Assessment of Circulating LncRNAs Under Physiologic and Pathologic Conditions in Humans Reveals Potential Limitations as Biomarkers
Bibliographic record
Abstract
Long non-coding RNAs (lncRNA) are a new class of regulatory molecules with diverse cellular functions. Recent reports have suggested that extracellular lncRNAs are detectable in human plasma and may serve as biomarkers. Here, we sought to investigate circulating lncRNAs as potential biomarkers for pulmonary arterial hypertension (PAH). Eighty-four lncRNAs, representing some of the most abundant and functionally relevant candidates identified in cellular studies, were assessed via RT-qPCR in plasma from PAH and healthy subjects. However, despite preamplification, the majority of lncRNAs were surprisingly undetectable or sporadically detectable, and showed no differential changes. Systematic characterization of plasma/RNA quality and technical performance via internal and external controls revealed no evidence of RNA degradation or RT-qPCR inhibition, and most lncRNAs were robustly detectable in pulmonary tissue. In plasma, lncRNA levels were the lowest among several different RNA species examined, and this was generalizable to other chronic and acute vascular conditions including coronary artery disease, acute coronary syndrome, and septic shock. In addition, two of three previously reported circulating lncRNA biomarker candidates were not detectable in any of the plasma samples. This study reveals new insight on the relative levels of lncRNAs in circulation, which has important implications for their potential development as biomarkers.
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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 | 0.001 | 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".