BioMed Research International

BioMed Research International / 2014 / Article

Review Article | Open Access

Volume 2014 |Article ID 569632 | 15 pages | https://doi.org/10.1155/2014/569632

The Landscape of Protein Biomarkers Proposed for Periodontal Disease: Markers with Functional Meaning

Academic Editor: Wuyuan Lu
Received06 Feb 2014
Accepted07 Apr 2014
Published26 Jun 2014

Abstract

Periodontal disease (PD) is characterized by a deregulated inflammatory response which fails to resolve, activating bone resorption. The identification of the proteomes associated with PD has fuelled biomarker proposals; nevertheless, many questions remain. Biomarker selection should favour molecules representing an event which occurs throughout the disease progress. The analysis of proteome results and the information available for each protein, including its functional role, was accomplished using the OralOme database. The integrated analysis of this information ascertains if the suggested proteins reflect the cell and/or molecular mechanisms underlying the different forms of periodontal disease. The evaluation of the proteins present/absent or with very different concentrations in the proteome of each disease state was used for the identification of the mechanisms shared by different PD variants or specific to such state. The information presented is relevant for the adequate design of biomarker panels for PD. Furthermore, it will open new perspectives and help envisage future studies targeted to unveil the functional role of specific proteins and help clarify the deregulation process in the PD inflammatory response.

1. Introduction

The different forms of periodontal disease (PD) share four stages: (i) bacterial biofilm presence and accumulation in the gingival sulcus (colonization), (ii) bacterial penetration of epithelium and connective tissue in the gingiva adjacent to the tooth surface (invasion), (iii) stimulation of a host response involving activation of the innate and acquired immune response (inflammation), and (iv) irreversible destruction of connective tissue attachment to the tooth surface and bone (tissue loss) [1].

Gingival epithelial cells and fibroblasts in PD respond to Gram-negative bacterial lipopolysaccharide (LPS) by the transient expression of cytokines playing an active role in the initiation and maintenance of gingival inflammation [2]. The next line of defence comes with neutrophils that, under microbiota continuous stimulation, exhibit prosurvival and hyperresponsive behaviours [3, 4]. Periodontitis is also characterized by abundant monocyte infiltration, which finds the adequate signalling microenvironment to rapidly differentiate into macrophages, namely, through surface toll-like receptors [5]. Like neutrophils, macrophages phagocytose periodontal pathogens and additionally orchestrate wound repair by functionally coordinating innate and adaptive immune responses. This is achieved by the production of specific cytokines and chemokines which contribute to the attraction and activation of subsets of T cells. Of the multiple types of CD4+ T cells (Th1 Th2, Th17, and Tregs), Th2 cells are thought to dominate over an initial Th1 response in progressive periodontitis [6]. The different T cell subsets may participate in osteoclastogenesis process through RANKL production or the expression of another osteoclastogenic cytokine, the IL-17, accomplished by Th17 cells [7]. In spite of this knowledge, there is not solid evidence on the specific role of T cell subsets in periodontitis and the signalling process to activate or regulate them, with the exception that CD4+ T cells are induced by P. gingivalis to express RANKL [8].

Tregs are present in periodontal tissue [9] and this T cell subset is known for their anti-inflammatory role; however, the reasons for the apparent lack of anti-inflammatory function in PD are not clear.

B cells dominate chronic periodontitis lesions [10] and their activation and differentiation depend on T cells. The B cells spearhead multiple host defence mechanisms, including the production of antibodies, and in addition secrete a proinflammatory cytokine profile [11]. The role for B cell cytokines in oral pathogenesis is not clear, in part because other cell types also secrete the same B cell cytokines. However, it is well established that B cells are probably the major source of proosteoclastogenic RANKL [12].

A less obvious player in the innate immune response is the platelets, but, presently, the important role of these molecules has been acknowledged. Platelet toll-like receptor expression enables activated platelets to bind and capture bacteria. Subsequently, the platelets may directly kill the bacteria or aggregate around them and “trap” the bacteria for elimination by “professional” phagocytes. It is now clear that different subsets of platelets exist and that they can also heterotypically interact with a wide variety of immune system cells, including leukocytes [13]. However, the net results of these interactions are not clearly established in PD.

Despite abundant information and data in the literature regarding biomarkers for periodontal disease, we are still lacking suitable molecular markers of soft and hard tissue destruction which can replace the clinical gold standards [14]. In this review, we summarize, for each protein proposed as a biomarker elsewhere, the inferred functions of that protein in PD by comparing its role in another osteoimmunology processes. The pertinence of the proposal of each protein as a biomarker will be analyzed considering preferentially their exclusive presence in each PD variant, the quantification data, and the relevance of the molecular event represented by that protein in the context of PD.

2. Biomarker Survey in Periodontal Diseases

In order to obtain the list of proteins suggested as biomarkers in periodontal diseases, we queried the OralOme database using OralCard [15, 16] (http://bioinformatics.ua.pt/oralcard/) for the mesh terms “aggressive periodontitis,” “chronic periodontitis,” “gingivitis,” and “periimplantitis.” Each of the identified proteins was checked to confirm if it was suggested as a biomarker for periodontal diseases proteins > action view > biomarker (true/false) and the information for each protein quantification and presence in the different PD variants was also obtained.

To complement and update the information obtained from OralCard, a thorough manual bibliography review was performed in PubMed, to gather the most recent studies on proteins identified in PD. The following PubMed query was performed: (“proteomics” or “proteomic” or “proteome”) and (“saliva” title/abstract or “oral” title/abstract). The articles retrieved were manually scrutinized and key information from the proteins found in the various references was annotated as described before [16]. Briefly, for each protein, the following data were recorded when available: the identification of the protein; the source of the sample; the disease (MeSH code) and the up-/downregulation (fold change calculations performed according to Chan et al. [17]) compared to normal samples; sample donor data (age, gender, and social habits); methods of sampling and analysis; type of study (proteomics and nonproteomics); and posttranslation modifications and whether the protein had been proposed as a biomarker. Finally, all of these data are mapped to the PubMed citation where they were published. The data collected in this study were used to update the OralCard database.

To analyse and discuss PD biomarkers they were divided into two categories: quantified and nonquantified, depending on whether there was an indication of change in a disease state relative to healthy subjects (regulation). The proteins referred to as being increased (+) or decreased (−), without providing a value for this variation, were included in the group of nonquantified biomarkers. When a protein presented several regulation values from different studies, the average of these values was estimated.

Heterogeneity has become widely acknowledged as a phenomenon that is characteristic of pathogenesis [18, 19]. Heterogeneity occurs at two levels: as multiple phenotypes within an individual (patient-specimen heterogeneity) and between individuals (disease heterogeneity). In PD, both levels of heterogeneity are present. Therefore, we considered, as being differently present, proteins whose quantification had a fold change ≥3x (up- or downregulated) between health and disease samples. The quantified biomarkers were distributed in two groups: those with up-/downregulation ≥3x or counterregulated in different variants of PD and those with up- or downregulation <3x. The total set of biomarkers was analysed, annotating to which disease variant they are proposed for.

From the 43 proteins proposed as biomarkers for PD, only 8 were identified as being exclusively present in one of the disease variants (Table 1).


Periodontal diseaseProposed biomarker Biomarker with quantificationBiomarker up/downExclusive biomarker

Aggressive periodontitis770/00
Chronic periodontitis37342/57
Gingivitis970/00
Periimplantitis331/01

3. Biomarker Functional Analysis

The functional analysis of the biomarkers identified in the PD was performed using the statistical enrichment analysis feature from STRING [20]. Briefly, the list of all biomarkers identified in periodontal diseases was uploaded to STRING using UniProtKB AC codes and the protein network was built. Then, the statistical enrichment analysis feature was used to automatically detect statistically enriched molecular functions or biological processes in the network. For each biomarker, the associated gene ontology terms (GO molecular function and GO biological process) considered of interest in the physiopathological context of PD were annotated. Furthermore, for each biomarker, the GO cellular components terms were also included in the analysis. The OralCard tool was used to verify which periodontal biomarkers were identified in saliva samples in different studies and if they were suggested as biomarkers in nonperiodontal diseases.

All of this information was used to produce Table 2 and the proposed biomarkers are organized according to quantification in each disease; the disease variant and the type of sample in which they were identified; relevant biological processes in which they participate; their molecular functions; and cellular components where they are found.


