Pilot investigation of circulating angiogenic and inflammatory biomarkers associated with vascular malformations
Bibliographic record
Abstract
BACKGROUND: Vascular malformations in the central nervous system are difficult to monitor and treat due to their inaccessible location. Angiogenic and inflammatory proteins are secreted into the bloodstream and may serve as useful biomarkers for identifying patients at risk for complications or with certain disease phenotypes. METHODS: A validated multiplex protein array consisting of 26 angiogenic and inflammatory biomarkers (Angiome) was assessed in plasma isolated from healthy controls and patients with either sporadic brain arteriovenous malformation (BAVM), familial cerebral cavernous malformation (CCM), or hereditary hemorrhagic telangiectasia (HHT). These samples were obtained from archives of ongoing research studies at the University of California San Francisco and through prospective collection at the Toronto HHT Centre at St. Michael's Hospital. RESULTS: We compared circulating biomarker levels from each patient group to healthy controls and analyzed each pairwise combination of patient groups for differences in biomarker levels. Additionally, we analyzed the HHT samples to determine the association between biomarker levels and the following HHT-specific phenotypes, BAVM, pulmonary arteriovenous malformation (PAVM), liver vascular malformation (LVM), and gastrointestinal (GI) bleeding. Compared to controls, levels of SDF1 were significantly elevated in HHT patients (Proportional Increase [PI] = 1.87, p < 0.001, q = 0.011). Levels of sENG were significantly reduced in HHT patients compared to controls (PI = 0.56, p < 0.001, q < 0.001), reflecting the prevalence of HHT1 patients in this cohort. Levels of IL6 (PI = 3.22, p < 0.001, q < 0.001) and sTGFβR3 (PI = 0.70, p = 0.001, q < 0.029) differed significantly in CCM patients compared to controls. Compared to controls, ten of the biomarkers were significantly different in sporadic BAVM patients (q-values < 0.05). Among the pairwise combinations of patient groups, a significant elevation was observed in TGFβ1 in CCM patients compared to sporadic BAVM patients (PI = 2.30, p < 0.001, q = 0.034). When examining the association of circulating biomarker levels with HHT-specific phenotypes, four markers were significantly lower in HHT patients with BAVM (q-values < 0.05), and four markers were significantly higher in patients with LVM (q-values < 0.05). CONCLUSIONS: This pilot study suggests that the profile of circulating angiogenic and inflammatory biomarkers may be unique to each type of vascular malformation. Furthermore, this study indicates that circulating biomarkers may be useful for assessing phenotypic traits of vascular malformations.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".