Longitudinal behavioral and neuropsychiatric changes and their MRI correlates in predementia <i>C9orf72</i> and <i>GRN</i> mutation carriers
Bibliographic record
Abstract
Background Neuropsychiatric symptoms (NPS) progress differently among individuals with autosomal dominant familial frontotemporal dementia (FTD) caused by genetic mutations in granulin ( GRN +) or chromosome 9 open reading frame 72 ( C9orf72 +). Objective To determine whether these differences begin prior to the onset of dementia, we compared the longitudinal rates of change of NPS among C9orf72 +, GRN +, and noncarrier controls in the predementia phase. Additionally, we assessed whether the NPS changes were correlated with gray matter (GM) volume loss or white matter signal abnormalities (WMSAs) on magnetic resonance imaging (MRI). Methods Eighty-two participants (N = 10 GRN +, N = 23 C9orf72 +, N = 49 noncarriers) were followed using various NPS rating scales for an average of 7.8 years. Group differences were compared using generalized linear mixed-effects models. GM volume and WMSA volumes were measured on 42 participants (N = 8 GRN +, N = 11 C9orf72 +, N = 23 noncarriers) who had two MRI visits. These measures were correlated with the rates of NPS score changes. Results C9orf72 + showed higher rates of increase in the Beck Depression Inventory (BDI) total and the Iowa Scales of Personality Change (ISPC) dysexecutive disturbance scores versus noncarriers. GRN + showed higher rates of increase in the BDI total, the ISPC total, and the emotional/social disturbance scores versus noncarriers; and higher rates of increase in the ISPC emotional/social personality and distressed disturbance scores versus C9orf72 +. Across all groups, faster WMSA accumulation correlated with higher rates of increase in the Neuropsychiatric Inventory Questionnaire total score. Conclusions Changes in NPS differ among C9orf72 +, GRN +, and noncarrier controls prior to the onset of overt FTD.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".