Indole-3-propionic acid links gut dysfunction to diabetic retinopathy: a biomarker and novel therapeutic approach
Bibliographic record
Abstract
BACKGROUND: Both host and microbe metabolism of tryptophan (Trp) is altered in diabetes; however, the molecular mechanisms are incompletely understood. OBJECTIVE: We used strategies to increase either angiotensin converting enzyme-2 (ACE-2) dependent or independent Trp absorption in a model of type 2 diabetes, db/db mice, and tested whether the strategies could prevent development of diabetic retinopathy (DR), the most common microvascular complication of diabetes. Additionally, we investigated levels of Trp metabolites in humans with and without DR. DESIGN: Enhanced ACE-2 dependent Trp absorption was achieved with gavage of genetically modified bacteria that preserved intestinal ACE2:sodium coupled neutral amino acid transporter expression. ACE-2 independent Trp absorption was achieved by gavage of the Trp dipeptide (Isoleucine-Trp; IW) absorbed via solute carrier family 15 member 1. Both strategies were used either as a prevention (6 months treatment) or intervention (3 months treatment) and at the conclusion, intestinal, metabolic and retinal studies were performed including spatial mass spectroscopy (MS). Plasma Trp metabolites and gut permeability markers were measured in individuals with T2D with (n=30) and without (n=40) DR and compared with healthy controls (n=35). RESULTS: -ACE2 or IW treatment prevented DR, corrected dysbiosis, enriched Trp-metabolising bacteria, improved gut barrier integrity, boosted incretin secretion and restored glucose homeostasis in db/db mice. Spatial MS identified indole propionic acid (IPA) as a metabolite in the retinal pigment epithelial layer protecting the posterior blood retinal barrier. T2D individuals with DR demonstrated elevated serum markers of endotoxemia and intestinal barrier disruption while showing reduced levels of the beneficial metabolite IPA and elevated levels of the toxic metabolite indole sulfate. CONCLUSION: Nutraceutical strategies that restore Trp metabolism or IPA serve as both a biomarker and a treatment for DR.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.001 | 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".