Branched-Chain Amino Acids and Their Interactions With Lipid Metabolites for Increased Risk of Gestational Diabetes
Bibliographic record
Abstract
OBJECTIVE: We aimed to explore associations of branched-chain amino acids (BCAA) in early pregnancy with gestational diabetes mellitus (GDM), and whether high BCAAs and lipidomics markers had interactive effects on the risk of GDM. METHODS: We conducted a 1:1 case-control study (n = 486) nested in a prospective cohort of pregnant women in Tianjin, China. Blood samples were collected at their first antenatal care visit (median 10 gestational weeks). Serum BCAAs, saturated fatty acids (SFA) and lysophosphatidylcholines (LPC) were measured by liquid chromatography-tandem mass spectrometry analysis. Conditional logistic regression was performed to examine associations of BCAAs with the risk of GDM. Interactions between high BCAAs and high SFA16:0 for GDM were examined using additive interaction measures. RESULTS: High serum valine, leucine, isoleucine, and total BCAAs were associated with markedly increased risk of GDM (OR of top vs bottom tertiles: 1.91 [95% CI, 1.22-3.01]; 1.87 [1.20-2.91]; 2.23 [1.41-3.52]; 1.93 [1.23-3.02], respectively). The presence of high SFA16:0 defined as ≥ 17.1 nmol/mL (ie, median) markedly increased the ORs of high leucine alone and high isoleucine alone up to 4.56 (2.37-8.75) and 4.41 (2.30-8.43) for the risk of GDM, with significant additive interaction. After adjustment for LPCs, the ORs were greatly elevated (6.33, 2.25-17.80 and 6.53, 2.39-17.86) and the additive interactions became more significant. CONCLUSION: BCAAs in early pregnancy were positively associated with the risk of GDM, and high levels of leucine and isoleucine enhanced the risk association of high SFA16:0 with GDM, independent of LPCs.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".