Sj""""""""gren's Syndrome (SS) is a progressive organ-specific autoimmune disease affecting about 4 million Americans. The disease results in irreversible salivary and lacrimal gland tissue damage and loss of saliva and tear production, leading to significant reduction in the quality of life for these patients. This complex disease is currently poorly understood resulting in no effective early detection technology and the lack of effective therapy. Of further importance is that approximately 5% of SS patients progress to develop malignant lymphoma, a lethal sequelae. This application aims to impact both the fundamental biological understanding of SS pathogenesis and the clinical outcomes of this autoimmune disease, diagnostically, therapeutically and prognostically. The RFA DE-08-001 sparked the coming together of a multi-disciplinary team of scientists in computational and biological sciences excited and committed to achieve these goals. This consortium aims to validate the hypothesis that the pathogenesis of primary SS (pSS) and lymphoma (pSS/MALT) development in salivary glands involve the aberrant activities of key intracellular networks, pathways and molecular targets. A systems approach is in place to identify the key biological pathways and critical molecular determinants whose values will be experimentally tested and validated. This iterative process will lead to the eventual emergence of key molecular targets (key drivers) that can be translated for clinical utilizations for diagnostics, therapeutics and prognostics.
Three specific aims are in place to achieve these basic and translational goals.
Specific Aim 1 is an experimental component to generate new, high quality foundation databases (proteomics and transcriptomics) of human salivary glands with pSS and lymphoma phenotypes.
Specific Aim 2 is a computational/model building component to integrate the transcriptomic and proteomic databases with a newly developed database of existing knowledge (Sj""""""""gren's Syndrome Knowledge Base, SSKB) and perform meta-analysis of networks, and identification of key molecular targets (key drivers) using the weigh-gene co-expression network analysis (WGCNA) for both pSS pathogenesis and malignant lymphoma conversion.
Specific Aim 3 is the experimental specific aim to validate the role of the identified molecular targets in the biological network. In silico validations, in vivo rodent models and in vitro cell line approaches will be used to achieve a comprehensive iteration and validation of the disease model. The SS disease model and supporting databases will be made publicly available. A related outcome of this project is the proof of principle of a systems approach to salivary gland pathogenesis, the ability to identify critical molecular targets, pathways and networks. The resources (databases) and computational/modeling approaches will be applicable to other salivary gland diseases and biology. Project Narrative: A novel and exciting research to discover key molecular targets responsible for Sj""""""""gren's syndrome development as well as malignant lymphoma. These key molecular targets will allow development of better diagnostics, therapeutics and prognostics for this major autoimmune disease.

Agency
National Institute of Health (NIH)
Institute
National Institute of Dental & Craniofacial Research (NIDCR)
Type
Research Project (R01)
Project #
5R01DE019255-02
Application #
7817012
Study Section
Special Emphasis Panel (ZDE1-RW (17))
Program Officer
Burgoon, Penny W
Project Start
2009-05-01
Project End
2012-04-30
Budget Start
2010-05-01
Budget End
2012-04-30
Support Year
2
Fiscal Year
2010
Total Cost
$879,493
Indirect Cost
Name
University of California Los Angeles
Department
Dentistry
Type
Schools of Dentistry
DUNS #
092530369
City
Los Angeles
State
CA
Country
United States
Zip Code
90095
Langfelder, Peter; Horvath, Steve (2012) Fast R Functions for Robust Correlations and Hierarchical Clustering. J Stat Softw 46:
Gorr, Sven-Ulrik; Wennblom, Trevor J; Horvath, Steve et al. (2012) Text-mining applied to autoimmune disease research: the Sjögren's syndrome knowledge base. BMC Musculoskelet Disord 13:119
Vissink, Arjan; Bootsma, Hendrika; Kroese, Frans G M et al. (2012) How to assess treatment efficacy in Sjogren's syndrome? Curr Opin Rheumatol 24:281-9
Cai, Chaochao; Langfelder, Peter; Fuller, Tova F et al. (2010) Is human blood a good surrogate for brain tissue in transcriptional studies? BMC Genomics 11:589
Hu, Shen; Gao, Kai; Pollard, Rodney et al. (2010) Preclinical validation of salivary biomarkers for primary Sjögren's syndrome. Arthritis Care Res (Hoboken) 62:1633-8