Biomedical subjects

Martin Däumer

Publications and source records attributed to Martin Däumer.

9 recordsLinked to original sources

PubMed2006

Stable coreceptor usage of HIV in patients with ongoing treatment failure on HAART.

BACKGROUND: Disease progression in HIV infection has been associated with switch of viral coreceptor usage from CCR5 to CXCR4. OBJECTIVES: To investigate the relationship between HIV-coreceptor tropism and clinical and virological outcome in 40 heavily pretreated patients over time. METHODS: Coreceptor phenotype was predicted after sequencing the V3 loop of the HIV glycoprotein 120. RESULTS: Coreceptor use was stable during observation time in 87% of patients, and CCR5 tropism was predominant. Viral mutations in the pol gene and clinical parameters were not predictive for coreceptor switching. CONCLUSIONS: Even in patients with repeated HAART failure, CCR5 antagonists might be a valuable treatment option.

Adult↗

PubMed2006

Primary HIV drug resistance and efficacy of first-line antiretroviral therapy guided by resistance testing.

BACKGROUND: Primary HIV drug resistance has been associated with poor treatment outcome of first-line highly active antiretroviral therapy (HAART) in several trials. The aim of the study was to assess the efficacy of first-line HAART guided by resistance testing. METHODS: In a prospective multicenter study in the state of Nordrhein-Westfalen, Germany, chronically HIV-infected patients underwent genotypic resistance testing and were monitored for 48 weeks after initiation of HAART. RESULTS: Primary drug resistance was found in 30 of 269 patients entering the study between January 2001 and December 2003 [11.2%; 95% confidence interval, 7.4-14.9]. In intent-to-treat analysis, the proportion of patients with viral load below 50 copies/mL after 24 and 48 weeks was 70.0% and 66.7%, respectively, in patients with resistance and 74.1% and 73.6%, respectively, in patients without (P = 0.66 and 0.51). In on-treatment analysis, the proportions were 80.8% and 83.3%, respectively, in patients with resistance and 81.9% and 85.0%, respectively, in patients without (P= 0.79 and 0.77). These results were also valid considering a detection limit of 400 copies/mL. CONCLUSIONS: The prevalence of primary drug resistance was 11.2% in chronically HIV-infected patients. HAART guided by resistance testing had similar efficacy in patients with primary drug resistance as compared with patients with wild-type virus. Based on these facts, resistance-adapted first-line HAART is suggested as routine practice.

Adult↗

PubMed2006

Functional domains of the human immunodeficiency virus type 1 Nef protein are conserved among different clades in Cameroon.

The Nef protein of human immunodeficiency virus type 1 (HIV-1) has multiple functional domains, is immunogenic, and contains several cytotoxic T lymphocyte (CTL)-targeted epitopes. Several defined subfunctions of Nef are important for the pathogenesis of HIV-1 infection. In this study, we present the genetic diversity of the nef gene of 55 newly derived HIV-1 sequences obtained from Cameroonian patients. Four genetic subtypes and three circulating recombinant forms (CRFs) were identified: subtypes A (11%), G (7.3%), D (5.4%), F1 (1.8%), F2 (5.4%), CRF01_AE (5.4%), CRF02_AG (58.2%), and CRF11_cpx (1.8%). Two isolates clustered distinctly from the known HIV-1 genetic subtypes in nef and were designated as unclassified. Interestingly, the majority of all functional domains including the myristoylation signal, CD4 binding motif, beta turn motif, and the phosphorylation sites were well conserved in our cohort. Putative CTL-epitopic domains of the central portion of Nef were also well conserved, whereas those at the C-term were not. Our study demonstrated that despite high genetic diversity observed in the nef gene, most described functional domains and CTL epitopes were well conserved among Cameroonian HIV-1 subtypes. These findings could be used for the development of antiretroviral-acting therapeutics and anti-HIV-1 vaccines.

Adult↗

PubMed2005

Computational methods for the design of effective therapies against drug resistant HIV strains.

The development of drug resistance is a major obstacle to successful treatment of HIV infection. The extraordinary replication dynamics of HIV facilitates its escape from selective pressure exerted by the human immune system and by combination drug therapy. We have developed several computational methods whose combined use can support the design of optimal antiretroviral therapies based on viral genomic data.

Database Management Systems↗

PubMed2005

Estimating HIV evolutionary pathways and the genetic barrier to drug resistance.

