Saliva Protein Biomarkers Research Articles

Potential protein biomarkers in saliva for detection of frailty syndrome by targeted proteomics

Frailty is a physiological geriatric syndrome, caused by immunosenescence, inflammation and alterations at the protein level leading to metabolic and microbiota changes. Currently, this syndrome is evaluated clinically with the Frailty-VIG index. The aim of the study was therefore to investigate the potential suitability of saliva as a non-invasive proximal biological fluid for the characterisation and identification of possible protein-level biomarkers in frailty syndrome. This cross-sectional study was conducted in a rural population of older Spanish adults using the SMR proteomics technique. A differential protein profile of eight potential and surrogate proteins (CYTC, CYTD, CYTS, CYTB, MIF, ALBU, CD44 and B2MG) was detected in saliva, all of which correlated with factors characterising frailty syndrome, such as vascular ageing (arterial stiffness and cardiovascular disease), obesity, mood problems, global cognitive impairment, changes in gait and hand pressure strength. The proteins CYTD (r = 0.415, p = 0.013) and CYTC (r = 0.280, p = 0.026), which were detected differentially in the protein profile, were associated with the Frailty-VIG index. All analysed proteins are associated not only with the clinical symptoms of frailty syndrome, but also with an acute inflammatory response, endothelial cell proliferation and the complement system, among others.

Label-Free SERS and MD Analysis of Biomarkers for Rapid Point-of-Care Sensors Detecting Head and Neck Cancer and Infections.

For the progress of point-of-care medicine, where individual health status can be easily and quickly monitored using a handheld sensor, saliva serves as one of the best-suited body fluids thanks to its availability and abundance of physiological indicators. Salivary biomarkers, combined with rapid and highly sensitive detection tools, may pave the way to new real-time health monitoring and personalized preventative therapy branches using saliva as a target matrix. Saliva is increasing in importance in liquid biopsy, a non-invasive approach that helps physicians diagnose and characterize specific diseases in patients. Here, we propose a proof-of-concept study combining the unique specificity in biomolecular recognition provided by surface-enhanced Raman spectroscopy (SERS) in combination with molecular dynamics (MD) simulations, which give leave to explore the biomolecular absorption mechanism on nanoparticle surfaces, in order to verify the traceability of two validated salivary indicators, i.e., interleukin-8 (IL-8) and lysozyme (LYZ), implicated in oropharyngeal squamous cell carcinoma (OSCC) and oral infection. This strategy simultaneously assures the detection and interpretation of protein biomarkers in saliva, ultimately opening a new route for the evolution of fast and accurate point-of-care SERS-based sensors of interest in precision medicine diagnostics.

Identification of novel salivary candidate protein biomarkers for tuberculosis diagnosis: A preliminary biomarker discovery study

BackgroundThere is an urgent need for new, accurate, rapid, and affordable tuberculosis (TB) diagnostic tests. The aim of the present study was to use mass spectrometry to identify new preliminary candidate TB diagnostic protein biomarkers in saliva obtained from individuals with TB, and patients with other respiratory diseases (ORD). MethodsSaliva samples were collected from 22 individuals who self-presented with symptoms suggestive of TB as part of a larger TB biomarker project. Purified salivary proteins were subjected to tryptic digestion peptides were analyzed using a QExactive Orbitrap Mass Spectrometer. Data are available via ProteomeXchange with identifier PXD027294. Identified proteins were subjected to gene ontology and ingenuity pathway analysis for functional enrichment analysis. Results26 of the 652 identified proteins significantly discriminated individuals with TB from those with ORD after Benjamini Hochberg correction (5% FDR), with five of these proteins diagnosing TB with an AUC ≥ 0.80. A 5-protein biosignature comprising of P01011, Q8NCW5, P28072, A0A2Q2TTZ9, and Q99574 diagnosed TB with an AUC of 1.00 (95% CI, 1.00–1.00), sensitivity of 100% (95% CI, 76.2–100%) and specificity of 90.9% (95% CI, 58.7–99.8%) after leave-one-out cross validation. ConclusionsWe identified novel candidate salivary protein biomarkers and biosignatures with strong potential as TB diagnostic candidates. Our results are preliminary and require validation in larger studies.

