Abstract
Personalized Oral Healthcare has recently become the new trend word in medicine and dentistry. In this context, saliva diagnostics using various biomarkers seem to be the gateway to personalized dental diagnostics and therapy. But the terminology is not (yet) uniformly defined, furthermore it is unclear to what extent which salivary markers play a relevant role in the therapeutic decision making. In this Scoping Review, an electronic search was conducted in PubMed and Web of Science databases using medical subject headings (MESH terms) “saliva”, “biomarker”, “personality/persons”, and “dentistry”. Only human studies were included, in which repeated salivary measurements were performed to analyze monitoring effects with at least ten patients per group. PRISMA-ScR and Tricco guidelines were followed: (i) to examine what salivary biomarkers have been explored in terms of personalized oral healthcare and precision dentistry, (ii) to investigate the clinical relevance for oral health and its correlation to systemic health, and (iii) to summarize an outlook for future developments based on these results. Out of 899 studies, a total of 57 were included for data extraction in this Scoping Review, mainly focusing on periodontal therapy and patient monitoring. Salivary biomarkers have shown the potential to change the field of dentistry in all dental disciplines as a key for personalized workflows. The increasing interest in dental research is obvious, demonstrated by the growing number of publications in recent years. At this time, however, the predominant discipline is periodontology, which allows biomarker-based monitoring of the disease prevention and progression. The studies included showed heterogeneous methods using manifolds biomarkers. Therefore, no uniformly accepted concept can be presented today. Further clinical research with well-defined outcomes including standardized procedures is necessary.
Introduction
The maintenance of oral health can be achieved by preventive measures and the early detection and timely treatment of incipient oral infections, namely caries and periodontitis. Both non-communicable diseases are based on a disbalance of microbial biofilms in the oral cavity (1). Preventive measures to combat these pathogenic biofilms on a daily basis were summarized recently in different Consensus Reports (2, 3). Evidently, the most powerful individual tools for prevention and maintenance were based on self-performed oral hygiene and use of cleaning agents containing fluoride. Aside, it seems crucial to control and detect individuals' deviations of the oral health status at an early stage to hinder disease outbreak. While gold standard clinical examinations and radiographs at the dental office may miss developing disorders on a cellular base, other diagnostic tools and modern technical possibilities gain more importance (4, 5). Different biofluids, such as periphery blood, gingival crevicular fluid (GCF), and saliva were evaluated for their diagnostic or prognostic qualification for disease detection (6). The ease and non-invasiveness in saliva collection positions this biofluid as potential alternative to blood testing. Interestingly, the search for saliva diagnostics in different databases demonstrates already a high quantity of clinical investigations using saliva as target vehicle for different biomarkers in oral diseases. Saliva bathes all healthy and diseased oral surfaces in the oral cavity (7, 8). It was shown, that the oral microbiome can be quantified to a certain extent in saliva (9, 10), and even more interesting, host immune response to pathogens can be analyzed nearly in real-time (11). Furthermore, modern technologies allow the detection and quantification of specific substances in low concentrations (4, 12). Today, improvements and further developments in point-of-care devices evolve from technical progress in the era of Covid 19 (13, 14). With that much data and even more technical possibilities, the questions arise, what to actually search for.
Single salivary measurements usually present a condition at a specific timepoint. These measurements can be used to define special patient groups or signature profiles of different diseases and to detect outlier (10). In contrast, repeated salivary measurements provide information on trends, progression of disease, and on response to different treatment strategies (11, 15). Furthermore, it allows the monitoring of patients during maintenance and offers thereby the possibility to retreat timely—if needed. The outcome might help to detect personalized salivary pattern in reaction to different trigger and in future to compute custom-fit therapies for precision dentistry. This might also pave the way for real-time measurements outside the dental office and its implementation in daily life.
Based on these thoughts, the high number of clinical trials using saliva, and on the lack of structure in saliva literature, the three objectives of this Scoping Review are:
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What salivary biomarkers have been investigated in clinical trials in terms of personalized oral healthcare and precision dentistry mapped for disciplines and/or indications (key elements: choice of biomarkers, number of participants, dental disciplines)?
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What has been the clinical relevance for oral health and its correlation to systemic health?
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What can be summarized for a future outlook?
Methods
The conduct of this review follows the Arksey and O'Malley framework, modified by Levac (16, 17), omitting the consultation step. Reporting follows the PRISMA-ScR statement (18), shown in Supplementary_Data 1; in addition, the preliminary review protocol including PCC-question is available as Supplementary_Data 2.