BACKGROUND: The evolution of drug-resistant viruses challenges the management of human immunodeficiency virus (HIV) infections. Understanding this evolutionary process is important for the design of effective therapeutic strategies. METHODS: We used mutagenetic trees, a family of probabilistic graphical models, to describe the accumulation of resistance-associated mutations in the viral genome. On the basis of these models, we defined the genetic barrier, a quantity that summarizes the difficulty for the virus to escape from the selective pressure of the drug by developing escape mutations. RESULTS: From HIV reverse-transcriptase sequences that had been obtained from treated patients, we derived evolutionary models for zidovudine, zidovudine plus lamivudine, and zidovudine plus didanosine. The genetic barriers to resistance to zidovudine, stavudine, lamivudine, and didanosine, for the above 3 regimens, were computed and analyzed. We found both the mode and the rate of development of resistance to be heterogeneous. The genetic barrier to zidovudine resistance was increased if lamivudine was added to zidovudine but was decreased for didanosine. The barrier to lamivudine resistance was maintained with zidovudine plus didanosine, whereas the barrier to didanosine resistance was reduced most with zidovudine plus lamivudine. CONCLUSION: Mutagenetic trees provide a quantitative picture of the evolution of drug resistance. The genetic barrier is a useful tool for design of effective treatment strategies.

Anti-HIV Agents↗

PubMed2004

Successful therapy of hepatitis B with tenofovir in HIV-infected patients failing previous adefovir and lamivudine treatment.

Three HIV-infected patients with chronic hepatitis B (genotype A) were switched to adefovir therapy after unsuccessful lamivudine treatment. Surprisingly, adefovir therapy failed, although none of the virus isolates displayed mutations known to be associated with adefovir resistance (A181V, N236T). In two isolates we identified hepatitis B virus DNA polymerase mutation L217R, in one case we found multiple frameshifts in the same region. In all cases adefovir was replaced by tenofovir, resulting in a significant drop in the viral load.

AIDS-Related Opportunistic Infections↗

PubMed2003

Geno2pheno: Estimating phenotypic drug resistance from HIV-1 genotypes.

Therapeutic success of anti-HIV therapies is limited by the development of drug resistant viruses. These genetic variants display complex mutational patterns in their pol gene, which codes for protease and reverse transcriptase, the molecular targets of current antiretroviral therapy. Genotypic resistance testing depends on the ability to interpret such sequence data, whereas phenotypic resistance testing directly measures relative in vitro susceptibility to a drug. From a set of 650 matched genotype-phenotype pairs we construct regression models for the prediction of phenotypic drug resistance from genotypes. Since the range of resistance factors varies considerably between different drugs, two scoring functions are derived from different sets of predicted phenotypes. Firstly, we compare predicted values to those of samples derived from 178 treatment-naive patients and report the relative deviance. Secondly, estimation of the probability density of 2000 predicted phenotypes gives rise to an intrinsic definition of a susceptible and a resistant subpopulation. Thus, for a predicted phenotype, we calculate the probability of membership in the resistant subpopulation. Both scores provide standardized measures of resistance that can be calculated from the genotype and are comparable between drugs. The geno2pheno system makes these genotype interpretations available via the Internet (http://www.genafor.org/).

Anti-HIV Agents↗

PubMed2003

Methods for optimizing antiviral combination therapies.

MOTIVATION: Despite some progress with antiretroviral combination therapies, therapeutic success in the management of HIV-infected patients is limited. The evolution of drug-resistant genetic variants in response to therapy plays a key role in treatment failure and finding a new potent drug combination after therapy failure is considered challenging. RESULTS: To estimate the activity of a drug combination against a particular viral strain, we develop a scoring function whose independent variables describe a set of antiviral agents and viral DNA sequences coding for the molecular targets of the respective drugs. The construction of this activity score involves (1) predicting phenotypic drug resistance from genotypes for each drug individually, (2) probabilistic modeling of predicted resistance values and integration into a score for drug combinations, and (3) searching through the mutational neighborhood of the considered strain in order to estimate activity on nearby mutants. For a clinical data set, we determine the optimal search depth and show that the scoring scheme is predictive of therapeutic outcome. Properties of the activity score and applications are discussed.

Algorithms↗

PubMedDate not supplied

Learning multiple evolutionary pathways from cross-sectional data.

We introduce a mixture model of trees to describe evolutionary processes that are characterized by the ordered accumulation of permanent genetic changes. The basic building block of the model is a directed weighted tree that generates a probability distribution on the set of all patterns of genetic events. We present an EM-like algorithm for learning a mixture model of K trees and show how to determine K with a maximum likelihood approach. As a case study, we consider the accumulation of mutations in the HIV-1 reverse transcriptase that are associated with drug resistance. The fitted model is statistically validated as a density estimator, and the stability of the model topology is analyzed. We obtain a generative probabilistic model for the development of drug resistance in HIV that agrees with biological knowledge. Further applications and extensions of the model are discussed.

Algorithms↗