Integrative multi-omics analysis reveals cellular and molecular insights into primary Sjogren's syndrome.
Ontology highlight
ABSTRACT: Objective
This study aims to comprehensively analyze genomic, transcriptomic, proteomic, and single-cell sequencing data to unravel the molecular basis of primary Sjögren's syndrome (pSS) and explore potential therapeutic targets.Methods
Mendelian randomization and single-cell RNA sequencing were employed to analyze pSS data. Differentially expressed genes specific to different blood cell types were identified. Integration of multiomics data facilitated the exploration of genetic regulatory relationships.Results
The analysis revealed distinct cell clusters representing various immune cell subsets. Several genes, including cathepsin S (CTSS) and glutathione S-transferase omega 1 (GSTO1), were identified as potential biomarkers and therapeutic targets for pSS. Diagnostic utility analysis demonstrated the discriminatory power of CTSS and GSTO1 in distinguishing pSS patients from healthy controls.Conclusion
The findings highlight the importance of integrating multiomics data for understanding pSS pathogenesis. CTSS and GSTO1 show promise as diagnostic biomarkers and potential therapeutic targets for pSS. Further investigations are warranted to elucidate the underlying mechanisms and develop targeted therapies for this complex autoimmune disease.
SUBMITTER: Tan Y
PROVIDER: S-EPMC11255657 | biostudies-literature | 2024 Jul
REPOSITORIES: biostudies-literature
Publications
Integrative multi-omics analysis reveals cellular and molecular insights into primary Sjögren's syndrome.
Tan Yao Y Yin Jiayang J Wu Zhenkai Z Xiong Wei W
Heliyon 20240624 13
<h4>Objective</h4>This study aims to comprehensively analyze genomic, transcriptomic, proteomic, and single-cell sequencing data to unravel the molecular basis of primary Sjögren's syndrome (pSS) and explore potential therapeutic targets.<h4>Methods</h4>Mendelian randomization and single-cell RNA sequencing were employed to analyze pSS data. Differentially expressed genes specific to different blood cell types were identified. Integration of multiomics data facilitated the exploration of genetic ...[more]
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