Protein name UniprotKB AC Gene name (STRING) Disease and disease biomarker Quantification (fold change) Saliva (OralCard) CF (OralCard) Mucosa (OralCard) Saliva non-PD (OralCard) Extracellular (GO CC) Intracellular (GO CC) Intracellular membrane bonded (GO CC) Secretory granule (GO CC) Endocytic vesicle (GO CC) Immune system process (GO BP) Regulation of immune system process (GO BP) Innate immune response (GO BP) Response to bacterium (GO BP) Response to LPS (GO BP) Leucocyte migration (GO BP) Regulation of cytokine production (GO BP) Inflammatory response (GO BP) Regulation of inflammatory response (GO BP) Positive regulation of acute inflammatory response (GO BP) Response to interleukin 1 (GO BP) Enzyme inhibitor activity (GO MF) Positive regulation of MAPK cascade (GO BP) Jak-Stat signaling (GO BP) Regulation of ERK1/2 cascade (GO BP) Adaptive response (GO BP) T cell activation (GO BP) Osteoclastogenesis (GO BP) Coagulation/wounding (GO BP) Platelet activation (GO BP) Platelet degranulation (GO BP) Platelet-derived growth factor receptor binding (GO MF) Angiogenic activity (GO BP) Regulation of peptidase activity (GO MF) Ras GTPase binding activity (GO MF) Biomarker for other pathologies (OralCard)

C-C motif chemokine ligand 13Q99616CCL13PC4.97+++++

Thymidine phosphorylaseP19971TYMPPC−3.70++++++

C-C motif chemokine 2P13500CCL2PC1.90+++++

Fibronectin (FN)P02751FN1PC1.84+++++++

Angiotensinogen (serpin A8)P01019AGTPC+++++++

ClusterinP10909CLUPC+++++++++++

Prostaglandin G/H synthase 2 (COX-2)P35354PTGS2PC0.00+++++++++++

Oncostatin-MP13725OSMPC  
G
726.0
128.0
++++++

C-C motif chemokine 3P10147CCL3PC  
PI
18.00
+
++++

Protein S100-A9P06702S100A9PA 
PC  
G
−1.40
10.41
−1.75
+++++++++++++

Protein S100-A8P05109S100A8PC  
G
3.07
0.00
++++++++

AzurocidinP20160AZU1PC  
G
6.15
3.35
+++++++++

Matrix metalloproteinase-9P14780MMP9PC  
G  
PI
3.54
0.00
+
++++++++

Prolactin-inducible proteinP12273PIPPC  
G
−2.55
0.00
+++++

Superoxide dismutaseP00441SOD1PA  
PC
0.00
1.85
++++++

LactotransferrinP02788LTFPA  
PC
0.60
1.94
++++++

Peptidyl-prolyl cis-trans isomerase AP62937PPIAPC  
G
1.73
0.00
++++++++

Apolipoprotein A-IP02647APOA1PC  
G
1.56
0.00
+++++

Cystatin-SNP01037CST1PC  
G
−1.47
0.00
+++++

Mucin 5BQ9HC84MUC5BPC  
G
1.01
0.00
+++++

Cystatin-SP01036CST4PC  
G
−0.10
0.00
++++

Hemoglobin subunit deltaP02042HBDPA  
PC  
G
158.2
30.87
11.00
++++

RANKLO14788TNFSF11PA  
PC  
G  
PI
56.99
16.09
1.32
12.89
++++++++++

OsteoprotegerinO00300TNFRSF11BPA  
PC  
G  
PI
−4.00
−2.28
−2.44
−0.71
++++++

Neutrophil gelatinase-associated lipocalinP80188LCN2PA  
PC
18.90
1.77
++++++++++

Plastin-2P13796LCP1PA  
PC  
G
15.60
4.93
0.00
+++++++

Neutrophil defensin 1P59665DEFA1PA  
PC
−14.8
4.00
+++++++ 

SerotransferrinP02787TFPA  
PC  
G
−10.4
1.56
0.00
++++++++++

Lysozyme CP61626LYZPA  
PC  
G
−9.10
1.99
−1.41
+++++++

Annexin A1P04083ANXA1PA  
PC  
G
−8.10
1.46
−1.43
++++++++++

Profilin-1P07737PFN1PA  
PC  
G
4.50
2.51
2.00
++++++++++

Ig alpha-1 chain C regionP01876IGHA1PA  
PC  
G
−4.70
1.67
0.00
+++++

Ig gamma-2 chain C regionP01859IGHG2PA  
PC
3.55
1.88
+++++

Ig alpha-2 chain C regionP01877IGHA2PA  
PC
3.10
−1.19
+++++

DermcidinP81605DCDPA  
PC  
G
−2.80
1.39
0.00
+++

Keratin, type II cytoskeletal 1P04264KRT1PA  
PC  
G
−44.3
34.9
−1.45
++++++

Keratin, type II cytoskeletal 2 oralQ01546KRT76PA  
PC  
G
−6.4
5.18
−1.79
+++

Complement C3P01024C3PA  
PC
−1.30
1.58
+++++++++

Neutrophil elastaseP08246ELANEPA  
PC  
G  
PI
2.00
6.50
0.00
12.80
+++++++++++

Neutrophil collagenaseP22894MMP8PA  
PC  
PI
1.10
1.82
9.70
++++++

Alpha-2-macroglobulinP01023A2MPC  
G  
PI
2.15
0.00
8.10
++++++++

Alkaline phosphatase. tissue-nonspecific isozymeP05186ALPLPI5.90++++

Neutrophil defensin 3P59666DEFA3PC  
G
2.63
−2.08
+++++

GO CC: gene ontology cellular component; GO BP: gene ontology biological process; GO MF: gene ontology molecular function.

The protein information presented, unless otherwise stated, was obtained from and is publicly available in the OralCard database.

Due to their pertinence as biomarkers, the proteins for which the up- or downregulation was ≥3x different from the health samples were discussed first.

4. The Functional Role of the Proteins Exclusively Proposed as Biomarkers for Chronic Periodontitis (CP)

In chronic periodontitis, 7 biomarkers exclusive to the pathology are suggested, but only 2, a chemokine (C-C motif) ligand 13 (Q99616), 4.97x upregulated in disease samples, and thymidine phosphorylase (P19971), 3.7x downregulated in disease samples, fulfill both requisites proposed for a biomarker, to be exclusive of the disease state and to have an up/down amount ≥3x.

The chemokine (C-C motif) ligand 13 (CCL13) is expressed in nonlymphoid tissues during chronic inflammation and acts as a chemotactic factor to attract monocytes, but not neutrophils, in tissues chronically exposed to exogenous pathogens. In rheumatoid arthritis, another disease involving inflammatory response, CCL13 was described as being associated with disease progression due to the increased macrophage infiltration and its antiapoptotic functions [21]. In CP, macrophage recruitment and antiapoptotic actions contribute to the permanence of these cells in periodontal tissues, a characteristic shared with other chronic inflammatory pathologies. Up to now, CCL13 was only found in crevicular fluid samples (Table 2); however, since this is an extracellular protein, it is possible to direct studies for its identification/quantification in saliva.

Thymidine phosphorylase has highly restricted target cell specificity, acting only on endothelial cells, promoting growth, angiogenic, and chemotactic activities. It is a cytosolic enzyme that is stored in platelets as a 45 kD single polypeptide chain and its presence in saliva has been detected. Thymidine phosphorylase was identified in mouth neoplasms where it is upregulated and promotes angiogenesis [22]. Because thymidine phosphorylase is downregulated in CP, the integrity of endothelial cells is compromised and it is possible that the normal mechanisms of angiogenesis are affected, leading to cellular hypoxia, characteristic of chronic inflammation and also linked to the promotion of anaerobic microbial growth.

The other two exclusive proteins suggested as biomarkers for CP have up/down quantification values <3x between health and disease samples: fibronectin (P02751), upregulated 1.84x, and the C-C motif chemokine 2 (P13500), upregulated 1.9x.

Fibronectin is an extracellular matrix protein involved in biological processes such as leucocyte migration and platelet degranulation. This protein, in spite of having been evaluated in CP, is a constitutive protein with low quantification values and therefore is not a promising biomarker candidate.

The C-C motif chemokine 2 is a chemotactic factor that attracts monocytes but not neutrophils [23]. This biomarker, which is upregulated only 1.9x, identifies the same process as the C-C motif chemokine ligand 13, which is upregulated 4.97x, and is considered more specific for the recruitment of monocytes in chronic situations.

Finally, 3 other proteins exclusive of PD were proposed as biomarkers but with no quantification (Table 2): angiotensinogen/serpin A8 (P01019) and clusterin (P10909) are both downregulated, while prostaglandin G/H synthase 2 (P35354) has only been identified as being present in CP.

Angiotensinogen/serpin A8 is cleaved by the enzyme renin and the resulting product, angiotensin I, is then processed by angiotensin converting enzyme (ACE) to generate the angiotensin II, the major effector peptide of renin-angiotensin system that mediates several key events of the inflammatory processes; namely, it increases vascular permeability via the release of prostaglandins [24]. It is in fact expected that angiotensinogen/serpin A8 is diminished in CP because it has been converted to angiotensin II and in this form will contribute to the increase of vascular permeability in this PD variant.

