CD4+ T cell count recovery in HIV type 1-infected patients is independent of class of antiretroviral therapy

BACKGROUND: In recent years, treatment options for human immunodeficiency virus type 1 (HIV-1) infection have changed from nonboosted protease inhibitors (PIs) to nonnucleoside reverse-transcriptase inhibitors (NNRTIs) and boosted PI-based antiretroviral drug regimens, but the impact on immunological recovery remains uncertain. METHODS: During January 1996 through December 2004 [corrected] all patients in the Swiss HIV Cohort were included if they received the first combination antiretroviral therapy (cART) and had known baseline CD4(+) T cell counts and HIV-1 RNA values (n = 3293). For follow-up, we used the Swiss HIV Cohort Study database update of May 2007 [corrected] The mean (+/-SD) duration of follow-up was 26.8 +/- 20.5 months. The follow-up time was limited to the duration of the first cART. CD4(+) T cell recovery was analyzed in 3 different treatment groups: nonboosted PI, NNRTI, or boosted PI. The end point was the absolute increase of CD4(+) T cell count in the 3 treatment groups after the initiation of cART. RESULTS: Two thousand five hundred ninety individuals (78.7%) initiated a nonboosted-PI regimen, 452 (13.7%) initiated an NNRTI regimen, and 251 (7.6%) initiated a boosted-PI regimen. Absolute CD4(+) T cell count increases at 48 months were as follows: in the nonboosted-PI group, from 210 to 520 cells/muL; in the NNRTI group, from 220 to 475 cells/muL; and in the boosted-PI group, from 168 to 511 cells/muL. In a multivariate analysis, the treatment group did not affect the response of CD4(+) T cells; however, increased age, pretreatment with nucleoside reverse-transcriptase inhibitors, serological tests positive for hepatitis C virus, Centers for Disease Control and Prevention stage C infection, lower baseline CD4(+) T cell count, and lower baseline HIV-1 RNA level were risk factors for smaller increases in CD4(+) T cell count. CONCLUSION: CD4(+) T cell recovery was similar in patients receiving nonboosted PI-, NNRTI-, and boosted PI-based cART.

Factors associated with the emergence of K65R in patients with HIV-1 infection treated with combination antiretroviral therapy containing tenofovir

BACKGROUND: The human immunodeficiency virus type 1 reverse-transcriptase mutation K65R is a single-point mutation that has become more frequent after increased use of tenofovir disoproxil fumarate (TDF). We aimed to identify predictors for the emergence of K65R, using clinical data and genotypic resistance tests from the Swiss HIV Cohort Study. METHODS: A total of 222 patients with genotypic resistance tests performed while receiving treatment with TDF-containing regimens were stratified by detectability of K65R (K65R group, 42 patients; undetected K65R group, 180 patients). Patient characteristics at start of that treatment were analyzed. RESULTS: In an adjusted logistic regression, TDF treatment with nonnucleoside reverse-transcriptase inhibitors and/or didanosine was associated with the emergence of K65R, whereas the presence of any of the thymidine analogue mutations D67N, K70R, T215F, or K219E/Q was protective. The previously undescribed mutational pattern K65R/G190S/Y181C was observed in 6 of 21 patients treated with efavirenz and TDF. Salvage therapy after TDF treatment was started for 36 patients with K65R and for 118 patients from the wild-type group. Proportions of patients attaining human immunodeficiency virus type 1 loads <50 copies/mL after 24 weeks of continuous treatment were similar for the K65R group (44.1%; 95% confidence interval, 27.2%-62.1%) and the wild-type group (51.9%; 95% confidence interval, 42.0%-61.6%). CONCLUSIONS: In settings where thymidine analogue mutations are less likely to be present, such as at start of first-line therapy or after extended treatment interruptions, combinations of TDF with other K65R-inducing components or with efavirenz or nevirapine may carry an enhanced risk of the emergence of K65R. The finding of a distinct mutational pattern selected by treatment with TDF and efavirenz suggests a potential fitness interaction between K65R and nonnucleoside reverse-transcriptase inhibitor-induced mutations.

