Evidence map›Paper›PMID 42135629›Full record

ReviewBMC immunology2026

Clinical applications and methodology updates in HLA typing.

Kaihao Feng, Le Chang, Ying Yan, Huizhen Sun, Yi Liu, Shi Song, Abudulimutailipu Nuermaimaiti, Shana Halemubieke, Ling Mei, Qian Su and 4 more

Abstract readReview
In one paragraph

Review in BMC 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

14 authors.

Kaihao FengBeijing Hospital, National center for Gerontology, The Key Laboratory of Geriatrics of NHC, Institute of Geriatric Medicine, National Center for Clinical Laboratories, National Clinical Research Center for Gerontology, Chinese Academy of Medical Sciences, Beijing, P.R. China.
Le ChangBeijing Hospital, National center for Gerontology, The Key Laboratory of Geriatrics of NHC, Institute of Geriatric Medicine, National Center for Clinical Laboratories, National Clinical Research Center for Gerontology, Chinese Academy of Medical Sciences, Beijing, P.R. China.
Ying YanBeijing Hospital, National center for Gerontology, The Key Laboratory of Geriatrics of NHC, Institute of Geriatric Medicine, National Center for Clinical Laboratories, National Clinical Research Center for Gerontology, Chinese Academy of Medical Sciences, Beijing, P.R. China.
Huizhen SunBeijing Hospital, National center for Gerontology, The Key Laboratory of Geriatrics of NHC, Institute of Geriatric Medicine, National Center for Clinical Laboratories, National Clinical Research Center for Gerontology, Chinese Academy of Medical Sciences, Beijing, P.R. China.
Yi LiuMilitary Hospital of the People's Liberation Army, Xi'an, Shaanxi, 63750, P. R. China.
Shi SongBeijing Hospital, National center for Gerontology, The Key Laboratory of Geriatrics of NHC, Institute of Geriatric Medicine, National Center for Clinical Laboratories, National Clinical Research Center for Gerontology, Chinese Academy of Medical Sciences, Beijing, P.R. China.
Abudulimutailipu NuermaimaitiBeijing Hospital, National center for Gerontology, The Key Laboratory of Geriatrics of NHC, Institute of Geriatric Medicine, National Center for Clinical Laboratories, National Clinical Research Center for Gerontology, Chinese Academy of Medical Sciences, Beijing, P.R. China.
Shana HalemubiekeBeijing Hospital, National center for Gerontology, The Key Laboratory of Geriatrics of NHC, Institute of Geriatric Medicine, National Center for Clinical Laboratories, National Clinical Research Center for Gerontology, Chinese Academy of Medical Sciences, Beijing, P.R. China.
Ling MeiBeijing Hospital, National center for Gerontology, The Key Laboratory of Geriatrics of NHC, Institute of Geriatric Medicine, National Center for Clinical Laboratories, National Clinical Research Center for Gerontology, Chinese Academy of Medical Sciences, Beijing, P.R. China.
Qian SuBeijing Hospital, National center for Gerontology, The Key Laboratory of Geriatrics of NHC, Institute of Geriatric Medicine, National Center for Clinical Laboratories, National Clinical Research Center for Gerontology, Chinese Academy of Medical Sciences, Beijing, P.R. China.
Xinru LiuBeijing Hospital, National center for Gerontology, The Key Laboratory of Geriatrics of NHC, Institute of Geriatric Medicine, National Center for Clinical Laboratories, National Clinical Research Center for Gerontology, Chinese Academy of Medical Sciences, Beijing, P.R. China.
Zhuoqun LuBeijing Hospital, National center for Gerontology, The Key Laboratory of Geriatrics of NHC, Institute of Geriatric Medicine, National Center for Clinical Laboratories, National Clinical Research Center for Gerontology, Chinese Academy of Medical Sciences, Beijing, P.R. China.
Huimin JiBeijing Hospital, National center for Gerontology, The Key Laboratory of Geriatrics of NHC, Institute of Geriatric Medicine, National Center for Clinical Laboratories, National Clinical Research Center for Gerontology, Chinese Academy of Medical Sciences, Beijing, P.R. China. 18611420225@163.com.
Lunan WangBeijing Hospital, National center for Gerontology, The Key Laboratory of Geriatrics of NHC, Institute of Geriatric Medicine, National Center for Clinical Laboratories, National Clinical Research Center for Gerontology, Chinese Academy of Medical Sciences, Beijing, P.R. China. lunan99@163.com.

Funding

Beijing Natural Science Foundation L244070
6 · The paper itself

Abstract

The Human Leukocyte Antigen (HLA) system is a key component of the immune system, involving aspects such as autoimmune reactions, transplant rejection reactions, and related diseases. HLA typing technology enables precise decision-making in clinical tissue matching, disease susceptibility assessment, and drug response prediction. Therefore, this article summarizes the genetic characteristics of HLA, several commonly used methods for typing, including serological methods and molecular biology methods. It also explores the clinical applications of HLA typing, such as in organ and stem cell transplantation, blood transfusion, and disease association studies. In addition, in recent years, the combination of Single Nucleotide Polymorphism (SNP) and PCR technology has shown its potential application in various gene typing. In particular, the application of SNP-PCR method in HLA typing provides new possibilities for improving typing accuracy, reducing costs, and shortening detection time. Therefore, we summarize the existing HLA typing technologies and prospects for the future development of SNP-PCR method in HLA typing. With the continuous progress of bioinformatics and high-throughput sequencing technology, SNP-PCR is expected to become an efficient, economical, and widely used method for HLA typing, providing strong support for precision medicine. In addition, combined with big data analysis, SNP-PCR is expected to further reveal the complex associations between HLA and various diseases, thereby promoting in-depth research and development in immunology, genetics, and clinical medicine.

Indexed as

Histocompatibility TestingHLA AntigensHigh-Throughput Nucleotide SequencingHumansPolymerase Chain ReactionPolymorphism, Single NucleotideHLA AntigensDisease associationHLA typingHLA typing methodsTransfusionTransplant

Identifiers

PMID42135629
PMCPMC13374135

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.