Correlations between Cerebrospinal Fluid Biomarkers and Gray Matter Atrophy in Alzheimer's and Behavioural Variant Frontotemporal Dementia


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Abstract

Introduction:Distinguishing between frontotemporal dementia (FTD) and Alzheimer’s disease (AD) in their early stages remains a significant clinical challenge. Cerebrospinal fluid (CSF) biomarkers (total Tau, phosphorylated Tau, and beta-amyloid) are promising candidates for identifying early differences between these conditions. This study investigates the relationship between grey matter density and CSF markers in the behavioural variant of frontotemporal dementia (bvFTD) and Alzheimer’s disease (AD).

Method:CSF and 3D T1-weighted magnetic resonance (MR) images were acquired from 14 bvFTD patients, 15 AD patients, and 13 cognitively normal (CN) matched subjects. The CSF markers and their relative ratios (total Tau/beta-amyloid, phosphorylated Tau/beta-amyloid) were compared across the three groups. Voxel-based morphometry (VBM) was performed to characterize the anatomical changes in bvFTD and AD patients compared to CN subjects. Grey matter density maps were obtained by automatic segmentation of 3.0 Tesla 3D T1-Weighted MR Images, and their correlation with CSF markers and relative ratios was investigated.

Results:Results demonstrated that, as compared to CN subjects, AD patients are characterised by higher CSF total Tau levels and lower beta-amyloid levels; however, beta-amyloid and relative ratios discriminated AD from bvFTD. In addition, AD and bvFTD patients showed different patterns of atrophy, with AD exhibiting more central (temporal areas) and bvFTD more anterior (frontal areas) atrophy. A correlation was found between grey matter density maps and CSF marker concentrations in the AD group, with total Tau and phosphorylated Tau levels showing a high association with low grey matter density in the left superior temporal gyrus.

Conclusion:Overall, while bvFTD lacks a CSF marker profile, CSF beta-amyloid levels are useful for differentiating AD from bvFTD. Furthermore, MR structural imaging can contribute significantly to distinguishing between the two pathologies.

About the authors

Benedetta Tafuri

Center for Neurodegenerative Diseases and the Aging Brain, University of Bari Aldo Moro at Pia Fondazione "Cardinale G. Panico",

Email: info@benthamscience.net

Davide Rivolta

Department of Education, Psychology and Communication, University of Bari Aldo Moro

Email: info@benthamscience.net

Giancarlo Logroscino

Center for Neurodegenerative Diseases and the Aging Brain, University of Bari Aldo Moro at Pia Fondazione "Cardinale G. Panico",

Email: info@benthamscience.net

Gaetano Scianatico

Department of Education, Psychology and Communication, University of Bari Aldo Moro

Email: info@benthamscience.net

Valerio Manippa

Department of Education, Psychology and Communication, University of Bari Aldo Moro

Author for correspondence.
Email: info@benthamscience.net

Domenico Zaca

Center for Mind/Brain Sciences, University of Trento

Email: info@benthamscience.net

Jorge Jovicich

Center for Mind/Brain Sciences, University of Trento

Email: info@benthamscience.net

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