Longitudinal Brain Volume Changes in Frontotemporal Dementia: Clinical and Demographic Influences
Poster No:
105
Submission Type:
Abstract Submission
Authors:
Taylor Solomon1, Terence O'Brien1, Ben Sinclair1, Lucy Vivash1
Institutions:
1Monash University, Melbourne, Victoria
First Author:
Co-Author(s):
Introduction:
Frontotemporal dementia (FTD) is a cluster of neurodegenerative syndromes characterised by progressive atrophy in the frontal and temporal lobes, resulting in a myriad of cognitive and behavioural changes (Gifford et al., 2023). Although the pathophysiology of FTD is well studied, longitudinal data tracking the progression of brain volume changes over time remain limited (Foxe et al., 2024). Given the role of demographic and clinical factors in influencing disease progression, understanding their relationship with brain atrophy is crucial for improving diagnostic and therapeutic strategies (Onyike & Diehl-Schmid, 2013). This study aimed to investigate brain volume changes across multiple MRI sessions in individuals with genetic FTD and assess the role of demographic and clinical factors in modulating these changes. It was hypothesised that brain volume would decline over time, with greater atrophy associated with worsened clinical symptoms. Furthermore, it was expected that older age and female sex would correlate with increased brain volume loss.
Methods:
Data for this study were obtained from the ARTFL LEFFTDS Longitudinal Frontotemporal Dementia (ALLFTD) cohort (Forsberg et al., 2022). Participants with MAPT (n=108), GRN (n=91), and C9orf72 (n=190) FTD genotypes were included to explore genotype-specific patterns in brain volume changes. Longitudinal brain volume measurements in cortical and subcortical regions were recorded across multiple scan sessions (ranging from 1 to 7 sessions) for each participant. T1-weighted MRIs were processed using Fastsurfer. A linear mixed model was applied in R Studio to assess the relationship between brain volume and predictors, including age, cognitive dementia rating (CDR) score, sex, and MRI scan session number. A random intercept for each subject was included to account for repeated measures, enabling analysis of individual trajectories and baseline differences. The model was fit using restricted maximum likelihood to estimate fixed effects and adjust for within-subject correlations.
Results:
The linear mixed model revealed significant relationships between brain volume and several predictors. The fixed effects showed that CDR score had a significant negative association with brain volume (p<0.001), with higher CDR scores corresponding to more pronounced atrophy. Increased session number, representing scans taken at later time points, also showed a strong negative effect on brain volume, indicating greater disease progression (p<0.001). Males had larger brain volumes compared to females (p<0.001). The interaction between the GRN genotype and CDR score was statistically significant (p=0.044), while the interactions between MAPT and C9orf72 genotypes and CDR score were not significant (p=0.534 and p=0.678, respectively). No single genotype exhibited a significant main effect on brain volume. Random effects indicated substantial between-subject variability, highlighting heterogeneity in individual brain volume trajectories.
Conclusions:
This study highlights the progressive nature of brain volume loss in FTD. While no genotype alone had a significant main effect on brain volume, the interaction between genotype, clinical, and demographic factors - along with substantial between-subject variability in individual brain trajectories - underscores the complexity and heterogeneity of brain atrophy patterns in FTD. As observed in this cohort, the significant interaction between the GRN genotype and CDR score suggests a unique pattern of brain atrophy in GRN carriers as clinical symptoms worsen. The negative association between CDR score and brain volume, combined with the effect of later scan sessions, emphasises the relationship between disease severity and atrophy. Ultimately, longitudinal studies such as this one enhance our understanding of FTD progression and brain atrophy, offering valuable insights that could inform the development of biomarkers and clinical interventions aimed at slowing disease progression.
Disorders of the Nervous System:
Neurodegenerative/ Late Life (eg. Parkinson’s, Alzheimer’s) 1
Novel Imaging Acquisition Methods:
Anatomical MRI 2
Keywords:
Degenerative Disease
Other - Frontotemporal dementia (FTD); brain atrophy; MRI volumetry; structural MRI; neurodegeneration; MRI biomarkers; longitudinal study; disease progression; cognitive decline
1|2Indicates the priority used for review
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Provide references using APA citation style.
Foxe, D., Irish, M., Cheung, S. C., D'Mello, M., Hwang, Y. T., Muggleton, J., Cordato, N. J., & Piguet, O. (2024). Longitudinal changes in functional capacity in frontotemporal dementia and Alzheimer's disease. Alzheimer's & Dementia, 16(4), e70028.
Gifford, A., Praschan, N., Newhouse, A., & Chemali, Z. (2023). Biomarkers in frontotemporal dementia: Current landscape and future directions. Biomarkers in Neuropsychiatry, 8, 100065.
Onyike, C. U., & Diehl-Schmid, J. (2013). The epidemiology of frontotemporal dementia.
International Review of Psychiatry, 25(2), 130-137.