4.5 Article

A Longitudinal Biomarker for the Extent of Skin Disease in Patients With Diffuse Cutaneous Systemic Sclerosis

期刊

ARTHRITIS & RHEUMATOLOGY
卷 67, 期 11, 页码 3004-3015

出版社

WILEY
DOI: 10.1002/art.39287

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资金

  1. NIH [UL1-TR000157, 5P30-AR-061271, 1P50-AR-060780, 2R01-AR-051089]
  2. Boston University Medical Center Microarray Resource Core Facility
  3. Scleroderma Research Foundation
  4. Dr. Ralph and Marian Falk Medical Research Trust
  5. Clinician Scientist Development Award through the Kellen Foundation at the Hospital for Special Surgery
  6. Novartis
  7. Rudolph Rupert Scleroderma Program at the Hospital for Special Surgery
  8. Pfizer
  9. Boehringer Ingelheim
  10. Alexion
  11. Roche/Genentech
  12. Human Genome Sciences/GlaxoSmithKline
  13. Actelion
  14. United Therapeutics
  15. Chemocentryx
  16. Bristol-Myers Squibb
  17. Cytori Therapeutics
  18. Gilead
  19. Celgene
  20. Reata
  21. Bayer
  22. Genentech
  23. InterMune
  24. Genzyme/Sanofi
  25. Shire
  26. Regeneron
  27. Biogen
  28. Inception
  29. Precision Dermatology
  30. PRISM
  31. UCB
  32. Lycera
  33. Amira
  34. Celdara
  35. Celltex
  36. Dart Therapeutics
  37. Idera
  38. Medimmune
  39. Promedior
  40. Zwitter Pharmaceuticals
  41. EMD Serono
  42. Akros
  43. Extera
  44. Reneo
  45. Scholar Rock
  46. Human Genome Sciences

向作者/读者索取更多资源

Objective. To define a pharmacodynamic biomarker based on gene expression in skin that would provide a biologic measure of the extent of disease in patients with diffuse cutaneous systemic sclerosis (dcSSc) and could be used to monitor skin disease longitudinally. Methods. Skin biopsy specimens obtained from a cohort of patients with dcSSc (including longitudinal specimens) were analyzed by microarray. Expression of genes correlating with the modified Rodnan skin thickness score (MRSS) were examined for change over time using a NanoString platform, and a generalized estimating equation (GEE) was used to define and validate longitudinally measured pharmacodynamic biomarkers composed of multiple genes. Results. Microarray analysis of genes parsed to include only those correlating with the MRSS revealed prominent clusters of profibrotic/transforming growth factor beta-regulated, interferon-regulated/proteasome, macrophage, and vascular marker genes. Using genes changing longitudinally with the MRSS, we defined 2 multigene pharmacodynamic biomarkers. The first was defined mathematically by applying a GEE to longitudinal samples. This modeling method selected cross-sectional THBS1 and longitudinal THBS1 and MS4A4A. The second model was based on a weighted selection of genes, including additional genes that changed statistically significantly over time: CTGF, CD163, CCL2, and WIF1. In an independent validation data set, biomarker levels calculated using both models correlated highly with the MRSS. Conclusion. Skin gene expression can be used effectively to monitor changes in SSc skin disease over time. We implemented 2 relatively simple models on a NanoString platform permitting highly reproducible assays that can be applied directly to samples from patients or collected as part of clinical trials.

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