CapsNet-SSP: multilane capsule network for predicting human saliva-secretory proteins

BackgroundCompared with disease biomarkers in blood and urine, biomarkers in saliva have distinct advantages in clinical tests, as they can be conveniently examined through noninvasive sample collection. Therefore, identifying human saliva-secretory proteins and further detecting protein biomarkers in saliva have significant value in clinical medicine. There are only a few methods for predicting saliva-secretory proteins based on conventional machine learning algorithms, and all are highly dependent on annotated protein features. Unlike conventional machine learning algorithms, deep learning algorithms can automatically learn feature representations from input data and thus hold promise for predicting saliva-secretory proteins.ResultsWe present a novel end-to-end deep learning model based on multilane capsule network (CapsNet) with differently sized convolution kernels to identify saliva-secretory proteins only from sequence information. The proposed model CapsNet-SSP outperforms existing methods based on conventional machine learning algorithms. Furthermore, the model performs better than other state-of-the-art deep learning architectures mostly used to analyze biological sequences. In addition, we further validate the effectiveness of CapsNet-SSP by comparison with human saliva-secretory proteins from existing studies and known salivary protein biomarkers of cancer.ConclusionsThe main contributions of this study are as follows: (1) an end-to-end model based on CapsNet is proposed to identify saliva-secretory proteins from the sequence information; (2) the proposed model achieves better performance and outperforms existing models; and (3) the saliva-secretory proteins predicted by our model are statistically significant compared with existing cancer biomarkers in saliva. In addition, a web server of CapsNet-SSP is developed for saliva-secretory protein identification, and it can be accessed at the following URL: http://www.csbg-jlu.info/CapsNet-SSP/. We believe that our model and web server will be useful for biomedical researchers who are interested in finding salivary protein biomarkers, especially when they have identified candidate proteins for analyzing diseased tissues near or distal to salivary glands using transcriptome or proteomics.

A method to study protein biomarkers in saliva using an automated capillary nano-immunoassay platform (Wes™)

Traditional immunoprobing techniques like Western blot continue to play a crucial role in the discovery and validation of biomarkers. This technique suffers from several limitations that affect reproducibility and feasibility for large-scale studies. Modern immunoprobing techniques have addressed several of these limitations. Here we contrast the use of Western blot and an automated capillary nano-immunoassay (CNIA), Wes™. We provide evidence highlighting the methodological advantages of Wes™ over Western blot in the validation of a novel biomarker, Calcium-binding protein and spermatid-associated 1 (hCABS1). While Wes™ offers a faster, more consistent approach with lower requirements for sample and antibody volumes, variations in expected molecular weights and computational algorithms used to analyze the data must receive careful consideration and assessment. Our data suggests that CNIA approaches are likely to positively impact biomarker discovery and validation.

Saliva protein biomarkers to detect oral squamous cell carcinoma (OSCC).

Saliva protein biomarkers to detect oral squamous cell carcinoma (OSCC).

Ultra-sensitive detection of protein biomarkers for diagnosis of Alzheimer's disease.

Beta amyloid peptide, tau, and phosphorylated tau are well recognized as promising biomarkers for the diagnosis of Alzheimer's disease (AD). In this work, we developed a direct, versatile, and ultrasensitive multiplex assay for the quantification of trace amounts of these protein biomarkers for AD in different types of biological fluids including cerebrospinal fluid, serum, saliva, and urine. The detection assay is based on the immunoreaction between the target proteins and their corresponding pair of antibodies followed by fluorescence labelling with a newly developed indolium-based turn-on fluorophore, namely SIM. SIM was tailor-made as a reporter to provide a high signal-to-noise ratio for the detection assay. An exceptionally low limit of detection down to the femto-molar level was achieved in this assay with minute consumption of the sample. This versatile detection assay is capable of reliably quantifying not only the target proteins simultaneously from a CSF sample in an hour but also trace amounts of protein biomarkers in saliva and urine. This assay has a high potential to serve as a practical tool for the diagnosis of AD.

Potential protein biomarkers for burning mouth syndrome discovered by quantitative proteomics.

Burning mouth syndrome (BMS) is a chronic pain disorder characterized by severe burning sensation in normal looking oral mucosa. Diagnosis of BMS remains to be a challenge to oral healthcare professionals because the method for definite diagnosis is still uncertain. In this study, a quantitative saliva proteomic analysis was performed in order to identify target proteins in BMS patients’ saliva that may be used as biomarkers for simple, non-invasive detection of the disease. By using isobaric tags for relative and absolute quantitation labeling and liquid chromatography-tandem mass spectrometry to quantify 1130 saliva proteins between BMS patients and healthy control subjects, we found that 50 proteins were significantly changed in the BMS patients when compared to the healthy control subjects (p ≤ 0.05, 39 up-regulated and 11 down-regulated). Four candidates, alpha-enolase, interleukin-18 (IL-18), kallikrein-13 (KLK13), and cathepsin G, were selected for further validation. Based on enzyme-linked immunosorbent assay measurements, three potential biomarkers, alpha-enolase, IL-18, and KLK13, were successfully validated. The fold changes for alpha-enolase, IL-18, and KLK13 were determined as 3.6, 2.9, and 2.2 (burning mouth syndrome vs. control), and corresponding receiver operating characteristic values were determined as 0.78, 0.83, and 0.68, respectively. Our findings indicate that testing of the identified protein biomarkers in saliva might be a valuable clinical tool for BMS detection. Further validation studies of the identified biomarkers or additional candidate biomarkers are needed to achieve a multi-marker prediction model for improved detection of BMS with high sensitivity and specificity.

