Evidence map›Paper›PMID 41890757›Full record

ArticleFrontiers in immunology2026

Population-agnostic real-time molecular mismatch estimation using rSSO-defined HLA allele strings: minimal impact of allelic discordance with NGS.

Raja Rajalingam, Pawan Kumar Raghav, Neelam Sharma, Gilberto Da Gente, Denice Kong

Abstract read
In one paragraph

Article in Frontiers in immunology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

5 authors.

Raja RajalingamImmunogenetics and Transplantation Laboratory, Department of Surgery, University of California, San Francisco, San Francisco, CA, United States.
Pawan Kumar RaghavImmunogenetics and Transplantation Laboratory, Department of Surgery, University of California, San Francisco, San Francisco, CA, United States.
Neelam SharmaImmunogenetics and Transplantation Laboratory, Department of Surgery, University of California, San Francisco, San Francisco, CA, United States.
Gilberto Da GenteImmunogenetics and Transplantation Laboratory, Department of Surgery, University of California, San Francisco, San Francisco, CA, United States.
Denice KongImmunogenetics and Transplantation Laboratory, Department of Surgery, University of California, San Francisco, San Francisco, CA, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Molecular HLA mismatch at the epitope level is strongly associated with donor-specific antibody formation, antibody-mediated rejection, and graft failure after transplantation. Accurate molecular mismatch assessment requires high-resolution HLA typing; however, in clinical practice-particularly in deceased donor transplantation-typing is often performed at low or intermediate resolution. Haplotype-based imputation methods have been developed to infer high-resolution alleles but show variable accuracy, particularly in underrepresented populations. We evaluated whether the first allele listed in the reverse sequence-specific oligonucleotide (rSSO)-derived National Marrow Donor Program (NMDP) multiple allele code (MAC) string can serve as a practical surrogate for high-resolution typing in molecular mismatch assessment. Methods: We analyzed 4,738 individuals who underwent dual HLA typing by rSSO and next-generation sequencing (NGS) across 11 classical HLA loci. Concordance between the first allele of the rSSO MAC string and the corresponding two-field NGS allele was assessed. For discordant allele pairs, molecular disparity was quantified by calculating eplet mismatches using the HLA Eplet Mismatch Calculator. Results: Allele-level concordance exceeded 94% for 9 of 11 loci, including HLA-A (97.9%), -B (98.5%), -C (95.2%), -DRB1 (96.8%), -DRB3 (94.5%), -DRB5 (99.6%), -DQB1 (98.3%), -DPB1 (96.8%), and -DPA1 (98.7%). Lower concordance was observed for HLA-DQA1 (86.7%) and -DRB4 (72.0%). Most discordant NGS alleles, except for the DPB1 locus, were present in the rSSO MAC string. Among discordant allele pairs, 30.4% had zero eplet mismatches and 77.6% had two or fewer mismatched eplets. Allele pairs with more than two mismatched eplets accounted for less than 0.3% of all comparisons across loci. No significant differences in concordance were observed across racial or ethnic groups. Conclusion: The first allele listed in the rSSO-derived MAC string provides a reliable, population-agnostic surrogate for high-resolution HLA typing in molecular mismatch assessment. Although allele-level discordance occurs, it rarely results in clinically meaningful increases in eplet mismatch burden. This laboratory-based approach enables real-time molecular mismatch estimation in time-sensitive settings and facilitates retrospective analysis of cohorts lacking sequencing-based HLA data, supporting broader integration of molecular mismatch into precision transplantation practice.

Indexed as

AllelesHigh-Throughput Nucleotide SequencingHistocompatibility TestingHLA AntigensHumansHLA Antigenseplet mismatchhigh-resolution HLA typingHLA imputationHLA matchingHLA typingmolecular mismatchnext-generation sequencing (NGS)organ transplantation

Identifiers

PMID41890757
PMCPMC13013013

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.