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Record W4411293215 · doi:10.2337/db25-1962-lb

1962-LB: Baseline Insulin Secretion Determines the Response to Abatacept In Stage 1 Type 1 Diabetes

2025· article· en· W4411293215 on OpenAlexaboutno aff
Alice L. J. Carr, Alfonso Galderisi, Peter W. Taylor, J Bonet, DAVID D. CUTHBERTSON, Jay M. Sosenko, Emily K. Sims, Carmella Evans‐Molina, Chiara Dalla Man, Peter Senior, Heba M. Ismail, BRANDON M. NATHAN, Alessandra Petrelli, JENNIFER L. SHERR, Kevan C. Herold, WILLIAM E. RUSSELL, Antoinette Moran, Colin Dayan

Bibliographic record

VenueDiabetes · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDiabetes and associated disorders
Canadian institutionsnot available
Fundersnot available
KeywordsAbataceptType 2 diabetesMedicineInternal medicineBaseline (sea)EndocrinologyInsulin glargineDiabetes mellitusInsulinType 1 diabetesBiology

Abstract

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Introduction and Objective: The TrialNet Abatacept Prevention study of 12 months use of the CTLA-4 immunoglobulin to delay disease progression in Stage 1 type 1 diabetes (T1D) did not meet its primary endpoint. We adopted the oral minimal model (OMM) to quantify insulin secretion and assess if high vs low baseline secretion determined treatment response. Methods: Beta cell responsivity to glucose (Phitotal ) was computed from oral glucose tolerance test at baseline and every 6 months up to 48 months in placebo and abatacept arms. Baseline secretor groups were defined as high-secretors (Phitotal >33rd centile) and low-secretors (Phitotal ≤33rd centile). Risk regression analyses compared time to Stage 2 or 3 T1D between arms, by baseline secretor group. Age-adjusted ANCOVA compared Phitotal at pre-specified discretized visits. Results: In high-secretors, abatacept delayed progression by ~12 months (48 (IQR 26, 48) vs 35 (IQR 17, 48), p=0.009) with 51% lower hazard for progression among abatacept high secretors (HR 0.51, (95% CI 0.29, 0.89), p=0.018). High-secretors on abatacept maintained Phitotal after treatment suspension for up to 48 months, unlike placebo high-secretors (0.3% (95% CI -3.8, 4.5) vs -9% (95% CI -13.2, -4.8), p=0.002). Conclusion: The OMM reveals heterogeneity within Stage 1 T1D and identifies abatacept responders with high baseline beta cell function. This is consistent with the observation in murine models that abatacept is most effective in early disease. Disclosure A.L. Carr: None. A. Galderisi: None. P. Taylor: None. J. Bonet: None. D.D. Cuthbertson: None. J. Sosenko: None. E.K. Sims: Consultant; Sanofi. Speaker's Bureau; Med Learning Group. Other Relationship; American Diabetes Association. C. Evans-Molina: Advisory Panel; DiogenX. Research Support; Bristol-Myers Squibb Company, Lilly Diabetes. Advisory Panel; Isla Technologies, Neurodon. Research Support; Neurodon. C. Dalla Man: None. P.A. Senior: Consultant; Abbott. Research Support; Canadian Institutes of Health Research, Eli Lilly and Company. Consultant; GlaxoSmithKline plc. Speaker's Bureau; GlaxoSmithKline plc. Consultant; Insulet Corporation, Novo Nordisk. Speaker's Bureau; Novo Nordisk. Consultant; Ypsomed AG, Vertex Pharmaceuticals Incorporated. H.M. Ismail: Consultant; Rise Therapeutics. B.M. Nathan: None. A. Petrelli: None. J.L. Sherr: Consultant; Abbott. Advisory Panel; StartUp Health T1D Moonshot. Research Support; Dexcom, Inc. Advisory Panel; Cecelia Health, MannKind Corporation. Consultant; Insulet Corporation, Vertex Pharmaceuticals Incorporated, Ypsomed AG. Advisory Panel; Medtronic, Vertex Pharmaceuticals Incorporated. K.C. Herold: Consultant; Sanofi, Dompé, Vertex Pharmaceuticals Incorporated, Sonoma, NexImmune. W.E. Russell: None. A. Moran: Research Support; Abbott. Consultant; Abata Therapeutics. Other Relationship; Novo Nordisk. C. Dayan: Advisory Panel; Provention Bio, Inc, Provention Bio, Inc, Microbion, Microbion, Sanofi. Speaker's Bureau; Sanofi. Advisory Panel; SAB Biotherapeutics, Inc. Consultant; SAB Biotherapeutics, Inc, Sanofi, AstraZeneca, Immunocore, Ltd. Advisory Panel; Amarna, Shoreline Bio, Vertex Pharmaceuticals Incorporated. Funding National Institutes of Health via National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), the National Institute of Allergy and Infectious Diseases, and the Eunice Kennedy Shriver National Institute of Child Health and Human Development (U01 DK061010, U01 DK061034, U01 DK061042, U01 DK061058, U01 DK085453, U01 DK085461, U01 DK085465, U01 DK085466, U01 DK085476, U01 DK085499, U01 DK085504, U01 DK085509, U01 DK103153, U01 DK103180, U01 DK103266, U01 DK103282, U01 DK106984, U01 DK106994, U01 DK107013, U01 DK107014, UC4 DK097835, U01 DK106993,R01DK121929, R01DK133881,DK057846,AI66387, DK106993,DK106993); National Center for Research Resources (UL1TR000142, UL1TR002366, UL1TR000445, UL1TR000064, UL1TR002537, UL1TR001082, UL1TR000114, UL1TR001857, UL1TR002529, UL1TR001872), Immune Tolerance Network (UM1 AI09565).

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.001

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.

Opus teacher head0.005
GPT teacher head0.241
Teacher spread0.236 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations0
Published2025
Admission routes1
Has abstractyes

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