Association of the Plasma Long Non-coding RNA MEG3 With Parkinson's Disease
Bibliographic record
Abstract
Objective: To investigate the expression level of the maternally expressed gene-3 (MEG3) of the free long non-coding RNA (lncRNAs) in the plasma of Parkinson's disease (PD) patients and its relationship with the disease. Methods: Thirty PD patients (PD group) who treated at Xuanwu Hospital of Capital University of Medical Sciences between January 2017 and December 2019 were selected as the research objects and 30 healthy subjects were enrolled in the study during the same period as the control group. Cognitive function was assessed according to the Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) were used to evaluate cognitive function, Non-Motor Symptoms Scale (NMSS) was used to evaluate severity of non-motor symptoms. The relative expression of lncRNAs MEG3 in plasma was measured by PCR, and the levels of neuron-specific enolase (NSE), nerve growth factor (NGF) and brain-derived neurotrophic factor (BDNF) in plasma were measured by ELISA, and the relationship with these all indexes was analyzed. Results: The NMSS score of PD group was significantly higher than that of the control group, while the MMSE and MoCA scores were significantly lower than that of the control group (P < 0.05); The relative expression of lncRNAs MEG3, NGF and BDNF levels of PD group were significantly lower than that of the control group, and NSE level was significantly higher than that of the control group (P < 0.05); The H&Y stage and NMSS score in PD group were negatively correlated with the relative expression of lncRNAs MEG3, the levels of NGF and BDNF (P < 0.05), and positively correlated with NSE (P < 0.05); The MMSE and MoCA scores in PD group were positively correlated with the relative expression of lncRNAs MEG3, NGF, BDNF levels (P < 0.05), and negatively correlated with NSE (P < 0.05); The relative expression of lncRNAs MEG3 in PD group was positively correlated with NGF, BDNF levels (P < 0.05), and negatively correlated with NSE (P < 0.05). Conclusion: The expression of lncRNAs MEG3 in the plasma of PD patients was downregulated compared to that of healthy control subjects, and its expression level was closely related to the aggravation of non-motor symptoms, cognitive decline, and PD stage. These associations may reflect the synergism of the increase of NSE and decrease of NGF and BDNF levels, highlighting plasma lncRNA MEG3 as a new candidate biomarker of PD.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".