Recent scientific advancements have been made in the use of saliva to identify several systemic diseases, oral cancer, periodontal disease, and viral infections - including Covid-19. Saliva contains a wealth of constituents that can serve as potential biomarkers of disease including DNA and RNA fragments, proteins, proteomes, hormones, and antigens. The future of saliva disease assessment (salivary diagnostics) will depend, ultimately, on the development of ‘point-of-care’ devices that can provide immediate feedback in the clinical, research, or public health setting. This represents the future of salivary diagnostics and in some cases that future is now.

The potential for saliva as a diagnostic aide was recognized in 2002 by the US based National Institute of Dental and Cranio-facial Research (the NIDCR). In light of the current pandemic, research groups throughout the US and other countries have initiated studies that seek to elucidate the diagnostic possibilities of using saliva to detect the Sars-CoV-2 virus (the virus that causes Covid-19) but it should be appreciated that prior to this current interest there has been much research assessing saliva as a potential diagnostic aide for a number of diseases [1]. This review article briefly outlines some of the more interesting innovations in salivary biomarker research and comments on the future of salivary diagnostics.

Salivary molecular biomarkers that have the potential to be indicators of systemic conditions such as cancer (including oral cancer), periodontal disease, autoimmune disease, viral and bacterial disease, and cardiovascular disease include: DNA, ctDNA, RNA, meta-RNA, RNA fragments, minor proteins, nucleic acids, various peptides, proteomes (the entire protein complement expressed by a cell), hormones, antigens, antibodies, and drugs. What makes saliva such a valuable target for molecular diagnostic research is that it is easy to retrieve and collection does not involve discomfort.

Some of the more recent studies underscoring the promise of saliva in the diagnoses of disease include those in the fields of brain research, systemic diseases (including Sjogren’s syndrome), oral cancer and other cancers, periodontal disease and infection.

As reported May 6-9, 2017, in an abstract presented at a Pediatric Academic Societies Annual Meeting in San Francisco, and subsequently in the Journal of Neurotrauma [2], micro-RNA fragments found in saliva were found to be predictive of pediatric brain concussion in children with traumatic brain injury. Micro-RNA fragments (mRNA) are short (length: 19-24 nt) non-coding molecules that are important in regulating numerous cellular processes including those involving the brain [3]. This preliminary research suggests that salivary mRNA fragments easily acquired and measured in the clinical setting, may be useful for identifying pediatric traumatic brain injury (TBI). As the authors indicate, concentrations of mRNA-320c (one of many fragments) were directly correlated with child and parent reports of attention difficulty. The test was shown to be 90 percent accurate. This contrasts with a concussion survey now commonly used that has less than 70 percent accuracy. However, additional studies assessing the influence of orthopedic injury and exercise on peripheral mRNA patterns are needed in adults and children to further understand the potential utility of this strategy for diagnosing concussion.

Researchers have identified potential salivary transcriptomic profiles for other diseases such as acute myocardial infarction, diabetes mellitus, Sjogren’s syndrome, cystic fibrosis, and Parkinson’s disease in addition to breast, pancreatic, ovarian, and gastric and lung cancer as well as melanoma [4].

A good salivary assay for identifying systemic disease should have high sensitivity, specificity, and functionality. The literature reflects optimism that these fundamental research parameters, although in some cases not currently at acceptable levels, will be improved in the future. Consequently, much work remains to be done before measurement of salivary proteins and nucleic acids yields meaningful diagnostic capability. Nonetheless, research to date has revealed some interesting results with respect to salivary proteomes and some systemic diseases. 

Saliva constituents appear to be altered in Sjogren’s syndrome (SS), an autoimmune disorder that causes, among other symptoms, dry mouth, and dry eyes. In one preliminary study, twenty five proteins in whole saliva, including ?-enolase, carbonic anhydrase I and II, and salivary ?-amylase fragments in patients with SS were found to be up-regulated and sixteen proteins expressed by the acinar cells of the glands, including lysozyme C, polymeric immunoglobulin receptor (pIgR), and calgranulin A were down-regulated as compared with the salivary proteomes of individuals without disease [5]. In another study 15 proteins in whole saliva differentiated non-SS subjects from those with SS [6]. There is also evidence that the microRNA profiles of minor labial salivary glands differ between normal subjects and those with SS [7]. These accumulated studies suggest that specific proteomic salivary biomarkers may prove useful in the development of a diagnostic panel that can be used on site to identify patients with Sjogren’s syndrome.

