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Steatosis in the Amygdala and Frontal Cortex: Potential Magnetic Resonance Imaging Biomarkers for Alzheimer's Disease

de Oliveira Andrade, L. J.; Matos de Oliveira, G. C.; Nunes Carneiro Andrade, J. C.; Malta de Figueiredo, A.; Smith, G.; Matos de Oliveira, L.

2025-01-25 neurology
10.1101/2025.01.15.24319769 medRxiv
Show abstract

IntroductionAlzheimers Disease (AD) is characterized by progressive neurodegeneration, with significant alterations in brain biochemistry. While previous studies have investigated various aspects of AD, the specific lipid changes in key brain regions remain inadequately defined. ObjectiveTo quantitatively evaluate lipid levels within the amygdala and frontal cortex regions of interest using Magnetic Resonance Spectroscopy (MRS) in a cohort of magnetic resonance imaging (MRI) scans of individuals with confirmed AD compared to healthy controls. MethodsThirty MRI examinations from individuals with confirmed AD were compared to 30 normal controls. MRS data were acquired using a 1.5T scanner, focusing on lipid peaks within specific frequency ranges. A voxel-based MRS technique was employed to assess lipid concentrations, focusing on spectral data in defined frequency ranges associated with lipid presence. Lipid concentrations were quantified, and statistical comparisons were performed between groups using the t-test. ResultsMRS analysis revealed distinct lipid peaks in both the amygdala and frontal cortex of AD patients, with frequencies indicating elevated lipid concentrations compared to controls. In the amygdala, increased lipid concentrations were observed in the 2.5-3.5 ppm range, suggesting alterations in lipid composition. The similar findings were observed in the frontal cortex, with AD patients showing significantly elevated lipid peaks within the 3.0-4.5 ppm range. ConclusionOur results underscore the potential of MRS to identify lipid alterations in AD, suggesting that lipid profiles in the amygdala and frontal cortex could serve as biomarkers for disease progression and provide understanding into neurodegenerative mechanisms.

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