Evidence map›Paper›PMID 21896007›Full record

ReviewImmunology2011

The emerging role of HLA-C in HIV-1 infection.

Deanna A Kulpa, Kathleen L Collins

Open access · greenAbstract readReview
In one paragraph

Review in Immunology, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers.

0numbers the graph read from it
0cells of the map it votes in
38citing papers in PubMed
2.6field-weighted citation impact, top 11% 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

38 citing papers in PubMed, 64 citations in OpenAlex.

  1. Trial
  2. Article
  3. Article
  4. Article
  5. The immunogenetics of COVID-19.Immunogenetics · 2023
    Review
  6. Article
  7. Review
  8. Article
  9. Review
  10. Article
  11. Article
  12. Influence of Disease Severity and Gender on HLA-C Methylation in COVID-19 Patients.Iranian journal of science and technology. Transaction A, Science · 2022
    Article
  13. Review
  14. Article
  15. Article
  16. Article
  17. HLA-C: An Accomplice in Rheumatic Diseases.ACR open rheumatology · 2019
    Review
  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

2 authors at 2 institutions in 1 country.

Deanna A KulpaDepartment of Internal Medicine, University of Michigan, Ann Arbor, MI, USA. klcollin@med.umich.edu
Kathleen L Collins
Michigan Medicine · USUniversity of Michigan–Ann Arbor · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recently, genome-wide association studies have identified the major histocompatibility complex class I protein HLA-C as an important molecule that affects HIV disease progression. The association between HLA-C and HIV disease outcome was originally determined through a single nucleotide polymorphism (SNP) 35 kb upstream of the HLA-C locus. More recent work has focused on elucidating the functional significance of the -35 SNP, and several groups now have demonstrated HLA-C surface expression to be a key element in control of HIV viral load, with higher surface expression associating with slower disease progression. Most recently, control of HLA-C surface expression has been correlated with the presence of microRNA binding sites that affect HLA-C expression and control of HIV disease. This review highlights these results and explores the ways in which HLA-C surface expression could affect immune system function in the setting of HIV disease.

Indexed as

Amino Acid SequenceDisease ProgressionHIV-1HIV InfectionsHLA-C AntigensHumansKiller Cells, NaturalMicroRNAsMolecular Sequence Datanef Gene Products, Human Immunodeficiency VirusT-Lymphocytes, CytotoxicHLA-C AntigensMicroRNAsnef Gene Products, Human Immunodeficiency Virus

Identifiers

PMID21896007
PMCPMC3194220
OpenAlexW1517627944

What OpenQuestion holds

Textmetadata
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.