BioMed Research International

BioMed Research International / 2011 / Article

Research Article | Open Access

Volume 2011 |Article ID 920763 |

Guorong Gu, Weizhong Cheng, Chenling Yao, Jun Yin, Chaoyang Tong, Andrew Rao, Lawrence Yen, Matthew Ku, Jianyu Rao, "Quantitative Proteomics Analysis by Isobaric Tags for Relative and Absolute Quantitation Identified Lumican as a Potential Marker for Acute Aortic Dissection", BioMed Research International, vol. 2011, Article ID 920763, 10 pages, 2011.

Quantitative Proteomics Analysis by Isobaric Tags for Relative and Absolute Quantitation Identified Lumican as a Potential Marker for Acute Aortic Dissection

Academic Editor: Saulius Butenas
Received06 Sep 2011
Revised27 Oct 2011
Accepted27 Oct 2011
Published20 Dec 2011


Acute aortic dissection (AAD) is a serious vascular disease. Currently the diagnosis relies on clinical and radiological means whereas serum biomarkers are lacking. The purpose of this study was to identify potential serum biomarkers for AAD using isobaric tags for relative and absolute quantitation (iTRAQ) approach. A total of 120 serum samples were collected from three groups: AAD patients ( ), patients with acute myocardial infarction (AMI, ), and healthy volunteers ( ), whereas the first 10 samples from each group were used for iTRAQ analysis. Using iTRAQ approach, a total of 174 proteins were identified as significantly different between AAD patients and healthy subjects. Among them, forty-six proteins increased more than twofold, full-scale analysis using serum sample for the entire 120 subjects demonstrated that Lumican level was significantly increased relative to control and AMI samples. Further, Lumican level correlated with time from onset to admission in AAD but not AMI samples. Using iTRAQ approach, our study showed that Lumican may be a potential AAD-related serum marker that may assist the diagnosis of AAD.

1. Introduction

Acute aortic dissection (AAD) has become a treatable disease due to recent advances in new therapeutic approaches for the management of heart and arterial diseases; however, development of quick and economic diagnostic methods remains a challenge. Variability in disease presentation often obscures diagnoses, and imaging modalities such as computed tomography (CT), magnetic resonance imaging (MRI), and esophagus ultrasound remain prohibitive due to cost and availability. Aortic dissection remains a frequent target of medicolegal litigations with accusations of failure to diagnose against treating physicians and hospitals [1]. Some progress in the biochemical diagnosis of AAD has been made in the last decade [2, 3]; several acute phase proteins and coagulation parameters were identified to increase in AAD patients, but these are nonspecific biomarkers for AAD as they may be also aberrantly expressed in other disease conditions such as acute myocardial infarction (AMI).

Recently a quantitative proteomic assay, isobaric tags for relative and absolute quantitation (iTRAQ), has been developed and utilized to identify biomarkers for various disease conditions [4, 5]. This chemical labeling method involves the stable incorporation of isotopes into an amine tagging reagent, which can then be reliably detected by mass spectrometry, thereby permitting comparative quantitation of various proteins in a multiplex manner. It has been suggested to be suitable for the discovery of biomarkers in a wide range of body fluids and tissues, including serum and plasma [5, 6]. With this method, we expect to find the potential biomarkers which are released from the disruption of the aortic media and can provide sufficient specificity and longer time window for the diagnosis of AAD.

2. Materials and Methods

2.1. Samples

The study included a total of 30 healthy individuals and 90 patients (60 AAD, 30 AMI). All the patients were selected in a consecutive manner from the period of July 2009 to November 2011 from Fudan University affiliated Zhongshan Hospital (Shanghai, China). iTRAQ analysis was performed for the first twenty patients (10 AAD and 10 AMI) and ten healthy individuals. All patients presented within 72 hours after an episode of chest and/or back pain lasting 5 minutes or more. The diagnosis of AAD was confirmed by computed tomographic arteriography (CTA). The AMI patient was confirmed by electrocardiography (ECG) and cardiac troponin T (cTNT) tests. All patients gave their informed consent for the study. The protocol was approved by the Ethics Committee of Zhongshan Hospital.