Multiplexed panel of precisely quantified salivary proteins for biomarker assessment.

An increasingly popular "absolute" quantitative technique involves the SRM or MRM approach with stable isotope-labeled standards (SIS). Using this approach, many proteins in human plasma/serum have been quantified for biomarker assessment and disease stratification. Due to the complexity of plasma and the invasive nature of its collection, alternative biosamples are currently being explored. Here, we present the broadest panel of multiplexed MRM assays with SIS peptides for saliva proteins developed to date. The validated panel consists of 158 candidate human saliva protein biomarkers, inferred from 244 interference-free peptides. The resulting concentrations were reproducibly quantified over a 6 order-of-magnitude concentration range (from 218μg/mL to 88pg/mL; average CVs of 12% over analytical triplicates). All concentrations were determined from reverse standard curves, which were generated using a constant concentration of endogenous material with varying concentrations of spiked-in SIS peptides. The large-scale screening of the soluble and membrane-associated proteins contained within the 158-plex assay could present new opportunities for biomarker assessment and clinical diagnostics.

Saliva protein biomarkers to detect oral squamous cell carcinoma in a high-risk population in Taiwan

Most cases of oral squamous cell carcinoma (OSCC) develop from visible oral potentially malignant disorders (OPMDs). The latter exhibit heterogeneous subtypes with different transformation potentials, complicating the early detection of OSCC during routine visual oral cancer screenings. To develop clinically applicable biomarkers, we collected saliva samples from 96 healthy controls, 103 low-risk OPMDs, 130 high-risk OPMDs, and 131 OSCC subjects. These individuals were enrolled in Taiwan's Oral Cancer Screening Program. We identified 302 protein biomarkers reported in the literature and/or through in-house studies and prioritized 49 proteins for quantification in the saliva samples using multiple reaction monitoring-MS. Twenty-eight proteins were successfully quantified with high confidence. The quantification data from non-OSCC subjects (healthy controls + low-risk OPMDs) and OSCC subjects in the training set were subjected to classification and regression tree analyses, through which we generated a four-protein panel consisting of MMP1, KNG1, ANXA2, and HSPA5. A risk-score scheme was established, and the panel showed high sensitivity (87.5%) and specificity (80.5%) in the test set to distinguish OSCC samples from non-OSCC samples. The risk score >0.4 detected 84% (42/50) of the stage I OSCCs and a significant portion (42%) of the high-risk OPMDs. Moreover, among 88 high-risk OPMD patients with available follow-up results, 18 developed OSCC within 5 y; of them, 77.8% (14/18) had risk scores >0.4. Our four-protein panel may therefore offer a clinically effective tool for detecting OSCC and monitoring high-risk OPMDs through a readily available biofluid.

OI0289 Quantitative detection of salivary biomarkers in whole saliva

Using saliva as a diagnostic fluid has increased exponentially in the past decade because of recent technologic developments. To identify protein biomarkers in saliva that could be associated with the pathogenesis of oral diseases is an interesting topic of research. However, at present, the accurate and reliable detection of protein biomarkers in saliva has yet to be achieved, owing to lack of standardized laboratory protocols in the analysis of highly complex and viscous saliva specimens. We therefore aim to create a common consensus on the detection of salivary biomarkers regarding saliva handling, the application into methodologic assays, and the presentation of the results. For this purpose, we evaluated the improvement of detection levels for interleukin 8 (IL-8) and epidermal growth factor (EGF) by the pretreatment of saliva samples with an anionic detergent, sodium dodecyl sulfate (SDS).

Top-Down Analytical Platforms for The Characterization of The Human Salivary Proteome

Comprehensive analysis and characterization of the human salivary proteome is an important step towards the possible use of saliva for diagnostic and prognostic purposes. The contribution of the different sources to whole saliva, and the evaluation of individual variability and physiological modifications have been investigated by top-down proteomic approaches, disclosing the faceted and complex profile of the human salivary proteome. All this information is essential to develop saliva protein biomarkers. In this Review the major results obtained in the field by top-down platforms, and the improvements required to allow a more complete picture, will be discussed.

