Mutations in progranulin are a major cause of ubiquitin-positive frontotemporal lobar degeneration
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Null mutations in the progranulin gene (PGRN) were recently reported to cause tau-negative frontotemporal dementia linked to chromosome 17. We assessed the genetic contribution of PGRN mutations in an extended population of patients with frontotemporal lobar degeneration (FTLD) (N=378). Mutations were identified in 10% of the total FTLD population and 23% of patients with a positive family history. This mutation frequency dropped to 5% when analysis was restricted to an unbiased FTLD subpopulation (N=167) derived from patients referred to Alzheimer's Disease Research Centers (ADRC). Among the ADRC patients, PGRN mutations were equally frequent as mutations in the tau gene (MAPT). We identified 23 different pathogenic PGRN mutations, including a total of 21 nonsense, frameshift and splice-site mutations that cause premature termination of the coding sequence and degradation of the mutant RNA by nonsense-mediated decay. We also observed an unusual splice-site mutation in the exon 1 5' splice site, which leads to loss of the Kozac sequence, and a missense mutation in the hydrophobic core of the PGRN signal peptide. Both mutations revealed novel mechanisms that result in loss of functional PGRN. One mutation, c.1477C>T (p.Arg493X), was detected in eight independently ascertained familial FTLD patients who were shown to share a common extended haplotype over the PGRN genomic region. Clinical examination of patients with PGRN mutations revealed highly variable onset ages with language dysfunction as a common presenting symptom. Neuropathological examination showed FTLD with ubiquitin-positive cytoplasmic and intranuclear inclusions in all PGRN mutation carriers.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 | 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 it