exRNA Atlas Analysis Reveals Distinct Extracellular RNA Cargo Types and Their Carriers Present across Human Biofluids.

To develop a map of cell-cell communication mediated by extracellular RNA (exRNA), the NIH Extracellular RNA Communication Consortium created the exRNA Atlas resource (https://exrna-atlas.org). The Atlas version 4P1 hosts 5,309 exRNA-seq and exRNA qPCR profiles from 19 studies and a suite of analysis and visualization tools. To analyze variation between profiles, we apply computational deconvolution. The analysis leads to a model with six exRNA cargo types (CT1, CT2, CT3A, CT3B, CT3C, CT4), each detectable in multiple biofluids (serum, plasma, CSF, saliva, urine). Five of the cargo types associate with known vesicular and non-vesicular (lipoprotein and ribonucleoprotein) exRNA carriers. To validate utility of this model, we re-analyze an exercise response study by deconvolution to identify physiologically relevant response pathways that were not detected previously. To enable wide application of this model, as part of the exRNA Atlas resource, we provide tools for deconvolution and analysis of user-provided case-control studies.

Single-stranded pre-methylated 5mC adapters uncover the methylation profile of plasma ultrashort Single-stranded cell-free DNA.

Whole-genome bisulfite sequencing (BS-Seq) measures cytosine methylation changes at single-base resolution and can be used to profile cell-free DNA (cfDNA). In plasma, ultrashort single-stranded cfDNA (uscfDNA, ∼50 nt) has been identified together with 167 bp double-stranded mononucleosomal cell-free DNA (mncfDNA). However, the methylation profile of uscfDNA has not been described. Conventional BS-Seq workflows may not be helpful because bisulfite conversion degrades larger DNA into smaller fragments, leading to erroneous categorization as uscfDNA. We describe the '5mCAdpBS-Seq' workflow in which pre-methylated 5mC (5-methylcytosine) single-stranded adapters are ligated to heat-denatured cfDNA before bisulfite conversion. This method retains only DNA fragments that are unaltered by bisulfite treatment, resulting in less biased uscfDNA methylation analysis. Using 5mCAdpBS-Seq, uscfDNA had lower levels of DNA methylation (∼15%) compared to mncfDNA and was enriched in promoters and CpG islands. Hypomethylated uscfDNA fragments were enriched in upstream transcription start sites (TSSs), and the intensity of enrichment was correlated with expressed genes of hemopoietic cells. Using tissue-of-origin deconvolution, we inferred that uscfDNA is derived primarily from eosinophils, neutrophils, and monocytes. As proof-of-principle, we show that characteristics of the methylation profile of uscfDNA can distinguish non-small cell lung carcinoma from non-cancer samples. The 5mCAdpBS-Seq workflow is recommended for any cfDNA methylation-based investigations.

Discovery and validation of plasma, saliva and multi-fluid plasma-saliva metabolomic scores predicting insulin resistance and diabetes progression or regression among Puerto Rican adults.

