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Erschienen in: BMC Musculoskeletal Disorders 1/2011

Open Access 01.12.2011 | Research article

Regulation of gene expression in human tendinopathy

verfasst von: Scott A Jelinsky, Scott A Rodeo, Jian Li, Lawrence V Gulotta, Joanne M Archambault, Howard J Seeherman

Erschienen in: BMC Musculoskeletal Disorders | Ausgabe 1/2011

Abstract

Background

Chronic tendon injuries, also known as tendinopathies, are common among professional and recreational athletes. These injuries result in a significant amount of morbidity and health care expenditure, yet little is known about the molecular mechanisms leading to tendinopathy.

Methods

We have used histological evaluation and molecular profiling to determine gene expression changes in 23 human patients undergoing surgical procedures for the treatment of chronic tendinopathy.

Results

Diseased tendons exhibit altered extracellular matrix, fiber disorientation, increased cellular content and vasculature, and the absence of inflammatory cells. Global gene expression profiling identified 983 transcripts with significantly different expression patterns in the diseased tendons. Global pathway analysis further suggested altered expression of extracellular matrix proteins and the lack of an appreciable inflammatory response.

Conclusions

Identification of the pathways and genes that are differentially regulated in tendinopathy samples will contribute to our understanding of the disease and the development of novel therapeutics.
Hinweise

Electronic supplementary material

The online version of this article (doi:10.​1186/​1471-2474-12-86) contains supplementary material, which is available to authorized users.

Competing interests

Howard Seeherman, Jian Li, Joanne Archambault and Scott Jelinsky were employed by Wyeth Research/Pfizer at the time of this research. Scott A Rodeo received research funding from Wyeth at the time of this study.

Authors' contributions

HJS, JMA and SAR worked on the study design. SAR recruited patients and collected the samples. LVG wrote the IRB and informed consents and help collect the samples. JL performed the histology analysis. SAJ performed the microarray analysis and drafted the manuscript. All authors have read and approved the final manuscript.

Background

Chronic injuries to the Achilles, patellar, extensor carpi radialis brevis, and supraspinatus tendons remain a common problem for both elite and recreational athletes, as well as for individuals engaging in repetitive activities. These overuse type injuries account for 30-50% of all sports injuries and result in a significant amount of morbidity and health care expenditure [1].
Histologic studies have shown that the primary pathology is not inflammation as implied by the commonly used term "tendonitis." Instead, samples of diseased tendons show collagen degeneration, fiber disorientation, mucoid ground substance, hypercellularity, vascular ingrowth, and relative absence of inflammatory cells under light microscopy [24]. Tendinopathy (or tendinosis) is now the term most commonly used to describe the clinical entity and histologic findings. Interestingly, these findings are common to all tendinopathies, suggesting a similar etiology and pathophysiology.
The etiology of tendinopathy remains unclear, but most believe that a combination of extrinsic and intrinsic factors is responsible. The extrinsic theory suggests that direct mechanical contact leads to tendon fiber micro-damage and subsequent injury of the tendon that eventually results in weakness and pain. An example is impingement of the acromion on the supraspinatus tendon, which serves as the rationale behind acromioplasty surgery [5]. The intrinsic theory suggests that the tendon itself becomes inherently degenerative, probably as a result of microscopic fiber failure leading to accumulation of damage due to inability of the tendon to self-repair. Local ischemia may also be a contributory factor. Studies on the supraspinatus tendon have shown that its mid-portion is relatively hypovascular [6]. This lack of perfusion may result in the formation of oxygen free radicals or other molecules that initiate the pathological process.
Several observations have been made about the molecular mediators of tendinopathy. Tenocyte apoptosis or "programmed cell death" has been shown to occur at an increased frequency in tendinopathy specimens [7]. Free radicals as well as cyclic loading may induce the activation of molecules that lead to apoptosis [8, 9]. In addition, animal studies have shown that various cytokines and matrix metalloproteinases (MMPs) may be disproportionately expressed in tendinopathy specimens. The application of cyclic strain has been shown to increase the production of prostaglandin E2 (PGE2), interleukin-6 (IL6), and IL1β [10, 11]. IL1β in turn increases the production of MMP1, MMP3, and PGE2 [12]. Alfredson et al. studied samples from patients with Achilles tendinopathy and found downregulation of MMP3 mRNA and upregulation of MMP2 and vascular endothelial growth factor compared with control samples [13]. Riley et al. reported decreased MMP3 and MMP2 mRNA activity, with an increase in MMP14 [14]. These studies show that an imbalance in cytokines and MMPs exists in diseased tendons and probably contributes to the pathophysiology; however, inconsistencies in the expression of specific molecules in various studies indicate that more research needs to be done.
Currently, the only non-surgical therapies available to patients who suffer from chronic tendinopathies are physical therapy, activity modification, non-steroidal anti-inflammatory medications (NSAIDs), and steroid or platelet-rich plasma injections. These therapies offer unpredictable results, and in the case of steroids, can lead to serious side effects and more rapid degeneration of the tendon. By understanding the molecular mediators that lead to tendinopathy, novel therapeutic targets could potentially be identified for drug development. This will result in more effective treatments while minimizing side effects.
Microarray analysis has become a powerful tool in drug development. Microarrays allow researchers to screen samples of tissue for the expression of thousands of genes encoded in the human genome. This "shotgun" approach can identify which genes are active in a given sample by quantifying the production of specific mRNAs. Identification of the products of these mRNAs and their functions can serve to direct future research and development.
The purpose of this study was to investigate whether there is selective regulation of certain cytokines, matrix metalloproteinases, and protein kinases in human samples of tendinopathy compared with normal tendons, as evidenced by microarray analysis. Specifically, we were interested in determining which specific cytokines and degenerative enzymes are upregulated, and which are downregulated, in diseased samples compared with normal control tendons from the same patients. This information may contribute to the development of drugs that can selectively modulate the disease process.

