Disruption of a Receptor-Mediated Mechanism for Intracellular Sorting of Proinsulin in Familial Hyperproinsulinemia
Bibliographic record
Abstract
In familial hyperproinsulinemia, specific mutations in the proinsulin gene are linked with a profound increase in circulating plasma proinsulin levels. However, the molecular and cellular basis for this disease remains uncharacterized. Here we investigated how these mutations may disrupt the sorting signal required to target proinsulin to the secretory granules of the regulated secretory pathway, resulting in the unregulated release of proinsulin. Using a combination of molecular modeling and site-directed mutagenesis, we have identified structural molecular motifs in proinsulin that are necessary for correct sorting into secretory granules of endocrine cells. We show that membrane carboxypeptidase E (CPE), previously identified as a prohormone-sorting receptor, is essential for proinsulin sorting. This was demonstrated through short interfering RNA-mediated depletion of CPE and transfection with a dominant negative mutant of CPE in a beta-cell line. Mutant proinsulins found in familial hyperproinsulinemia failed to bind to CPE and were not sorted efficiently. These findings provide evidence that the elevation of plasma proinsulin levels found in patients with familial hyperproinsulinemia is caused by the disruption of CPE-mediated sorting of mutant proinsulins to the regulated secretory pathway.
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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) | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".