Regional Radiomics Similarity Networks Reveal Distinct Subtypes and Abnormality Patterns in Mild Cognitive Impairment.
Alzheimer's Disease Neuroimaging Initiative
Adv Sci (Weinh)
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Zhao, K., Zheng, Q., Dyrba, M., Rittman, T., Li, A., Che, T., Chen, P., et al. (2022). Regional Radiomics Similarity Networks Reveal Distinct Subtypes and Abnormality Patterns in Mild Cognitive Impairment.. Adv Sci (Weinh) https://doi.org/10.1002/advs.202104538
Funder: Startup Funds for Leading Talents at Beijing Normal University
Individuals with mild cognitive impairment (MCI) of different subtypes show distinct alterations in network patterns. The first aim of this study is to identify the subtypes of MCI by employing a regional radiomics similarity network (R2SN). The second aim is to characterize the abnormality patterns associated with the clinical manifestations of each subtype. An individual-level R2SN is constructed for N = 605 normal controls (NCs), N = 766 MCI patients, and N = 283 Alzheimer's disease (AD) patients. MCI patients' R2SN profiles are clustered into two subtypes using nonnegative matrix factorization. The patterns of brain alterations, gene expression, and the risk of cognitive decline in each subtype are evaluated. MCI patients are clustered into "similar to the pattern of NCs" (N-CI, N = 252) and "similar to the pattern of AD" (A-CI, N = 514) subgroups. Significant differences are observed between the subtypes with respect to the following: 1) clinical measures; 2) multimodal neuroimaging; 3) the proportion of progression to dementia (61.54% for A-CI and 21.77% for N-CI) within three years; 4) enriched genes for potassium-ion transport and synaptic transmission. Stratification into the two subtypes provides new insight for risk assessment and precise early intervention for MCI patients.
Research Article, Research Articles, mild cognitive impairment, progression, regional radiomics similarity network, subtypes
Fundamental Research Funds for the Central Universities (2021XD‐A03‐1)
National Natural Science Foundation of China (81972160, 81871438, 82172018, 61802330)
Beijing Natural Science Funds for Distinguished Young Scholar (JQ20036)
External DOI: https://doi.org/10.1002/advs.202104538
This record's URL: https://www.repository.cam.ac.uk/handle/1810/333470