Evidence map›Paper›PMID 35101308›Full record

ArticleHuman immunology2022

hlaR: A rapid and reproducible tool to identify eplet mismatches between transplant donors and recipients.

Aileen C Johnson, Joan Zhang, H Cliff Sullivan, Chris Wiebe, Robert Bray, Howard Gebel, Christian P Larsen

Open access · greenAbstract read
In one paragraph

Article in Human immunology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
2.3field-weighted citation impact, top 13% 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

5 citing papers in PubMed, 11 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Belatacept with time-limited tacrolimus coimmunosuppression modifies the 3-year risk of eplet mismatch in kidney transplantation.American journal of transplantation : official journal of the American Society of Transplantation and the American Society of Transplant Surgeons · 2024
    Article
  5. 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

7 authors at 2 institutions in 2 countries.

Aileen C JohnsonDepartment of Surgery, Emory University, United States.
Joan ZhangDepartment of Surgery, Emory University, United States.
H Cliff SullivanDepartment of Pathology, Emory University, United States.
Chris WiebeDepartment of Medicine, University of Manitoba, Winnipeg, Manitoba, Canada.
Robert BrayDepartment of Pathology, Emory University, United States.
Howard GebelDepartment of Pathology, Emory University, United States.
Christian P LarsenDepartment of Surgery, Emory University, United States. Electronic address: clarsen@emory.edu.
Emory University · USUniversity of Manitoba · CA

Funding

Transplant Tolerance in Non-Human PrimatesU19AI051731 · NIAID · UNIVERSITY OF WESTERN ONTARIO · PI ADAMS, ANDREW B · 2002 to 2022
$54.1M
Selective CD28 Blockade in Renal Transplant RecipientsU01AI138909 · NIAID · EMORY UNIVERSITY · PI BADELL, IDELBERTO RAUL, FORD, MANDY L · 2018 to 2022
$4.9M
Optimizing Strategies to Overcome Kidney Xenograft RejectionR01AI126322 · NIAID · UNIVERSITY OF MINNESOTA · PI ADAMS, ANDREW B · 2016 to 2020
$4.6M
Advanced Research Training in Transplantation ScienceT32AI070081 · NIAID · EMORY UNIVERSITY · PI Mandy L Ford · 2006 to 2026
$3.1M
Reducing Disparities among Kidney Transplant RecipientsR01MD011682 · NIMHD · EMORY UNIVERSITY · PI ADAMS, ANDREW B, PATZER, RACHEL E · 2017 to 2021
$2.4M
NIAID NIH HHS R01 AI126322NIAID NIH HHS T32 AI070081NIAID NIH HHS U01 AI138909NIAID NIH HHS U19 AI051731NIMHD NIH HHS R01 MD011682
6 · The paper itself

Abstract

Eplet mismatch load, both overall and at the single molecule level, correlates with transplant recipient outcomes. However, precise eplet assessment requires high-resolution HLA typing of both the donor and recipient. Anything less than high-resolution typing requires imputation of HLA types. The currently available methods to identify eplet mismatch are both tedious and demanding. Therefore, we developed a software package and user-friendly web application (hlaR), that simplifies the workflow of eplet analysis, provides functions to impute high-resolution from low-resolution data and calculates both overall and single molecule eplet mismatch for single or multiple donor recipient pairs. Compared to manual assessments using currently available tools (namely, HLAMatchMaker), hlaR resulted in only minimal discrepancy in eplet mismatches (mean absolute difference of 0.56 for class I and 0.86 for class II for unique sum across loci). Additionally, output of the single molecule eplet function compared well to manual calculation, with an average single antigen count increase of 0.19. Importantly, the hlaR tool permits rapid and reproducible imputation and eplet mismatch including comparison between eplet reference tables (e.g. HLAMatchMaker version 2 or 3). Users can import data from a spreadsheet rather than relying on keystroke entry of individual donor and recipient data, thus reducing the risk of data entry errors. The resulting improved scalability of the hlaR tool is highlighted by plotting analysis time against the size of the input dataset. The new hlaR tool can provide eplet mismatch data with a streamlined workflow. With decreased effort from the end user, eplet matching and mismatch load data can be further incorporated into both research and clinical use.

Indexed as

Graft RejectionKidney TransplantationHistocompatibility TestingHLA AntigensHumansTissue DonorsTransplant RecipientsHLA AntigensEpitopeEpletHLAImputationSoftware

Identifiers

PMID35101308
PMCPMC11016307
OpenAlexW4210532306

What OpenQuestion holds

Textmetadata
LicenceTDM
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.