Role of viral load in Hepatitis B virus evolution in persistently normal ALT chronically infected patients

Chronic HBV infection has been associated with severe liver disease although most of them do not progress to this stage. Even though low replicative carriers form the largest group of HBV chronically infected patients, there is a paucity of longitudinal studies to evaluate the molecular evolution of the whole genome in this subset of patients. In this study, longitudinal samples from 10 patients with persistently normal ALT levels were collected. HBV full-length genome sequences were obtained from 3 samples per patient (baseline, 5 and 10-years of follow-up). Patients were grouped according to HBV-DNA level into  103 IU/ml (group B). The substitution rate was inversely related with HBV-DNA levels. Moreover, the rate in the 10-year follow-up was significantly higher in group A (6.9 × 10−4 ± 1.3 × 10−4) than group B (2.7 × 10−4 ± 7.4 × 10−5 substitution/site/year, p < .001). Most of the substitutions were in the Core region and the majority were non-synonymous changes. The rate of nucleotide substitution was inversely related to HBV-DNA levels, highlighting the role of viral load in the HBV intra-host dynamics, even in low replicative state patients. Moreover, the difference in the substitution rate between the analysed groups was mainly consequence of substitutions restricted to the Core region, particularly in the simple coding region and antigenic epitopes, which suggest that the immune pressure drives the different evolutionary behaviour of groups.Fil: Gauder, Catalina. Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica. Departamento de Microbiología, Inmunología y Biotecnología. Cátedra de Virología; ArgentinaFil: Mojsiejczuk, Laura Noelia. Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica. Departamento de Microbiología, Inmunología y Biotecnología. Cátedra de Virología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Tadey, Luciana. Gobierno de la Ciudad de Buenos Aires. Hospital de Infecciosas "Dr. Francisco Javier Muñiz"; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Mammana, Lilia. Gobierno de la Ciudad de Buenos Aires. Hospital de Infecciosas "Dr. Francisco Javier Muñiz"; ArgentinaFil: Bouzas, Maria Belen. Gobierno de la Ciudad de Buenos Aires. Hospital de Infecciosas "Dr. Francisco Javier Muñiz"; ArgentinaFil: Campos, Rodolfo Hector. Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica. Departamento de Microbiología, Inmunología y Biotecnología. Cátedra de Microbiología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Flichman, Diego Martin. Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica. Departamento de Microbiología, Inmunología y Biotecnología. Cátedra de Microbiología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Investigaciones Biomédicas en Retrovirus y Sida. Universidad de Buenos Aires. Facultad de Medicina. Instituto de Investigaciones Biomédicas en Retrovirus y Sida; Argentin

The Hepatitis C Virus 5′UTR Genomic Region Remains Highly Conserved Under HAART: A 4- to 8-Year Longitudinal Study from HCV/HIV Co-Infected Patients

Fil: Moretti, Franco. Universidad de Buenos Aires. Facultad de Medicina. Departamento de Microbiología. Area Virologia; ArgentinaFil: Bolcic, Federico Martin. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de Buenos Aires. Facultad de Medicina. Departamento de Microbiología. Area Virologia; ArgentinaFil: Mammana, Lilia. Gobierno de la Ciudad de Buenos Aires. Hospital de Infecciosas ; ArgentinaFil: Bouzas, Maria Belen. Gobierno de la Ciudad de Buenos Aires. Hospital de Infecciosas ; ArgentinaFil: Laufer, Natalia Lorna. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de Buenos Aires. Facultad de Medicina. Departamento de Microbiología. Area Virologia; Argentina. Gobierno de la Ciudad de Buenos Aires. Hospital General de Agudos "Juan A. Fernández"; ArgentinaFil: Quarleri, Jorge Fabian. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de Buenos Aires. Facultad de Medicina. Departamento de Microbiología. Area Virologia; Argentin

Discordances between Interpretation Algorithms for Genotypic Resistance to Protease and Reverse Transcriptase Inhibitors of Human Immunodeficiency Virus Are Subtype Dependent

