#### TABLE 1 | Proteins with significant change in WS levels during the inflammatory phase of EG (Day 0 vs. Day 21).

(Continued)

#### TABLE 1 | Continued

periodontal tissue inflammation. The inflammatory response observed during gingivitis is mediated by neutrophils migrating from the blood stream to the gingival tissues and in to the oral cavity through the GCF. We speculate that the increase in oral neutrophil levels during the experimental gingivitis phase is responsible in part for the observed increase in whole saliva cytoprotective proteins. The association between oral neutrophil levels and levels of proteins of interest was tested through correlation analysis during the experimental gingivitis phase (days 0–21), and the healing period which followed (days 28–35). In general, we found moderate to strong correlations between oral neutrophil numbers and levels of several salivary cytoprotective proteins in inflammation and resolution of gingivitis.

Lactotransferrin (also known as lactoferrin) is an iron-binding protein (Brock, 2002; Ammons and Copié, 2013), found in

TABLE 2 | Proteins with significant increase of >2 fold during the inflammatory phase of EG.

Highlighted proteins are proteins considered cytoprotective proteins.

serum and secreted fluids, and also present in specific neutrophil granules (Masson et al., 1969). Its antibacterial properties result from bacteriostatic activity, directly related to its ironchelating capacity; and bactericidal activity, as a result of a direct interaction between the protein and bacteria where the N-terminal region of LTF, known as lactoferricin, can disrupt or possibly even penetrate bacterial cell membranes (Brock, 2002). Anti-biofilm activity of LTF was also demonstrated, as it inhibits biofilm formation and reduces the established biofilm of oral bacteria at physiological concentrations (Wakabayashi et al., 2010; Ammons and Copié, 2013). It has been speculated that LTF inhibits biofilm formation and disrupts existing biofilm by preventing bacterial adhesion or stimulating bacterial motility. Similar to our current findings, significant increase in LTF abundance was previously demonstrated in GCF samples during EG (15). The reported antibacterial and antibiofilm properties of LTF can explain its increased abundance during EG, as an innate protective response to bacterial accumulation. Due to these protective properties, LTF was suggested as a potential treatment for CP (Wakabayashi et al., 2010).

In addition to biofilm control-associated factors, several anti-inflammatory proteins were changed during the course of inflammation-resolution in our EG study. Two inflammation regulating proteins were increased in the inflammatory phase of EG: Annexin A1 and Vitamin D binding protein. Annexins are a family of calcium and phospholipid binding proteins (Gerke and Moss, 2002), which dampen the inflammatory response via inhibition of neutrophil activation (Chatterjee et al., 2005). Annexin A1 levels in GCF were previously demonstrated to be stable during 21 days EG, opposing our current findings (Grant et al., 2010). One possible explanation is that we used WS samples and not GCF samples. Therefore, it is possible that salivary sources contribute to annexin A1 production and its involvement in regulating gingival inflammation.

Vitamin D binding protein (DBP) is a multifunctional protein found in plasma. Its ability to bind to vitamin D (calcitriol) and its metabolites and to transfer them to target cells has a major role in the involvement of vitamin D in inflammatory regulation. Vitamin D was shown to be involved in both the innate and adaptive immune systems, with vitamin D insufficiency being linked to many inflammatory disorders, including periodontal diseases. It has been suggested that vitamin D may act similarly to cytokines, and regulate the inflammatory process by several mechanisms: stimulating phagocytosis and antibody-presenting actions to enhance the initial immune response. As the inflammatory process progresses, vitamin D plays a role in inhibition of T-cell proliferation and thus inflammatory resolution (Stein et al., 2014). DBP itself

were reduced by day 35, 2 weeks after oral hygiene was resumed.

was demonstrated to have significant neutrophil chemotactic activity in vivo where DBP knock-out mice demonstrated significant decreases in neutrophil recruitment to the site of infection when compared to the wild type group. Exogenous addition of DBP was shown to restore neutrophil response (Trujillo et al., 2013). Our observation of increased DBP levels during EG may suggest an increased abundance of vitamin D during this phase. High vitamin D levels were suggested to reduce inflammation during gingivitis (Dietrich et al., 2005).

Increases in oxidative stress, where reactive oxygen species (ROS) levels exceed antioxidant levels, have been shown to directly contribute to periodontal inflammation and connective tissue breakdown during periodontal disease. The antioxidant defense systems have an important role in balancing physiological oxidative stress (Chapple and Matthews, 2007). Total antioxidant capacity (TAC) levels were found to be significantly lower in periodontitis patients when compared to healthy controls (Chapple et al., 2007). Our current findings demonstrate an increase in antioxidant proteins–β-globin and Thioredoxin during the development of EG, suggesting an additional protective mechanism during this reversible phase of periodontal disease.

The globin superfamilies are hemeproteins which can be found in all known life forms. Its common role in O2 transport in vertebrate erythrocytes is recognized as a relatively recent adaptation from its more primative functions in non-erythroid cells, including iron metabolism regulation, intracellular oxygen transport, oxygen sensing, NO scavenging, and hydrogen peroxide scavenging (Vinogradov and Moens, 2008). Several human studies demonstrated that hemoglobin overexpression reduces oxidative stress, suggesting its cytoprotective role as an antioxidant (Liu et al., 2011; Li et al., 2013). Increased β-globin levels were demonstrated in mice macrophages treated with lipopolysaccharide and interferon-γ (Liu et al., 1999). In-line with our current findings, salivary proteome analysis of samples collected from gingivitis patients with gingivitis revealed increase in both α- and βglobin compared to healthy controls (Gonçalves Lda et al., 2011).

Thioredoxin (Trx) is an intra-cellular protein that together with thioredoxin reductase and NADPH, comprises the thioredoxin system. This system has been shown to play a key role in many intra-cellular pathways including H2O2 as a means to reduce oxidative stress (Holmgren and Lu, 2010). The cytoprotective effects of Trx were demonstrated in transgenic mice overexpressing human Trx1 that are resistant to oxidative stress conditions, and are more resistant to inflammation (Yoshida et al., 2005). In humans, increased extracellular Trx levels were reported for various systemic conditions, including rheumatoid arthritis (RA; Maurice et al., 1999). Our current results demonstrate an increase in Trx during EG, supporting its protective role during this reversible inflammatory phase.

Several proteolytic enzymes have been demonstrated to play a key role in periodontal tissue destruction. The main sources for these enzymes are the neutrophils that populate the periodontal pocket and produce proteolytic enzymes as part of the non-oxidative killing function (Meyer-Hoffert and Wiedow, 2011). We identified a significant increase in the protease inhibitor proteins Cystatin SN and Cystatin S during EG. Cystatins SN and S were first identified in saliva, and have been identified in other secreted fluids. Their production in secretory glands suggests their role as cytoprotective inhibitors of exogenous cysteine peptidases (Abrahamson et al., 2003). Cystatin S levels in GCF have been demonstrated to be stable during the 21 days EG model, which once again is in contrast

to our current findings (Grant et al., 2010). In a different study, GCF proteome analysis reported decrease in cystatin S abundance in GCF samples obtained from GI patients (Huynh et al., 2014). Salivary glands contribute to cystatin S production, which can explain the differences in our analysis of WS samples, as opposed to GCF samples. In support of our findings, cystatin activity was demonstrated to increase in WS samples obtained from GI patients (Henskens et al., 1993), as well as in inflamed gingival tissues (Babnik et al., 1988).

The increase in cytoprotective proteins during the development of EG, suggests that production of proteins that can dampen the effector proteins involved in the inflammatory process is important during inflammatory diseases including GI (**Figures 3**, **4**). Similar findings were reported in a human tears study, which demonstrated increase in cystatin S and lactotransferrin levels in tears collected from patients with autoimmune conditions (Katunuma et al., 2003). Interestingly, reduced levels of several of these cytoprotective proteins were previously reported in patients diagnosed with CP. Reduced cystatins (S, SN, SA) levels were previously reported in WS samples obtained from CP patients when compared to healthy controls (Henskens et al., 1996; Ito et al., 2008; Gonçalves Lda et al., 2010). Reports of LTF levels during CP were inconsistent: WS proteome analysis demonstrated a 2-fold increase in LTF levels when compared to healthy controls (Salazar et al., 2013). Contrary to this report, low levels of LTF were demonstrated in WS samples obtained from patients diagnosed with Aggregatibacter actinomycetemcomitans-associated periodontitis (Groenink et al., 1999), and in WS samples obtained from patients diagnosed with generalized aggressive periodontitis (GAgP) when compared to healthy controls (Wu et al., 2009). The same study also showed increased vitamin D binding protein levels in GAgP patients when compared to healthy controls (Wu et al., 2009).

Several theories may explain the reduced levels of protective proteins during CP: as the inflammatory process progresses, increased levels of endogenous and exogenous ROS and proteases may lead to damage of the cytoprotective proteins. A second theory suggests that once bacterial and inflammatory overload reach a specific threshold, the cytoprotective mechanisms are reduced. This threshold can vary between subjects, and may be responsible for the observed variability in the development of CP among subjects. The findings of the present study demonstrate that in the initial inflammatory phase of GI levels of salivary cytoprotective proteins are increased and that they decrease as inflammation resolves.

## CONCLUSIONS

We were able to demonstrate in the current pilot study a significant increase in several cytoprotective proteins during the inflammatory phase of GI. Further, we found that levels of these proteins decreased in the healing phase of GI indicating a doseresponse relationship with gingival inflammation-resolution. The increase in cytoprotective proteins in onset of GI may prevent periodontal tissue destruction and clinical attachment loss in patients at risk of developing CP due to other host and environmental factors. Future studies to investigate whether these proteins can serve as biomarkers for GI progression to CP are necessary.

### AUTHOR CONTRIBUTIONS

GA, CS, WS, MG contributed to conception or design. GA, CS, WS, MG, YX, EM, KC contributed to acquisition, analysis, or interpretation. GA, CS, WS, MG drafted the

### REFERENCES

manuscript. GA, CS, WS, MG, YX, EM, KC critically revised the manuscript. GA, CS, WS, MG, YX, EM, KC gave final approval. GA, CS, WS, MG, YX, EM, KC agrees to be accountable for all aspects of work ensuring integrity and accuracy.

#### ACKNOWLEDGMENTS

The authors would like to give special thanks to Ricky Livay-Shakked (Matrix Dynamics Group, Faculty of Dentistry, University of Toronto). Research funds provided by Canadian Institute for Health Research (CIHR) grants to MG (grant number #122068) and to WLS grant number #97577; Canadian Foundation for Innovation (CFI-LOF grant to WLS); Harron scholarship, Faculty of Dentistry, University of Toronto; Department of Periodontology, Faculty of Dentistry, University of Toronto; and the Alpha Omega Foundation of Canada. WLS is recipient of a CIHR New Investigator Award grant#113166.

in periodontal health and disease. J. Periodontal Res. 50, 330–336. doi: 10.1111/jre.12211

of whole human saliva by mass spectrometric analysis. J. Clin. Periodontol. 40, 825–832. doi: 10.1111/jcpe.12130

**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2016 Aboodi, Sima, Moffa, Crosara, Xiao, Siqueira and Glogauer. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

# Salivary markers of oxidative stress in oral diseases

L'ubomíra Tóthová1, 2, Natália Kamodyová1 , Tomáš Cervenka ˇ 1 and Peter Celec1, 2, 3, 4 \*

1 Institute of Molecular Biomedicine, Faculty of Medicine, Comenius University, Bratislava, Slovakia, 2 Center for Molecular Medicine, Slovak Academy of Sciences, Bratislava, Slovakia, 3 Department of Molecular Biology, Faculty of Natural Sciences, Comenius University, Bratislava, Slovakia, 4 Institute of Pathophysiology, Faculty of Medicine, Comenius University, Bratislava, Slovakia

Saliva is an interesting alternative diagnostic body fluid with several specific advantages over blood. These include non-invasive and easy collection and related possibility to do repeated sampling. One of the obstacles that hinders the wider use of saliva for diagnosis and monitoring of systemic diseases is its composition, which is affected by local oral status. However, this issue makes saliva very interesting for clinical biochemistry of oral diseases. Periodontitis, caries, oral precancerosis, and other local oral pathologies are associated with oxidative stress. Several markers of lipid peroxidation, protein oxidation and DNA damage induced by reactive oxygen species can be measured in saliva. Clinical studies have shown an association with oral pathologies at least for some of the established salivary markers of oxidative stress. This association is currently limited to the population level and none of the widely used markers can be applied for individual diagnostics. Oxidative stress seems to be of local oral origin, but it is currently unclear whether it is caused by an overproduction of reactive oxygen species due to inflammation or by the lack of antioxidants. Interventional studies, both, in experimental animals as well as humans indicate that antioxidant treatment could prevent or slow-down the progress of periodontitis. This makes the potential clinical use of salivary markers of oxidative stress even more attractive. This review summarizes basic information on the most commonly used salivary markers of oxidative damage, antioxidant status, and carbonyl stress and the studies analyzing these markers in patients with caries or periodontitis.

