# Neuroimmune Dysregulation and AI-Driven Therapeutic Strategies in Alzheimer’s Disease

## TL;DR

This paper explores how neuroimmune interactions contribute to Alzheimer’s disease and how AI can help develop new therapeutic strategies.

## Contribution

The paper introduces AI-driven approaches to understand and target neuroimmune dysregulation in Alzheimer’s disease.

## Key findings

- Microglial metabolic reprogramming and lipid-metabolism dysregulation are major drivers of neuroinflammation in Alzheimer’s.
- AI and machine learning can accelerate drug discovery and simulate disease progression in Alzheimer’s research.
- Integrated, multitargeted interventions are proposed to improve personalized therapies for Alzheimer’s.

## Abstract

Neuroimmune interactions have arisen as central contributors to the pathogenesis and progression of Alzheimer’s disease. The exacerbation of neuronal dysfunction in Alzheimer’s disease is collectively contributed by dysregulation of astrocytic and microglial responses, invasion of peripheral immune cells, and chronic inflammation. A mechanistic understanding of molecular, cellular, and systems-level neuroimmune interactions in Alzheimer’s disease is enabling rational, testable therapeutic strategies. We have tried to extensively address the molecular regulation of glial activation, inflammasome signaling, and immune cell invasion in Alzheimer’s disease. This review highlights microglial metabolic reprogramming and lipid-metabolism dysregulation as major drivers of neuroinflammation. Existing and future therapeutic approaches to glial activation, immunometabolism, and inflammasome signaling are thoroughly reviewed, together with novel strategies involving stem cell-derived exosomes and peripheral immunity modulation. Artificial intelligence and machine learning technologies are the latest game-changing technologies in unraveling neuroimmune complexity, discovering biomarkers, simulating disease courses, and speeding up drug discovery. Integration of multi-omics information and AI-based predictive models is suggested as a critical strategy for the development of precision medicine strategies in neuroimmune therapeutics. Advancements in neuroimmune research, coupled with computational biology technological advancements, hold the promise to transform the therapeutic environment for Alzheimer’s disease. Multitargeted, integrated interventions and data-driven strategies are set to overcome current limitations and advance closer to effective, personalized therapies.