Dyslipidemia induced large-scale network connectivity abnormality facilitates cognitive decline in the Alzheimer's disease

被引:16
作者
Wang, Qing [1 ]
Zang, Feifei [1 ]
He, Cancan [1 ]
Zhang, Zhijun [1 ,2 ,3 ]
Xie, Chunming [1 ,2 ,3 ]
机构
[1] Southeast Univ, Affiliated ZhongDa Hosp, Sch Med, Dept Neurol, Nanjing 210009, Jiangsu, Peoples R China
[2] Southeast Univ, Affiliated ZhongDa Hosp, Inst Neuropsychiat, Nanjing 210009, Jiangsu, Peoples R China
[3] Southeast Univ, Key Lab Dev Genes & Human Dis, Nanjing 210009, Jiangsu, Peoples R China
基金
中国国家自然科学基金;
关键词
Alzheimer's disease; Lipid; Large-scale network; Canonical correlation analysis; FUNCTIONAL NETWORK; BRAIN CONNECTIVITY; ASSOCIATION; RISK; LIPIDS; CHOLESTEROL; BETA; LIPOPROTEINS; DEMENTIA; FAILURE;
D O I
10.1186/s12967-022-03786-w
中图分类号
R-3 [医学研究方法]; R3 [基础医学];
学科分类号
1001 ;
摘要
Background: Although lipid metabolite dysfunction contributes substantially to clinical signs and pathophysiology of Alzheimer's disease (AD), how dyslipidemia promoting neuropathological processes and brain functional impairment subsequently facilitates the progression of AD remains unclear. Methods: We combined large-scale brain resting-state networks (RSNs) approaches with canonical correlation analysis to explore the accumulating effects of lipid gene- and protein-centric levels on cerebrospinal fluid (CSF) biomarkers, dynamic trajectory of large-scale RSNs, and cognitive performance across entire AD spectrum. Support vector machine model was used to distinguish AD spectrum and pathway analysis was used to test the influences among these variables. Results: We found that the effects of accumulation of lipid-pathway genetic variants and lipoproteins were significantly correlated with CSF biomarkers levels and cognitive performance across the AD spectrum. Dynamic trajectory of large-scale RSNs represented a rebounding mode, which is characterized by a weakened network cohesive connector role and enhanced network incohesive provincial role following disease progression. Importantly, the fluctuating large-scale RSNs connectivity was significantly correlated with the summative effects of lipid-pathway genetic variants and lipoproteins, CSF biomarkers, and cognitive performance. Moreover, SVM model revealed that the lipid-associated twenty-two brain network connections represented higher capacity to classify AD spectrum. Pathway analysis further identified dyslipidemia directly influenced brain network reorganization or indirectly affected the CSF biomarkers and subsequently caused cognitive decline. Conclusions: Dyslipidemia exacerbated cognitive decline and increased the risk of AD via mediating large-scale brain networks integrity and promoting neuropathological processes. These findings reveal a role for lipid metabolism in AD pathogenesis and suggest lipid management as a potential therapeutic target for AD.
引用
收藏
页数:14
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