#### Edited by:

Ulvi Kahraman Gürsoy, University of Turku, Finland

#### Reviewed by:

Fares Zeidán-Chuliá, Universidade Federal do Rio Grande do Sul, Brazil Daisuke Ekuni, Okayama University, Japan

> \*Correspondence: Peter Celec<EMAIL_ADDRESS>
Received: 01 September 2015 Accepted: 02 October 2015 Published: 20 October 2015

#### Citation:

Tóthová L', Kamodyová N, Cervenka T ˇ and Celec P (2015) Salivary markers of oxidative stress in oral diseases. Front. Cell. Infect. Microbiol. 5:73. doi: 10.3389/fcimb.2015.00073

Keywords: saliva, biomarkers, oxidative stress, antioxidant status, oral diseases

### INTRODUCTION

Saliva has become a popular diagnostic fluid for research and clinics in recent years. Its availability, easy collection and possibility of repeated non-invasive sampling makes it ideal for screening, diagnosis, or monitoring of many diseases. However, many technical issues have to be overcome and sensitivity as well as specificity have to be increased before routine clinical use. Several articles have been published dealing with saliva and its diagnostic potential in the past (Kaufman and Lamster, 2002; Chiappin et al., 2007; Lee and Wong, 2009). One review article has summarized the literature on oxidative stress in oral cavity-related pathologies. However, the review was not specifically oriented on oxidative stress in saliva (Iannitti et al., 2012). One critical review on this topic has been published recently, but was mainly focused on the methodology and statistical analysis used in the published studies (Wang et al., 2015a).

Periodontitis and dental caries represent the most common oral diseases. Very often, low adherence to oral hygiene and follow-up treatment lead to worsening of the disease and subsequently to loss of teeth (Renz et al., 2007). A noninvasive approach to diagnose and to monitor the progress of periodontitis and dental caries is needed that would improve the adherence and the overall therapeutic outcome. This review therefore aims to summarize the current findings in the research of oxidative stress analyzed in saliva in relation to oral diseases.

### SALIVA AS A DIAGNOSTIC FLUID

Saliva is produced by secretion from the three major salivary glands (the parotid, submandibular, and sublingual glands) and numerous minor salivary glands. The collected whole saliva is a more complex mixture of fluids including gingival cevicular fluid, as well as oral, nasal, and mucosal transudate (Humphrey and Williamson, 2001). Additionally, oral bacteria and their metabolites, desquamated epithelial and blood cells, food debris and various chemical products are present in the saliva (de Almeida Pdel et al., 2008). Daily saliva production is estimated to be between 0.75 and 1.5 L in healthy adults. Salivary secretion is under both neural and hormonal control (Proctor and Carpenter, 2007). Nevertheless, salivary flow rate can be affected by various factors, such as circadian cycle, age, hydratation, chewing, oral hygiene, physical exercise, and others (Dawes, 1972; Chicharro et al., 1998; Chiappin et al., 2007; de Almeida Pdel et al., 2008).

Physiologial pH of saliva is between 6.2 and 7.4 (Schipper et al., 2007). From biochemical point of view, saliva is an aqueous solution (more than 99% is water) containing numerous organic and anorganic molecules (Greabu et al., 2009; Lima et al., 2010). Saliva may reflect the current physiological condition of the body and therefore is often called "the mirror of health of the organism" (Farnaud et al., 2010; Yoshizawa et al., 2013). The exchange between plasma and saliva takes place in the salivary ducts, which are separated from the circulation system as a thin layer of epithelial cells. The exchange includes active transport, diffusion across the cell membrane by passive diffusion directed by the concentration gradient (Lee and Wong, 2009). In patients suffering from oral diseases such as periodontitis there is a higher probability of blood leakage into saliva. This leads to the occurrence of blood components in saliva (Schwartz and Granger, 2004). This could interfere with various analytical methods and, thus, hinder the diagnostic use of saliva. However, at least for some of the most commonly used markers of oxidative stress we have found that blood contamination up to 1% does not affect even spectrophotometric methods and samples with higher blood concentrations can easily be excluded (Kamodyová et al., 2015). Since saliva represents a rapidly changing dynamic environment, it can potentially be used for long-term monitoring of oral diseases. In addition, new high-throughput approaches are being introduced for fast, reliable, and reproducible salivary diagnostic tests. Research on saliva cannot escape the current technological revolution. The whole salivary metabolome has already been described using several methodological approaches (Dame et al., 2015).

Similarly to plasma and tissues, free radicals and reactive oxygen/nitrogen species (ROS/RNS) in saliva play an important role in redox-dependent signaling and are necessary for physiological functions (Valko et al., 2007). On the other hand, excessive production of free radicals can lead to oxidative stress (Sies, 1997). Redox balance is than shifted in favor of oxidants. ROS/RNS can induce oxidative damage to cellular components with serious pathophysiological consequences (Devasagayam et al., 2004). On contrary, various antioxidant mechanisms are present in saliva including low molecular antioxidants glutathione, ascorbic, and uric acid as well as melatonin (Moore et al., 1994; Balaji et al., 2015). Antioxidant enzymes such as superoxide dismutase, catalase, and glutathione peroxidase are present in saliva (Battino et al., 2002). Their function is to protect oral cavity against the negative effects of endogenous and exogenous ROS/RNS. Additionally, membrane and DNA repair enzymes as well as proteases that degrade oxidatively modified proteins reduce the consequences of oxidative damage in saliva. Saliva is intended to be the first line defense against free radicals (Amerongen and Veerman, 2002; Battino et al., 2002). The dysbalance between the production of free radicals and antioxidant status in favor of oxidants is called oxidative stress. Oxidative stress has been implicated in the etiology and pathogenesis of several oral diseases including dental caries and periodontitis (Iannitti et al., 2012). This has already been shown by expression analysis of antioxidant genes in periodontitis patients (Zeidan-Chulia et al., 2013). Although it is not clear whether it is a cause or consequence of the disease process.

### SALIVARY BIOMARKERS OF OXIDATIVE, CARBONYL STRESS, AND ANTIOXIDANT STATUS

Biomarkers are any characteristics which can be objectively measured and allow to predict the diagnosis, onset, or progression of a disease (Maiese et al., 2010). Optimal biomarkers for diagnostics of oxidative stress related diseases should be stable, accumulated in detectable concentrations, reflect specific oxidation pathways, and correlate with disease severity (Dalle-Donne et al., 2006). Considering free radicals are highly reactive and have a short half-life, the products formed from the reaction of ROS/RNS with cellular macromolecules are used preferentially as biomarkers of oxidative damage (Palmieri and Sblendorio, 2007a,b). Lipid peroxidation products, oxidized proteins, and products of DNA oxidation and fragmentation—are used for the assessment of oxidative stress. Measurement of various antioxidants or total antioxidant status represent another option of analyzing the redox status. Nevertheless, the use of a panel of biomarkers instead of a single parameter provides more informative results, reduces false positive and false negative results and enables a better understanding of the underlying pathomechanisms. The recent technological advances enabled the progress in systems biology and saliva research is moving into the omics world. Also using the metabolomic approach markers of oxidative stress were found to be among the discriminative between patients with periodontitis and healthy controls (Barnes et al., 2014). This confirms that the research of salivary markers of oxidative stress is worth the effort.

### Lipid Peroxidation

Lipid peroxidation is a reaction of lipids such as polyunsaturated fatty acids with ROS/RNS leading to formation of lipid hydroperoxides. This is accompanied by a complex process of degradation and decomposition reactions of hydroperoxides, whereby a wide range of products is formed (Dotan et al., 2004; Palmieri and Sblendorio, 2007a). The endproducts of lipid peroxidation are more stable than free radicals. Additionally, they can further react with other macromolecules, including DNA, proteins and phospholipids, far from the site of their production (Dalle-Donne et al., 2006). The most studied marker of lipid peroxidation is malondialdehyde (MDA). MDA is produced from fatty acids with two or more methylene-interrupted double bonds (Ayala et al., 2014). Standard method used for MDA detection is the spectrophotometric assay developed by Yagi, which is based on the reaction with thiobarbituric acid in acidic environment. It is also referred to as thiobarbituric acid reacting substances (TBARS) assay (Yagi, 1976). This assay is not specific for MDA and other aldehydes may react with thiobarbituric acid to produce a compound that absorbs wavelengths in the same range as MDA. Liquid chromatography or mass spectroscopy methods were reported as more reliable and specific for the measurement of MDA (Akalin et al., 2007), but the TBARS assay still represents a commonly used, cheap and high throughput method for the quantitative analysis of lipid peroxidation.

Another marker produced during lipid peroxidation is 4 hydroxy-2-nonenal that is generated by free radical attack on ω—6 polyunsaturated fatty acids (arachidonic, linoleic, and linolenic acids) (Sayre et al., 2006). Isoprostanes are unique products of lipid peroxidation of arachidonic acid and are considered to be reliable biomarkers of free radical mediated lipid peroxidation in vivo (Devasagayam et al., 2004; Spickett, 2013). Conjugated dienes are another option for analysis of lipid peroxidation. Unfortunately, few studies dealt with several of these markers, so the data about their usefulness for oral disease monitoring are limited.

### Protein Oxidation

Proteins are major targets for ROS/RNS because they are highly abundant and are responsible for most functional processes in the cell (Dalle-Donne et al., 2003). The oxidation of proteins can take place at the level of single amino acid residues, it can lead to fragmentation of polypeptide chains or to covalent crosslinking of two amino acids either of the same or of two different proteins (Shacter, 2000). Oxidized proteins are either catabolized in proteosomal and lysosomal pathways or aggregated and accumulated in cellular compartments (Stadtman and Berlett, 1998).

Widespread methods for assessment of protein oxidation are the measurement of carbonyl groups by specific antibodies in ELISA or Western blot and by spectrophotometric assay based on dinitrophenylhydrazine derivitization (Dalle-Donne et al., 2003; Cabiscol et al., 2014). The advantages of protein carbonyls as a marker in comparison to lipid peroxidation products include early production and greater stability of oxidized proteins. Nonetheless, the production of protein carbonyl groups can be induced by almost all types of ROS and so, the protein carbonyl assay does not provide information about the source of oxidative stress. A major factors influencing most biomarkers of oxidative stress and protein carbonyl especially is aging. The relatively high correlation coefficients between salivary carbonyls and age led to a suggestion of protein carbonyls as an alternative biomarker of aging (Wang et al., 2015b).

Advanced oxidation protein products (AOPP) represent a sensitive biomarker of protein oxidation, especially due to neutrophil activation and the enzymatic activity of myeloperoxidase (Witko-Sarsat et al., 1996). AOPP were formerly thought to be a novel uremic toxin, reflecting highly oxidized protein status, but oxidized fibrinogen was found to be the major molecule responsible for the increase of the AOPP concentration (Selmeci, 2011). This should be taken into account, when interpreting the results.

### Oxidative DNA Damage

The ROS/RNS react with DNA inducing damage to purine and pyrimidine bases and also the deoxyribose backbone (Halliwell, 2000). Pyrimidine damage products include thymine glycol, uracil glycol, urea residue, 5-hydroxydeoxyuridine, 5-hydroxydeoxycytidine, hydantoin, and others. Purine damage products are 8-hydroxydeoxyguanosine (8-OHdG), 8-hydroxydeoxyadenosine, formamidopyrimidines, and other less characterized purine oxidative products (Cadet et al., 2003).

Measurement of 8-OHdG has been used to assess "wholebody" oxidative DNA damage using various analytical methods (Henderson et al., 2010). The issue with measuring 8-OHdG concentration is that 8-OHdG may not truly reflect oxidative damage to DNA. 8-OHdG can arise not just from removal of oxidized guanine residues from DNA by repair processes but also from degradation of oxidized dGTP in the DNA precursor pool. Recently published data, however, show that there is a clear strong association between the salivary concentrations of 8- OHdG and the clinical indices of periodontal status (Villa-Correa et al., 2015).

### Carbonyl Stress

Carbohydrates such as glucose react non-enzymatically with the free amino groups of proteins and proceeds from reversible Schiff base adducts to more stable Amadori products. Some Amadori products are further converted to advanced glycation end products (AGEs) through a series of chemical rearrangements, dehydration, and fragmentation reactions (Ott et al., 2014). In addition to endogenously formed, AGEs can also be derived from exogenous sources such as smoking and food (Singh et al., 2001; Nass et al., 2007). Carbonyl precursors can form oxidative AGEs such as Nε -(carboxymethyl)lysine and pentosidine or non-oxidative AGEs such as 3-deoxyglucosone or methylglyoxal (Singh et al., 2001). Pentosidine is derived exclusively from carbohydrate-derived carbonyl group and protein amino group while Nε -(carboxymethyl)lysine originates not only from carbohydrates but also from autooxidation of lipids and amino acids (Zoccali et al., 2000). Nε -(carboxymethyl)lysine therefore serves as a general biomarker of oxidative stress, mostly assessed by ELISA or Western blotting.

AGEs are a heterogeneous group of protein-bound moieties and are characterized by browning, fluorescence, and crosslinking. Their determination is based on detection of specific fluorescence of AGEs at 370 nm excitation and 440 nm emission (Münch et al., 1997). Other methods such as ELISA, polyclonal antibodies, HPLC, or immunohistochemistry have been also applied to determine specific AGEs (Ahmed et al., 2002; Lapolla et al., 2005; Schmitt et al., 2005). Measurement of non-enzymatically glycated total proteins is referred to as fructosamine assay (Armbruster, 1987). Glucose bound to protein by aldimine linkage undergoes Amadori rearrangement through nonenzymatic glycation to the ketoamine (generically termed fructosamine). Fructosamine spectrophotometric assay is a simple test based upon the property of fructosamines to act as reducing agents in alkaline solution (San-Gil et al., 1985).

