亚型
疾病
神经科学
生物信息学
计算生物学
危险分层
医学
生物
精密医学
机制(生物学)
萎缩
人口分层
心理学
组学
计算机科学
临床疾病
阿尔茨海默病
作者
Klara Gawor,Kevin Statz,Jolien Schaeverbeke,Dietmar Rudolf Thal
出处
期刊:Brain
[Oxford University Press]
日期:2026-05-01
卷期号:149 (9): 2936-2954
标识
DOI:10.1093/brain/awag157
摘要
Alzheimer's disease (AD) is characterized by amyloid-β plaques and abnormal phosphorylated Tau protein-containing neurofibrillary tangles, yet it shows marked heterogeneity in clinical presentation, neuroanatomical involvement and progression rate. This variability challenges the traditional view of AD as a single disease entity and has prompted efforts to define patient subgroups with shared characteristics who might benefit from targeted treatment strategies. Here, we provide a cross-disciplinary overview of current subtyping strategies. We describe both traditional stratification approaches, including those based on clinical AD syndromes, neuropathological staging and age of onset, as well as emerging data-driven methods that utilize clinical information, neuroimaging, omics data and multimodal data integration. Subtypes derived using these data-driven methods overlap to some extent with hypothesis-driven classifications but also uncover additional axes of heterogeneity, including distinct anatomical patterns and molecular signatures. Furthermore, we highlight that most AD patients exhibit co-pathologies such as transactive response DNA-binding protein 43, α-synuclein or cerebrovascular changes, which are often overlooked in existing stratification systems, despite their potential to affect atrophy patterns and progression rate and, hence, influence subtype interpretation. Finally, we outline future directions for developing unified stratification frameworks that link clinical features with underlying biology, including co-pathologies, aiming to enhance diagnostic precision and enable future personalized therapeutic interventions.
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