Associations between insulin-like growth factor binding protein-2 and lipoprotein kinetics in men
Bibliographic record
Abstract
Low circulating concentrations of insulin-like growth factor binding protein-2 (IGFBP-2) have been associated with dyslipidemia, notably with high triglyceride (TG) levels. However, the determinants by which IGFBP-2 influences lipoprotein metabolism, especially that of TG-rich lipoproteins (TRLs), are poorly understood. Here, we aimed to assess the relationships between IGFBP-2 levels and lipoprotein production and catabolism in human subjects. Fasting IGFBP-2 concentrations were measured in the plasma of 219 men pooled from previous lipoprotein kinetics studies. We analyzed production rate and fractional catabolic rates of TRLapoB-48, and LDL-, IDL-, and VLDLapoB-100 by multicompartmental modeling of l-[5,5,5-D3] leucine enrichment data after a 12 h primed constant infusion in individuals kept in a constant nutritional steady state. Subjects had an average BMI of 30 kg/m2, plasma IGFBP-2 levels of 157 ng/ml, and TG of 2.2 mmol/l. After adjustments for age and BMI, IGFBP-2 levels were negatively associated with plasma TG (r = −0.29; P < 0.0001) and positively associated with HDL-cholesterol (r = 0.26; P < 0.0001). In addition, IGFBP-2 levels were positively associated with the fractional catabolic rate of VLDLapoB-100 (r = 0.20; P < 0.01) and IDLapoB-100 (r = 0.19; P < 0.05) and inversely with the production rate of TRLapoB-48 (r = −0.28; P < 0.001). These correlations remained statistically significant after adjustments for age, BMI, and the amount of fat given during the tracer infusion. These findings show that the association between low plasma IGFBP-2 and high TG concentrations could be due to both an impaired clearance of apoB-100-containing VLDL and IDL particles and an increased production of apoB-48-containing chylomicrons. Additional studies are necessary to investigate whether and how IGFBP-2 directly impacts the kinetics of TRL.
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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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| 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".