In recent years there has been a focus on micro RNA fragments (mRNAs) in saliva as biomarkers of oral cancer because these cellular constituents are known to have an effect on cell growth, proliferation, and apoptosis and also appear to serve as oncogenes within different cancer types [8,9]. Multiple studies suggest that mRNAs may prove useful in early detection of oral cancer and could potentially lead to changes in how oral cancer is treated [10]. Yoshizawa and Wong provide a good overview of oral cancer detection and salivary mRNAs [11].  

In a study funded, by the ‘Early Disease Research Network’ a working group within the National Cancer Institute, salivary biomarkers were assessed for their utility in discriminating patients with oral cancer from healthy subjects [12]. In this case-controlled study utilizing two independent laboratories, 395 subjects from five independent cohorts were assessed. The result was that seven mRNAs and three proteins were found to be increased in oral squamous carcinoma cancers versus controls in all the cohorts. Specifically, the increase in two markers: IL-8 and SAT demonstrated good sensitivity and specificity in predicting disease. These biomarkers were found to effectively discriminate patients with oral OSCC from healthy controls.

Other studies have identified additional proteomic salivary biomarkers potentially useful in detecting OSCC [13]. In a comparison of sera with saliva in patients with OSCC, three tumor markers: specifically Cyfra 21-1, tissue polypeptide antigen (TPA), and a cancer antigen CA125 were found to be significantly more elevated in the saliva of diseased subjects [14]. And results of an additional study suggest that five salivary proteins (M2BP, MRP14, profilin, CD59, and catalase) can discriminate oral cancer with 90% accuracy [15].

Additional research will help to fully elucidate candidate proteins that can be used to indicate the presence of OSCC [16,17]. Thus far, the research on salivary biomarkers is unclear regarding their use in defining oral cancer disease severity and progression, but the discovery of specific biomarkers that can be used to diagnose cancer presents a big step forward in salivary diagnostics. Arellano, et al. [18] and Sannam, et al. [19] provide excellent reviews covering the advancements in the identification of OSCC via salivary proteomics.

A few cancers, including those involving the ovaries, endometrial tissues, fallopian tubes, the pancreas, stomach, esophagus, colon, liver, and breast demonstrate an elevation of the cancer antigen 125 (CA 125) in blood. This protein biomarker has also been found in at least one study to be elevated in the saliva of individuals with malignant ovarian tumors. Saliva CA 125 levels were correlated with serum levels in subjects with ovarian cancer in terms of sensitivity and specificity (81.3 and 93.8 respectively). And in patients with endometriomas and pelvic tuberculosis the false positive rate was significantly lower for saliva CA 125 than serum CA 125 (13.6, 10% versus 72.7, 80%) [20]. suggesting that saliva CA 125 may have better diagnostic value for these conditions than CA 125 found in serum. However, subsequent research results are in conflict with the above findings and suggest a lack of relationship between CA 125 levels and epithelial ovarian cancer and benign gynecologic conditions so the issue of its potential diagnostic use remains cloudy [21]. More recent research suggests that better specificity and sensitivity of CA125 as a tumor biomarker may occur when the assay is combined with another biomarker HE4 [22] and the presence of mRNAs may also help in determining therapeutic response [23]. The introduction of FDA-approved algorithms is reported to have improved the ability to assess risk of ovarian cancer from sera of patients with a pelvic mass. The extent to which this applies to the same markers found in saliva remains unclear.

With advancement of methodological techniques able to identify viral DNA, RNA, mRNA proteins or salivary antibodies, a few viruses can now be identified in saliva. These include norovirus, rabies, human papillomavirus (HPV), Epstein-Barr virus, herpes simplex viruses, hepatitis C virus, cytomegalovirus (CMV), HIV, and now Covid-19 [24].

