Abstract 64: Novel and Known Genes Elucidated in Cerebral Cavernous Malformation Through Comparative Transcriptomic Analysis of Multiple Model Species and Human Microdissected Lesional Endothelial Cells
Bibliographic record
Abstract
Cerebral cavernous malformations (CCMs) are vascular brain lesions predisposing 0.5% of the population to a lifetime risk of hemorrhagic stroke and seizures. The disease is associated to a mutation in one of the three CCM genes ( CCM1, CCM2 and CCM3 ). CCM pathogenesis has been shown to be endothelial autonomous, linked to angiogenic, adhesion, and inflammatory processes. Using RNA-Seq, we profiled the transcriptomes of lesional endothelial cells (ECs) extracted from 5 human CCMs. We also profiled the more common Ccm1, and the exceptionally aggressive Ccm3 genotypes in mouse brain microvascular endothelial cells (BMECs) and C. elegans . We first identified differently expressed genes (DEGs), gene ontology (GO) functions, and gene networks for each model separately. We then cross-compared the models and genotypes to identify the important and conserved genes likely contributing to pathogenesis of CCM disease. Nine hundred-fifteen DEGs in human microdissected lesional ECs, 1932 in Ccm1 ECKO and 524 in Ccm3 ECKO BMECs, as well as 1643 in ccm1 C. elegans and 1581 in ccm3 C. elegans were identified (p<0.05, FDR corrected, fold change≥1.2). FAT1 was commonly identified in the 5 models, while 7 other DEGs were common between human lesional ECs, mouse BMEC Ccm1 ECKO and ccm1 C. elegans: GNAO1 , SPARCL1 , PLXDC2 , PLCD3 , PDGFRA , FAXC , and UNC13A . Seventy-one DEGs were only identified in Ccm1 models, these genes were related to DNA repair, angiogenesis, microtubule functions and magnesium ion binding. Eleven DEGs were only found in Ccm3 models, and were related to rRNA processing, ribosome biogenesis and structural constituent, protein targeting to endoplasmic reticulum, protein intracellular targeting, and vesicle transportation to a cell membrane. We provide a comprehensive transcriptome library of CCM disease across species and genotypes. The results will be useful for validating putative mechanistic targets and biomarkers in this disease. For the first time, we also report fundamental transcriptomic differences between Ccm1 and Ccm3 genotypes, potentially explaining differences in CCM disease severity. Our results confirm several previously reported mechanisms, and suggest multiple novel gene candidates to be investigated in CCM pathogenesis.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".