AIMS/HYPOTHESIS: Many studies have examined the relationship between plasma metabolites and type 2 diabetes progression, but few have explored saliva and multi-fluid metabolites. METHODS: We used LC/MS to measure plasma (n=1051) and saliva (n=635) metabolites among Puerto Rican adults from the San Juan Overweight Adults Longitudinal Study. We used elastic net regression to identify plasma, saliva and multi-fluid plasma-saliva metabolomic scores predicting baseline HOMA-IR in a training set (n=509) and validated these scores in a testing set (n=340). We used multivariable Cox proportional hazards models to estimate HRs for the association of baseline metabolomic scores predicting insulin resistance with incident type 2 diabetes (n=54) and prediabetes (characterised by impaired glucose tolerance, impaired fasting glucose and/or high HbA1c) (n=130) at 3 years, along with regression from prediabetes to normoglycaemia (n=122), adjusting for traditional diabetes-related risk factors. RESULTS: Plasma, saliva and multi-fluid plasma-saliva metabolomic scores predicting insulin resistance included highly weighted metabolites from fructose, tyrosine, lipid and amino acid metabolism. Each SD increase in the plasma (HR 1.99 [95% CI 1.18, 3.38]; p=0.01) and multi-fluid (1.80 [1.06, 3.07]; p=0.03) metabolomic scores was associated with higher risk of type 2 diabetes. The saliva metabolomic score was associated with incident prediabetes (1.48 [1.17, 1.86]; p=0.001). All three metabolomic scores were significantly associated with lower likelihood of regressing from prediabetes to normoglycaemia in models adjusting for adiposity (HRs 0.72 for plasma, 0.78 for saliva and 0.72 for multi-fluid), but associations were attenuated when adjusting for lipid and glycaemic measures. CONCLUSIONS/INTERPRETATION: The plasma metabolomic score predicting insulin resistance was more strongly associated with incident type 2 diabetes than the saliva metabolomic score. Only the saliva metabolomic score was associated with incident prediabetes.

The Kinetics of COVID-19 Vaccine Response in a Community-Vaccinated Population.

We used a noninvasive electrochemical quantitative assay for IgG Abs to SARS-CoV-2 S1 Ag in saliva to investigate the kinetics of Ab response in a community-based population that had received either the Pfizer or Moderna mRNA-based vaccine. Samples were received from a total of 97 individuals, including a subset of 42 individuals who collected samples twice weekly for 3 mo or longer. In all, >840 samples were collected and analyzed. In all individuals, salivary SARS-CoV-2 S1 IgG Ab levels rose sharply in the 2-wk period after their second vaccination, with peak Ab levels seen at 10-20 d after vaccination. We observed that 20%, 10%, and 2.4% of individuals providing serial samples had a 90%, 95%, and 99% drop, respectively, from peak levels during the duration of monitoring, and in two patients, Abs fell to prevaccination levels (5%). The use of noninvasive quantitative salivary Ab measurement can allow widespread, cost-effective monitoring of vaccine response.

The Association Between Retinal Thickness Fluctuations and Visual Outcomes Under Anti-VEGF Therapy: A Systematic Review and Meta-Analysis.

INTRODUCTION: To examine the association between retinal thickness (RT) fluctuations and best-corrected visual acuity (BCVA) in eyes with neovascular AMD, macular edema secondary to RVO, and DME treated with anti-VEGF therapy. METHODS: A systematic search of Ovid MEDLINE, EMBASE, and the Cochrane Library was performed from January 2006 to March 2024. Studies comparing visual or anatomic outcomes of patients treated with anti-VEGF therapy, stratified by magnitudes of RT fluctuation, were included. ROBINS-I and Cochrane RoB 2 tools were used to assess risk of bias, and certainty of evidence was evaluated with GRADE criteria. Meta-analysis was performed with a random effects model. Primary outcomes were final BCVA and change in BCVA relative to baseline. RESULTS: 15725 articles were screened; 15 studies were identified in the systematic review and 5 studies were included in the meta-analysis. Final ETDRS VA was significantly worse in eyes with the highest level of RT fluctuation (weighted mean difference (WMD) = 7.86 letters; 95% CI, 4.97, 10.74; p < 0.00001; I² = 81%; 3136 eyes). RT at last observation was significantly greater in eyes with high RT fluctuations (WMD = -27.35 µm; 95% CI, -0.04, 54.75; p = 0.05; I2 = 88%; 962 eyes). CONCLUSIONS: Final visual outcome is associated with magnitude of RT fluctuation over the course of therapy. It is unclear whether minimizing RT fluctuations would help to optimize visual outcomes in patients treated with anti-VEGF therapy. These findings are limited by a small set of studies, risk of bias, and considerable heterogeneity.

Distinct Features of Plasma Ultrashort Single-Stranded Cell-Free DNA as Biomarkers for Lung Cancer Detection.

