Robust Identification of Alzheimer's Disease subtypes based on cortical atrophy patterns

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초록

Accumulating evidence suggests that Alzheimer's disease (AD) is heterogenous and can be classified into several subtypes. Here, we propose a robust subtyping method for AD based on cortical atrophy patterns and graph theory. We calculated similarities between subjects in their atrophy patterns throughout the whole brain, and clustered subjects with similar atrophy patterns using the Louvain method for modular organization extraction. We applied our method to AD patients recruited at Samsung Medical Center and externally validated our method by using the AD Neuroimaging Initiative (ADNI) dataset. Our method categorized very mild AD into three clinically distinct subtypes with high reproducibility (>90%); the parietal-predominant (P), medial temporal-predominant (MT), and diffuse (D) atrophy subtype. The P subtype showed the worst clinical presentation throughout the cognitive domains, while the MT and D subtypes exhibited relatively mild presentation. The MT subtype revealed more impaired language and executive function compared to the D subtype.

키워드

NEUROIMAGING INITIATIVE ADNI; WHITE-MATTER HYPERINTENSITIES; RATING-SCALE SUM; DEFINED SUBTYPES; COMPOSITE SCORE; PARIETAL CORTEX; NORMATIVE DATA; MEMORY; SYSTEM; HETEROGENEITY
제목
Robust Identification of Alzheimer's Disease subtypes based on cortical atrophy patterns
저자
Park, Jong-Yun; Na, Han Kyu; Kim, Sungsoo; Kim, Hyunwook; Kim, Hee Jin; Seo, Sang Won; Na, Duk L.; Han, Cheol E.; Seong, Joon-Kyung
DOI
10.1038/srep43270
발행일
2017-03-09
유형
Article
저널명
Scientific Reports
권
7