Methods

Subjects

All protocols were approved by the Institutional Review Board at the Hospital for Special Surgery and informed consent was obtained from each participant. A prospective study was initiated to collect tissue from patients undergoing surgery as standard of care for tendinopathy. Biopsies (~3 mm3) of diseased tendons and a section of grossly normal appearing tendon were collected from 35 patients. Written informed consent was obtained from all patients prior to any study-related procedure. Information on patient demographics, diagnosis, prior treatments, current procedures, and operative findings was collected and is presented in Table 1. Patients with a diagnosis of inflammatory arthritis (such as rheumatoid arthritis or lupus) or those who had prior surgery on the involved tendon were excluded. Patients who received prior corticosteroid injection were included and this information was recorded.
Table 1
Demographics and patient clinical diagnosis
ID
Age
Sex
Diagnosis
Duration of Sx (months)
Num of Inject*
Pathology Sample
Control Sample
5
45
M
Distal Biceps Rupture
0.3
 
Distal Biceps
Brachialis
9
48
M
ECRB tear
12
 
ECRB
EDC
10
41
M
Patella Tendon Rupture
0.1
 
Patella
Quad tendon
12
62
M
Flexor/Pronator
18
1
flexor/pronator
Distal Flexor/Pronator
13
62
F
RTC tear
48
2
Supraspinatus
Subscap
15
32
M
Patella Tendon Tear
3
 
Patella tendon
Nl Patellar Tendon
16
61
F
RTC tear
24
2
Supraspinatus
Subscap
17
59
M
RTC tear
6
1
Supraspinatus
Subscap
19
45
M
Flexor/Pronator
18
3
flexor/pronator
Distal Flexor/Pronator
20
63
F
RTC tear
9
1
Supraspinatus
Subscap
21
65
F
RTC tear
3
1
Supraspinatus
Biceps
23
64
F
RTC tear
8
1
Supraspinatus
Subscap
24
50
M
RTC tear
18
1
Supraspinatus
Biceps
26
55
M
ECRB tear
4
 
ECRB
Distal ECRB
27
50
M
RTC tear
4
 
Supraspinatus
Normal RTC
28
41
M
Supra tear (PT), OA, Bankart
>24
 
Supraspinatus
Biceps Tendon
29
46
M
RTC tear, Adhesive Capsulitis
4
 
Supraspinatus
Biceps Tendon
30
52
M
ECRB tear
12
 
ECRB
ECRL
31
66
M
RTC tear
6
 
Supraspinatus
Subscap
32
46
F
RTC tear
2
1
Supraspinatus
Teres minor
33
44
M
RTC tear
6
1
Supraspinatus
Subscap
34
59
F
RTC tear
1
3
Supraspinatus
Biceps
35
49
F
RTC tear
24
 
Supraspinatus
Subscap
* Number of corticosteroids injections
ECRB Extensor Carpi Radialis Brevis
RTC Rotator Cuff
OA Osteoarthitis
EDC extensor digitorum comunis

RNA Preparation and Hybridization

RNA extraction and isolation were performed as previously described [15]. Fifty nanograms of RNA was labeled using the WT-Ovation FFPE System (Nugen, San Carlos, CA). Labeled cDNA was hybridized to GeneChip® Human Genome U133 2.0 arrays according to the manufacturer's protocol (Affymetrix, Santa Clara, CA). For each array, all probe sets were normalized to a mean signal intensity value of 100. The default GeneChip Operating Software statistical values were used for all analyses. The raw microarray data has been deposited in the Gene Expression Omnibus (GEO) database http://​www.​ncbi.​nlm.​nih.​gov/​projects/​geo/​ as accession number GSE26051.

Identification of Differentially Expressed Genes

Expression values for all probe sets were subjected to locally weighted scatterplot smoothing (LOWESS) transformation. Correlation analysis and hierarchical clustering verified that all samples had similar patterns of expression. Only transcripts that were called as present in 65% of the samples and expressed greater than 35 signal units in either the normal or diseased samples were used for further analysis. Expression values were log2 transformed and transcripts were considered differentially regulated if the p-value based on a paired t-test analysis was < 0.01 and the average fold change was greater than 1.5. Extensive clinical information was collected for each patient. Analysis of variance models were constructed to determine whether any differences in expression could be explained by differences in histological disease score, disease duration, gender, steroid use, or NSAID use. Values presented are expressed as mean ± standard error of the mean. Differences were considered statistically significant for p < 0.01.

Identification of Significantly Regulated Gene Sets

Significantly regulated biological pathways were identified using a modified version of the sigPathway algorithm [16] incorporating a modified normalization routine and using gene sets collections C1 to C5 defined by the Molecular Signatures Database (MSigDB) [17]. A gene set was considered significant when q1 ≤0.05 and q2 ≤0.05, where q1 or q2 are the permutation-based false-discovery rates for the Q1 or Q2 hypotheses (see [18] for an explanation of Q1 and Q2). These cut-offs were met by1761 gene sets, which can be considered as differentially expressed.