In April, the FDA authorized, by prescription only, the use of a saliva test for diagnosing Covid-19. Multiple institutions including Yale University have assessed saliva testing capability. In a letter to the editor of the NEJM, August of 2020, it is reported that a Covid-19 saliva test was used on 70 patients who had already tested positive for Covid-19 (confirmed by positive nasal swab). The author, Anne Wyllie, notes that a higher percentage of saliva samples were positive for SARS-CoV-2 at 10 days than the nasopharyngeal swab samples. She reports that at 1 to 5 days after diagnosis, 81% (95% CI, 71-96) of the saliva samples were positive, as compared with 71% (95% CI, 67-94) of the nasal specimens, suggesting that both tests were relatively equivalent in terms of sensitivity (detection of the disease). What remains a concern for both nasal swab and saliva tests, however, is their generally low sensitivity (detection of actual disease) and their degree of specificity (their ability to detect whose individuals who do not have the disease) Nonetheless, the initial reported results related to use of saliva are quite promising for its use in detecting Covid-19 disease [25].

With the Morbillivirus virus that causes measles infection, the presence of salivary antibodies demonstrates 97% sensitivity and 100% specificity [26], for Paramyxoviridae virus that causes mumps 94% sensitivity and 94% specificity [27], and for the Togaviridiae virus that causes rubella, 98% sensitivity and 98% specificity [28].

Antibodies used to diagnose HIV infection are also found in saliva and salivary assays have been shown to be as accurate as those associated with serum, particularly when plasma virus exceeds 50 copies/mL (when there is active disease) [29]. A commercial product called OraQuick has been FDA approved and is available for assessing HIV antibodies in saliva [30]^, The testing kit contains a collection stick, test tube, and testing information/directions. It is reported to be able to detect antibodies to HIV-1 and HIV-2 within 20 minutes [31].

In a move towards establishing more precise diagnosis of periodontal disease a number of salivary constituents have been considered as potential biomarkers including DNA from specific bacteria, inflammatory cytokines that are host-derived, cell death host-derived proteins, and enzyme, protein, or calcium derived factors from bone destruction [32]. The many biomarkers associated with periodontal disease. The validated biomarkers include: bacteria-derived DNA salivary (porphyromonas gingivalis, prevotella intermedia, and tannerella forsythia) host-derived in?ammatory mediators (in?ammatory cytokines (IL-1? and MIP-1?), host-derived markers associated with soft tissue destruction (MMP-8, MMP-9, HGF, lactate dehydrogenase, aspartate aminotransferase, and TIMP-2), and host-derived markers associated with bone destruction (alkaline phosphatase, osteonectin, RANKL, and calcium). Among the various salivary biomarkers listed, P. gingivalis has been shown to satisfy all the requirements for an ideal biomarker of periodontitis.

Presently periodontal disease remains a clinical diagnosis established through visual examination, periodontal probing of the gingival sulcus, and evaluation of radiographic imaging to detect bone loss. For public health and research purposes, the Community Periodontal Index (CPI) that includes a periodontal ‘probe’ and rating system defining pocket depth was developed and adopted for use by the World Health Organization [33]. Elements of the rating instrument, including a version of the probe, currently represent the standard of care in clinical practice in establishing a diagnosis of periodontal disease and its severity. Tracking the specific cellular processes associated with periodontal disease progression continues to be a problem in the context of clinical care.

However, recent advances in salivary research suggest that periodontal disease progression may be effectively tracked via integration of biologic measures (e.g. the presence of the specific biomarkers in saliva mentioned above) coupled with standard clinical and radiologic measures. Ebersole, et al., [34] in a case controlled study of 209 subjects, evaluate a specific kit (the Milliplex Map Kit – EMD Millipore, Billerica, MA, USA) to detect saliva analytes related to the biological processes of periodontitis. IL-1? and IL-6 (both cytokine inflammatory signals), MMP-8 (a primary collagenase), and MIP-1? (also known as CCL3 -a chemokine macrophage inflammatory protein) isolated alone or in combination, were found to distinguish healthy subjects from those with gingivitis and periodontitis. Their findings suggest that the salivary level of MIP-1? could have clinical utility as a screening tool for identifying moderate to severe periodontal disease and that sensitivity, specificity, and accuracy may be improved by exploring combinations of the identified biomarkers.

