Circulating miR‐144‐3p as a Novel Independent Biomarker Associated With Low Muscle Strength Among Older Adults
Bibliographic record
Abstract
BACKGROUND: Low muscle strength, a key component of sarcopenia, is significant in the development of adverse health outcomes among older adults. MicroRNAs (miRNAs) have been implicated in mechanisms of sarcopenia; however, their specific functions in sarcopenia components, particularly low muscle strength, remain unclear. We aimed to examine distinct miRNA signatures associated with muscle mass, strength, and performance and to explore independent biomarkers for identifying older adults with low muscle strength. METHODS: Ninety-six older adults were selected from the Korean Frailty and Aging Cohort Study using stratified random sampling based on age and sex, and classified into four groups according to Asian Working Group for Sarcopenia 2019 criteria: normal (n = 25), low muscle mass (Low MM)-only (n = 23), low muscle strength (Low MS)-only (n = 25) and low physical performance (Low PP)-only (n = 23). MiRNA profiles were generated through miRNA sequencing, and differentially expressed (DE) miRNAs among groups were identified using log2|Fold Change (FC)| ≥ 1 and a Benjamini-Hochberg (BH)-adjusted p < 0.05. Subsequently, candidate miRNAs were validated by quantitative real-time polymerase chain reaction. Differences in relative miRNA expression between groups were assessed using analysis of variance. The utility of identified miRNAs for discriminating older adults with low muscle strength was assessed using receiver operating characteristic (ROC) analysis. RESULTS: In 96 older adults (50.0% women, mean age 76.6 ± 3.6 years), 16, 5 and 1 DE miRNAs were observed in comparisons of Low MS-only vs. Low MM-only, Low PP-only vs. Low MM-only, and Low PP-only vs. Low MS-only, respectively (log2|FC| ≥ 1 and BH-adjusted p < 0.05). Among these, miR-144-3p, miR-142-3p and miR-122-3p overlapped across at least two comparisons. In the validation phase, miR-144-3p exhibited significantly higher expression in the Low MS-only group than in other groups. Areas under the ROC curve (AUC) for miR-144-3p were 0.943 (95% CI = 0.854-1.000), 0.836 (95% CI = 0.698-0.974) and 0.844 (95% CI = 0.700-0.989) for distinguishing the Low MS-only group from normal, Low MM-only and Low PP-only groups, respectively (p < 0.001). Kyoto Encyclopedia of Genes and Genomes analysis revealed that identified novel miRNAs were mainly associated with FoxO and insulin signalling (BH-adjusted p < 0.001), with a trend toward neurotrophic signalling (BH-adjusted p = 0.0647). CONCLUSIONS: miR-144-3p was identified as a novel biomarker for low muscle strength among older adults, independent of muscle mass and physical performance. Longitudinal studies are required to determine whether the identified miRNAs can function as predictive biomarkers for muscle strength decline.
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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".