Association of Initial Side of Brain Atrophy With Clinical Features and Disease Progression in Patients With <i>GRN</i> Frontotemporal Dementia
Bibliographic record
Abstract
Background and Objectives Pathogenic variants in the GRN gene cause frontotemporal dementia (FTD- GRN ) with marked brain asymmetry. This study aims to assess whether the disease progression of FTD- GRN depends on the initial side of the atrophy. We also investigated the potential use of brain asymmetry as a biomarker of the disease. Methods Retrospective examination of data from the prospective Genetic Frontotemporal Initiative (GENFI) cohort study that recruits individuals who carry or were at risk of carrying a pathogenic variant causing FTD. GENFI participants underwent a standardized clinical and neuropsychological assessment, MRI, and a blood sample test yearly. We generated an asymmetry index for brain MRI to characterize brain asymmetry in participants with or at risk of FTD- GRN . Depending on the side of the asymmetry, we classified symptomatic GRN patients as right- GRN or left- GRN and compared their clinical features and disease progression. We generated generalized additive models to study how the asymmetry index evolves in carriers and noncarriers and compare its models with others created with volumetric values and plasma neurofilament light chain. Results A total of 399 participants (mean age 49.7 years, 59% female) were included (63 symptomatic carriers, 177 presymptomatic carriers, and 159 noncarriers). Symptomatic carriers showed higher brain asymmetry (11.6) than noncarriers (1.0, p < 0.001) and presymptomatic carriers (1.0, p < 0.001), making it possible to classify most of them as right- GRN (n = 21) or left- GRN (n = 36). Patients with right- GRN showed more disease severity at baseline ( β = 6.9, 95% CI 2.4–11.0, p = 0.003) but a lower deterioration by year ( β = −1.5, 95% CI −2.7 to −0.31, p = 0.015) than patients with left- GRN . Brain asymmetry could be found in GRN carriers 10.4 years before the onset of the symptoms (standard difference 0.85, CI 0.01–1.68). Discussion FTD- GRN affects the brain hemispheres asymmetrically and causes 2 anatomical asymmetry patterns depending on the side of the disease onset. We demonstrated that these 2 anatomical asymmetry patterns present different symptoms, severity at the time of the first visit, and different disease courses. Our results also suggest brain asymmetry as a possible biomarker of conversion in GRN carriers.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".