Clusterin is a 75–80 kDa disulphide-linked heterodimeric associated with the clearance of cellular debris and has been ascribed a plethora of functions such as recruitment, complement attack prevention, inhibition, and/or scavenging and inhibition [25]. Having clusterin in lower concentrations in CP may contribute to the lack of apoptotic induction of macrophages allowing them to remain in the tissues and consequently maintain a proinflammatory situation.

Prostaglandin G/H synthase 2 (COX-2) has a role as a major mediator of inflammation and is generally expressed only in cells which are upregulated during inflammation.

The clear role of COX-2 and angiotensin II as proteins is important in the inflammatory process and the fact that clusterin acts in several aspects of the immune response suggests the need for the quantification of these proteins in future studies of PD. COX-2 has been identified in crevicular fluid and mucosa samples, and angiotensin II and clusterin were found only in crevicular fluid; nevertheless, because the latter are extracellular, it may also be possible and useful to quantify them in saliva samples.

From the total of 7 exclusive proteins proposed as biomarkers in CP, chemokine (C-C motif) ligand 13 (upregulated 4.97x), characterizing the monocyte recruitment and differentiation stages, and thymidine phosphorylase (downregulated 3.7x), identifying angiogenesis involvement, are the two proteins which better identify CP.

5. A Panel for CP Biomarkers Using Proteins Which Are Common to Other PDs

Because most of the proteins proposed as biomarkers in PD are shared by disease variants (Table 2), it will not be possible to associate the majority of proposed biomarkers with specific events in each pathology. However, if the quantification of the protein is different enough and especially if the protein is counterregulated (upregulated in one pathology and downregulated in the other one), it may be a marker for a common molecular event, allowing the inference from the quantification data (up- or downregulated) of the role that protein may have in the CP.

The two major forms of periodontitis, chronic (CP) and aggressive (AP), do not display sufficiently distinct microbiological/immunological features and a recent work revealed limited differences between the gingival tissue transcriptional profiles of AP and CP, of genes related to immune response and apoptosis. Only signal transduction is overexpressed in AP, and genes related to epithelial integrity and metabolism are overexpressed in CP [26].

Table 2 presents 6 proteins present in CP and in other PDs, upregulated 3x relative to health: oncostatin-M (P13725), C-C motif chemokine 3 (P10147), protein S100-A9 (P06702), protein S100-A8 (P05109), azurocidin (P20160), and MMP9 (P14780).

Oncostatin-M is a multipotent cytokine produced by macrophages and activated T cells; it is structurally and functionally related to the IL-6 cytokine family and elevated expression levels of this cytokine have been determined in many inflammatory diseases [27, 28]. It seems that oncostatin-M alone, or in concert with proinflammatory cytokines like IL-1, can stimulate expression of genes that promote inflammation, namely, IL-6 [29], and also enhance the differentiation and proliferation of osteoblasts, inducing the formation of osteoclasts and consequently bone erosion [28, 30, 31]. Li et al. demonstrated that oncostatin-M can regulate MMP and TIMP mRNA in primary chondrocytes by activation of the Jak/Stat pathway [32] contributing to the expression of proteins involved in bone remodelling.

Oncostatin-M is upregulated 726x in CP and 128x in G. This protein was proposed as a biomarker for both CP and G (Table 2). Considering its role in the modulation of inflammatory processes, it is recommended that further quantification studies are designed to determine the levels of protein present in each PD. If the quantification results are promising, this protein can be a biomarker to predict the evolution from G to a CP status.

The C-C motif chemokine 3 or MIP-1 alpha (macrophage inflammatory protein 1 alpha) is a member of the CC or beta chemokine subfamily that binds to CC chemokine receptor 1 (CCR1) and CCR5 with high affinity. CC chemokines mainly act on monocytes and lymphocytes without affecting neutrophils [33]. In rheumatoid arthritis patients, the C-C motif chemokine 3 is associated with disease progression as a result of its antiapoptotic effects, increased macrophage infiltration, and synovial tissue angiogenesis [34]. C-C motif chemokine 3 in CP is upregulated 18x which contributes to macrophage presence due to the antiapoptotic effect of this protein and therefore promotes the establishment of a chronic inflammatory response. C-C motif chemokine 3 has also been identified in samples from periimplantitis patients but there are no published quantification data for this clinical situation.

S100 protein family is a prominent player in innate immunity [35]. Two S100 proteins, namely, protein S100-A9 and protein S100-A8, are calcium- and zinc-binding proteins abundant in the cytosol of neutrophils [36] which are released as a heterodimeric complex, S100A8/A9, under inflammatory conditions [37]. As a calprotectin (S100A8/A9) complex, it has a wide array of intra- and extracellular functions and recently has been associated with numerous human disorders, including acute and chronic inflammatory conditions [3842]. Apparently, these proteins are able to perform cytokine-like and chemokine-like roles via activation of toll-like receptor 4 (TLR4) dependent signalling cascades and potentially other signalling pathways. Binding to TLR4 activates the MAPK and nuclear factor NF-kappa-B signalling pathways resulting in the amplification of the proinflammatory cascade [43].

Protein S100-A9 is upregulated in CP 10.4x, downregulated in AP 1.4x, and downregulated in G 1.75x, whereas protein S100-A8 is upregulated 3.07x in CP. The calprotectin complex S100-A9/S100-A8 may act as the main trigger for the activation of the proinflammatory cascade in CP.

Azurocidin was proposed as a biomarker in CP and G. This protein is upregulated in CP 6.5x and 3.35x in G. Azurocidin is a chemokine produced by neutrophils that attracts monocytes in a second wave of invasion [44], which clearly reflects the synergy of mechanisms, induced by the recurring microbial challenge characteristic of CP and G that contribute to the permanence of macrophages in periodontal tissues.

Matrix metalloproteinases are considered modifiers of host response and it has been suggested that their role and involvement should be interpreted not solely as surrogate promoters of tissue destruction, but also as defensive or protective factors against inflammation as a whole [45, 46]. MMPs produced by inflammatory cells, such as macrophages and neutrophils, facilitate migration and recruitment of cells, including inflammatory cells, and are also related to angiogenesis and vascular remodelling [47, 48].

Matrix metalloproteinase-9 plays an essential role in leukocyte migration by cleaving the IL-8 precursors, but many other cytokines are also substrates, including TNF-α and interleukin-1β [49]. On the other hand, proinflammatory cytokines are implicated in the transcriptional control of MMP-9 [50, 51]. MMP-9 is upregulated 3.54x in CP; furthermore, it is also annotated as upregulated in G but without quantification. In PI this protein is only reported as present without any quantification or regulation data.

Among the proteins proposed as biomarkers for CP, there are eight which are common to other PDs but have quantification values up/down <3x when compared to health, which makes them less adequate as biomarkers: prolactin-inducible protein (P12273), superoxide dismutase (P00441), lactotransferrin (P02788), peptidyl-prolyl cis-trans isomerase A (P62937), apolipoprotein A-I (P02647), cystatin-SN (P01037), mucin 5B (Q9HC84), and cystatin-S (P01036). Of these, prolactin-inducible protein may act on different subsets of T cells via the CD4 receptor and have antiapoptotic action. The fact that this protein is downregulated (2.55x) may denote the involvement in the mechanism by which, for example, Treg lymphocytes are eliminated in chronic inflammatory processes. Further studies are recommended to evaluate the role of this protein in PD.

6. Functional Roles of the Main Proteins Common to AP and CP: Are There Biomarkers for AP?

From the analysis of PD proteomes and the integration of the information on the proteins proposed as biomarkers for AP (Table 2), a set of 14 proteins seems to be the most promising considering their quantification data, but all proteins were identified in other variants of PD (Table 2). Even though some of the 14 proteins have not been proposed earlier as biomarkers for AP, the quantification data suggest that they might be an adequate choice. The following proteins ordered by decreasing fold change relative to the quantification in AP and health: hemoglobin subunit delta (P02042), RANKL (O14788), osteoprotegerin (O00300), neutrophil gelatinase-associated lipocalin (P80188), plastin (P13796), neutrophil defensin 1 (P59665), serotransferrin (P02787), lysozyme C (P61626), annexin A1 (P04083), profilin-1 (P07737), Ig alpha-1 chain C region (P01876), Ig gamma-2 chain C region (P01859), Ig alpha-2 chain C region (P01877), and dermcidin (P81605). All of these proteins have been previously identified in saliva except dermcidin identified only in crevicular fluid.

