1095-P: Proteomic Analyses Identify Novel Predictors of Loss of Glycemic Control in Youth-Onset Type 2 Diabetes
Bibliographic record
Abstract
The basis for the more aggressive loss of β-cell function in youth-onset type 2 diabetes (Y-T2D) compared to adult-onset T2D and its unresponsiveness to interventions remain incompletely understood. Given the increasing incidence of Y-T2D, there is an urgent need to better understand its pathophysiology and develop appropriate interventions. Accordingly, we sought to identify multiprotein signatures that predict loss of glycemic control in Y-T2D. We measured 7604 Aptamers in 374 baseline plasma samples from the Treatment Options for type 2 Diabetes in Adolescents and Youth (TODAY) study, using the SomaScan 7K Proteomic (SomaLogic) platform. 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 body mass index (BMI) and estimated insulin sensitivity. Gene set enrichment analysis identified pathways of interest. The false discovery rate was controlled at 5% and we report q-values. Participants were 14±2 years of age, 37% male; 72% experienced loss of glycemic control. Seventy-four proteins were associated with time to loss of glycemic control, with sixty-seven proteins remaining associated with time to loss of glycemic control after multivariable adjustments, such as: plexin-B2 (HR: 1.54 per 1 SD [95% CI 1.35, 1.76], q<0.0001) and Ephrin-A3 (HR: 1.25 [1.13, 1.39], q=0.012). Twenty gene sets, including HIF-1 signaling, metabolic and cell adhesion pathways, were positively related and 13 gene sets were negatively related to time to loss of glycemic control. Novel proteins, including those involved in regulation of insulin secretion and ligand-receptor pairing in β-cells, predict loss of glycemic control in Y-T2D, independently of BMI and estimated insulin sensitivity. Future work should include validation of these findings and investigating potential therapeutic targets. Disclosure T.B.Vigers: None. 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. A.S.Shah: None. K.Drews: None. J.R.Ryder: None. R.Gubitosi-klug: None. P.Bjornstad: Advisory Panel; AstraZeneca, Novo Nordisk, Lilly, Horizon Therapeutics plc, Boehringer Ingelheim (Canada) Ltd., LG Chem, Consultant; Bayer Inc., Bristol-Myers Squibb Company. L.Pyle: None. L.El ghormli: 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. R.G.Nelson: None. K.Sharma: Advisory Panel; Reata Pharmaceuticals, Inc., Otsuka America Pharmaceutical, Inc. S.Waikar: 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. N.White: None. K.L.Tommerdahl: None.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".