Islet Amyloid Polypeptide (IAPP): A Second Amyloid in Alzheimer's Disease
Bibliographic record
Abstract
Amyloid formation is the pathological hallmark of type 2 diabetes (T2D) and Alzheimer's disease (AD). These diseases are marked by extracellular amyloid deposits of islet amyloid polypeptide (IAPP) in the pancreas and amyloid β (Aβ) in the brain. Since IAPP may enter the brain and disparate amyloids can cross-seed each other to augment amyloid formation, we hypothesized that pancreatic derived IAPP may enter the brain to augment misfolding of Aβ in AD. The corollaries for validity of this hypothesis are that IAPP [1] enters the brain, [2] augments Aβ misfolding, [3] associates with Aβ plaques, and most importantly [4] plasma levels correlate with AD diagnosis. We demonstrate the first 3 corollaries that: (1) IAPP is present in the brain in human cerebrospinal fluid (CSF), (2) synthetic IAPP promoted oligomerization of Aβ in vitro, and (3) endogenous IAPP localized to Aβ oligomers and plaques. For the 4th corollary, we did not observe correlation of peripheral IAPP levels with AD pathology in either an African American cohort or AD transgenic mice. In the African American cohort, with increased risk for both T2D and AD, peripheral IAPP levels were not significantly different in samples with no disease, T2D, AD, or both T2D and AD. In the Tg2576 AD mouse model, IAPP plasma levels were not significantly elevated at an age where the mice exhibit the glucose intolerance of pre-diabetes. Based on this negative data, it appears unlikely that peripheral IAPP cross-seeds or "infects" Aβ pathology in AD brain. However, we provide novel and additional data which demonstrate that IAPP protein is present in astrocytes in murine brain and secreted from primary cultured astrocytes. This preliminary report suggests a potential and novel association between brain derived IAPP and AD, however whether astrocytic derived IAPP cross-seeds Aβ in the brain requires further research.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".