P3‐279: A novel progranulin mutation in a large frontotemporal dementia calabrian kindred
Bibliographic record
Abstract
Frontotemporal dementia (FTD) in several 17q21-linked families was recently explained by truncating mutations in the progranulin gene (GRN). Objective of this study is to determine the frequency of GRN mutations in a cohort of Caucasian FTD patients without mutations in known FTD genes. GRN was sequenced in a series of 78 independent FTD patients including 23 familial subjects. A different Calabrian dataset (109 normal controls and 96 FTD patients) was used to establish the frequency of the GRN mutation A novel truncating GRN mutation (c.1145insA) was detected in a proband of an extended consanguineous Calabrian kindred. Segregation analysis of 70 family members revealed 19 heterozygous mutation carriers including 9 patients affected by FTD. The absence of homozygous carriers in highly consanguineous kindred may indicate that the loss of both GRN alleles might lead to embryonic lethality. An extremely variable age-at-onset in the mutation carriers (more than five decades apart) is not explained by APOE genotypes or the H1/H2 MAPT haplotypes. Intriguingly, the mutation was excluded in four FTD patients belonging to branches with an autosomal dominant mode of inheritance of FTD, suggesting that another novel FTD gene accounts for the disease in the phenocopies. It is difficult to clinically distinguish phenocopies from GRN mutation carriers, except that language in mutation carriers was more severely compromised. The current results imply further genetic heterogeneity of FTD, since we detected only one GRN-linked family (∼1%). The value of discovering large kindred includes the possibility of a longitudinal study of GRN mutation carriers.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".