ArticleJAMA ophthalmology2017
Gene Expression Profiling and Heterogeneity of Nonspecific Orbital Inflammation Affecting the Lacrimal Gland.
Article in JAMA ophthalmology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 1 of them a synthesis that pooled it.
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Who cites it
22 citing papers in PubMed, 1 synthesis or guideline pooled it, 45 citations in OpenAlex.
- cDC2 and plasmacytoid dendritic cells diminish from tissues of patients with non-Hodgkin orbital lymphoma and idiopathic orbital inflammation.European journal of immunology · 2020Pooled it
- Radiologic imaging shows variable accuracy in diagnosing orbital inflammatory disease and assessing its activity.Scientific reports · 2020Trial
- Biglycan knockdown improves Graves' orbitopathy (GO)-like features via inhibiting NF-kB and ERK signaling.Journal of endocrinological investigation · 2026Article
- Integrated multiple machine learning and Mendelian randomization reveal LTF gene as a prognostic biomarker for nonspecific orbital inflammation.BMC pharmacology & toxicology · 2025Article
- Gluconeogenesis related gene signatures as biomarkers for nonspecific orbital inflammation.Scientific reports · 2025Article
- The miR-320a/PRDX3 Axis Alleviates the Oxidative Stress and Fibrotic Alterations in Fibroblasts in Thyroid Eye Disease.Investigative ophthalmology & visual science · 2025Article
- Machine learning unveils hypoxia-immune gene hub for clinical stratification of thyroid-associated ophthalmopathy.Scientific reports · 2025Article
- Immune Regulation and ECM-Related Pathway Enrichment Reveal ATP2A3 as a Prognostic Biomarker for Nonspecific Orbital Inflammation: An Integrated Machine Learning and Mendelian Randomization Analysis.Mediators of inflammation · 2025Article
- Integrated machine learning and Mendelian randomization reveal PALMD as a prognostic biomarker for nonspecific orbital inflammation.Scientific reports · 2024Article
- Deciphering the role of HLF in idiopathic orbital inflammation: integrative analysis via bioinformatics and machine learning techniques.Scientific reports · 2024Article
- The roles of IRF8 in nonspecific orbital inflammation: an integrated analysis by bioinformatics and machine learning.Journal of ophthalmic inflammation and infection · 2024Article
- Article
- Glutamine metabolism-related genes and immunotherapy in nonspecific orbital inflammation were validated using bioinformatics and machine learning.BMC genomics · 2024Article
- Bioinformatic validation and machine learning-based exploration of purine metabolism-related gene signatures in the context of immunotherapeutic strategies for nonspecific orbital inflammation.Frontiers in immunology · 2024Article
- Elucidating the multifaceted roles of GPR146 in non-specific orbital inflammation: a concerted analytical approach through the prisms of bioinformatics and machine learning.Frontiers in medicine · 2024Article
- Bioinformatic meta-analysis reveals novel differentially expressed genes and pathways in sarcoidosis.Frontiers in medicine · 2024Article
- Longitudinal changes in tear cytokines and antimicrobial proteins in trachomatous disease.PLoS neglected tropical diseases · 2023Article
- Novel Insights into Pathophysiology of Orbital Inflammatory Diseases and Progression to Orbital Lymphoma by Pathway Enrichment Analysis.Life (Basel, Switzerland) · 2022Article
- Evaluation of Orbital Lymphoproliferative and Inflammatory Disorders by Gene Expression Analysis.International journal of molecular sciences · 2022Article
- Identification of Hub Genes Associated with Nonspecific Orbital Inflammation by Weighted Gene Coexpression Network Analysis.Disease markers · 2022Article
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Authors and funding
33 authors at 16 institutions in 6 countries.
Funding
Abstract
Importance: Although a variety of well-characterized diseases, such as sarcoidosis and granulomatosis with polyangiitis, affect the lacrimal gland, many patients with dacryoadenitis are diagnosed as having nonspecific orbital inflammation (NSOI) on the basis of histology and systemic disease evaluation. The ability to further classify the disease in these patients should facilitate selection of effective therapies. Objective: To test the a priori hypothesis that gene expression profiles would complement clinical and histopathologic evaluations in identifying well-characterized diseases and in subdividing NSOI into clinically relevant groups. Design, Setting, and Participants: In this cohort study, gene expression levels in biopsy specimens of inflamed and control lacrimal glands were measured with microarrays. Stained sections of the same biopsy specimens were used for evaluation of histopathology. Tissue samples of patients were obtained from oculoplastic surgeons at 7 international centers representing 4 countries (United States, Saudi Arabia, Canada, and Taiwan). Gene expression analysis was done at Oregon Health & Science University. Participants were 48 patients, including 3 with granulomatosis with polyangiitis, 28 with NSOI, 7 with sarcoidosis, 4 with thyroid eye disease, and 6 healthy controls. The study dates were March 2012 to April 2017. Main Outcomes and Measures: The primary outcome was subdivision of biopsy specimens based on gene expression of a published list of approximately 40 differentially expressed transcripts in blood, lacrimal gland, and orbital adipose tissue from patients with sarcoidosis. Stained sections were evaluated for inflammation (none, mild, moderate, or marked), granulomas, nodules, or fibrosis by 2 independent ocular pathologists masked to the clinical diagnosis. Results: Among 48 patients (mean [SD] age, 41.6 [19.0] years; 32 [67%] female), the mclust algorithm segregated the biopsy specimens into 4 subsets, with the differences illustrated by a heat map and multidimensional scaling plots. Most of the sarcoidosis biopsy specimens were in subset 1, which had the highest granuloma score. Three NSOI biopsy specimens in subset 1 had no apparent granulomas. Thirty-two percent (9 of 28) of the NSOI biopsy specimens could not be distinguished from biopsy specimens of healthy controls in subset 4, while other examples of NSOI tended to group with gene expression resembling granulomatosis with polyangiitis or thyroid eye disease. The 4 subsets could also be partially differentiated by their fibrosis, granulomas, and inflammation pathology scores but not their lymphoid nodule scores. Conclusions and Relevance: Gene expression profiling discloses clear heterogeneity among patients with lacrimal inflammatory disease. Comparison of the expression profiles suggests that a subset of patients with nonspecific dacryoadenitis might have a limited form of sarcoidosis, while other patients with NSOI cannot be distinguished from healthy controls.
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