BACKGROUND: Using broad range cell-free DNA sequencing (BRcfDNA-Seq), a nontargeted next-generation sequencing (NGS) methodology, we previously identified a novel class of approximately 50 nt ultrashort single-stranded cell-free DNA (uscfDNA) in plasma that is distinctly different from 167 bp mononucleosomal cell-free DNA (mncfDNA). We hypothesize that uscfDNA possesses characteristics that are useful for disease detection. METHODS: Using BRcfDNA-Seq, we examined both cfDNA populations in the plasma of 18 noncancer controls and 14 patients with late-stage nonsmall cell lung carcinoma (NSCLC). In comparison to mncfDNA, we assessed whether functional element (FE) peaks, fragmentomics, end-motifs, and G-Quadruplex (G-Quad) signatures could be useful features of uscfDNA for NSCLC determination. RESULTS: In noncancer participants, compared to mncfDNA, uscfDNA fragments showed a 45.2-fold increased tendency to form FE peaks (enriched in promoter, intronic, and exonic regions), demonstrated a distinct end-motif-frequency profile, and presented with a 4.9-fold increase in G-Quad signatures. Within NSCLC participants, only the uscfDNA population had discoverable FE peak candidates. Additionally, uscfDNA showcased different end-motif-frequency candidates distinct from mncfDNA. Although both cfDNA populations showed increased fragmentation in NSCLC, the G-Quad signatures were more discriminatory in uscfDNA. Compilation of cfDNA features using principal component analysis revealed that the first 5 principal components of both cfDNA subtypes had a cumulative explained variance of >80%. CONCLUSIONS: These observations indicate that the distinct biological processes of uscfDNA and that FE peaks, fragmentomics, end-motifs, and G-Quad signatures are uscfDNA features with promising biomarker potential. These findings further justify its exploration as a distinct class of biomarker to augment pre-existing liquid biopsy approaches.

Single-Droplet Microsensor for Ultra-Short Circulating EFGR Mutation Detection in Lung Cancer Based on Multiplex EFIRM Liquid Biopsy.

Liquid biopsy is a rapidly emerging field that involves the minimal/non-invasive assessment of signature somatic mutations through the analysis of circulating tumor DNA (ctDNA) shed by tumor cells in bodily fluids. Broadly speaking, the unmet need in liquid biopsy lung cancer detection is the lack of a multiplex platform that can detect a mutation panel of lung cancer genes using a minimum amount of sample, especially for ultra-short ctDNA (usctDNA). Here, we developed a non-PCR and non-NGS-based single-droplet-based multiplexing microsensor technology, "Electric-Field-Induced Released and Measurement (EFIRM) Liquid Biopsy" (m-eLB), for lung cancer-associated usctDNA. The m-eLB provides a multiplexable assessment of usctDNA within a single droplet of biofluid in only one well of micro-electrodes, as each electrode is coated with different probes for the ctDNA. This m-eLB prototype demonstrates accuracy for three tyrosine-kinase-inhibitor-related EGFR target sequences in synthetic nucleotides. The accuracy of the multiplexing assay has an area under the curve (AUC) of 0.98 for L858R, 0.94 for Ex19 deletion, and 0.93 for T790M. In combination, the 3 EGFR assay has an AUC of 0.97 for the multiplexing assay.

Urinary Cell-Free DNA in Liquid Biopsy and Cancer Management.