One of the hallmarks of periodontitis has been the massive accumulation of neutrophils, which can be found in the gingival connective tissue, the junctional epithelium, and especially the periodontal pocket, where they constitute the overwhelming majority of recruited leukocytes [52]. Among the proteins excreted by activated neutrophils, neutrophil gelatinase-associated lipocalin (NGAL) is released from azurophil, specific, and gelatinase granules [53]. NGAL is an important protein protecting against Gram-negative bacterial infection and is a ligand for MMP-9 activating this enzyme. The expression of NGAL is altered in inflammatory conditions [54]. Agents that induce NF-κB signalling, such as IL-1β and TLRs activation via LPS, positively regulate NGAL expression. Additionally a cross-talk between the JNK (activated via LPS) and NF-κB has been suggested to act together to upregulate NGAL expression [55]. NGAL is upregulated 18.9x in AP, while in CP it is upregulated only 1.8x. The increased expression of NGAL in AP may be one of the few effective antimicrobial mechanisms since most of the proteins involved in microbial defence are downregulated.

Defensins are small, cationic, antimicrobial peptides that are considered to be important antibiotic-like effectors of innate immunity. Defensins also function as immunomodulatory molecules by inducing cytokine and chemokine production, as well as inflammatory and immune cell activation [56]. By using chemokine receptors on dendritic cells and naïve T cells, defensins might also contribute to the regulation of host adaptive immunity. Recently, the role of neutrophil defensin 1 in the integrity of keratinocytes has been demonstrated and in low concentrations of this molecule, keratinocyte proliferation is enhanced [57]. Neutrophil defensin 1 is one of the counterregulated proteins; it is 14.8x downregulated in AP and 4x upregulated in CP. Up to now, there is no evidence available on the exact role of neutrophil defensin 1 in AP. Is the decrease in neutrophil defensin 1 responsible for the apparent decrease in the host’s capacity to fight off infection characteristic of AP? Or is the decrease in this molecule aimed only at guaranteeing the proliferation of the keratinocytes to compensate tissue destruction characteristic of PD?

Another protein released by neutrophils, annexin I, inhibits the signal transduction pathway, acting as a negative regulator of proinflammatory mediators including IL-1 and IL-6. Annexin I also regulates phospholipase A2 activity and consequently the cyclooxygenase-2. Annexin I has the ability to restrict leukocyte transmigration and recruitment during inflammation in a MAPK-dependent manner [5860]. In several experimental models of arthritis, absence of annexin-1 has been associated with increased levels of cytokines and exacerbation of acute inflammation [61, 62]. Annexin A1 is downregulated 8.1x in AP and upregulated 1.5x in CP which means that a low concentration of this protein in AP contributes to a higher neutrophil migration and an increase in proinflammatory molecules.

Plastin-2 is a leukocyte-specific F-actin-bundling protein implicated in cell migration, neutrophil function, DNA repair, and endocytosis [63, 64]. The expression of plastin-2 is restricted to leukocytes, although L-plastin is also aberrantly upregulated in many cancer cells [6365]. A recent study demonstrates an important role for plastin-2 and the signalling pathways regulating its phosphorylation in response to chemokines which adds plastin-2 to a growing list of proteins implicated in T lymphocyte polarity and migration [66]. Plastin-2 is upregulated 15.6x in AP and 4.9x in CP and is probably one of the proteins responsible for the migration and activation of T cells in PD. This protein has been proposed as a biomarker for AP, CP, and G.

The role of the receptor activator of nuclear factor NF-kappa-B ligand and the osteoprotegerin (RANKL-OPG), a bimolecular system considered as the “bottle-neck” regulator of osteoclastogenesis and bone resorption, in both physiological and pathological conditions, is well known. However, the sequence of molecular and cellular events which lead to the production of these molecules in PD is not clear. Neutrophils can induce osteoclastic bone resorption through the expression of membrane-bound RANKL but could only mediate periodontal bone resorption if they are in close proximity to the bone [67]. Nevertheless, all resident mesenchymal cells may also express RANKL under bacterial challenge [68]. It was recently stated that the increased RANKL/OPG ratio may denote the occurrence of periodontitis but may not predict ongoing disease activity because its steadily elevated levels frequently remain after treatment, suggesting that the molecular mechanisms of bone resorption are still active [69]. RANKL is upregulated 57x in AP, 16x in CP, and 12x in PI. Osteoprotegerin (OPG) is downregulated 4x in AP, 2.28x in CP, and 2.44x in PI.

Together these 6 proteins, neutrophil gelatinase-associated lipocalin, neutrophil defensin 1, annexin A1, plastin, RANKL,and OPG, identify the following molecular mechanisms present in AP: (i) high number of neutrophils remaining in the tissue which leads to an exaggerated innate immune response and prevalence of the associated molecular mechanisms (neutrophil gelatinase-associated lipocalin); (ii) decrease in the antimicrobial defence mechanisms (neutrophil defensin 1); (iii) increase in the expression of proinflammatory cytokines due to a decrease in the concentration of the main anti-inflammatory molecules (annexin A1); (iv) the onset of the acquired immune response by the recruitment and activation of T lymphocytes (plastin); (v) strong activation of osteoclastogenesis by a great increase in the protein regulating the differentiation and activation of osteoclasts (RANKL) accompanied by a corresponding decrease in the OPG.

Neutrophil gelatinase-associated lipocalin and neutrophil defensin 1 have not been suggested as biomarkers for AP yet, only for CP (Table 2). However, from the functional role and the quantification data, we suggest that these two proteins are the biomarkers which identify AP more specifically.

From the remaining proteins in the proposed biomarker group, 3 act as antimicrobial molecules and are downregulated in AP and upregulated in CP revealing that the general antimicrobial defence mechanisms are definitely compromised.

Dermcidin forms tiny channels perforating the cell membrane and its presence in granules of neutrophils has been reported [53]. It is also known that dermcidin expression is not induced under inflammatory conditions in keratinocytes [70, 71]. In AP, dermcidin is downregulated 2.3x and it is upregulated 1.4x in CP.

Lysozyme C is a proteolytic enzyme secreted by oral leucocytes that acts on both peptide-substituted and unsubstituted peptidoglycan. Lysozyme C is downregulated 9.1x in AP, upregulated 1.99x in CP, and downregulated 1.41x in G.

Serotransferrin binds iron and prevents bacterial survival. The level of serotransferrin decreases in inflammation [72]. Serotransferrin is downregulated 10.4x in AP and upregulated 1.56x in CP.

Another protein present in AP proteome is profilin-1, an actin-binding protein, which is widely distributed in various types of cells with highly conserved sequences. Profilin-1 achieves its function via the regulation of unpolymerised actin in cells contributing to endothelial cell contraction and vascular hyperpermeability. Recently, it has been reported that overexpression of profilin-1 upregulated the expression of ICAM-1, increased endothelial cell permeability, induced endothelial cell apoptosis, and promoted endothelial cell migration [73]. Under pathological conditions, such as diabetes or atherosclerosis, profilin-1 levels increase. It has been verified that AGEs upregulated the expression of profilin-1 via the excess production of ROS and subsequent activation of PKC and NF-κB [73].

Profilin 1 is upregulated in AP 4.5x, in CP 2.51x, and 2.00x in G. This protein has been proposed as a biomarker only for CP. Due to this protein’s relevance in vascular tissue lesion, further studies in PD are recommended as it may be an early indicator of the host’s response in PD and will be the link between PD and cardiovascular disease.

Finally, keratin type II cytoskeletal 1 (P04264) is downregulated 44.3x in AP and upregulated 34.9x in CP. Keratin, type II cytoskeletal 2 oral, is downregulated 6.4x in AP and upregulated 5.2x in CP. McLaughlin demonstrated that the keratin concentration in GCF was significantly higher at sites exhibiting signs of gingivitis and periodontitis compared with healthy sites [74]. The OralCard data shows counterregulated quantities of keratins in AP versus CP. The keratins are the typical intermediate filament proteins of epithelia, showing an outstanding degree of molecular diversity. They are expressed in highly specific patterns related to the epithelial type and stage of cellular differentiation. The keratin, type II cytoskeletal 2 oral, is synthesized during maturation of epidermal keratinocytes. Stress conditions affect not only keratin expression profiles, but also keratin expression levels and posttranslational modification. In terms of the importance of keratins for PD diagnostics there is not enough evidence to associate the differential expression present in AP and CP.

Because we have not identified a single protein exclusive of AP, we consider that, with the functional information available, the conjugation of neutrophil gelatinase-associated lipocalin upregulated in AP, with neutrophil defensin 1 and annexin A1 both downregulated in AP, may be used to identify AP.