For each study subject, whole blood samples were immediately collected in BD Vacutainer SST tubes (BD Diagnostics, Plymouth, UK) after admission and centrifuged at 4000 rpm for 10 min at room temperature. The serum was frozen and stored in aliquots at −80°C until analysis.

2.2. Serum C-Reactive Protein and Myoglobin Test

Vitros 5.1 FS automatic biochemistry analyzer (Johnson & Johnson; Calif, USA) was used for serum C-reactive protein (CRP) test, and Cobas e411 immunoassay analyzer (Roche; Mannheim, Germany) was used for the serum myoglobin (Myo) test. The results were then interpreted in accordance with that tested by the International Federation of Clinical Chemistry (IFCC) recommended method. Analyses were performed immediately after the centrifugation of whole blood samples.

2.3. iTRAQ Sample Preparation: Strong Cation Exchange (SCX) Chromatography

iTRAQ reagents were purchased from Applied Biosystems (Foster City, USA). Fourteen interfering highly abundant proteins from serum samples were removed using Agilent multiple affinity removal liquid chromatography (LC) column-Human 14 (MARS) (shimadzu, Kyoto, Japan). One hundred micrograms of each extract were precipitated using acetone at −20°C and suspended in 20 μL of dissolution buffer (Applied Biosystems, Foster City, USA). After reduction and alkylation, each sample was digested with trypsin (w(trypsin) : w(protein) = 1 : 20) at 37°C overnight. The tryptic peptides were labeled with the iTRAQ reagents as follows: normal controls group was labeled with iTRAQ 113, AMI group was labeled with iTRAQ 114, and AAD group was labeled with iTRAQ 115. The peptides were pooled and desalted with Sep-Pak Vac C18 (Waters, Milford, USA). The peptide mixture was diluted with buffer A containing 10 mM KH2PO4 in 25% acetonitrile (ACN) at pH 2.6. The peptides were fractionated by 20AD high-performance liquid chromatography (HPLC) system (Shimadzu; Kyoto, Japan) equipped with a polysulfoethyl A column (2.1 mm × 100 mm, 5u, 200 A; The Nest Group, Southborough, Mass). The composition of buffer B was 350 mM KCl, 10 mM KH2PO4, and 25% ACN at pH 2.6. Separation was performed using a linear binary gradient of 0–80% buffer B in buffer A at a flow rate of 200 μL/min for 60 min. The fractions were combined into 20 groups.

2.4. LC-MS Analysis

Each SCX fraction was dried down by the rotary vacuum concentrator, dissolved in buffer C (0.1% formic acid, 5% ACN, 95% water), and analyzed on Qstar XL (Applied Biosystems; Foster City, USA). The HPLC gradient was 5–35% buffer D (95% ACN, 0.1% formic acid) in buffer C at a flow rate of 300 nL/min for 70 min. Analysis survey scans were acquired MS from m/z 400–1800 with up to 4 precursors selected for MS/MS from m/z 100–2000.

2.5. The Confirmative ELISA Analysis for Lumican

The confirmative ELISA analysis for Lumican was performed using the kits from CUSABIO BIOTECH CO, following manufacture’s recommendation (CUSABIO BIOTECH CO., LTD., Wuhan, China).

2.6. Data Analysis

All statistical analyses were performed in SPSS 12.0 (SPSS Inc. Chicago, USA). Results were presented as Mean ± SD. A comparative analysis of multiple groups was performed with a one-way-ANOVA or Mann-Whitney/Kruskal-Wallis Test. Statistical significance was defined as . Peptide and protein identification was performed by searching the MS/MS spectra against the SwissProt database using the local Protein Pilot 2.0.1 software. Only peptides identified with confidence interval values of no less than 95% (Unused ProtScore >1.3) were used for protein identification compilation and subsequent quantitation calculation. Fold changes of >2 or <0.5 were set as cut-off values to designate significant differences in protein expression among the AAD group and the normal control group.

