Distinct Neuroanatomical Correlates of Neuropsychiatric Symptoms in the Three Main Forms of Genetic Frontotemporal Dementia in the GENFI Cohort
Bibliographic record
Abstract
BACKGROUND: The overlap between frontotemporal dementia (FTD) and primary psychiatric disorders has been brought to light by reports of prominent neuropsychiatric symptoms (NPS) in FTD-related genetic mutations, particularly among C9orf72 and GRN carriers. It has been recently demonstrated that early neuroanatomical changes in genetic FTD may be different across the major disease-causing mutations. OBJECTIVE: We aimed to identify whether NPS could be driven by distinct structural correlates. METHODS: One hundred and sixty-seven mutation carriers (75 GRN, 60 C9orf72, and 32 MAPT) were included from the Genetic FTD Initiative (GENFI) study, a large international cohort of genetic FTD. Neuropsychiatric symptoms including delusions, hallucinations (visual, auditory, and tactile), depression, and anxiety were investigated using a structured interview. Voxel-based morphometry was performed to identify neuroanatomical correlates of NPS. RESULTS: Psychotic symptoms correlated mainly with grey matter (GM) atrophy in the anterior insula, left thalamus, cerebellum, and cortical regions including frontal, parietal, and occipital lobes in GRN mutations carriers. GM atrophy in posterior structures of the default-mode network was associated with anxiety in the GRN group. Delusions in C9orf72 expansion carriers were mainly associated with left frontal cortical atrophy. Cerebellar atrophy was found to be correlated only with anxiety in C9orf72 carriers. NPS in the MAPT group were mainly associated with volume loss in the temporal lobe. CONCLUSION: Neuroanatomical correlates of NPS appear to be distinct across the main forms of genetic FTD. Overall, our findings support overlapping brain structural changes between FTD and primary psychiatric disorders.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".