Self-reported non-adherence to antiretroviral therapy repeatedly assessed by two questions predicts treatment failure in virologically suppressed patients

BACKGROUND: The aim of this study was to explore the predictive value of longitudinal self-reported adherence data on viral rebound. METHODS: Individuals in the Swiss HIV Cohort Study on combined antiretroviral therapy (cART) with RNA <50 copies/ml over the previous 3 months and who were interviewed about adherence at least once prior to 1 March 2007 were eligible. Adherence was defined in terms of missed doses of cART (0, 1, 2 or >2) in the previous 28 days. Viral rebound was defined as RNA >500 copies/ml. Cox regression models with time-independent and -dependent covariates were used to evaluate time to viral rebound. RESULTS: A total of 2,664 individuals and 15,530 visits were included. Across all visits, missing doses were reported as follows: 1 dose 14.7%, 2 doses 5.1%, >2 doses 3.8% taking <95% of doses 4.5% and missing > or =2 consecutive doses 3.2%. In total, 308 (11.6%) patients experienced viral rebound. After controlling for confounding variables, self-reported non-adherence remained significantly associated with the rate of occurrence of viral rebound (compared with zero missed doses: 1 dose, hazard ratio [HR] 1.03, 95% confidence interval [CI] 0.72-1.48; 2 doses, HR 2.17, 95% CI 1.46-3.25; >2 doses, HR 3.66, 95% CI 2.50-5.34). Several variables significantly associated with an increased risk of viral rebound irrespective of adherence were identified: being on a protease inhibitor or triple nucleoside regimen (compared with a non-nucleoside reverse transcriptase inhibitor), >5 previous cART regimens, seeing a less-experienced physician, taking co-medication, and a shorter time virally suppressed. CONCLUSIONS: A simple self-report adherence questionnaire repeatedly administered provides a sensitive measure of non-adherence that predicts viral rebound.

Predicting the evolution of Kaposi sarcoma, in the highly active antiretroviral therapy era

BACKGROUND: The outcome of Kaposi sarcoma varies. While many patients do well on highly active antiretroviral therapy, others have progressive disease and need chemotherapy. In order to predict which patients are at risk of unfavorable evolution, we established a prognostic score. METHOD: The survival analysis (Kaplan-Meier method; Cox proportional hazards models) of 144 patients with Kaposi sarcoma prospectively included in the Swiss HIV Cohort Study, from January 1996 to December 2004, was conducted. OUTCOME ANALYZED: use of chemotherapy or death. VARIABLES ANALYZED: demographics, tumor staging [T0 or T1 (16)], CD4 cell counts and HIV-1 RNA concentration, human herpesvirus 8 (HHV8) DNA in plasma and serological titers to latent and lytic antigens. RESULTS: Of 144 patients, 54 needed chemotherapy or died. In the univariate analysis, tumor stage T1, CD4 cell count below 200 cells/microl, positive HHV8 DNA and absence of antibodies against the HHV8 lytic antigen at the time of diagnosis were significantly associated with a bad outcome.Using multivariate analysis, the following variables were associated with an increased risk of unfavorable outcome: T1 [hazard ratio (HR) 5.22; 95% confidence interval (CI) 2.97-9.18], CD4 cell count below 200 cells/microl (HR 2.33; 95% CI 1.22-4.45) and positive HHV8 DNA (HR 2.14; 95% CI 1.79-2.85).We created a score with these variables ranging from 0 to 4: T1 stage counted for two points, CD4 cell count below 200 cells/microl for one point, and positive HHV8 viral load for one point. Each point increase was associated with a HR of 2.26 (95% CI 1.79-2.85). CONCLUSION: In the multivariate analysis, staging (T1), CD4 cell count (<200 cells/microl), positive HHV8 DNA in plasma, at the time of diagnosis, predict evolution towards death or the need of chemotherapy.

STrengthening the REporting of Genetic Association studies (STREGA)--an extension of the STROBE statement

Making sense of rapidly evolving evidence on genetic associations is crucial to making genuine advances in human genomics and the eventual integration of this information in the practice of medicine and public health. Assessment of the strengths and weaknesses of this evidence, and hence the ability to synthesize it, has been limited by inadequate reporting of results. The STrengthening the REporting of Genetic Association studies (STREGA) initiative builds on the STrengthening the Reporting of OBservational Studies in Epidemiology (STROBE) Statement and provides additions to 12 of the 22 items on the STROBE checklist. The additions concern population stratification, genotyping errors, modelling haplotype variation, Hardy-Weinberg equilibrium, replication, selection of participants, rationale for choice of genes and variants, treatment effects in studying quantitative traits, statistical methods, relatedness, reporting of descriptive and outcome data and the volume of data issues that are important to consider in genetic association studies. The STREGA recommendations do not prescribe or dictate how a genetic association study should be designed, but seek to enhance the transparency of its reporting, regardless of choices made during design, conduct or analysis.

