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Record W4210731498 · doi:10.1101/2022.01.31.478486

Common signatures of differential microRNA expression in Parkinson’s and Alzheimer’s disease brains

2022· preprint· en· W4210731498 on OpenAlexfundno aff
Valerija Dobričić, Marcel Schilling, Djordje Gverić, Jessica Schulz, Lefkos Middleton, Steve Gentleman, Laura Parkkinen, Lars Bertram, Christina M. Lill

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2022
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA regulation and disease
Canadian institutionsnot available
FundersNIHR Oxford Biomedical Research CentreDeutsche ForschungsgemeinschaftImperial College LondonParkinson's UKNational Institute for Health and Care ResearchAlzheimer SocietyMedical Research CouncilCure Alzheimer's Fund
KeywordsmicroRNABiologyDiseaseParkinson's diseaseBioinformaticsNeuroscienceGeneticsMedicinePathologyGene

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.633
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.011
GPT teacher head0.236
Teacher spread0.225 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2022
Admission routes1
Has abstractyes

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