#### Nitrosative Stress

Similarly to oxidative stress, nitrosative stress is characterized as the imbalance between reactive nitrogen species and the antioxidants in favor of pro-oxidant RNS. Immoderate/excessive production of nitric oxide (NO) have detrimental effects on biomacromolecules. Due to its highly reactive nature, NO reacts with other reactive species (i.e., superoxide) leading to formation of more reactive compounds resulting in cytotoxic effects (Eiserich et al., 1998). On the other hand, NO can be oxidized to nitrite (NO− 2 ) and subsequently oxidized to nitrate (NO− 3 ). Therefore, the total concentrations of nitrite and nitrate are summed to adequately determine complex NO production. Salivary nitrates/nitrites are measured by Gries colorimetric assay (Andrukhov et al., 2013). Salivary NO and its derivates have been studied in relation to plasma NO, endothelial function, dietary intake of NO donors etc. However, most of the analyzed correlations were not significant (Clodfelter et al., 2015). Although the test was originally developed to help cardiologists, it is clear that the salivary NO concentrations are most affected by local oral processes and could, thus, be more usable for dentists and their patients.

### Antioxidant Status

The measurement of individual antioxidants in biological samples is time consuming, labor-intensive, costly and requires complicated chemical techniques. In addition, the antioxidant effects are additive and therefore total antioxidant capacity of samples is preferentially measured (Erel, 2004). Antioxidant capacity assays can be divided into assays involving oxidants that are not necessarily pro-oxidants and assays involving oxidants that are pro-oxidants (Prior and Cao, 1999). To the first group of assays belong for example the ferric reducing/antioxidant power (FRAP) assay and the Trolox equivalent antioxidant capacity. The second group of assays includes total radical trapping parameter assay, luminolbased assays, dichlorofluorescin-diacetate based assay, crocin based assays, phycoerythrin based assays, and oxygen radical absorbance capacity assay (Prior and Cao, 1999). The increased antioxidant capacity can be a consequence of an adaptive response to a long term increased oxidative stress. On the other hand, the decrease in antioxidant capacity is not necessarily an undesirable condition when the production of reactive species decreases. The results of antioxidant assays should therefore be interpreted with caution.

### SALIVARY OXIDATIVE STRESS IN ORAL DISEASES

### Dental Caries

Dental caries is the most prevalent oral disease worldwide affecting both, children and adults and leading to pain and tooth loss. Systematic review dealing with the pathogenesis, epidemiology, diagnosis, and treatment of dental caries was published previously (Selwitz et al., 2007). Dental caries is a multifactorial inflammatory disease. However, the primary trigger is usually acidic by-products formed during bacterial fermentation of carbohydrates (Selwitz et al., 2007). In a recent review, the concept of inflammatory response in dentin, tightly connected with oxidative stress leading to the destruction of dental hard tissues is discussed (Southward, 2011). It was shown that dentinal fluid movement is inhibited by high sucrose levels causing down-regulation of parotid hormone from hypothalamic signaling. The consequence is that teeth become susceptible to bacterial acids (Leonora et al., 1993). The important role of ROS and antioxidants on the regulation of parotid hormone was hypothesized in a review dealing with the systemic theory of dental caries (Southward, 2011).

The importance of saliva in terms of salivary flow and antibacterial protection is generally accepted for the pathogenesis of dental caries (Lenander-Lumikari and Loimaranta, 2000; Stookey, 2008). The role of oxidative stress in dental caries is less clear, but it is the focus of intense research. Nine studies performed on children and four studies performed on adult subjects analyzing salivary oxidative stress in relation to dental caries are summarized in **Table 1**. Most research dealing with salivary oxidative stress in relation to dental caries is analyzing the antioxidant properties of saliva. Tulunoglu et al. have measured the antioxidant capacity of saliva in 80 children with and without caries activity (Tulunoglu et al., 2006). Children were divided into 8 groups according to age, gender, and caries activity. Non-significantly higher TAC was observed in caries active children and this observation was attributed to higher protein concentrations in caries active children. The exception was the group of 11–15 years old girls, where total protein and antioxidant capacity were lower in caries active group (Tulunoglu et al., 2006). In a very similar study TAC was analyzed in 120 children with and without caries activity (Preethi et al., 2010). Similarly to the previous study, children were divided into 8 groups. TAC was significantly higher in caries active girls and also boys in comparison to age matched control subjects. Total proteins were significantly higher in caries active in comparison to caries free children (Preethi et al., 2010; Dodwad et al., 2011). In the next study, relationship between the total antioxidant capacity of saliva and dental caries was assessed in deciduous and permanent teeth of Saharan children (Uberos et al., 2008).

This study is one of the largest focusing on caries and salivary markers of antioxidant status. The authors have found a higher TAC in deciduous teeth of caries active patients than of caries free patients. Linear association was observed between the number of deciduous, but not permanent teeth affected by caries and TAC (Uberos et al., 2008). Hegde et al. and Kumar et al. have found that TAC in children with early childhood caries is higher than in controls with age being a significant confounding factor (Hegde et al., 2009; Kumar et al., 2011). The results were confirmed in another study in very young children (Muchandi et al., 2015). In a case-control study performed on 80 children FRAP as a measure of antioxidant status higher in children with caries (Mahjoub et al., 2014). Similarly, TAC was higher in adolescent males with active caries (Ahmadi-Motamayel et al., 2013). The reason for the higher antioxidant status in all studies remains unclear. A likely mechanism could include the response of the host to an infection/inflammation. All above mentioned studies had a case-control design. The study conducted by Tóthová et al. had a cross-sectional design with 82 children (4–18 years old) (Tóthová et al., 2013a). In this study beyond salivary antioxidant status (TAC and FRAP) also oxidative stress markers were analyzed in relation to caries index in children. These included TBARS, AOPP, and AGEs. Multivariate analysis showed that salivary AOPP are related to caries index (eta 8.6%), however ANOVA revealed no significant association between CI and AOPP (Tóthová et al., 2013a).

The study conducted in adults by Öztürk et al. was the first study analyzing the role of salivary glutathione (GSH) as an antioxidant in relation to dental caries (Oztürk et al., 2008). Significantly lower GSH concentrations were detected in adults with caries compared to subjects without caries and a negative correlation was observed between clinical indices and GSH. In this study no difference in lipid peroxidation was observed between subjects with and without caries (Oztürk et al., 2008). Rai et al. have analyzed TBARS in the saliva of caries active patients. Higher lipid peroxidation was detected in caries active patients than in control patients (Rai et al., 2006). Ahmadi-Motamayel et al. have analyzed TAC in caries active and caries free students (Ahmadi-Motamayel et al., 2013). In this study higher TAC was found in the group with caries, especially in males. Subtle gender differences were indicated by lower TAC in caries active females than in caries active males (Ahmadi-Motamayel et al., 2013). The association between TAC and caries severity was confirmed later (Hegde et al., 2013).

Most of the studies found that the antioxidant status is higher in caries active probands. As emphasized by Prior and Cao, an increased antioxidant capacity may be an adaptive response to increased oxidative stress (Prior and Cao, 1999). On the other hand, decreased GSH levels could suggest a tendency to decreased antioxidant status (Oztürk et al., 2008). The contradictory findings could be partially explained by temporal differences. As an acute effect the antioxidant status could be increased, but long term effects could contribute to consumption of antioxidants. It is clear that a panel of oxidative stress and antioxidant status markers is needed to interpret the role of oxidative stress in disease pathogenesis and progression (Prior and Cao, 1999). The only study in which a panel of salivary oxidative stress and antioxidant status markers was analyzed was the study conducted in children by Tóthová et al. (2013a). Although association studies have a clear outcome, there is a lack of mechanistic studies on the role of ROS or oxidative damage in saliva in relation to dental caries. Based on previous studies, it appears that there is no association between salivary lipid peroxidation and dental caries (Rai et al., 2006; Oztürk et al., 2008; Tóthová et al., 2013a). However, to interpret the relationship between dental caries and oxidative stress in saliva it is necessary to perform more carefully designed studies incorporating whole palette of oxidative stress and antioxidant status markers and, more importantly, experimental animal studies focusing on the underlying mechanism associated with ROS/RNS.

### Periodontal Diseases

Periodontitis is affecting 11% of the global population (Marcenes et al., 2013). Its incidence varies in different populations and depends on oral hygiene and socio-economic status (Rylev and Kilian, 2008). Periodontitis is a chronic infectious disease of the supporting tissues of teeth and can lead to loss of connective tissue attachment, alveolar bone resorption, increased mobility of teeth and subsequent teeth loss. The etiology and pathogenesis of periodontitis is multifactorial and includes periodontal pathogens, biofilm formation, host immune response, and genetic risk factors (Laine et al., 2012).

The production of proteolytic enzymes and the respiratory burst of neutrophils mediated by enzymes such as NADPH oxidase and myeloperoxidase lead to generation of ROS/RNS and induce oxidative stress (Nizam et al., 2014; Syndergaard et al., 2014). These mechanisms play a key role in the pathogenesis of periodontitis as summarized by Chapple and Matthews in their comprehensive review (Chapple and Matthews, 2007). Salivary myeloperoxidase was found to be higher in periodontitis patients (Meschiari et al., 2013). The most common parameters of oxidative damage in association to periodontal diseases are markers of lipid peroxidation. Tsai et al. found higher lipid peroxidation in saliva of chronic periodontitis patients in a casecontrol study. An important secondary finding was that lipid peroxidation in saliva and gingival crevicular fluid correlated positively (Tsai et al., 2005). The association between periodontal status and salivary TBARS was confirmed in our large crosssectional study with 217 patients (Celec et al., 2005). In a preliminary part of this study we found no correlation between salivary and plasma TBARS and, thus, local intraoral production of TBARS was hypothesized (Celec et al., 2005). Other studies confirmed higher lipid peroxidation in patients with severe but not moderate periodontitis (Mashayekhi et al., 2005; Khalili and Biloklytska, 2008) suggesting that the association between periodontitis and salivary TBARS might not be linear (Dalai et al., 2013). More recently, male patients, but not women with chronic periodontitis showed higher concentrations of salivary TBARS compared to healthy controls (Banasová et al., 2015). This could be due to changes in the changes in salivary cytokines during the menstrual cycle (Becerik et al., 2010). However, menstrual cycle related changes in salivary TAC concentrations have also been described with lower TAC during the ovulation period

(Kawamoto et al., 2012). In line with these findings are the results of unique study on pregnant women. It has been shown that pregnancy has an effect on several markers of oxidative stress and, more importantly, that the association between TBARS and periodontal status found in the general population could not be proved for pregnant women or women who gave birth recently (Gümüs et al., 2015). This is very likely related to the hormonal changes in pregnancy that have major impact on oral health and local immune status (Gürsoy et al., 2014).

MDA is the most studied product of lipid peroxidation. However, MDA is only one of many products formed during lipid peroxidation. TOS assay developed by Erel provides a possibility to measure additive effects of oxidants (Erel, 2005). Akalin et al. utilized TOS assay to measure oxidants in saliva of chronic periodontitis patients. Higher MDA and TOS levels were observed in saliva and also gingival crevicular fluid of chronic periodontitis patients (Akalin et al., 2007). The importance of lipid peroxidation in saliva was confirmed in another showing that the lipid peroxidation in saliva of patients who smoke and suffer from periodontitis is higher when compared to healthy probands (Guentsch et al., 2008). Increased oxidative damage of DNA, lipids and proteins were observed in periodontitis patients in a cross-sectional study (Su et al., 2009). In our crosssectional study with more than 200 participants salivary TBARS, AOPP, AGEs, and TAC were assessed in relation to dental health, gender, and age (Celecová et al., 2013). We have found a strong association between TBARS and papillary bleeding index and confirmed the results from a previous study (Celec et al., 2005). Moreover, it was shown that this association is age independent. Only TBARS and no other analyzed markers of oxidative stress were associated with periodontitis (Celecová et al., 2013). When MDA was assessed using HPLC periodontitis patients had higher MDA in gingival crevicular fluid but not in saliva (Wei et al., 2010). These results are in accordance with our results showing that salivary TBARS other than MDA are associated with periodontitis (Celec et al., 2005). On the other hand, superoxide dismutase and TOS levels were higher in periodontitis patients in both, gingival crevicular fluid and saliva. In addition, 16 weeks of non-surgical treatment decreased lipid peroxidation. Significant positive correlations were observed between clinical indices and MDA, TOS, and superoxide dismutase levels in both oral fluids (Wei et al., 2010). Scaling and root planing resulted in an increase in TAC, uric acid, and glutathione peroxidase, but also in a decrease in superoxide dismutase activity (Novakovic et al., 2014). This finding has been further strengthened by mass spectrometry analysis of ions in patients with periodontitis where Cu, Zn, and Mn ions—all important for superoxide dismutase isoforms were lower in patients vs. controls. In line are the found higher concentrations of isoprostanes as a consequence of lipid peroxidation (Huang et al., 2014). Several authors have assumed that higher lipid peroxidation in saliva is associated with increased percentage of gingival crevicular fluid in the saliva of periodontitis patients (Akalin et al., 2007; Su et al., 2009; Wei et al., 2010). Lipid peroxidation products in saliva might arise from ROS/RNS production by neutrophils activated by periodontal pathogens (Chapple and Matthews, 2007) or from direct microbial production of ROS/RNS (Vlková and Celec, 2009). Especially DNA damage markers seem to be associated with the presence and abundance of specific periodontal pathogens (Almerich-Silla et al., 2015).

Salivary 8-OHdG as a marker of DNA damage was higher in periodontitis patients in comparison to controls (Novakovic et al., 2013) but not in gingivitis patients (Sezer et al., 2012). Higher concentrations of salivary 8-OHdG in periodontal diseases were found also in several other studies (Takane et al., 2002; Sawamoto et al., 2005; Canakçi et al., 2009; Su et al., 2009; Novakovic et al., 2013; Miricescu et al., 2014). Initial periodontal therapy led to a decrease in salivary 8-OHdG. Thus, 8-OHdG could become a useful biomarker for evaluating the efficacy of periodontal treatment and individual prognosis (Takane et al., 2002, 2005). In another study, however, these findings could not be confirmed (Dede et al., 2013). Some studies have found a correlation between salivary 8-OHdG and the presence of Porphyromonas gingivalis or the large mitochondrial DNA deletion in gingival tissues (Canakçi et al., 2009).