Other salivary constituents including the enzymes aspartate aminotransferase, alanine aminotransferase, lactate dehydrogenase (LD), and alkaline phosphatase have also been considered useful as biomarkers for diagnosing and screening periodontal disease [35]. Given that lactate dehydrogenase is related to epithelial cell breakdown, a ‘kit’ allowing quick assessment of this enzyme was tested on 70 healthy volunteers against standard periodontal examination. Salivary LD level was positively correlated with bleeding on probing and the sensitivity and specificity of the kit was 0.89 and 0.98 respectively, at a cut-off value of 8.0 for LD level. Although the above study was limited because it was cross sectional, it was concluded that the evaluated ‘kit’ could have utility in the early detection of gingivitis [36].

Additional studies suggest that assessment of salivary biomarkers may also help in determining treatment response in the management of gingivitis, with some biomarkers more important than others in defining efficacy. In a study by Syndergaard, et al., mean biomarker concentrations were found to decrease in the gingivitis groups following dental prophylaxis. However, certain markers, specifically MIP-1? and PGE₂, remained significantly higher in the healthy group [37]. Based on these results, the authors conclude that relative change in the assessed biomarkers could prove helpful in identifying diseased patients who, despite prophylaxis, might be at risk for continued chronic gingival inflammation and the development of more destructive periodontal disease.

With respect to disease progression, the accumulated research evidence suggests that a panel of optimal biomarkers must be carefully selected based on the pathogenesis of periodontitis. The biggest hurdle for the diagnosis and tracking of periodontitis progression using saliva may be validating specific disease related biomarkers as well as the efficacy of point-of-care devices within large diverse patient populations.

There are currently two point-of-care devices that have been developed for the salivary diagnosis of periodontitis: one is called the Integrated Micro?uidic Platform for Oral Diagnostics (IMPOD), the other is a lab-on-a-chip (LOC) system developed by the University of Texas. The IMPOD measures MMP-8 (a neutrophil collagenase, also known as matrix metalloproteinase-8), TNF-? (a tumor necrosis factor), IL-6, and CRP (C-reactive protein) in saliva and the LOC measures CRP, MMP-8, and IL-1?. The LOC has shown good comparative accuracy with the enzyme-linked immunosorbent assay (ELISA). The LOC device is currently undergoing clinical trials: (NCT02403297 at ClinicalTrials.gov) [38].

The emergence of Covid-19 and the worldwide pandemic underscores the need for non-invasive tests offering immediate diagnostic results. And recent developments affirm that saliva can be used to diagnose this disease as well as many others. Developments in the field of salivary diagnostics should lead to significant advances in point-of-care precision medicine and dentistry. The benefits of using saliva as a biomarker for disease are multiple. Collection of fluid is non-invasive, simple, and easily accomplished by the patient or in the clinical setting. Relative to collection of serum it is inexpensive, and clotting is not a problem as it is with serum. Saliva contains physiological markers for many conditions, both systemic as well as those localized to the oral environment [39]. Salivary diagnostic assessment will also allow for the screening of patients outside the clinical setting, for purposes of treatment monitoring, and for epidemiological research or public health screening. Combining point-of-care devices such as those currently available or those being developed for assessment and monitoring of periodontal disease and oral cancer, as well as systemic diseases, coupled with improved medical and dental electronic software communication could lead to more accurate disease tracking of patients by providers, researchers, and community health screeners via the internet and through digital charting. As pointed out by Yager, et al., “underserved communities and resource-limited areas may be accessed more efficiently than by current cumbersome and poorly utilized screening programs” [40]. Further, the use of salivary diagnostics may increase access to treatment for identified at-risk individuals not aware of developing disease and help in containing community spread of viral infections such as Covid-19. Kaczor-Urbanowicz and colleagues provide a nice overview of salivary diagnostics, the current views, and directions [41].

