Age‐Dependent Effects of Muscle Resting Calcium on Fasting Blood Glucose: Implications for Prediabetes Risk
Bibliographic record
Abstract
ABSTRACT Background and Aims Skeletal muscle is the primary site for insulin‐mediated glucose uptake and is critical in maintaining whole‐body glucose homeostasis. Muscle cells from malignant hyperthermia‐susceptible (MHS) individuals exhibit elevated resting cytosolic calcium concentration ([Ca2+]cyto), and MHS subjects have a higher incidence of hyperglycaemia. This study investigates the association between elevated resting [Ca2+]cyto and fasting blood sugar (FBS) levels while accounting for subject demographics and clinical variables. Methods We measured resting [Ca2+]cyto in myotubes derived from muscle biopsies of control and MHS subjects. We analysed the impact of [Ca2+]cyto on FBS levels based on age, sex, and MH status through correlation and comparative analyses. Data were stratified by FBS, [Ca2+]cyto, and age, and heat map and 3D mesh plot analyses were performed to assess the risk of prediabetes in subjects with varying [Ca2+]cyto and age. Results Between 2013 and 2024, muscle biopsies from 152 subjects (90 MHS, 62 controls) were used to establish primary myotube culture. MHS myotubes exhibited significantly higher resting [Ca2+]cyto than controls and [Ca2+]cyto positively correlated with fasting blood sugar (FBS) in MHS subjects (r = 0.227; p = 0.031) and across the entire cohort (r = 0.176; p = 0.034). This correlation was high in prediabetic individuals (r = 0.43; p = 0.005) but absent in those with normal FBS. Subjects over 40 years with [Ca2+]cyto > 150 nM showed a higher risk of prediabetes. While aging is a significant risk factor for type 2 diabetes, increased age did not impact FBS levels in individuals with [Ca2+]cyto below 150 nM. However, in those with [Ca2+]cyto exceeding 150 nM, increasing age significantly influenced FBS. Conclusions Elevated resting [Ca2+]cyto in skeletal muscle amplifies the risk of hyperglycemia and may contribute to the onset of type 2 diabetes.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".