ABSTRACT
Introduction: Sjögren's syndrome (SS) is a systemic autoimmune disease, which affects the exocrine glands leading to glandular dysfunction and, particularly, symptoms of oral and ocular dryness. The aetiology of SS remains unclear, and the disease lacks distinctive clinical features. The current diagnostic work-up is complex, invasive and often time-consuming. Thus, there is an emerging need for identifying disease-specific and, ideally, non-invasive immunological and molecular biomarkers that can simplify the diagnostic process, allow stratification of patients, and assist in monitoring the disease course and outcome of therapeutic intervention in SS. Methods: This systematic review addresses the use of proteomics and miRNA-expression profile analyses in this regard. Results and discussion: Out of 272 papers that were identified and 108 reviewed, a total of 42 papers on proteomics and 23 papers on miRNA analyses in saliva, blood and salivary gland tissue were included in this review. Overall, the proteomic and miRNA studies revealed considerable variations with regard to candidate biomarker proteins and miRNAs, most likely due to variation in sample size, processing and analytical methods, but also reflecting the complexity of SS and patient heterogeneity. However, interesting novel knowledge has emerged and further validation is needed to confirm their potential role as biomarkers in SS.
Subject(s)
MicroRNAs , Sjogren's Syndrome , Humans , Sjogren's Syndrome/diagnosis , Sjogren's Syndrome/genetics , Sjogren's Syndrome/metabolism , MicroRNAs/genetics , MicroRNAs/metabolism , Proteomics/methods , Saliva/metabolism , BiomarkersABSTRACT
OBJECTIVES: Increasing evidence suggests that aberrant expression of microRNAs (miRNAs) is involved in the pathogenesis of primary Sjögren's syndrome (pSS). The aim was thus to characterize the miRNA profile in saliva, salivary gland tissue, and plasma from patients with pSS and compare findings with those of patients having Sjögren-like disease (non-pSS). In addition, to correlate miRNA levels and clinicopathological features of pSS. METHODS: miRNA real-time quantitative polymerase chain reaction was performed on saliva, plasma, and salivary gland tissue samples from 24 patients with pSS and 16 non-pSS in 384-well plates. T test was used for comparison of miRNA profiles, followed by Benjamini-Hochberg correction. The discriminatory power of miRNAs was evaluated by receiver-operating characteristic curves, and Pearson/Spearman correlation was used for correlation analyses. RESULTS: In saliva, 14 miRNAs were significantly differentially expressed between pSS and non-pSS, including downregulation of the miR-17 family in pSS. In salivary gland tissue of patients with pSS, miR-29a-3p was significantly upregulated. Plasma miRNAs did not differ between the two groups, although the miR-17 family tended to be downregulated. The combination of miR-17-5p and let-7i-5p in saliva yielded an area under curve of 97% (CI 92%-100%). Several miRNAs correlated significantly with one another and with salivary flow rates and histopathology. CONCLUSION: Our findings indicate that the miRNA expression profile in saliva may enable to discriminate between pSS and non-pSS patients. However, further validation in larger cohorts is needed as well as functional analyses of the miRNAs of interest.
Subject(s)
MicroRNAs , Sjogren's Syndrome , Humans , MicroRNAs/genetics , Real-Time Polymerase Chain Reaction , Saliva , Salivary Glands , Sjogren's Syndrome/diagnosis , Sjogren's Syndrome/geneticsABSTRACT
Objective: To characterize and compare the salivary microbiota in patients with pSS and patients with non-Sjögren's-related sicca, and to relate the findings to their oral health status and saliva flow rates. Methods: Twenty-four patients fulfilled the 2016 classification criteria for pSS and 34 did not (non-pSS). A clinical examination included registration of decayed, missing and filled teeth/-surfaces and collection of whole saliva. The microbiota was characterized using next-generation sequencing of the V1-V3 region of the 16S rRNA gene. Data were annotated against the eHOMD database. Results: A total of 509 different bacterial taxa were identified. There were no statistically significant differences between the groups with regard to the abundance of predominant genera, bacterial diversity and relative abundance on the genus or species level. The two groups did not differ with regard to general health, including intake of xerogenic medication and polypharmacy, oral health status or unstimulated and stimulated whole saliva flow rates. Conclusion: The salivary microbiota and oral health status, as well as salivary flow rate in patients with pSS resemble that of non-pSS patients. Our findings indicate that changes in the salivary microbiota do not appear to be determined by the disease entity pSS itself.
