A Joint Tau Propagation and Neuroinflammation Model Reinforces Inflammatory Modulation of Network-Driven Spread in Alzheimer's Disease
Dhaliwal, I.; Sandell, R.; Raj, A.
Show abstract
Alzheimers disease (AD) is a progressive neurodegenerative disorder and the leading cause of dementia. Despite over a century of research, AD remains untreatable due to an incomplete understanding of its underlying mechanisms. While amyloid beta has dominated therapeutic efforts, tau pathology and neuroinflammation represent critical disease drivers and intriguing therapeutic targets. We developed an extended computational model building upon the open-source Aggregation Network Diffusion (AND) framework by coupling spatial tau propagation and aggregation with ordinary differential equations representing key inflammatory cascades. The model incorporates M1/M2 microglia and astrocytic activation, cytokine-mediated feedback loops, and neuronal loss, all modulated via region-specific genetic expression matrices of ApoE and TREM2 with variant-specific weighting. The model maintains biologically plausible tau dynamics while generating robust inflammatory marker trends, serving as a computational testbed for hypothesis generation and mechanistic exploration. The inflammatory components independently capture experimental observations and display a marked M1/M2 microglia divergence. The model demonstrates enhanced similarity to regional tau propagation patterns due to inflammatory and genetic components, reinforcing neuroinflammations role in tau spread and highlighting the need to incorporate these processes in modeling efforts. Finally, through parsimony analysis, we identify microglia and pro-inflammatory rates (including microglia-facilitated tau spread) as key contributors to improved model accuracy, informing future modeling approaches.
Matching journals
The top 10 journals account for 50% of the predicted probability mass.
Similar papers in this journal
Similar papers in this journal
- Non-linear microglial, inflammatory and oligodendrocyte dynamics across stages of Alzheimer's disease 92%
- Functional dynamic network connectivity differentiates biological patterns in the Alzheimer's disease continuum 90%
- Co-expression patterns of microglia markers Iba1, TMEM119 and P2RY12 in Alzheimer's disease 90%
Similar papers in this journal
- Virtual brain simulations reveal network-specific parameters in neurodegenerative dementias 93%
- Network efficiency predicts resilience to cognitive decline in elderly at risk for Alzheimer's 92%
- Phenotyping Neuropsychiatric Symptoms Profiles of Alzheimer's Disease Using Cluster Analysis on EEG Power 91%
Similar papers in this journal
- The impact of genetic risk for Alzheimers disease on the structural brain networks of young adults 92%
- Levetiracetam Modulates Brain Metabolic Networks and Transcriptomic Signatures in the 5XFAD Mouse Model of Alzheimer's disease. 91%
- Increased excursions to functional networks in schizophrenia in the absence of task 91%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.