Histology

Tissue samples were frozen and sectioned for histological analysis. Sections were processed using standard procedures, including Alcian blue (AB) staining. Sections were scored on four categories: intratendinous cellular proliferation, intratendinous vascular proliferation, intratendinous glycosaminoglycan (GAG) accumulation, and intratendinous fiber disorientation. Each category was scored based on a 5-point scale, from 0 for normal, 3 for moderate, and 5 for severe, by two independent histologists.

Results

Analysis of Tendinopathy Tissue Samples

Diseased and normal tendons were collected from 35 patients with rotator cuff tendinopathy, lateral epicondylitis (tennis elbow), patellar tendinopathy, or chronic Achilles tendinopathy who were undergoing surgery as standard of care treatment for tendinopathy. Tendinopathy was confirmed both macroscopically and microscopically. The diseased tendon appeared dull, yellow, and soft compared with normal tissue, which is shiny, white, and firm. Normal tendon tissue had relatively few cells, contained little vasculature, and had collagen fibers aligned in the direction of force. All diseased tendons had a similar loss of normal fibrillar structure and changes in cell orientation, which are histological characteristics of tendinopathy [2, 19, 20]. All diseased tissue had an increased number of fibroblasts, increased vasculature, and increased glycosaminoglycan staining (GAG content) although the degree of increase in each of the parameters was variable between patients (Figure 1, Table 2). There was little evidence of any inflammatory cells in either the tendon or the surrounding paratenon.
Table 2
Intratendinous tendinopathy scorea
Patientb
Cellular Proliferation
Vascular Proliferation
GAG Accumulation
Fiber Disorientation
Total Score
5
3.5
1.5
1.5
5
11.5
9
5
2
5
5
17
10
4.5
5
5
5
19.5
12
4
5
1
5
15
13
5
1
3.5
5
14.5
15
5
5
5
4.5
19.5
16
3.5
2.5
2
5
13
17
5
4.5
3
5
17.5
19
4.5
5
3
5
17.5
20
5
3
3
5
16
21
5
1
2
5
13
23
4.5
3
4
5
16.5
24
5
5
3
5
18
26
5
3
5
5
18
27
4.5
3
1
5
13.5
28
5
1.5
5
5
16.5
29
5
5
5
5
20
30
4
4.5
3
4.5
16
31
4.5
1.5
4
5
15
32
4.5
1.5
5
5
16
33
5
0.5
4
5
14.5
34
5
0.5
3
5
13.5
35
5
5
3
5
18
a Average of two independent histologist evaluation
b Normal tendon were scored 0 in all fields

