P4‐320: LRP10, a new regulator of APP trafficking and processing
Bibliographic record
Abstract
Accumulation of extracellular amyloid peptide (Aß), generated from amyloid precursor protein (APP) processing by ß- and γ-secretases, is toxic to neurons and is central to the pathogenesis of Alzheimer's disease (AD). Production of Aß from APP is greatly affected by the subcellular localization and trafficking of APP. Therefore understanding how APP is moved around and controlled is central to developing therapies for AD treatment. Various members of the LDLR family (LRP1, SorLA) have been found to interact with APP and to regulate its trafficking and processing. We recently characterized a new member of the LDLR family called LRP10 which shuttles between the trans-Golgi Network (TGN) and endosomes. LRP10 homology to the sorting receptor SorLA leads us to hypothesize that LRP10 is a functional APP receptor involved in APP trafficking and processing Studies were performed mainly in human neuroblastoma cells (SH-SY5Y) stably expressing LRP10 wild-type or trafficking mutant. Protein interactions were determined by immunoprecipitation and pull-down assays. The subcellular localizations were characterized by confocal microscopy. APP processing products were determined by WB and ELISA. LRP10 interacts directly with APP and colocalizes with APP at the TGN. Mutations of key motifs responsible for the recycling of LRP10 to the TGN results in the aberrant targeting of LRP10 (named LRP10-DXXAA) to the endosomal compartment and the plasma membrane and induces the redistribution of APP to early endosomes. Increased expression of LRP10 wild-type reduces processing of APP into Aß and sAPP, while expression of LRP10-DXXAA trafficking mutant increased ß-site cleavage of APP and accelerate generation of Aß. A possible role for LRP10 as risk factor for AD was supported by preliminary studies indicating decreased levels of LRP10 in post mortem brain tissue of AD patients. Our data show that LRP10 binds to APP and modulates its intracellular distribution as well as its processing, strengthening the potential role of LRP10 as a novel APP sorting receptor. LRP10 wild-type seems to protect APP from processing into Aß and thereby reduces the burden of amyloidogenic peptide formation. Consequently, reduced LRP10 receptor expression in the human brain may increase Aß production and plaque formation and promote spontaneous AD.
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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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".