Evidence map›Paper›PMID 42907884›Full record

ArticleGenome medicine2026

Cross-species molecular stratification enables T cell receptor diagnosis of Parkinson's disease.

Jiayu Chen, Xian Xia, Yuruo Zhang, Xiaoge Tong, Yue Liang, Xiangding Fan, Qinghao Meng, Yihong Wei, Gang Hu

Abstract read
In one paragraph

Article in Genome medicine, 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

9 authors.

Jiayu Chen *Jiangsu Key Laboratory of Neurodegeneration, Department of Pharmacology, School of Basic Medical Sciences, Nanjing Medical University, Nanjing, China.
Xian Xia *Jiangsu Key Laboratory of Neurodegeneration, Department of Pharmacology, School of Basic Medical Sciences, Nanjing Medical University, Nanjing, China. xianxia@njmu.edu.cn.
Yuruo ZhangSchool of Medicine, Nanjing University of Chinese Medicine, Nanjing, China.
Xiaoge TongSchool of Medicine, Nanjing University of Chinese Medicine, Nanjing, China.
Yue LiangJiangsu Key Laboratory of Neurodegeneration, Department of Pharmacology, School of Basic Medical Sciences, Nanjing Medical University, Nanjing, China.
Xiangding FanJiangsu Key Laboratory of Neurodegeneration, Department of Pharmacology, School of Basic Medical Sciences, Nanjing Medical University, Nanjing, China.
Qinghao MengJiangsu Key Laboratory of Neurodegeneration, Department of Pharmacology, School of Basic Medical Sciences, Nanjing Medical University, Nanjing, China.
Yihong WeiSchool of Medicine, Nanjing University of Chinese Medicine, Nanjing, China.
Gang HuJiangsu Key Laboratory of Neurodegeneration, Department of Pharmacology, School of Basic Medical Sciences, Nanjing Medical University, Nanjing, China. ghu@njmu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDeveloping peripheral blood-based diagnostic models for idiopathic Parkinson's disease (iPD), particularly those leveraging the T-cell receptor (TCR) repertoire, has long been considered infeasible because patient-derived TCRs appear to lack convergent sequence motifs. We reasoned that this apparent absence of shared TCR features likely reflects both insufficient sample sizes and unaccounted immune heterogeneity within the iPD population.

methodsWe reconstructed TCR repertoires from the two largest iPD cohorts currently available, anchoring them with three mechanistically distinct mouse models to stratify patients into model-anchored informed subtypes. Within these data-driven subtypes, we trained subtype-specific, multimodal multi-instance classifiers.

resultsWe demonstrated that iPD patients can be successfully stratified into model-anchored informed subtypes. Furthermore, the trained subtype-specific, multimodal multi-instance classifiers achieved an Area Under Curve (AUC) exceeding 0.8 for both subtypes.

conclusionsOur findings underscore the critical role of disease stratification in enabling TCR repertoire-based modeling in neurodegenerative diseases.

Indexed as

Parkinson DiseaseReceptors, Antigen, T-CellAnimalsDisease Models, AnimalHumansMachine LearningMiceReceptors, Antigen, T-CellDiagnosisMachine learningParkinson’s diseaseT-cell receptor

Identifiers

PMID42907884
PMCPMC13689350

What OpenQuestion holds

Textmetadata
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.