2.7. PANTHER Analysis

The PANTHER database was used to elucidate cellular components, biological processes, and the molecular functions associated with each individual protein (

3. Results

3.1. Clinical Features of Study Subjects

The clinical features of the AAD patients, AMI patients, and normal controls are summarized in Table 1. There were no differences in age distribution and sex composition among the three groups involved either for ELISA analysis ( ) ( and 0.378, resp.,) or iTRAQ analysis ( and 0.873, resp.). There was no differences in the time from onset to admission between AAD and AMI group either ( ).

AADAMINormal controls value

ELISA test ( )Age (Mean ± SD) 0.351a
Gender, (%), male30 (50)17 (56.67)16 (53.33)0.378b
Admission after onset hours (Mean ± SD) /0.776c
Type A (%)31 (51.67)//
Type B (%)29 (48.33)//
Marfan (%)7 (11.67)//


iTRAQ test ( )Age (Mean ± SD) 0.241a
Gender, (%), male6 (60)6 (60)5 (50)0.873b
Admission after onset hours (Mean ± SD) /0.363c
Type A (%)5 (50)//
Type B (%)5 (50)//
Marfan (%)2 (20)//

a One-way-ANOVA; bChi-square Test; cMann-Whitney Test.
3.2. Functional Classification of Identified Proteins by iTRAQ

A total of 174 proteins with confidence interval values of no less than 95% were identified (Unused ProtScore > 1.3). However, after manually rechecking the MS/MS data thoroughly peak by peak, 155 proteins (89.08%) had a relative quantitation of one or more peptides. Fifteen proteins had no quantifiable peptides that could be ascertained, and four proteins had peptides with confidence interval values that were less than 95%.

In total, 174 proteins were sorted using the PANTHER classification system, which sorts the proteins into respective categories based on their molecular functions. The major groups include: signaling molecules (13%), enzyme modulators (12%), transfer/carrier proteins (11%), and proteases (10%). Other groups include: structural proteins (1%), cell adhesion molecules (1%), cytoskeletal proteins (3%), extracellular matrix proteins (2%), and cell junction proteins (1%).

As a way to cross-check the reliability of quantitation of iTRAQ reagent, serum CRP and Myo levels were assessed using both conventional biochemical and immunoassay tests and iTRAQ analysis on the same specimens. With biochemical and immunoassay analysis, CRP was 41.31 ± 32.76 mg/mL and Myo was 66.42 ± 81.23 mg/mL in AAD group, while in normal controls, the former was 5.88 ± 1.42 and the latter was 32.07 ± 14.14 mg/mL. CRP and Myo levels of AAD patients were 7.03-fold and 2.07-fold higher, respectively, than normal controls. Using iTRAQ, the AAD/normal controls ratios of CRP and Myo were similar at 9.12-fold (Table 2) and 1.47-fold. The ratios of CRP and Myo among three groups were similar with either biochemical and immunoassay or iTRAQ analysis, confirming the reliability of iTRAQ analysis.

NUnusedaPeptidesbAccession #NameBiological processCellular componentProtein classAAD/CON ratioAAD/AMI ratio