ABSTRACT
BACKGROUND: The purpose of this study was to characterize and compare subgingival and salivary microbiotas before and after periodontal treatment to learn if any changes of the subgingival microbiota were reflected in saliva. We tested the hypothesis that salivary levels of specific periopathogens correlate with corresponding subgingival levels before and after periodontal treatment. METHODS: Twenty-five patients with generalized chronic periodontitis completed the study. Stimulated saliva samples and subgingival plaque samples were collected at baseline and 2, 6, and 12 weeks after nonsurgical periodontal therapy. Subgingival and salivary microbiotas were processed by means of the Human Oral Microbe Next Generation Sequencing (HOMINGS) technique and characterized based on relative abundance. Spearman signed rank test was used to test correlation of periopathogens in subgingival and saliva samples. RESULTS: Periodontal treatment resulted in significantly higher relative abundance of Streptococcus, Rothia and Actinomyces in combination with a significant decrease in Porphyromonas and Treponema in subgingival plaque samples. Relative abundance of the overall predominant genera in saliva was not influenced by periodontal treatment. However, there was a positive correlation between samples of subgingival plaque and saliva before and after periodontal treatment (p < 0.0001) with respect to relative abundance of specific periopathogens, such as Porphyromonas gingivalis (r = 0.68), Prevotella intermedia (r = 0.72), Filifactor alocis (r = 0.58), Treponema denticola (r = 0.51), Tannerella forsythia (r = 0.45) and Parvimonas micra (r = 0.45). CONCLUSIONS: Subgingival and salivary abundance of periodontal pathogens correlated before and after treatment. Thus, data from this study suggest that periopathogens identified in saliva may be spill-over from the subgingival microbiota.
Subject(s)
Dental Plaque , Microbiota , Aggregatibacter actinomycetemcomitans , Humans , Porphyromonas gingivalis , Prevotella intermedia , Treponema denticolaABSTRACT
OBJECTIVES: The purpose of this study was to compare microbial profiles of saliva, pooled and site-specific subgingival samples in patients with periodontitis. We tested the hypotheses that saliva can be an alternative to pooled subgingival samples, when screening for presence of periopathogens. DESIGN: Site specific subgingival plaque samples (n = 54), pooled subgingival plaque samples (n = 18) and stimulated saliva samples (n = 18) were collected from 18 patients with generalized chronic periodontitis. Subgingival and salivary microbiotas were characterized by means of HOMINGS (Human Oral Microbe Identification using Next Generation Sequencing) and microbial community profiles were compared using Spearman rank correlation coefficient. RESULTS: Pronounced intraindividual differences were recorded in site-specific microbial profiles, and site-specific information was in general not reflected by pooled subgingival samples. Presence of Porphyromonas gingivalis, Treponema denticola, Prevotella intermedia, Filifactor alocis, Tannerella forsythia and Parvimona micra in site-specific subgingival samples were detected in saliva with an AUC of 0.79 (sensitivity: 0.61, specificity: 0.94), compared to an AUC of 0.76 (sensitivity: 0.56, specificity: 0.94) in pooled subgingival samples. CONCLUSIONS: Site-specific presence of periodontal pathogens was detected with comparable accuracy in stimulated saliva samples and pooled subgingival plaque samples. Consequently, saliva may be a reasonable surrogate for pooled subgingival samples when screening for presence of periopathogens. Future large-scale studies are needed to confirm findings from this study.