Evidence map›Paper›PMID 38633407›Full record

ArticleFrontiers in genetics2024

Donor whole blood DNA methylation is not a strong predictor of acute graft

Amy P Webster, Simone Ecker, Ismail Moghul, Xiaohong Liu, Pawan Dhami, Sarah Marzi, Dirk S Paul, Michelle Kuxhausen, Stephanie J Lee, Stephen R Spellman and 5 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in genetics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.7field-weighted citation impact, top 32% 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

2 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
  2. 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

15 authors at 8 institutions in 3 countries.

Amy P WebsterUCL Cancer Institute, University College London, London, United Kindom.
Simone EckerUCL Cancer Institute, University College London, London, United Kindom.
Ismail MoghulUCL Cancer Institute, University College London, London, United Kindom.
Xiaohong LiuUCL Cancer Institute, University College London, London, United Kindom.
Pawan DhamiUCL Cancer Institute, University College London, London, United Kindom.
Sarah MarziBlizard Institute, Barts and the London School of Medicine and Dentistry, London, United Kindom.
Dirk S PaulCardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kindom.
Michelle KuxhausenCenter for International Blood and Marrow Transplant Research, NMDP, Minneapolis, United Kindom.
Stephanie J LeeCenter for International Blood and Marrow Transplant Research, Medical College of Wisconsin, Milwaukee, United Kindom.
Stephen R SpellmanCenter for International Blood and Marrow Transplant Research, NMDP, Minneapolis, United Kindom.
Tao WangCenter for International Blood and Marrow Transplant Research, Medical College of Wisconsin, Milwaukee, United Kindom.
Andrew FeberUCL Cancer Institute, University College London, London, United Kindom.
Vardhman RakyanBlizard Institute, Barts and the London School of Medicine and Dentistry, London, United Kindom.
Karl S PeggsUCL Cancer Institute, University College London, London, United Kindom.
Stephan BeckUCL Cancer Institute, University College London, London, United Kindom.
University College London · GBCancer Institute (WIA) · INMedical College of Wisconsin · USNational Marrow Donor Program · USQueen Mary University of London · GBGuy's Hospital · GBUniversity of Cambridge · GBUniversity of Exeter · GB

Funding

Data Resource for Analyzing Blood &Marrow TransplantsU24CA076518 · NCI · MEDICAL COLLEGE OF WISCONSIN · PI Amy M Moskop, Bronwen Shaw · 1998 to 2026
$105.2M
NTP INFORMATION SYSTEMS SUPPORT27305C0011 · NIEHS · Z-TECH CORPORATION · 2007 to 2009
$4.3M
PROVIDE RABBITS, RATS, IMCE, HAMSTERS, GERBILS, AND GUINEA PIGS27307C0009 · NIEHS · PI MARSION, LESLIE · 2007 to 2007
$540k
PROVIDE RABBITS, RATS, MICE, HAMSTERS, GERBILS, GUINEA PIGS27307C0011 · NIEHS · PI BOLEN, WAYNE · 2007 to 2007
$500k
CLC NIH HHS C0000008NCI NIH HHS U24 CA076518NIEHS NIH HHS 27305C0011NIEHS NIH HHS 27307C0009NIEHS NIH HHS 27307C0011NIEHS NIH HHS 27398C0011
6 · The paper itself

Abstract

Allogeneic hematopoietic cell transplantation (HCT) is used to treat many blood-based disorders and malignancies, however it can also result in serious adverse events, such as the development of acute graft-versus-host disease (aGVHD). This study aimed to develop a donor-specific epigenetic classifier to reduce incidence of aGVHD by improving donor selection. Genome-wide DNA methylation was assessed in a discovery cohort of 288 HCT donors selected based on recipient aGVHD outcome; this cohort consisted of 144 cases with aGVHD grades III-IV and 144 controls with no aGVHD. We applied a machine learning algorithm to identify CpG sites predictive of aGVHD. Receiver operating characteristic (ROC) curve analysis of these sites resulted in a classifier with an encouraging area under the ROC curve (AUC) of 0.91. To test this classifier, we used an independent validation cohort (n = 288) selected using the same criteria as the discovery cohort. Attempts to validate the classifier failed with the AUC falling to 0.51. These results indicate that donor DNA methylation may not be a suitable predictor of aGVHD in an HCT setting involving unrelated donors, despite the initial promising results in the discovery cohort. Our work highlights the importance of independent validation of machine learning classifiers, particularly when developing classifiers intended for clinical use.

Indexed as

biomarker identification and validationDNA methylationepigeneticshaematopoietic stem cell transplantHCT (hematopoietic cell transplant)machine learning

Identifiers

PMID38633407
PMCPMC11021570
OpenAlexW4393867388

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.