Dentistry-related clinical trials, written in English, which investigated salivary analysis at different timepoints, and participants at least 18 years, were included. Different timepoints were defined as a minimum of two separate repeated salivary measurements at different periods. Clinical trials investigating plain general medicine subjects, without reference to the oral health status, were excluded. Clinical trials with less than 10 participants per group, and animal studies, as well as review articles were excluded.
An electronic search was performed in the database PubMed and Web of Science for relevant papers using “saliva” as the source of analysis, “biomarker” as concept, and “(personalized) dentistry” or “precision dentistry” as context. Search combinations in PubMed included: ("saliva"[MeSH Terms] OR "saliva"[All Fields] OR "salivas"[All Fields] OR "saliva s"[All Fields] OR "salivary"[All Fields]) AND ("biomarker s"[All Fields] OR "biomarkers"[MeSH Terms] OR "biomarkers"[All Fields] OR "biomarker"[All Fields]) AND ((("person s"[All Fields] OR "personable"[All Fields] OR "personableness"[All Fields] OR "personal"[All Fields] OR "personalisation"[All Fields] OR "personalise"[All Fields] OR "personalised"[All Fields] OR "personalising"[All Fields] OR "personality"[MeSH Terms] OR "personality"[All Fields] OR "personalities"[All Fields] OR "personality s"[All Fields] OR "personalization"[All Fields] OR "personalize"[All Fields] OR "personalized"[All Fields] OR "personalizes"[All Fields] OR "personalizing"[All Fields] OR "personally"[All Fields] OR "personals"[All Fields] OR "persons"[MeSH Terms] OR "persons"[All Fields] OR "person"[All Fields]) AND ("dentistry"[MeSH Terms] OR "dentistry"[All Fields] OR "dentistry s"[All Fields])) OR (("precise"[All Fields] OR "precised"[All Fields] OR "precisely"[All Fields] OR "preciseness"[All Fields] OR "precises"[All Fields] OR "precision"[All Fields] OR "precisions"[All Fields]) AND ("dentistry"[MeSH Terms] OR "dentistry"[All Fields] OR "dentistry s"[All Fields]))). All publications were included until the 30th of June 2022. The search in Web of Science was conducted with the terms “(ALL = (saliva*biomarker* ((person* and dentistry*) or (precis* and dentistry*)))).
Title and abstract screening were performed by three authors (PNP, JH, AZ) using a data chart, which was discussed during a first exploratory screening (Supplementary_Data 3). The following data items were extracted during the full-text search: first author, year of publication, country of origin (= where the study was conducted), dental discipline (e.g., periodontology, implantology, prosthodontics), topic (research question), applied salivary biomarker, monitoring intervals, total number of patients, outcome metrics/conclusion of the study, study design (Table 1). All included studies were categorized to dental disciplines, including a total number of patients per group. Major biomarkers of included studies were specified in frequency of occurrence and in their combination.
Table 1
| Study | Year | Country | Dental Discipline | Biomarker | Monitoring intervals | Patients | Study design | |
|---|---|---|---|---|---|---|---|---|
| 1 | Al-Hamoudi N (19) | 2018 | Saudi Arabia | Periodontology | Resistin, IL-6 | Baseline, 6 months | 137 | Observational study |
| 2 | Alajbeg IZ (20) | 2020 | Croatia | TMD | OS | Baseline, 3 and 6 months | 34 | RTC |
| 3 | AlJasser R (21) | 2021 | Saudi Arabia | Implantology | IL-1β, IL-6, MMP-8, TNF-α, TIMP-1 | Baseline, 1, 6 and 12 months | 60 | Case-control study |
