ArticleCommunications biology2021
High-throughput sequencing defines donor and recipient HLA B-cell epitope frequencies for prospective matching in transplantation.
Article in Communications biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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.
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.
Who cites it
11 citing papers in PubMed, 17 citations in OpenAlex.
- Article
- Simulation of prospective PIRCHE-II molecular matching in Canada: a feasibility study.Frontiers in immunology · 2026Article
- Eplet mismatch analysis in kidney transplantation: from concept to clinical practice.Clinical transplantation and research · 2025Review
- The Progress and Challenges of Implementing HLA Molecular Matching in Clinical Practice.Transplant international : official journal of the European Society for Organ Transplantation · 2025Review
- Editorial: Novel applications of epitope biology to improve outcomes in transplantation.Frontiers in genetics · 2025Article
- Article
- Canadian Kidney Transplant Professionals' Perspectives on Precision Medicine and Molecular Matching in Kidney Allocation.Transplantation direct · 2024Article
- An Integrated Approach Using HLAMatchmaker and Pirche II for Epitopic Matching in Pediatric Kidney Transplant-A Romanian Single-Center Study.Children (Basel, Switzerland) · 2023Article
- Pediatric Kidney Transplantation-Can We Do Better? The Promise and Limitations of Epitope/Eplet Matching.Frontiers in pediatrics · 2022Review
- Snowflake epitope matching correlates with child-specific antibodies during pregnancy and donor-specific antibodies after kidney transplantation.Frontiers in immunology · 2022Article
- The portrayal of organ donation on TikTok: A content analysis of popular English-language TikTok videos.Digital healthArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
13 authors at 20 institutions in 9 countries.
Funding
Abstract
Compatibility for human leukocyte antigen (HLA) genes between transplant donors and recipients improves graft survival but prospective matching is rarely performed due to the vast heterogeneity of this gene complex. To reduce complexity, we have combined next-generation sequencing and in silico mapping to determine transplant population frequencies and matching probabilities of 150 antibody-binding eplets across all 11 classical HLA genes in 2000 ethnically heterogeneous renal patients and donors. We show that eplets are more common and uniformly distributed between donors and recipients than the respective HLA isoforms. Simulations of targeted eplet matching shows that a high degree of overall compatibility, and perfect identity at the clinically important HLA class II loci, can be obtained within a patient waiting list of approximately 250 subjects. Internal epitope-based allocation is thus feasible for most major renal transplant programs, while regional or national sharing may be required for other solid organs.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.