ACR Meeting Abstracts

ACR Meeting Abstracts

Abstract Number: 2322

Quantitative Proteomics Comparison of Children with Inactive and Active Uveitis

Sheila Angeles-Han1, Duc Duong2, Steven Yeh3, Purnima Patel4, Virginia Miraldi Utz5, Kirsten Jenkins6, Danielle Lowe7, Sampath Prahalad8 and Gary Holland9, 1Pediatrics, Cincinnati Children's Hospital Medical Center and University of Cincinnati, Cincinnati, OH, 2Emory University, Atlanta, GA, 3Ophthalmology, Emory University School of Medicine, Atlanta, GA, 4Emory University School of Medicine, Atlanta, GA, 5Pediatric Ophthalmology, Cincinnati Children's Hospital Medical Center and University of Cincinnati, Cincinnati, OH, 6Children's Healthcare of Atlanta, Atlanta, GA, 7Pediatrics, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, 8Emory University School of Medicine and Children's Healthcare of Atlanta, Atlanta, GA, 9Jules Stein Eye Institute, Jules Stein Eye Institute, University of California, Los Angeles, Los Angeles, CA

Meeting: 2017 ACR/ARHP Annual Meeting

Date of first publication: September 18, 2017

Keywords: , ,

Session Information

Date: Tuesday, November 7, 2017

Title: Pediatric Rheumatology – Pathogenesis and Genetics Poster

Session Type: ACR Poster Session C

Session Time: 9:00AM-11:00AM

Background/Purpose: Children with chronic non-infectious uveitis are at high risk for sight-threatening complications and vision loss. No biomarker predicts uveitis development or treatment response. Aqueous humor has been studied but is not feasible to collect in children with JIA without eye disease.  Tear proteomics is increasingly used for biomarker discovery in ocular and non-ocular diseases.  Advantages of tear collection are easy accessibility, non-invasiveness and tolerance.  We examined the tear profile of children with uveitis to identify potential markers for activity vs dormancy.

Methods: Tear samples were collected from children with chronic non-infectious uveitis (Table 1). A Schirmer strip was placed 6mm from the lateral canthus of the anesthetized eye for 2-5 minutes.  Then, 50 ug of proteins were extracted for Tandem Mass Tag (TMT) labeling.  The TMT pool was loaded onto an offline electrostatic repulsion interaction chromatography (ERLIC) fractionation HPLC system and 20 fractions were collected. LC-MS/MS analysis was done on all 20 fractions. Proteome Discoverer 2.1 (ThermoFisher Scientific, San Jose, CA) was used to search all the MS/MS spectra against a Uniprot human reference protein database (retrieved April 20, 2015; 90,411 target sequences) and TMT reporter quantitation was performed.

We compared children with 1) active vs inactive uveitis of all locations and 2) active vs. inactive anterior uveitis only (JIA-associated and idiopathic). Active uveitis was defined as anterior chamber cell grade of 0.5+ (1-5 cells/hpf) and greater. Inactive uveitis was grade 0.

Results: There were 19 children (29 eyes) examined.  We quantified 1426 unique protein groups and found 34 and 39 statistically significant proteins, respectively for all uveitis and anterior uveitis only comparisons.  Gene ontology showed pathways related to extracellular exosomes (adjusted p=10.6e-13 for all uveitis locations and p=1.23 e-14 for anterior uveitis only).  In children with anterior uveitis only, there were pathways related to intracellular RNP complex (p=7.47 e-04), poly (A) RNA binding (p=0.002), and cadherin binding involved in cell-cell adhesion (p =0.012).  These results suggest the homeostatic balance of translational and signaling machinery is disrupted during disease activity. 

Conclusion: We identified potential biomarkers that may differentiate active ocular inflammation in children with uveitis.  This may improve our understanding of the underlying mechanisms associated with ocular inflammation in children with JIA.  Discovery of biomarkers in combination with clinical outcome measures may lead to better prediction of uveitis development and response to therapy.

Table 1. Demographics and Clinical Characteristics of Children with Chronic Non-infectious Uveitis, N (%)

 

ALL

N = 19 children

29 eyes

Active

N = 12 children

10 eyes

Inactive

N = 7 children

19 eyes

Female

16 (84)

10 (83)

6 (86)

Race

 

 

 

     Caucasian

13 (68)

6 (50)

7 (100)

     African American

6 (32)

6 (50)

0

Non-Hispanic

17 (89)

10 (83)

7 (100)

Age at uveitis diagnosis

7.6 years

8.5 years

5.8 years

Diagnosis

 

 

 

     JIA-associated uveitis (oligo or poly RF  negative)

9 (5)

5 (42)

4 (57)

     Idiopathic chronic anterior uveitis

5 (26)

4 (33)

1 (14)

     Idiopathic uveitis, not anterior in location

3 (16)

3 (25)

0

     HLA-B27 associated

2 (10)

0

2 (28)

Uveitis location

 

 

 

     Anterior

15 (79)

9 (75)

6 (86)

     Anterior/

     Intermediate

1 (5)

0

1 (14)

     Intermediate

2 (10)

2 (17)

0

     Posterior

1 (5)

1 (8)

0

Bilateral

16 (84)

10 (83)

6 (85)

Medication use at time of collection

 

 

 

     Topical steroids (prednisolone acetate or difluprednate)

12 (63)

10 (83)

2 (28)

     Timolol

3 (16)

3 (25)

0

     Methotrexate

12 (63)

10 (83)

2 (28)

     Mycophenolate

1 (5)

 

1 (14)

     Lefunomide

2 (10)

1 (8)

1 (14)

     Infliximab

6 (32)

3 (25)

3 (43)

     Adalimumab

3 (16)

2 (17)

1 (14)

     Tocilizumab

2 (10)

1 (8)

1 (14)

 

Disclosure: S. Angeles-Han, None; D. Duong, None; S. Yeh, None; P. Patel, None; V. Miraldi Utz, None; K. Jenkins, None; D. Lowe, None; S. Prahalad, None; G. Holland, None.

To cite this abstract in AMA style:

Angeles-Han S, Duong D, Yeh S, Patel P, Miraldi Utz V, Jenkins K, Lowe D, Prahalad S, Holland G. Quantitative Proteomics Comparison of Children with Inactive and Active Uveitis [abstract]. Arthritis Rheumatol. 2017; 69 (suppl 10). https://acrabstracts.org/abstract/quantitative-proteomics-comparison-of-children-with-inactive-and-active-uveitis/. Accessed .

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