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Abstract Number: 765

Proteomic Analysis of Scleroderma Associated Joint Disease

Chan Kim1, Julio Mantero2, Robert A. Lafyatis3 and Robert W. Simms4, 1Rheumatology and Clinical Epidemiology, Boston University School of Medicine, Boston, MA, 2Arthritis Center, Boston University School of Medicine, Boston, MA, 3Division of Rheumatology and Clinical Immunology, University of Pittsburgh School of Medicine, Pittsburgh, PA, 4Rheumatology, Boston University School of Medicine, Boston, MA

Meeting: 2017 ACR/ARHP Annual Meeting

Date of first publication: September 18, 2017

Keywords: biomarkers and proteomics, Scleredema

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Session Information

Date: Sunday, November 5, 2017

Title: Systemic Sclerosis, Fibrosing Syndromes and Raynaud's – Pathogenesis, Animal Models and Genetics Poster I

Session Type: ACR Poster Session A

Session Time: 9:00AM-11:00AM

Background/Purpose:

The pathophysiology of joint disease in scleroderma, a heterogeneous multisystem disease mostly characterized by fibrosis, is unknown.  We performed proteomic analysis of serum in patients with scleroderma and joint tenderness.  Understanding systemic protein expression in scleroderma may help us understand joint disease in scleroderma.  Our goal was to characterize protein expression differences between scleroderma patients with joint tenderness and scleroderma patients without joint tenderness.

Methods:

Patients with scleroderma were recruited from the registry at Boston University Medical Center’s Scleroderma Center.  Serum (blood) samples were drawn and were analyzed with SOMAscan for 1129 protein biomarkers.  As part of the routine examination performed by a senior rheumatologist on all registry participants, tender joint count (0-18) was assessed on physical exam.  If a subject had a tender joint count of 2 or more, then that subject had joint disease.  If a subject had a tender joint count of 0, then that subject did not have joint disease.  For this study, 40 scleroderma subjects had both SOMAscan data and tender joint count assessment. One subject with only 1 tender joint count was excluded, so 39 subjects were analyzed.  For analysis, the biomarkers were log2 transformed, and differential expression analyses were performed using the “limma” package using the R statistical software. 

Results:

Among the 39 scleroderma subjects, 9 participants had joint pain (average tender joint count 4.9), and protein expression was compared between scleroderma participants with joint disease and scleroderma participants without joint disease.  The top 20 most significant biomarkers are shown in table 1.  In previous analyses (not shown), similar biomarkers (such as MMP (matrix metalloproteinase), fibrinogen, tumor necrosis factor), were seen elevated in all scleroderma participants (compared to normal subjects without scleroderma).   Notably, IL-6, cadherin-2 (involved in bone and cartilage formation), BRF1 (RNA Polymerase III transcription initiation factor subunit) were expressed higher in scleroderma subjects with joint disease compared to those without joint disease.  VEGF-121 (vascular endothelial growth factor) was expressed lower in scleroderma subjects with joint pain compared to those without joint disease. 

Conclusion:

Although scleroderma participants had many protein expression changes due to fibrosis, autoimmunity and vasculopathy, several biomarkers such as IL-6, cadherin-2, BRF1, VEGF-121 were differentially expressed in scleroderma participants with joint disease and could provide insight into the pathophysiology of joint disease in scleroderma.

 

Table 1:  Joint disease vs no joint disease

Log Fold Change

P Value

MK12

0.375414

0.000385

IL-6

0.425859

0.002113

VEGF121

-0.69485

0.002898

MBL

0.697418

0.003867

ADAM 9

0.920928

0.008789

a1-Antitrypsin

0.459117

0.00907

CDC37

0.173549

0.009931

TSP4

0.472696

0.012891

LDH-H 1

0.32681

0.013691

BRF-1

0.29382

0.014471

MMP-14

0.379094

0.016855

PDGF-BB

-0.44877

0.017505

iC3b

-0.46833

0.017607

Siglec-9

1.04874

0.020749

Carbonic Anhydrase IV

-0.30158

0.023048

Cadherin-2

0.285673

0.024096

MK11

0.265757

0.025145

Thrombospondin-1

-0.34304

0.025595

Fibrinogen

0.429274

0.027908

Macrophage mannose receptor

0.269891

0.029517

 


Disclosure: C. Kim, None; J. Mantero, None; R. A. Lafyatis, None; R. W. Simms, None.

To cite this abstract in AMA style:

Kim C, Mantero J, Lafyatis RA, Simms RW. Proteomic Analysis of Scleroderma Associated Joint Disease [abstract]. Arthritis Rheumatol. 2017; 69 (suppl 10). https://acrabstracts.org/abstract/proteomic-analysis-of-scleroderma-associated-joint-disease/. Accessed .
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