Evidence map›Paper›PMID 42260594›Full record

ArticleArthritis research & therapy2026

Molecular classification of primary Sjögren's syndrome based on salivary gland omics.

Wuwei Zhuang, Qi Zhang, Jie Shen, Lin Zhu, Wenyan Shen, Xinyu Pu, Tingting Yan, Qiao Ye

Abstract read
In one paragraph

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

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0citing papers in PubMed
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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

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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

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No citing paper in PubMed yet.

4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

8 authors.

Wuwei Zhuang *Department of Rheumatology, The Second Affiliated Hospital of Jiaxing University, Jiaxing, People's Republic of China.
Qi Zhang *Department of Dermatology, Jinling Clinical Medical College, Nanjing Medical University, Nanjing, People's Republic of China.
Jie ShenDepartment of Rheumatology, The Second Affiliated Hospital of Jiaxing University, Jiaxing, People's Republic of China.
Lin ZhuDepartment of Rheumatology, The Second Affiliated Hospital of Jiaxing University, Jiaxing, People's Republic of China.
Wenyan ShenDepartment of Pathology, The Second Affiliated Hospital of Jiaxing University, Jiaxing, People's Republic of China.
Xinyu PuDepartment of Rheumatology, The Second Affiliated Hospital of Jiaxing University, Jiaxing, People's Republic of China.
Tingting YanDepartment of Rheumatology, The Second Affiliated Hospital of Jiaxing University, Jiaxing, People's Republic of China. candyytt@163.com.
Qiao YeDepartment of Rheumatology, The Second Affiliated Hospital of Jiaxing University, Jiaxing, People's Republic of China. jxdeyyyq@163.com.

Funding

Zhejiang Provincial Health Bureau Science Foundation nos.2025KY1608
6 · The paper itself

Abstract

Primary Sjögren's syndrome is a complex and heterogeneous disease, often involving multiple organ systems and carrying an increased risk of lymphoma development. In this study, we integrated single-cell RNA sequencing and bulk RNA-seq data to deconvolute the disease heterogeneity using non-negative matrix factorization.This analysis identified four distinct molecular subtypes, which we designated as the Classical Immune Type, Ion Channel Type, Fibrotic Senescent Type, and Immune Desert Type. Through differential expression analysis, we further identified characteristic gene sets for each of these subtypes. The Gene Set Variation Analysis scores of these subtype-specific gene signatures in patient minor salivary gland RNA-seq data may potentially inform patient stratification. We preliminarily characterized the clinical features and local immune microenvironment profiles associated with each subtype. These findings may have implications for personalized therapeutic strategies and potentially inform the selection of patients for future clinical trials.

Indexed as

Salivary GlandsSjogren's SyndromeFemaleGene Expression ProfilingHumansSequence Analysis, RNASingle-Cell Gene Expression AnalysisTranscriptomePrimary Sjögren's Syndrome Senescence Fibrosis Single-cell RNA sequencing Tertiary Lymphoid Structures

Identifiers

PMID42260594
PMCPMC13465307

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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.