BACKGROUND: The current methodology used to detect, diagnose, and monitor many types of cancers requires invasive tissue biopsy testing. Recently, liquid biopsy using blood, plasma, urine, saliva, and various other bodily fluids has shown utility to solve many issues associated with tissue biopsy. Blood/plasma has received most of the attention within the liquid biopsy field, however, obtaining blood samples from patients is still somewhat invasive and requires trained professionals. Using urine to detect cell-free DNA cancer biomarkers offers a truly non-invasive sampling method that can be easily and reproducibly conducted by patients. CONTENT: Novel technologies and approaches have made the detection of small quantities of cell-free tumor DNA of varying lengths possible. Recent studies using urine circulating tumor DNA to detect cancer mutations and other biomarkers have shown sensitivity comparable to blood/plasma cell-free DNA liquid biopsy for many cancer types. Thus, urine cell-free DNA liquid biopsy may replace or provide supplementary information to tissue/blood biopsies. Further investigation with larger patient cohorts and standardization of pre-analytical factors is necessary to determine the utility of urine cell-free DNA liquid biopsy for cancer detection, diagnosis, and monitoring in a clinical setting. SUMMARY: In this mini-review we discuss the biological aspects of cell-free DNA in urine, numerous studies using urine cell-free DNA to detect urological cancers, and recent studies using urine cell-free DNA to detect and monitor non-urological cancers including lung, breast, colorectal, and other cancers.

Integrated Multiomics Analysis of Salivary Exosomes to Identify Biomarkers Associated with Changes in Mood States and Fatigue.

Fatigue and other deleterious mood alterations resulting from prolonged efforts such as a long work shift can lead to a decrease in vigilance and cognitive performance, increasing the likelihood of errors during the execution of attention-demanding activities such as piloting an aircraft or performing medical procedures. Thus, a method to rapidly and objectively assess the risk for such cognitive fatigue would be of value. The objective of the study was the identification in saliva-borne exosomes of molecular signals associated with changes in mood and fatigue that may increase the risk of reduced cognitive performance. Using integrated multiomics analysis of exosomes from the saliva of medical residents before and after a 12 h work shift, we observed changes in the abundances of several proteins and miRNAs that were associated with various mood states, and specifically fatigue, as determined by a Profile of Mood States questionnaire. The findings herein point to a promising protein biomarker, phosphoglycerate kinase 1 (PGK1), that was associated with fatigue and displayed changes in abundance in saliva, and we suggest a possible biological mechanism whereby the expression of the PGK1 gene is regulated by miR3185 in response to fatigue. Overall, these data suggest that multiomics analysis of salivary exosomes has merit for identifying novel biomarkers associated with changes in mood states and fatigue. The promising biomarker protein presents an opportunity for the development of a rapid saliva-based test for the assessment of these changes.

Consensus statements on the clinical usage and characteristics of aripiprazole for Hong Kong.

Aripiprazole, a dopamine partial agonist, is a second-generation anti-psychotic that is widely used for the treatment of schizophrenia and other psychotic disorders. A group of psychiatric experts in Hong Kong developed a set of consensus statements, aiming to facilitate the understanding of clinical properties and usages of aripiprazole among local physicians. Of note, because aripiprazole long-acting injectable has been available locally not long before the establishment of the consensus panel, which limited the discussion on its use in the local context, the consensus statements were focused primarily on oral aripiprazole. To draft the consensus statements, the panellists discussed the published evidence and their clinical experience regarding aripiprazole in a series of meetings based on several areas. At the final meeting, each drafted statement was voted on anonymously by all panellists based on its practicability of recommendation in Hong Kong. A set of consensus statements on the characteristics and clinical use of aripiprazole was established and accepted by the panel. These statements serve to provide a practical reference for physicians in Hong Kong, and possibly other parts of the Asia-Pacific region, on the use of aripiprazole in people with schizophrenia spectrum disorders and other psychotic problems.

Novel approaches for bioinformatic analysis of salivary RNA sequencing data for development.

