The Longitudinal Evaluation of Familial Frontotemporal Dementia Subjects (LEFFTDS) Protocol: Known Kindreds and Preliminary Data (P5.003)
Bibliographic record
Abstract
OBJECTIVE: To present background data on a newly funded protocol focused on familial frontotemporal lobar degeneration (fFTLD). BACKGROUND: It is important to determine the natural history of fFTLD and generate clinical, neuropsychological, neuroimaging and biofluid data for planning disease-modifying trials. DESIGN/METHODS: As part of the Longitudinal Evaluation of Familial Frontotemporal Dementia Subjects (LEFFTDS) protocol, investigators at 8 centers in North America pooled data and developed strategies for evaluating subjects in kindreds with mutations in microtubule associated protein tau (MAPT), progranulin (GRN), or chromosome 9 open reading frame 72 (C9orf72) genes. RESULTS: There are 306 known kindreds (45 MAPT, 81 GRN and 180 C9orf72) and 835 total subjects (including 295 mutation carriers) already identified. The median (SD) age of onset data across all genes is 55 (11), and for each gene is as follows: MAPT - 49 (10) years, GRN - 61 (12) years, and C9orf72 - 55 (11). Serial scans were used to develop Tensor Based Morphometry maps to measure changes in frontotemporal volume (FTV) in 43 symptomatic mutation carriers, and the findings revealed declines in FTV of 3.27[percnt]/year for MAPT, 3.44[percnt]/year for C9orf72 and 5.75[percnt]/year for GRN. Declines on neuropsychological measures sensitive to frontotemporal network dysfunction were also shown for symptomatic mutation carriers across the 3 groups. Among 15 asymptomatic MAPT mutation carriers, a decline of 0.95[percnt]/year in FTV was demonstrated, but scores on neuropsychological measures did not change significantly. CONCLUSIONS: These kindreds and findings underscore the potential utility of evaluating symptomatic and asymptomatic fFTLD subjects longitudinally with traditional and novel MRI and neuropsychological measures. These measures as well as biofluid samples (eg, DNA, plasma, mRNA and CSF) will be collected prospectively in 300 subjects beginning in 2015 as part of the LEFFTDS protocol, with key data and samples being available to interested investigators worldwide.
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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 | 0.015 | 0.015 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.017 | 0.007 |
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".