| Primary information |
|---|
| SALID | SAL_24516 |
| Biomarker name | hsa-miR-346 |
| Biomarker Type | Diagnostic |
| Sampling Method | Twelve patients (6 males and 6 females) with pancreatobiliary tract cancers |
| Collection Method | NA |
| Analysis Method | qPCR |
| Collection Site | Saliva |
| Disease Category | Nervous System Disorder |
| Disease/Condition | Fibromyalgia |
| Disease Subtype | NA |
| Fold Change/ Concentration | NA |
| Up/Downregulated | NA |
| Exosomal | NA |
| Organism | Homo sapiens |
| PMID | 27796750 |
| Year of Publication | 2017 |
| Biomarker ID | hsa-miR-346 |
| Biomarker Category | miRNA |
| Sequence | GGUCUCUGUGUUGGGCGUCUGUCUGCCCGCAUGCCUGCCUCUCUGUUGCUCUGAAGGAGGCAGGGGCUGGGCCUGCAGCUGCCUGGGCAGAGCGG |
| Title of study | Circulating microRNA Profiles as Liquid Biopsies for the Characterization and Diagnosis of Fibromyalgia Syndrome |
| Abstract of study | This work was aimed at investigating the circulating microRNA (miRNA) profiles in serum and saliva of patients affected by fibromyalgia syndrome (FM), correlating their expression values with clinical and clinimetric parameters and to suggest a mathematical model for the diagnosis of FM. A number of 14 FM patients and sex- and age-matched controls were enrolled in our study. The expression of a panel of 179 miRNAs was evaluated by qPCR. Statistical analyses were performed in order to obtain a mathematical linear model, which could be employed as a supporting tool in the diagnosis of FM. Bioinformatics analysis on miRNA targets were performed to obtain the relevant biological processes related to FM syndrome and to characterize in details the disease. Six miRNAs were found downregulated in FM patients compared to controls. Five of these miRNAs have been included in a linear predictive model that reached a very high sensitivity (100 %) and a high specificity (83.3 %). Moreover, miR-320b displayed a significant negative correlation (r = -0.608 and p = 0.036) with ZSDS score. Finally, several biological processes related to brain function/development and muscular functions were found potentially implicated in FM syndrome. Our study suggests that the study of circulating miRNA profiles coupled to statistical and bioinformatics analyses is a useful tool to better characterize the FM syndrome and to propose a preliminary model for its diagnosis. |