Insulin Null β-cells Have a Prohormone Processing Defect That Is Not Reversed by AAV Rescue of Proinsulin Expression
Bibliographic record
Abstract
Up to 6% of diabetes has a monogenic cause including mutations in the insulin gene, and patients are candidates for a gene therapy. Using a mouse model of permanent neonatal diabetes, we assessed the efficacy of an adeno-associated virus (AAV)-mediated gene therapy. We used AAVs with a rat insulin 1 promoter (Ins1) regulating a human insulin gene (INS; AAV Ins1-INS) or native mouse insulin 1 (Ins1; AAV Ins-Ins1) to deliver an insulin gene to β-cells of constitutive insulin null mice (Ins1-/-Ins2-/-) and adult inducible insulin-deficient mice [Ins1-/-Ins2f/f PdxCreER and Ins1-/-Ins2f/f mice administered AAV Ins1-Cre)]. Although AAV Ins1-INS could successfully infect and confer insulin expression to β-cells, insulin null β-cells had a prohormone processing defect. Secretion of abundant proinsulin transiently reversed diabetes. We reattempted therapy with AAV Ins1-Ins1, but Ins1-/-Ins2-/- β-cells still had a processing defect of both replaced Ins1 and pro-islet amyloid polypeptide (proIAPP). In adult inducible models, β-cells that lost insulin expression developed a processing defect that resulted in impaired proIAPP processing and elevated circulating proIAPP, and cells infected with AAV Ins1-Ins1 to rescue insulin expression secreted proinsulin. We assessed the subcellular localization of prohormone convertase 1/3 (PC1/3) and detected defective sorting of PC1/3 to glycogen-containing vacuoles and retention in the endoplasmic reticulum as a potential mechanism underlying defective processing. We provide evidence that persistent production of endogenous proinsulin within β-cells is necessary for β-cells to be able to properly store and process proinsulin.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".