Using Fatty Acid-Binding Proteins as Potential Biomarkers to Discriminate between Parkinson’s Disease and Dementia with Lewy Bodies: Exploration of a Novel Technique

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Abstract

An increase in the global aging population is leading to an increase in age-related conditions such as dementia and movement disorders, including Alzheimer’s disease (AD), Parkinson’s disease (PD), and dementia with Lewy bodies (DLB). The accurate prediction of risk factors associated with these disorders is crucial for early diagnosis and prevention. Biomarkers play a significant role in diagnosing and monitoring diseases. In neurodegenerative disorders like α-synucleinopathies, specific biomarkers can indicate the presence and progression of disease. We previously demonstrated the pathogenic impact of fatty acid-binding proteins (FABPs) in α-synucleinopathies. Therefore, this study investigated FABPs as potential biomarkers for Lewy body diseases. Plasma FABP levels were measured in patients with AD, PD, DLB, and mild cognitive impairment (MCI) and healthy controls. Plasma FABP3 was increased in all groups, while the levels of FABP5 and FABP7 tended to decrease in the AD group. Additionally, FABP2 levels were elevated in PD. A correlation analysis showed that higher FABP3 levels were associated with decreased cognitive function. The plasma concentrations of Tau, GFAP, NF-L, and UCHL1 correlated with cognitive decline. A scoring method was applied to discriminate between diseases, demonstrating high accuracy in distinguishing MCI vs. CN, AD vs. DLB, PD vs. DLB, and AD vs. PD. The study suggests that FABPs could serve as potential biomarkers for Lewy body diseases and aid in early disease detection and differentiation.

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Kawahata, I., Sekimori, T., Oizumi, H., Takeda, A., & Fukunaga, K. (2023). Using Fatty Acid-Binding Proteins as Potential Biomarkers to Discriminate between Parkinson’s Disease and Dementia with Lewy Bodies: Exploration of a Novel Technique. International Journal of Molecular Sciences, 24(17). https://doi.org/10.3390/ijms241713267

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