Session Information
Date: Monday, October 22, 2018
Title: Systemic Sclerosis and Related Disorders – Basic Science Poster II
Session Type: ACR Poster Session B
Session Time: 9:00AM-11:00AM
Background/Purpose: Proteomic studies with an extensive panel of measured proteins are still scarce in systemic sclerosis (SSc). The Scleroderma: Cyclophosphamide or Transplantation (SCOT) trial showed improved clinical outcomes in participants randomized to myeloablation followed by autologous hematopoietic stem cell transplantation compared to monthly cyclophosphamide (1). In the present study, we performed a proteomic analysis of baseline serum samples collected in the SCOT trial to investigate clinical correlates of serum protein dysregulation at baseline in early diffuse cutaneous SSc (dcSSc).
Methods: A panel of 232 baseline serum proteins in 66 SCOT participants (mean disease duration=2.2 years) compared to 66 age and gender matched controls was analyzed by RBM Human Discovery Multi-Analyte Profiling multiplexed assays. Proteins with levels below the lower limit of detection in more than 50% of SCOT participants, were excluded. Proteins were considered differentially expressed with false discovery rate(FDR) of <5%.
Results: Ninety proteins were differentially expressed in dcSSc versus controls (FDR<0.05). Sixty-five proteins were upregulated, of which 42% (27 molecules) were Type I IFN inducible accordingly to the Interferome database. The ten most up- and down-regulated proteins are presented in Table 1. Serum protein correlates of modified Rodnan Skin Score (mRSS) are shown in Table 2. Carcinoma Antigen 15.3 (CA 15.3) and Epithelial Derived Neutrophil Activating Protein78 (CXCL5) were inversely correlated with forced vital capacity (FVC) (r=-0.33, p<0.006; r=-0.34, p<0.06 respectively) and positively correlated with HRCT fibrosis score (r=0.28, p<0.023; r=0.28, p<0.025) showing an association with lung fibrosis. The Ingenuity Pathway Analysis (IPA) revealed hepatic fibrosis, granulocyte adhesion and diapedesis and agranulocyte adhesion and diapedesis as the top three over-represented pathways, indicating that the serum protein profile of SSc reflects fibrotic as well as immunological dysregulations in SSc.
Conclusion: SSc has a distinct serum protein profile including a prominent upregulation of IFN inducible proteins. The IPA pathway analysis showed top over-represented pathways in SSc serum proteomic analysis parallels those found to be dysregulated in SSc skin global gene expression studies. (2). Finally, we identified several serum proteins that correlate with the extent of skin and lung fibrosis in SSc.
(1) Sullivan KM, et al. N Engl J Med. 2018 Jan 4;378(1):35-47
(2) Assassi S, et al. Arthritis Rheum. 2015 Nov;67(11):3016-26
|
||||||
|
|
|
|
|
|
|
Growth Hormone |
GH1* |
3.69 |
<0.001 |
<0.001 |
Up-regulated |
|
Ferritin |
FTH1 |
3.04 |
<0.001 |
<0.001 |
Up-regulated |
|
C-Reactive Protein |
CRP |
2.98 |
<0.001 |
<0.001 |
Up-regulated |
|
Chromogranin-A |
CHGA |
2.77 |
<0.001 |
<0.001 |
Up-regulated |
|
Macrophage inflammatory protein 3 beta |
CCL19* |
2.48 |
<0.001 |
<0.001 |
Up-regulated |
|
Monocyte Chemotactic Protein 1 |
CCL2* |
2.48 |
<0.001 |
<0.001 |
Up-regulated |
|
Myoglobin |
MB |
2.38 |
<0.001 |
<0.001 |
Up-regulated |
|
Monokine Induced by Gamma Interferon |
CXCL9* |
2.30 |
<0.001 |
<0.001 |
Up-regulated |
|
B Lymphocyte Chemoattractant |
CXCL13 |
2.19 |
<0.001 |
<0.001 |
Up-regulated |
|
Prolactin |
PRL |
