Common signatures of differential microRNA expression in Parkinson’s and Alzheimer’s disease brains
Bibliographic record
Abstract
Abstract Background Dysregulation of microRNA (miRNA)-mediated gene expression has been implicated in the pathogenesis and course of many neurodegenerative diseases including Parkinson’s disease (PD). However, the functionally relevant miRNAs remain largely unknown. Previous meta-analyses on differential miRNA expression data in post-mortem PD brains have highlighted several miRNAs showing consistent and statistically significant effects. However, these meta-analyses were based on exceedingly small sample sizes. Methods In this study, we quantified the expression of the four most compelling PD candidate miRNAs from these meta-analyses in the superior temporal gyrus (STG) of one of the largest case-control post-mortem brain datasets available (261 samples), thereby quadruplicating previously investigated sample sizes. Furthermore, we probed for common differential miRNA expression signatures with Alzheimer’s disease (AD) by also analyzing these miRNAs in post-mortem STG of 190 AD patients and controls and by testing six top AD miRNAs in the PD brains. Results Of all ten analyzed miRNAs, PD candidate miRNA homo sapiens (hsa-) miR-132-3p showed evidence for differential expression in both PD (p=4.89E-06) and AD (p=3.20E-24), and AD miRNAs hsa-miR-132-5p (p=4.52E-06) and hsa-miR-129-5p (p=0.0379) showed evidence for differential expression in PD. Combining these novel data with previously published data substantially improved the statistical support (α=3.85E-03 using Bonferroni correction) of the corresponding meta-analyses clearly and compellingly implicating these miRNAs in both PD and AD. Furthermore, hsa-miR-132-3p/-5p (but not hsa-miR-129-5p) showed association with neuropathological Braak PD staging (p=3.51E-03/p=0.0117), suggesting that these miRNAs may play a role in α-synuclein aggregation beyond the early disease phase. Conclusions Our study represents the largest independent assessment of recently highlighted candidate brain miRNAs in PD and AD post-mortem brain samples, to date. Our results implicate hsa-miR-132-3p/-5p and hsa-miR-129-5p to be differentially expressed in both PD and AD brains, potentially pinpointing shared pathogenic mechanisms across these neurodegenerative diseases.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".