Evidence map›Paper›PMID 18788913›Full record

ArticleAIDS research and human retroviruses2008

Bioinformatic prediction programs underestimate the frequency of CXCR4 usage by R5X4 HIV type 1 in brain and other tissues.

Megan E Mefford, Paul R Gorry, Kevin Kunstman, Steven M Wolinsky, Dana Gabuzda

Abstract readCase Reports
In one paragraph

Article in AIDS research and human retroviruses, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed
1.5field-weighted citation impact, top 19% 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

21 citing papers in PubMed, 28 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. Review
  5. Article
  6. HIV-1 target cells in the CNS.Journal of neurovirology · 2015
    Review
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Review
  14. Editorial neuroAIDS review.AIDS (London, England) · 2011
    Review
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Review
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

5 authors at 4 institutions in 2 countries.

Megan E MeffordDepartment of Cancer Immunology and AIDS, Dana-Farber Cancer Institute, Boston, Massachusetts 02115, USA.
Paul R Gorry
Kevin Kunstman
Steven M Wolinsky
Dana Gabuzda
Northwestern University · USBurnet Institute · AUDana-Farber Cancer Institute · USHarvard University · US

Funding

CHEMOKINE RECEPTORS IN HIV1 INFECTION OF THE CNSR01NS037277 · NINDS · DANA-FARBER CANCER INSTITUTE · PI GABUZDA, DANA H. · 1998 to 2006
$2.9M
Env-Receptor Interactions in HIV-1 Infection of the CNSR01MH083588 · NIMH · DANA-FARBER CANCER INST · PI GABUZDA, DANA H. · 2007 to 2011
$2.9M
characterization of gp120 C3 Variants that Influence HIV NeurotropismF31NS060644 · NINDS · HARVARD MEDICAL SCHOOL · PI MEFFORD, MEGAN E · 2007 to 2009
$83k
NIMH NIH HHS MH83588NIMH NIH HHS R01 MH083588NINDS NIH HHS 1F31NS060611-01NINDS NIH HHS F31 NS060644NINDS NIH HHS NS37277NINDS NIH HHS R01 NS037277
6 · The paper itself

Abstract

Human immunodeficiency virus (HIV-1) variants in brain primarily use CCR5 for entry into macrophages and microglia, but dual-tropic (R5X4) HIV-1 has been detected in brain and cerebral spinal fluid (CSF) of some patients with HIV-associated dementia (HAD). Here, we sequenced the gp120 coding region of nine full-length dual-tropic (R5X4) env genes cloned directly from autopsy brain and spleen tissue from an AIDS patient with severe HAD. We then compiled a dataset of 30 unique clade B R5X4 Env V3 sequences from this subject and 16 additional patients (n = 4 brain and 26 lymphoid/blood) and used it to compare the ability of six bioinformatic algorithms to correctly predict CXCR4 usage in R5X4 Envs. Only one program (SVM(geno2pheno)) correctly predicted the ability of R5X4 Envs in this dataset to use CXCR4 with 90% accuracy (n = 27/30 predicted to use CXCR4). The PSSM(SINSI), Random Forest, and SVM(genomiac) programs and the commonly used charge rule correctly predicted CXCR4 usage with >50% accuracy (22/30, 16/30, 19/30, and 25/30, respectively), while the PSSM(X4R5) matrix and "11/25" rule correctly predicted CXCR4 usage in <50% of the R5X4 Envs (10/30 and 13/30, respectively). Two positions in the V3 loop (19 and 32) influenced coreceptor usage predictions of nine R5X4 Envs from patient MACS1 and a total of 12 Envs from the dataset (40% of unique V3 sequences). These results demonstrate that most predictive algorithms underestimate the frequency of R5X4 HIV-1 in brain and other tissues. SVM(geno2pheno) is the most accurate predictor of CXCR4 usage by R5X4 HIV-1.

Indexed as

Virus InternalizationAIDS Dementia ComplexAlgorithmsAmino Acid SequenceBrainComputational BiologyHIV-1HIV Envelope Protein gp120HIV InfectionsHumansMaleMolecular Sequence DataPhylogenyReceptors, CXCR4Sequence AlignmentSequence Analysis, DNAgp120 protein, Human immunodeficiency virus 1HIV Envelope Protein gp120Receptors, CXCR4

Identifiers

PMID18788913
PMCPMC2801411
OpenAlexW1973539155

What OpenQuestion holds

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Read underepoch 390

Registered trials

None linked

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.