STrengthening the REporting of Genetic Association Studies (STREGA)--an extension of the STROBE statement

Making sense of rapidly evolving evidence on genetic associations is crucial to making genuine advances in human genomics and the eventual integration of this information in the practice of medicine and public health. Assessment of the strengths and weaknesses of this evidence, and hence the ability to synthesize it, has been limited by inadequate reporting of results. The STrengthening the REporting of Genetic Association studies (STREGA) initiative builds on the STrengthening the Reporting of OBservational Studies in Epidemiology (STROBE) Statement and provides additions to 12 of the 22 items on the STROBE checklist. The additions concern population stratification, genotyping errors, modelling haplotype variation, Hardy-Weinberg equilibrium, replication, selection of participants, rationale for choice of genes and variants, treatment effects in studying quantitative traits, statistical methods, relatedness, reporting of descriptive and outcome data, and the volume of data issues that are important to consider in genetic association studies. The STREGA recommendations do not prescribe or dictate how a genetic association study should be designed but seek to enhance the transparency of its reporting, regardless of choices made during design, conduct, or analysis.

Strengthening the reporting of genetic association studies (STREGA): an extension of the strengthening the reporting of observational studies in epidemiology (STROBE) statement

Making sense of rapidly evolving evidence on genetic associations is crucial to making genuine advances in human genomics and the eventual integration of this information in the practice of medicine and public health. Assessment of the strengths and weaknesses of this evidence, and hence, the ability to synthesize it, has been limited by inadequate reporting of results. The STrengthening the REporting of Genetic Association (STREGA) studies initiative builds on the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement and provides additions to 12 of the 22 items on the STROBE checklist. The additions concern population stratification, genotyping errors, modeling haplotype variation, Hardy-Weinberg equilibrium, replication, selection of participants, rationale for choice of genes and variants, treatment effects in studying quantitative traits, statistical methods, relatedness, reporting of descriptive and outcome data, and the volume of data issues that are important to consider in genetic association studies. The STREGA recommendations do not prescribe or dictate how a genetic association study should be designed, but seek to enhance the transparency of its reporting, regardless of choices made during design, conduct, or analysis.

STrengthening the REporting of Genetic Association Studies (STREGA): an extension of the STROBE statement

Making sense of rapidly evolving evidence on genetic associations is crucial to making genuine advances in human genomics and the eventual integration of this information in the practice of medicine and public health. Assessment of the strengths and weaknesses of this evidence, and hence the ability to synthesize it, has been limited by inadequate reporting of results. The STrengthening the REporting of Genetic Association studies (STREGA) initiative builds on the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement and provides additions to 12 of the 22 items on the STROBE checklist. The additions concern population stratification, genotyping errors, modelling haplotype variation, Hardy-Weinberg equilibrium, replication, selection of participants, rationale for choice of genes and variants, treatment effects in studying quantitative traits, statistical methods, relatedness, reporting of descriptive and outcome data, and the volume of data issues that are important to consider in genetic association studies. The STREGA recommendations do not prescribe or dictate how a genetic association study should be designed but seek to enhance the transparency of its reporting, regardless of choices made during design, conduct, or analysis.

STrengthening the REporting of Genetic Association studies (STREGA): an extension of the STROBE Statement

Making sense of rapidly evolving evidence on genetic associations is crucial to making genuine advances in human genomics and the eventual integration of this information into the practice of medicine and public health. Assessment of the strengths and weaknesses of this evidence, and hence the ability to synthesize it, has been limited by inadequate reporting of results. The STrengthening the REporting of Genetic Association studies (STREGA) initiative builds on the STrengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement and provides additions to 12 of the 22 items on the STROBE checklist. The additions concern population stratification, genotyping errors, modeling haplotype variation, Hardy-Weinberg equilibrium, replication, selection of participants, rationale for choice of genes and variants, treatment effects in studying quantitative traits, statistical methods, relatedness, reporting of descriptive and outcome data, and issues of data volume that are important to consider in genetic association studies. The STREGA recommendations do not prescribe or dictate how a genetic association study should be designed but seek to enhance the transparency of its reporting, regardless of choices made during design, conduct, or analysis.