Analysis of Gene Expression

Global transcriptional analysis using Affymetrix genome-wide U133 2.0 Plus arrays identified 20055 transcripts expressed in 23 pairs of normal and diseased tendons that passed quality control filters. Of these, 983 transcripts were differentially regulated based on a paired t-test (p < 0.01, fold change ≥1.5. Among the top regulated genes were a disintegrin and metalloprotease 12 (ADAM12), tenascin C (TNC), periostin (POSTN), and interleukin 13 receptor alpha 2 (IL13RA2; Figure 2, Table 3). An analysis of covariance (ANCOVA) showed little relationship between the age of the patient and the level of gene expression for most transcripts. Furthermore, ANCOVA analysis suggested that < 1.2% of the transcripts showed any relationship between gene expression and histological disease score, disease duration, steroid use, NSAID use, gender, or duration of symptoms.
Table 3
Top regulated transcripts in human tendinopathy as determined by microarray analysis
Gene Symbol
Description
p-value
q-value
Fold Change
ADAM12
A disintegrin and metalloproteinase domain 12
1.57E-05
2.09E-04
5.6
AP3M1
Adaptor-related protein complex 3, mu 1 subunit
1.24E-03
1.91E-03
1.7
ARL7
ADP-ribosylation factor-like 7
1.43E-03
2.11E-03
4.0
ARPC5
Actin related protein 2/3 complex, subunit 5
3.63E-05
2.10E-04
1.8
ASXL1
Additional sex combs like 1 (Drosophila)
1.11E-03
1.78E-03
1.8
ATP6V1A
ATPase, H+ transporting, lysosomal 70 kDa
4.18E-05
2.10E-04
2.5
BACE2
Beta-site APP-cleaving enzyme 2
3.17E-06
8.01E-05
1.9
BNC2
Basonuclin 2
1.08E-04
3.15E-04
2.9
CA12
Carbonic anhydrase XII
3.57E-05
2.10E-04
2.8
CTHRC1
Collagen triple helix repeat containing 1
5.20E-04
1.10E-03
4.4
DDEF1
Development and differentiation enhancing factor
2.83E-05
2.10E-04
2.1
DOCK10
Dedicator of cytokinesis 10
7.91E-03
8.11E-03
3.3
EDIL3
EGF-like repeats and discoidin I-like domains 3
4.80E-03
5.34E-03
2.9
FOXP1
Forkhead box P1
4.67E-05
2.10E-04
1.7
GPR161
G protein-coupled receptor 161
2.76E-04
6.89E-04
1.9
IGFBP3
Insulin-like growth factor binding protein 3
7.29E-03
7.67E-03
3.5
IL13RA2
Interleukin 13 receptor, alpha 2
2.80E-03
3.50E-03
3.5
ILK
Integrin-linked kinase
1.00E-04
3.15E-04
1.6
IQGAP1
IQ motif containing GTPase activating protein 1
4.73E-05
2.10E-04
1.5
ITGB1
Integrin, beta 1
3.52E-04
8.29E-04
1.7
ITPKB
Inositol 1,4,5-trisphosphate 3-kinase B
7.37E-04
1.34E-03
2.5
JAG1
Jagged 1 (Alagille syndrome)
1.90E-03
2.52E-03
3.1
KCNE4
Potassium voltage-gated channel 4
8.19E-03
8.19E-03
3.4
LAMA4
Laminin, alpha 4
6.73E-04
1.31E-03
3.4
LRRC15
Leucine rich repeat containing 15
3.50E-03
4.24E-03
3.2
LRRC17
Leucine rich repeat containing 17
1.74E-03
2.40E-03
2.8
MARCKS
Myristoylated alanine-rich kinase C substrate
3.93E-03
4.50E-03
2.8
NOTCH3
Notch homolog 3 (Drosophila)
1.65E-03
2.36E-03
3.6
PDIR
protein disulfide isomerase-related
4.86E-04
1.08E-03
2.1
POSTN
Periostin, osteoblast specific factor
1.10E-04
3.15E-04
3.5
RAP1GDS1
RAP1, GTP-GDP dissociation stimulator 1
1.01E-03
1.68E-03
2.1
S100A10
S100 calcium binding protein A10
1.95E-03
2.52E-03
2.8
SIN3A
SIN3 homolog A, transcription regulator (yeast)
9.51E-05
3.15E-04
1.7
SLC2A13
Solute carrier family 2 13
5.41E-03
5.85E-03
2.8
TAOK1
TAO kinase 1
1.51E-04
4.03E-04
1.7
TJP1
Tight junction protein 1 (zona occludens 1)
6.87E-04
1.31E-03
1.6
TNC
Tenascin C (hexabrachion)
9.20E-05
3.15E-04
5.3
UBE2E3
Ubiquitin-conjugating enzyme E2E 3
8.72E-04
1.52E-03
3.7
WDR1
WD repeat domain 1
4.01E-06
8.01E-05
1.6
WISP1
WNT1 inducible signaling pathway protein 1
3.93E-03
4.50E-03
3.4
Global pathway analysis, based on a modified sigPathway algorithm [16], identified increased expression of genes involved in the extracellular matrix, including genes involved in focal adhesion, integrin signaling, and collagen synthesis. In addition, expression of genes involved in cell cycle progression, TGFβ signaling, and NFκB signaling was increased (Table 4). This global pathway analysis did not suggest that cytokines as a whole were differentially regulated. However, of the 426 transcripts annotated by Gene Ontology as cytokines, cytokine signaling molecules, or related to cytokines, six were differentially regulated in diseased tendons, including chemokine-like factor super family 4 (CMTM4), interleukin 13 receptor alpha 2 (IL13RA2), interleukin 17D (IL17D), and interleukin 4 receptor (IL4R) (Table 5).
Table 4
Genesets regulated in human tendinopathy as determined by sigpathway
 
NTk*
Up regulated
 
   HSA04110_CELL_CYCLE
6.52
   RNA_PROCESSING
6.44
   SPINDLE
6.25
   HSA04510_FOCAL_ADHESION
6.10
   TGFBETA_LATE_UP
6.02
   CELL_CYCLE_KEGG
6.00
   CELL_CYCLE
5.94
   ST_INTEGRIN_SIGNALING_PATHWAY
5.40
   COLLAGEN
5.32
   RUIZ_TENASCIN_TARGETS
5.24
   I_KAPPAB_KINASE_NF_KAPPAB_CASCADE
5.23
   MITOSIS
5.03
   INOS_ALL_UP
4.89
Down Regulated
 
