Regional Radiomics Similarity Networks Reveal Distinct Subtypes and Abnormality Patterns in Mild Cognitive Impairment

被引:41
作者
Zhao, Kun [1 ,2 ]
Zheng, Qiang [3 ]
Dyrba, Martin [4 ]
Rittman, Timothy [5 ]
Li, Ang [6 ]
Che, Tongtong [1 ]
Chen, Pindong [7 ,8 ,9 ]
Sun, Yuqing [7 ,8 ,9 ]
Kang, Xiaopeng [7 ,8 ,9 ]
Li, Qiongling [10 ]
Liu, Bing [10 ]
Liu, Yong [2 ,7 ,8 ]
Li, Shuyu [1 ,10 ]
机构
[1] Beihang Univ, Sch Biol Sci & Med Engn, Beijing Adv Innovat Ctr Biomed Engn, Beijing 100191, Peoples R China
[2] Beijing Univ Posts & Telecommun, Sch Artificial Intelligence, Beijing 100876, Peoples R China
[3] Yantai Univ, Sch Comp & Control Engn, Yantai 264005, Peoples R China
[4] German Ctr Neurodegenerat Dis DZNE, D-18147 Rostock, Germany
[5] Univ Cambridge, Dept Clin Neurosci, Cambridge Biomed Campus, Cambridge CB2 0SZ, England
[6] Chinese Acad Sci, State Key Lab Brain & Cognit Sci, Inst Biophys, Beijing 100101, Peoples R China
[7] Chinese Acad Sci, Inst Automat, Brainnetome Ctr, Beijing 100190, Peoples R China
[8] Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
[9] Chinese Acad Sci, Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China
[10] Beijing Normal Univ, State Key Lab Cognit Neurosci & Learning, Beijing 100875, Peoples R China
基金
加拿大健康研究院; 中国国家自然科学基金; 美国国家卫生研究院;
关键词
mild cognitive impairment; progression; regional radiomics similarity network; subtypes; ALZHEIMERS-DISEASE; CORTICAL ATROPHY; DEMENTIA; MRI; MCI; HETEROGENEITY; PROGRESSION; EXTRACTION; BIOMARKERS; MICROGLIA;
D O I
10.1002/advs.202104538
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
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.
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页数:13
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  • [1] Imaging structural co-variance between human brain regions
    Alexander-Bloch, Aaron
    Giedd, Jay N.
    Bullmore, Edward T.
    [J]. NATURE REVIEWS NEUROSCIENCE, 2013, 14 (05) : 322 - 336
  • [2] Bardakjian Tanya, 2018, Handb Clin Neurol, V147, P93, DOI 10.1016/B978-0-444-63233-3.00008-7
  • [3] Microglia modulate neurodegeneration in Alzheimer's and Parkinson's diseases
    Bartels, Tim
    De Schepper, Sebastiaan
    Hong, Soyon
    [J]. SCIENCE, 2020, 370 (6512) : 66 - +
  • [4] Morphometric network differences n ageing versus Alzheimer's disease dementia
    Binette, Alexa Pichet
    Gonneaud, Julie
    Vogel, Jacob W.
    La Joie, Renaud
    Rosa-Neto, Pedro
    Collins, D. Louis
    Poirier, Judes
    Breitner, John C. S.
    Villeneuve, Sylvia
    Vachon-Presseau, Etienne
    [J]. BRAIN, 2020, 143 : 635 - 649
  • [5] Microglia become hypofunctional and release metalloproteases and tau seeds when phagocytosing live neurons with P301S tau aggregates
    Brelstaff, Jack H.
    Mason, Matthew
    Katsinelos, Taxiarchis
    McEwan, William A.
    Ghetti, Bernardino
    Tolkovsky, Aviva M.
    Spillantini, Maria Grazia
    [J]. SCIENCE ADVANCES, 2021, 7 (43):
  • [6] Hippocampal plasticity underpins long-term cognitive gains from resistance exercise in MCI
    Broadhouse, Kathryn M.
    Singh, Maria Fiatarone
    Suo, Chao
    Gates, Nicola
    Wen, Wei
    Brodaty, Henry
    Jain, Nidhi
    Wilson, Guy C.
    Meiklejohn, Jacinda
    Singh, Nalin
    Baune, Bernhard T.
    Baker, Michael
    Foroughi, Nasim
    Wang, Yi
    Kochan, Nicole
    Ashton, Kevin
    Brown, Matt
    Li, Zhixiu
    Mavros, Yorgi
    Sachdev, Perminder S.
    Valenzuela, Michael J.
    [J]. NEUROIMAGE-CLINICAL, 2020, 25
  • [7] The future of functional MRI in clinical medicine
    Bullmore, Edward T.
    [J]. NEUROIMAGE, 2012, 62 (02) : 1267 - 1271
  • [8] A New Initiative on Precision Medicine
    Collins, Francis S.
    Varmus, Harold
    [J]. NEW ENGLAND JOURNAL OF MEDICINE, 2015, 372 (09) : 793 - 795
  • [9] Exploring relationships in gene expressions: A partial least squares approach
    Datta, S
    [J]. GENE EXPRESSION, 2001, 9 (06): : 249 - 255
  • [10] Genetic assessment of age-associated Alzheimer disease risk: Development and validation of a polygenic hazard score
    Desikan, Rahul S.
    Fan, Chun Chieh
    Wang, Yunpeng
    Schork, Andrew J.
    Cabra, Howard J., I
    Cupples, L. Adrienne
    Thompson, Wesley K.
    Besser, Lilah
    Kukull, Walter A.
    Holland, Dominic
    Chen, Chi-Hua
    Brewer, James B.
    Karow, David S.
    Kauppi, Karolina
    Witoelar, Aree
    Karch, Celeste M.
    Bonham, Luke W.
    Yokoyama, Jennifer S.
    Rosen, Howard J.
    Miller, Bruce L.
    Dillon, William P.
    Wilson, David M.
    Hess, Christopher P.
    Pericak-Vance, Margaret
    Haines, Jonathan L.
    Farrer, Lindsay A.
    Mayeux, Richard
    Hardy, John
    Goate, Alison M.
    Hyman, Bradley T.
    Schellenberg, Gerard D.
    McEvoy, Linda K.
    Andreassen, Ole A.
    Dale, Anders M.
    [J]. PLOS MEDICINE, 2017, 14 (03):