406-P: Spatial Metabolomics of Human Kidney Tissues Reveal Impaired Tricarboxylic Acid (TCA) Cycle Turnover in Type 1 Diabetes (T1D)
Bibliographic record
Abstract
In abstract 2023-A-3497-Diabetes, we show impaired TCA cycle turnover using 11C acetate PET and lower proximal tubular transcripts of TCA cycle enzymes by single-cell RNA sequencing of kidney biopsies in young adults with T1D vs. healthy controls (HC). Spatial metabolomics analyses of the kidney tissue were conducted to further explore perturbations in kidney oxidative metabolism in T1D. Matrix-assisted laser desorption/ionization-mass spectrometry imaging-based spatial metabolomics was used to analyze metabolites in situ (spatial resolution: 20 μm) in kidney tissues from 8 participants with T1D and preserved kidney function and 5 HC. Univariate analysis (t-test or Wilcoxon Mann Whitney test) demonstrated that 36 of 456 METASPACE annotated metabolites were altered (P<0.05) in T1D vs. HC. Partial least squares-discriminant analysis (PLS-DA) and heatmaps showed clearly separated clusters of metabolites. To identify the most significant discriminators for T1D, a variable importance in projection (VIP) plot from PLS-DA model was applied. Of the top 15 metabolites, two TCA cycle intermediates, succinic acid (m/z 117.0193, -H; P = 0.016) and malic acid (m/z 133.0142, -H; P = 0.026), were reduced in kidney tissues of participants with T1D. Pathway analysis revealed that the TCA cycle, mitochondrial electron transport chain, glutamate metabolism, malate-aspartate shuttle, and purine pathway were the dominant metabolic pathways perturbed in T1D kidney tissue. Spatial metabolomics comparing T1D kidney biopsies vs. HC reveal alterations of TCA cycle intermediates indicating mitochondrial dysfunction in the subclinical stages of diabetic kidney disease. The spatial metabolomics data are consistent with the data from transcriptomics and stable isotope tracing analysis in a subset of same participants. Further analysis with pathologic features will identify potential pathways linked to disease development. Disclosure G.Zhang: None. C.Birznieks: 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. J.A.Schaub: None. K.J.Nadeau: None. V.Nair: None. F.Alakwaa: None. P.J.Mccown: None. A.Naik: Advisory Panel; CareDx. L.Pyle: None. D.Blondin: None. L.Liu: None. G.Richard: 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. P.Bjornstad: Advisory Panel; AstraZeneca, Novo Nordisk, Lilly, Horizon Therapeutics plc, Boehringer Ingelheim (Canada) Ltd., LG Chem, Consultant; Bayer Inc., Bristol-Myers Squibb Company. K.Sharma: Advisory Panel; Reata Pharmaceuticals, Inc., Otsuka America Pharmaceutical, Inc. I.M.Tamayo: None. N.Garcia ponce de leon: None. T.B.Vigers: None. K.L.Tommerdahl: None. R.G.Nelson: None. P.E.Ladd: None. T.Alexandrov: None. Funding National Institutes of Health (UH3DK114920); JDRF (2-SRA-2019-845-S-B); Diabetes Research Center (P30DK116073)
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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; both teacher heads agree on what is shown here.
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".