Abstract TP343: Co-Expression Modules In The Periphreal Blood Transcriptome Following Subarachnoid Hemorrhage Associate With 90-Day Outcome
Bibliographic record
Abstract
Background: Subarachnoid Hemorrhage (SAH) accounts for 2-7% of strokes and has high mortality and morbidity. We sought to identify peripheral blood transcriptome changes in the acute SAH phase that associated with 90-day outcome, as measured by the modified Rankin Scale (mRS), to gain insights about potential mechanisms contributing to long term outcome. Methods: We sequenced the peripheral blood transcriptome of SAH patients within 3 days post ictus and stratified the patients into patients with Good (mRS≤2, n=37) and Poor (mRS≥3, n=23) outcomes at 90-day follow up. We generated the co-expression networks using the Weighted Gene Co-Expression Network Analysis (WGCNA) package to determine modules (groups of co-expressed genes) associated with 90-day SAH outcome. The outcome-significant modules (p<0.05) were further analyzed for their biological relevance using pathway analysis. Results: We identified two outcome-significant modules, the Pink module and the Purple module. The Pink module was enriched (corrected p<0.05) in Monocyte- and Granulocyte-specific genes, while the Purple module and its hubs were enriched in Monocyte-specific genes. The hub genes are the most interconnected genes in each module, which are therefore potential master regulators. The Pink module was enriched (corrected p<0.05) in Neutrophil Degranulation, an inflammatory pathway which was predicted to be activated in patients with worse outcome, in Histone Modification Signaling, which is involved in epigenetic control of gene expression, and in SUMOylation of transcriptional cofactors, which confers post-transcriptional modifications of these cofactors. The Purple module was enriched in 45 canonical biological pathways, including numerous inflammatory pathways predicted to be activated in SAH patients with worse outcomes, such as Neutrophil Degranulation, Phagosome Formation, IL-8 Signaling, and Macrophage Classical Activation Signaling. Conclusions: Early peripheral blood changes in the transcriptome architecture following SAH are associated with long-term outcome. The identified genes and networks may guide the search for potential biomarkers of outcome and novel treatment targets.
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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 | 0.001 |
| 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) | 0.003 | 0.001 |
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".