Glycerophosphocholine Metabolites and Cardiovascular Disease Risk Factors in Adolescents
Bibliographic record
Abstract
Background: Glycerophosphocholine (GPC) metabolites modulate atherosclerosis and thus risk for cardiovascular disease (CVD). Preclinical CVD may start during adolescence. Here, we used targeted serum lipidomics to identify a new panel of GPCs, and tested whether any of these GPCs are associated, in adolescence, with classical risk factors of CVD, namely excess visceral fat (VF), elevated blood pressure, insulin resistance, and atherogenic dyslipidemia. Methods: We studied a population-based sample of 990 adolescents (12–18 years, 48% male), as part of the Saguenay Youth Study. Using liquid chromatography-electrospray ionization-mass spectrometry, we identified 69 serum GPCs within the 450 to 680 m / z range. We measured VF with MRI. Results: We identified several novel GPCs that were associated with multiple CVD risk factors. Most significantly, PC16:0/2:0 was negatively associated with VF ( P =1.4×10 –19 ), blood pressure ( P =7.7×10 –5 ), and fasting triacylglycerols ( P =9.0×10 –5 ), and PC14:1/0:0 was positively associated with VF ( P =3.0×10 –7 ), fasting insulin ( P =5.4×10 –32 ), and triacylglycerols ( P =1.4×10 –29 ). The Sobel test of mediation revealed that both GPCs mediated their respective relations between VF (as a potential primary exposure) and CVD risk factors (as outcomes, P values<1.3×10 –3 ). Furthermore, a GPC shown recently to predict incident coronary heart disease in older adults, PC18:2/0:0, was associated with several CVD risk factors in adolescents; these associations were less strong than those with the newly identified GPCs. Conclusions: We identified novel GPCs strongly associated with multiple CVD risk factors in adolescents. These GPCs may be sensitive indicators of obesity-related risk for CVD outcomes in adults, and may improve biological understanding of CVD risk.
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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".