Strengthening the reporting of genetic association studies (STREGA): an extension of the STROBE statement

Making sense of rapidly evolving evidence on genetic associations is crucial to making genuine advances in human genomics and the eventual integration of this information in the practice of medicine and public health. Assessment of the strengths and weaknesses of this evidence, and hence the ability to synthesize it, has been limited by inadequate reporting of results. The STrengthening the REporting of Genetic Association studies (STREGA) initiative builds on the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement and provides additions to 12 of the 22 items on the STROBE checklist. The additions concern population stratification, genotyping errors, modeling haplotype variation, Hardy-Weinberg equilibrium, replication, selection of participants, rationale for choice of genes and variants, treatment effects in studying quantitative traits, statistical methods, relatedness, reporting of descriptive and outcome data, and the volume of data issues that are important to consider in genetic association studies. The STREGA recommendations do not prescribe or dictate how a genetic association study should be designed but seek to enhance the transparency of its reporting, regardless of choices made during design, conduct, or analysis.

Strengthening the reporting of genetic association studies (STREGA): an extension of the STROBE Statement

Making sense of rapidly evolving evidence on genetic associations is crucial to making genuine advances in human genomics and the eventual integration of this information in the practice of medicine and public health. Assessment of the strengths and weaknesses of this evidence, and hence the ability to synthesize it, has been limited by inadequate reporting of results. The STrengthening the REporting of Genetic Association studies (STREGA) initiative builds on the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement and provides additions to 12 of the 22 items on the STROBE checklist. The additions concern population stratification, genotyping errors, modeling haplotype variation, Hardy-Weinberg equilibrium, replication, selection of participants, rationale for choice of genes and variants, treatment effects in studying quantitative traits, statistical methods, relatedness, reporting of descriptive and outcome data, and the volume of data issues that are important to consider in genetic association studies. The STREGA recommendations do not prescribe or dictate how a genetic association study should be designed but seek to enhance the transparency of its reporting, regardless of choices made during design, conduct, or analysis.

A Missense Mutation in the SERPINH1 Gene in Dachshunds with Osteogenesis Imperfecta

Osteogenesis imperfecta (OI) is a hereditary disease occurring in humans and dogs. It is characterized by extremely fragile bones and teeth. Most human and some canine OI cases are caused by mutations in the COL1A1 and COL1A2 genes encoding the subunits of collagen I. Recently, mutations in the CRTAP and LEPRE1 genes were found to cause some rare forms of human OI. Many OI cases exist where the causative mutation has not yet been found. We investigated Dachshunds with an autosomal recessive form of OI. Genotyping only five affected dogs on the 50 k canine SNP chip allowed us to localize the causative mutation to a 5.82 Mb interval on chromosome 21 by homozygosity mapping. Haplotype analysis of five additional carriers narrowed the interval further down to 4.74 Mb. The SERPINH1 gene is located within this interval and encodes an essential chaperone involved in the correct folding of the collagen triple helix. Therefore, we considered SERPINH1 a positional and functional candidate gene and performed mutation analysis in affected and control Dachshunds. A missense mutation (c.977C>T, p.L326P) located in an evolutionary conserved domain was perfectly associated with the OI phenotype. We thus have identified a candidate causative mutation for OI in Dachshunds and identified a fifth OI gene.

CTL induction by cross-priming is restricted to immunodominant epitopes

CTL are induced by two pathways, i.e. direct priming, where tumor cells present tumor antigens to naïve specific CTL, and cross-priming, where professional APC cross-present captured tumor antigens to CTL. Here, we examined direct priming versus cross-priming after immunizing (H-2(b) x H-2(d)) F1 mice with either H-2(b) or H-2(d) positive tumor cells transfected with the GP or nucleoprotein (NP) of lymphocytic choriomeningitis virus (LCMV). Cross-priming was observed for the immunodominant epitopes LCMV-gp33 and -np118, although direct induction resulted in higher CTL frequencies. In contrast, CTL specific for the subdominant epitopes LCMV-gp283 or -np396 were induced only if epitopes were presented directly on MHC class I molecules of the immunizing cell. The broader repertoire and the higher CTL frequencies induced after vaccination with haplotype-matched tumor cells resulted in more efficient anti-tumor and antiviral protection. Firstly, our results indicate that certain virus and tumor antigens may not be detected by CD8(+) T cells because of impaired cross-priming. Secondly, efficient cross-priming contributes to the immunodominant nature of a tumor-specific CTL epitope. Thirdly, vaccine strategies using autologous or syngenic antigen-expressing cells induce a broader repertoire of tumor-specific CTL and higher CTL frequencies.