12.71Q13509Tubulin beta-3 chainCellular component morphogenesisCytoskeleltonCytoskeletal protein/tubulin39.84060.0711
221P01600Ig kappa chain V-I region HauUnclassified31.34803.0760
36.673P02743Serum amyloid P-componentResponse to stressDefense/immunity protein/antibacterial response24.44999.1241
413.5310P05546Heparin cofactor 2Protein metabolic processEnzyme modulator19.762811.2740
517.679P36955Pigment epithelium-derived factorProtein metabolic processEnzyme modulator19.76289.8135
66.244P05543Thyroxine-binding globulinProtein metabolic processEnzyme modulator12.70653.7665
712.6318P01834Ig kappa chain C regionResponse to stimulusImmunoglobulin complexDefense/immunity protein11.69591.8031
855.1443P02751FibronectinBlood coagulationExtracellular matrixTransfer/carrier protein11.58753.7327
935.9429P01011Alpha-1-antichymotrypsinProtein metabolic processEnzyme modulator10.57088.0906
102.221P02741C-reactive proteinResponse to stressDefense/immunity protein9.12415.9701
1121Q9UK55Protein Z-dependent protease inhibitorProtein metabolic processEnzyme modulator8.78732.4888
12100.7851P04114Apolipoprotein B-100Lipid metabolic processTransfer/carrier protein8.62812.8050
139.194P35858Insulin-like growth factor-binding protein complex acid labile chainCell-cell adhesionExtracellular matrixReceptor8.47464.0177
1447.8842P19827Inter-alpha-trypsin inhibitor heavy chain H1Protein metabolic processEnzyme modulator5.80725.6497
15106.7289P00450CeruloplasminBlood coagulationExtracellular matrixTransporter5.10469.6339
1637.5623P04196Histidine-rich glycoproteinBlood coagulationUnclassified4.61253.2206
174.152P08571Monocyte differentiation antigen CD14Immune system processReceptor4.09332.4888
182.721Q96KN2Beta-Ala-His dipeptidaseProtein metabolic processProtease4.09331.9231
1931.6620P01871Ig mu chain C regionResponse to stimulusDefense/immunity protein3.80232.3552
2012.126P51884LumicanCell-cell adhesionExtracellular matrixReceptor3.63111.2942
212.711P00740Coagulation factor IXBlood coagulationProtease3.40372.0137
226.273P08185Corticosteroid-binding globulinProtein metabolic processEnzyme modulator3.28085.4945
232.5821P00739Haptoglobin-related proteinUnclassified3.22061.7538
244.984P04003C4b-binding protein alpha chainBlood coagulationTransfer/carrier protein3.16265.0582
256.026P02745Complement C1q subcomponent subunit AResponse to stimulusTransfer/carrier protein3.10463.6982
265.833P22792Carboxypeptidase N subunit 2Cell adhesionExtracellular matrixReceptor3.02021.3805
2715.9911P05155Plasma protease C1 inhibitorProtein metabolic processEnzyme modulator2.96471.2824
282.022P01742Ig heavy chain V-I region EUUnclassified2.85801.1695
2921P09486SPARCCell-cell signalingTransfer/carrier protein2.70420.7312
3018.069P02760Protein AMBPBlood coagulationEnzyme modulator2.60623.5651
318.995P12259Coagulation factor VBlood coagulationExtracellular matrixTransporter2.60623.2206
328.316P27169Serum paraoxonase/arylesterase 1Immune system processOxidoreductase2.53495.6497
332.321P19320Vascular cell adhesion protein 1Cell-cell adhesionDefense/immunity protein2.31212.1478
342.011O00187Mannan-binding lectin serine protease 2Response to stimulusProtease2.31211.5277
3543.1929P02749Beta-2-glycoprotein 1Blood coagulationTransfer/carrier protein2.22877.1124
363.522P11226Mannose-binding protein CResponse to stimulusDefense/immunity protein2.20802.6062
3787.9367P00738HaptoglobinBlood coagulationProtease2.16783.5651
385.74Q13790Apolipoprotein FLipid metabolic processTransporter2.14783.9448
3965.4241P02790HemopexinVitamin transportTransfer/carrier protein2.14783.9078
402.961P20851C4b-binding protein beta chainBlood coagulationTransfer/carrier protein2.12814.8309
4121P61769Beta-2-microglobulinResponse to stimulusDefense/immunity protein2.10882.1281
4220.8610P02748Complement component C9Response to stimulusReceptor2.10880.6252
436.963P07477Trypsin-1Protein metabolic processProtease2.10880.3436
4413.647P05156Complement factor IResponse to stimulusProtease2.03250.9120
4515.1710P01842Ig lambda chain C regionsResponse to stimulusImmunoglobulin complexDefense/immunity protein2.01372.1678
464.291P35030Trypsin-3Protein metabolic processProtease2.01371.3931

a Unused > 1.3 means at least 95% confidence; bnumber of peptides with 95% confidence; AAD: acute aortic dissection; AMI: acute myocardial infarction; CON: normal controls.
3.3. Proteins with Over Twofold Differential Expression

