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The Role of Emerging Environmental Contaminants on Alzheimer’s Disease

IntechOpen eBooks 2025 Score: 48 ? 0–100 AI score estimating relevance to the microplastics field. Papers below 30 are filtered from public browse.
İ. İpek Boşgelmez, Beyza Mertaş

Summary

This review examined the role of emerging environmental contaminants, including microplastics, in the development and progression of Alzheimer's disease. The authors discussed mechanisms including oxidative stress, neuroinflammation, and blood-brain barrier disruption as potential pathways linking environmental exposures to AD pathogenesis.

Body Systems

According to the latest data from WHO, about 57 million individuals worldwide were living with dementia in 2021, with 10 million new cases diagnosed each year. Alzheimer’s disease (AD) accounts for approximately 60–80% of dementia cases and ranks as the seventh leading cause of death globally. Currently, the therapeutic options available for AD have limited effectiveness, and potential disease-modifying therapies are not widely adopted or reliably deemed safe. Therefore, implementing preventive strategies and raising public awareness about the relevant AD risk factors are crucial. Existing data delineate various risk factors for AD, encompassing non-modifiable factors such as age, genetic predisposition, and gender, alongside modifiable factors including environmental pollution and diet. This chapter aims to explore emerging environmental risk factors that contribute to AD, including air pollution, toxic elements, pesticides, microplastics, nanoplastics, endocrine disruptors, pharmaceuticals and personal care products, environmental disasters, and global climate change. The intricate and multifaceted nature of neurodegenerative disorders such as AD necessitates an interdisciplinary approach to unravel the underlying mechanisms. This involves the effective application of various omics techniques—such as genomics, transcriptomics, proteomics, metabolomics, and lipidomics—paired with advanced artificial intelligence (AI) methods, including machine learning and deep learning.

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