Belibasakis and Bostanci suggest studies establishing the levels of RANKL to discriminate between health and periodontal disease [69]. These results are important to establish the RANKL level that discriminate between health and the PD variants.

Serotransferrin, a keratin type II cytoskeletal 1, and keratin type II cytoskeletal 2 oral, being counterregulated in AP and CP, may allow the differential diagnostic between the two pathologies.

7. The Scenario of the Proposed Biomarkers for Perimplantitis

The sequence of immunopathological events and the qualitative composition of the immune cells in periimplant infections are similar to that of periodontal infections. Nevertheless, compared to periodontitis, periimplantitis is marked by a more extensive inflammatory infiltrate and innate immune response, a greater severity of tissue destruction, and a faster progression rate [75].

In PI, a single exclusive protein has been proposed as a biomarker: alkaline phosphatase, tissue-nonspecific isozyme (P05186) which is upregulated 5.9x.

Alkaline phosphatase (TNAP) belongs to a ubiquitous family of metalloenzymes that play an essential physiological role during osteoblastic bone matrix mineralization [76, 77]. It is expressed on the cell membrane of osteoblasts and odontoblasts, as an ectoenzyme transported to the plasma membrane. Infections, including bone infections, can lead to increased tissue-nonspecific alkaline phosphatase levels. TNAP is also present in neutrophils granules and its activity increases in bacterial infection [78]. As to the relevance of this enzyme in PD, the literature is not consensual; some authors state that elevated alkaline phosphatase levels precede attachment loss, when the clinical parameters are not yet discriminatory [79], and others consider that there is no support for the predictive value of alkaline phosphatase levels in periodontal breakdown but that it may serve as a marker in periodontal treatment planning and monitoring [80, 81]. Another function of TNAP is its ability to remove one of the two phosphate groups from the lipid moiety of the Gram-negative bacterial LPS, which results in the formation of nontoxic dephosphorylated monophosphoryl LPS (MPLPS), ineffective to activate the TLR receptors [82]. Two other proteins proposed as biomarkers in PI were also identified: neutrophil collagenase/MMP-8 (P22894) upregulated 1.1x in AP, 1.82x in CP, and 9.7x in PI and neutrophil elastase (P08246) upregulated 2x in AP, 6.5x in CP, and 12.8x in PI.

MMP-8, released from neutrophils and potentially other cellular sources at sites of inflammation, activates IL-8 and IL-6 and chemokines, creating a “feed-forward” response that drives further neutrophil recruitment and a self-reinforcing protease-immunomodulatory circuit that may underpin its function in diverse physiological repair and defence mechanisms [83, 84].

Neutrophil elastase (NE), a cationic glycoprotein, is stored in readily active form in PMN primary granules [85], is a key antimicrobial enzyme that mediates defence against Gram-negative bacteria by degradation of structural proteins localized on the cell wall [86] or by targeting their virulence factors [87]. NE also binds to PMN-derived chromatin structures, termed neutrophil extracellular traps, and exerts its own antimicrobial function [88].

Alpha-2-macroglobulin (P01023) (α2-M), one of the acute phase proteins, apart from inhibiting proteinases, regulates binding of transferrin to its surface receptor, binds defensin and several important cytokines, including interleukin-1β and interleukin-6, and modifies their biological activity [89]. Alpha-2-macroglobulin is upregulated 2.15x in CP and 8.1x in PI, but it has been proposed as a biomarker only in CP.

For the 4 proteins which represent a greater impact on PI, it is still not possible to clarify their participation in PD, but considering their role, namely, as immune response modulators, a deeper study of their influence in PD is justified.

8. The Proposed Biomarkers in Gingivitis

Although dental plaque accumulation causes gingivitis (a reversible form of periodontal inflammation that does not involve the alveolar bone), gingivitis in turn does not necessarily lead to periodontitis, suggesting that stable gingivitis means that a protective host response exists.

As biomarkers for G, the following molecules were proposed: oncostatin-M and azurocidin, already discussed in CP; RANKL which is shared by all PD variants being the lower values observed in G; and plastin-2 and serotransferrin shared with AP and CP, which have been proposed as biomarkers in G but have not been quantified in this disease variant.

Our analysis points to neutrophil defensin 3 as a molecule which may be suitable for the differential diagnostic between G and CP. In addition to its antimicrobial effects, it has also been reported to attract monocytes [90] and T and dendritic cells [91]. Neutrophil defensin 3 is counterregulated in G and CP, and future studies should be performed to evaluate if the protein is present in quantities up/down 3x.

9. Conclusions

The analysis of the 43 proteins proposed as biomarkers for PD allowed the identification of their functional role and the cells which produce them. Figure 1 shows a selection of biomarkers that, due to their quantification, better characterize each PD variant. Clearly, the biomarkers proposed for CP are produced by neutrophils and macrophages and are involved in mechanisms responsible for monocyte and neutrophil recruitment and the regulation of proinflammatory molecule production. Platelets are a source of thymidine phosphorylase, a protein eventually implicated in the deregulation of angiogenesis.

In contrast, the biomarkers proposed for AP are essentially produced by neutrophils. The quantification data of these proteins points to a decrease in antimicrobial defence mechanisms.

The biomarkers proposed for PI are also produced by neutrophils. They represent mechanisms involved in the innate response and bone remodelling processes.

Some of the biomarkers proposed so far for PD are promising but the quantification data are scarce. Further quantitative proteomic studies are needed not only to establish the expression levels of these proteins in each PD variant, but also to establish the protein levels associated with health.

Abbreviations

ACE:Angiotensin converting enzyme
AGEs:Advanced glycation end-products
AP:Aggressive periodontitis
CCL13:Chemokine (C-C motif) ligand 13
CCR1:CC chemokine receptor 1
CD4:T cell surface glycoprotein CD4
COX-2:Prostaglandin G/H synthase 2
CP:Chronic periodontitis
G:Gingivitis
ICAM-1:Intercellular adhesion molecule 1
IL-1:Interleukin-1
IL-17:Interleukin-17
IL-6:Interleukin-6
IL-8:Interleukin-8
Jak/Stat:Janus kinase/signal transducer and activator of transcription
JNK:c-Jun N-terminal kinase
LPS:Lipopolysaccharide
MAPK:Mitogen activated protein kinases
MIP-1:Macrophage inflammatory protein 1
MMP:Matrix metalloproteinase
MPLPS:Monophosphoryl lipopolysaccharide
NE:Neutrophil elastase
NF-κ-B:Nuclear factor NF-kappa-B
NGAL:Neutrophil gelatinase-associated lipocalin
OPG:Osteoprotegerin
PD:Periodontal diseases
PI:Periimplantitis
PKC:Protein kinase C
PMN:Polymorphonuclear leukocytes
RANKL:Tumor necrosis factor ligand superfamily member 11
ROS:Reactive oxygen species
STRING:Search tool for the retrieval of interacting genes/proteins
Th:T helper cells.
TIMP:Tissue inhibitor of metalloproteinases
TLR4:Toll-like receptor 4
TNAP:Tissue-nonspecific alkaline phosphatase
TNF-α:Tumor necrosis factor
Tregs:Regulatory T cells
α2-M:Alpha-2-macroglobulin.

Conflict of Interests

The authors declare that there is no conflict of interests regarding the publication of this paper.

Authors’ Contribution

The paper was written through contributions of all authors. All authors have given approval to the final version of the paper.

Acknowledgments

The authors acknowledge Artspazios for the creation of the artwork presented in this paper.

