Reduced plasma GDF10 levels are positively associated with cholesterol impairment and childhood obesity
Bibliographic record
Abstract
Childhood obesity is a global health concern affecting over 150 million children worldwide, with projections of a rise to 206 million by 2025. Understanding the mechanisms underlying this epidemic is crucial for developing effective interventions. In this study, we investigated circulating levels of Growth Differentiation Factor 10 (GDF10), a novel regulator of adipogenesis. Previous studies report diminished circulating GDF10 levels contribute to obesity and hepatic steatosis in mice. To further understand the role of plasma GDF10 in childhood obesity, a prospective case-control study was conducted. Using an enzyme-linked immunosorbent assay, plasma GDF10 levels were measured in children aged 5-17 years of age with normal (n = 36) and increased (n = 56) body mass index (BMI). Subsequently, plasma GDF10 levels were compared to various cardio-metabolic parameters. Children with increased BMI exhibit significantly lower levels of plasma GDF10 compared to children with normal BMI (p < 0.05). This study not only supports previous mouse data but is the first to report that lower levels of GDF10 is associated with childhood obesity, providing an important human connection for the relevance of GDF10 in obesity. Furthermore, this study revealed a significant correlation between low plasma GDF10 levels and elevated LDL-cholesterol and total cholesterol levels dependent on BMI (95% CI, p < 0.05). This study supports the hypothesis that children with obesity display lower plasma levels of GDF10, which correlates with elevated cholesterol levels. These insights shed light on potential mechanisms contributing to childhood obesity and may lead to future therapeutic interventions targeting GDF10 to mitigate adverse effects of adipogenesis in cardiometabolic health.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".