Evidence map›Paper›PMID 38911277›Full record

ArticleTransplantation direct2024

HLA Genotype Imputation Results in Largely Accurate Epitope Mismatch Risk Categorization Across Racial Groups.

Gregory S Cohen, Alison J Gareau, Melissa A Kallarakal, Tayyiaba Farooq, Maria P Bettinotti, H Cliff Sullivan, Abeer Madbouly, Scott M Krummey

Abstract read
In one paragraph

Article in Transplantation direct, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
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

8 citing papers in PubMed.

  1. Imputed HLA typing as a practical approach to molecular mismatch risk stratification in kidney transplantation.Transplant international : official journal of the European Society for Organ Transplantation · 2026
    Article
  2. Article
  3. Article
  4. Article
  5. Review
  6. Article
  7. Optimizing kidney allocation: challenges and solutions.Current opinion in organ transplantation · 2025
    Review
  8. HLA-DR/DQ eplet mismatch predictsFrontiers in genetics · 2024
    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

8 authors.

Gregory S CohenDepartment of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD.
Alison J GareauDepartment of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD.
Melissa A KallarakalDepartment of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD.
Tayyiaba FarooqDepartment of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD.
Maria P BettinottiDepartment of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD.
H Cliff SullivanDepartment of Pathology and Laboratory Medicine, Emory University School of Medicine, Atlanta, GA.
Abeer MadboulyNational Marrow Donor Program/Be The Match, Minneapolis, MN.
Scott M KrummeyDepartment of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD.ORCID https://orcid.org/0000-0002-7504-9162

Funding

Data Resource for Analyzing Blood &Marrow TransplantsU24CA076518 · NCI · MEDICAL COLLEGE OF WISCONSIN · PI Amy M Moskop, Bronwen Shaw · 1998 to 2026
$105.2M
NCI NIH HHS U24 CA076518
6 · The paper itself

Abstract

Background: Biomarkers that predict posttransplant alloimmunity could lead to improved long-term graft survival. Evaluation of the number of mismatched epitopes between donor and recipient HLA proteins, termed molecular mismatch analysis, has emerged as an approach to classify transplant recipients as having high, intermediate, or low risk of graft rejection. When high-resolution genotypes are unavailable, molecular mismatch analysis requires algorithmic assignment, or imputation, of a high-resolution genotyping. Although imputation introduces inaccuracies in molecular mismatch analyses, it is unclear whether these inaccuracies would impact the clinical risk assessment for graft rejection. Methods: Using renal transplant patients and donors from our center, we constructed cohorts of surrogate donor-recipient pairs with high-resolution and low-resolution HLA genotyping that were racially concordant or discordant. We systemically assessed the impact of imputation on molecular mismatch analysis for cohorts of 180-200 donor-recipient pairs for each of 4 major racial groups. We also evaluated the effect of imputation for a racially diverse validation cohort of 35 real-world renal transplant pairs. Results: In the surrogate donor-recipient cohorts, imputation preserved the molecular mismatch risk category for 90.5%-99.6% of racially concordant donor-recipient pairs and 92.5%-100% of racially discordant pairs. In the validation cohort, which comprised 72% racially discordant pairs, we found that imputation preserved the molecular mismatch risk category for 97.1% of pairs. Conclusions: Overall, these data demonstrate that imputation preserves the molecular mismatch risk assessment in the vast majority of cases and provides evidence supporting imputation in the performance of molecular mismatch analysis for clinical assessment.

Identifiers

PMID38911277
PMCPMC11191912

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