1. Streckfus CF, Bigler LR. Saliva as a diagnostic fluid. Oral Diseases. 2002.
2. Boyle JO, Mao L, Brennan JA, Koch WM, DW Eisele. Gene mutations in saliva as molecular markers for head and neck squamous cell carcinomas. Am J Surg 1994; 168: 429-432.
3. Hicks SD, Johnson J, Carney MC, Bramley H, Olympia RP. Overlapping microrna expression in saliva and cerebrospinal fluid accurately identifies pediatric traumatic brain injury. J Neurotrauma. 2018; 35: 64-72.
4. Hamilton J. Spit test may reveal the severity of a child's concussion. NPR 2017.
5. Aro K, Wei F, Wong DT, Tu M. Saliva liquid biopsy for point-of-care applications. Front Public Health. 2017; 5: 77.
6. Hu S, Wang J, Meijer J, Leong S, Xie YM. Salivary proteomic and genomic biomarkers for primary Sjogren’s syndrome. Arthritis Rheumatism. 2007; 56: 3588-3600.
7. Baldini C, Giusti L, Ciregia F, Valle D, Giacomelli C. Proteomic analysis of saliva: a unique tool to distinguish primary Sjögren’s syndrome from secondary Sjogren’s syndrome and other sicca syndromes. Arthritis Res Ther. 2011; 13: 194.
8. Wang Y, Zhang G, Zhang L, Zhao M, Huang H. Decreased microRNA-181a and ?16 expression levels in the labial salivary glands of Sjögren syndrome patients. Exp Ther Med. 2018; 15: 426-432.
9. Varol N, Konac E, Gurocak OS, Sozen S. The realm of microRNAs in cancers. Mol Biol Rep. 2010; 38: 1079-1089.
10. Elashoff D, Zhou H, Reiss J, Wang J, Xiao H. Pre-Validation of salivary biomarkers for oral cancer detection. Cancer Epidemiol Biomarkers Prev. 2012; 21: 664-672.
11. Cheng Y-SL, Jordan L, Rees T, Chen HS, Oxford L. Levels of potential oral cancer salivary mrna biomarkers in oral cancer patients in remission and oral lichen planus patients. Clin Oral Inven. 2014; 18: 985-993.
12. Yoshizawa JM, Wong DTW. Salivary micrornas and oral cancer detection. Methods Mol Bio. 2013; 936: 313-324.
13. Wu CC, Chu HW, Hsu CW, Chang KP, Liu HP. Saliva proteome profiling reveals potential salivary biomarkers for detection of oral cavity squamous cell carcinoma. Proteomics. 2015; 15: 3394-3404.
14. Nagler R, Bahar G, Shpitzer T, Feinmesser R. Concomitant analysis of salivary tumor markers--a new diagnostic tool for oral cancer. Clin Cancer Res. 2006; 12: 3979-3984.
15. Hu S, Arellano M, Boontheung P, Wang J, Zhou H. Salivary proteomics for oral cancer biomarker discovery. Clin Cancer Res. 2008; 14: 6246-6252.
16. Brinkmann O, Wong DT. Salivary transcriptome biomarkers in oral squamous cell cancer detection. Adv Clin Chem 2011; 55: 21-34.
17. Dowling P, Wormald R, Meleady P, Henry M, Curran A. Analysis of the saliva proteome from patients with head and neck squamous cell carcinoma reveals differences in abundance levels of proteins associated with tumour progression and metastasis. J Proteomics. 2008; 71: 168-175.
18. Arellano M, Jiang J, Zhou X, Zhang L, Ye H, et al. Current advances in identification of cancer biomarkers in saliva. Front Biosci. 2009; 1: 296-303.
19. Khan RS, Khurshid Z, Akhbar S, Moin SF Advances of salivary proteomics in oral squamous cell carcinoma (OSCC) Detection: An Update. Proteomes. 2016; 4: 41.
20. Chen DX, Schwartz PE, Li FQ. Saliva and serum CA 125 assays for detecting malignant ovarian tumors. Obstet Gynecol. 1990, 75: 701-704.
21. Plante M, Wong GY, Nisselbaum JS, Almadrones L, Hoskins WJ, et al. Relationship between saliva and serum CA 125 in women with and without epithelial ovarian cancer. Obstet Gynecol. 1993; 81: 989-992.
22. Bottoni P, Scatena R. The Role of CA 125 as Tumor marker: biochemical and clinical aspects. Adv Exp Med Biol. 2015; 867: 229-244.
23. Prahm KP, Novotny GW, Høgdall C, Høgdall E. Current status on microRNAs as biomarkers for ovarian cancer. APMIS. 2016; 124: 337-355.
