# Linking dietary patterns to Alzheimer's disease biomarkers with network mathematical modeling could enable new approach methodologies in preventative AD research: a narrative interdisciplinary review

## TL;DR

This paper explores how mathematical models can help understand how diet affects Alzheimer's disease risk and could guide prevention strategies.

## Contribution

The paper proposes using network mathematical modeling as a new approach to link dietary patterns with Alzheimer's biomarkers.

## Key findings

- Dietary patterns influence one third of Alzheimer's disease risk factors.
- Mathematical and computational models are encouraged as new approaches to study Alzheimer's disease.
- Interdisciplinary collaboration is needed to develop simulation-based models linking diet to Alzheimer's pathology.

## Abstract

Alzheimer's disease (AD) is a significant global health concern. With no reliable pharmaceutical treatments on the horizon, the best path forward is preventative. Dietary patterns are related to one third of AD risk factors and have long been thought to influence the onset or the progression of AD. Studies of the preventative possibilities of diet on AD offer the prospect of helping to suppress AD prevalence until effective pharmaceutical interventions are discovered but can be challenging due to variations, duration, cost or ethical considerations presented by human and animal studies. At the same time, the National Institutes of Health and the Food and Drug Administration are encouraging new approach methodologies (NAMs), including mathematical and computational models, to help study human diseases like AD (AD-NAMs). This narrative review is an approachable starting point for interdisciplinary teams of nutritional scientists, neuroscientists, mathematicians and computer scientists with an interest in developing mathematical or simulation-based AD-NAMs that aim to link diet to AD biomarker pathology.

We introduce the interdisciplinary reader to the three essential areas, including their historical context and contemporary advances, required to chart the further development of simulation-based AD-NAMs: the fundamentals and contextual significance of AD protein biomarker pathology; the history and evidence for dietary influence on that pathology; and an introduction to network mathematical models to mathematically analyze and computationally simulate the progression of that pathology. Afterwards, we offer views on bridging the gap between the contemporary approach and those

. that may be used to mathematically and computationally investigate: potential mechanistic links between dietary patterns and AD biomarker pathology; and the potential of dietary patterns to help suppress AD prevalence, at least until reliable pharmaceutical options can be developed