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      Frequency and Genotype of Hepatitis D Virus Infection in Patients Infected with HIV and Those Undergoing Hemodialysis

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          Abstract

          Background

          Hepatitis D virus (HDV) is a defective virus dependent on hepatitis B virus (HBV) for its replication. Due to HDV transmission routes, patients undergoing hemodialysis and those with HIV infection are at risk of acquiring HDV.

          Objectives

          This study was aimed to determine the frequency and genotype of HDV infection among patients with HIV infection and those undergoing hemodialysis.

          Patients and Methods

          720 cases including 120 patients undergoing hemodialysis, and 600 patients with HIV infection were studied. All cases with positive results for HBsAg were evaluated for the presence of anti-HDV antibodies. Samples with Anti-HDV positive results were subjected to nested PCR for HDV-RNA confirmation, and sequenced for HDV genotype determination.

          Results

          HBsAg was found in 9 (7.5%) of 120 patients undergoing hemodialysis, and 9 (1.5%) of 600 patients with HIV infection. 3 (33.3%) of patients undergoing hemodialysis with positive results for HBsAg, and 5 (55.5%) of cases with HIV infection and positive results for HBsAg, had positive findings for anti-HDV which were then subjected to nested PCR. The amplification results confirmed that in 3 (37.5%) samples HDV-RNA was detected. Overall 2.5% of patients undergoing hemodialysis, and 0.8% of cases infected with HIV had positive results for anti-HDV and 1.7% and 0.2% of cases undergoing hemodialysis and patients infected with HIV had positive findings for HDV-RNA respectively. All of the HDV isolates were clustered in clade 1.

          Conclusions

          The survey showed that overall HDV frequency was not high in our high risk cases. Therefore, practitioners and health care managers should become aware of the risk of dual infection with HBV and HDV especially in high risk patients.

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          Most cited references 44

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          MEGA4: Molecular Evolutionary Genetics Analysis (MEGA) software version 4.0.

          We announce the release of the fourth version of MEGA software, which expands on the existing facilities for editing DNA sequence data from autosequencers, mining Web-databases, performing automatic and manual sequence alignment, analyzing sequence alignments to estimate evolutionary distances, inferring phylogenetic trees, and testing evolutionary hypotheses. Version 4 includes a unique facility to generate captions, written in figure legend format, in order to provide natural language descriptions of the models and methods used in the analyses. This facility aims to promote a better understanding of the underlying assumptions used in analyses, and of the results generated. Another new feature is the Maximum Composite Likelihood (MCL) method for estimating evolutionary distances between all pairs of sequences simultaneously, with and without incorporating rate variation among sites and substitution pattern heterogeneities among lineages. This MCL method also can be used to estimate transition/transversion bias and nucleotide substitution pattern without knowledge of the phylogenetic tree. This new version is a native 32-bit Windows application with multi-threading and multi-user supports, and it is also available to run in a Linux desktop environment (via the Wine compatibility layer) and on Intel-based Macintosh computers under the Parallels program. The current version of MEGA is available free of charge at (http://www.megasoftware.net).
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            The neighbor-joining method: a new method for reconstructing phylogenetic trees.

            A new method called the neighbor-joining method is proposed for reconstructing phylogenetic trees from evolutionary distance data. The principle of this method is to find pairs of operational taxonomic units (OTUs [= neighbors]) that minimize the total branch length at each stage of clustering of OTUs starting with a starlike tree. The branch lengths as well as the topology of a parsimonious tree can quickly be obtained by using this method. Using computer simulation, we studied the efficiency of this method in obtaining the correct unrooted tree in comparison with that of five other tree-making methods: the unweighted pair group method of analysis, Farris's method, Sattath and Tversky's method, Li's method, and Tateno et al.'s modified Farris method. The new, neighbor-joining method and Sattath and Tversky's method are shown to be generally better than the other methods.
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              A simple method for estimating evolutionary rates of base substitutions through comparative studies of nucleotide sequences.

               Motoo Kimura (1980)
              Some simple formulae were obtained which enable us to estimate evolutionary distances in terms of the number of nucleotide substitutions (and, also, the evolutionary rates when the divergence times are known). In comparing a pair of nucleotide sequences, we distinguish two types of differences; if homologous sites are occupied by different nucleotide bases but both are purines or both pyrimidines, the difference is called type I (or "transition" type), while, if one of the two is a purine and the other is a pyrimidine, the difference is called type II (or "transversion" type). Letting P and Q be respectively the fractions of nucleotide sites showing type I and type II differences between two sequences compared, then the evolutionary distance per site is K = -(1/2) ln [(1-2P-Q) square root of 1-2Q]. The evolutionary rate per year is then given by k = K/(2T), where T is the time since the divergence of the two sequences. If only the third codon positions are compared, the synonymous component of the evolutionary base substitutions per site is estimated by K'S = -(1/2) ln (1-2P-Q). Also, formulae for standard errors were obtained. Some examples were worked out using reported globin sequences to show that synonymous substitutions occur at much higher rates than amino acid-altering substitutions in evolution.
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                Author and article information

                Affiliations
                [1 ]Department of Hepatitis and AIDS, Pasteur Institute, Tehran, IR Iran
                [2 ]Iranian Research Center for HIV/AIDS, Tehran, IR Iran
                [3 ]Department of Clinical Research, Pasteur Institute, Tehran, IR Iran
                [4 ]Iranian Society for Support of Patients With Infectious Diseases, Tehran, IR Iran
                [5 ]Nephrology Research Center, Tehran University of Medical Sciences, Tehran, IR Iran
                Author notes
                [* ]Corresponding authors: Amitis Ramezani, Department of Clinical Research, Pasteur Institute, Tehran, IR Iran. Tel.: +98-2166465147, Fax: +98-2166465147, E-mail: amitisramezani@ 123456hotmail.com ; Ali Eslamifar, Department of Clinical Research, Pasteur Institute, Tehran, IR Iran. Tel.: +98-2166968852, Fax: +98-2166968852, E-mail: shafaghlab@ 123456yahoo.com .
                Journal
                Hepat Mon
                Hepat Mon
                10.5812/hepatmon
                Kowsar
                Hepatitis Monthly
                Kowsar
                1735-143X
                1735-3408
                11 May 2013
                May 2013
                : 13
                : 5
                23914228 3728973 10.5812/hepatmon.7481
                Copyright © 2013, Kowsar Corp.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                Categories
                Research Article

                Infectious disease & Microbiology

                genotype, hepatitis delta virus, hiv, hemodialysis

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