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Alzheimer’s disease (AD) is a complex, multifactorial, and currently incurable neurodegenerative disorder. Existing treatments can only slow disease progression, highlighting the urgent need for reliable biomarkers for early diagnosis. Among the most promising candidates are iron and amyloid-beta 42 (Aβ42), which can be measured both in blood and cerebrospinal fluid (CSF).
One of the hypothesized contributing mechanisms in AD is the formation of amyloid-beta plaques in the brain. However, this process remains difficult to observe and quantify in vivo. To address this limitation, several mathematical models have been proposed by our group to describe the temporal accumulation of iron and amyloid-beta in the brain (Ficiarà et al. 2022, 2023). Despite their relevance, these models are constrained by simplifying assumptions, most notably the representation of the brain as a single homogeneous compartment rather than a complex, spatially structured system.
In this work, we propose an integrated mathematical framework that combines existing models of iron and Aβ dynamics into a more comprehensive description of their interaction and evolution. Model validation is performed using multimodal data from the Alzheimer’s Disease Neuroimaging Initiative (ADNI («ADNI | Alzheimer’s Disease Neuroimaging Initiative», s.d.)), including PET and T2-weighted imaging, CSF measurements of iron and Aβ, and cognitive assessment scores such as the Mini-Mental State Examination (MMSE).
Bibliography
«ADNI | Alzheimer’s Disease Neuroimaging Initiative». s.d. Consultato 19 marzo 2026. https://adni.loni.usc.edu/.
Ficiarà, Eleonora, Ilaria Stura, e Caterina Guiot. 2022. «Iron Transport across Brain Barriers: Model and Numerical Parameter Estimation». Mathematics 10 (23). https://doi.org/10.3390/math10234461.
Ficiarà, Eleonora, Ilaria Stura, Caterina Guiot, e Ezio Venturino. 2023. «A mathematical model on Aβ blood–brain transport: Simulations of plaques’ formation in Alzheimer’s disease». Medical Hypotheses 181 (dicembre): 111194. https://doi.org/10.1016/j.mehy.2023.111194.
