1096-P: Plasma Metabolites Predict Loss of Glycemic Control in Youth with Type 2 Diabetes (T2D)
Bibliographic record
Abstract
We aimed to identify metabolites that predict the loss of glycemic control in youth-onset T2D (Y-T2D), a disease characterized by more rapid decline in β-cell function than adults-onset T2D. The increasing incidence of Y-T2D highlights the need to understand its pathophysiology and develop appropriate interventions. We measured 40 plasma metabolites in 374 baseline and 10-year follow-up samples from the Treatment Options for type 2 Diabetes in Adolescents and Youth (TODAY) study, using mass spectrometry with a targeted ZipChip based assay. Loss of glycemic control was defined as HbA1c ≥8% for 6 months or inability to wean from temporary insulin after acute metabolic decompensation. We evaluated associations with time to loss of glycemic control in Cox proportional hazards models adjusted for HbA1c, triglycerides, systolic blood pressure, and estimated insulin sensitivity. Participants were 14±2 years of age, 63% female; 72% experienced loss of glycemic control. Five baseline plasma metabolites (threonine, asparagine, glycine, glutamine, L-alpha-aminobutyrate) associated with lower risk of loss of glycemic control, and one baseline plasma metabolite (citrate) associated with higher risk of loss of glycemic control. After multivariable adjustments, only plasma citrate remained statistically significant (HR: 1.16 per 1 SD [95% CI 1.04, 1.30]). At 10-year follow-up, of these plasma metabolites only threonine (logFC: -0.28, p=3.8×10-11) and glycine (logFC: -0.17, p=5.7×10-5) were significantly lower. Plasma metabolites, such as citrate that might originate from an excess of fatty acids, predicted loss of glycemic control in youth with T2D. Future work should validate these findings and investigate their response to promising therapies. Disclosure P.Bjornstad: Advisory Panel; AstraZeneca, Novo Nordisk, Lilly, Horizon Therapeutics plc, Boehringer Ingelheim (Canada) Ltd., LG Chem, Consultant; Bayer Inc., Bristol-Myers Squibb Company. R.Gubitosi-klug: None. K.Drews: None. K.L.Tommerdahl: None. J.B.Tryggestad: None. E.M.Isganaitis: None. F.Bacha: Other Relationship; Takeda Pharmaceutical Co., Ltd., AstraZeneca. L.Pyle: None. K.Sharma: Advisory Panel; Reata Pharmaceuticals, Inc., Otsuka America Pharmaceutical, Inc. T.B.Vigers: None. I.De boer: Advisory Panel; AstraZeneca, Boehringer Ingelheim and Eli Lilly Alliance, Boehringer Ingelheim International GmbH, Otsuka America Pharmaceutical, Inc., Bayer Inc., Consultant; George Clinical, Gilead Sciences, Inc., Medscape, Research Support; Dexcom, Inc. L.El ghormli: None. H.L.Heerspink: Consultant; AstraZeneca, Boehringer Ingelheim International GmbH, Bayer Inc., Eli Lilly and Company, Chinook Therapeutics Inc., CSL Behring, Gilead Sciences, Inc., George Clinical, Merck & Co., Inc., Janssen Research & Development, LLC, Traveere Pharmaceuticals, Novo Nordisk. L.M.Laffel: Advisory Panel; Medtronic, Lilly Diabetes, Novo Nordisk, Vertex Pharmaceuticals Incorporated, Roche Diagnostics, Provention Bio, Inc., Consultant; Dexcom, Inc., Janssen Pharmaceuticals, Inc., Medscape. J.R.Ryder: None. A.S.Shah: None. J.L.Lynch: Research Support; Novo Nordisk. Funding National Institute of Diabetes and Digestive and Kidney Diseases
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".