   ION_TRANSMEMBRANE_TRANSPORTER_ACTIVITY
-4.99
   G_PROTEIN_COUPLED_RECEPTOR_ACTIVITY
-5.01
   ELECTRON_TRANSPORT_CHAIN
-5.21
   MOOTHA_VOXPHOS
-6.01
   ION_CHANNEL_ACTIVITY
-6.20
   SUBSTRATE_SPECIFIC_CHANNEL_ACTIVITY
-6.27
* As defined in Tian et. al [18]
Table 5
Chemokines regulated in human tendinopathy
Gene Symbol
Description
p-value
q-value
Fold Change
BMP1
Bone morphogenetic protein 1
0.000
0.005
1.69
BMP8B
Bone morphogenetic protein 8b
0.002
0.011
1.79
CCL2
Chemokine (C-C motif) ligand 2
0.005
0.014
1.74
CMTM4
Chemokine-like factor super family 4
0.008
0.017
1.98
CMTM6
Chemokine-like factor super family 6
0.014
0.023
1.37
IFNGR1
Interferon gamma receptor 1
0.027
0.034
1.42
IL13RA2
Interleukin 13 receptor, alpha 2
0.003
0.011
3.48
IL17D
Interleukin 17D
0.008
0.017
0.54
IL6R
Interleukin 6 receptor
0.026
0.034
0.73
LEPR
Leptin receptor
0.028
0.034
0.49
OSMR
Oncostatin M receptor
0.038
0.043
1.81
SP110
SP110 nuclear body protein
0.010
0.019
1.51
STAT2
Signal transducer and activator of transcription 2
0.051
0.054
1.4
STAT3
Signal transducer and activator of transcription 3
0.004
0.013
1.87
TXLNA
Taxilin
0.001
0.006
1.39
Consistent with a role in increased matrix turnover, tendonopathy tissue exhibited increased expression of genes encoding MMPs (Table 6) and genes encoding collagens (Table 7). The majority of collagens interrogated showed a modest 2-fold increase in expression in diseased tendons. Diseased tendons also showed increased expression of several enzymes that mediate collagen breakdown, including MMP2, MMP9, MMP14, MMP13, and MMP19. While many MMP genes were induced in diseased tendons, not all transcripts encoding MMPs were upregulated; in fact, MMP3 and MMP24 were significantly downregulated in diseased tissue. Of the four known tissue inhibitors of metalloproteases (TIMPs), only expression of TIMP1 was increased. No ADAMTS (a disintegrin and metalloprotease with thrombospondin motifs) family members were differentially regulated based on our cut-offs.
Table 6
Change in matrix metallopeptidase gene expression in human tendinopathy
Gene Symbol
Description
 
p-value
q-value
Fold Change
Regulated
     
MMP2
Matrix metallopeptidase 2
Expressed
7.42E-03
4.82E-02
1.8
MMP3
Matrix metallopeptidase 3
Expressed
5.50E-02
2.38E-01
0.3
MMP14
Matrix metallopeptidase 14
Expressed
1.79E-03
1.66E-02
1.9
MMP19
Matrix metallopeptidase 19
Expressed
1.91E-03
1.66E-02
3.4
Not Regulated
     
MMP28
Matrix metallopeptidase 28
Expressed
0.09
0.30
1.4
TIMP1
TIMP metallopeptidase inhibitor 1
Expressed
0.10
0.30
1.6
TIMP2
TIMP metallopeptidase inhibitor 2
Expressed
0.37
0.50
1.1
TIMP3
TIMP metallopeptidase inhibitor 3
Expressed
0.26
0.49
0.9
TIMP4
TIMP metallopeptidase inhibitor 4
Expressed
0.71
0.80
0.9
Expressed below limited of detection
     
MMP1
Matrix metallopeptidase 1
-
0.96
0.96
1.0
MMP7
Matrix metallopeptidase 7
-
0.34
0.49
0.8
MMP8
Matrix metallopeptidase 8
-
0.81
0.84
0.8
MMP9
Matrix metallopeptidase 9
-
0.00
0.02
3.2
MMP10
Matrix metallopeptidase 10
-
0.08
0.30
0.8
MMP12
Matrix metallopeptidase 12
-
0.79
0.84
0.9
MMP13
Matrix metallopeptidase 13
-
0.03
0.14
2.6
MMP15
Matrix metallopeptidase 15
-
0.15
0.35
0.5
MMP16
Matrix metallopeptidase 16
-
0.57
0.67
0.6
MMP17
Matrix metallopeptidase 17
-
0.56
0.67
0.8
MMP20
Matrix metallopeptidase 20
-
0.53
0.67
0.7
MMP21
Matrix metallopeptidase 21
-
0.13
0.33
1.5
MMP23A/B
Matrix metallopeptidase 23A/B
-
0.34
0.49
0.8
MMP24
Matrix metallopeptidase 2
-
0.29
0.49
0.6
MMP25
Matrix metallopeptidase 25
-
0.18
0.40
0.7
MMP26
Matrix metallopeptidase 26
-
0.34
0.49
0.8
MMP27
Matrix metallopeptidase 27
-
0.33
0.49
0.8
Table 7
Change in collagen gene expression in human tendinopathy
Gene Symbol
Description
 
p-value
q-value
Fold Change
Regulated
     
COL1A1
Collagen, type I, alpha 1
Expressed
9.37E-03
3.96E-02
1.7
COL1A2
Collagen, type I, alpha 2
Expressed
4.45E-03
3.16E-02
1.6
COL3A1
Collagen, type III, alpha 1
Expressed
1.50E-02
4.28E-02
2.0
COL4A1
Collagen, type IV, alpha 1
Expressed
1.91E-02
4.53E-02
2.7
COL4A2
Collagen, type IV, alpha 2
Expressed
6.09E-03
3.16E-02
2.3
COL5A1
Collagen, type V, alpha 1
Expressed
1.20E-02
4.28E-02
2.0
COL5A2
Collagen, type V, alpha 2
Expressed
3.99E-03
3.16E-02
2.1
COL5A3
Collagen, type V, alpha 3
Expressed
3.02E-03
3.16E-02
2.0
COL6A1
Collagen, type VI, alpha 1
Expressed
2.93E-02
6.18E-02
1.8
COL6A2
Collagen, type VI, alpha 2
Expressed
3.62E-02
6.89E-02
1.8
COL6A3
Collagen, type VI, alpha 3
Expressed
5.45E-03
3.16E-02
1.7
COL8A1
Collagen, type VIII, alpha 1
Expressed
2.49E-02
5.57E-02
2.0
COL8A2
Collagen, type VIII, alpha 2
Expressed
1.48E-02
4.28E-02
1.8
COL10A1
Collagen, type X, alpha 1
Expressed
1.69E-02
4.28E-02
2.1
COL12A1
Collagen, type XII, alpha 1
Expressed
4.10E-03
3.16E-02
2.1
COL18A1
Collagen, type XVIII, alpha 1
Expressed
6.65E-03
3.16E-02
2.2
COL27A1
Collagen, type XXVII, alpha 1
Expressed
1.20E-03
3.16E-02
2.5
Not Regulated
     