Motivation: Analysis of RNA sequencing (RNA-Seq) data in human saliva is challenging. Lack of standardization and unification of the bioinformatic procedures undermines saliva's diagnostic potential. Thus, it motivated us to perform this study. Results: We applied principal pipelines for bioinformatic analysis of small RNA-Seq data of saliva of 98 healthy Korean volunteers including either direct or indirect mapping of the reads to the human genome using Bowtie1. Analysis of alignments to exogenous genomes by another pipeline revealed that almost all of the reads map to bacterial genomes. Thus, salivary exRNA has fundamental properties that warrant the design of unique additional steps while performing the bioinformatic analysis. Our pipelines can serve as potential guidelines for processing of RNA-Seq data of human saliva. Availability and implementation: Processing and analysis results of the experimental data generated by the exceRpt (v4.6.3) small RNA-seq pipeline (github.gersteinlab.org/exceRpt) are available from exRNA atlas (exrna-atlas.org). Alignment to exogenous genomes and their quantification results were used in this paper for the analyses of small RNAs of exogenous origin. Contact: dtww@ucla.edu.

Identification of salivary metabolites for oral squamous cell carcinoma and oral epithelial dysplasia screening from persistent suspicious oral mucosal lesions.

OBJECTIVE: To identify salivary metabolite biomarkers to differentiate patients with oral squamous cell carcinoma and oral epithelial dysplasia (OSCC/OED) from those with persistent suspicious oral mucosal lesions (PSOML). SUBJECTS AND METHODS: Whole unstimulated saliva samples were collected from age-, sex-, and race-matched patients who had a lesion in the oral cavity and for whom open biopsies were performed. The patients included OSCC (n = 6), OED (n = 10), and PSOML (n = 32). Hydrophilic metabolites in saliva samples were comprehensively analyzed using capillary electrophoresis mass spectrometry. To evaluate the discrimination ability of a combination of multiple markers, a multiple logistic regression (MLR) model was developed to differentiate OSCC/OED from PSOML. RESULTS: Six metabolites were significantly different in OSCC/OED compared with PSOML. From these six metabolites, ornithine, o-hydroxybenzoate, and ribose 5-phosphate (R5P) were used to develop the MLR model, which resulted in a high value for the area under receiver operating characteristic curve (AUC 0.871, 95% confidential interval (CI) 0.760-0.982; p < 0.001) to discriminate OSCC/OED from PSOML. CONCLUSIONS: This is the first study to identify salivary metabolites that discriminate OSCC/OED from PSOML rather than from healthy controls. The profiles of salivary metabolites were significantly different between OSCC/OED and PSOML. The ability to discriminate OSCC/OED from PSOML is important for dentists who are not oral surgery specialists. These salivary metabolites showed potential for non-invasive screening to discriminate OSCC/OED from PSOML. CLINICAL RELEVANCE: Salivary metabolites in this study showed potential for non-invasive screening to discriminate OSCC/OED from PSOML.

Characterization of Human Salivary Extracellular RNA by Next-generation Sequencing.

BACKGROUND: It was recently discovered that abundant and stable extracellular RNA (exRNA) species exist in bodily fluids. Saliva is an emerging biofluid for biomarker development for noninvasive detection and screening of local and systemic diseases. Use of RNA-Sequencing (RNA-Seq) to profile exRNA is rapidly growing; however, no single preparation and analysis protocol can be used for all biofluids. Specifically, RNA-Seq of saliva is particularly challenging owing to high abundance of bacterial contents and low abundance of salivary exRNA. Given the laborious procedures needed for RNA-Seq library construction, sequencing, data storage, and data analysis, saliva-specific and optimized protocols are essential. METHODS: We compared different RNA isolation methods and library construction kits for long and small RNA sequencing. The role of ribosomal RNA (rRNA) depletion also was evaluated. RESULTS: The miRNeasy Micro Kit (Qiagen) showed the highest total RNA yield (70.8 ng/mL cell-free saliva) and best small RNA recovery, and the NEBNext library preparation kits resulted in the highest number of detected human genes [5649-6813 at 1 reads per kilobase RNA per million mapped (RPKM)] and small RNAs [482-696 microRNAs (miRNAs) and 190-214 other small RNAs]. The proportion of human RNA-Seq reads was much higher in rRNA-depleted saliva samples (41%) than in samples without rRNA depletion (14%). In addition, the transfer RNA (tRNA)-derived RNA fragments (tRFs), a novel class of small RNAs, were highly abundant in human saliva, specifically tRF-4 (4%) and tRF-5 (15.25%). CONCLUSIONS: Our results may help in selection of the best adapted methods of RNA isolation and small and long RNA library constructions for salivary exRNA studies.