References

  1. D. T. Graves, T. Oates, and G. P. Garlet, “Review of osteoimmunology and the host response in endodontic and periodontal lesions,” Journal of Oral Microbiology, vol. 3, no. 2011, article 5304, 2011. View at: Publisher Site | Google Scholar
  2. M. Miyauchi, S. Sato, S. Kitagawa et al., “Cytokine expression in rat molar gingival periodontal tissues after topical application of lipopolysaccharide,” Histochemistry and Cell Biology, vol. 116, no. 1, pp. 57–62, 2001. View at: Google Scholar
  3. I. H. K. Dias, J. B. Matthews, I. L. C. Chapple, H. J. Wright, C. R. Dunston, and H. R. Griffiths, “Activation of the neutrophil respiratory burst by plasma from periodontitis patients is mediated by pro-inflammatory cytokines,” Journal of Clinical Periodontology, vol. 38, no. 1, pp. 1–7, 2011. View at: Publisher Site | Google Scholar
  4. F. S. Lakschevitz, G. M. Aboodi, and M. Glogauer, “Oral neutrophil transcriptome changes result in a pro-survival phenotype in periodontal diseases,” PLoS ONE, vol. 8, no. 7, Article ID e68983, 2013. View at: Publisher Site | Google Scholar
  5. M. Muthukuru, R. Jotwani, and C. W. Cutler, “Oral mucosal endotoxin tolerance induction in chronic periodontitis,” Infection and Immunity, vol. 73, no. 2, pp. 687–694, 2005. View at: Publisher Site | Google Scholar
  6. M. Yamamoto, K. Fujihashi, T. Hiroi, J. R. McGhee, T. E. van Dyke, and H. Kiyono, “Molecular and cellular mechanisms for periodontal diseases: role of Th1 and Th2 type cytokines in induction of mucosal inflammation,” Journal of Periodontal Research, vol. 32, no. 1, part 2, pp. 115–119, 1997. View at: Google Scholar
  7. N. M. Moutsopoulos, H. M. Kling, N. Angelov et al., “Porphyromonas gingivalis promotes Th17 inducing pathways in chronic periodontitis,” Journal of Autoimmunity, vol. 39, no. 4, pp. 294–303, 2012. View at: Publisher Site | Google Scholar
  8. G. N. Belibasakis, D. Reddi, and N. Bostanci, “Porphyromonas gingivalis induces RANKL in T-cells,” Inflammation, vol. 34, no. 2, pp. 133–138, 2011. View at: Publisher Site | Google Scholar
  9. C. R. Cardoso, G. P. Garlet, A. P. Moreira, W. Martins Jr., M. A. Rossi, and J. S. Silva, “Characterization of CD4+CD25+ natural regulatory T cells in the inflammatory infiltrate of human chronic periodontitis,” Journal of Leukocyte Biology, vol. 84, no. 1, pp. 311–318, 2008. View at: Publisher Site | Google Scholar
  10. T. Berglundh and M. Donati, “Aspects of adaptive host response in periodontitis,” Journal of Clinical Periodontology, vol. 32, no. 6, pp. 87–107, 2005. View at: Publisher Site | Google Scholar
  11. B. S. Nikolajczyk, M. Jagannathan-Bogdan, and G. V. Denis, “The outliers become a stampede as immunometabolism reaches a tipping point,” Immunological Reviews, vol. 249, no. 1, pp. 253–275, 2012. View at: Publisher Site | Google Scholar
  12. M. Onal, J. Xiong, X. Chen et al., “Receptor activator of nuclear factor κB ligand (RANKL) protein expression by B lymphocytes contributes to ovariectomy-induced bone loss,” Journal of Biological Chemistry, vol. 287, no. 35, pp. 29851–29860, 2012. View at: Publisher Site | Google Scholar
  13. J. W. Semple, J. E. Italiano Jr., and J. Freedman, “Platelets and the immune continuum,” Nature Reviews Immunology, vol. 11, no. 4, pp. 264–274, 2011. View at: Publisher Site | Google Scholar
  14. N. Buduneli and D. F. Kinane, “Host-derived diagnostic markers related to soft tissue destruction and bone degradation in periodontitis,” Journal of Clinical Periodontology, vol. 38, no. 11, pp. 85–105, 2011. View at: Publisher Site | Google Scholar
  15. N. Rosa, M. J. Correia, J. P. Arrais et al., “From the salivary proteome to the OralOme: comprehensive molecular oral biology,” Archives of Oral Biology, vol. 57, no. 7, pp. 853–864, 2012. View at: Publisher Site | Google Scholar
  16. J. P. Arrais, N. Rosa, J. Melo et al., “OralCard: a bioinformatic tool for the study of oral proteome,” Archives of Oral Biology, vol. 58, no. 7, pp. 762–772, 2013. View at: Publisher Site | Google Scholar
  17. H. H. Chan, Z. H. A. Rahim, K. Jessie, O. H. Hashim, and T. B. Taiyeb-Ali, “Salivary proteins associated with periodontitis in patients with type 2 diabetes mellitus,” International Journal of Molecular Sciences, vol. 13, no. 4, pp. 4652–4654, 2012. View at: Publisher Site | Google Scholar
  18. R. C. Deo and F. P. Roth, “Pathways of the heart,” Circulation: Cardiovascular Genetics, vol. 2, no. 4, pp. 303–305, 2009. View at: Publisher Site | Google Scholar
  19. B. Fisher, C. K. Redmond, and E. R. Fisher, “Evolution of knowledge related to breast cancer heterogeneity: a 25-year retrospective,” Journal of Clinical Oncology, vol. 26, no. 13, pp. 2068–2071, 2008. View at: Publisher Site | Google Scholar
  20. A. Franceschini, D. Szklarczyk, S. Frankild et al., “STRING v9.1: protein-protein interaction networks, with increased coverage and integration,” Nucleic Acids Research, vol. 41, no. 1, pp. D808–D815, 2013. View at: Publisher Site | Google Scholar
  21. L. V. Bagaeva, P. Rao, J. M. Powers, and B. M. Segal, “CXC chemokine ligand 13 plays a role in experimental autoimmune encephalomyelitis,” Journal of Immunology, vol. 176, no. 12, pp. 7676–7685, 2006. View at: Google Scholar
  22. L.-M. Chi, C.-W. Lee, K.-P. Chang et al., “Enhanced interferon signaling pathway in oral cancer revealed by quantitative proteome analysis of microdissected specimens using 160/180 labeling and integrated two-dimensional LC-ESI-MALDI tandem MS,” Molecular and Cellular Proteomics, vol. 8, no. 7, pp. 1453–1474, 2009. View at: Publisher Site | Google Scholar
  23. S. L. Deshmane, S. Kremlev, S. Amini, and B. E. Sawaya, “Monocyte chemoattractant protein-1 (MCP-1): an overview,” Journal of Interferon and Cytokine Research, vol. 29, no. 6, pp. 313–325, 2009. View at: Publisher Site | Google Scholar
  24. A. Benigni, P. Cassis, and G. Remuzzi, “Angiotensin II revisited: new roles in inflammation, immunology and aging,” EMBO Molecular Medicine, vol. 2, no. 7, pp. 247–257, 2010. View at: Publisher Site | Google Scholar
  25. S. E. Jones and C. Jomary, “Clusterin,” International Journal of Biochemistry and Cell Biology, vol. 34, no. 5, pp. 427–431, 2002. View at: Publisher Site | Google Scholar
  26. B. G. Loos and G. Papantonopoulos:, “Molecular biotypes for periodontal diseases?” Journal of Dental Research, vol. 92, no. 12, pp. 1056–1057, 2013. View at: Publisher Site | Google Scholar
  27. M. Akdis, S. Burgler, R. Crameri et al., “Interleukins, from 1 to 37, and interferon-γ: receptors, functions, and roles in diseases,” Journal of Allergy and Clinical Immunology, vol. 127, no. 3, pp. 701–721, 2011. View at: Publisher Site | Google Scholar
  28. C. D. Richards, “The enigmatic cytokine oncostatin M and roles in disease,” ISRN Inflammation, vol. 2013, Article ID 512103, 23 pages, 2013. View at: Publisher Site | Google Scholar
  29. W. Hui, T. E. Cawston, C. D. Richards, and A. D. Rowan, “A model of inflammatory arthritis highlights a role for oncostatin M in pro-inflammatory cytokine-induced bone destruction via RANK/RANKL,” Arthritis Research & Therapy, vol. 7, no. 1, pp. R57–R64, 2005. View at: Google Scholar
  30. N. A. Sims and N. C. Walsh, “GP130 cytokines and bone remodelling in health and disease,” BMB Reports, vol. 43, no. 8, pp. 513–523, 2010. View at: Google Scholar
  31. C. D. Richards, C. Langdon, P. Deschamps, D. Pennica, and S. G. Shaughnessy, “Stimulation of osteoclast differentiation in vitro by mouse oncostatin M, leukaemia inhibitory factor, cardiotrophin-1 and interleukin 6: synergy with dexamethasone,” Cytokine, vol. 12, no. 6, pp. 613–621, 2000. View at: Publisher Site | Google Scholar