Oxidative damage to proteins may have dangerous consequences in a cell due to their important catalytic functions (Dalle-Donne et al., 2003). Protein carbonyl content is the most widely used marker of protein oxidation (Sezer et al., 2012). It is associated with clinical indices of oral health, especially if gender of the patients is taken into account (Sculley and Langley-Evans, 2003). This has been confirmed in another study focusing on the prognostic potential of specifically oxidized salivary proteins such as transferrin, human IgG1 heavy chain fragment and amylase (Su et al., 2009). AOPP was originally suggested as a marker of oxidative damage in plasma of chronic uremic patients (Witko-Sarsat et al., 1996). Only two studies coming from our group have analyzed AOPP in saliva in relation to periodontal status. However, we have found an association between salivary AOPP and papillary bleeding index neither in adults (Celecová et al., 2013) nor in children (Tóthová et al., 2013a). Oxidative and carbonyl stress are closely linked. Reactive carbonyl groups can non-enzymatically react with amino groups of proteins leading to the production of AGEs. Lipid peroxidation products including MDA possess reactive carbonyl groups and can substitute carbohydrates in the Maillard reaction as the basis of AGEs production (Miyata et al., 2000). Similarly to AOPP, salivary AGEs were not associated with periodontal status in any of the studied group of patients (Celecová et al., 2013; Tóthová et al., 2013a).

Relatively few studies examined the concentrations of salivary NO in patients with gingivitis or periodontitis. Most of them observed higher NO concentrations depending on the periodontitis severity when compared to healthy controls (Reher et al., 2007; Parwani et al., 2012; Sundar et al., 2013; Wadhwa et al., 2013; Poorsattar Bejeh-Mir et al., 2014), but NO was decreased by the treatment (Parwani et al., 2012). Interestingly, in another study nitrite concentrations were lowered by treatment only in erythrocytes and not in plasma or saliva (Meschiari et al., 2015). Salivary concentrations of NO can be altered by other factors, especially smoking. Some studies, however, found lower salivary NO in patients with periodontitis compared to the healthy controls (Aurer et al., 2001; Andrukhov et al., 2013). The reasons for these discrepancies might include differences in the analytical methods, but also in the pre-analytic phase.

Similar reasons could explain some of the contradictory findings on TAC (Chapple and Matthews, 2007). In most of the studies TAC was found to be lower in patients with periodontitis (Chapple, 1997; Diab-Ladki et al., 2003; Mashayekhi et al., 2005). This has been confirmed by another study, while the three main specific salivary antioxidants assessed—uric acid, ascorbic acid, and albumin were not significantly different from controls (Diab-Ladki et al., 2003). A study focusing on the antioxidant melatonin found that neither plasma, nor salivary concentrations were different between patients and controls. The difference with lower concentrations for patients was found in the gingival tissue showing that saliva is not representative for all analyzed markers in the oral cavity (Balaji et al., 2015). Mashayekhi et al. have shown that TAC depends on the clinical severity of periodontitis. In addition, the role of cyclic nucleotides cAMP and cGMP, which were lower in patients vs. controls was highlighted in this study (Mashayekhi et al., 2005). Two other studies, however, found no difference between patients and controls in salivary TAC (Brock et al., 2004; Tóthová et al., 2013b). In contrast, higher salivary TAC was observed in periodontitis patients in a crosssectional study (Su et al., 2009). Patients with periodontitis in that study were, however, older and consumed higher amounts of antioxidants than controls. Nevertheless, after adjusting for age and antioxidant intake, the multivariate analysis showed positive correlation between salivary TAC and periodontitis (Su et al., 2009). The crucial difference might, thus, lie in the dynamics of the disease that could differ between studies and is rarely reported. There might be also an often overlooked sex difference in salivary TAC being lower in women (Sculley and Langley-Evans, 2003). Miricescu et al. have reported lower salivary TAC and also uric acid as well as glutathione peroxidase in whole saliva of patients with periodontitis (Novakovic et al., 2013). In other studies lower salivary glutathione—the main intracellular antioxidant and ceruloplasmin—an important extracellular antioxidant were reported in periodontitis patients in comparison to healthy probands (Tsai et al., 2005; Dalai et al., 2013). This could be explained by a depletion of the antioxidants due to increased ROS/RNS generation. It is unclear whether periodontal pathogens could be directly involved (Tsai et al., 2005). The studies on salivary oxidative stress and antioxidant status markers in relation to periodontal disease are summarized in **Table 2**.

### ISSUES AND LIMITATIONS

Numerous studies summarized in this review show the potential of salivary markers of oxidative, carbonyl stress and antioxidant status as they seem to be associated with oral diseases, their severity and respond to treatment (**Figure 1**). However, there are several limitations that explain why these markers are not in routine clinical use yet. From the summary tables it is clear that the reported concentrations of the salivary markers differ by orders of magnitude between studies. With such a variability, contradictory results from the studies are not surprising. The reasons for such a variability are both, technical and biological. Various different methods and protocols for each particular assay are used as comprehensively reviewed by others (Palmieri and Sblendorio, 2007a; Wang et al., 2015a). Our research uncovered several pre-analytical factors that affect the salivary markers of oxidative stress including saliva collection, daytime, intake of antioxidants, tooth-brushing and others (Kamodyová and Celec, 2011; Kamodyová et al., 2013). Importantly, salivation should not be induced as such samples are biased in comparison to spontaneous salivation. And although collection devices such as Salivette make saliva collection even more effective, their use should be limited to biomarkers that are resistant to such a collection method. This is not the case for most of the studied markers of oxidative stress. Our unpublished preliminary data show that a major impact on the subsequent analyses can come from such a small step as centrifugation after saliva collection. Although our data do not support this assumption, it can be expected that prolonged storage at different temperatures can lead to variable results in the analysis. The stability of the biomarkers very likely differs from marker to marker.

Beyond periodontitis and caries there are other oral and systemic diseases that were studied in relation to salivary markers of oxidative stress. Oral precanceroses such as lichen planus and leukoplakia but also patients with oral squamous cell carcinoma were found to be associated with higher MDA (Lopez-Jornet et al., 2014; Metgud and Bajaj, 2014). In one study autistic children had lower salivary TAC in comparison to their healthy siblings, although this difference can be attributed to worse oral hygiene (Rai et al., 2012). Markers of carbonyl stress such as salivary AGEs are modified by the treatment in sleep apnea syndrome (Celec et al., 2012). Even patients with the Down syndrome have higher salivary MDA and superoxide dismutase when compared with controls (de Sousa et al., 2015). It is very likely that other physiological and pathological factors including renal diseases, diabetes mellitus, and systemic inflammatory disorders influence salivary concentrations of biomarkers and a lot of research is yet to be conducted. A summary of the current research on salivary oxidative stress markers including studies on extra-oral or systemic diseases was published recently (Buczko et al., 2015).

The level of evidence varies between the studies. Only few of them report results from more than 100 patients. With such high technical and biological variability it is clear that the number of patients/samples has to be high to extract meaningful information from the gathered data. The most important limitations are, however, the unclear causality of the observed associations. Even tight correlation do not have to be due to a causal relationship. The causality can only be tested in interventional experiments in animal models or human patients.

### FUTURE OUTLOOK

Especially, the easy and non-invasive collection of saliva makes it a very interesting diagnostic fluid. Although numerous pitfalls have to be taken into account, analysis of salivary biomarkers could make it into routine clinic when it comes to salivary steroids, DNA, RNA, or the oral microflora. It is possible that in the future also salivary markers of oxidative stress will be

 diseases.

TABLE

2

Continued

**60**

TABLE 2 | Continued

(Continued)

(Continued)

TABLE 2 | Continued

TABLE

2

Continued

**65**

liquid

chromatography;

 C-ELISA, competitive

 ELISA;

 denotes levels estimated from graph.

substances/malondialdehyde; TOS, total oxidant status; SOD, superoxide dismutase.

FIGURE 2 | The origin of salivary markers of oxidative stress. Three possible sources are shown—blood plasma (A), oral bacteria (B), and immune cells (C). Although direct evidence is lacking, salivary markers of oxidative stress seem to be of local oral origin. At least in periodontitis the production of reactive oxygen species by oral bacteria or activated neutrophils seems to be of importance. In systemic diseases diffusion from plasma could be the main source of salivary markers of oxidative stress.

used for screening and monitoring of oral diseases such as periodontitis or caries as these markers seem to be mostly of local oral origin (**Figure 2**). It should not be seen as a substitute for proper clinical examination but rather an adjuvant tool for various applications such monitoring of the patients with poor adherence to dental visits. Especially, if the biochemical detection methods will be developed into simple strips that change color based on the concentration of the particular marker similarly to urine strips. Such first example already exist with a strip detecting thiol compounds known to be higher in periodontitis patients (Khocht et al., 2013). However, before that numerous mentioned obstacles have to be solved. Future studies should concentrate on identification of the sources of the observed variability, widening the palette of the available markers and experiments proving the role of oxidative stress in the pathogenesis of oral diseases. Inflammatory markers measured in saliva are very informative regarding the periodontal status

#### REFERENCES

of patients (Rathnayake et al., 2013; Salminen et al., 2014). Cooperative efforts focused on large multi-centric studies with sufficient power and standardized analysis are needed. Promising targeted antioxidant treatments could be a way how to approach cases of therapy-resistant periodontitis as partially shown for melatonin (Kara et al., 2013; Arabaci et al., 2015). The potential of non-invasive diagnosis and treatment of oral diseases makes salivary markers of oxidative stress very attractive for further research. And for this future a paradigm shift will be needed as the research will very likely by dominated by high-throughput approaches such as salivary metabolome analysis (Dame et al., 2015).

#### ACKNOWLEDGMENTS

This work was supported by grants VEGA 1/0674/12, 1/0222/14, and 1/0172/14.

periodontitis patients: a pilot study. J. Clin. Diagn. Res. 9, Zc23–Zc25. doi: 10.7860/JCDR/2015/11311.5652

status described by the papillary bleeding index. Dis. Markers 21, 133–137. doi: 10.1155/2005/693437

oxide levels in chronic and aggressive periodontitis: a biochemical study. J. Clin. Diagn. Res. 7, 1223–1227. doi: 10.7860/jcdr/2013/538 6.3068

**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2015 Tóthová, Kamodyová, Cervenka and Celec. This is an open-access ˇ article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

# Total Antioxidant Capacity and Total Oxidant Status in Saliva of Periodontitis Patients in Relation to Bacterial Load

Taowen Zhang1, 2 †, Oleh Andrukhov 2 † , Hady Haririan2 , Michael Müller-Kern2 , Shutai Liu1 , Zhonghao Liu1 and Xiaohui Rausch-Fan2 \*

1 Department of Science and Education, Yantai Stomatological Hospital, Binzhou Medical University, Yantai, China, 2 Division of Conservative Dentistry and Periodontology, University Clinic of Dentistry, Medical University of Vienna, Vienna, Austria

The detection of salivary biomarkers has a potential application in early diagnosis and monitoring of periodontal inflammation. However, searching sensitive salivary biomarkers for periodontitis is still ongoing. Oxidative stress is supposed to play an important role in periodontitis progression and tissue destruction. In this cross-sectional study, we investigated total antioxidant capacity (TAC) and total oxidant status (TOS) in saliva of periodontitis patients compared to healthy controls and their relationship with periodontopathic bacteria and periodontal disease severity. Unstimulated saliva was collected from 45 patients with generalized severe periodontitis and 37 healthy individuals and the TAC/TOS were measured. In addition, salivary levels of Aggregatibacter actinomycetemcomitans, Porphyromonas gingivalis, Tannerella forsythia, Treponema denticola, and Fusobacterium nucleatum in saliva were measured. Salivary TAC was lower in periodontitis patients compared to healthy controls. Moreover, a significant negative correlation of salivary TAC with clinical attachment loss was observed in periodontitis patients. No significant difference in the salivary TOS was observed between periodontitis patients and healthy controls. Bacterial load was enhanced in periodontitis patients and exhibited correlation with periodontal disease severity but not with salivary TAC/TOS. Our data suggest that changes in antioxidant capacity in periodontitis patients are not associated with increased bacterial load and are probably due to a dysregulated immune response.

#### Edited by:

Ulvi Kahraman Gürsoy, University of Turku, Finland

#### Reviewed by:

Peter Celec, Comenius University, Slovakia Sivge Kurgan, Ankara University, Turkey

\*Correspondence:

Xiaohui Rausch-Fan<EMAIL_ADDRESS>
† These authors have contributed equally to this work.

Received: 25 September 2015 Accepted: 09 December 2015 Published: 06 January 2016

#### Citation:

Zhang T, Andrukhov O, Haririan H, Müller-Kern M, Liu S, Liu Z and Rausch-Fan X (2016) Total Antioxidant Capacity and Total Oxidant Status in Saliva of Periodontitis Patients in Relation to Bacterial Load. Front. Cell. Infect. Microbiol. 5:97. doi: 10.3389/fcimb.2015.00097 Keywords: oxidative stress, periodontopathic bacteria, saliva, total oxidant status, total antioxidant capacity

## INTRODUCTION

Periodontitis is an inflammatory disease caused by specific bacteria and is characterized by gingival bleeding, periodontal pocket formation, destruction of connective tissue attachment, and alveolar bone resorption (Armitage, 1995). Periodontitis is initiated by the sub-gingival biofilm, but the progression of this destructive disease appears to depend upon an abnormal host response to those organisms (Cekici et al., 2014; Hasturk and Kantarci, 2015; Meyle and Chapple, 2015). Some specific bacteria such as Aggregatibacter actinomycetemcomitans, Porphyromonas gingivalis, Tannerella forsythia, Treponema denticola, and Fusobacterium nucleatum are strongly related to periodontitis (Socransky et al., 1998; Signat et al., 2011).

