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Balance between transmitted HLA preadapted and nonassociated polymorphisms is a major determinant of HIV-1 disease progression

Overview of attention for article published in The Journal of Experimental Medicine, August 2016
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  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (95th percentile)
  • High Attention Score compared to outputs of the same age and source (82nd percentile)

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7 news outlets
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3 X users
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1 Facebook page
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1 Google+ user

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34 Mendeley
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Article details
Title
Balance between transmitted HLA preadapted and nonassociated polymorphisms is a major determinant of HIV-1 disease progression
Published in
The Journal of Experimental Medicine, August 2016
DOI 10.1084/jem.20151984
Pubmed ID
Authors
Abstract

HIV-1 adapts to a new host through mutations that facilitate immune escape. Here, we evaluate the impact on viral control and disease progression of transmitted polymorphisms that were either preadapted to or nonassociated with the new host's HLA. In a cohort of 169 Zambian heterosexual transmission pairs, we found that almost one-third of possible HLA-linked target sites in the transmitted virus Gag protein are already adapted, and that this transmitted preadaptation significantly reduced early immune recognition of epitopes. Transmitted preadapted and nonassociated polymorphisms showed opposing effects on set-point VL and the balance between the two was significantly associated with higher set-point VLs in a multivariable model including other risk factors. Transmitted preadaptation was also significantly associated with faster CD4 decline (<350 cells/µl) and this association was stronger after accounting for nonassociated polymorphisms, which were linked with slower CD4 decline. Overall, the relative ratio of the two classes of polymorphisms was found to be the major determinant of CD4 decline in a multivariable model including other risk factors. This study reveals that, even before an immune response is mounted in the new host, the balance of these opposing factors can significantly influence the outcome of HIV-1 infection.

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X Demographics

X Demographics

The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 34 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
Unknown 34 100%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Ph. D. Student 8 24%
Researcher 8 24%
Professor > Associate Professor 4 12%
Student > Bachelor 2 6%
Professor 2 6%
Other 3 9%
Unknown 7 21%
Readers by discipline
Readers by discipline Count As %
Immunology and Microbiology 8 24%
Biochemistry, Genetics and Molecular Biology 7 21%
Agricultural and Biological Sciences 6 18%
Medicine and Dentistry 2 6%
Computer Science 1 3%
Other 2 6%
Unknown 8 24%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 48. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 25 August 2016.
All research outputs
#1,110,841
of 34,447,360 outputs
Outputs from The Journal of Experimental Medicine
#587
of 13,372 outputs
Outputs of similar age
#15,041
of 345,011 outputs
Outputs of similar age from The Journal of Experimental Medicine
#11
of 63 outputs
Altmetric has tracked 34,447,360 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 13,372 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.3. This one has done particularly well, scoring higher than 95% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 345,011 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 95% of its contemporaries.
We're also able to compare this research output to 63 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 82% of its contemporaries.