Showing papers by "Manisha Pal published in 2013"
TL;DR: The prevalence of HIV/HBV co-infection was relatively higher in the study subjects and pre-treatment screening for anti-HBV drug resistant mutations is not necessary before ART initiation.
Abstract: OBJECTIVE The study was designed to assess the hepatitis B virus (HBV) and hepatitis C virus (HCV) co-infection scenario among the human immunodeficiency virus (HIV) infected patients attending a tertiary healthcare unit in eastern India. Additionally, clinical and virological characterization of these viruses, prior to antiretroviral therapy (ART) initiation was also done for better understanding of the disease profile. METHODS Pool of ART-naive HIV/HBV co-infected and HIV mono-infected patients, participating in two different studies, were included in this study. HBV DNA was detected by nested-PCR amplification followed by HBV genotype determination and HBV reverse transcriptase (RT) region amplification and direct sequencing for detecting drug resistance. RESULTS The prevalence of HBsAg (11.3%) was higher compared to anti-HCV (1.9%) among the HIV infected ART-naive patients. Moreover, majority of the HBeAg positive HIV/HBV co-infected patients (87.7%) had HBV DNA ≥20,000 IU/ml with median HBV DNA significantly higher than that of HBeAg negative subjects (5.7 log10 IU/ml vs. 4.2 log10 IU/ml; p<0.0001). Multivariate analysis also showed that HBeAg-positive status was independently associated with higher HBV DNA level (p = <0.001). Notably, 60.9% of the HBeAg negative co-infected subjects had HBV DNA ≥2,000 IU/ml of which 37.0% had HBV DNA ≥20,000 IU/ml. Genotype HBV/D (68.2%) was the predominant genotype followed by HBV/A (24.3%) and HBV/C (7.5%). Anti-HBV drug resistant mutations were detected in two (3.8%) of the ART-naive patients. CONCLUSION The prevalence of HIV/HBV co-infection was relatively higher in our study subjects. HBeAg testing might provide clue for early treatment initiation. Furthermore, HBeAg negative patients are also associated with high HBV DNA levels and therefore require appropriate medical attention. Pre-treatment screening for anti-HBV drug resistant mutations is not necessary before ART initiation.
23 citations
TL;DR: Binary logistic regression analysis revealed that both HBV/A and 1762T/1764A mutations are predictors of chronic liver disease state over asymptomatic carrier state, highlighting the possible influence of HBV genotype shift on the changing scenario ofHBV epidemiology and disease in the population.
Abstract: In a previous study from eastern India, the prevalence of HBV/C has been increasing among the blood donors. In order to analyze whether there has been any shift in HBV genotype distributions in recent years, the HBV genotypes prevalent during the periods 2000–2002 (Group-I; n = 176) and 2007–2009 (Group-II; n = 203) were compared, with special attention to changes in the proportion of HBV/C. The rate of prevalence of the three HBV genotypes (A, C, and D; percent prevalence 19.9/21.6/58.5 in Group-I vs. 31.0/28.6/40.4 in Group-II) underwent significant changes with increases in HBV/A and HBV/C among the HBV carriers (0.002). Among the asymptomatic carriers, the prevalence of these two genotypes (P = 0.021 for HBV/A and P = 0.005 for HBV/C) was significantly high. A notable increase was also observed among the chronic liver disease cases. HBV/A increased significantly among the older age Groups (≥51 years), whereas the increase of HBV/C was significant among the younger age Groups (≤20 years). With the increase of HBV/A and HBV/C, the rates of basal core promoter double mutation (1762T/1764A) also increased considerably. Binary logistic regression analysis revealed that both HBV/A and 1762T/1764A mutations are predictors of chronic liver disease state over asymptomatic carrier state. Thus, this study highlights the possible influence of HBV genotype shift on the changing scenario of HBV epidemiology and disease in the population. J. Med. Virol. 85:1340–1347, 2013. © 2013 Wiley Periodicals, Inc.
16 citations
TL;DR: IL-1β polymorphisms are found to be associated with disease severity and different polymorphic combinations are associated with degree of disease severity in HBV-infected individuals.
Abstract: Background Interleukin-1β (IL-1β) is an important member of the family of the proinflammatory cytokines that modulate outcome of hepatitis B virus (HBV) infection. Objectives This study was designed to investigate the relationship between the polymorphic genotypes of the interleukin-1β (IL-1β) promoter region and the interleukin-1 receptor antagonist gene (IL-1RN) and disease outcome in HBV-infected individuals. Methods DNA was extracted from 395 study subjects including HBV carriers with varying clinical presentations, as well as healthy controls and spontaneously recovered cases (SRC). Polymorphisms in IL-1β (at position −511) and IL-1RN (variable nucleotide tandem repeats, VNTR) were analyzed by polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) and PCR based assay respectively. Results Among the study subjects, different IL-1β (at position −511) (CC, CT and TT) and IL-1RN (1/1, 1/2, 2/2 and 1/3) polymorphic genotypes were found at variable proportions. Logistic regression analysis revealed, no notable difference at the level of IL-1β promoter ( P = 0.244; OR = 0.78; 95% CI = 0.52–1.18) or IL-1RN genotype polymorphism ( P = 0.840; OR = 1.03; 95% CI = 0.78–1.36) among the HBV carriers and controls or SRC cases. Pairwise proportion testing showed, IL-1β −511 genotype CC was significantly higher among asymptomatic carriers (ASC) in comparison with liver cirrhosis (LC) patients ( P value = 0.028) and healthy control group ( P -value = 0.036). IL-1RN genotype 2/2 was considerably higher in LC group than SRC as well as control group. Combinations of IL-1β (−511) and IL-1RN polymorphisms were associated with disease progression, such as CC-1/2 with ASC and TT-2/2 with LC. Conclusion IL-1β polymorphisms are found to be associated with disease severity. Different polymorphic combinations are associated with degree of disease severity. Overall this is the first report from Eastern India, which shows association of IL-1β polymorphisms with HBV-related hepatic complications.
