Abstract P244: MicroRNAs Implicated in Angiogenesis Are Upregulated in Lower Extremity Peripheral Artery Disease (PAD): the San Diego Population Study (SDPS)
Bibliographic record
Abstract
Introduction: Lower extremity PAD affects approximately 9 million people in the US. However, the genetic factors underlying PAD remain elusive. MicroRNAs are short non-coding RNA segments that regulate gene expression post-transcriptionally. MicroRNAs are hypothesized to be involved in angiogenesis, inflammation, and immune processes central to atherosclerotic process, are modifiable, and thus have potential as therapeutic targets. No previous studies have assessed the role of microRNAs in PAD in a population-based sample. Methods: The SDPS is a prospective population-based cohort of non-Hispanic White, African-American, Hispanic and Asian men and women designed to study PAD and venous disease. A sex- and age-matched nested sample of 24 PAD cases and 24 controls were chosen from 1103 participants who attended the 2007-11 exam. PAD was defined as ankle brachial index (ABI)<0.90, while the ABI range for controls was 1.1-1.3. Thirty-five microRNAs hypothesized to be of importance in development of atherosclerosis were measured in plasma using a high throughput RT qPCR method on the BioMark microfluidic System. MicroRNA expression levels (Cq values) were compared between PAD cases and controls using linear regression and least squares means, with adjustment for age and sex to remove residual confounding. Results: Overall mean±SD age was 79±7, with mean ABI among the PAD cases of 0.60±0.12 and among controls was 1.17±0.06.Six microRNAs, miR-181b, -195, -22, -27b, -424, and -503, were significantly upregulated in PAD cases vs. controls ( Figure ), all p<0.05. Existing evidence indicates that miR-195,-27b, -424, and -503 are involved in angiogenesis, and miR-503 is upregulated in ischemic leg muscle of patients with diabetes. Conclusions: Individuals with PAD have significantly higher expression of miRNAs linked to angiogenesis.Additional research is needed in larger studies to further assess associations with clinical and subclinical PAD, as well as the viability of these miRNAs as therapeutic targets for PAD.
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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 | 0.001 |
| 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) | 0.003 | 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".