A Systematic Review of the Genetics and Pathology of Psychosis in Frontotemporal Dementia
Bibliographic record
Abstract
ABSTRACT: Objectives: Frontotemporal dementia (FTD) patients frequently present with psychosis, which complicates diagnosis and management. In this study, we aim to examine the relationship between psychosis and the most common genetic mutations predisposing to FTD, and in the different pathological subtypes of FTD. Design: We conducted a systematic review, searching the literature up to December 2022, and reviewed 50 articles that met our inclusion criteria. From the reviewed articles, we extracted and summarized data regarding the frequency of psychosis and patient characteristics in each major genetic and pathological subtype of FTD. Results: Among FTD patients with confirmed genetic mutations or pathological diagnosss, the frequency of psychosis was 24.2%. Among the genetic mutation carriers, C9orf72 mutation carriers had the highest frequency of psychosis (31.4%), whereas GRN (15.0%) and MAPT (9.2%) mutation carriers had lower frequencies of psychosis. MAPT mutation carriers notably developed psychosis at a younger age compared to other genetic groups. The most common psychotic symptoms were delusions among C9orf72 carriers and visual hallucinations among GRN mutation carriers. Among the pathological subtypes, 30% of patients with FUS pathology, 25.3% of patients with TDP-43 pathology, and 16.4% of patients with tau pathology developed psychosis. In the TDP-43 group, subtype B pathology was the most common subtype reported in association with psychosis. Conclusion: Our systematic review suggests a high frequency of psychosis in specific subgroups of FTD patients. Further studies are required to understand the structural and biological underpinnings of psychosis in 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 | 0.006 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.019 | 0.018 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".