Metabolomics analysis of human plasma metabolites reveals the age- and sex-specific associations
Bibliographic record
Abstract
Objectives: The objective of this study was the investigation of age- and sex-associations in a set of blood plasma metabolites in healthy male and female subjects.Methods: A comparison study design with male and female subjects of various ages was used. Metabolic profiling was performed using electrospray ionization tandem mass spectrometry that yielded 186 metabolite concentrations for each study participant. The key age-related metabolites were identified using an integrative analysis of absolute concentrations, metabolite ratios and the differential correlation of pairwise metabolite concentrations. All of the age-associated metabolites were adjusted prior to the analysis to account for differences in Body Mass Index (BMI).Results: A total of 236 plasma samples from 140 female and 96 male subjects aged 20 to 82 years-old were collected and analyzed in the study. 13 and 14 age-associated metabolites (|r| > 0.33 and p < 6.6×10−5), 438 and 337 age-associated metabolite ratios (|r| > 0.37 and p < 3.5×10−6), and 5 and 10 core metabolites were discovered in the female and male groups, respectively. 80% of the metabolites displaying associations with age belonged to sphingolipids and phosphatidylcholines, and the two sexes shared less than 50% of the age-associated metabolites.Conclusion: The study found that changes in metabolite concentrations, metabolite ratios and differential correlations were age and sex-specific.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".