2.08 |
<0.001 |
<0.001 |
Up-regulated |
|
Lactoylglutathione lyase |
GLO1 |
0.49 |
<0.001 |
<0.001 |
Down-regulated |
|
Neuron-Specific Enolase |
ENO2 |
0.56 |
0.002 |
0.007 |
Down-regulated |
|
Vitamin K-Dependent Protein S |
PROS1 |
0.56 |
0.005 |
0.013 |
Down-regulated |
|
Superoxide Dismutase 1 |
SOD1 |
0.65 |
<0.001 |
<0.001 |
Down-regulated |
|
Protein S100-A6 |
S100A6 |
0.69 |
0.002 |
0.006 |
Down-regulated |
|
Macrophage Migration Inhibitory Factor |
MIF |
0.71 |
0.023 |
0.046 |
Down-regulated |
|
Adiponectin |
ADIPOQ |
0.72 |
<0.001 |
<0.001 |
Down-regulated |
|
Kallikrein-7 |
KLK7 |
0.73 |
<0.001 |
<0.001 |
Down-regulated |
|
Insulin like Growth Factor Binding Protein 6 |
IGFBP6 |
0.73 |
<0.001 |
<0.001 |
Down-regulated |
|
Tetranectin |
CLEC3B |
0.75 |
<0.001 |
<0.001 |
Down-regulated |
|
*: type I IFN related protein according to http://interferome.its.monash.edu.au/interferome/ |
||||||
Table 2: Serum proteins correlating significantly with mRSS |
|||||
Protein name |
Gene name |
Correlation |
Adjusted for age, gender |
||
|
r |
Pᵘ |
b (CI) |
Pᵐ |
|
Alpha 1 Antichymotrypsin |
SERPINA3 |
0.42 |
0.001 |
9.07 (4.04, 14.12) |
0.001 |
NT proBNP |
NPPB |
0.38 |
0.002 |
3.11 (1.18, 5.04) |
0.002 |
Endostatin |
COL18A1 |
0.37 |
0.002 |
12.56 (4.81, 20.31) |
0.002 |
Osteopontin |
SPP1 |
0.34 |
0.006 |
7.08 (2.61, 11.56) |
0.002 |
Angiopoietin 2 |
ANGPT2 |
0.33 |
0.005 |
5.43 (1.51, 9.36) |
0.007 |
Serum Amyloid P Component |
APCS |
0.32 |
0.008 |
9.55 (2.38, 16.72) |
0.010 |
Tenascin C |
TNC |
0.31 |
0.011 |
5.53 (1.36, 9.70) |
0.010 |
Alpha 1 Microglobulin |
AMBP |
0.31 |
0.011 |
8.85 (2.02, 15.69) |
0.012 |
Insulin like Growth Factor Binding Protein 4 |
IGFBP4 |
0.30 |
0.018 |
5.36 (1.41, 9.31) |
0.009 |
Interleukin 22 |
IL22 |
-0.30 |
0.016 |
-8.20 (-15.08, -1.32) |
0.020 |
Hepatocyte Growth Factor receptor |
MET |
-0.30 |
0.016 |
-9.63 (-17.08, -2.18) |
0.012 |
Tetranectin |
CLEC3B |
-0.31 |
0.011 |
-11.99 (-20.57, -3.41) |
0.007 |
Kallikrein 5 |
KLK5 |
-0.33 |
0.007 |
-6.35 (-10.95, -1.77) |
0.007 |
Urokinase type Plasminogen Activator |
PLAU |
-0.34 |
0.005 |
-6.83 (-11.55, -2.12) |
0.005 |
Thymus and activation regulated chemokine |
CCL17 |
-0.35 |
0.003 |
-4.10 (-6.80, -1.41) |
0.003 |
Tamm Horsfall Urinary Glycoprotein |
UMOD |
-0.40 |
0.001 |
-7.55 (-11.75, -3.35) |
0.001 |
Macrophage Derived Chemokine |
CCL22 |
-0.43 |
<0.001 |
-11.14 (-16.96, -5.31) |
<0.001 |
Epidermal Growth Factor Receptor |
EGFR |
-0.43 |
<0.001 |
-11.61 (-18.02, -5.32) |
0.001 |
r: Pearson correlation coefficient; Pᵘ: p value from univariable model; b: Mean difference in the cytokine per unit of mRSS in the multivariable model; CI: confidence interval; Pᵐ: p value from multivariable model after adjustment for age and gender |
To cite this abstract in AMA style:
Bellocchi C, Ying J, Goldmuntz E, Keyes-Elstein L, Varga J, Hinchcliff M, McSweeney P, Furst DE, Nash R, Crofford L, Welch B, Pinckney A, Mayes MD, Sullivan K, Assassi S. Systemic Sclerosis Has a Distinct Serum Protein Profile That Correlates with Its Clinical Manifestations [abstract]. Arthritis Rheumatol. 2018; 70 (suppl 9). https://acrabstracts.org/abstract/systemic-sclerosis-has-a-distinct-serum-protein-profile-that-correlates-with-its-clinical-manifestations/. Accessed .« Back to 2018 ACR/ARHP Annual Meeting
ACR Meeting Abstracts - https://acrabstracts.org/abstract/systemic-sclerosis-has-a-distinct-serum-protein-profile-that-correlates-with-its-clinical-manifestations/