A total of 155 proteins had a relative quantitation difference for AAD patients compared with the normal control group of which 46 proteins increased more than twofold (Table 2), while 36 proteins decreased more than twofold among the AAD patients (Table 3). Among the identified proteins with increased levels in AAD, there were a number of acute phase reactants (CRP, Beta-2-microglobulin, Complement factor I), blood coagulation marker (Haptoglobin, Coagulation factor V, Coagulation factor IX), and cellular components (Lumican, Tubulin beta-3 chain, Fibronectin). However when compared to AMI patients, 14 of the 46 protein showed less than 2-fold increase, including complement component 9, complement factor1, Plasma protein C1 inhibitor, and Ig Kappa chain C-region (Table 2). Interestingly, some acute phase proteins such as CRP remains on the list as it showed the differential expression between the two conditions.

NUnusedaPeptidesbAccession #NameBiological processCellular componentProtein classificationAAD/CON ratioAAD/AMI ratio

119.3117P02775Platelet basic proteinBlood coagulationTransfer/carrier protein0.02090.0398
244.631P02671Fibrinogen alpha chainBlood coagulationExtracellular matrixTransfer/carrier protein0.03700.0203
319.8230P02656Apolipoprotein C-IIILipid metabolic processTransporter0.05700.0240
45.75P01717Ig lambda chain V-IV region HilUnclassified0.06550.0679
58.454P02768Serum albuminTransportTransfer/carrier protein0.07240.8472
63.221P04264Keratin, type II cytoskeletal 1Cellular component morphogenesisCytoskeleltonStructural protein0.07800.9639
72.051P04070Vitamin K-dependent protein CBlood coagulationProtease0.07940.0441
834.9827P02652Apolipoprotein A-IILipid metabolic processTransporter0.09910.1067
920.310P02654Apolipoprotein C-ILipid metabolic processTransporter0.11590.0847
1094.94108P02765Alpha-2-HS-glycoproteinProtein metabolic processExtracellular matrixExtracellular matrix protein0.11800.1472
1139.0725P01008Antithrombin-IIIProtein metabolic processEnzyme modulator0.12020.0973
1272.6957P00734ProthrombinBlood coagulationEnzyme modulator0.12250.2051
136.883P27918ProperdinResponse to stimulusUnclassified0.14190.1905
146.314P69905Hemoglobin subunit alphaBlood circulationTransfer/carrier protein0.15000.2312
158.9715Q03591Complement factor H-related protein 1Blood coagulationTransfer/carrier protein0.17060.0991
1721Q15942ZyxinCellular component morphogenesisEnzyme modulator0.19230.2109
1820.426P01024Complement C3Protein metabolic processTransfer/carrier protein0.20700.1406
197.433P17936Insulin-like growth factor-binding protein 3Cell-matrix adhesionUnclassified0.20890.3162
202.232P55290Cadherin-13Cell-cell adhesionCell junctionReceptor0.21880.1660
211.411P13598Intercellular adhesion molecule 2Cell-cell adhesionTransfer/carrier protein0.23550.1600
2296.2464P00751Complement factor BBlood coagulationTransfer/carrier protein0.24660.2729
2328.8216P09871Complement C1s subcomponentBlood coagulationProtease0.26060.4169
2413.749P01019AngiotensinogenProtein metabolic processEnzyme modulator0.26300.5058
2595.3474P19823Inter-alpha-trypsin inhibitor heavy chain H2Protein metabolic processEnzyme modulator0.28050.5649
265.152P18065Insulin-like growth factor-binding protein 2Cell-matrix adhesionUnclassified0.28840.3281
2716.8410P07996Thrombospondin-1Blood coagulationExtracellular matrixTransfer/carrier protein0.34040.8317
285.313P26927Hepatocyte growth factor-like proteinBlood coagulationTransfer/carrier protein0.34360.3436
297.854O14791Apolipoprotein L1Lipid metabolic processTransporter0.39080.2831
3094.7657P06727Apolipoprotein A-IVLipid metabolic processTransporter0.40180.1837
3114.19P35527Keratin, type I cytoskeletal 9Cellular component morphogenesisStructural protein0.40550.7244
329.486P00746Complement factor DBlood coagulationProtease0.45710.6668
3348.0924P02649Apolipoprotein ELipid metabolic processTransporter0.46560.2051
3438.832P02735Serum amyloid A proteinImmune system processTransporter0.47420.0319
359.465P10720Platelet factor 4 variantBlood coagulationTransfer/carrier protein0.47420.5105
3653.3129P02774Vitamin D-binding proteinTransportTransfer/carrier protein0.48312.2287

