June 2015
Volume 56, Issue 7
Free
ARVO Annual Meeting Abstract  |   June 2015
Identification of a gene expression profile specific to non infectious uveitis using high throughput microarray data and a novel pipeline of in-silico methods
Author Affiliations & Notes
  • Srilakshmi Sharma
    Ophthalmology, Oxford Eye Hospital, Oxford, United Kingdom
    Moorfields Eye Hospital, London, United Kingdom
  • Sarah Wheelan
    Johns Hopkins University, Baltimore, MD
  • Luigi Marchionni
    Johns Hopkins University, Baltimore, MD
  • Christina A. Harrington
    Oregon Health & Sciences University, Portland, OR
  • Dongseok Choi
    Oregon Health & Sciences University, Portland, OR
    Casey Eye Institute, Portland, OR
  • Stephen R Planck
    Casey Eye Institute, Portland, OR
    Legacy Devers Eye Institute, Legacy Devers Eye Institute, OR
  • James T Rosenbaum
    Casey Eye Institute, Portland, OR
    Legacy Devers Eye Institute, Legacy Devers Eye Institute, OR
  • Footnotes
    Commercial Relationships Srilakshmi Sharma, None; Sarah Wheelan, None; Luigi Marchionni, None; Christina Harrington, None; Dongseok Choi, None; Stephen Planck, None; James Rosenbaum, None
  • Footnotes
    Support None
Investigative Ophthalmology & Visual Science June 2015, Vol.56, 1719. doi:
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      Srilakshmi Sharma, Sarah Wheelan, Luigi Marchionni, Christina A. Harrington, Dongseok Choi, Stephen R Planck, James T Rosenbaum; Identification of a gene expression profile specific to non infectious uveitis using high throughput microarray data and a novel pipeline of in-silico methods. Invest. Ophthalmol. Vis. Sci. 2015;56(7 ):1719.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract
 
Purpose
 

Microarray technology presents opportunities to study etiological or genetic commonalities within ocular manifestations of heterogenous diseases. Our aims are to characterise gene expression in active uveitis of distinct etiologies and as single heterotype and to develop a novel in-silico pipeline of orthogonal analyses translatable to other diseases.

 
Methods
 

Gene expression was assayed in the OHSU Gene Microarray Shared Resource using Affymetrix Hu U133 Plus 2.0 Microarray chips on peripheral whole blood samples from active uveitis compared with inactive uveitis for separate etiologies and as a combined class of heterogeneous aetiologies. We studied 35 subjects with active noninfectious (NIU) uveitis, 28 inactive NIU in Ankylosing Spondylitis (AS), Sarcoidosis, Idiopathic Uveitis, Behcets Disease and 25 healthy controls. We developed an in-silico pipeline including frozen Robust Multi-array Average normalisation, Linear Model for Microarray in 'R', differential gene expression identification. False discovery rate <5% defined significance. Methods for downstream analysis included Gene Set enrichment Analysis , Ingenuity Pathway Analysis modules, Panther and text-mining literature search.

 
Results
 

TOLL, RIG-1 and NOD, IL21 and Integrin pathways were enriched in subjects with active uveitis. Functional distinctions between individual uveitis aetiologies are present: IL4 pathway is downregulated in Idiopathic uveitis; IL12, p53, IL17/23 pathways are upregulated and wnt-catenin, integrin pathways downregulated. The IL2 pathway is downregulated in AS Uveitis. We identified 13 (3.5 %) DEGs concordant between active uveitis disease classes, e.g., secretory leukocyte peptidase inhibitor & peroxisomal proliferator-activated receptor A (PPAR) interacting complex 285.

 
Conclusions
 

Combining multiple analysis modalities enables discovery of genes and pathways shared among heterogeneous diseases & potentially specific to a single clinical features in these diseases. We were able to identify both a common mRNA profile associated with active uveitis in various diseases in peripheral blood and show that each uveitis phenotype is associated with functional relationships distinct from systemic disease and other uveitides.  

 
Heatmap following Single Sample Gene Set Enrichment Analysis showing distinctions in pathways between Uveitis and Inactive Uveitis
 
Heatmap following Single Sample Gene Set Enrichment Analysis showing distinctions in pathways between Uveitis and Inactive Uveitis

 
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