Neurodevelopmental effects of genetic frontotemporal dementia mutations revealed by total intracranial volume differences
Bibliographic record
Abstract
Background Converging evidence hints at neurodevelopmental effects in people at risk of genetic frontotemporal dementia (FTD). Objective We investigated total intracranial volume (TIV), a neuroimaging marker of neurodevelopment, and years of education differences between adult mutation carriers and familial non-mutation carriers, as measures of the structural and functional neurodevelopmental effects of FTD-causing genetic mutations. Methods This cross-sectional cohort study, facilitated through the FTD Prevention Initiative (FPI), included 902 adult pathogenic mutation carriers of GRN , MAPT , or C9orf72 , and 532 familial non-carriers. ANCOVAs were computed to compare TIV and education between groups per gene. Pearson's correlations were used to examine associations between TIV and education. Results Mutation carriers (mean ± SD age = 50.0 ± 13.2 years, sex = 55% female, n ( GRN ) = 298, n( MAPT ) = 187, n ( C9orf72 ) = 417) were compared to familial non-carriers (age = 48.0 ± 12.9 years, sex = 58% female, n ( GRN ) = 201, n( MAPT ) = 114), n ( C9orf72 ) = 217). Consistent with prior findings in young adults, GRN carriers showed larger TIV, on average by 20531 mm 3 , compared to familial non-carriers (95% CI [85.4, 40977], p = 0.049, η 2 p = 0.008). Larger TIV correlated with higher years of education in GRN carriers (95% CI [0.01, 0.24], r (295) = 0.12, p = 0.03) and GRN non-carriers (95% CI [0.08, 0.34], r(198) = 0.21, p = 0.002). MAPT carriers demonstrated smaller TIV than non-carriers, on average by 29896 mm 3 (95% CI [–58248, −1545], p = 0.039, η 2 p = 0.02). Models with C9orf72 and education as outcome variables did not reveal significant differences. Conclusions In support of the neurodevelopmental hypothesis of FTD, GRN and MAPT mutations are linked to structural neurodevelopmental changes in TIV. Further research is needed to identify mechanisms underlying neurodevelopmental influences of FTD mutations and ascertain their suitability as intervention targets.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.002 | 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".