COL7A1
Collagen, type VII, alpha 1
Expressed
0.96
0.96
1.0
COL11A1
Collagen, type XI, alpha 1
Expressed
0.58
0.71
1.2
COL15A1
Collagen, type XV, alpha 1
Expressed
0.51
0.64
1.2
COL16A1
Collagen, type XVI, alpha 1
Expressed
0.12
0.19
1.4
COL21A1
Collagen, type XXI, alpha 1
Expressed
0.34
0.45
1.4
Expressed below limited of detection
     
COL2A1
Collagen, type II, alpha 1
-
0.21
0.31
0.5
COL4A3
Collagen, type IV, alpha 3
-
0.15
0.23
0.6
COL4A4
Collagen, type IV, alpha 4
-
0.90
0.96
1.0
COL4A5
Collagen, type IV, alpha 5
-
0.71
0.84
0.9
COL4A6
Collagen, type IV, alpha 6
-
0.94
0.96
1.0
COL9A1
Collagen, type IX, alpha 1
-
0.94
0.96
1.0
COL9A2
Collagen, type IX, alpha 2
-
0.05
0.08
1.9
COL11A2
Collagen, type XI, alpha 2
-
0.12
0.19
0.7
COL13A1
Collagen, type XIII, alpha 1
-
0.08
0.13
2.0
COL14A1
Collagen, type XIV, alpha 1
-
0.02
0.04
1.8
COL17A1
Collagen, type XVII, alpha 1
-
0.33
0.45
1.3
COL19A1
Collagen, type XIX, alpha 1
-
0.02
0.04
0.5
COL22A1
Collagen, type XXII, alpha 1
-
0.03
0.07
0.5
COL23A1
Collagen, type XXIII, alpha 1
-
0.75
0.84
1.0
COL24A1
Collagen, type XXIV, alpha 1
-
0.33
0.45
1.3
COL25A1
Collagen, type XXV, alpha 1
-
0.76
0.84
0.9
Diseased tendons showed increased expression of a number of relevant and important signaling pathways; for example the fibroblast growth factors FGFR1 (1.7-fold) and FGFR2 (2.7-fold), and genes in the Notch signaling pathway, including JAG1 (3.1-fold) and Notch3 (3.6-fold). There was also evidence for increased WNT signaling. Among the highest regulated transcripts, four are involved in WNT signaling: WISP1 (4.2-fold), DKK3 (3.6-fold), WNT3 (3.6-fold), and LEF1 (4.1-fold). Additionally, tendinopathy tissue showed differential expression of other WNT pathway genes, including increased expression of CTNNB (1.5-fold), WNT5a (2.7-fold), and FZD1 (1.7-fold) and decreased expression of LRP5 (0.59-fold) and FRZB (0.35-fold).
We found little evidence for endochondral ossification even though this has been reported in Achilles and patella tendinopathy [21]. Histological evaluation failed to identify any gross areas of ossification in any of the patients and RNA analysis did not show increased expression of the bone markers osteocalcin or osterix. However, expression of CBFA1, a transcription factor associated with osteoblast differentiation, was increased 1.8-fold and that of RANKL, a key factor for osteoclast differentiation and activation, was increased 4.0-fold in diseased tendons.
In addition to the global pathway analysis, we specifically investigated the regulation of kinases in diseased tendons (Table 8). The most statistically significant regulated kinase is diseased tendons is the thousand and one amino acid kinase (TAOK1), which showed a 1.7-fold increase in expression. TAOK1 activates the p38 MAP kinase pathway and tendonopathy tissue also showed increased expression of multiple MAP kinases, including MAP3K2 (1.8-fold), MAP4K5 (1.9-fold), and MAPK8 (2.0-fold).
