Prospective Study on Plasma MicroRNA‐4286 and Incident Acute Coronary Syndrome
Bibliographic record
Abstract
Background Mounting evidence suggests that circulating microRNAs (miRNAs) are critical indicators of cardiovascular disease. However, prospective studies linking circulating miRNAs to incident acute coronary syndrome (ACS) are limited, and the underlying effect of associated miRNA on incident ACS remains unknown. Methods and Results Based on a 2‐stage prospective nested case–control design within the Dongfeng‐Tongji cohort, we profiled plasma miRNAs from 23 pairs of incident ACS cases and controls by microarray and validated the candidate miRNAs in 572 incident ACS case–control pairs using quantitative real‐time polymerase chain reaction. We observed that plasma miR‐4286 was associated with higher risk of ACS (adjusted odds ratio according to an interquartile range increase, 1.26 [95% CI, 1.07–1.48]). Further association analysis revealed that triglyceride was positively associated with plasma miR‐4286, and an interquartile range increase in triglyceride was associated with an 11.04% (95% CI, 3.77%–18.83%) increase in plasma miR‐4286. In addition, the Mendelian randomization analysis suggested a potential causal effect of triglyceride on plasma miR‐4286 ( β coefficients: 0.27 [95% CI, 0.01–0.53] and 0.27 [95% CI, 0.07–0.47] separately by inverse variance‐weighted and Mendelian randomization‐pleiotropy residual sum and outlier tests). Moreover, the causal mediation analysis indicated that plasma miR‐4286 explained 5.5% (95% CI, 0.7%–17.0%) of the association of triglyceride with incident ACS. Conclusions Higher level of plasma miR‐4286 was associated with an increased risk of ACS. The upregulated miR‐4286 in plasma can be attributed to higher triglyceride level and may mediate the effect of triglyceride on incident ACS.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".