Evidence map›Paper›PMID 41294018›Full record

ArticleJournal of cellular and molecular medicine2025

Genetic Crosstalk Between Type 1 Diabetes and Sjögren's Syndrome: A Systematic Exploration of Risk Genes and Common Pathways.

Aamir Fahira, Kai Zhuang, Xuemin Jian, Syed Mansoor Jan, Yong Liu, Jianbo Sun, Yongyong Shi, Zunnan Huang

Abstract read
In one paragraph

Article in Journal of cellular and molecular medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

8 authors.

Aamir FahiraDongguan Key Laboratory of Computer-Aided Drug Design, The First Dongguan Affiliated Hospital, Guangdong Medical University, Dongguan, Guangdong, China.
Kai ZhuangDongguan Key Laboratory of Computer-Aided Drug Design, The First Dongguan Affiliated Hospital, Guangdong Medical University, Dongguan, Guangdong, China.
Xuemin JianNHC Key Laboratory of Nuclear Technology Medical Transformation, Mianyang Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Mianyang, Sichuan, China.
Syed Mansoor JanDepartment of Bioinformatics and Biostatistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, China.
Yong LiuDongguan Key Laboratory of Computer-Aided Drug Design, The First Dongguan Affiliated Hospital, Guangdong Medical University, Dongguan, Guangdong, China.
Jianbo SunDongguan Key Laboratory of Computer-Aided Drug Design, The First Dongguan Affiliated Hospital, Guangdong Medical University, Dongguan, Guangdong, China.
Yongyong ShiBio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), Shanghai Jiao Tong University, Shanghai, China.
Zunnan HuangDongguan Key Laboratory of Computer-Aided Drug Design, The First Dongguan Affiliated Hospital, Guangdong Medical University, Dongguan, Guangdong, China.ORCID 0000-0002-5821-703X

Funding

Innovation Team Project of Guangdong Province Regular Higher Education Institutions 2025KCXTD018Special Education Development Funding of Guangdong Medical University 4SG24186G
6 · The paper itself

Abstract

Sjögren's Syndrome (SS) and Type 1 Diabetes (T1D) are autoimmune disorders that can co-occur in patients, leading to complex clinical presentations. Despite observational evidence of their co-occurrence, the underlying genetic mechanisms remain poorly understood. To investigate the shared genetic factors and pathways between SS and T1D, we conducted a comprehensive analysis using multiomic approaches. Conditional and conjunctional false discovery rate analyses were performed to identify genetic polygenicity and overlap between the two diseases. Functional annotation and pathway analysis identified SNPs with regulatory potential. Furthermore, Mendelian Randomization (MR) analyses were employed to investigate causal associations between gene expression and disease risk. Single-cell differential gene expression analysis was also employed to validate the associations of risk genes with T1D and SS. Our analysis identified 36 shared loci, revealing common genetic enrichment between SS and T1D. Functional annotation and pathway analysis revealed 52 credible genes involved in cysteine-related processes, apoptotic signalling and immune responses. MR analyses revealed that AC007283.5 was positively linked with both SS and T1D, while PLEKHM1 and CRHR1-T1 were negatively associated. Additionally, CERS2 was positively associated with SS, DEF6 was positively associated with T1D, and KANSL1-AS1 was negatively associated with T1D, indicating the presence of complex regulatory mechanisms. Moreover, Single-cell differential gene expression analysis confirmed the dysregulation of risk genes in SS and T1D. This study identified shared genetic factors and pathways underlying SS and T1D, highlighting cysteine-related processes and apoptotic signalling. The findings underscore the complex interplay of autoimmunity and the need for targeted treatments addressing their common mechanisms.

Indexed as

Diabetes Mellitus, Type 1Genetic Predisposition to DiseaseSjogren's SyndromeGene Expression ProfilingGene Expression RegulationGene Regulatory NetworksGenome-Wide Association StudyHumansMendelian Randomization AnalysisPolymorphism, Single NucleotideRisk FactorsSignal Transductioncausal risk genesgenetic pleiotropyMendelian randomizationpathway analysisSjögren's syndrometype 1 diabetes

Identifiers

PMID41294018
PMCPMC12648307

What Socratic holds

Textmetadata
LicenceCC BY
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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 Socratic graph.