Evidence map›Paper›PMID 33918115›Full record

ReviewGenes2021

Elucidation of Early Evolution of HIV-1 Group M in the Congo Basin Using Computational Methods.

Marcel Tongo, Darren P Martin, Jeffrey R Dorfman

Abstract readReview
In one paragraph

Review in Genes, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
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

3 authors.

Marcel TongoCenter for Research on Emerging and Re-Emerging Diseases (CREMER), Institute of Medical Research and Study of Medicinal Plants (IMPM), Yaoundé, Cameroon.ORCID 0000-0002-5262-892X
Darren P MartinDivision of Computational Biology, Department of Integrative Biomedical Sciences and Institute of Infectious Disease and Molecular Medicine, Faculty of Health Sciences, University of Cape Town, Cape Town 7925, South Africa.
Jeffrey R DorfmanDivision of Medical Virology, School of Pathology, Faculty of Health Sciences, Stellenbosch University, Cape Town 7505, South Africa.ORCID 0000-0001-9938-8911

Funding

Wellcome Trust 107752/Z/15/Z
6 · The paper itself

Abstract

The Congo Basin region is believed to be the site of the cross-species transmission event that yielded HIV-1 group M (HIV-1M). It is thus likely that the virus has been present and evolving in the region since that cross-species transmission. As HIV-1M was only discovered in the early 1980s, our directly observed record of the epidemic is largely limited to the past four decades. Nevertheless, by exploiting the genetic relatedness of contemporary HIV-1M sequences, phylogenetic methods provide a powerful framework for investigating simultaneously the evolutionary and epidemiologic history of the virus. Such an approach has been taken to find that the currently classified HIV-1 M subtypes and Circulating Recombinant Forms (CRFs) do not give a complete view of HIV-1 diversity. In addition, the currently identified major HIV-1M subtypes were likely genetically predisposed to becoming a major component of the present epidemic, even before the events that resulted in the global epidemic. Further efforts have identified statistically significant hot- and cold-spots of HIV-1M subtypes sequence inheritance in genomic regions of recombinant forms. In this review we provide ours and others recent findings on the emergence and spread of HIV-1M variants in the region, which have provided insights into the early evolution of this virus.

Indexed as

Computational BiologyCongoEpidemicsEvolution, MolecularGenetic VariationHIV-1HIV InfectionsHumansPhylogenyCongo BasinevolutionHIV-1 group M (HIV-1M)phylogeneticsequences

Identifiers

PMID33918115
PMCPMC8065694

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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.