a Unused > 1.3 means at least 95% confidence; bnumber of peptides with 95% confidence; AAD: acute aortic dissection; AMI: acute myocardial infarction; CON: normal control.

Among proteins with decreased expression in AAD patients compared with normal controls, there were a number of molecules involved in protein metabolism (Inter-alpha-trypsin inhibitor heavy chain H2, Alpha-2-HS-glycoprotein), lipid metabolic process (Apolipoprotein A-IV, Apolipoprotein E, Apolipoprotein C-I), blood coagulation marker (Fibrinogen alpha chain, Prothrombin), and cellular components (Alpha-2-HS-glycoprotein, thrombospondin-1 (TSP-1)). When compared to AMI patients, 8 of 36 proteins did not reach the 2-fold differential expression (Table 3).

3.4. The ELISA Analysis of Serum Concentrations of Lumican

Based on the iTRAQ findings above we selected two targets, Fibronectin and Lumican, the protein markers potentially associated with vascular injury, for the validation using ELISA method. At the initial analysis using 10 AAD and 10 normal samples we found that statistical significant difference between AAD and normal individual was seen for Lumican but not Fibronectin (data not shown). Therefore, we carried a full validation study only for Lumican, using the entire 120 samples collected (see Table 1). A statistical significant difference between AAD, AMI, and normal individual was seen in serum concentrations of Lumican (2.66 ± 4.58 ng/mL in AAD group, 0.69 ± 0.34 ng/mL in AMI group, and 0.85 ± 0.53 ng/mL in normal control, ). The difference for AAD and AMI also reached statistical significance ( ) suggesting the specificity of this marker for AAD (Figure 1). We further analyzed the correlation between Lumican levels with time from onset of symptoms to admission. As shown in Figure 2, a correlation was seen in AAD group ( , ) but not in AMI group ( , ), further confirming the specificity of Lumican as a marker for AAD.

4. Discussion

iTRAQ analysis is recently been used as a potentially more effective biomarker discovery method than traditional proteomic methods. The high reproducibility optimizes this technique for embarking on “fishing-expeditions” as an initial screening for potential useful biomarkers [68]. As a means of internal validation, the iTRAQ method was compared with CRP biochemical assay and Myo immunoassay. In our study there were no significant differences in the serum levels determined by the different methods. Thus, the iTRAQ method we employed appears in this preliminary analysis to be suitable for the detection of relevant proteins.

To identify differentially expressed proteins, in many studies, the cut-off points were set at 20% to 50% average variance [7, 9, 10]. However, such approaches may result in finding markers with low specificity [2, 3]. We therefore appropriated to increase the cut-off point at 100% variance in serum levels of candidate proteins between AAD patients and normal subjects. Thus, only twofold changes below or above normal controls were considered significant. In our study, total of 155 proteins had a relative difference between AAD patients and healthy volunteers. Therefore, with higher specificity, these candidate proteins are more likely to be potential biomarkers for AAD.