| 4 | Aspiras MB (22) | 2013 | USA | General Dentistry | IL-1β, IL-8, MCP-1, MMP-1, MMP-3, MMP-8, MMP-9, TIMP-1, TIMP-2, TIMP-3, TIMP-4, IL-1ra, NGAL | Baseline, 21 and 49 days | 175 | RCT (single-blinded) |
| 5 | Äyräväinen L (23) | 2018 | Finland | Periodontology | IL-6, MMP-8, TIMP-1 | Baseline, 12 months | 124 | Observational study |
| 6 | Bertl K (24) | 2013 | Austria | Periodontology | Melatonin | Baseline, 3 months | 60 | Observational study |
| 7 | Bikker FJ (25) | 2019 | Denmark | Periodontology | Protease activity | -14 d, baseline, 7, 14 and 21 days | 42 | Observational study |
| 8 | Buczko P (26) | 2017 | Poland | Orthodontics | Thio-Barbituric Acid Reacting Substances (TBARS), TOS, SOD, CAT, UA, Peroxidase activity, TAS | Baseline, 1 and 24 weeks | 60 | Observational study |
| 9 | Buduneli N (27) | 2006 | Turkey | Periodontology | Glutathiode, Ascorbic Acid, TAC, Cotinine | Baseline, 1 month | 20 | Observational study |
| 10 | Chang CH (28) | 2018 | Taiwan | Periodontology | Oxidative biomarkers, Cu/Zn SOD, MnSOD, TRX1, PRX2 | Baseline, 3 months | 167 | Observational study |
| 11 | Cutando A (29) | 2013 | Spain | General Dentistry | Alkaline Phosphatase, Acid Phosphatase, Osteocalcin, Osteopontin | Baseline, 20 days | 60 | Observational study |
| 12 | Dede FÖ (30) | 2013 | Turkey | Periodontology | 8-Hydroxy-Deoxy-Guanosine (8-OHdG) | Baseline, 10 days, 1 and 3 months | 48 | Observational study |
| 13 | Fine DH (31) | 2014 | USA | Periodontology | Macrophage Inflammatory Protein (MIP) 1a / 1 b, IL-a, IL-1β, IL-8 | Baseline, 6, 12, 18, 24, 30, 36 months | 100 | Observational study |
| 14 | Fujimori K (32) | 2021 | Japan | Periodontology | miRNAs | Baseline, 2 years | 120 | Observational study |
| 15 | Ghallab N (33) | 2010 | Egypt | Periodontology | sCD44 | Baseline, 1 month | 44 | Pilot study |
| 16 | Gutiérrez-Corrales A (34) | 2017 | Spain | Oral Surgery | Total protein, IgA, Alpha-Amylase | Baseline, immediately after extraction, 2 h, 7 days | 15 | Observational study |
| 17 | Hassan SH (35) | 2015 | Egypt | Periodontology | Osteoprotegerin (OPG) | Baseline, 3 and 6 months | 30 | Observational study |
| 18 | Hendek MK (36) | 2015 | Turkey | Periodontology | 8-Hydroxy-Deoxy-Guanosine (8-OHdG), 4-Hydroxy-Nonenal (HNE), enzyme activity of Glutathione Peroxidase (GSH-Px) | Baseline, 1 and 3 months | 93 | Observational study |
| 19 | Hodosy H (37) | 2005 | Slovak republic | General Dentistry | Thio-Barbituric Acid Reacting Substances (TBARS) | Morning, afternoon, evening, 2 consecutive days | 10 | Observational study |
| 20 | Jentsch H (38) | 2004 | Germany | Periodontology | Lactoferrin, Lysozyme, Peroxidase activities | Baseline, 14 days | 25 | Observational study |
| 21 | Jenzsch A (39) | 2009 | Germany | Periodontology | Periopathogens, IL-1β, IL-6, Granulocyte Elastase activity, anti-oxidative and oxidative variables | Baseline, 2, 3 and 6 weeks, 12 months | 20 | Observational study |
| 22 | Justino AB (40) | 2017 | Brazil | General Dentistry | Salivary total protein, Nitrite, total anti-oxidant capacity, Alpha-Amylase | Baseline, after toothbrushing | 14 | Observational study |
| 23 | Kamodyová N (41) | 2013 | Slovakia | General Dentistry | Advanced oxidation protein products (AOPP), Thio-Barbituric Acid Reactive Substances (TBARS), Advanced Glycation End Products (AGEs), Ferric Reducing Antioxidant Power (FRAP), total antioxidant capacity | Morning, afternoon, evening, each, before and after toothbrushing | 19 | Observational study |
| 24 | Kibayashi M (42) | 2007 | Japan | Periodontology | Periopathogens, Prostaglandin E2, Lactoferrin, Albumin, Aspartate Aminotransferase, Lactate Dehydrogenase, Alkaline Phosphatase | Baseline, 4 years | 256 | Observational study |
