Chewing Over Salivary Diagnostics and the Epigenome
Over the last decade there has been substantial advances in salivary biomarker development and diagnostics. Unlike blood draws, saliva collection is noninvasive, inexpensive, and convenient for repeated sampling, making it especially useful for research in vulnerable populations, such as young children, the sick, and the elderly. This month’s thematic issue of Clinical Therapeutics highlights the recent advances in salivary diagnostics presented at the first annual North American Saliva Symposium1. Our commentary, available within that issue, surveyed the diverse field of “salivaomics”2 and reviewed new research focused on the salivary epigenome. Through the use of diverse biochemical techniques, including flow cytometry, mass spectrometry, qRT-PCR, microarray, and deep sequencing, saliva samples yield a wealth of epigenetic information relevant to healthy development and disease pathogenesis. However, methodological factors influence the validity of salivary diagnostics and must be optimized for downstream analytic targets. Furthermore, advances in salivary biomarkers and diagnostics should incorporate a critical comparison between blood and saliva sampling. The end goal of this discussion is to ignite interest in the pursuit of new biomarkers leveraging the salivary epigenome as complimentary to the existing contextual framework established in diverse domains of saliva-centric research – the salivary microbiome, proteome, endocrine analytes, genome, and transcriptome.
Prominent epigenetic markers measurable with saliva include DNA methylation, microRNA (miRNAs), and telomere length. These readily accessible analytes highlight epigenetic plasticity and its relation to developmental trajectories, health status, and environmental exposures. Furthermore, the fluctuating levels of these and other putative biomarkers in saliva illustrate how individuals change rapidly, even at a molecular level. Appreciation of the temporal dynamics of salivary diagnostics will likely result in more informative applications with enhanced predictive power for health outcomes across the lifespan.
Methylation and demethylation of DNA are central epigenetic mechanisms involved in the regulation of gene expression across development that may also reveal how environmental exposures impact both behavioral and physiologic adaptation. Salivary DNA has already been used to study methylation changes in relation to systemic conditions, as well as exposure to adversity and maltreatment. More recently, salivary DNA methylation patterns have been found to correlate with methylation patterns found across different regions of the brain in both healthy adults and clinical cohorts. In fact, methylation patterns in the brain were more correlated with total DNA methylation in saliva than blood3.
In addition to salivary DNA methylation, it is now recognized that telomeres – the distal segments of nucleotide repeats that form stabilizing caps at the ends of chromosomes – are also a dynamic element of the functional genome. Recently, monochrome multiplex qPCR (MMqPCR) has been adapted to measure the telomere length of human DNA isolated from the salivary genome4.Such an assay has the potential to establish salivary telomere length (sTL) as a direct marker of genomic stability and cellular aging with applicability across a diverse range of health conditions. Further validation of sTL may establish it as a robust biological indicator of cumulative stress exposure with predictive value for lifetime health.
Finally, saliva-based cancer diagnostics have proven to be fertile ground for identifying disease-dependent RNA panels within the salivary transcriptome. Examples of the translational utility of salivary transcriptomics in oncology have been described in a number of disease models,as well as in human clinical cohorts. Direct comparison of oral cancer biomarkers between the salivary and blood transcriptomes has suggested substantial utility for salivary analytics independent of blood-based approaches, and as more salivary biomarkers of disease are identified and validated in vitro or with animal models, the clinical efficacy of salivary diagnostics is expected to increase. Significantly, a variety of noncoding RNAs (ncRNAs), such as miRNAs, have been characterized in saliva through microarray and sequencing. The miRNAome represents another important level of epigenetic regulation responsive to both disease states and environmental exposures.
There is increasing evidence to support the utility and practicality of salivary diagnostics; however, future biomarker development must remain cognizant of methodology as translational applications are developed. This critical lens notwithstanding, the efficacy of salivary analytics is clear. Sample quality, assay sensitivity, and analytical validity are equal, or in some cases superior, to that of blood-based diagnostics for an increasing number of biomolecular analytes. The ability of this noninvasive biofluid to provide time-sensitive information uniquely positions saliva researchers to extend the range of diagnostic applications targeting the dynamic epigenome. The challenge now is how to best translate these readily available analytic approaches in salivary diagnostics to predict an individual’s long-term health and risk.
Wren ME, Shirtcliff EA, & Drury SS (2015). Not all biofluids are created equal: chewing over salivary diagnostics and the epigenome. Clinical therapeutics, 37 (3), 529-39 PMID: 25778408
1. Maron JL (2015). Bringing salivary diagnostics into the 21st century. Clinical therapeutics, 37 (3), 496-7 PMID: 25748292
2. Ai JY, Smith B, & Wong DT (2012). Bioinformatics advances in saliva diagnostics. International journal of oral science, 4 (2), 85-7 PMID: 22699264
3. Smith AK, Kilaru V, Klengel T, Mercer KB, Bradley B, Conneely KN, Ressler KJ, & Binder EB (2015). DNA extracted from saliva for methylation studies of psychiatric traits: evidence tissue specificity and relatedness to brain. American journal of medical genetics. Part B, Neuropsychiatric genetics : the official publication of the International Society of Psychiatric Genetics, 168B (1), 36-44 PMID: 25355443
4. Cawthon RM (2009). Telomere length measurement by a novel monochrome multiplex quantitative PCR method. Nucleic acids research, 37 (3) PMID: 19129229