Quantitation of 55 Common Human Plasma Proteins in Healthy Young Adults and Correlation with Body Mass Index and Dietary Patterns
Bibliographic record
Abstract
Abstract Plasma biomarkers are a useful tool for monitoring dietary exposures and the development of chronic disease. Measuring multiple biomarkers at once provides a more complete characterization of phenotype than measuring single markers. Certain dietary patterns have been associated with increased risk of obesity. Adhering to a ‘Western’ dietary pattern, characterized by high consumption of meat products and low fruit and vegetable consumption, may put individuals at a higher risk of becoming overweight or obese than a ‘Prudent’ or an ‘Eastern’ dietary pattern. A novel mass spectrometry-based multiple reaction monitoring (MRM) proteomics assay was used to quantitate 55 common plasma proteins that have been linked to chronic disease. We measured the concentrations of these proteins in 1088 participants of the Toronto Nutrigenomics and Health (TNH) study, an ethnically diverse population of young adults. Our goals were: 1) to explore clustering patterns within the protein panel; 2) to investigate whether protein cluster scores differ between normal weight (BMI<25) and overweight/obese (BMI≥25) individuals; and 3) to determine whether protein cluster scores differ between ‘Prudent’, ‘Western’ and ‘Eastern’ dietary patterns. Four principal components (PC) account for most of the variability in the protein profiles, with eigenvalues ranging from 22.3 (PC 1) to 2.9 (PC 4). Significant differences were observed in the average loading scores between normal weight and overweight/obese individuals for PCs 2 and 3. In particular, PC3 scores were significantly higher among those with BMI≥25. Linear regression adjusted for age, sex, ethnicity, physical activity and total caloric intake showed significant associations between dietary intake and PCs 1, 2 and 3. PCs 1 and 3 were positively associated with the ‘Western’ dietary pattern, and PC1 was also inversely associated with the ‘Eastern’ pattern. PC 2 was positively associated with the ‘Eastern’ dietary pattern. These results suggest a relationship between the examined panel of protein biomarkers, BMI and certain dietary patterns. Future analyses will assess the biological relevance of these results.
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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 | 0.001 | 0.002 |
| 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".