Abstract WP242: Transcriptomic Changes In Peripheral Blood Leukocytes Associated With The Cerebral Amyloid Angiopathy Small Vessel Disease Score
Bibliographic record
Abstract
Introduction: Cerebral amyloid angiopathy (CAA) is a cerebrovascular disease characterized by beta-amyloid deposition within cerebral vessels. Clinical markers of CAA severity include recurrent ICH, cognitive decline, and imaging features of CAA including microhemorrhage, dilated perivascular spaces, cortical superficial siderosis, and white matter hyperintensities. CAA is an important cause of cognitive decline and intracerebral hemorrhage in the elderly, leading to the need for CAA treatments. The contribution of the immune system to CAA severity is not well understood. This study sought to evaluate changes in peripheral leukocyte gene expression associated with CAA severity. Methods: In 22 patients with CAA peripheral blood was collected into PAXgene tubes. RNA was isolated, and sequencing performed. Differentially expressed genes based on CAA small vessel disease (CAA-SVD) score as a marker of CAA severity were identified using ANOVA and functional pathway analysis. The relationship between leukocyte gene expression and CAA severity were assessed. Results: ANOVA was used to identify genes that were associated with CAA-SVD score (p≤0.05, partial correlation coefficient ≥;|0.5|). HDAC11, IL23A, TRAIL, TRAILR1 , TRAILR2 , and ICAM-1 were associated with CAA severity (CAA-SVD score). Canonical pathway analysis identified included induction of T lymphocytes, binding of antigen presentation cells, IL-12 signaling in macrophages/monocytes, activation of phagocytes, tight junction signaling, and activation of antigen presenting cells to be associated with CAA severity (p≤0.05). Conclusion: An association between the peripheral immune system and CAA severity was identified. Changes in neutrophil, monocyte, and Th17 cell gene expression in peripheral blood was associated with CAA severity. Further evaluation of immune system changes associated with CAA severity is needed to understand contribution to cerebral small vessel disease, cognitive decline, and potential roles as treatment targets or risk stratification markers in CAA.
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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 | 0.001 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".