The Spectrum of Mutations in Progranulin
Bibliographic record
Abstract
BACKGROUND: Mutation in the progranulin gene (GRN) can cause frontotemporal dementia (FTD). However, it is unclear whether some rare FTD-related GRN variants are pathogenic and whether neurodegenerative disorders other than FTD can also be caused by GRN mutations. OBJECTIVES: To delineate the range of clinical presentations associated with GRN mutations and to define pathogenic candidacy of rare GRN variants. DESIGN: Case-control study. SETTING: Clinical and neuropathology dementia research studies at 8 academic centers. PARTICIPANTS: Four hundred thirty-four patients with FTD, including primary progressive aphasia, semantic dementia, FTD/amyotrophic lateral sclerosis (ALS), FTD/motor neuron disease, corticobasal syndrome/corticobasal degeneration, progressive supranuclear palsy, Pick disease, dementia lacking distinctive histopathology, and pathologically confirmed cases of frontotemporal lobar degeneration with ubiquitin-positive inclusions (FTLD-U); and 111 non-FTD cases (controls) in which TDP-43 deposits were a prominent neuropathological feature, including subjects with ALS, Guam ALS and/or parkinsonism dementia complex, Guam dementia, Alzheimer disease, multiple system atrophy, and argyrophilic grain disease. MAIN OUTCOME MEASURES: Variants detected on sequencing of all 13 GRN exons and at least 80 base pairs of flanking introns, and their pathogenic candidacy determined by in silico and ex vivo splicing assays. RESULTS: We identified 58 genetic variants that included 26 previously unknown changes. Twenty-four variants appeared to be pathogenic, including 8 novel mutations. The frequency of GRN mutations was 6.9% (30 of 434) of all FTD-spectrum cases, 21.4% (9 of 42) of cases with a pathological diagnosis of FTLD-U, 16.0% (28 of 175) of FTD-spectrum cases with a family history of a similar neurodegenerative disease, and 56.2% (9 of 16) of cases of FTLD-U with a family history. CONCLUSIONS: Pathogenic mutations were found only in FTD-spectrum cases and not in other related neurodegenerative diseases. Haploinsufficiency of GRN is the predominant mechanism leading to FTD.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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) | 0.002 | 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".