Discovery and Validation of Salivary Extracellular RNA Biomarkers for Noninvasive Detection of Gastric Cancer.

BACKGROUND: Biomarkers are needed for noninvasive early detection of gastric cancer (GC). We investigated salivary extracellular RNA (exRNA) biomarkers as potential clinical evaluation tools for GC. METHODS: Unstimulated whole saliva samples were prospectively collected from 294 individuals (163 GC and 131 non-GC patients) who underwent endoscopic evaluation at the Samsung Medical Center in Korea. Salivary transcriptomes of 63 GC and 31 non-GC patients were profiled, and mRNA biomarker candidates were verified with reverse transcription quantitative real-time PCR (RT-qPCR). In parallel, microRNA (miRNA) biomarkers were profiled and verified with saliva samples from 10 GC and 10 non-GC patients. Candidate biomarkers were validated with RT-qPCR in an independent cohort of 100/100 saliva samples from GC and non-GC patients. Validated individual markers were configured into a best performance panel. RESULTS: We identified 30 mRNA and 15 miRNA candidates whose expression pattern associated with the presence of GC. Among them, 12 mRNA and 6 miRNA candidates were verified with the discovery cohort by RT-qPCR and further validated with the independent cohort (n = 200). The configured biomarker panel consisted of 3 mRNAs (SPINK7, PPL, and SEMA4B) and 2 miRNAs (MIR140-5p and MIR301a), which were all significantly down-regulated in the GC group, and yielded an area under the ROC curve (AUC) of 0.81 (95% CI, 0.72-0.89). When combined with demographic factors, the AUC of the biomarker panel reached 0.87 (95% CI, 0.80-0.93). CONCLUSIONS: We have discovered and validated a panel of salivary exRNA biomarkers with credible clinical performance for the detection of GC. Our study demonstrates the potential utility of salivary exRNA biomarkers in screening and risk assessment for GC.

Saliva exosomes from pancreatic tumor-bearing mice modulate NK cell phenotype and antitumor cytotoxicity.

Tumor exosomes are emerging as antitumor immunity regulators; however, their effects on secondary exosome secretion by distal organs have not been explored. We have previously demonstrated that suppression of exosomes at the distal tumor site of pancreatic ductal adenocarcinoma (PDAC) ablated the development of salivary biomarker profile. Here, we explore the function of salivary exosomes from tumor-bearing mice in immune surveillance. We provide evidence that salivary exosomes from mice with PDAC exhibit a suppressive effect that results in reduced tumor-killing capacity by NK cells. Salivary exosomes from mice with PDAC where pancreatic tumors were engineered to suppress exosome biogenesis failed to suppress NK cell cytotoxic potential against tumor cells, as opposed to salivary exosomes from mice with PDAC with normal tumor exosome biogenesis. These results reveal an important and previously unknown mechanism of antitumor immune regulation and provide new insights into our understanding of the alterations of this biofluid during tumor development.-Katsiougiannis, S., Chia, D., Kim, Y., Singh, R. P., Wong, D. T. W. Saliva exosomes from pancreatic tumor-bearing mice modulate NK cell phenotype and antitumor cytotoxicity.

Salivary exRNA biomarkers to detect gingivitis and monitor disease regression.