| 25 | Kim HN (43) | 2022 | Korea | Periodontology | MMP-3, MMP-8, MMP-9 | Baseline, 3 and 6 weeks | 51 | Observational study |
| 26 | Kinney JS (15) | 2011 | USA | Periodontology | Periopathogens, Osteoprotegerin (OPG), MMP-9, MMP-8, IL-1β, Calprotectin, ICTP | Bi-monthly over 12 months | 100 | Observational study |
| 27 | Kochurova EV (44) | 2017 | Russia | Prosthodontics | MMP-2,MMP-8, MMP-9, TIMP-1, TIMP-2 | Baseline, 2 weeks, 3 months | 89 | Observational study |
| 28 | Koppolu P (45) | 2021 | Saudi Arabia and India | Periodontology | Alkaline Phosphatase, Acid Phosphatase | Baseline, 4 weeks | 135 | Observational study |
| 29 | Kuboniwa M (46) | 2016 | Japan | Periodontology | Metabolites assessed by GC-MS (best fitting: Cadaverine, 5-Oxoproline, Histidine) | Baseline, 15 min | 19 | Observational study |
| 30 | Lee CH (47) | 2018 | Taiwan | Periodontology | IL-1β, IL-1ra, IL-6, IL-8, Platelet-Derived Growth Factor-BB, Vascular Endothelial Growth Factor, MMP-8, MMP-9, C-Reactive Protein, Lactoferrin | Baseline, 15 min | 53 | Observational study |
| 31 | Liu KH (48) | 2016 | South Korea | Periodontology | MMP-8, MMP-9, IL-1β in GCF, Nicotine, Cotinine, Hydroxy-Cotinine in saliva | Baseline, 2, 4 and 6 weeks, 12 months | 122 | Observational study |
| 32 | Morelli T (49) | 2014 | USA | General Dentistry | IL-1β, IL-1ra, IL-8, MCP-1, MMP-1, MMP-3, MMP-8, MMP-9, TIMP-1 through TIMP- 4, Neutrophil Gelatinase-Associated Lipocalin (NGAL) | Baseline, 1, 2 and 3 weeks | 168 | Observational study |
| 33 | Nascimento GG (50) | 2019 | Denmark | Periodontology | Myeloperoxidase (MPO), Neutrophil Elastase (NE), Soluble Urokinase-type Plasminogen Activator Receptor (suPAR), MMP-8, TIMP-1 | Baseline, 1, 2 and 3 weeks | 42 | Observational study |
| 34 | Nishida N (51) | 2008 | Japan | Periodontology | Periopathogens, AST, Lactoferrin, Prostaglandin E2, IL-1β, MMP-8, MMP-9, IgA, Albumin | Baseline, 1 and 2 years | 273 | Observational study |
| 35 | Novakovic N (52) | 2014 | Serbia | Periodontology | Total antioxidant capacity, Albumin, Uric Acid, Superoxide Dismutase, Glutathione Peroxidase | Baseline, 2 months | 63 | Observational study |
| 36 | Oktay S (53) | 2020 | Turkey | Periodontology | Sialic Acid | Baseline, 3 months | 40 | Observational study |
| 37 | Önder C (54) | 2017 | Turkey | Periodontology | Malondialdehyde (MDA), 8-Hydroxy-Deoxy-Guanosine (8-OHdG), 4-Hydroxy-2-Nonenal (4-HNE) | Baseline, 6 weeks | 51 | Observational study |
| 38 | Öngöz Dede F (55) | 2016 | Turkey | Periodontology | 8-Hydroxy-Deoxy-Guanosine (8-OHdG) | Baseline, 4 weeks | 90 | Observational study |
| 39 | Park JY (56) | 2021 | Korea | Periodontology | IL-1β, IL-6, MMP-8, MMP-9 | Baseline, 4 and 8 weeks | 104 | Observational study |
| 40 | Parawani SR (57) | 2012 | India | Periodontology | Nitric Oxide (NO) | Baseline, 3 and 6 weeks | 90 | Observational study |
| 41 | Prakasam S (58) | 2014 | India | Periodontology | IL-4, IL-6, IL-10, IL-17, sTLR-2, sCD14 | Baseline, 1 and 6 weeks | 40 | Observational study |
| 42 | Raghav D (59) | 2017 | India | Prosthodontics | IL-1β, Osteoprotegerin (OPG), MMP, Periopathogens | Baseline, up to 1 year | 60 | Observational study |
| 43 | Rabelo MS (60) | 2021 | Brazil | Periodontology | IL-1β, IL-8, IL-6, IL-2, IL-5, IL-4, IL-10, Interferon Gamma (IFN-γ), Granulocyte Macrophage Colony-Stimulating Factor (GM-CSF), TNF-α | Baseline, 30 days | 60 | Observational study |
| 44 | Ramseier CA (61) | 2021 | Switzerland | Periodontology | MMP-3, MMP-8, IL-1β | Baseline, 2,4 and 8 weeks | 60 | RTC |
| 45 | Rangbulla V (62) | 2017 | India | Periodontology | IgA, IL-1β, MMP-8 | Baseline, 12 weeks | 50 | Observational study |