The classical parameters for diagnosis of periodontitis are clinical parameters such as probing depths of the gingival crevice, bleeding on probing, clinical attachment levels, and radiographic analysis (Goodson, 1986). These parameters are reliable to assess the severity of periodontitis under the condition of significant tissue destruction. However, measuring these parameters has poor prognostic impact (Lindhe et al., 1983) and therefore oral fluids have been investigated as an alternative diagnostic and prognostic approach (Kinney et al., 2011). In particular, salivary analysis has the potential to reflect current disease activity and severity, which can be advantageous for providing information used in risk assessment and monitoring of disease progress (Miller et al., 2010; Kinney et al., 2011).

Recently the advanced researches in molecular mechanisms in the pathogenesis of periodontitis have provided information about the specific biological pathways and biomolecules that could be used as biomarkers for risk assessment, diagnosis, and prognosis (Kinney et al., 2011). Obviously, most studies focused on markers that hold potential diagnostic significance relevant to three important biological phases of periodontal disease: inflammatory phase, connective-tissue degradation phase, and bone-turnover phase (Miller et al., 2010). Moreover, many factors associated with host-immune reaction to periodontal pathogens have been detected in saliva of periodontitis patients, for instance cytokines, chemokines, enzymes and immunoglobulins (Lamster and Grbic, 1995; Kaufman and Lamster, 2000; Seymour and Gemmell, 2001; Lamster et al., 2003). Nevertheless, studies about salivary biomarkers for the assessment of periodontitis are still ongoing (Giannobile et al., 2009).

Oxidative stress is defined as an imbalance between the production of reactive oxygen species (ROS) and the antioxidant capacity of organism. As most inflammatory diseases, periodontitis is characterized by oxidative stress, which might contribute to the host tissue destruction (for review, see Chapple and Matthews, 2007). Salivary markers of oxidative stress are extensively discussed as a possible tool for periodontal diagnostic (Tóthová et al., 2015). Since most oxidants have a very short half-life time, the measuring of oxidation products is widely used as an indicator of oxidative stress (Palmieri and Sblendorio, 2007). Previous studies show that periodontitis patients have the increased salivary levels of lipid peroxidation products, protein oxidation markers, and DNA damage marker (reviewed in Tóthová et al., 2015). Alternatively to measurements of oxidation products, a test measuring total oxidative status (TOS) was recently developed (Erel, 2005). Previous studies show that salivary TOS is increased in periodontitis patients and can be restored by periodontal therapy (Akalin et al., 2007; Wei et al., 2010). Oxidants produced during inflammatory response either react with target proteins or are neutralized by different antioxidants system. Therefore, measuring salivary total antioxidant capacity (TAC) can be also considered as an important tool for periodontal diagnostic. Some previous studies show that salivary TAC is decreased in periodontitis patients (Diab-Ladki et al., 2003; Mashayekhi et al., 2005; Guentsch et al., 2008), some studies report no significant difference in the salivary TAC between periodontitis patients and healthy controls (Brock et al., 2004; Tóthová et al., 2013), and one recent study shows an increase in salivary TAC in periodontitis patients (Almerich-Silla et al., 2015).

Oxidative stress in periodontitis arises from the immune response of the host to periodontal bacteria. Therefore, it would be interesting to investigate if there is some connection between salivary oxidative stress markers and the bacterial load. However, to date this relationship has not been investigated extensively (Almerich-Silla et al., 2015). Therefore, in the present study we investigated salivary TAC and TOS in periodontitis patients in relation to the levels of periodontal pathogens as well as in relation to clinical parameters of periodontitis.

### MATERIALS AND METHODS

### Study Population and Clinical Periodontal Examination

This cross-sectional study included 45 periodontitis patients and 37 periodontally healthy volunteers recruited from February 2010 until July 2012. The group of periodontitis patients included 15 patients with aggressive periodontitis and 30 patients with chronic periodontitis. All study participants gave written consent for participation in the study. The study protocol was approved by the ethics committee of the Medical University of Vienna (EK 623/2007).

Periodontal disease was diagnosed by experienced periodontologists with a postgraduate specialization in periodontology with clinical assessments using a periodontal probe and radiographs. Probing pocket depth (PD), clinical attachment loss (CAL), and bleeding on probing (BOP) were recorded at six sites per tooth using a periodontal probe (Hu-Friedy, Chicago, US). Bone loss was evaluated with intraoral and panoramic radiographs. Periodontitis was classified according to the classification of the World Workshop 1999 (Armitage, 1999). Inclusion criteria for periodontitis patients were: ≥20 teeth, generalized aggressive periodontitis with a clinical attachment-loss ≥5 mm at minimum six different teeth, age of onset <35 years; and for those with generalized chronic periodontitis a clinical attachment-loss ≥5 mm at minimum six different teeth. In the control group, no radiographic bone loss and no probing pocket depth ≥4 mm was recorded. The control group exhibited no clinical signs of gingivitis. Exclusion criteria for all study participants were: systemic diseases, medication, periodontal or antibiotic treatment >6months prior to the investigation, pregnancy. Smoking status was recorded based on a questionnaire. Only current smoking status was considered, the amount of cigarette consumption was not recorded.

### Saliva Collection

Unstimulated whole saliva samples were used in this study. Salivary collection was carried out between 8:00 and 11:00 a.m. Participants were asked to refrain from eating, drinking, smoking or brushing their teeth after midnight on the day of sampling. Unstimulated saliva was collected for 5 min according to the protocol of Navazesh et al. (2008), aliquoted and stored at −80◦C until analysis.

### Total Antioxidant Capacity and Total Oxidant Status Measurements

TAC and total oxidant status (TOS) were measured by commercially available TAC kit and TOS kit, respectively (both Rel Assay Diagnostics, Turkey). Measurements were performed according to the manufacturer's instruction.

TAC assay was based on the measurements of the reduction of 2,2′ -azino-bis(3-ethylbenzothiazoline-6-sulphonic acid; ABTS) radical. For the measurements of salivary TAC 225µl of assay Reagent 1 (acetate buffer, pH 5.8) was mixed with 5µl of saliva and the absorbance was measured at 420 nm after 30 s incubation. Afterwards, 20µl of Reagent 2 (ABTS, 30 mM in acetate buffer, pH 3.6) were added into each sample and the absorbance at 420 nm was measured after 5 min incubation. TAC was calculated based on the differences in the absorbance at 420 nm before and after adding the Reagent 2. The assay was calibrated with trolox and the results were expressed in terms of mM trolox equivalent per liter (mmol trolox Equiv/L).

TOS of saliva samples were measured using a method developed by Erel (Erel, 2005). Briefly, 225µL Reagent 1 (xylenol orange 150µM, NaCl 140 mM and glycerol 1.35M in 25 mM H2SO4 solution, pH 1.75) was mixed with 35µL of samples (saliva) and the absorbance of each sample was read spectrophotometrically at 560 nm as a sample blank. After that, 11µL Reagent 2 (ferrous ion 5 mM and o-dianisidine10 mM in 25 mM H2SO4 solution) was added to the mixture, mixed for about 3–4 min and the last absorbance was read at 560 nm. TOS was calculated based on the differences in the absorbance at 560 nm before and after adding the Reagent 2. The assay was calibrated with H2O2 and the results were expressed in terms of µM H2O2 equivalent per liter (µmol H2O2 Equiv/L).

### Microbiological Analysis

Salivary bacteria were measured using the method described previously (Haririan et al., 2014). A. actinomycetemcomitans, P. gingivalis, T. forsythia, T. denticola, and F. nucleatum in saliva were measured. Saliva in the tubes was centrifuged, and the supernatant was transferred into 2 mL tubes. DNA was extracted by means of a DNA Extraction Kit (ParoCheck R , Greiner Bio One, Kremsmuenster, Austria). Protein kinase K, buffer solution, and EtOH were added, and tubes were centrifuged, vortexed, and heated at 95◦C. Part of the 16S rRNA gene was amplified by a highly conserved specific primer pair flanking the diversity box of each 16S rRNA gene. A chip (ParoCheckChip R , Greiner Bio One, Kremsmuenster, Austria) was used for hybridization, followed by washes at 50◦C and drying by centrifugation. Finally, the DNA-Chip was analyzed by a scanner (CheckScanner) semi quantitatively using specific analytic software (Check Report Software Version 4.0.2, Greiner Bio One, Kremsmuenster, Austria). The signals describing the bacterial load in the samples were scored as −, (+), +, ++, or +++.

#### Statistical Analysis

Differences in TAC/TOS values between periodontitis and control groups were analyzed using Students t-test. The effect of diagnosis, age, gender, smoking status, and bacterial load on the salivary TAC and TOS was tested using multivariate generalized linear model. The differences in the detection frequency of particular bacteria, the proportion of female/male, and the proportion of smokers between groups were examined by χ 2 test. Correlations between different parameters were checked by Spearmans's rank correlation tests. Differences were considered to be statistically significant at p < 0.05. Statistical power was calculated using freely available online tool (www.powerandsamplesize.com). All other statistical analysis was performed using statistical program SPSS 21.0.

## RESULTS

### Demographic and Clinical Characterization of the Study Groups

Demographical characteristics and clinical parameters of healthy controls and periodontitis patients are listed in the **Table 1**. No significant difference in the proportion of female and male participants was found between the groups. The proportion of smokers was significantly higher in the periodontitis group compared to the control group (p < 0.01). Clinical parameters were significantly higher in the periodontitis group than in the control group (p < 0.01). The results of the semiquantitative analysis of A. actinomycetemcomitans, P. gingivalis, T. denticola, T. forsythia, and F. nucleatum in saliva of healthy individuals and

Data are presented as mean ± SD. BOP, bleeding on probing; PPD, probing pocket depth; CAL, clinical attachment loss. \*Significantly different vs. control group, p < 0.05, t-test. # significantly different vs. control group, p < 0.05, χ 2 test.

periodontitis patients are shown in the **Figure 1**. Significantly higher detection rates of P. gingivalis, T. denticola, and T. forsythia, were observed in periodontitis patients compared to healthy subjects (p < 0.01). No significant difference in the detection rate of A. actinomycetemcomitans (p = 0.051) and F. nucleatum (p = 0.642) was found between periodontitis and control groups.

### Salivary TAC and TOS

The results of a multivariate generalized linear model analysis of the effect of overall diagnosis, smoking status, gender, age, and bacterial load on the salivary TAC and TOS are presented in the **Table 2**. Multivariate test showed a significant dependency of study parameters on the overall diagnosis. Between subject tests showed that only overall diagnosis has a significant effect on the salivary TAC, whereas age, gender, smoking status, and bacterial load had no significant effect on this parameter. None of the factors had a significant effect on salivary TOS. The salivary TAC and TOS in control and periodontitis groups are shown in the **Figure 2**. The salivary TAC values in periodontitis group were significantly lower compared to the control group (p < 0.05, power = 0.82). No significant difference in the salivary TOS between control and periodontitis groups was found. No significant difference in the salivary TAC and TOS was found between patients with aggressive and chronic periodontitis (data not shown).

#### Correlation of TAC and TOS with Clinical Parameters of Periodontitis

In periodontitis patients, the salivary TAC exhibited a significantly negative correlation with CAL parameter (r = −0.312, p < 0.05, see **Figure 3A**). A negative but non-significant correlation was observed between salivary TAC and BOP (r = −0.258, p = 0.087, see **Figure 3B**). No significant correlation of TAC with clinical parameters BOP, PPD, and the number of teeth with PPD ≥ 5 mm was found. No significant correlation of salivary TOS with any clinical parameter was found.

### Clinical Parameters and Salivary TAC/TOS in Relation to Bacterial Load

The dependency of PPD, number of teeth with PPD ≥ 5 mm, and BOP on the bacterial load measured in the saliva of periodontitis patients is shown in **Figure 4**. Increased salivary content of A. actinomycetemcomitans, P. gingivalis, and T. denticola was associated with significantly higher PPD and the number of teeth with PPD ≥ 5 mm in periodontitis patients. No significant effect of the salivary presence of bacteria on BOP (**Figure 4C**) and CAL (data not shown) was observed.

**Figure 5** shows salivary TAC and TOS depending on the presence of different bacteria in the saliva of periodontitis patients. No significant effect of any periodontal bacteria on the salivary TAC (**Figure 5A**) and salivary TOS (**Figure 5B**) was observed.

### DISCUSSION

In the present study we investigated the differences in TAC and TOS in saliva in individuals with periodontitis and healthy controls and investigated their relationship with clinical parameters of periodontitis and the presence of periodontopathic bacteria A. actinomycetemcomitans, P. gingivalis, T. forsythia, T. denticola, and F. nucleatum in saliva. Activation of the host response by periodontal pathogens results in an activation and infiltration of neutrophils, which are the primary source of ROS in periodontitis (Ryder, 2010; Scott and Krauss, 2012). ROS production by neutrophils is considered as an important mechanism of bacteria killing (Nauseef, 2007). However, ROS production by neutrophils might also cause damages of host tissues when ROS are not neutralized by the antioxidant system or in case of an impaired neutrophils clearance (Hajishengallis and Hajishengallis, 2014). A proper balance between ROS production and TAC of the host tissue plays an important role in the homeostasis of periodontal tissue and prevents tissue

TABLE 2 | Effect of overall diagnosis, gender, smoking status, age, and bacterial load on the salivary TAC and TOS analyzed by multivariate generalized linear model.