In the group of significantly increased proteins, there were numerous acute phase reactants, such as Beta-2-microglobulin (P61769), which could be indicative of an increased inflammatory response among AAD patients. CRP (P02741), a protein found to be elevated in patients who presented with symptoms or rupture of AAD and abdominal aortic aneurysm, was also identified using iTRAQ [11, 12]. CRP is a nonspecific biomarker associated with AAD and a predictor for long-term adverse events [13], and it can be used to monitor evolution of false lumen thrombosis [14]. Unfortunately, CRP is also produced in coronary plaques [15], acute myocardial infarction [16], and so forth. The elevations of these acute phase reactants represent a generalized reaction to vascular injury, and as such, they are nonspecific biomarkers. In addition, many proteins identified are associated with blood coagulation and fibrinolytic system. Among which, ten had increased serum levels (e.g., P00450-Ceruloplasmin, P02751-Fibronectin, P00738-Haptoglobin…), and twelve had decreased serum levels (e.g., P02671-Fibrinogen alpha chain, P00751-Complement factor B, P00734-Prothrombin…). The pathophysiological mechanism for the appearance of these proteins may be explained by the release of tissue factors from the dissected aortic wall then the activation of the extrinsic coagulation system [1719]. In addition, platelets can be activated by injuries to the vessel wall, activation of the coagulation cascade, or by activating factors released from stimulated endothelial cells and platelets (e.g., ADP, thromboxane, von Willebrand Factor). It also has been found that platelet functions were affected secondary to acute massive consumption coagulopathy in the false lumen in AAD patient [20, 21].

In the past few years, extracellular matrix (ECM) components of vessel walls such as elastin have been shown to be elevated in aortic dissections; however, such increases were less than twofold [3]. Our study found 9 extracellular matrix component proteins with greater than twofold differences, among these are Carboxypeptidase (P22792), Lumican (P51884), Fibronectin (P02751), Ceruloplasmin (P00450), and Thrombospondin-1 (TSP-1, P07996). Fibronectin is a polymorphic and multifunctional glycoprotein that plays wide-ranging roles in tissue injury [2225]. TSP-1, which is an extracellular protein that participates in cell-to-cell and cell-to-matrix communication, can stimulate or inhibit the migration of vascular smooth muscle cells or endothelial cells. It has been known as a plasma marker of peripheral arterial disease [26].

Lumican is distributed in interstitial collagenous matrices throughout the body. In coronary arteries ischemic lesion, it is overexpressed by vascular smooth muscle cells (VSMCs) [27] and also synthesized in aortic smooth muscle cells [28]. In iTRAQ analysis, serum Lumican levels in patients with AAD were 1.29-fold and 3.63-fold higher than in patients with AMI and normal controls, respectively. It is interesting to note that with iTRAQ analysis, the level of difference between AAD and AMI for Lumican is less than that of Fibronectin (Table 2), yet the initial validation using ELISA method showed that only Lumican was significantly increased in AAD and AMI samples. While there may be variety reasons to explain the variations of the findings between the two methods, it highlights the importance of validation in biomarker studies. The finding that Lumican expression correlated with the time from onset to admission only in AAD but not in AMI sample further confirmed the specificity of this protein in association with AAD.

Proteomic approach provides an exciting platform to identify clinically useful protein biomarkers. As an initial step our study identified potential candidate protein biomarkers in the serum of AAD patients with the iTRAQ technique. However, the ultimate development of biomarkers which provide sufficient sensitivity or specificity for the diagnosis of AAD will require multiple validations and clinical testing, which may include nonprotein markers. Nevertheless our findings provide preliminary list of candidate biomarkers that should be further validated, either alone or in combination.

5. Conclusion

In this paper, we found that iTRAQ technique is a suitable approach for the detection of the new potential protein markers in the serum of AAD patients. Using iTRAQ approach, our study identified that Lumican may be a potentially interesting new serum marker of AAD, and upon further validation this marker may assist the clinical diagnosis of AAD.


This study was supported by Shanghai Committee of Science and Technology (114119a9000). The authors also thank the Department of Chemistry and the Institute of Biomedical Science, Fudan University, Peoples Republic of China, for providing support for the project.


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Copyright © 2011 Guorong Gu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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