化疗相关认知障碍与阿尔茨海默病之间的生物学交叉。

IF 4.7 2区 医学 Q1 PATHOLOGY American Journal of Pathology Pub Date : 2025-01-23 DOI:10.1016/j.ajpath.2024.12.013
Matthew Torre, Camila A Zanella, Mel B Feany
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The Biological Intersection Between Chemotherapy-Related Cognitive Impairment and Alzheimer Disease.

Alzheimer disease (AD) is the most common type of dementia and one of the leading causes of death in elderly patients. The number of patients with AD in the United States is projected to double by 2060. Thus, understanding modifiable risk factors for AD is an urgent public health priority. In parallel with the number of patients with AD, the number of cancer survivors is estimated to increase significantly, and up to 80% of cancer patients treated with chemotherapy will develop cognitive deficits, termed chemotherapy-related cognitive impairment. This review discusses biologically plausible pathways underlying both disorders, with the goal of understanding why a proportion of chemotherapy patients may be at higher risk of developing AD. Highlighted are the E4 allele of the apolipoprotein E gene, neuroinflammation, oxidative stress, DNA damage, mitochondrial dysfunction, neuronal and synaptic loss, cellular senescence, brain-derived neurotrophic factor signaling, white matter damage, blood-brain barrier/vascular dysfunction, tau pathology, and transposable element reactivation.

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来源期刊
CiteScore
11.40
自引率
0.00%
发文量
178
审稿时长
30 days
期刊介绍: The American Journal of Pathology, official journal of the American Society for Investigative Pathology, published by Elsevier, Inc., seeks high-quality original research reports, reviews, and commentaries related to the molecular and cellular basis of disease. The editors will consider basic, translational, and clinical investigations that directly address mechanisms of pathogenesis or provide a foundation for future mechanistic inquiries. Examples of such foundational investigations include data mining, identification of biomarkers, molecular pathology, and discovery research. Foundational studies that incorporate deep learning and artificial intelligence are also welcome. High priority is given to studies of human disease and relevant experimental models using molecular, cellular, and organismal approaches.
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