Salivary microR‐153 and microR‐223 Levels as Potential Diagnostic Biomarkers of Idiopathic Parkinson's Disease
Bibliographic record
Abstract
BACKGROUND: Parkinson's disease (PD) is the most common movement disorder among adults, affecting 2% of the world population older than 65 years of age. No diagnostic biomarker for routine use in clinical settings currently exists. Dysregulation of microRNAs (miRNAs) has been implicated in various neurodegenerative conditions, including PD. Distinct miRNAs have been demonstrated to be involved in the regulation of α-synuclein, a key player in PD pathogenesis; miR-153 and miR-223 are downregulated in the brain and serum of parkinsonian GFAP.HMOX1 transgenic mice where they directly regulate α-synuclein. OBJECTIVE: To ascertain whether salivary miR-153 and miR-223 are similarly downmodulated in, and may serve as diagnostic biomarkers of, idiopathic PD. METHODS: Using reverse transcriptase quantitative polymerase chain reaction, miR-153 and miR-223 levels were evaluated in the saliva of 77 non-neurological controls and 83 PD patients. Levels of heme oxygenase-1 and α-synuclein were measured using enzyme-linked immunosorbent assay. Analyses were adjusted by age, sex, medication exposure, disease duration, and relevant comorbidities. RESULTS: Log-transformed expression levels of miR-153 and miR-223 were significantly decreased in the saliva of human PD patients in comparison with nonneurological controls. The miRNA expression levels did not change as a function of disease progression (Hoehn and Yahr staging). The area under the receiver operating characteristic curve separating controls from PD patients was 79% (95% confidence interval, 61%-96%) for miR-153 and 77% (95% confidence interval, 59%-95%) for miR-223. The ratios of miRNAs to oligomeric α-synuclein, total α-synuclein, or heme oxygenase-1 protein did not improve accuracy of the test. CONCLUSION: Salivary miR-153 and miR-223 levels may serve as useful, noninvasive, and relatively inexpensive diagnostic biomarkers of idiopathic PD. © 2019 International Parkinson and Movement Disorder Society.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".