  32. W. Q. Li, F. Dehnade, and M. Zafarullah, “Oncostatin M-induced matrix metalloproteinase and tissue inhibitor of metalloproteinase-3 genes expression in chondrocytes requires Janus kinase/STAT signaling pathway,” Journal of Immunology, vol. 166, no. 5, pp. 3491–3498, 2001. View at: Google Scholar
  33. A. D. Luster, “Mechanisms of disease: chemokines—chemotactic cytokines that mediate inflammation,” New England Journal of Medicine, vol. 338, no. 7, pp. 436–445, 1998. View at: Publisher Site | Google Scholar
  34. A. Yamaguchi, K. Nozawa, M. Fujishiro et al., “CC motif chemokine ligand 13 is associated with rheumatoid arthritis pathogenesis,” Modern Rheumatology, vol. 23, no. 5, pp. 856–863, 2013. View at: Publisher Site | Google Scholar
  35. W. Nacken, J. Roth, C. Sorg, and C. Kerkhoff, “S100A9/S100A8: myeloid representatives of the S100 protein family as prominent players in innate immunity,” Microscopy Research and Technique, vol. 60, no. 6, pp. 569–580, 2003. View at: Google Scholar
  36. S. Yui, Y. Nakatani, and M. Mikami, “Calprotectin (S100A8/S100A9), an inflammatory protein complex from neutrophils with a broad apoptosis-inducing activity,” Biological and Pharmaceutical Bulletin, vol. 26, no. 6, pp. 753–760, 2003. View at: Google Scholar
  37. Y. Nakatani, M. Yamazaki, W. J. Chazin, and S. Yui, “Regulation of S100A8/A9 (calprotectin) binding to tumor cells by zinc ion and its implication for apoptosis-inducing activity,” Mediators of Inflammation, vol. 2005, no. 5, pp. 280–292, 2005. View at: Publisher Site | Google Scholar
  38. C. Perera, H. P. McNeil, and C. L. Geczy, “S100 Calgranulins in inflammatory arthritis,” Immunology and Cell Biology, vol. 88, no. 1, pp. 41–49, 2010. View at: Publisher Site | Google Scholar
  39. M. M. Averill, C. Kerkhoff, and K. E. Bornfeldt, “S100A8 and S100A9 in cardiovascular biology and disease,” Arteriosclerosis, Thrombosis, and Vascular Biology, vol. 32, no. 2, pp. 223–229, 2012. View at: Publisher Site | Google Scholar
  40. C. Gebhardt, J. Németh, P. Angel, and J. Hess, “S100A8 and S100A9 in inflammation and cancer,” Biochemical Pharmacology, vol. 72, no. 11, pp. 1622–1631, 2006. View at: Publisher Site | Google Scholar
  41. G. Srikrishna, “S100A8 and S100A9: new insights into their roles in malignancy,” Journal of Innate Immunity, vol. 4, no. 1, pp. 31–40, 2011. View at: Publisher Site | Google Scholar
  42. E. Stragier and G. van Assche, “The use of fecal calprotectin and lactoferrin in patients with IBD: review,” Acta Gastro-Enterologica Belgica, vol. 76, no. 3, pp. 322–328, 2013. View at: Google Scholar
  43. T. Vogl, A. L. Gharibyan, and L. A. Morozova-Roche, “Pro-inflammatory S100A8 and S100A9 proteins: self-assembly into multifunctional native and amyloid complexes,” International Journal of Molecular Sciences, vol. 13, no. 3, pp. 2893–2917, 2012. View at: Publisher Site | Google Scholar
  44. O. Soehnlein, L. Lindbom, and C. Weber, “Mechanisms underlying neutrophil-mediated monocyte recruitment,” Blood, vol. 114, no. 21, pp. 4613–4623, 2009. View at: Publisher Site | Google Scholar
  45. T. Sorsa, L. Tjäderhane, and T. Salo, “Matrix metalloproteinases (MMPs) in oral diseases,” Oral Diseases, vol. 10, no. 6, pp. 311–318, 2004. View at: Publisher Site | Google Scholar
  46. T. Sorsa, L. Tjäderhane, Y. T. Konttinen et al., “Matrix metalloproteinases: contribution to pathogenesis, diagnosis and treatment of periodontal inflammation,” Annals of Medicine, vol. 38, no. 5, pp. 306–321, 2006. View at: Publisher Site | Google Scholar
  47. W. C. Parks, C. L. Wilson, and Y. S. López-Boado, “Matrix metalloproteinases as modulators of inflammation and innate immunity,” Nature Reviews Immunology, vol. 4, no. 8, pp. 617–629, 2004. View at: Google Scholar
  48. Q. Chen, M. Jin, F. Yang, J. Zhu, Q. Xiao, and L. Zhang, “Matrix metalloproteinases: inflammatory regulators of cell behaviors in vascular formation and remodeling,” Mediators of Inflammation, vol. 2013, Article ID 928315, 14 pages, 2013. View at: Publisher Site | Google Scholar
  49. S.-T. Vilen, T. Salo, T. Sorsa, and P. Nyberg, “Fluctuating roles of matrix metalloproteinase-9 in oral squamous cell carcinoma,” The Scientific World Journal, vol. 2013, Article ID 920595, 11 pages, 2013. View at: Publisher Site | Google Scholar
  50. Y. Zhang, K. McCluskey, K. Fujii, and L. M. Wahl, “Differential regulation of monocyte matrix metalloproteinase and TIMP-1 production by TNF-α, granulocyte-macrophage CSF, and IL-1β through prostaglandin-dependent and -independent mechanisms,” Journal of Immunology, vol. 161, no. 6, pp. 3071–3076, 1998. View at: Google Scholar
  51. K. A. C. Harkness, P. Adamson, J. D. Sussman, G. A. B. Davies-Jones, J. Greenwood, and M. N. Woodroofe, “Dexamethasone regulation of matrix metalloproteinase expression in CNS vascular endothelium,” Brain, vol. 123, no. 4, pp. 698–709, 2000. View at: Google Scholar
  52. G. Hajishengallis, “Immunomicrobial pathogenesis of periodontitis: keystones, pathobionts, and host response,” Trends in Immunology, vol. 35, no. 1, pp. 3–11, 2014. View at: Publisher Site | Google Scholar
  53. G. Lominadze, D. W. Powell, G. C. Luerman, A. J. Link, R. A. Ward, and K. R. McLeish, “Proteomic analysis of human neutrophil granules,” Molecular and Cellular Proteomics, vol. 4, no. 10, pp. 1503–1521, 2005. View at: Publisher Site | Google Scholar
  54. S. Chakraborty, S. Kaur, S. Guha, and S. K. Batra, “The multifaceted roles of neutrophil gelatinase associated lipocalin (NGAL) in inflammation and cancer,” Biochimica et Biophysica Acta: Reviews on Cancer, vol. 1826, no. 1, pp. 129–169, 2012. View at: Publisher Site | Google Scholar
  55. S. Chakraborty, S. Kaur, Z. Tong, S. K. Batra, and S. Guha, “Neutrophil gelatinase associated lipocalin: structure, function and role in human pathogenesis,” in Acute Phase Proteins—Regulation and Functions of Acute Phase Proteins, F. Veas, Ed., InTech, 2011. View at: Publisher Site | Google Scholar
  56. I. Nagaoka, K. Suzuki, T. Murakami, F. Niyonsaba, H. Tamura, and M. Hirata, “Evaluation of the effect of α-defensin human neutrophil peptides on neutrophil apoptosis,” International Journal of Molecular Medicine, vol. 26, no. 6, pp. 925–934, 2010. View at: Publisher Site | Google Scholar
  57. U. K. Gursoy, E. Könönen, N. Luukkonen, and V.-J. Uitto, “Human neutrophil defensins and their effect on epithelial cells,” Journal of Periodontology, vol. 84, no. 1, pp. 126–133, 2013. View at: Publisher Site | Google Scholar
  58. M. C. Côté, J. R. Lavoie, F. Houle, A. Poirier, S. Rousseau, and J. Huot, “Regulation of vascular endothelial growth factor-induced endothelial cell migration by LIM kinase 1-mediated phosphorylation of annexin 1,” Journal of Biological Chemistry, vol. 285, no. 11, pp. 8013–8021, 2010. View at: Publisher Site | Google Scholar
  59. F. N. E. Gavins and M. J. Hickey, “Annexin A1 and the regulation of innate and adaptive immunity,” Frontiers in Immunology, vol. 3, Article ID Article 354, 2012. View at: Publisher Site | Google Scholar
  60. X. Liu, B. Ma, A. B. Malik et al., “Bidirectional regulation of neutrophil migration by mitogen-activated protein kinases,” Nature Immunology, vol. 13, no. 5, pp. 457–464, 2012. View at: Publisher Site | Google Scholar
  61. Y. Yang, P. Hutchinson, and E. F. Morand, “Inhibitory effect of annexin I on synovial inflammation in rat adjuvant arthritis,” Arthritis & Rheumatology, vol. 42, no. 7, pp. 1538–1544, 1999. View at: Google Scholar
  62. A. S. Damazo, S. Yona, F. D'Acquisto, R. J. Flower, S. M. Oliani, and M. Perretti, “Critical protective role for annexin 1 gene expression in the endotoxemic murine microcirculation,” The American Journal of Pathology, vol. 166, no. 6, pp. 1607–1617, 2005. View at: Google Scholar
