Different Rates of Disease Progression of HIV Type 1 Infection in Tanzania Based on Infecting Subtype

Vasan, Ashwin; Renjifo, Boris; Hertzmark, Ellen; Chaplin, Beth; Msamanga, Gernard; Essex, Max; Fawzi, Wafaie W.; Hunter, David J.

doi:10.1086/499952

Cited by 180 publications

(161 citation statements)

References 40 publications

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“…epidemiological hypotheses concerning HIV and other pathogens such as Influenza A ( Janies et al 2007). For instance, the exceptional subtype distributions seen in Tanzania that lead it to cluster with countries in central Africa is consistent with the hypothesis that events such as the Tanzania-Uganda war, which ended in 1979, were responsible for founder events that introduced non-C subtypes into Tanzania, while C arrived later from elsewhere in east Africa (Serwadda et al 1985;Vasan et al 2006). Additionally, Kenya and Tanzania may show distinct patterns due to the convergence of major north-south and east-west travel corridors (Bwayo et al 1994;Robbins et al 1999).…”

Section: Nonrecombinant Hiv-1 Subtypes In Africasupporting

confidence: 73%

“…Together with their derived recombinant forms such as CRF01(AE) and CRF02(AG), these subtypes are responsible for the vast majority of HIV infections worldwide. Subtype distributions vary dramatically by continent, country, and region (Kuiken et al 2000;Peeters et al 2003;Hemelaar et al 2006), and there is considerable evidence and speculation that subtype differences influence the likelihood of detection, disease progression, and potential responses to antiviral treatment (Vasan et al 2006;Taylor et al 2008). The geographic origins of certain subtypes have been probed in depth: For instance, it is thought that the widely dispersed subtype B may have originated in Haiti during the 1960s (Gilbert et al 2007).…”

Section: Nonrecombinant Hiv-1 Subtypes In Africamentioning

confidence: 99%

See 1 more Smart Citation

GenGIS: A geospatial information system for genomic data

Parks¹,

Porter²,

Churcher³

et al. 2009

Genome Res.

111

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The increasing availability of genetic sequence data associated with explicit geographic and ecological information is offering new opportunities to study the processes that shape biodiversity. The generation and testing of hypotheses using these data sets requires effective tools for mathematical and visual analysis that can integrate digital maps, ecological data, and large genetic, genomic, or metagenomic data sets. GenGIS is a free and open-source software package that supports the integration of digital map data with genetic sequences and environmental information from multiple sample sites. Essential bioinformatic and statistical tools are integrated into the software, allowing the user a wide range of analysis options for their sequence data. Data visualizations are combined with the cartographic display to yield a clear view of the relationship between geography and genomic diversity, with a particular focus on the hierarchical clustering of sites based on their similarity or phylogenetic proximity. Here we outline the features of GenGIS and demonstrate its application to georeferenced microbial metagenomic, HIV-1, and human mitochondrial DNA data sets.

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Section: Nonrecombinant Hiv-1 Subtypes In Africasupporting

confidence: 73%

Section: Nonrecombinant Hiv-1 Subtypes In Africamentioning

confidence: 99%

GenGIS: A geospatial information system for genomic data

Parks¹,

Porter²,

Churcher³

et al. 2009

Genome Res.

111

View full text Add to dashboard Cite

show abstract

“…This diversity of strains possesses threats toward HIV diagnosis as well as viral load measurements assays. Finding Ashwin Vasan s from east Africa evidenced on how different strains has different disease progression and even transmission capacity [20]. Basing on current phylogenetic analysis HIV-1 has been classified into four groups: main group (M), outlier group (O), non-M-non-O (N) group and newly group P [20].…”

Section: Hiv-1 Diversity In East Africamentioning

confidence: 99%

“…Finding Ashwin Vasan s from east Africa evidenced on how different strains has different disease progression and even transmission capacity [20]. Basing on current phylogenetic analysis HIV-1 has been classified into four groups: main group (M), outlier group (O), non-M-non-O (N) group and newly group P [20]. Group M is responsible for the majority of HIV-1 infections globally and is divided into nine genetic subtypes (A, B, C, D, F, G, H, J, and K) [21].…”

Section: Hiv-1 Diversity In East Africamentioning

confidence: 99%

HIV-1 Diversity in Tanzania and its Implication toward Development of Effective Vaccines: A Review Article

2014

J Vaccines Vaccin

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Background: Human immunodeficiency viruses (HIV) are characterized by extremely high genetic variability. This extensive heterogeneity resulted from high error rate of reverse transcriptase enzyme in combination with fast turnover of virions among HIV-infected individuals. With geographical distribution of subtypes its evolution and unpredictable process and intermixing of HIV-1 variants is inevitable. Recombinant viruses contribute already substantially to the global pandemic especially in sub-Saharan African. East Africa studies has shown more complex mixture of HIV-1 Subtypes and associated recombinant virus especially in Tanzania.

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“…V3 peptide serology is an easy technique and can be useful particularly in developing countries, where resources are limited. In addition, the peptides have amino acid sequences and conformations that may minimize the differences in V3 loop conformation between subtypes (16,17).…”

Section: Introductionmentioning

confidence: 99%

Techniques used to identify the Brazilian variant of HIV-1 subtype B

Komninakis¹,

Fukumori²,

Alcalde³

et al. 2007

Braz J Med Biol Res

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The purpose of the present study was to compare the sensitivity and specificity of V3 enzyme immunoassay (solid phase EIA and EIA inhibition) and restriction fragment length polymorphism (RFLP) with the DNA sequencing "gold standard" to identify the Brazilian HIV-1 variants of subtype B and B"-GWGR. Peripheral blood mononuclear cells were collected from 61 HIV-1-infected individuals attending a clinic in São Paulo. Proviral DNA was amplified and sequentially cleaved with the Fok I restriction enzyme. Plasma samples were submitted to a V3-loop biotinylated synthetic peptide EIA. Direct partial DNA sequencing of the env gene was performed on all samples. Based on EIA results, the sensitivity for detecting B-GPGR was 70%, compared to 64% for the Brazilian variant B"-GWGR while, the specificity of B-GPGR detection was 85%, compared to 88% for GWGR. The assessment of RFLP revealed 68% sensitivity and 94% specificity for the B-GPGR strain compared to 84 and 90% for the B"-GWGR variant. Moreover, direct DNA sequencing was able to detect different base sequences corresponding to amino acid sequences at the tip of the V3 loop in 22 patients. These results show a similar performance of V3 serology and RLFP in identifying the Brazilian variant GWGR. However, V3 peptide serology may give indeterminate results. Therefore, we suggest that V3 serology be used instead of DNA sequencing where resources are limited. Samples giving indeterminate results by V3 peptide serology should be analyzed by direct DNA sequencing to distinguish between B-GPGR and the Brazilian variant B"-GWGR.

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Different Rates of Disease Progression of HIV Type 1 Infection in Tanzania Based on Infecting Subtype

Abstract: We observed heterogeneity in the rates of disease progression of HIV-1 disease in infected persons, on the basis of the infecting subtype. Subtype D was associated with the most rapid progression of the disease, relative to the other 3 categories of viruses in our cohort.

Cited by 180 publications

References 40 publications

GenGIS: A geospatial information system for genomic data

GenGIS: A geospatial information system for genomic data

HIV-1 Diversity in Tanzania and its Implication toward Development of Effective Vaccines: A Review Article

Techniques used to identify the Brazilian variant of HIV-1 subtype B

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