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A donor-specific epigenetic classifier for acute graft-versus-host disease severity in hematopoietic stem cell transplantation

Overview of attention for article published in Genome Medicine, December 2015
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (79th percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

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13 tweeters

Citations

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6 Dimensions

Readers on

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43 Mendeley
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Title
A donor-specific epigenetic classifier for acute graft-versus-host disease severity in hematopoietic stem cell transplantation
Published in
Genome Medicine, December 2015
DOI 10.1186/s13073-015-0246-z
Pubmed ID
Authors

Dirk S. Paul, Allison Jones, Rob S. Sellar, Neema P. Mayor, Andrew Feber, Amy P. Webster, Neuza Afonso, Ruhena Sergeant, Richard M. Szydlo, Jane F. Apperley, Martin Widschwendter, Stephen Mackinnon, Steven G. E. Marsh, J. Alejandro Madrigal, Vardhman K. Rakyan, Karl S. Peggs, Stephan Beck

Abstract

Allogeneic hematopoietic stem cell transplantation (HSCT) is a curative treatment for many hematological conditions. Acute graft-versus-host disease (aGVHD) is a prevalent immune-mediated complication following HSCT. Current diagnostic biomarkers that correlate with aGVHD severity, progression, and therapy response in graft recipients are insufficient. Here, we investigated whether epigenetic marks measured in peripheral blood of healthy graft donors stratify aGVHD severity in human leukocyte antigen (HLA)-matched sibling recipients prior to T cell-depleted HSCT. We measured DNA methylation levels genome-wide at single-nucleotide resolution in peripheral blood of 85 HSCT donors, matched to recipients with various transplant outcomes, with Illumina Infinium HumanMethylation450 BeadChips. Using genome-wide DNA methylation profiling, we showed that epigenetic signatures underlying aGVHD severity in recipients correspond to immune pathways relevant to aGVHD etiology. We discovered 31 DNA methylation marks in donors that associated with aGVHD severity status in recipients, and demonstrated strong predictive performance of these markers in internal cross-validation experiments (AUC = 0.98, 95 % CI = 0.96-0.99). We replicated the top-ranked CpG classifier using an alternative, clinical DNA methylation assay (P = 0.039). In an independent cohort of 32 HSCT donors, we demonstrated the utility of the epigenetic classifier in the context of a T cell-replete conditioning regimen (P = 0.050). Our findings suggest that epigenetic typing of HSCT donors in a clinical setting may be used in conjunction with HLA genotyping to inform both donor selection and transplantation strategy, with the ultimate aim of improving patient outcome.

Twitter Demographics

The data shown below were collected from the profiles of 13 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 43 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 2%
Unknown 42 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 11 26%
Researcher 10 23%
Other 7 16%
Professor 2 5%
Student > Doctoral Student 2 5%
Other 6 14%
Unknown 5 12%
Readers by discipline Count As %
Agricultural and Biological Sciences 10 23%
Biochemistry, Genetics and Molecular Biology 8 19%
Medicine and Dentistry 8 19%
Computer Science 2 5%
Immunology and Microbiology 2 5%
Other 4 9%
Unknown 9 21%

Attention Score in Context

This research output has an Altmetric Attention Score of 7. 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 06 April 2016.
All research outputs
#4,050,031
of 20,418,018 outputs
Outputs from Genome Medicine
#794
of 1,324 outputs
Outputs of similar age
#81,835
of 397,407 outputs
Outputs of similar age from Genome Medicine
#72
of 111 outputs
Altmetric has tracked 20,418,018 research outputs across all sources so far. Compared to these this one has done well and is in the 80th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,324 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 23.4. This one is in the 39th percentile – i.e., 39% of its peers scored the same or lower than it.
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 397,407 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 79% of its contemporaries.
We're also able to compare this research output to 111 others from the same source and published within six weeks on either side of this one. This one is in the 34th percentile – i.e., 34% of its contemporaries scored the same or lower than it.