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Home » Meeting Abstracts » ACR Convergence 2024

Abstract Number: 1781

Tear Proteomics as a Classifier of Disease Type and Activity Status in Pediatric Uveitis

Melissa Lerman1, Devlin Eckardt1, Stefanie Davidson2 and Edward Behrens3, 1Children's Hospital of Philadelphia, Philadelphia, PA, 2University of Pennsylvania/CHOP, Philadelphia, PA, 3Children's Hospital of Philadelphia, West Chester, PA

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Meeting: ACR Convergence 2024

Keywords: Eye Disorders, Pediatric rheumatology, proteomics

Session Information

Date: Monday, November 18, 2024

Title: Pediatric Rheumatology – Basic Science Poster

Session Type: Poster Session C

Session Time: 10:30AM-12:30PM

Background/Purpose: Measurement of proteins from tear fluid represents a non-invasive means to assess the local biology of ocular autoimmune disease such as uveitis. Pediatric uveitis can result from an array of underlying conditions or may be idiopathic. In this study, we leveraged a new proteomic technology, Proximity Extension Assay, to investigate the ocular biology of a diverse cohort of pediatric uveitis patients for classifiers of both disease type and uveitis activity. 

Methods: Tear fluid was collected from 50 eyes of 25 patients with pediatric uveitis (active or inactive). Eligible patients were identified by record review from a multidisciplinary uveitis clinic. All patients had a history of anterior uveitis; some also had intermediate or posterior uveitis. Disease activity was based upon pediatric uveitis specialist’s assessment, including: presence of cells; retinitis or use of corticosteroids (CS). Active uveitis was defined as (1) >0.5+ anterior chamber cell and/or ≥1+vitreous cell/haze and/or retinitis or (2) quiet uveitis, along with the use of ≥2 drops/day topical or systemic CS. Tear proteins were eluted from Schirmer’s strips in a standard volume and analyzed using the Olink Explore® platform for 3072 proteins. Only proteins which passed quality control measures were included for analysis. R 4.3.3 was used to perform statistical analysis and data visualizations. 

Results: Tears were obtained from patients with JIA-associated uveitis (JIA-U, n=10), Tubulointerstitial nephritis (TINU, n=4), and idiopathic-uveitis (IU, n=10).  All had history of anterior uveitis, 2 had Anterior-intermediate uveitis, and 4 pan-uveitis (2 IU, 1 TINU). Eyes clustered in a principal component analysis predominantly by underlying disease (Figure 1). 111 differentially expressed proteins (DEPs) distinguish JIA eyes from TINU and Idiopathic eyes, with 7 unique to JIA as compared to the other diagnoses (Figure 2). Within JIA, unsupervised hierarchical clustering reveals a set of 44 DEPs that robustly classify disease activity (Figure 3). Amongst gene ontology pathways significantly enriched in the DEPs of active eyes, bone morphogenic protein (BMP) signaling represented the highest fold enrichment. 

Conclusion: Differential protein expression in easily accessible tear fluid reflects the biology of both underlying disease type and activity state in pediatric uveitis. Because BMP is a member of the anti-inflammatory TGF-b signaling family, future analysis will focus on TGF-b biology as a regulator of inflammatory activity in the eye. Assays of specific protein biomarkers in tear fluid have the potential to become useful diagnostic and prognostic biomarkers in pediatric uveitis.  

Supporting image 1

Figure 1. Principal component analysis (PCA) of tear protein dataset. PCA reveals that approximate 46% of the variance in tear protein samples can be captured in two principal components PC1 and PC2. Samples in the 2 dimensional PC1 x PC2 space tend to cluster by diagnosis, suggesting that this variance reflects the underlying diagnosis of uveitis in these patients and that protein measurement from tears can classify diagnosis.

Supporting image 2

Figure 2. Upregulated tear proteins in patients with a Juvenile Idiopathic Arthritis (JIA) diagnosis. Venn diagram showing the number of proteins upregulated in the tears from patients with JIA compared to Tubulointerstitial Nephritis with Uveitis (TINU) or Idiopathic uveitis diagnoses. A core set of 7 proteins is upregulated in JIA tears compared to both of these diagnoses.

Supporting image 3

Figure 3. Differentially expressed proteins (DEPs) in tears from JIA patients classify patients with active disease. 44 DEPs are able to correctly classify 7/8 eyes as active using unsupervised hierarchical clustering. Heat map of protein expression and protein names shown below.


Disclosures: M. Lerman: None; D. Eckardt: None; S. Davidson: None; E. Behrens: Ab2Bio, 5, Pharming, 2, Sobi, 2.

To cite this abstract in AMA style:

Lerman M, Eckardt D, Davidson S, Behrens E. Tear Proteomics as a Classifier of Disease Type and Activity Status in Pediatric Uveitis [abstract]. Arthritis Rheumatol. 2024; 76 (suppl 9). https://acrabstracts.org/abstract/tear-proteomics-as-a-classifier-of-disease-type-and-activity-status-in-pediatric-uveitis/. Accessed .

ACR Meeting Abstracts - https://acrabstracts.org/abstract/tear-proteomics-as-a-classifier-of-disease-type-and-activity-status-in-pediatric-uveitis/

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