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Identification of Cognitive Dysfunction in Patients with T2DM Using Whole Brain Functional Connectivity

文献类型：期刊论文

作者Liu, Zhenyu6,8; Liu, Jiangang1,9; Yuan, Huijuan2,10; Liu, Taiyuan2,3; Cui, Xingwei4,5; Tang, Zhenchao8,11; Du, Yang8; Wang, Meiyun2,3; Lin, Yusong4,5; Tian, Jie1,6,7,8
刊名GENOMICS PROTEOMICS & BIOINFORMATICS
出版日期2019-08-01
卷号17期号:4页码:441-452
关键词Type 2 diabetes mellitus Resting state functional connectivity Elastic net Support vector machines MoCA
ISSN号1672-0229
DOI10.1016/j.gpb.2019.09.002
通讯作者Wang, Meiyun(mywang@ha.edu.cn) ; Lin, Yusong(yslin@ha.edu.cn) ; Tian, Jie(jie.tian@ia.ac.cn)
英文摘要Majority of type 2 diabetes mellitus (T2DM) patients are highly susceptible to several forms of cognitive impairments, particularly dementia. However, the underlying neural mechanism of these cognitive impairments remains unclear. We aimed to investigate the correlation between whole brain resting state functional connections (RSFCs) and the cognitive status in 95 patients with T2DM. We constructed an elastic net model to estimate the Montreal Cognitive Assessment (MoCA) scores, which served as an index of the cognitive status of the patients, and to select the RSFCs for further prediction. Subsequently, we utilized a machine learning technique to evaluate the discriminative ability of the connectivity pattern associated with the selected RSFCs. The estimated and chronological MoCA scores were significantly correlated with R = 0.81 and the mean absolute error (MAE) = 1.20. Additionally, cognitive impairments of patients with T2DM can be identified using the RSFC pattern with classification accuracy of 90.54% and the area under the receiver operating characteristic (ROC) curve (AUC) of 0.9737. This connectivity pattern not only included the connections between regions within the default mode network (DMN), but also the functional connectivity between the task-positive networks and the DMN, as well as those within the task-positive networks. The results suggest that an RSFC pattern could be regarded as a potential biomarker to identify the cognitive status of patients with T2DM.
WOS关键词ALZHEIMERS-DISEASE ; INSULIN-RESISTANCE ; NETWORK ; REGULARIZATION ; IMPAIRMENT ; DISORDERS ; PATTERNS ; MRI
资助项目National Natural Science Foundation of China[81772012] ; National Natural Science Foundation of China[81227901] ; National Natural Science Foundation of China[61673051] ; National Natural Science Foundation of China[81641168] ; National Natural Science Foundation of China[31470047] ; National Natural Science Foundation of China[81271565] ; National Natural Science Foundation of China[81527805] ; National Natural Science Foundation of China[61231004] ; National Key R&D Program of China[2017YFA0205200] ; Youth Innovation Promotion Association, Chinese Academy of Sciences[2019136]
WOS研究方向Genetics & Heredity
语种英语
WOS记录号WOS:000505053300010
出版者ELSEVIER
资助机构National Natural Science Foundation of China ; National Key R&D Program of China ; Youth Innovation Promotion Association, Chinese Academy of Sciences
源URL[http://ir.ia.ac.cn/handle/173211/29445]  
专题自动化研究所_中国科学院分子影像重点实验室
通讯作者Wang, Meiyun; Lin, Yusong; Tian, Jie
作者单位1.Beihang Univ, Beijing Adv Innovat Ctr Big Data Based Precis Med, Sch Med, Beijing 100191, Peoples R China
2.Zhengzhou Univ, Peoples Hosp, Zhengzhou 450003, Henan, Peoples R China
3.Zhengzhou Univ, Dept Radiol, Henan Prov Peoples Hosp, Zhengzhou 450003, Henan, Peoples R China
4.Zhengzhou Univ, Sch Software, Zhengzhou 450003, Henan, Peoples R China
5.Zhengzhou Univ, Cooperat Innovat Ctr Internet Healthcare, Zhengzhou 450003, Henan, Peoples R China
6.Univ Chinese Acad Sci, Beijing 100080, Peoples R China
7.Xidian Univ, Engn Res Ctr Mol & Neuro Imaging, Sch Life Sci & Technol, Minist Educ, Xian 710126, Shaanxi, Peoples R China
8.Chinese Acad Sci, Inst Automat, CAS Key Lab Mol Imaging, Beijing 100190, Peoples R China
9.Beijing Jiaotong Univ, Sch Comp & Informat Technol, Beijing 100044, Peoples R China
10.Zhengzhou Univ, Dept Endocrinol & Metab, Henan Prov Peoples Hosp, Zhengzhou 450003, Henan, Peoples R China
推荐引用方式
GB/T 7714		 Liu, Zhenyu,Liu, Jiangang,Yuan, Huijuan,et al. Identification of Cognitive Dysfunction in Patients with T2DM Using Whole Brain Functional Connectivity[J]. GENOMICS PROTEOMICS & BIOINFORMATICS,2019,17(4):441-452.
APA Liu, Zhenyu.,Liu, Jiangang.,Yuan, Huijuan.,Liu, Taiyuan.,Cui, Xingwei.,...&Tian, Jie.(2019).Identification of Cognitive Dysfunction in Patients with T2DM Using Whole Brain Functional Connectivity.GENOMICS PROTEOMICS & BIOINFORMATICS,17(4),441-452.
MLA Liu, Zhenyu,et al."Identification of Cognitive Dysfunction in Patients with T2DM Using Whole Brain Functional Connectivity".GENOMICS PROTEOMICS & BIOINFORMATICS 17.4(2019):441-452.

入库方式： OAI收割

来源：自动化研究所

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