Not All Biofluids Are Created Equal: Chewing Over Salivary Diagnostics and the Epigenome

Abstract

Purpose This article describes progress to date in the characterization of the salivary epigenome and considers the importance of previous work in the salivary microbiome, proteome, endocrine analytes, genome, and transcriptome. Methods PubMed and Web of Science were used to extensively search the existing literature (original research and reviews) related to salivary diagnostics and bio-marker development, of which 125 studies were examined. This article was derived from the most relevant 73 sources highlighting the recent state of the evolving field of salivary epigenomics and contributing significantly to the foundational work in saliva-based research. Findings Validation of any new saliva-based diagnostic or analyte will require comparison to previously accepted standards established in blood. Careful attention to the collection, processing, and analysis of salivary analytes is critical for the development and implementation of newer applications that include genomic, transcriptomic, and epigenomic markers. All these factors must be integrated into initial study design. Implications This commentary highlights the appeal of the salivary epigenome for translational applications and its utility in future studies of development and the interface among environment, disease, and health.

Biological Aging in Childhood and Adolescence Following Experiences of Threat and Deprivation: A Systematic Review and Meta-Analysis

“…Although there have been prior reviews and meta-analyses exploring the effects of ELA on telomere length (Coimbra et al, 2017;Price et al, 2013) or DNAm age (Gershon & High, 2015;Lewis & Olive, 2014;Silberman, Acosta, & Zorrilla Zubilete, 2016;Vinkers et al, 2015;Wolf et al, 2018), none has focused on differences across distinct adversity types or restricted the focus to studies measuring ELA and cellular aging in childhood or adolescence. Telomere length and DNAm age can be assessed through both blood and saliva samples (Wren, Shirtcliff, & Drury, 2015); we have included both measures in our analyses.…”

Depressive Symptoms and Salivary Telomere Length in a Probability Sample of Middle-Aged and Older Adults

“…These results add to our understanding of how depression may be associated with age-related illnesses and shortened life span, which may help to advance understanding of the links between depression on the one hand and health and mortality on the other hand, including potential sex differences in these pathways. Furthermore, because saliva collection is noninvasive, painless, relatively inexpensive, and rapidly renewable (15), the finding that salivary telomere length was associated with depression (and several variables treated as covariates in these analyses) suggests that assessment of the correlates and predictors of salivary telomere length holds considerable promise in understanding telomere biology.…”

“…First, whereas prior studies have evaluated telomere length obtained from DNA extracted from blood leukocytes, we examined the association between depression and telomere length obtained from DNA extracted from saliva. Saliva contains both white blood cells and epithelial cells (15), and therefore has both similarities and differences to previously used sources of DNA in studies examining the association between depression and telomere length. Presumably, the differences in leukocyte telomere length associated with depression (and other health outcomes) would be found in DNA extracted from other cells, but this hypothesis remains to be tested.…”

Orthognathic surgery induces genomewide changes longitudinally in DNA methylation in saliva

“…Analysis of biomolecules (i.e., DNA, microRNA and antibodies) enables the detection of local diseases of the mouth and throat and the prediction/diagnosis of systemic diseases and health conditions (Langie et al., 2016;Wren, Shirtcliff, & Drury, 2015). A select set of studies focusing on healthy subjects has compared DNA methylation patterns in blood and saliva (Langie et al, 2016;Smith et al, 2015;Thompson et al, 2015;Wu et al, 2014).…”