Leukocyte cell-derived chemotaxin 2 (LECT2)–associated amyloidosis is a frequent cause of hepatic amyloidosis in the United States
Bibliographic record
Abstract
Using laser microdissection and mass spectrometry (MS)-based proteomics, we subtyped amyloid deposits from 130 cases of hepatic amyloidosis. Although we confirmed that immunoglobulin light chain amyloidosis was the most frequent cause of hepatic amyloidosis, leukocyte cell-derived chemotaxin 2 (LECT2) amyloidosis (ALect2) accounted for 25% of cases. This novel finding was associated with Hispanic ancestry, incidental discovery of amyloid in liver specimens sampled for other unrelated conditions, and a characteristic pattern of hepatic amyloid deposition. Although ALect2 patients had a common LECT2 polymorphism, pathogenic mutations were not discovered, suggesting that constitutive or compensatory LECT2 overexpression led to ALect2 deposition. These findings indicate that ALect2 is a common cause of hepatic amyloidosis in the population of the United States, and subtyping hepatic amyloid deposits by an accurate analytic method such as MS is required for optimal clinical management of hepatic amyloidosis patients and to avoid incorrect and unnecessarily toxic therapies.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.000 | 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".