Parameters are calculated by multivariate generalized linear models with TAC and TOS as dependent variable and overall diagnosis, gender, smoking status, age, or bacterial load as independent variables. β, standardized regression coefficient.

destruction upon activation of the immune system by periodontal pathogens.

Analysis using multivariate generalized linear model showed that salivary TAC was significantly dependent on the overall diagnosis but not on other parameters such as age, gender, smoking status, and bacterial load. None of the parameters, such as overall diagnosis, age, gender, smoking status, and bacterial load exhibited a significant effect on salivary TOS. The antioxidant capacity of saliva is due to low molecular antioxidants such as uric acid, ascorbic acid, and albumin (Moore et al., 1994) as well as due to antioxidant enzymes such as superoxide dismutase, catalase, and glutathione peroxidase (Battino et al., 2002). Salivary TOS might be accounted by different reactive oxygen and nitrogen species, such as hydroxyl radical, hydrogen peroxide, or peroxynitrite (Takahama et al., 2005; Chitra et al., 2012). Our data suggest that changes in the oxidative stress parameters in periodontitis patients are presumably associated with the inflammatory processes in periodontitis and not directly with a bacterial load. The contribution of other factors such as age, gender, and smoking status on the oxidative stress parameters must be considered in the future studies with higher number of patients.

Salivary TAC in periodontitis patients was significantly lower than those in healthy subjects. There was a significant negative relationship between salivary TAC and CAL. Moreover, a tendency of a negative relationship of salivary TAC with BOP was also observed. Our results are supported by some previous studies showing that salivary TAC is lower in periodontitis patients and negatively correlates with periodontitis severity (Diab-Ladki et al., 2003; Mashayekhi et al., 2005; Guentsch et al., 2008). Immune response against periodontal pathogens is associated with an enhanced production of ROS by neutrophils

FIGURE 2 | Oxidative stress parameter in the control and periodontitis groups. Salivary total antioxidant capacity (A) and total oxidant status (B) are presented as mean ± s.e.m. \*Significantly different vs. control group, p < 0.05, t-test.

and macrophages (for review, see Chapple and Matthews, 2007). To avoid host tissue destruction these ROS are neutralized by antioxidants, which might result in decreased TAC. Systemic and local TAC in periodontitis patients might reflect increased oxygen radical activity during periodontal inflammation and can be restored to control subject levels by non-surgical therapy (Chapple and Matthews, 2007). However, there are also some studies showing that salivary TAC is either increased or remains on the same level in periodontitis patients compared to healthy controls (Brock et al., 2004; Tóthová et al., 2013; Almerich-Silla et al., 2015). The differences in the results of TAC between different studies could be explained by different analytical methods used by TAC assessment (reviewed in Wang et al., 2015). Particularly, in our study, TAC was measured based on the ability of saliva sample to reduce ABTS radical, whereas in another study TAC measurements were based on the saliva ability to prevent ABTS oxidation (Almerich-Silla et al., 2015). It should be also noted that TAC is a complex parameter which includes the integrated activity of different antioxidants and often depends on their interaction and synergistic effects (Ghiselli et al., 2000).

We did not find any significant difference in the salivary TOS between periodontitis patients and healthy controls. Salivary TOS exhibited no correlation with clinical parameters and the bacterial load. This observation is in contrast to recent studies reporting salivary TOS in periodontitis patients of about 1.5 times higher compared to healthy individuals as well as a strong correlation of TOS with clinical parameter of periodontitis (Akalin et al., 2007; Wei et al., 2010). However, in these two studies, patients' selection was more restrictive: they include only never smokers, all studies participants have similar age, socio-economic status and nutrition habits. Therefore, patient selection could be a crucial parameter influencing salivary levels of TOS and this fact is rather limiting the use of salivary TOS as a marker of periodontal disease.

An assumption that an increased salivary TOS reflects an increased production of ROS in periodontitis is rather questionable. Most ROS produced by neutrophils and macrophages either reacts with target proteins or are neutralized by antioxidants. Furthermore, the production of ROS as a result of an inflammatory reaction occurs either before or at the same time of tissue damages (Halliwell, 2000). Therefore, lipid peroxidation products malondialdehyde (MDA) and thiobarbituric acid-reacting substances (TBARS), advanced

oxidation protein products (AOPP), and oxidative DNA damage product 8-hydroxydeoxyguanosine (8-OHdG) are often used as an indicator of oxidative stress (Chapple and Matthews, 2007; Tóthová et al., 2015; Wang et al., 2015). Previous studies suggest that salivary TBARS and 8-OHdG levels are enhanced in periodontitis patients compared to controls (for review, see Tóthová et al., 2015). Two previous studies show a significant positive correlation between the levels of periodontal pathogens and oxidative stress markers in saliva from periodontitis patients (Sawamoto et al., 2005; Almerich-Silla et al., 2015). Moreover, analysis with predictive model shows that salivary markers of lipid peroxidation and DNA damage might have good diagnostic potential for periodontitis (Almerich-Silla et al., 2015).

We have determined the levels of different bacteria in saliva. As shown by our previous study, salivary bacteria levels exhibit a good correlation with the subgingival bacterial load in the dental plaque of periodontitis patients (Haririan et al., 2014). We observed that the salivary levels of P. gingivalis, T. forsythia, and T. denticola were significantly enhanced in periodontitis patients compared to healthy subjects. This confirms the previous finding suggesting the importance of red complex bacteria as true pathogens in adult periodontitis patients (Socransky et al., 1998). We further found that a high bacterial load was associated with increased clinical parameters of periodontitis such as PPD and BOP but exhibited no correlation with salivary TAC and TOS. However, a negative correlation of salivary TAC with CAL

and BOP was observed. Our observations suggest that changes in salivary antioxidant capacity are associated rather with the inflammatory response than with an enhanced bacterial load. This conclusion is generally in line with the current opinion that periodontal tissue destruction is mainly due to a dysregulated unresolved immune response than due to an enhanced bacterial load (Hasturk and Kantarci, 2015; Meyle and Chapple, 2015).

As well-known, periodontitis is a local inflammatory disease with multifactorial character, with fluctuations in bacterial burden, systemic host immune response, and tissue destruction. Up to date, various host-derived factors in periodontitis can be detected in saliva, which provide important information regarding the status of periodontal tissues. Most of the studies focused on biomarkers, which hold a potential diagnostic significance relevant to three important biological phases of periodontal disease, i.e., well-known markers C-reactive protein, IL-1β, IL-6, TNF-α involved in inflammatory phase; matrix metalloproteinases (MMP-8 and MMP-9) in connective-tissue degradation phase and alkaline phosphatase, receptor activator of NF-κB ligand, and osteoprotegerin in bone-turnover phase (for review, see Miller et al., 2010). Moreover, our previous studies demonstrate other biomolecules such as histamine, chromogranin A (CgA), melatonin, and nitric oxide derivatives to be related to the periodontal bacterial load and severity of periodontitis, as well as some of them were restored by a non-surgical therapy and influenced by smoking and gender (Bertl et al., 2012, 2013; Haririan et al., 2012; Andrukhov et al., 2013).

Before considering oxidative stress parameters as potential markers of periodontitis, it is important to take into account their dependency on different factors such as age, smoking, gender, and nutrition. We did not find any effect of gender on both TAC and TOS. Gender is a well-known risk factor of periodontitis and other oxidative stress related disease (Genco, 1996). Male individuals usually have a higher prevalence and severity of periodontal disease than females (Shiau and Reynolds, 2010). In our previous study we also indicated male gender should be considered an important factor by assessing the risk of CVDs in periodontitis patients (Andrukhov et al., 2013). A recent study reports that changes of TAC and oxidative stress marker TBARS in saliva of periodontitis patients might be gender dependent (Banasová et al., 2015 ˇ ). Antioxidant protection in females is usually higher due to an increased activity of antioxidant enzymes in pre-menopausal females when compared to men (Pepe et al., 2009; Bloomer and Fisher-Wellman, 2010). Various markers of oxidative stress such as MDA, AOPP, nitric oxide derivatives, as well as Trolox-Equivalent Antioxidant Capacity (TEAC) are reported to differ between men and women (Andrukhov et al., 2013; Bloomer and Lee, 2013). However, the exact effect of gender on salivary TAC and TOS must be investigated in further studies with higher patients' numbers.

Smoking is another important factor influencing the salivary levels of oxidative stress parameters. Smoking stimulates the oxidative burst of neutrophils and therefore influences the oxidative balance in the whole body (Ryder et al., 1998). In our study we did not observe any significant effect of smoking on salivary TAC and TOS. Similarly to our observation, some previous studies also do not observe any significant effect of smoking on salivary TAC (Charalabopoulos et al., 2005; Guentsch et al., 2008). In contrast, another study reports that the activity of antioxidant enzymes superoxide dismutase, glutathione peroxidase, and catalase is increased in smoking periodontitis patients compared to non-smokers (Tonguç et al., 2011). Salivary levels of lipid peroxidation marker MDA are reported to be higher in smoking patients than in non-smokers (Guentsch et al., 2008; Tonguç et al., 2011). The dependency of oxidative stress markers on current smoking status, smoking history, and smoking intensity (cigarette per day or pack per years) must be taken into account before considering these parameters as candidate for periodontal disease markers.

Age might also influence the salivary levels of oxidative stress parameters. Previous studies suggest that the levels of salivary antioxidants as well as protein oxidation products positively correlate with the age (Hershkovich et al., 2007; Celecová et al., 2013). However, these changes seem to be pronounced mainly in the elderly individuals. In our study, we did not observe any significant effect of age on the salivary TAC and TOS. Periodontitis patients included in our study were about 9 years older than healthy controls. The observed differences in salivary TAC observed in our study cannot be contributed to the different

#### REFERENCES

age on the salivary because older individual have higher TAC (Hershkovich et al., 2007; Celecová et al., 2013) but we observed the lower TAC in periodontitis patients.

In conclusion, the present study showed that salivary TAC is decreased in periodontitis patients compared to healthy controls. The change of TAC correlates with the severity of periodontal disease but not with the bacterial load, which implies that changes in the oxidative status in periodontitis patients are rather due to dysregulated immune response than an increased bacterial load.

### AUTHOR CONTRIBUTIONS

Designed research: TZ, OA, HH, XR. Performed research and analyzed data: TZ, OA, HH, MM, SL. Edited the manuscript: HH, MM, SL, ZL. Wrote the manuscript: TZ, OA, XR.

#### ACKNOWLEDGMENTS

The authors would like to thank Mrs. Nguyen Phuong Quynh and Mrs. Hedwig Rutschek (both Medical University of Vienna) for excellent technical assistances. This study was supported by a grant from the Austrian National Bank (ONB 14152) and by Greiner Bio-One, Kremsmuenster, Austria (reagents and saliva collection system).

periodontitis patients: effect of smoking and periodontal treatment. Clin. Oral Investig. 12, 345–352. doi: 10.1007/s00784-008-0202-z

**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2016 Zhang, Andrukhov, Haririan, Müller-Kern, Liu, Liu and Rausch-Fan. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

# Using Salivary Nitrite and Nitrate Levels as a Biomarker for Drug-Induced Gingival Overgrowth

Erkan Sukuroglu1 \*, Güliz N. Güncü2 , Kamer Kilinc3 and Feriha Caglayan2

1 Department of Periodontology, Faculty of Dentistry, Karadeniz Technical University, Trabzon, Turkey, 2 Department of Periodontology, Faculty of Dentistry, Hacettepe University, Ankara, Turkey, 3 Department of Biochemistry, TOBB University of Economics and Technology, Ankara, Turkey

Aim: Drug-induced gingival overgrowth has a multifactorial nature and the pathogenesis is still uncertain. It has been suggested that Nitric Oxide (NO) might play a role in the pathogenesis of drug-induced gingival overgrowth due to the contribution of NO to immune response and matrix degradation. NO levels in biological fluids have been used as a diagnostic biomarker in many diseases. The aim of this study is to determine whether NO levels in plasma, saliva, and gingival crevicular fluid (GCF) can serve as a potential biomarker for the evaluation of drug-induced gingival overgrowth risk.

#### Edited by:

Ulvi Kahraman Gürsoy, University of Turku, Finland

#### Reviewed by:

Gena D. Tribble, University of Texas Health Science Center at Houston, USA Christian Damgaard, University of Copenhagen, Denmark Telma Blanca Lombardo Bedran, Centro Universitario Nove de Julho (UNINOVE), Brazil

#### \*Correspondence:

Erkan Sukuroglu<EMAIL_ADDRESS>
Received: 30 August 2015 Accepted: 16 November 2015 Published: 01 December 2015

#### Citation:

Sukuroglu E, Güncü GN, Kilinc K and Caglayan F (2015) Using Salivary Nitrite and Nitrate Levels as a Biomarker for Drug-Induced Gingival Overgrowth. Front. Cell. Infect. Microbiol. 5:87. doi: 10.3389/fcimb.2015.00087

Materials and Methods: A total of 104 patients, receiving cyclosporine A (n = 35), phenytoin (n = 25), nifedipine (n = 26), or diltiazem (n = 18) participated in the study. The amount of gingival overgrowth was evaluated with two indices and was given as percentage. Periodontal clinical parameters including plaque index (PI), gingival index (GI), gingival bleeding time index (GBTI), and probing depth (PD) were also assessed. Saliva, GCF, and plasma samples were obtained from each participants. Nitrite and nitrate levels in saliva, GCF, and plasma were analyzed by Griess reagent.