Performance of Multiplex Cytokine Assays in Serum and Saliva among Community-Dwelling Postmenopausal Women

Multiplexing arrays increase the throughput and decrease sample requirements for studies employing multiple biomarkers. The goal of this project was to examine the performance of Multiplex arrays for measuring multiple protein biomarkers in saliva and serum. Specimens from the OsteoPerio ancillary study of the Women’s Health Initiative Observational Study were used. Participants required the presence of at least 6 teeth and were excluded based on active cancer and certain bone issues but were not selected on any specific condition. Quality control (QC) samples were created from pooled serum and saliva. Twenty protein markers were measured on five multiplexing array panels. Sample pretreatment conditions were optimized for each panel. Recovery, lower limit of quantification (LLOQ) and imprecision were determined for each analyte. Statistical adjustment at the plate level was used to reduce imprecision estimates and increase the number of usable observations. Sample pre-treatment improved recovery estimates for many analytes. The LLOQ for each analyte agreed with manufacturer specifications except for MMP-1 and MMP-2 which were significantly higher than reported. Following batch adjustment, 17 of 20 biomarkers in serum and 9 of 20 biomarkers in saliva demonstrated acceptable precision, defined as <20% coefficient of variation (<25% at LLOQ). The percentage of cohort samples having levels within the reportable range for each analyte varied from 10% to 100%. The ratio of levels in saliva to serum varied from 1∶100 to 28∶1. Correlations between saliva and serum were of moderate positive magnitude and significant for CRP, MMP-2, insulin, adiponectin, GM-CSF and IL-5. Multiplex arrays exhibit high levels of analytical imprecision, particularly at the batch level. Careful sample pre-treatment can enhance recovery and reduce imprecision. Following statistical adjustments to reduce batch effects, we identified biomarkers that are of acceptable quality in serum and to a lesser degree in saliva using Multiplex arrays.

Multiplexed immunobead‐based assay for detection of oral cancer protein biomarkers in saliva

For clinical applications of biomarkers, there is a need for multiplex assays using high throughput platforms. The objective of this study was to determine the efficacy of Luminex Multianalyte Profiling (xMAP) technology for measurement of salivary proteins and to evaluate whether multiplex assays are as effective as single-plex assays and enzyme-linked immunosorbent assay (ELISA). The average levels of interleukin-8 (IL-8) from the single-plex assay were 3313.2 +/- 3759.8 pg ml(-1) [oral squamous cell carcinoma (OSCC), n = 20] and 1061.7 +/- 1978.8 pg ml(-1) (control, n = 20). The IL-1beta average levels from the single-plex assay were 945.2 +/- 1134.8 pg ml(-1) (OSCC, n = 20) and 314.2 +/- 444.8 pg ml(-1) (control, n = 20). The average levels of IL-8 from the multiplex assay were 2834.9 +/- 3385.6 pg ml(-1) (OSCC, n = 20) and 947.3 +/- 2036.8 pg ml(-1) (control, n = 20). The IL-1beta average levels from the multiplex assay were 1013.5 +/- 1221.1 pg ml(-1) (OSCC, n = 20) and 376.3 +/- 576.3 pg ml(-1) (control, n = 20). The correlation coefficient between Luminex and ELISA assay for IL-8 (n = 19) and IL-1beta (n = 19) was 0.91 and 0.84, respectively. Luminex xMAP single-plex and multiplex assays are as effective as ELISA assays for quantification of proteins in saliva. Both IL-8 and IL-1beta were expressed at significantly higher levels in OSCC subjects than in the matched healthy control subjects.

Human saliva proteome analysis and disease biomarker discovery

Human saliva is an attractive body fluid for disease diagnosis and prognosis because saliva testing is simple, safe, low-cost and noninvasive. Comprehensive analysis and identification of the proteomic content in human whole and ductal saliva will not only contribute to the understanding of oral health and disease pathogenesis, but also form a foundation for the discovery of saliva protein biomarkers for human disease detection. In this article, we have summarized the proteomic technologies for comprehensive identification of proteins in human whole and ductal saliva. We have also discussed potential quantitative proteomic approaches to the discovery of saliva protein biomarkers for human oral and systemic diseases. With the fast development of mass spectrometry and proteomic technologies, we are enthusiastic that saliva protein biomarkers will be developed for clinical diagnosis and prognosis of human diseases in the future.