Mathematical model probes metals’ role in Alzheimer’s plaque formation

Mathematics is being used to investigate how common metals could influence the formation of protein plaques associated with Alzheimer’s disease and how potential therapies might disrupt the process.

Shantia Yarahmadian, an associate professor in Mississippi State University’s Department of Mathematics and Statistics, has developed a mathematical model that simulates a series of reactions involving amyloid-beta, a protein associated with plaque formation in Alzheimer’s disease.

The research builds on Yarahmadian’s work developing mathematical models to investigate biological processes involved in the disease.

“Every biological phenomenon occurs in the physical world – in space and time – and involves changes in shape, quantity and matter. Because of its abstract power, mathematics allows us to uncover patterns, test hypotheses and make predictions that may not be possible through observation alone. Mathematics does not replace laboratory or clinical research; it complements it by helping us understand the larger system, identify the most influential mechanisms and guide future experiments.”

Shantia Yarahmadian, a faculty member in MSU’s Department of Mathematics and Statistics. 

Examining metals and amyloid-beta

The model focuses on metals including copper and zinc, which may interact with amyloid-beta and influence the way the protein aggregates. These aggregates can contribute to the formation of plaques associated with Alzheimer’s disease.

Yarahmadian and collaborators created a framework capable of simulating the chain of chemical reactions involved in these processes, allowing the researchers to examine two potential approaches for disrupting aggregation.

Rather than relying solely on mathematical calculations, the researchers tested the model against experimental evidence. They compared its results with data obtained using atomic force microscopy, a technique that can be used to examine microscopic aggregates.

The comparison provided evidence that the mathematical framework could reproduce patterns observed in laboratory experiments.

Connecting mathematics with experiments

The model successfully reproduced the patterns seen in the laboratory, an important step to prove the model is not just a theoretical calculation. It can accurately predict real-world behavior, giving scientists greater confidence in understanding how aggregates form and potentially how they might be controlled.

The approach demonstrates how mathematical modelling can complement laboratory research by allowing scientists to explore complex biological systems and test how changes to individual mechanisms could affect the wider process.

Such models could also help researchers identify questions for future experiments and investigate how potential therapeutic strategies might influence amyloid-beta aggregation.

A broader approach to Alzheimer’s research

For Yarahmadian, the attraction of Alzheimer’s research lies in both its complexity and its potential human significance.

“What drew me to Alzheimer’s research is the combination of its profound human impact and its extraordinary biological complexity,” he said. “My goal is to use mathematical modeling to identify important mechanisms and generate insights that may help guide future experimental and therapeutic research.”

The research does not replace experimental or clinical studies. Instead, the mathematical framework provides another way to examine the interactions involved in amyloid-beta aggregation and explore possible interventions.

By linking mathematical predictions with laboratory observations, the researchers hope the work can contribute to a more detailed understanding of the mechanisms underlying plaque formation and support future research into potential therapies for Alzheimer’s disease.