Sensitivity analysis of a mathematical model of Alzheimer's disease progression unveils important causal pathways
IntroductionMathematical models serve as essential tools to investigate brain aging, the onset of Alzheimer's disease (AD) and its progression. By studying the representation of the complex dynamics of brain aging processes, such as amyloid beta (Aβ) deposition, tau tangles, neuro-inflammation,...
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Frontiers Media S.A.
2025-07-01
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| Series: | Frontiers in Neuroinformatics |
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| author | Seyedadel Moravveji Halima Sadia Halima Sadia Nicolas Doyon Nicolas Doyon Simon Duchesne Simon Duchesne Simon Duchesne |
| author_facet | Seyedadel Moravveji Halima Sadia Halima Sadia Nicolas Doyon Nicolas Doyon Simon Duchesne Simon Duchesne Simon Duchesne |
| author_sort | Seyedadel Moravveji |
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| description | IntroductionMathematical models serve as essential tools to investigate brain aging, the onset of Alzheimer's disease (AD) and its progression. By studying the representation of the complex dynamics of brain aging processes, such as amyloid beta (Aβ) deposition, tau tangles, neuro-inflammation, and neuronal death. Sensitivity analyses provide a powerful framework for identifying the underlying mechanisms that drive disease progression. In this study, we present the first local sensitivity analysis of a recent and comprehensive multiscale ODE-based model of Alzheimer's Disease (AD) that originates from our group. As such, it is one of the most complex model that captures the multifactorial nature of AD, incorporating neuronal, pathological, and inflammatory processes at the nano, micro and macro scales. This detailed framework enables realistic simulation of disease progression and identification of key biological parameters that influence system behavior. Our analysis identifies the key drivers of disease progression across patient profiles, providing insight into targeted therapeutic strategies.MethodsWe investigated a recent ODE-based model composed of 19 variables and 75 parameters, developed by our group, to study Alzheimer's disease dynamics. We performed single- and paired-parameter sensitivity analyses, focusing on three key outcomes: neural density, amyloid beta plaques, and tau proteins.ResultsOur findings suggest that the parameters related to glucose and insulin regulation could play an important role in neurodegeneration and cognitive decline. Second, the parameters that have the most important impact on cognitive decline are not completely the same depending on sex and APOE status.DiscussionThese results underscore the importance of incorporating a multifactorial approach tailored to demographic characteristics when considering strategies for AD treatment. This approach is essential to identify the factors that contribute significantly to neural loss and AD progression. |
| format | Article |
| id | doaj-art-0613cc3c52f14b798e794e3ae5a22f08 |
| institution | Matheson Library |
| issn | 1662-5196 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Neuroinformatics |
| spelling | doaj-art-0613cc3c52f14b798e794e3ae5a22f082025-07-23T05:35:12ZengFrontiers Media S.A.Frontiers in Neuroinformatics1662-51962025-07-011910.3389/fninf.2025.15909681590968Sensitivity analysis of a mathematical model of Alzheimer's disease progression unveils important causal pathwaysSeyedadel Moravveji0Halima Sadia1Halima Sadia2Nicolas Doyon3Nicolas Doyon4Simon Duchesne5Simon Duchesne6Simon Duchesne7Department of Mathematics and Statistics, Université Laval, Quebec, QC, CanadaMedics Laboratory, Quebec Heart and Lung Institute, Quebec, QC, CanadaFaculty of Medecine, Université Laval, Quebec, QC, CanadaDepartment of Mathematics and Statistics, Université Laval, Quebec, QC, CanadaCERVO Brain Research Centre (Centre de recherche CERVO sur le cerveau, le comportement et la neuropsychiatrie), Quebec, QC, CanadaMedics Laboratory, Quebec Heart and Lung Institute, Quebec, QC, CanadaCERVO Brain Research Centre (Centre de recherche CERVO sur le cerveau, le comportement et la neuropsychiatrie), Quebec, QC, CanadaDepartment of Radiology and Nuclear Medicine, Université Laval, Quebec, QC, CanadaIntroductionMathematical models serve as essential tools to investigate brain aging, the onset of Alzheimer's disease (AD) and its progression. By studying the representation of the complex dynamics of brain aging processes, such as amyloid beta (Aβ) deposition, tau tangles, neuro-inflammation, and neuronal death. Sensitivity analyses provide a powerful framework for identifying the underlying mechanisms that drive disease progression. In this study, we present the first local sensitivity analysis of a recent and comprehensive multiscale ODE-based model of Alzheimer's Disease (AD) that originates from our group. As such, it is one of the most complex model that captures the multifactorial nature of AD, incorporating neuronal, pathological, and inflammatory processes at the nano, micro and macro scales. This detailed framework enables realistic simulation of disease progression and identification of key biological parameters that influence system behavior. Our analysis identifies the key drivers of disease progression across patient profiles, providing insight into targeted therapeutic strategies.MethodsWe investigated a recent ODE-based model composed of 19 variables and 75 parameters, developed by our group, to study Alzheimer's disease dynamics. We performed single- and paired-parameter sensitivity analyses, focusing on three key outcomes: neural density, amyloid beta plaques, and tau proteins.ResultsOur findings suggest that the parameters related to glucose and insulin regulation could play an important role in neurodegeneration and cognitive decline. Second, the parameters that have the most important impact on cognitive decline are not completely the same depending on sex and APOE status.DiscussionThese results underscore the importance of incorporating a multifactorial approach tailored to demographic characteristics when considering strategies for AD treatment. This approach is essential to identify the factors that contribute significantly to neural loss and AD progression.https://www.frontiersin.org/articles/10.3389/fninf.2025.1590968/fullAlzheimer's diseasemathematical modelsneural densitysensitivity analysisamyloid betatau proteins |
| spellingShingle | Seyedadel Moravveji Halima Sadia Halima Sadia Nicolas Doyon Nicolas Doyon Simon Duchesne Simon Duchesne Simon Duchesne Sensitivity analysis of a mathematical model of Alzheimer's disease progression unveils important causal pathways Frontiers in Neuroinformatics Alzheimer's disease mathematical models neural density sensitivity analysis amyloid beta tau proteins |
| title | Sensitivity analysis of a mathematical model of Alzheimer's disease progression unveils important causal pathways |
| title_full | Sensitivity analysis of a mathematical model of Alzheimer's disease progression unveils important causal pathways |
| title_fullStr | Sensitivity analysis of a mathematical model of Alzheimer's disease progression unveils important causal pathways |
| title_full_unstemmed | Sensitivity analysis of a mathematical model of Alzheimer's disease progression unveils important causal pathways |
| title_short | Sensitivity analysis of a mathematical model of Alzheimer's disease progression unveils important causal pathways |
| title_sort | sensitivity analysis of a mathematical model of alzheimer s disease progression unveils important causal pathways |
| topic | Alzheimer's disease mathematical models neural density sensitivity analysis amyloid beta tau proteins |
| url | https://www.frontiersin.org/articles/10.3389/fninf.2025.1590968/full |
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