The complexity of dementia development and its comorbidities: The collaborative cross‐mouse population for multivarious tasks approach

TL;DR

This paper reviews how systemic factors like inflammation and metabolism contribute to dementia and explores using genetically diverse mouse models to better understand and treat these conditions.

Contribution

The paper introduces the use of the Collaborative Cross mouse model to study gene-environment interactions in dementia and related neurodegenerative diseases.

Findings

CC mice show strain-dependent susceptibility to inflammation and cognitive impairment.

Metabolic disorders like diabesity accelerate cognitive decline through insulin resistance and oxidative stress.

Autoimmune diseases increase dementia risk via immune activation and neuroinflammation.

Abstract

The rising incidence of dementia and associated neurodegenerative disorders poses a growing public health challenge. These conditions have traditionally been studied as isolated central nervous system disorders; however, emerging evidence suggests that broader systemic factors, including chronic inflammation, immune dysregulation, metabolic dysfunction, and genetic susceptibility, may also play a role. This review examines the interconnection between autoimmune diseases and metabolic syndromes in the pathogenesis and exacerbation of neurodegeneration. Conditions such as rheumatoid arthritis, systemic lupus erythematosus, and type 1 diabetes mellitus have been associated with a heightened risk of developing dementia through chronic immune activation, blood–brain barrier disruption, and neuroinflammatory signaling. Similarly, metabolic disorders such as diabesity promote insulin resistance and oxidative stress, accelerating cognitive decline. The review also discusses glaucoma as a neurodegenerative condition with autoimmune features, underscoring the need for expanded classification and treatment strategies. A key focus is the utilization of the Collaborative Cross (CC) mouse model, which enables the study of gene–environment interactions across genetically diverse backgrounds. Findings from CC mice reveal strain‐dependent susceptibility to inflammation, cognitive impairment, and gut–brain axis dysfunction, providing a translational bridge to human variability. This review highlights the importance of integrating precision‐based approaches to dementia research that consider systemic influences. Advancing our understanding of these multiorgan interactions holds potential for designing precision‐based therapeutic approaches to postpone the onset or reduce the incidence of neurodegenerative conditions.

The increasing prevalence of dementia and related neurodegenerative diseases—including Alzheimer's disease, Parkinson's disease, multiple sclerosis, and amyotrophic lateral sclerosis—poses a growing public health challenge. These conditions have traditionally been studied as isolated central nervous system disorders, but emerging evidence points to broader systemic factors, including chronic inflammation, immune dysregulation, metabolic dysfunction, and genetic susceptibility. Diseases such as rheumatoid arthritis, systemic lupus erythematosus, and type 1 diabetes mellitus have been linked to increased risk of dementia through chronic immune activation, blood–brain barrier disruption, and neuroinflammatory signaling. Similarly, metabolic disorders such as diabesity promote insulin resistance and oxidative stress, accelerating cognitive decline. A key focus is the application of the Collaborative Cross (CC) mouse model, which enables the study of gene–environment interactions across genetically diverse backgrounds. Findings from CC mice reveal strain‐dependent susceptibility to inflammation, cognitive impairment, and gut–brain axis dysfunction, providing a translational bridge to human variability. This review emphasizes the importance of integrated, precision‐based approaches to dementia research that account for systemic influences.

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