# Transcriptomic changes in the lacrimal glands of a Sjogren’s disease animal model highlight key molecular mediators and altered biological functions underpinning glandular inflammation and hypofunction

**Authors:** Danny Toribio, Junji Morokuma, Albert Tai, Driss Zoukhri

PMC · DOI: 10.3389/fopht.2026.1697924 · Frontiers in Ophthalmology · 2026-03-13

## TL;DR

This study identifies key genes and biological processes involved in lacrimal gland inflammation and dysfunction in a mouse model of Sjogren’s disease.

## Contribution

The study reveals novel molecular mediators and altered functions in lacrimal glands during Sjogren’s disease progression.

## Key findings

- Differentially expressed genes increased with disease progression, linked to immune responses and inflammation.
- Cytokines, transcription factors, and toll-like receptors were key drivers of gene expression changes.
- Lymphocyte recruitment and lipid metabolism were significantly impacted in the disease model.

## Abstract

Sjogren’s disease (SjD) is a chronic autoimmune condition that targets the lacrimal glands (LGs), resulting in aqueous-deficient dry eye disease (DED). Insufficient or low-grade tear secretion onto the ocular surface affects the normal physiology of the cornea and conjunctiva and can result in ocular surface damage. Herein, we evaluated the transcriptomic profiles of diseased versus healthy LGs to investigate the underlying molecular mechanisms underscoring LG autoimmune inflammation and secretory hypofunction.

LGs were removed from male NOR/LtJ mice (SjD mouse model) and sex- and age-matched BALB/c controls at 3 weeks (pre-disease), 8 weeks (early disease onset), and 16 weeks (intermediately advanced disease stage). LGs were processed for either RNA extraction or histopathological staining. Bulk RNA sequencing was conducted for each LG sample followed by downstream data processing for differential expression analysis using the DESeq2 R package. Biological interpretation of the differential gene expression datasets was achieved using the QIAGEN Ingenuity Pathway Analysis (IPA) software. IPA was used to compare the differential gene expression results obtained in our analyses to those of previously published, publicly available datasets from other SjD-related transcriptomic-based studies.

The number of differentially expressed genes between NOR and BALB/c mice increased in correlation with the development and progression of dacryoadenitis. The most significantly upregulated pathways were primarily related to immune responses, emphasizing the activation of cellular and cytokine-mediated inflammatory responses. Several cytokines, transcription factors, and toll-like receptors were significantly predicted to drive most of the differential gene expression observed across our datasets. Biological processes involving the migration, recruitment, and activation of lymphocytes, but also lipid metabolism, were most significantly impacted in our disease model. Many of the identified dysregulated genes and affected biological functions were similarly regulated in the differential expression datasets of other transcriptomic-based studies of SjD patients and mouse models.

Chronic inflammation induces significant alterations to the LG transcriptome, promoting the recruitment of immune cells into the LG and the overactivation of inflammatory responses that severely impede normal secretory function. Future studies targeting some of the discovered key dysregulated molecules/pathways could open up potential therapeutic avenues for the treatment of chronic LG inflammation and secretory hypofunction.

## Full-text entities

- **Diseases:** secretory hypofunction (MESH:D008579), autoimmune condition (MESH:D001327), ocular surface damage (MESH:D010534), dacryoadenitis (MESH:D003607), Chronic inflammation (MESH:D007249), DED (MESH:D015352), SjD (MESH:D012859)
- **Chemicals:** lipid (MESH:D008055)
- **Species:** Mus musculus (house mouse, species) [taxon 10090], Homo sapiens (human, species) [taxon 9606]

## Full text

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## Figures

9 figures with captions in the complete paper: https://tomesphere.com/paper/PMC13021454/full.md

## References

63 references — full list in the complete paper: https://tomesphere.com/paper/PMC13021454/full.md

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Source: https://tomesphere.com/paper/PMC13021454