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Record W4381376673 · doi:10.2337/db23-9-or

9-OR: Insulin Resistance (IR) and Kidney Oxidative Metabolism in People with Type 1 Diabetes (T1D)

2023· article· en· W4381376673 on OpenAlexaboutno aff
G. A. Richard, Carissa Birznieks, Guanshi Zhang, Lynette Driscoll, Kalie L. Tommerdahl, JENNIFER A. SCHAUB, Abhijit S. Naik, VIJI NAIR, Alexis MacDonald, Susan Gross, Viral N. Shah, Laura Pyle, Tim Vigers, Janet K. Snell‐Bergeon, IAN DE BOER, Daniël H. van Raalte, LU-PING LI, POTTUMARTHI V. PRASAD, Patricia Ladd, Bennett B. Chin, DAVID CHERNEY, Phillip J. McCown, FADHL ALAKWAA, MATTHIAS KRETZLER, Kumar Sharma, Frank C. Brosius, Robert G. Nelson, Kristen J. Nadeau, Petter Bjornstad

Bibliographic record

VenueDiabetes · 2023
Typearticle
Languageen
FieldMedicine
TopicDialysis and Renal Disease Management
Canadian institutionsnot available
Fundersnot available
KeywordsInternal medicineEndocrinologyMedicineInsulin resistanceKidneyDiabetes mellitusOxidative phosphorylationType 2 diabetesMetabolismType 1 diabetesChemistryBiochemistry

Abstract

fetched live from OpenAlex

IR has been linked to kidney injury in T1D. Animal models show that IR associates with impaired TCA cycle turnover and oxidative phosphorylation, collectively termed oxidative metabolism, but little is known about this relationship in humans with T1D. Thirty young adults with T1D (age: 23±3 years, diabetes duration: 13±5 years, 53% female, HbA1c: 7.9±1.1%, BMI: 25±3 kg/m2, UACR: 5 [3, 8] mg/g) and 20 healthy controls (HC) (age: 25±3, 50% female, HbA1c: 5.2±0.3%, BMI: 23±2 kg/m2, UACR: 5 [3, 9] mg/g) underwent hyperinsulinemic-euglycemic clamps to assess whole-body insulin sensitivity (IS), and MRI to assess kidney perfusion. A subset underwent voxel-wise and region-of-interest (ROI) pharmacokinetic (PK) 11C-acetate PET analyses (n=16 T1D; n=10 HC) to quantify kidney cortical oxidative metabolism (k 2), and research kidney biopsies with single-cell RNA sequencing (n=28 T1D; n=13 HC). Compared to HC, participants with T1D exhibited lower IS (7.8±2.6 vs. 14.3±4.0 mg/kg/min, p<0.0001), cortical perfusion (196±68 vs. 243±46 ml/min/100g, p=0.01) and lower cortical k 2 (0.16±0.02 vs. HC 0.18±0.02 min-1, p=0.04) in voxel-wise models, although significance was not reached in the ROI PK analyses. IS associated with cortical k 2 (r:0.43, p=0.03) and the associations remained significant after adjusting for age, sex, and HbA1c (p=0.04). No significant interaction observed between T1D and HC for IS and cortical k2 (p=0.78). Proximal tubular transcripts of the enzymes catalyzing the proximal steps of the TCA cycle (e.g., ACO1, IDH1, SUCLG1) were lower in T1D vs. HC (all FDR-adjusted p<0.0001). Kidney oxidative metabolism is impaired in young people with T1D and is linked to lower whole-body IS. Statistical differences in k 2 from ROI and voxel-wise analyses suggest regional variations in kidney oxidative metabolism that may not be apparent in global analysis. Spatial metabolomic analyses of kidney tissue in a subset of these participants are shown in abstract #2023-A-3407-Diabetes. Disclosure G.Richard: None. S.Gross: None. V.N.Shah: Advisory Panel; LifeScan Diabetes Institute, Medscape, Consultant; DKSH, Research Support; Novo Nordisk, Tandem Diabetes Care, Inc., Dexcom, Inc., Insulet Corporation, JDRF, National Institutes of Health, Speaker's Bureau; Dexcom, Inc., Insulet Corporation. L.Pyle: None. T.B.Vigers: None. J.K.Snell-bergeon: 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. D.Van raalte: Consultant; Boehringer Ingelheim and Eli Lilly Alliance, AstraZeneca, Merck & Co., Inc., Research Support; Boehringer Ingelheim and Eli Lilly Alliance, AstraZeneca, Merck & Co., Inc. L.Li: None. P.V.Prasad: None. P.E.Ladd: None. C.Birznieks: None. B.B.Chin: None. D.Cherney: Other Relationship; Boehringer Ingelheim-Lilly, Merck, AstraZeneca, Sanofi, Mitsubishi-Tanabe, Abbvie, Janssen, Bayer, Prometic, BMS, Maze, Gilead, CSL-Behring, Otsuka, Novartis, Youngene, Lexicon and Novo-Nordisk, Research Support; Boehringer Ingelheim-Lilly, Merck, Janssen, Sanofi, AstraZeneca, CSL-Behring and Novo-Nordisk. P.J.Mccown: None. F.Alakwaa: None. M.Kretzler: Research Support; Lilly, Boehringer Ingelheim Inc., Traveere Pharmaceuticals, Novo Nordisk, certa, Chinook Therapeutics Inc., Janssen Research & Development, LLC, AstraZeneca, Moderna, Inc., Gilead Sciences, Inc., Regeneron, Ionis Pharmaceuticals, Angioin, Renalytix. K.Sharma: Advisory Panel; Reata Pharmaceuticals, Inc., Otsuka America Pharmaceutical, Inc. F.C.Brosius: Advisory Panel; Gilead Sciences, Inc. R.G.Nelson: None. K.J.Nadeau: 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. G.Zhang: None. L.Driscoll: None. K.L.Tommerdahl: None. J.A.Schaub: None. A.Naik: Advisory Panel; CareDx. V.Nair: None. A.A.Macdonald: None. Funding JDRF; National Institute of Diabetes and Digestive and Kidney Diseases

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)0.000
metaresearch head score (Gemma)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.010
GPT teacher head0.237
Teacher spread0.227 · 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
Published2023
Admission routes1
Has abstractyes

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