13 citations
TL;DR: Clinically relevant mutations were prevalent among the OBI strains which are of serious concern and needs further study.
Abstract: A previous study from West Bengal documented very high rate of occult HBV infection (OBI) among the HBsAg negative blood donors. This study was aimed to characterize the OBI strains circulating among the blood donors and to estimate the risk associated with the prevailing viral variants/mutants. Blood samples from 2195 voluntary blood donors were included in the study. HBsAg, HBeAg, anti-HBc, and anti-HBs statuses of the samples were done by ELISA based detection. PCR amplification and sequencing were done to determine HBV genotypes, basal core promoter (BCP), and precore (Pre-C) mutations. Among the study samples, 268 were anti-HBc positive/HBsAg negative, among which 65 (24.25%) were HBV DNA positive. Phylogenetic analysis revealed the presence of HBV/D (87.23%), HBV/A (8.51%), and HBV/C (4.26%) (P < 0.0001). HBV/D3 (65.85%) was the significantly prevalent subgenotype over HBV/D2 (26.83%) and HBV/D1 (7.31%) (P = 0.0003). Considerable prevalence of differential BCP (1752C, 1753C, 1762T/1764A, 1753C+1762T/1764A, 1773C, and 1814C) and reverse transcriptase (rt) gene (rtI91L, rtL93P, rtS106C, rtR110G, rtN118T, rtS119T, rtY126H, rtG127W/R, rtC136R, and rtY158H) mutations was identified. Association of specific HBV subgenotypes with OBI was interesting and needs further study. Clinically relevant mutations were prevalent among the OBI strains which are of serious concern.
13 citations
TL;DR: An attempt has been made to investigate optimum designs for estimating optimum mixing proportions in a multiresponse mixture experiment.
Abstract: Optimal designs for estimating the parameters and also the optimum factor combinations in multiresponse experiments have been considered by various authors. However, till date, in mixture experiments optimum designs have been studied only in the single response case. In this article, attempt has been made to investigate optimum designs for estimating optimum mixing proportions in a multiresponse mixture experiment.
6 citations
Journal Article•
TL;DR: In this paper, the pseudo-Bayesian approach has been used to investigate optimum designs for estimating optimum mixing proportions and also the optimum amount of mixture in a multi-response experiment, and the support points of the optimum design are found to be the union of the supporting points of a weighted centroid and a three-point symmetric design, with support points at the two extremes and one at the centre.
Abstract: Optimal designs for estimating the parameters and also the optimum factor combinations in multi-response experiments have been considered by some authors However, the existing literature on mixture experiments shows studies mainly in the single response case In this paper an attempt has been made to investigate optimum designs for estimating optimum mixing proportions and also the optimum amount of mixture in a multi-response experiment The pseudo-Bayesian approach has been used, and the support points of the optimum design are found to be the union of the support points of a weighted centroid design and a three-point symmetric design, with support points at the two extremes and one at the centre
3 citations
TL;DR: In this paper, the authors study a mixture model appropriate in such a situation and attempt to find optimum designs for estimation of parameters in the model, and also for estimating the optimum proportions of components in a group.
Abstract: In many experimentations with mixtures, the classical mixture models are found to be inappropriate to describe the response. In pharmaceutical research, for example, the components of the mixture are often classified into groups and the proportions of different groups in the mixture are fixed. This results in relational constraints on the mixing components. In the paper, we study a mixture model appropriate in such a situation. We attempt to find optimum designs for estimation of parameters in the model, and also for estimation of the optimum proportions of components in a group. The support points of the optimum designs are found to belong to the union of barycentres of the domains of the groups involved.
3 citations
TL;DR: In this article, the authors attempt to find the optimum designs for testing the presence of synergistic effects in a mixture model using the maximin criterion, which is the same as in this paper.
TL;DR: This article attempts to find the optimum design for testing the presence of synergistic effects in a mixture model using the classical F-test and finds that the barycenters are necessarily the support points of the trace-optimal design.
Abstract: In mixture experiments, optimal designs for the estimation of parameters, both linear and non-linear, have been discussed by several authors. Optimal designs for the estimation of a subset of parameters have also been investigated. However, designs for testing the effects of certain factors and interactions have been studied only in the context of response surface models. In this article, we attempt to find the optimum design for testing the presence of synergistic effects in a mixture model. The classical F-test has been considered and the optimum design has been obtained so as to maximize the power of the test. It is observed that the barycenters are necessarily the support points of the trace-optimal design.