  63. N. Ozmeric, “Advances in periodontal disease markers,” Clinica Chimica Acta, vol. 343, no. 1-2, pp. 1–16, 2004. View at: Publisher Site | Google Scholar
  64. H. Shinomiya, “Plastin family of actin-bundling proteins: its functions in leukocytes, neurons, intestines, and cancer,” International Journal of Cell Biology, vol. 2012, Article ID 213492, 8 pages, 2012. View at: Publisher Site | Google Scholar
  65. Y. Ning, A. Gerger, W. Zhang et al., “Plastin polymorphisms predict gender- and stage-specific colon cancer recurrence after adjuvant chemotherapy,” Molecular Cancer Therapeutics, vol. 13, no. 2, pp. 528–539, 2014. View at: Publisher Site | Google Scholar
  66. M. Freeley, F. O'Dowd, T. Paul et al., “L-plastin regulates polarization and migration in chemokine-stimulated human T lymphocytes,” Journal of Immunology, vol. 188, no. 12, pp. 6357–6370, 2012. View at: Publisher Site | Google Scholar
  67. A. Chakravarti, M.-A. Raquil, P. Tessier, and P. E. Poubelle, “Surface RANKL of Toll-like receptor 4-stimulated human neutrophils activates osteoclastic bone resorption,” Blood, vol. 114, no. 8, pp. 1633–1644, 2009. View at: Publisher Site | Google Scholar
  68. M. Kajiya, G. Giro, M. A. Taubman, X. Han, M. P. A. Mayer, and T. Kawai, “Role of periodontal pathogenic bacteria in RANKL-mediated bone destruction in periodontal disease,” Journal of Oral Microbiology, vol. 2, no. 2010, article 5532, 2010. View at: Publisher Site | Google Scholar
  69. G. N. Belibasakis and N. Bostanci, “The RANKL-OPG system in clinical periodontology,” Journal of Clinical Periodontology, vol. 39, no. 3, pp. 239–248, 2012. View at: Publisher Site | Google Scholar
  70. Y. Minami, K. Uede, K. Sagawa, A. Kimura, T. Tsuji, and F. Furukawa, “Immunohistochemical staining of cutaneous tumours with G-81, a monoclonal antibody to dermcidin,” The British Journal of Dermatology, vol. 151, no. 1, pp. 165–169, 2004. View at: Publisher Site | Google Scholar
  71. S. Rieg, C. Garbe, B. Sauer, H. Kalbacher, and B. Schittek, “Dermcidin is constitutively produced by eccrine sweat glands and is not induced in epidermal cells under inflammatory skin conditions,” The British Journal of Dermatology, vol. 151, no. 3, pp. 534–539, 2004. View at: Publisher Site | Google Scholar
  72. A. M. Koorts, P. F. Levay, P. J. Becker, and M. Viljoen, “Pro- and anti-inflammatory cytokines during immune stimulation: modulation of iron status and red blood cell profile,” Mediators of Inflammation, vol. 2011, Article ID 716301, 11 pages, 2011. View at: Publisher Site | Google Scholar
  73. Z. Li, Q. Zhong, T. Yang, X. Xie, and M. Chen, “The role of profilin-1 in endothelial cell injury induced by advanced glycation end products (AGEs),” Cardiovascular Diabetology, vol. 12, article 141, 2013. View at: Publisher Site | Google Scholar
  74. W. S. McLaughlin, “Human gingival crevicular fluid keratin at healthy, chronic gingivitis and chronic adult periodontitis sites,” Journal of Clinical Periodontology, vol. 23, no. 4, pp. 331–335, 1996. View at: Google Scholar
  75. G. N. Belibasakis, “Microbiological and immuno-pathological aspects of peri-implant diseases,” Archives of Oral Biology, vol. 59, no. 1, pp. 66–72, 2014. View at: Publisher Site | Google Scholar
  76. K. A. Johnson, L. Hessle, S. Vaingankar et al., “Osteoblast tissue-nonspecific alkaline phosphatase antagonizes and regulates PC-1,” The American Journal of Physiology: Regulatory Integrative and Comparative Physiology, vol. 279, no. 4, pp. R1365–R1377, 2000. View at: Google Scholar
  77. H. Orimo, “The mechanism of mineralization and the role of alkaline phosphatase in health and disease,” Journal of Nippon Medical School, vol. 77, no. 1, pp. 4–12, 2010. View at: Publisher Site | Google Scholar
  78. A. Udristioiu, R. Iliescu, M. Cojocaru, and A. Joanta, “Alkaline phosphatase isoenzymes and leukocyte alkaline phosphatase score in patients with acute and chronic disease: a brief review,” The British Journal of Medicine and Medical Research, vol. 4, no. 1, pp. 340–350, 2014. View at: Publisher Site | Google Scholar
  79. C. Cafiero and S. Matarasso, “Predictive, preventive, personalised and participatory periodontology: “the 5Ps age” has already started,” EPMA Journal, vol. 4, no. 1, article 16, 2013. View at: Publisher Site | Google Scholar
  80. L. K. McCauley and R. M. Nohutcu, “Mediators of periodontal osseous destruction and remodeling: principles and implications for diagnosis and therapy,” Journal of Periodontology, vol. 73, no. 11, pp. 1377–1391, 2002. View at: Publisher Site | Google Scholar
  81. M. Taba Jr., J. Kinney, A. S. Kim, and W. V. Giannobile, “Diagnostic biomarkers for oral and periodontal diseases,” Dental Clinics of North America, vol. 49, no. 3, pp. 551–571, 2005. View at: Publisher Site | Google Scholar
  82. A. F. Pike, N. I. Kramer, B. J. Blaauboer, W. Seinen, and R. Brands, “A novel hypothesis for an alkaline phosphatase 'rescue' mechanism in the hepatic acute phase immune response,” Biochimica et Biophysica Acta: Molecular Basis of Disease, vol. 1832, no. 12, pp. 2044–2056, 2013. View at: Publisher Site | Google Scholar
  83. A. M. Tester, J. H. Cox, A. R. Connor et al., “LPS responsiveness and neutrophil chemotaxis in vivo require PMN MMP-8 activity,” PLoS ONE, vol. 2, no. 3, article e312, 2007. View at: Publisher Site | Google Scholar
  84. S. Thirkettle, J. Decock, H. Arnold, C. J. Pennington, D. M. Jaworski, and D. R. Edwards, “Matrix metalloproteinase 8 (collagenase 2) induces the expression of interleukins 6 and 8 in breast cancer cells,” Journal of Biological Chemistry, vol. 288, no. 23, pp. 16282–16294, 2013. View at: Publisher Site | Google Scholar
  85. R. Benabid, J. Wartelle, L. Malleret et al., “Neutrophil elastase modulates cytokine expression: contribution to host defense against pseudomonas aeruginosa-induced pneumonia,” Journal of Biological Chemistry, vol. 287, no. 42, pp. 34883–34894, 2012. View at: Publisher Site | Google Scholar
  86. T. O. Hirche, R. Benabid, G. Deslee et al., “Neutrophil elastase mediates innate host protection against Pseudomonas aeruginosa,” Journal of Immunology, vol. 181, no. 7, pp. 4945–4954, 2008. View at: Google Scholar
  87. Y. S. López-Boado, M. Espinola, S. Bahr, and A. Belaaouaj, “Neutrophil serine proteinases cleave bacterial flagellin, abrogating its host response-inducing activity,” Journal of Immunology, vol. 172, no. 1, pp. 509–515, 2004. View at: Google Scholar
  88. Y. Weinrauch, D. Drujan, S. D. Shapiro, J. Weiss, and A. Zychlinsky, “Neutrophil elastase targets virulence factors of enterobacteria,” Nature, vol. 417, no. 6884, pp. 91–94, 2002. View at: Publisher Site | Google Scholar
  89. A. A. Rehman, H. Ahsan, and F. H. Khan, “Alpha-2-macroglobulin: a physiological guardian,” Journal of Cellular Physiology, vol. 228, no. 8, pp. 1665–1675, 2013. View at: Publisher Site | Google Scholar
  90. M. C. Territo, T. Ganz, M. E. Selsted, and R. Lehrer, “Monocyte-chemotactic activity of defensins from human neutrophils,” Journal of Clinical Investigation, vol. 84, no. 6, pp. 2017–2020, 1989. View at: Google Scholar
  91. D. Yang, Q. Chen, O. Chertov, and J. J. Oppenheim, “Human neutrophil defensins selectively chemoattract naive T and immature dendritic cells,” Journal of Leukocyte Biology, vol. 68, no. 1, pp. 9–14, 2000. View at: Google Scholar

Copyright © 2014 Nuno Rosa 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.

1839 Views | 744 Downloads | 7 Citations
 PDF  Download Citation  Citation
 Download other formatsMore
 Order printed copiesOrder