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Salivary Exrna Biomarkers to Detect Gingivitis and Monitor Disease Regression

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Salivary Exrna Biomarkers to Detect Gingivitis and Monitor Disease Regression Received: 3 December 2017 | Revised: 14 April 2018 | Accepted: 13 May 2018 DOI: 10.1111/jcpe.12930 OTHER Salivary exRNA biomarkers to detect gingivitis and monitor disease regression Karolina E. Kaczor-Urbanowicz1,2* | Harsh M. Trivedi3* | Patricia O. Lima1,4 | Paulo M. Camargo5 | William V. Giannobile6 | Tristan R. Grogan7 | Frederico O. Gleber-Netto8 | Yair Whiteman9 | Feng Li1 | Hyo Jung Lee10 | Karan Dharia11 | Katri Aro1 | Carmen Martin Carerras-Presas12 | Saarah Amuthan11 | Manjiri Vartak11 | David Akin1 | Hiba Al-adbullah11 | Kanika Bembey11 | Perry R. Klokkevold5 | David Elashoff7 | Virginia M. Barnes13 | Rose Richter13 | William DeVizio13 | James G. Masters3 | David T. W. Wong1 1UCLA School of Dentistry, Center for Oral/Head & Neck Oncology Research, University of California at Los Angeles, Los Angeles, California 2Section of Orthodontics, UCLA School of Dentistry, University of California at Los Angeles, Los Angeles, California 3Early Research Oral Care, Colgate Palmolive Co., Piscataway, New Jersey 4Department of Physiological Sciences, Piracicaba Dental School, University of Campinas, Piracicaba, São Paulo, Brazil 5Section of Periodontics, UCLA School of Dentistry, University of California at Los Angeles, Los Angeles, California 6Department of Periodontics and Oral Medicine, School of Dentistry, University of Michigan, Ann Arbor, Michigan 7Department of Biostatistics, University of California at Los Angeles, Los Angeles, California 8Medical Genomics Laboratory, Centro Internacional de Pesquisa e Ensino (CIPE), AC Camargo Cancer Center, São Paulo, Brazil 9UCLA School of Dentistry, Center for Esthetic Dentistry, University of California at Los Angeles, Los Angeles, California 10Section of Dentistry, Department of Periodontology, Seoul National University Bundang Hospital, Seoul, Korea 11UCLA School of Dentistry, University of California at Los Angeles, Los Angeles, California 12Faculty of Biomedical Sciences, Adult’s Dentistry Department, Universidad Europea de Madrid, Madrid, Spain 13Clinical Research Oral Care, Colgate Palmolive Co., Piscataway, New Jersey Correspondence David T. W. Wong, UCLA School of Abstract Dentistry, Center for Oral/Head & Neck Aim: This study tests the hypothesis that salivary extracellular RNA (exRNA) bio- Oncology Research (COOR), 10833 Le Conte Avenue, Los Angeles, CA 90095-1668. markers can be developed for gingivitis detection and monitoring disease Email: [email protected] regression. and William DeVizio and James G. Masters, Materials and Methods: Salivary exRNA biomarker candidates were developed from a Advanced Technology Oral Care, Colgate total of 100 gingivitis and non- gingivitis individuals using Affymetrix’s expression mi- Palmolive Co., 909 River Road, Piscataway, NJ 08855. croarrays. The top 10 differentially expressed exRNAs were tested in a clinical cohort Emails: [email protected]; to determine whether the discovered salivary exRNA markers for gingivitis were as- [email protected] sociated with clinical gingivitis and disease regression. For this purpose, unstimulated saliva was collected from 30 randomly selected gingivitis subjects, the gingival and Funding information This work was supported by a research grant plaque indexes scores were taken at baseline, 3 and 6 weeks and salivary exRNAs from the Colgate- Palmolive Company— were assayed by means of reverse transcription quantitative polymerase chain Protocol Number ERO- 2015- SAL- 03- HT and the Public Health Service (PHS) grants from reaction. the National Institutes of Health (NIH): UH3 TR000923 and R90 DE022734. *Joint first authors. J Clin Periodontol. 2018;1–12. wileyonlinelibrary.com/journal/jcpe © 2018 John Wiley & Sons A/S. | 1 Published by John Wiley & Sons Ltd 2 | KACZOR- URBANOWICZ ET AL. Results: Eight salivary exRNA biomarkers developed for gingivitis were statistically significantly changed over time, consistent with disease regression. A panel of four salivary exRNAs [SPRR1A, lnc- TET3- 2:1, FAM25A, CRCT1] can detect gingivitis with a clinical performance of 0.91 area under the curve, with 71% sensitivity and 100% specificity. Conclusions: The clinical values of the developed salivary exRNA biomarkers are as- sociated with gingivitis regression. They offer strong potential to be advanced for definitive validation and clinical laboratory development test. KEYWORDS biomarkers, exRNA, gingivitis, monitoring, saliva 1 | INTRODUCTION Clinical Relevance Periodontal diseases are the most common inflammatory diseases in humankind (Kassebaum et al., 2017). Gingivitis, the reversible form Scientific rationale for the study: Presently, the gold of the disease, is induced by the accumulation of