressors (37.5%), in whom a fall followed by a rise (>1 log??) in viraemia was observed. This was associated with superinfection with new HCV strains and partially effective T cell responses. Spontaneous clearance was strongly associated with a 2.2 log?? viral load drop within 100 days of infection (HR = 1.78; p < 0.0001), elevated bilirubin (? 40 ?mol/l; HR = 5.04; p = 0.006), elevated alanine aminotransferase (ALT; ? 1000 IU/ml; HR = 2.62; p = 0.048) and baseline CD4 count ? 650 × 10?/l (HR = 2.66; p = 0.045), and only occurred in patients with genotype 1 infection. Evolution to spontaneous clearance occurred in patients with low viral diversity in the presence of an early multispecific T cell response. CONCLUSIONS:Spontaneous clearance of acute HCV in HIV-positive men can be predicted by a rapid decline in viral load, high CD4 count, elevated bilirubin and ALT, and is associated with low viral diversity and strong T cell responses.

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The individualized genetic barrier predicts treatment response in a large cohort of HIV-1 infected patients.

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The individualized genetic barrier predicts treatment response in a large cohort of HIV-1 infected patients.

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