Results: Salivary nitrite and nitrate levels in responders were significantly higher than those in non-responders in only phenytoin group (p < 0.05). Nitrite and nitrate levels of gingival crevicular fluid and plasma did not significantly differ between responders and non-responders in all study groups (p > 0.05). Salivary nitrite levels exhibited a significant correlation with PD, GBTI, severity of gingival overgrowth (%GO), and GCF volume (p < 0.05). Additionally, a strong positive correlation was detected between saliva and plasma nitrate levels (p < 0.005). However, both nitrite and nitrate levels in GCF and plasma demonstrated no significant correlation with clinical parameters, GO severity, and GCF volume (p > 0.05).

Conclusion: Salivary nitrite and nitrate levels could be used as periodontal disease biomarkers in phenytoin induced gingival overgrowth, and that saliva seems to have a better diagnostic potential than GCF and plasma for the evaluation of drug-induced gingival overgrowth risk. However, when all drug groups were considered, saliva nitrite and nitrate levels could not be used as a biomarker for drug-induced gingival overgrowth.

Keywords: nitric oxide, nitrite, nitrate, saliva, drug induced gingival overgrowth, biomarker

## INTRODUCTION

Drug-induced gingival overgrowth is a well-known side effect of anticonvulsant phenytoin, immunosupressant cyclosporine A (CsA), and antihypertensive calcium channel blockers. Although the structural characteristics and pharmacologic effects of each of these drugs are different, all of them can cause gingival overgrowth that generally has a similar clinical and histological appearance. The overgrowth normally begins at the interdental papillae and is usually confined to the attached gingiva, but it may extend coronally and interfere with the occlusion, mastication and speech, and may also compromise proper plaque control (Marshall and Bartold, 1999). The prevalence rate of gingival overgrowth is about 50% for phenytoin (Güncü et al., 2006) and 25–30% for CsA (Boltchi et al., 1999). This prevalence rate in patients treated with calcium channel blockers varies widely from 10 to 50% (Ellis et al., 1999; Güncü et al., 2007).

Not all patients receiving these drugs develop gingival overgrowth and the severity of overgrowth varies between patients. Although, many clinical and laboratory studies have been performed to clarify the underlying pathogenic mechanisms responsible for drug-induced gingival overgrowth, the etiology remains still undisclosed. Many risk factors including poor plaque control, gender, age of the patient, drug dosage, pharmacokinetic variables, and genetic predisposition have been identified in a number of studies, but it is not possible to determine the patients at high risk for developing gingival overgrowth (Seymour et al., 2000).

The essential feature of drug-induced gingival overgrowth is an increase in the connective tissue matrix and it results from disturbance of the intricate balance between synthesis and degradation of the extracellular matrix of the gingival tissues. Some of the suggested factors responsible for this imbalance are cytokines, inflammatory mediators, and growth factors (Trackman and Kantarci, 2004; Chae et al., 2006; Kantarci et al., 2006).

Nitric oxide (NO) is a gaseous free radical generated from the conversion of L-arginine to L-citrulline by nitric oxide synthase (NOS) (Jenkins et al., 1995). Three distinct isoforms of NOS are known and identified as endothelial NOS (eNOS), neuronal NOS (nNOS), and inducible NOS (iNOS). eNOS and nNOS release small amounts of NO for a short period of time following receptor stimulation and they play an important role in regulation of physiological processes including platelet aggregation, vascular relaxation, and immune modulation. iNOS produces large amount of NO, and is expressed in response to bacterial endotoxins and cytokines, such as interleukin-1β and TNF-α (Forstermann et al., 1994; Lyons, 1995). Distinct from eNOS and nNOS, iNOS is considered to act in pathological conditions and plays a detrimental role in the regulation of inflammatory reactions. These NO-mediated detrimental effects probably occur in combination with the action of metalloproteinases and collagenases, produced by activated macrophages, polymorphonuclear cells, and fibroblasts (Kröncke et al., 1997; Kendall et al., 2001).

It has been shown that NO takes part in the etiopathogenesis of many diseases, including periodontal disease (Ohashi et al., 1999; Batista et al., 2002). Increased production of NO can cause destruction of periodontal tissues (Batista et al., 2002). Based on the role of NO on both immune response and matrix degradation in the periodontal environment, it can be speculated that NO may play an important role in the pathogenesis of drug-induced gingival overgrowth. However, only few animal and clinical studies have investigated the relationship between NO and drug-induced gingival overgrowth (Fu et al., 2000; Gau et al., 2005; Rezaie et al., 2005; Gürkan et al., 2009). Fu et al. (2000) reported a decrease in gingival dimensions of CsAfed rats after NO substrate (L-arginine) treatment compared to controls. In another animal study, Gau et al. (2005) demonstrated that CsA-treated rats have increased plasma nitrite/nitrate levels compared to control rats. In a recent study, Gürkan et al. (2009) showed higher iNOS and eNOS immunostaining in connective tissues from patients in the gingivitis and CsA induced gingival overgrowth groups compared to healthy and subjects without gingival overgrowth. However, no intergroup differences were reported regarding nitrite/nitrate levels in gingival crevicular fluid (GCF). There is no clinical human study evaluating the relation of salivary nitrite and nitrate levels to drug-induced gingival overgrowth in the literature. There is only one study conducted on rats, in which the relation of nitric oxide to nifedipine-induced gingival overgrowth and salivary gland function was assessed. It was suggested that nitric oxide mediated positive signal-transduction mechanisms in salivary glands may play an important role in nifedipine-induced gingival overgrowth (Rezaie et al., 2005).

Due to its reactivity and short half-life, direct measurements of NO from tissues and biological fluids are hard to perform. Although NO metabolites have a very short life, nitrite and nitrate are the relatively stable end products of NO oxidation (Lappin et al., 2000; Ugar-Cankal and Ozmeric, 2006). The total levels of nitrite and nitrate in biological fluids are generally used for adequate monitoring of the NO synthesis (Moshage et al., 1995). Based on the findings that showed a marked increase in NO synthesis in overgrown gingiva, measuring nitrite and nitrate levels in saliva, GCF, and plasma might be useful to understand the etiopathogenesis of druginduced gingival overgrowth. To the best of our knowledge, there is no study evaluating the association of nitrite and nitrate levels in saliva, plasma, and GCF with drug-induced gingival overgrowth. Drug-induced gingival overgrowth may constitute speech, mastication, hygienic, and aesthetic problems. Thus, early diagnosis of drug-induced gingival overgrowth is very important and it needs to have a diagnostic biological marker to determine the risk of developing drug-induced gingival overgrowth in patients receiving these drugs, before the occurrence of gingival overgrowth. Therefore, the present study was conducted to evaluate nitrite and nitrate levels in plasma, saliva, and GCF from responders and non-responders treated with either CsA, phenytoin, nifedipine, or diltiazem, and to determine whether NO levels in plasma, saliva, and GCF can serve as a potential biomarker for the evaluation of drug-induced gingival overgrowth risk.

### MATERIALS AND METHODS

### Study Population and Design

This research study was conducted at the Department of Periodontology, Hacettepe University between February 2010 and September 2013. A total of 104 Turkish patients (50 male, 54 female) were included in the study. The study groups consisted of 35 renal transplant patients receiving CsA, 25 patients receiving phenytoin, 26 patients receiving nifedipine, and 18 patients receiving diltiazem therapy. Patients participated in this study were obtained from outpatients attending the Department of Nephrology, Neurology, and Cardiology, Faculty of Medicine, Hacettepe University. Only patients receiving one of these drugs (including CsA, phenytoin, nifedipine, and diltiazem) in regular doses for at least 6 months were included in the study. The presence of all maxillary and mandibular anterior teeth was also required. Pregnant women, subjects with systemic diseases such as diabetes mellitus or any other form of systemic inflammatory involvement, patients who have mouth breath and restorative crowns at anterior regions, and used any antibiotics or received periodontal treatment within the last 6 months and who also received one more drug leading to gingival overgrowth were excluded from the study. Due to the fact that NO levels could be affected by smoking, smokers were not included in the study. The protocol of the study was approved by the ethics committee of the Hacettepe University. (#FON 07/15-1) Written informed consent in accordance with the Declaration of Helsinki was obtained from each patient prior to enrollment in the study.

### Clinical Parameters

Periodontal examinations were carried out on the upper and lower six anterior teeth by one calibrated periodontal specialist (ES) during the study period. Periodontal clinical parameters including plaque index (PI; Löe, 1967), gingival index (GI; Löe, 1967), probing depth (PD), and gingival bleeding time index (GBTI; Nowicki et al., 1981) were recorded. Demographic variables including age and gender were also recorded.

In order to assess the overgrowth of gingival tissues accurately, alginate impressions were obtained from each patient and gypsum individual models were created. Gingival overgrowth was assessed on these individual models by performing measurements in vertical and horizontal dimensions. Vertical measurements were performed according to the Miller and Damm index (1992). Briefly, the height of the gingival tissue was measured from the cemento-enamel junction (CEJ) to the free gingival margin. The following grades were scored in six points around each tooth on maxillary and mandibular anterior region: 0 = normal gingiva; 1 = minimal enlargement (≤2 mm in size); 2 = moderate enlargement (2–4 mm in size); and 3 = severe enlargement (nodular growth >4 mm). Horizontal gingival overgrowth was measured in the buccal-lingual direction of all interdental papillae of maxillary and mandibular anterior teeth according to Miranda et al. (2001). The increase in the size of buccal and lingual papillae was measured from the enamel surface to the outer papillary surface at the interdental contact point. Horizontal measurements were assigned a score of between 0 and 2, as follows: 0 = normal thickness (1 < mm); 1 = thickness between 1 and 2 mm; and 2 = thickness more than 2 mm.

The vertical and horizontal scores were calculated to determine an overgrowth score for each gingival papillae. The maximum overgrowth score obtained for each interdental unit was five. Twenty interdental units were identified, giving a maximum overgrowth score of 100 for a patient. Therefore, this index could be expressed as a percentage (Thomason et al., 2005). A score of 30% was determined as the critical value for gingival overgrowth index. Patients were classified into two subgroups (Seymour and Smith, 1991) as followed: patients with a gingival overgrowth index of <30% were identified as non-responders (GO–) and patients with a value of ≥30% were defined as responders (GO+). The severity of GO was also determined with this percentage.

#### GCF, Saliva, and Plasma Sampling

The participants were told not to eat any high nitrate foods (e.g., spinach, beets, and other green leafy vegetables) at least 12 h before sampling due to the fact that it may affect the study results. GCF samples were obtained from maxillary anterior teeth. To avoid blood contamination and possible stimulation of GCF flow during clinical measurements, samples were collected before any other clinical recordings except the PI. GCF samples were obtained by the technique described by Rüdin et al. (1970). Prior to sampling, the respective region was dried by isolation with cotton rolls and a 5-s gentle air stream with a 90◦ angle to the tooth axis, and supragingival plaque was eliminated with a curette. Standardized strips were inserted 1 mm into the sulcus and left for 30 s. Papers with visible blood contaminations were discarded and sampling was replicated from another site of the natural tooth that was not sampled. To eliminate the risk of evaporation, paper strips with GCF were immediately transported to a previously calibrated electronic GCF measuring device for volume determination. The GCF was measured electronically in Periotron units, which were converted to micro liters (µl) by MCCONVRT software (Software version 2.52, Oraflow Inc., Amityville, NY, USA). GCF samples were then placed in sterile Eppendorf tubes and stored at −30◦C until the day of laboratory analysis. A total of 10 paper strips with GCF were obtained with this standardize technique from maxillary anterior six teeth of each patient for detecting GCF nitrite and nitrate levels.

After GCF collection, stimulated parotid saliva samples were obtained from each patient using Lashley cup (Lashley, 1916) during stimulation with 1% citric acid. Citric acid was applied to the dorsum of the tongue, held there by the subject for 10 s and 1 ml of saliva was collected from each patient as described in detail before (Francis et al., 2001). Saliva samples were then placed in sterile Eppendorf tubes and stored at −80◦C until the laboratory analysis.

After saliva collection, in order to determine the plasma nitrite and nitrate levels, venous blood samples were collected into lithium-heparin tubes. Blood samples were placed within 3 min into a refrigerated (4◦C) centrifuge and centrifuged at 4000 rpm for 10 min according to standard procedures (Uzar et al., 2011). After getting plasma, samples were frozen at −80◦C for later analysis of plasma nitrite and nitrate concentrations.

### Determination of Nitrite and Nitrate Levels in GCF, Saliva, and Plasma

For the determination of nitrite and nitrate levels in GCF samples, 300 ml of phosphate buffer (50 mM, pH: 7.4) was added onto each sample and the samples were mixed vigorously for the extraction of nitrite and nitrate into buffer. Nitrite and nitrate content of the samples extracts was determined using Griess reagent (Grisham et al., 1996). The sum of nitrate and nitrite was measured by the same assay after reduction of nitrate to nitrite with nitrate reductase from Aspergillus niger (Roche Diagnostics, Mannheim, Germany). Nitrite and nitrate levels in both saliva and plasma were determined by the same method without any pretreatment. The nitrate concentrations were calculated by subtracting the nitrite level from the total nitrite level (nitrite + nitrate). This assay is in the routine research analyze protocol of the laboratories of Hacettepe University Faculty of Medicine Department of Biochemistry for more than a decade and its sensitivity and specificity is being tested routinely by the university staff, together with other routine tests. However, commercial standards were implemented to confirm its sensitivity and specificity in the present study.