bacterial biofilm standard for diagnosis of gingivitis includes mainly clini- that can be treated with professional biofilm removal and improve- cal examination. As a companion diagnostics, scientifi- ment in oral hygiene (Kim, Kim, & Camargo, 2013). If left untreated, cally based evaluation of gingivitis would be very gingivitis may progress to an irreversible form—periodontitis that in- beneficial as it is the most prevalent inflammatory dis- volves bone and attachment loss. Periodontitis can advance to the ease in humans. point that it induces tooth mobility and tooth loss (Kim et al., 2013). Principal findings: Principles of prospective study design It may also adversely influence systemic health via cardiovascular (PRoBE) and rigorous clinical classification of gingivitis led diseases (Kim et al., 2013), ischemic stroke (Grau et al., 2004) or can- to the development and validation of salivary exRNA bio- cers (Binder Gallimidi et al., 2015; Mitsuhashi et al., 2015; Rajesh, markers for gingivitis detection that are associated with Thomas, Hegde, & Kumar, 2013). The common risk factors for peri- disease regression. Discriminatory salivary exRNA bio- odontitis could be divided into inherited (e.g. genetic variants), and markers were developed for gingivitis detection. Four sali- those that are acquired (e.g. socioeconomic factors, poor oral hy- vary exRNA panels can discriminate gingivitis from healthy giene, cigarette smoking and diabetes) (Chapple et al., 2017). periodontium with a performance of 0.91 AUC, with 71% The quest to develop salivary biomarkers for periodontal dis- sensitivity and 100% specificity. eases has been elusive (Giannobile et al., 2009). Despite the scien- Practical implications: Salivary exRNA markers can be ob- tific acceptance of salivary biomarkers for the detection of gingivitis jective molecular indicators of periodontal health for dis- (Henskens, Van Der Velden, Veerman, & Nieuw Amerongen, 1993; ease detection as well as gingivitis regression. Kinney et al., 2011; Lee et al., 2012; Morelli et al., 2014; Shaila, Pai, & Shetty, 2013), the absence of definitively validated biomarkers did not allow for such technology to receive regulatory approval and translating this diagnostic test to move into clinical practice. that many of the affected cases are left undiagnosed and untreated Presently, the gold standard for early detection and diagnosis for gin- (Albandar & Kingman, 1999; Tomar & Asma, 2000). givitis includes a comprehensive periodontal exam along with clinical The applications of such biomarkers could be multiple. Firstly, examination (i.e. redness, swelling or gingival bleeding) performed they might be used by community at large as self- administered during dental examinations. Unfortunately, the absence of pain in point- of- care (POC) tests to screen for periodontal diseases, gingivitis often renders individuals unaware of their pathological gin- thus making people aware of the pathology in their oral cavities gival condition, particularly if they do not have to visit the dentist and to encourage them to search for a dental care. The chairside regularly (Kim et al., 2013). While very helpful, clinical parameters do POC devices will require minimal clinical training and resources, not provide full information about the current status of the disease lead to simpler, more cost- effective and less intensive treatment activity, patient- specific variations, do not predict non- responders (Giannobile, 2012). Due to close proximity of saliva to periodon- for treatment therapy and those who are “at risk” for disease pro- tal tissues and its easy collection, saliva constitutes a valuable di- gression (Ebersole, Nagarajan, Akers, & Miller, 2015). Thus, it is de- agnostic source, specifically as its collection is easy, repeatable sirable to develop objective and scientifically credible biomarkers for and can be performed by auxiliary personnel. In addition, the early detection and monitoring of periodontal diseases, especially salivary biomarkers present an attractive tool for quantitative KACZOR- URBANOWICZ ET AL. | 3 and qualitative objective evaluation and monitoring of gingivitis Bossuyt, & Potter, 2008), saliva was collected prospectively from for both scientists and dentists. The use of salivary- based POCs 750 human subjects at the UCLA School of Dentistry. The inclusion would also enable the underserved communities an improved and exclusion criteria are presented in Figure 1. Subjects were classi- access to oral health programmes as well as offers the ability to fied as healthy or gingivitis according to research and clinical criteria identify and monitor the patients at risk (Giannobile, 2012). Lastly, (Figure 1). the dental, pharmaceutical and oral health care companies could Prior to a clinical evaluation, unstimulated whole saliva was use them for optimizing the pharmaceutical
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