| 46 | Saloom HF (63) | 2017 | London | Orthodontics | Adipokines Leptin, Resistin, Myeloperoxidase (MPO), Cytokine Receptor for Nuclear Factor Kappa-B Ligand (RANKL) | Baseline, 1 h, 1 week | 55 | Observational study |
| 47 | Sanchez GA (64) | 2013 | Argentina | Periodontology | IL-1β, Prostaglandin E2 | Baseline, 3 months | 74 | Observational study |
| 48 | Sexton WM (65) | 2011 | USA | General Dentistry | IL-1β, IL-8, Macrophage Inflammatory Protein (MIP) 1α, MMP-8, Osteoprotegerin (OPG), TNF-α | Baseline, 16 and 28 weeks | 33 | Observational study |
| 49 | Silbereisen A (66) | 2020 | Sweden | Periodontology | Molecular MMP-8, TIMP-1 | Baseline, 7, 14, 21 and 35 days | 10 | Observational study |
| 50 | Syndergaard B (67) | 2014 | USA | Periodontology | IL-1β, IL-6, MMP-8, Macrophage Inflammatory Protein (MIP) 1α, Prostaglandin E2 | Baseline, 7, 10 and 30 days | 80 | Observational study |
| 51 | Tatarakis N (68) | 2014 | USA | Periodontology | Osteoprotegerin (OPG), IL-4, IL-10 | Baseline, 1 year | 32 | Observational study |
| 52 | Varghese J (69) | 2020 | India | Periodontology | 8-Hydroxy-Deoxy-Guanosine (8-OHdG) | Baseline, 3 months, | 40 | Case-Control study |
| 53 | Venza M (70) | 2006 | Italy | Periodontology | Histamine | Baseline, 6, 12 and 24 months | 125 | Observational study |
| 54 | Wu J (71) | 2018 | China | Orthodontics | Different peptide profiles assessed by Maldi-Tof | Baseline, 1, 2 weeks, 1, 2, 6 months | 36 | Observational study |
| 55 | Yarkac F (72) | 2018 | Turkey | Periodontology | IL-1β, IL-10, salivary Chromogranin A (CgA) | Baseline, after periodontal therapy | 60 | RCT |
| 56 | Yoshida RA (73) | 2019 | Brazil | Periodontology | IL-1β, IL-6, IL-8, IL-10, TNF-α, IL-12p70 | Baseline, 15 days | 38 | Observational study |
| 57 | Yoshie H (74) | 2007 | Japan | Periodontology | Aspartate Aminotransferase, Alanine Aminotransferase, Lactate Dehydrogenase | Baseline, 4 weeks | 49 | Observational study |
Included studies with extracted data items.
Results
Included studies
The Scoping Research was completed on 2022-06-30 and results are current as of this date. Of the 914 titles retrieved by the search, 899 abstracts were further screened, and successively, 60 full-texts identified. A total of 3 full-texts were excluded from the final analysis. Finally, 57 full-texts were included for data extraction (Figure 1).
Figure 1
Included studies were judged to be of sufficient quality considering the specific study design. Detailed information of each study is tabularized for general data in Table 1 (author, year of publication, country of origin, then categorized in study design, dental disciplines including topics investigated and target biomarkers, monitoring intervals, total number of patients, and outcome metrics).
The publication dates range from 2000 to 2022 with continuously increasing numbers in recent years. Study types were categorized in observational clinical studies (n = 50), RCTs (n = 4), case-control studies (n = 2), and pilot study (n = 1). A total of 4,125 patients were investigated with patient monitoring intervals from 2 h up to 3 years, depending on the respective trial design and focused research question. Dental disciplines involved were periodontology (n = 42), general dentistry (n = 7), orthodontics (n = 3), prosthodontics (n = 2), oral surgery (n = 1), implantology (n = 1), and temporo-mandibular disorders (n = 1). As explanation, the term “general dentistry” has been used for diagnostic or therapy protocols fundamental to protecting and maintaining a good standard of oral health, but not related to any dental specialty.
