Predicting Disease Progression in Scleroderma with Skin and Blood Biomarkers

Abstract

Scleroderma (Systemic Sclerosis, SSc) is a chronic, incurable autoimmune disease associated with high morbidity and mortality primarily due to SSc-lung disease (1, 2). There is a large variability in individual patients courses and current predictors of disease progression are inadequate. The overall objective of the proposed research is to develop reliable predictors for clinical outcomes, particularly interstitial lung disease, in scleroderma, utilizing the biospecimens and longitudinal clinical data in the GENISOS cohort to perform an analysis combining data from multiple areas to develop robust prediction models for ILD progression. The model will include genotypic data, gene expression profiling and cytokine/analyte levels, in addition to clinical parameters of pulmonary function tests and chest CAT (computer assisted tomography) scans. In the first year we have focused on patient recruitment, clinical characterization, specimen collection (DNA, RNA, skin biopsies, serum, plasma, monocytes). We have begun the analysis of serum analytes and gene expression. We have prepared 3 abstracts accepted for presentation at the annual American College of Rheumatology meeting Nov 16-19, 2014 in Boston.

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Document Details

Document Type
Technical Report
Publication Date
Oct 01, 2014
Accession Number
ADA613314

Entities

People

  • Maureen D Mayes

Organizations

  • University of Texas Health Science Center at Houston

Tags

DTIC Thesaurus Topics

  • Abstracts
  • Biomedical Research
  • Biospecimens
  • Blood
  • Computers
  • Cytokines
  • Data Storage Systems
  • Databases
  • Department Of Defense
  • Disease Attributes
  • Diseases And Disorders
  • Gene Expression
  • Institutional Review Board
  • Lung Diseases
  • Monocytes
  • Rheumatology
  • Sclerosis

Fields of Study

  • Medicine

Readers

  • Immunology and Pathology
  • Oncology and Biomarker-Based Cancer Detection.
  • Technical Research and Report Writing.