Regional Radiomics Similarity Networks Reveal Distinct Subtypes and Abnormality Patterns in Mild Cognitive Impairment
Abstract 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...
| Main Authors: | , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2022-04-01
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| Series: | Advanced Science |
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| Online Access: | https://doi.org/10.1002/advs.202104538 |
| _version_ | 1817989079338319872 |
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| author | Kun Zhao Qiang Zheng Martin Dyrba Timothy Rittman Ang Li Tongtong Che Pindong Chen Yuqing Sun Xiaopeng Kang Qiongling Li Bing Liu Yong Liu Shuyu Li for the Alzheimer's Disease Neuroimaging Initiative |
| author_facet | Kun Zhao Qiang Zheng Martin Dyrba Timothy Rittman Ang Li Tongtong Che Pindong Chen Yuqing Sun Xiaopeng Kang Qiongling Li Bing Liu Yong Liu Shuyu Li for the Alzheimer's Disease Neuroimaging Initiative |
| author_sort | Kun Zhao |
| collection | DOAJ |
| description | Abstract 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. |
| first_indexed | 2024-04-14T00:42:39Z |
| format | Article |
| id | doaj.art-a8219ae3547841519e105cd1604fbe7a |
| institution | Directory Open Access Journal |
| issn | 2198-3844 |
| language | English |
| last_indexed | 2024-04-14T00:42:39Z |
| publishDate | 2022-04-01 |
| publisher | Wiley |
| record_format | Article |
| series | Advanced Science |
| spelling | doaj.art-a8219ae3547841519e105cd1604fbe7a2022-12-22T02:22:09ZengWileyAdvanced Science2198-38442022-04-01912n/an/a10.1002/advs.202104538Regional Radiomics Similarity Networks Reveal Distinct Subtypes and Abnormality Patterns in Mild Cognitive ImpairmentKun Zhao0Qiang Zheng1Martin Dyrba2Timothy Rittman3Ang Li4Tongtong Che5Pindong Chen6Yuqing Sun7Xiaopeng Kang8Qiongling Li9Bing Liu10Yong Liu11Shuyu Li12for the Alzheimer's Disease Neuroimaging InitiativeBeijing Advanced Innovation Centre for Biomedical Engineering School of Biological Science and Medical Engineering Beihang University Beijing 100191 ChinaSchool of Computer and Control Engineering Yantai University Yantai 264005 ChinaGerman Center for Neurodegenerative Diseases (DZNE) Rostock 18147 GermanyDepartment of Clinical Neurosciences University of Cambridge Cambridge Biomedical Campus Cambridge CB2 0SZ UKState Key Laboratory of Brain and Cognitive Science, Institute of Biophysics Chinese Academy of Sciences Beijing 100101 ChinaBeijing Advanced Innovation Centre for Biomedical Engineering School of Biological Science and Medical Engineering Beihang University Beijing 100191 ChinaBrainnetome Center & National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences Beijing 100190 ChinaBrainnetome Center & National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences Beijing 100190 ChinaBrainnetome Center & National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences Beijing 100190 ChinaState Key Laboratory of Cognition Neuroscience & Learning Beijing Normal University Beijing 100875 ChinaState Key Laboratory of Cognition Neuroscience & Learning Beijing Normal University Beijing 100875 ChinaSchool of Artificial Intelligence Beijing University of Posts and Telecommunications Beijing 100876 ChinaBeijing Advanced Innovation Centre for Biomedical Engineering School of Biological Science and Medical Engineering Beihang University Beijing 100191 ChinaAbstract 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.https://doi.org/10.1002/advs.202104538mild cognitive impairmentprogressionregional radiomics similarity networksubtypes |
| spellingShingle | Kun Zhao Qiang Zheng Martin Dyrba Timothy Rittman Ang Li Tongtong Che Pindong Chen Yuqing Sun Xiaopeng Kang Qiongling Li Bing Liu Yong Liu Shuyu Li for the Alzheimer's Disease Neuroimaging Initiative Regional Radiomics Similarity Networks Reveal Distinct Subtypes and Abnormality Patterns in Mild Cognitive Impairment Advanced Science mild cognitive impairment progression regional radiomics similarity network subtypes |
| title | Regional Radiomics Similarity Networks Reveal Distinct Subtypes and Abnormality Patterns in Mild Cognitive Impairment |
| title_full | Regional Radiomics Similarity Networks Reveal Distinct Subtypes and Abnormality Patterns in Mild Cognitive Impairment |
| title_fullStr | Regional Radiomics Similarity Networks Reveal Distinct Subtypes and Abnormality Patterns in Mild Cognitive Impairment |
| title_full_unstemmed | Regional Radiomics Similarity Networks Reveal Distinct Subtypes and Abnormality Patterns in Mild Cognitive Impairment |
| title_short | Regional Radiomics Similarity Networks Reveal Distinct Subtypes and Abnormality Patterns in Mild Cognitive Impairment |
| title_sort | regional radiomics similarity networks reveal distinct subtypes and abnormality patterns in mild cognitive impairment |
| topic | mild cognitive impairment progression regional radiomics similarity network subtypes |
| url | https://doi.org/10.1002/advs.202104538 |
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