Depending on these classified dental disciplines, a variety of topics with diverse salivary biomarkers using different research techniques and monitoring intervals were reported. Here, main focus of salivary biomarkers investigated was on Matrix-Metalloproteinases (MMP) plus Interleukins (IL). Figure 2 shows a map of disciplines by number of studies and patients included in this Scoping Review, and Figure 3 displays the major salivary biomarkers and their distribution within the studies.
Figure 2
Figure 3
Due to the pronounced heterogeneity of the included studies, a direct comparison among the identified publications was not deemed possible. Therefore, this Scoping Review of the included full-texts followed a descriptive analysis. Supplementary_Data 3 summarizes the detailed information of the included studies.
Discussion
The aims of this Scoping Review were: (i) to compile studies on salivary biomarkers in terms of personalized oral healthcare and precision dentistry, (ii) to investigate the clinical relevance for oral health, and (iii) to summarize an outlook for future developments based on these results. “Scoping Reviews are also executed in a systematic, replicable manner, but usually intended to identify the types of available evidence in a given field and to discover knowledge gaps, to clarify concepts and definitions, and to examine how research is conducted, eventually, inform research, educational and clinical policy and priorities” (75, 76). A Scoping Review aims to “map the literature on a particular topic or research area and provide an opportunity to identify key concepts, gaps in the research; and types and sources of evidence to inform practice, policymaking, and research” (77). Therefore, the specific format Scoping Review was chosen to screen this relatively young topic and to summarize the current state of research in the context of a broad overview. Although a preliminary review protocol is available as Supplementary_Data 2, it should be noted that this Scoping Review was not registered on an online platform.
In general, precision dentistry provides diagnostic or therapeutic protocols that are as individualized as the disease with specific signs and symptoms. This approach is based on the identification of clinical information enabling the understanding of the patients' unique genomic constitution and how that makes them vulnerable to certain diseases. Each patient is to be treated with comprehensive consideration of individual circumstances using multidisciplinary channels, beyond the solely functional aspect of disease diagnosis. This also includes the continuous adjustment of therapy to keep pace with the progress of dental and medical knowledge (78, 79). It is still a very recent development: the move from purely evidence-based to personalized dentistry – and the meaning (and importance) for the dental sub-disciplines is entirely different.
Several research groups all over the world concentrate on personalized oral healthcare and precision dentistry today. The topic is of great interest in the field of dentistry, although there is (still) an imbalance in the distribution of the dental disciplines involved. The majority of all included publications were assigned to the field of periodontology, representing a proportion of 74% related to the number of studies, or 79% related to the number of patients, respectively. In restorative and reconstructive dentistry, research on salivary biomarkers seems to play a minor role at the present time. A possible explanation could be that periodontal diagnostics and treatment is very standardized following generally accepted principles (80). Therefore, it is much easier to implement personalized workflows in periodontology compared to other disciplines. For example, in reconstructive dentistry, it is per se a highly personalized discipline and uniform standard operating procedures (SOP) are hard to implement, except for situations that are directly comparable, such as complete edentulous patients (81).
The main causes of tooth loss are caries and periodontitis (82). Caries can usually be prevented very well by the patients' self-discipline with oral hygiene devices and the use of fluoride-containing toothpaste combined with mouth rinses. For periodontitis, however, clinical study outcomes could help to understand closer associations of genetic factors in periodontitis patients (83). It is therefore not surprising that with the further development of laboratory methods in recent years, salivary biomarkers have increasingly become the focus of periodontal research (84).
What saliva biomarkers have been investigated in clinical trials in terms of personalized oral healthcare and precision dentistry mapped for disciplines and/or indications?
The abundance of matrix metalloproteinases (MMP) and interleukins (IL) as salivary biomarkers was particularly striking in this Scoping Review. It was also observed that a variety of different combinations of MMP and IL were examined. Most commonly, IL-1β, MMP-8, IL-6, and MMP-9 were determined in saliva, followed by IL-8, TIMP-1, IL-10 and MMP-3. Altogether, more than 92 different biomarkers were analyzed in saliva. This leads to the conclusion that currently no consensus exists on which biomarkers should be used for what specific scientific target(s) and with which intention.