The major limitation of drug resistance genotyping for human immunodeficiency virus remains the interpretation of the results. We evaluated the concordance in predicting therapy response between four different interpretation algorithms (Rega 6.3, HIVDB-08/04, ANRS [07/04], and VGI 8.0). Sequences were gathered through a worldwide effort to establish a database of non-B subtype sequences, and demographic and clinical information about the patients was gathered. The most concordant results were found for nonnucleoside reverse transcriptase (RT) inhibitors (93%), followed by protease inhibitors (84%) and nucleoside RT inhibitor (NRTIs) (76%). For therapy-naive patients, for nelfinavir, especially for subtypes C and G, the discordances were driven mainly by the protease (PRO) mutational pattern 82I/V + 63P + 36I/V for subtype C and 82I + 63P + 36I + 20I for subtype G. Subtype F displayed more discordances for ritonavir in untreated patients due to the combined presence of PRO 20R and 10I/V. In therapy-experienced patients, subtype G displayed a lot of discordances for saquinavir and indinavir due to mutational patterns involving PRO 90 M and 82I. Subtype F had more discordance for nelfinavir attributable to the presence of PRO 88S and 82A + 54V. For the NRTIs lamivudine and emtricitabine, CRF01_AE had more discordances than subtype B due to the presence of RT mutational patterns 65R + 115 M and 118I + 215Y, respectively. Overall, the different algorithms agreed well on the level of resistance scored, but some of the discordances could be attributed to specific (subtype-dependent) combinations of mutations. It is not yet known whether therapy response is subtype dependent, but the advice given to clinicians based on a genotypic interpretation algorithm differs according to the subtype

Proportions of Persons Receiving Treatment with Specific NRTIs, NNRTIs, and PIs

<p>The number of persons with non-B virus receiving the NRTI tenofovir (ten), the NNRTI delavirdine (three), and the PIs amprenavir (13) and lopinavir (28) are not shown. 3TC, lamivudine; ABC, abacavir; AZT, zidovudine; D4T, stavudine; DDC, zalcitabine; DDI, didanosine; EFV, efavirenz; IDV, indinavir; NFV, nelfinavir; NVP, nevirapine; RTV, ritonavir; SQV, saquinavir.</p

Number of Treated and Untreated Persons Infected with B and Non-B HIV-1 Subtypes from Whom Protease and/or RT Sequences Were Available for Analysis

<p>Number of Treated and Untreated Persons Infected with B and Non-B HIV-1 Subtypes from Whom Protease and/or RT Sequences Were Available for Analysis</p

Amino Acid Differences from Consensus B Sequence at Drug-Resistance Positions in Protease and RT according to Subtype

<p>(A) shows data for protease, and (B) shows data for RT. In both, the first line lists the drug-resistance positions. The second line shows single-letter amino acid codes for the consensus B sequence. For each subtype (left column), the frequency of specific mutations in untreated persons is shown above the dashed line, whereas the frequency of specific mutations in treated persons is shown below the dashed line. Positions with significant differences in mutation frequency between B and non-B subtypes (<i>p</i> < 0.01, according to χ² test with Yate's correction) are circled. A pound sign indicates an insertion.</p

Impact of HIV-1 Subtype and Antiretroviral Therapy on Protease and Reverse Transcriptase Genotype: Results of a Global Collaboration

<div><h3>Background</h3><p>The genetic differences among HIV-1 subtypes may be critical to clinical management and drug resistance surveillance as antiretroviral treatment is expanded to regions of the world where diverse non-subtype-B viruses predominate.</p> <h3>Methods and Findings</h3><p>To assess the impact of HIV-1 subtype and antiretroviral treatment on the distribution of mutations in protease and reverse transcriptase, a binomial response model using subtype and treatment as explanatory variables was used to analyze a large compiled dataset of non-subtype-B HIV-1 sequences. Non-subtype-B sequences from 3,686 persons with well characterized antiretroviral treatment histories were analyzed in comparison to subtype B sequences from 4,769 persons. The non-subtype-B sequences included 461 with subtype A, 1,185 with C, 331 with D, 245 with F, 293 with G, 513 with CRF01_AE, and 618 with CRF02_AG. Each of the 55 known subtype B drug-resistance mutations occurred in at least one non-B isolate, and 44 (80%) of these mutations were significantly associated with antiretroviral treatment in at least one non-B subtype. Conversely, of 67 mutations found to be associated with antiretroviral therapy in at least one non-B subtype, 61 were also associated with antiretroviral therapy in subtype B isolates.</p> <h3>Conclusion</h3><p>Global surveillance and genotypic assessment of drug resistance should focus primarily on the known subtype B drug-resistance mutations.</p> </div