Evidence map›Paper›PMID 28196510›Full record

ArticleVirology journal2017

Partial HIV C2V3 envelope sequence analysis reveals association of coreceptor tropism, envelope glycosylation and viral genotypic variability among Kenyan patients on HAART.

Rose C Kitawi, Carol W Hunja, Rashid Aman, Bernhards R Ogutu, Anne W T Muigai, Gilbert O Kokwaro, Washingtone Ochieng

Open access · goldAbstract read
In one paragraph

Article in Virology journal, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.4field-weighted citation impact, top 44% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 5 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 3 institutions in 2 countries.

Rose C KitawiCenter for Research in Therapeutic Sciences, Strathmore University, P.O. Box 59857-00200, Nairobi, Kenya.
Carol W HunjaCenter for Research in Therapeutic Sciences, Strathmore University, P.O. Box 59857-00200, Nairobi, Kenya.
Rashid AmanCenter for Research in Therapeutic Sciences, Strathmore University, P.O. Box 59857-00200, Nairobi, Kenya.
Bernhards R OgutuCenter for Research in Therapeutic Sciences, Strathmore University, P.O. Box 59857-00200, Nairobi, Kenya.
Anne W T MuigaiJomo Kenyatta University of Agriculture and Technology, P.O Box 62000 -00200, Nairobi, Kenya.
Gilbert O KokwaroInstitute of Healthcare Management, Strathmore University, P.O. Box 59857-00200, Nairobi, Kenya.
Washingtone OchiengCenter for Research in Therapeutic Sciences, Strathmore University, P.O. Box 59857-00200, Nairobi, Kenya. ochiengwashingtone@gmail.com.ORCID 0000-0002-9035-4405
Strathmore University · KEHarvard University · USJomo Kenyatta University of Agriculture and Technology · KE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHIV-1 is highly variable genetically and at protein level, a property it uses to subvert antiviral immunity and treatment. The aim of this study was to assess if HIV subtype differences were associated with variations in glycosylation patterns and co-receptor tropism among HAART patients experiencing different virologic treatment outcomes.

methodsA total of 118 HIV env C2V3 sequence isolates generated previously from 59 Kenyan patients receiving highly active antiretroviral therapy (HAART) were examined for tropism and glycosylation patterns. For analysis of Potential N-linked glycosylation sites (PNGs), amino acid sequences generated by the NCBI's Translate tool were applied to the HIVAlign and the N-glycosite tool within the Los Alamos Database. Viral tropism was assessed using Geno2Pheno (G2P), WebPSSM and Phenoseq platforms as well as using Raymond's and Esbjörnsson's rules. Chi square test was used to determine independent variables association and ANOVA applied on scale variables.

resultsAt respective False Positive Rate (FPR) cut-offs of 5% (p = 0.045), 10% (p = 0.016) and 20% (p = 0.005) for CXCR4 usage within the Geno2Pheno platform, HIV-1 subtype and viral tropism were significantly associated in a chi square test. Raymond's rule (p = 0.024) and WebPSSM (p = 0.05), but not Phenoseq or Esbjörnsson showed significant associations between subtype and tropism. Relative to other platforms used, Raymond's and Esbjörnsson's rules showed higher proportions of X4 variants, while WebPSSM resulted in lower proportions of X4 variants across subtypes. The mean glycosylation density differed significantly between subtypes at positions, N277 (p = 0.034), N296 (p = 0.036), N302 (p = 0.034) and N366 (p = 0.004), with HIV-1D most heavily glycosylated of the subtypes. R5 isolates had fewer PNGs than X4 isolates, but these differences were not significant except at position N262 (p = 0.040). Cell-associated isolates from virologic treatment success subjects were more glycosylated than cell-free isolates from virologic treatment failures both for the NXT (p = 0.016), and for all the patterns (p = 0.011).

conclusionThese data reveal significant associations of HIV-1 subtype diversity, viral co-receptor tropism, viral suppression and envelope glycosylation. These associations have important implications for designing therapy and vaccines against HIV. Heavy glycosylation and preference for CXCR4 usage of HIV-1D may explain rapid disease progression in patients infected with these strains.

Indexed as

Antiretroviral Therapy, Highly ActiveViral TropismComputational Biologyenv Gene Products, Human Immunodeficiency VirusGenetic VariationGlycosylationHIV-1HIV InfectionsHumansKenyaSequence Analysisenv Gene Products, Human Immunodeficiency VirusAfricaHIV-1KenyaPotential N-linked glycosylationSubtypeTreatmentTropism

Identifiers

PMID28196510
PMCPMC5310022
OpenAlexW2588098830

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.