Therefore, no clear recommendations can be given related to specific salivary biomarkers associated for personalized oral healthcare principles at this time. MMP and IL seem to be the most promising biomarkers, in particular in periodontology.
What has been the clinical relevance for oral health and its correlation to systemic health?
An exciting field also seems to be the pre-therapeutic examination of saliva for risk assessment of patients with regard to specific periodontal treatment modalities. This represents a true evolution from purely evidence-based (always applied in the same way) approaches to personalized treatment cascades. It remains very exciting whether new treatment concepts can be derived from this in the future, such as the creation of pre-therapeutic risk profiles of individual patients. Training datasets could be used to compute predictive biomarkers using statistic model predictions and clinical assessments to either differentiate health conditions or to predict treatment outcomes (85). Ideally, clinical measurements, applied threshold values, handling of missing data or data below the detection limit should be described thoroughly and very precisely to allow generalizability.
Only few studies in this Scoping Review examined a possible association of oral and systemic health (n = 6): most common was obesity/nutrition (19, 55, 56), followed by diabetes mellitus (59, 68, 70), and influence of pregnancy (72).
Outlook to the future
Although salivary biomarker research appears to be extremely promising, it remains to be seen to what extent the MedTech industry will jump on this technology in the future (86). Without an economic driver, it will be difficult to further investigate this costly research topic. Besides periodontology, peri-implantitis might also be an exciting field. This is certainly also in the interest of implant manufacturers, so that financial support for research would be guaranteed. Nevertheless, the results of this Scoping Review revealed only 1 clinical trial focusing on saliva and possible association with peri-implantitis (21). In addition, dentistry could become the door-opener for routine diagnostics in medicine, e.g., assessment of glucose concentration in diabetes patients (84).
Unfortunately, the studies identified demonstrated heterogeneous quality standards, starting with the study design, the number patients included, the salivary biomarkers investigated, and monitoring intervals. Direct comparisons are not possible. It would certainly be helpful if biomarkers could be defined (according to the classification in the different dental disciplines) and then examined under standardized conditions in various clinical studies.
Salivary biomarkers have the potential to change the field of dentistry in all disciplines. The increasing interest in dental research is obvious, demonstrated by the growing number of publications in recent years. At this time, however, the predominant discipline is periodontology. Precision dentistry and personalized workflows are trendy buzzwords, the future research will proof, if the high expectations can be fulfilled. Several research groups investigating diverse salivary biomarkers in a variety of combinations. The limiting factor of Big Data research is the amount of structured data available (87, 88). Therefore, the establishment of an open research data community comprising information of salivary samples could help to foster the further development of personalized oral healthcare and precision dentistry.
Statements
Data availability statement
The original contributions presented in the study are included in the article/Supplementary Material, further inquiries can be directed to the corresponding author/s.
Author contributions
Conceptualization: TJ and NPP; Methodology: NPP, JH, ANZ and TJ, Writing-Original Draft Preparation: NPP and TJ, Writing-Review / Editing: JH, ANZ and REJ, Supervision: TJ, Project Administration: NPP and TJ. All authors contributed to the article and approved the submitted version.
Conflict of interest
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.
Publisher’s note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.
Supplementary material
The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/froh.2022.1003679/full#supplementary-material.
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Summary
Keywords
saliva, oral infections, gingivitis, periodontitis, diagnostics
Citation
Paqué PN, Hjerppe J, Zuercher AN, Jung RE and Joda T (2022) Salivary biomarkers as key to monitor personalized oral healthcare and precision dentistry: A scoping review. Front. Oral. Health 3:1003679. doi: 10.3389/froh.2022.1003679
Received
26 July 2022
Accepted
01 September 2022
Published
22 September 2022
Volume
3 - 2022
Edited by
Gustavo G. Nascimento, Aarhus University, Denmark
Reviewed by
Leandro Machado Oliveira, Federal University of Santa Maria, Brazil Elli Anna Kotsailidi, University of Rochester Medical Center, United States
Updates
Copyright
© 2022 Paqué, Hjerppe, Zuercher, Jung and Joda.
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) and the copyright owner(s) 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.
*Correspondence: Tim Joda tim.joda@zzm.uzh.ch
Specialty Section: This article was submitted to Oral Health Promotion, a section of the journal Frontiers in Oral Health
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