Table 8
Kinases regulated in human tendinopathy
Gene Symbol
Description
pValue
q-value
Fold Change
ABL2
v-abl Abelson leukemia viral oncogene homolog 2
4.79E-03
7.83E-03
31.0
BMPR2
Bone morphogenetic protein receptor, type II
4.10E-03
7.83E-03
27.0
CAV2
Caveolin 2
1.22E-02
1.44E-02
43.0
CDK6
Cyclin-dependent kinase 6
1.37E-02
1.53E-02
24.0
CSNK1D
Casein kinase 1, delta
5.21E-03
8.13E-03
19.0
CSNK1G1
Casein kinase 1, gamma 1
8.18E-03
1.03E-02
40.0
DCLK1
Doublecortin-like kinase 1
3.78E-03
7.83E-03
28.0
EML4
Echinoderm microtubule associated protein like 4
9.69E-04
3.15E-03
41.0
EPS8
Epidermal growth factor receptor substrate 8
1.96E-04
1.67E-03
9.0
FGFR1
Fibroblast growth factor receptor 1
5.64E-03
8.46E-03
1.7
ILK
Integrin-linked kinase
1.00E-04
1.67E-03
1.6
JAK3
Janus kinase 3
4.62E-03
7.83E-03
1.8
KIAA0220
PI-3-kinase-related kinase SMG-1
2.70E-03
7.02E-03
1.6
KIAA0999
KIAA0999 protein
1.62E-03
4.86E-03
2.1
MAP3K2
Mitogen-activated protein kinase kinase kinase 2
4.82E-03
7.83E-03
1.8
MAP4K5
Mitogen-activated protein kinase kinase kinase 5
1.31E-02
1.50E-02
1.9
MAPK8
Mitogen-activated protein kinase 8
1.42E-02
1.54E-02
2.0
NAGK
N-acetylglucosamine kinase
4.16E-03
7.83E-03
1.8
PALM2-AKAP2
A kinase (PRKA) anchor protein 2
2.31E-02
2.37E-02
1.9
PANK2
Pantothenate kinase 2
6.39E-04
2.67E-03
1.6
PAPSS1
3'-phosphoadenosine 5'-phosphosulfate synthase 1
2.35E-04
1.67E-03
1.8
PDLIM5
PDZ and LIM domain 5
8.94E-03
1.09E-02
1.9
PFTK1
PFTAIRE protein kinase 1
4.74E-03
7.83E-03
1.6
PGAM1
Phosphoglycerate mutase 1 (brain)
4.81E-04
2.35E-03
1.6
PI4K2B
Phosphatidylinositol 4-kinase type 2 beta
7.80E-03
1.02E-02
1.7
PIK3C2A
Phosphoinositide-3-kinase, class 2, alpha
2.28E-02
2.37E-02
1.5
PIP4K2A
Phosphatidylinositol-5-phosphate 4-kinase, Iia
7.52E-04
2.67E-03
1.5
PRKAA1
Protein kinase, AMP-activated, alpha 1
5.32E-02
5.32E-02
1.7
PRKD1
Protein kinase D1
7.86E-03
1.02E-02
1.8
PTK9
Twinfilin, actin-binding protein, homolog 1
1.62E-04
1.67E-03
1.7
RIPK2
Receptor-interacting serine-threonine kinase 2
1.84E-03
5.11E-03
1.6
RIPK5
Receptor interacting protein kinase 5
5.91E-03
8.53E-03
1.7
SGMS2
Sphingomyelin synthase 2
3.38E-03
7.76E-03
2.3
SHC1
Src homology 2 domain containing protein 1
2.99E-04
1.67E-03
1.7
SOCS3
Suppressor of cytokine signaling 3
3.07E-03
7.48E-03
1.7
SSA2
TROVE domain family, member 2
2.72E-04
1.67E-03
1.6
TAOK1
TAO kinase 1
1.51E-04
1.67E-03
1.7
TRIM27
Tripartite motif-containing 27
6.94E-04
2.67E-03
1.6
TTN
Titin
6.67E-03
9.29E-03
0.2

