OR33-05 Amino Acid Signature of Abdominal Obesity in the TwinsUK Cohort
Bibliographic record
Abstract
Abstract Background and aim: Metabolomic studies have shown that circulating amino acid levels are altered in the context of obesity. The branched-chain amino acids (BCAAs, namely leucine, isoleucine and valine) have been the most studied because of their consistent positive association with adiposity and their ability to prospectively predict type 2 diabetes and cardiovascular diseases (1). Circulating glutamate has been much less investigated, but some have shown that its specific association with central fat accumulation was stronger than that of BCAAs (2). This study aimed to evaluate the relationship between circulating glutamate and abdominal obesity and the impact of genetic factors on this association. Methods: In the TwinsUK cohort, we selected individuals for whom both metabolomics and DXA trunk fat measurements were available (n=4 665). We used linear regression to assess the correlation between glutamate level and trunk fat. Those with a trunk fat mass greater than 15 kg were considered abdominally obese. We compared the odds of presenting abdominal obesity in each circulating glutamate quintile with logistic regression models. Monozygotic twin pairs discordant for trunk fat were selected to identify analyte differences driven by non-genetic factors. All analyses were also performed with BCAAs for comparison. Results: Circulating glutamate was positively and significantly associated with trunk fat (β: 0.28, 95%CI: 0.26-0.31). Individuals in the highest circulating glutamate quintile had a more than 8-fold higher risk of being characterized by abdominal obesity compared to those in the lowest quintile (OR: 8.44, 95%CI: 6.17-11.55). In the 54 monozygotic twin pairs discordant for trunk fat, the heavier twin had significantly higher glutamate level compared to the leaner co-twin (p-value: 4.05e-07). In all these analyses, the results for glutamate were more significant than with any of the BCAAs. Conclusion: There is a positive relationship between circulating glutamate and trunk fat that is partially independent of genetic background. This often-overlooked metabolite might represent an interesting biomarker of abdominal obesity. References: (1) Newgard (2017). Metabolomics and Metabolic Diseases: Where Do We Stand? Cell Metab, 25(1), 43-56, (2) Kimberly et al. (2017). Metabolite profiling identifies anandamide as a biomarker of nonalcoholic steatohepatitis. JCI Insight, 2(9).
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".