### STATISTICAL ANALYSIS

Statistical analysis was performed with (SPSS Inc.,Chicago, IL; Serial number: 2Z7ZHN12FA70P1JXWYNCMWY5). The normality of data was tested with Kolmogorov Smirnov test. Mann Whitney U test was used to compare each clinical or laboratory findings for individual drug group between responders and non-responders. Spearman correlation test was obtained to determine the interactions between laboratory and clinical parameters for all participants. The differences between the age groups were tested with Independent sample t-test, and the distribution differences of gender was analyzed with chisquare test interms of between responders and non-responders. The confidence interval was set as 95%.

All patients participated in this study (n = 104) revealed a power of 87.74% with a normal approximation method. A difference in salivary nitrate levels between responders and non-responders in phenytoin group can be detected at an alpha level of 0.05, with a statistical power of 87.74%.

#### RESULTS

A total of 104 patients consisting of CsA group (n = 35), phenytoin group (n = 25), nifedipine group (n = 26), and diltiazem group (n = 18) were included in the study. The demographic variables of groups including mean age and gender ratio are presented in **Table 1.**

Patients in each drug group were divided into two subgroups as responders (overgrowth index ≥30%) and non-responders (overgrowth index <30%) according to gingival overgrowth index. Out of 35 patients in CsA group, 13 (37.1%) were identified as responders, those values in phenytoin, nifedipine, and diltiazem groups were 11 (44%), 11 (42.3%), and 2 (11.1%), respectively. The gingival overgrowth index was significantly higher in responders in all drug groups, as expected (**Table 2**). There were statistically no significant differences between responders and non-responders in mean age and gender ratio in all drug groups except for nifedipine. While the mean age was similar between subgroups in nifedipine group, there was a significant difference in gender ratio (p < 0.05).

### Clinical Periodontal Parameters

All clinical periodontal parameters including PI, GI, PD, and GBTI were statistically higher in responders compared to nonresponders in all drug groups (p < 0.05), except for diltiazem and nifedipine group (**Table 3**). In diltiazem group, these clinical parameters were higher in responders but only the differences in GBTI and GI reached statistically significance (p < 0.05). In nifedipine group, all clinical periodontal parameters except PI were statistically higher in responders (p < 0.05).

### Nitrite and Nitrate Levels in Saliva, GCF, and Plasma

Nitrite and nitrate levels of saliva, GCF, and plasma for the subgroups of each study group are shown on **Table 3**. Salivary nitrite and nitrate levels (µM) did not differ significantly between responders and non-responders in all study groups, except for phenytoin group. In phenytoin group, salivary nitrite and nitrate levels in responders were significantly higher than those in nonresponders (p < 0.05). Nitrite and nitrate levels of GCF (nmol)

#### TABLE 2 | Clinical periodontal parameters in all groups.

PD, probing depth; PI, plaque index; GI, gingival index; GBTI, gingival bleeding time index; %GO, percentage of gingival overgrowth; GCF V, Volume of gingival crevicular fluid. \*p < 0.05.

#### TABLE 3 | Nitrite and nitrate levels in saliva, plasma, and in GCF.

\*p < 0.05.

and plasma (µM) did not significantly differ between responders and non-responders in all study groups (p > 0.05).

Correlations between saliva, GCF, and plasma nitrite/nitrate levels, periodontal clinical parameters, severity of GO, and GCF volume were presented in **Table 4**. Salivary nitrite level exhibited a significant correlation with PD, GBTI, severity of GO (%GO), and GCF volume (p < 0.05). There was no significant correlation between salivary nitrate level and periodontal clinical parameters, except PD. A strong positive correlation was detected between salivary and plasma nitrate levels (p < 0.005). There was a negative significant correlation between nitrite and nitrate levels in GCF (p < 0.05). Both nitrite and nitrate levels in GCF and plasma demonstrated no significant correlation with clinical parameters, GO severity, and GCF volume (p > 0.05).

#### DISCUSSION

To examine the role of NO in the pathogenesis of drug-induced gingival overgrowth and also to determine whether NO levels in plasma, saliva, and GCF can serve as a potential biomarker for the evaluation of drug-induced gingival overgrowth risk, nitrite and nitrate levels in saliva, GCF, and plasma were evaluated in patients receiving either CsA, phenytoin, nifedipine, or diltiazem therapy. To the best of our knowledge, this is the first study that has evaluated the association of plasma, saliva, and GCF nitrite/nitrate levels with drug-induced gingival overgrowth in patients receiving either CsA, phenytoin, nifedipine, or diltiazem therapy.

Although the pathogenesis of drug-induced gingival overgrowth is still uncertain, it is characterized by excessive deposition of extracellular matrix reflecting both elevated synthesis and reduced degradation of matrix components (Seymour et al., 1996). Fibroblasts are well-known to play a critical role in collagen synthesis and connective tissue turnover. The expression of iNOS has been demonstrated in human dermal fibroblasts (Wang et al., 1996). And, it has been reported that iNOS expression and NO production were elevated in keloid scar tissue which is characterized by excess collagen deposition (Hsu et al., 2006). Furthermore, exposure of fibroblasts to exogenous NO resulted in increased expression of collagen in a dose dependent manner (Hsu et al., 2006). Similar to these findings, increased iNOS enzyme activities were detected in overgrown gingiva from patients taking CsA (Gürkan et al., 2009). Additionally, iNOS is

largely expressed for sustained periods as a consequence of induction by bacterial lipopolysaccharide and pro-inflammatory mediators such as interleukin 1, tumor necrosis factor-α, and interferon-γ, which are present in inflamed periodontal tissues (Kendall et al., 2001). In drug-induced gingival overgrowth patients due to the abundant gingiva, plaque elimination becomes harder. When plaque accumulates and could not be eliminated, gingival inflammation takes place. Thus, prolonged production of NO by inflammatory cells in gingiva may result in excess collagen deposition via fibroblasts.

In the present study we did not collect whole saliva samples from participants due to the fact that nitrite and nitrate concentrations in whole saliva originate from sources other than the glandular cells, such as GCF and intraoral bacteria. Salivary nitrate is converted to salivary nitrite by oral bacteria (Kleinbongard et al., 2003). Thus, we used pure stimulated parotid saliva for analyzing saliva nitrite and nitrate levels.

In the present study, no significant differences were detected according to age between responders and non-responders in each drug groups. Although age has been suggested as a predisposing factor associated with drug-induced gingival overgrowth (Hefti et al., 1994; Somacarrera et al., 1994), in the present study no significant differences were detected according to age among the study groups for all the drug groups investigated. Similar to our results, Ellis et al. (1999) have reported no relations between age and drug-induced gingival overgrowth.

There were no significant differences in gender ratios between responders and non-responders in all drug groups, except for nifedipine group. In nifedipine group, males were found to be more dominant in patients developing gingival overgrowth, as previously shown before (Hattori et al., 1995; Tavassoli et al., 1998). This difference can be explained with the alteration in androgen metabolism in males.

All periodontal clinical parameters including PI, GI, GBTI, and PD were significantly higher in responders in all drug groups except for diltiazem group. These differences in periodontal clinical parameters between responders and non-responders can be explained by poor plaque control in responders due to the gingival overgrowth. In diltiazem group, although all periodontal clinical parameters were higher in responders, only the GI, GBTI, and %GO scores were significantly different. The reason for the lack of significant differences in PD and PI scores may be the limited number of responders in this drug group.

A total of 104 patients were analyzed separately in four groups according to drugs that patients were taking due to the fact that these drugs may affect directly or indirectly the NO metabolism. Patients receiving nifedipine or diltiazem were not evaluated within the same group although both of the drugs have been known as calcium channel blockers. Because it has been reported that nifedipine had an inhibitory effect on induction of NO synthesis, and also inhibited nitrite production in vascular smooth muscle cells, mesangial cells, and cardiac myocytes. However, diltiazem had no effect on nitrite formation in these three cell types (Hattori et al., 1995). Like diltiazem, it has not been demonstrated such an inhibitory effect of phenytoin on NO production (Nagatomo et al., 2000). On the other hand, it was

TABLE 4 | Correlations

 between

nitrite/nitrate

 levels and clinical periodontal

 parameters

 in whole population.

suggested that CsA could increase gingival iNOS expression (Gau et al., 2005).

The results of the present study demonstrated a significant difference in salivary nitrite and nitrate levels between responders and non-responders in phenytoin group. However, nitrite and nitrate levels in saliva did not differ significantly between responders and non-responders in other drug groups. Similarly, nitrite and nitrate levels in GCF and plasma were not significantly different between subgroups in all study groups.

Although, there have been many studies evaluating the nitrite and nitrate levels of biological fluids as a diagnostic biomarker in oral diseases and periodontitis, only few of them have focused on NO contribution to drug-induced gingival overgrowth. Fu et al. (2000) reported that significantly decreased dimensions of gingival tissues from CsA fed rats receiving L-arginine (NO substrate) or L-NAME (NO blocker) compared to control rats. They also found that plasma nitrite/nitrate concentrations were higher in L-arginine supplement. In another study conducted on rats, it was reported that significantly greater iNOS enzyme activities in gingival tissues obtained from CsA-treated rats than from control rats (Gau et al., 2005). Similarly, the plasma nitrite/nitrate levels were higher in CsA-treated rats than those in control group. In these two studies conducted on rats, nitrite and nitrate were reduced to NO and depicted as total nitrite and nitrate concentration, however nitrite and nitrate concentrations were not reported separately in studied groups. In contrast to the results of these studies, we did not found any significant differences in plasma nitrite and nitrate concentrations between responders and non-responders in all drug groups. In a clinical study, iNOS production significantly increased in connective tissue from gingivitis and CsA-induced gingival overgrowth groups (Gürkan et al., 2009). However, no intergroup differences were found regarding nitrite/nitrate levels in GCF. It was suggested that the reason of this situation might be related to the higher dilution of nitrite and nitrate by GCF volume, which was clearly elevated in responders than non-responders. Another reason might be environmental differences in oral cavity such as composition of oral flora. In the present study, similar to these results, we did not observe any significant difference in nitrite and nitrate levels of GCF between responders and non-responders in all groups.

In the present study, both nitrite and nitrate levels in saliva were found to be significantly increased in responders in phenytoin group. However, no significant differences in salivary nitrite and nitrate levels were observed between responders and non-responders in other drug groups. To the results of a clinical study comparing the NO levels in saliva with the severity of chronic periodontitis, NO levels in saliva increased with severity of chronic periodontitis (Reher et al., 2007). On contrast to these results, Topcu et al. (2014) suggested that nitrite in GCF is a better periodontal disease marker than nitrate in GCF and those in saliva. In another study of the same research group, a tendency to increase in nitrite levels in GCF and peri-implant sulcular fluid with the presence of gingival/peri-implant inflammation was reported (Tözüm et al., 2007).

When the correlations between nitrite and nitrate levels in GCF, saliva, and plasma, periodontal clinical parameters, GCF volume and severity of GO are taken into account, the nitrite level in saliva was found to be significantly correlated to PD and GBTI scores, severity of GO and GCF volume. However, nitrate levels in saliva significantly correlated only to PD score and plasma nitrate level. On the contrary, no significant correlation was found between periodontal clinical parameters, severity of GO and nitrite/nitrate levels in plasma and GCF. Based on these results, it can be suggested that nitrite and nitrate levels in saliva, especially nitrite levels, are more powerful biomarkers than those in plasma and GCF for evaluating drug-induced gingival overgrowth risk. Similar to our results, in a clinical study evaluating the diagnostic role of salivary and GCF nitrite, nitrate and nitric oxide to distinguish healthy periodontium from gingivitis and periodontitis, it was reported that detecting NO biomarker and its end metabolites in saliva is of more value to assess the periodontal health comparing to GCF (Poorsattar Bejeh-Mir et al., 2014). We also found a significant positive correlation between nitrate levels in saliva and plasma, as previously shown before (Clodfelter et al., 2015). The positive correlation between salivary nitrate and plasma nitrate might be explained by the nitrate–nitrite–NO cycle (Lundberg et al., 2008). Ingested nitrate enters the plasma and is taken back up from the circulation by the salivary glands (Lundberg and Govoni, 2004; Lundberg et al., 2008, 2009). Thus, nitrate levels in plasma and saliva are interrelated.

Nitrite and nitrate levels in biological fluids such as plasma, GCF, and saliva might be useful for diagnosis and monitoring of many diseases, including periodontal disease. However, nitrite and nitrate levels in these biological fluids do not always demonstrate the activity and expression of NOS in tissues. It is well-known that NO is produced from L-arginine by NOS in cells (Jenkins et al., 1995). On the other hand, cigarette smoking, oral medicines and supplements that contain nitro-substances, and foods such as spinach, beets, and other green leafy vegetables are exogenous sources of systemic NO (Jobgen et al., 2007). Thus, it is not appropriate to measure nitrite and nitrate levels in biological fluids as an indicator of NO synthesis when these factors are not taken into account.

The most effective treatment of drug-induced gingival overgrowth is substitution of these medications by the patient's physician. The resolution of gingival lesions may take from 1 to 8 weeks depending on the severity of overgrowth (Khocht and Schneider, 1997). However, not all patients respond to this treatment modality, especially those with long-standing gingival overgrowth (Harel-Raviv et al., 1995). Thus, surgical intervention is commonly required to solve the aesthetic and functional problems caused by gingival overgrowth.

### CONCLUSION