Abstract 256: The Direct Characterization of Endothelial Inflammation in Patients with Psoriasis
Bibliographic record
Abstract
Objective: Psoriasis, an inflammatory autoimmune disease, increases the risk of cardiovascular disease (CVD). Active psoriatic disease is linked to systemic vascular inflammation, yet how this contributes to CVD is unknown. Using in vivo and ex-vivo measures of the vascular endothelium our study investigates the vascular health of psoriasis patients to better understand the mechanism(s) that predispose psoriatics to CVD. Methods: Ten patients with active psoriasis (average age 46 years, 50% male (5 of 10), 6% [3.5% – 90%] body surface area involvement) were compared to age- and sex- matched controls. In vivo vascular endothelial function was assessed by brachial artery reactivity testing (BART, %) with high resolution ultrasonography. Venous endothelial cells were collected from the brachial vein using guidewires inserted through an angiocatheter and isolated with magnetic beads directed against CD146. Following collection, endothelial RNA was isolated, converted to cDNA and inflammatory gene profiling performed by RT-qPCR with Taqman probes and primers. Results: Transcriptomic profiling of venous endothelial cells revealed upregulation of genes associated with inflammatory cytokines and chemokines ( lymphotoxin beta [2.5 - fold], CCL3 [3.5 - fold], and IL-1 β [2.8 - fold], P < 0.05 for all) and genes related to intracellular adhesion and inflammation ( ICAM1 [2.3 – fold] and COX-2 [1.4 – fold], P < 0.05 for both) in psoriatics vs. controls. Unexpectedly, endothelial nitric oxide synthase (eNOS) and phosphorylated eNOS (higher levels indicate healthy endothelial NO production) were upregulated (2 - 3 fold) in psoriatics vs. controls (p = 0.24, p = 0.14 respectively). BART was also higher in psoriatics when compared to controls (7.1 ± 1% vs. 3.9 ± 2.7%, P = 0.03). Conclusion: This cross-sectional study is the first to directly examine the vascular endothelium of psoriatic patients. Compared to controls, active psoriatic disease was associated with upregulation of cytokines, chemokines and genes regulating intracellular adhesion as well as increased expression of eNOS, and increased BART. These findings suggest potential mechanisms to explain the increased prevalence of atherosclerosis and CVD risk seen in those with psoriasis.
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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) | 0.000 | 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) | 0.003 | 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".