Novel genetic risk markers for ulcerative colitis in the IL2/IL21 region are in epistasis with IL23R and suggest a common genetic background for ulcerative colitis and celiac disease

OBJECTIVES: Recently, a genome-wide association study showed that single-nucleotide polymorphisms (SNPs) in the chromosome 4q27 region containing IL2 and IL21 are associated with celiac disease. Given the increased prevalence of inflammatory bowel disease (IBD) among celiac disease patients, we investigated the possible involvement of these SNPs in IBD. METHODS: Five SNPs strongly associated with celiac disease within the KIAA1109/TENR/IL2/IL21 linkage disequilibrium block on chromosome 4q27 and one coding SNP within the IL21 gene were analyzed in a large German IBD cohort. The study population comprised a total of 2,948 Caucasian individuals, including 1,461 IBD patients (ulcerative colitis (UC): n=514, Crohn's disease (CD): n=947) and 1,487 healthy unrelated controls. RESULTS: Three of the five celiac disease risk markers had a protective effect on UC susceptibility, and this effect remained significant after correcting for multiple testing: rs6840978: P=0.0082, P(corr)=0.049, odds ratio (OR) 0.77, 95% confidence interval (CI) 0.63-0.93; rs6822844: P=0.0028, P(corr)=0.017, OR 0.73, 95% CI 0.59-0.90; rs13119723: P=0.0058, P(corr)=0.035, OR 0.75, 95% CI 0.61-0.92. A haplotype consisting of the six SNPs tested was markedly associated with UC susceptibility (P=0.0025, P(corr)=0.015, OR 0.72, 95% CI 0.58-0.89). Moreover, in UC, epistasis was observed between the IL23R SNP rs1004819 and three SNPs in the KIAA1109/TENR/IL2/IL21 block (rs13151961, rs13119723, and rs6822844). CONCLUSIONS: Similar to other autoimmune diseases such as celiac disease, rheumatoid arthritis, type 1 diabetes, Graves' disease, and psoriatic arthritis, genetic variation in the chromosome 4q27 region predisposes to UC, suggesting a common genetic background for these diseases.

Virological and immunological responses to efavirenz or boosted lopinavir as first-line therapy for patients with HIV

BACKGROUND: Efavirenz and lopinavir boosted with ritonavir are both recommended as first-line therapies for patients with HIV when combined with two nucleoside reverse transcriptase inhibitors. It is uncertain which therapy is more effective for patients starting therapy with an advanced infection. METHODS: We estimated the relative effect of these two therapies on rates of virological and immunological failure within the Swiss HIV Cohort Study and considered whether estimates depended on the CD4(+) T-cell count when starting therapy. We defined virological failure as either an incomplete virological response or viral rebound after viral suppression and immunological failure as failure to achieve an expected CD4(+) T-cell increase calculated from EuroSIDA statistics. RESULTS: Patients starting efavirenz (n=660) and lopinavir (n=541) were followed for a median of 4.5 and 3.1 years, respectively. Virological failure was less likely for patients on efavirenz, with the adjusted hazard ratio (95% confidence interval) of 0.63 (0.50-0.78) then multiplied by a factor of 1.00 (0.90-1.12) for each 100 cells/mm(3) decrease in CD4(+) T-cell count below the mean when starting therapy. Immunological failure was also less likely for patients on efavirenz, with the adjusted hazard ratio of 0.68 (0.51-0.91) then multiplied by a factor of 1.29 (1.14-1.46) for each 100 cells/mm(3) decrease in CD4(+) T-cell count below the mean when starting therapy. CONCLUSIONS: Virological failure is less likely with efavirenz regardless of the CD4(+) T-cell count when starting therapy. Immunological failure is also less likely with efavirenz; however, this advantage disappears if patients start therapy with a low CD4(+) T-cell count.