24. Nagura-Ikeda M, Imai K, Tabata S, Miyoshi K, Murahara N, et al. Clinical evaluation of self-collected saliva by quantitative reverse transcription-PCR (RT-qPCR), Direct RT-qPCR, reverse transcription-loop-mediated isothermal amplification, and a rapid antigen test to diagnose COVID-19. J Clin Microbiol. 2020; 58: 01438-20.
25. Hung KF, Sun YC, Chen BH. New COVID-19 saliva-based test: How good is it compared to the current nasopharyngeal or throat swab test? J Chin Med Assoc. 2020; 10.
26. Sheikhakbari S, Mokhtari-Azad T, Salimi V, Norouzbabaei Z, Abbasi S, et al. The use of oral fluid samples spotted on filter paper for the detection of measles virus using nested rt-PCR. J Clin Lab Anal. 2012; 26: 215-522.
27. Vainio K, Samdal HH, Anestad G, Wedege E, Skutlaberg DH, et al. Detection of measles-and mumps-specific IgG antibodies in paired serum and oral fluid samples from Norwegian conscripts. Eur J Clin Microbiol Infect Dis. 2008; 27: 461-465.
28. Vijaylakshmi P, Muthukkaruppan VR, Rajasundari A, Korukluoglu G, Nigatu W, et al. Evaluation of a commercial rubella IgM assay for use on oral fluid samples for diagnosis and surveillance of congenital rubella syndrome and postnatal rubella. J Clin Virol. 2006; 37: 265-268.
29. Balamane M, Winters MA, Dalai SC, Freeman AH, Traves MW, et al. Detection of HIV-1 in Saliva: implications for case-identification, clinical monitoring and surveillance for drug resistance. Open Virol J. 2010; 4: 88-93.
30. Pascoe SJ, Langhaug LF, Mudzori J, Burke E, Hayes R, et al. Field evaluation of diagnostic accuracy of an oral fluid rapid test for HIV, tested at point-of-service sites in rural Zimbabwe. AIDS Patient Care STDS. 2009; 23: 571-576.
31. Zachary D, Mwenge L, Muyoyeta M, Shanaube K, Schaap A, et al. Field comparison of OraQuick ADVANCE Rapid HIV-1/2 antibody test and two blood-based rapid HIV antibody tests in Zambia. BMC Infect Dis. 2012; 12: 183.
32. Ji S, Choi Y. Point-of-care diagnosis of periodontitis using saliva: technically feasible but still a challenge. Front Cell Infect Microbiol. 2015; 5:65.
33. Ainamo J, Barmes D, Beagrie G, Cutress T, Martin J, et al. Development of the World Health Organization (WHO) community periodontal index of treatment needs (CPITN). Int Dental J. 1982; 32: 281-291.
34. Ebersole JL, Nagarajan R, Akers D, Miller CS. Targeted salivary biomarkers for discrimination of periodontal health and disease(s). Front Cell Infect Microbiol. 2015; 5: 62.
35. Nomura Y, Shimada Y, Hanada N, Numabe Y, Kamoi K, et al. Salivary biomarkers for predicting the progression of chronic periodontitis. Arch Oral Biol. 2012; 57: 413-420.
36. Ekuni D, Yamane-Takeuchi M, Kataoka K, Yokoi A, Taniguchi-Tabata A, et al. Validity of a new kit measuring salivary lactate dehydrogenase level for screening gingivitis. Dis Markers. 2017; 2017: 9547956.
37. Syndergaard B, Al-Sabbagh M, Kryscio RJ, Xi J, Ding X. Salivary biomarkers associated with gingivitis and response to therapy. J Periodontal. 2014; 85: 295-303.
38. Herr A, Hatch AV, Giannobile WV, Throckmorton DJ, Tran HM. Integrated microfluidic platform for oral diagnostics. Ann N Y Acad Sci. 2007; 1098: 362-374.
39. Mikkonen JJ, Singh SP, Herrala M, Lappalainen R, Myllymaa S. Salivary metabolomics in the diagnosis of oral cancer and periodontal diseases. J Periodontal Res. 2016; 51: 431-437.
40. Yager P, Edwards T, Fu E, Helton K, Nelson K. Microfluidic diagnostic technologies for global public health. Nature. 2006; 442: 412-418.
41. Kaczor-Urbanowicz KE, Martin Carreras-Presas C, Aro K, Tu M, Garcia-Godoy F. Saliva diagnostics – Current views and directions. Exp Bio Med. 2017; 242: 459-472.