AIM: This study tests the hypothesis that salivary extracellular RNA (exRNA) biomarkers can be developed for gingivitis detection and monitoring disease regression. MATERIALS AND METHODS: Salivary exRNA biomarker candidates were developed from a total of 100 gingivitis and non-gingivitis individuals using Affymetrix's expression microarrays. The top 10 differentially expressed exRNAs were tested in a clinical cohort to determine whether the discovered salivary exRNA markers for gingivitis were associated with clinical gingivitis and disease regression. For this purpose, unstimulated saliva was collected from 30 randomly selected gingivitis subjects, the gingival and plaque indexes scores were taken at baseline, 3 and 6 weeks and salivary exRNAs were assayed by means of reverse transcription quantitative polymerase chain reaction. 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 associated with gingivitis regression. They offer strong potential to be advanced for definitive validation and clinical laboratory development test.

Emerging technologies for salivaomics in cancer detection.

Salivary diagnostics has great potential to be used in the early detection and prevention of many cancerous diseases. If implemented with rigour and efficiency, it can result in improving patient survival times and achieving earlier diagnosis of disease. Recently, extraordinary efforts have been taken to develop non-invasive technologies that can be applied without complicated and expensive procedures. Saliva is a biofluid that has demonstrated excellent properties and can be used as a diagnostic fluid, since many of the biomarkers suggested for cancers can also be found in whole saliva, apart from blood or other body fluids. The currently accepted gold standard methods for biomarker development include chromatography, mass spectometry, gel electrophoresis, microarrays and polymerase chain reaction-based quantification. However, salivary diagnostics is a flourishing field with the rapid development of novel technologies associated with point-of-care diagnostics, RNA sequencing, electrochemical detection and liquid biopsy. Those technologies will help introduce population-based screening programs, thus enabling early detection, prognosis assessment and disease monitoring. The purpose of this review is to give a comprehensive update on the emerging diagnostic technologies and tools for the early detection of cancerous diseases based on saliva.

The emerging landscape of salivary diagnostics.

Saliva contains a variety of biomolecules, including DNA, coding and noncoding RNA, proteins, metabolites and microbiota. The changes in the salivary levels of these molecular constituents can be used to develop markers for disease detection and risk assessment. Use of saliva as an early-detection tool is a promising approach because collection of saliva is easy and noninvasive. Here, we review recent developments in salivary diagnostics, accomplished using salivaomics approaches, including genomic, transcriptomic, proteomic, metabolomic and microbiomic technologies. Additionally, we illustrate the mechanisms of how diseases distal from the oral cavity can lead to the appearance of discriminatory biomarkers in saliva, and discuss the relevance of these markers for translational and clinical applications.

The landscape of microRNA, Piwi-interacting RNA, and circular RNA in human saliva.

BACKGROUND: Extracellular RNAs (exRNAs) in human body fluids are emerging as effective biomarkers for detection of diseases. Saliva, as the most accessible and noninvasive body fluid, has been shown to harbor exRNA biomarkers for several human diseases. However, the entire spectrum of exRNA from saliva has not been fully characterized. METHODS: Using high-throughput RNA sequencing (RNA-Seq), we conducted an in-depth bioinformatic analysis of noncoding RNAs (ncRNAs) in human cell-free saliva (CFS) from healthy individuals, with a focus on microRNAs (miRNAs), piwi-interacting RNAs (piRNAs), and circular RNAs (circRNAs). RESULTS: Our data demonstrated robust reproducibility of miRNA and piRNA profiles across individuals. Furthermore, individual variability of these salivary RNA species was highly similar to those in other body fluids or cellular samples, despite the direct exposure of saliva to environmental impacts. By comparative analysis of >90 RNA-Seq data sets of different origins, we observed that piRNAs were surprisingly abundant in CFS compared with other body fluid or intracellular samples, with expression levels in CFS comparable to those found in embryonic stem cells and skin cells. Conversely, miRNA expression profiles in CFS were highly similar to those in serum and cerebrospinal fluid. Using a customized bioinformatics method, we identified >400 circRNAs in CFS. These data represent the first global characterization and experimental validation of circRNAs in any type of extracellular body fluid. CONCLUSIONS: Our study provides a comprehensive landscape of ncRNA species in human saliva that will facilitate further biomarker discoveries and lay a foundation for future studies related to ncRNAs in human saliva.