Abstract 103: Isomir Diversity Is Increased In Peripheral Blood Following Ischemic Stroke And May Represent Shifts In Regulation Of Neuroinflammatory Response
Bibliographic record
Abstract
MicroRNA (miRNA) expression is altered following ischemic stroke. Advances in RNA sequencing and bioinformatic tools allow study of isomiRs, isoforms of miRNA, which can have altered regulatory actions from canonical parent miRNA due to base modifications within the molecule or on the flanking regions. Here, we characterize isomiRs in the blood of ischemic stroke patients compared to vascular risk factor controls (VRFCs) and elucidate diversity of the post-stroke miRNA environment. Total RNA was isolated from peripheral blood of 47 ischemic stroke patients and 31 VRFCs using PAXgene protocol. Small RNA libraries were prepared using QIAseq miRNA Library Kit and sequenced to 14±2 M 1x75 bp reads. Raw sequence reads were trimmed, de-duplicated, and profiled using isomiRmap , which separates isomiRs from canonical miRNA sequences based on 3’ and 5’ miRNA modifications. Analysis of differentially expressed isomiRs was performed with DESeq2. A total of 74,562 unique isomiRs were identified, the majority expressed at very low level. Filtering for low abundance left 2,133 isomiRs (from 335 canonical miRNA) expressed in all subjects. Of these, 505 isomiRs (from 129 canonical miRNA) were differentially expressed (LFC > |0.5|, p adj < 0.05) between stroke and VRFCs. These isomiRs represent significant elevations in 3’ modifications (68.3% of DE isomiRs), 5’ modifications (20.2%) and non-template additions (34.3%). miRNA previously implicated in stroke had diverse isomiR profiles including cases where all isomiRs within a miRNA group were differentially expressed (e.g. let-7i) and cases where multiple isomiRs were present but not differentially expressed (e.g. miR-363). Four of 28 differentially expressed let-7i isomiRs have changes to the seed region that interacts with mRNA. Thus, miRNA-mRNA interactions distinct from the canonical let-7i seed may exist and play an altered role in stroke pathology and neuroinflammation. Analysis of small noncoding RNA sensitive to base-specific variations detects many differentially expressed isomiRs and highlights the complexity of the post-stroke miRNA environment. Further study of these isomiRs within mRNA regulatory networks will deepen our understanding of stroke related neuroinflammation and neural repair.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".