Discussion

We have evaluated gene expression and histological changes associated with human tendinopathy. While gene expression changes in human tendinopathy have previously been described [13, 22, 23], this study represents the largest and most complete study to date. However, our study has several limitations. First, control tendons were taken from the same joints as the diseased tendons. These control tendons appeared normal macroscopically but their proximity to the diseased tendon may have some effect on the control tendon. Furthermore, the control tendon was an anatomically distinct tendon exposed to different loads and strains and it is not known how this may affect the gene expression profile. Moreover, the tendon specimens were collected from a heterogeneous population with differences in age, gender, symptoms, duration of disease, and physical activity (Table 1). While changes in gene expression were not related to any of these differences, they all contribute to variations in the data. Given the vast variation in the human population, we reasoned that control samples from the same patients would be a better control for interpatient variability than tendons from control patients without any tendon symptoms.
Progression of tendinopathy is dependent on extracellular matrix integrity and remodeling of the tendon is a common feature of tendinopathy [24]. The extracellular matrix of normal tendons consists of many of structural proteins (collagens) and proteoglycans. Collagen is the main component of tendons and type I collagens account for 65% to 80% of the total tendon mass [25]. mRNA levels for type I and type III collagens (COL1A1, COL1A2, and COL3A1) were increased in the diseased tendons. Tendons also contain several proteoglycans, although none of the proteoglycans analyzed (including aggrecan, versican, decorin, biglycan, fibromodulin, and lumican) showed increased expression in diseased tendons. In contrast, expression of the non-collagen glycoproteins fibronectin, tenascin C, fibrillin, and laminin was increased in diseased tendons. Consistent with active remodeling, increased MMP activity, particularly of MMP2 and MMP9, has been associated with ruptured Achilles tendon [26]. Diseased tendons showed increased expression of several matrix associated proteins including MMP19, MMP9, MMP13, MMP14, and MMP2. In contrast, MMP3 expression was decreased in tendinopathy in both our study and in others [13, 22].
We can begin to speculate how MMP activity is regulated in tendinopathy tissue. Diseased tissues showed increased expression of components of the JAK/STAT pathway (STAT3, 1.9-fold, and JAK3, 1.8-fold). The JAK/STAT pathway is known to activate IL4R [27], which induces expression of IL13RA2 [28]. Expression of both IL4R and IL13RA2 was elevated in diseased tissue (3.2- and 3.5-fold, respectively). IL13, secreted by T helper type 2 cells, has anti-inflammatory properties and through interaction with its receptor IL13RA2 induces certain MMPs [29] including MMP9 and MMP14 [30]. Together, these findings suggest that activation of the JAK/STAT pathway may lead to increased MMP activation.
Chard et al. previously suggested that tendon pathology is linked to formation of excessive fibrocartilage [31]; however, other prior studies [22] and our current study found little evidence of chondrocyte-like cells. Tendinopathy tissue showed decreased expression of a number of cartilage markers including COMP, but expression of other cartilage markers such as aggrecan was not altered. In contrast, expression of type I collagen was increased, further supporting the absence of increased chondrocytic cells in diseased tendons. This is in contrast to an overuse animal model of tendinopathy [32, 33] that suggested increased formation of fibrocartilage associated with overuse. This discrepancy can possibly be explained by differences in disease severity. The human samples were collected during surgery following tendon tear or rupture and represent late stage disease in which surgical intervention became necessary, while the animal models represent earlier development of disease. Furthermore, the human tendon samples represent small biopsies, mostly from the midsubstance. One might expect any increase in fibrocartilage to occur near the bone insertion site, an area from which samples were not collected.
Global pathway analysis identified novel pathways that are differentially regulated in human tendinopathy including regulation of genes involved in WNT signaling. Tendinopathy is characterized by increased cellular infiltration and proliferation. Increases in WNT signaling can promote proliferation and maintain cells in an undifferentiated state [34] and the regulation of multiple WNT signaling genes suggests that this pathway is activated in tendinopathy. Pathway analysis also suggested an increased regulation of genes involved in integrin signaling. Integrins are receptors involved in cell adhesion to the extracellular matrix and transmit extracellular signals into the cell to regulate gene expression. While many of the genes encoding integrins were only slightly upregulated, expression of integrin beta 1 (fibronectin receptor) was significantly increased in tendinopathy tissue.
We found little direct evidence to support an inflammatory response in established human tendinopathy. Histological evaluation did not identify a significant number of inflammatory cells and analysis of the gene expression of inflammatory cytokines identified only a handful of cytokine genes that were differentially regulated in diseased tendons, although a number of these are implicated in tendon function and tendon healing. Expression of the proinflammatory cytokine IL17D was reduced in diseased tendons. IL17 increases the turnover of type I collagen through both inhibiting its synthesis and promoting its breakdown [35], and members of the IL17 cytokine family members are inhibitors of human hematopoietic progenitor proliferation [36]. The oncostatin M receptor was significantly upregulated in diseased tendons. Oncostatin M contributes to the release of proteoglycans and the breakdown of collagens [37]. IL6 is a pro-inflammatory cytokine important for tendon healing; lack of IL6 prevents proper tendon healing [38]. Evidence for aberrant regulation of the IL6 pathway in damaged tendons includes decreased expression of the IL6 receptor. IL6 can also signal through STAT3, which was upregulated in diseased tendons. STAT3 expression has also been identified in ruptured rotator cuff. However, activation of STAT3 is mainly induced by proliferating vessels [39], and since diseased tendons have increased vasculature, many of the observed changes in cytokine expression may simply be due to this change in vasculature. Therefore, whether these cytokines play a direct role in tendonopathy requires further study. In addition to the lack of evidence for direct regulation of many pro-inflammatory cytokines, there is also indirect evidence for the absence of inflammatory cytokine activity. The lack of expression of MMP1 and MMP13, which are known to be induced by inflammatory cytokines [40], further supports the proposal that pro-inflammatory cytokines do not play a major role in tendinopathy at this late stage of disease.

Conclusions

In this paper we describe the global transcriptome of human tendinopathy. Although we have identified a number of genes that are differentially regulated, the ultimate roles of these genes and pathways in tendon disease are yet to be determined. However, we have provided a resource that we and other investigators can use to explore the molecular changes associated with tendinopathy.

Acknowledgements

Some authors were employed by Wyeth Research at the time of the research. The authors wish to thank Christine Huard and Ying Zhang for microarray processing and Katy Wallace and Donna Gavin for histology processing.
This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://​creativecommons.​org/​licenses/​by/​2.​0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Competing interests

Howard Seeherman, Jian Li, Joanne Archambault and Scott Jelinsky were employed by Wyeth Research/Pfizer at the time of this research. Scott A Rodeo received research funding from Wyeth at the time of this study.

Authors' contributions

HJS, JMA and SAR worked on the study design. SAR recruited patients and collected the samples. LVG wrote the IRB and informed consents and help collect the samples. JL performed the histology analysis. SAJ performed the microarray analysis and drafted the manuscript. All authors have read and approved the final manuscript.
Anhänge

Authors’ original submitted files for images

Below are the links to the authors’ original submitted files for images.
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Metadaten
Titel
Regulation of gene expression in human tendinopathy
verfasst von
Scott A Jelinsky
Scott A Rodeo
Jian Li
Lawrence V Gulotta
Joanne M Archambault
Howard J Seeherman
Publikationsdatum
01.12.2011
Verlag
BioMed Central
Erschienen in
BMC Musculoskeletal Disorders / Ausgabe 1/2011
Elektronische ISSN: 1471-2474
DOI
https://doi.org/10.1186/1471-2474-12-86

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