Metabolomics profiling predicts SORT1 LDL‐cholesterol locus in a fit, young adult population
Bibliographic record
Abstract
SORT1 locus was originally identified by genome wide association studies of LDL‐cholesterol (LDL‐C) in older adults. We hypothesized that a younger population would show a greater genetic effect due to fewer confounding variables. As such, we investigated the association between the SORT1 locus and LDL‐C in a group of healthy, young adults. Subjects (n=80, age=23) were recruited. Lipid measures and genomic DNA were collected from blood after an overnight fast. Blood pressure, body fat (%BF), V02 max, and metabolomics profile (LC‐MS) were measured. Associations between genotype and LDL‐C were investigated using linear regression. 21.7% of male subjects had %BF that was above a healthy range, while 25% had non‐optimal LDL‐C values. A significant association was observed between the SORT1 locus (GG: 2.46±0.11 mmol/L versus TG/TT: 2.06±0.12 mmol/L, p=0.016) and LDL‐C in male subjects with genotype explaining 3.0% of the variability in LDL‐C. LC‐MS metabolite profiling was able to further discriminate between genotypes independent of other clinical parameters. Differentially affected metabolites included sphingomyelins, phosphatidylcholines and acylcarnitines. The marriage of metabolomics and genomics represents a powerful means to identify the earliest biomarkers associated with cardiovascular disease that could be used to identify individuals who would most benefit from early interventions. Grant Funding Source : Metabolomics Research Center
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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 | 0.000 | 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) | 0.002 | 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".