Convergent Neuroimaging and Molecular Signatures in Mild Cognitive Impairment and Alzheimer’s Disease: A Data-Driven Meta-Analysis with N = 3,118
Xiaopeng Kang1,2 · Dawei Wang3 · Jiaji Lin4,5 · Hongxiang Yao6 · Kun Zhao7 · Chengyuan Song8 · Pindong Chen1,2 · Yida Qu1,2 · Hongwei Yang9 · Zengqiang Zhang10 · Bo Zhou11 · Tong Han12 · Zhengluan Liao13 · Yan Chen13 · Jie Lu9 · Chunshui Yu14 · Pan Wang15 · Xinqing Zhang16 · Ming Li17 · Xi Zhang11 · Tianzi Jiang1,2 · Yuying Zhou15 · Bing Liu1,2,18 · Ying Han16,19,20 · Yong Liu1,2,7 · The Alzheimer’s Disease Neuroimaging Initiative · The Multi-Center Alzheimer’s Disease Imaging (MCADI) Consortium1 School of Artifcial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China
2 Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
3 Department of Radiology, Qilu Hospital of Shandong University, Ji’nan 250063, China
4 Department of Neurology, the Second Afliated Hospital of Air Force Medical University, Xi’an 710032, China
5 Department of Radiology, Chinese PLA General Hospital, Beijing 100853, China
6 Department of Radiology, the Second Medical Centre, National Clinical Research Centre for Geriatric Diseases, Chinese PLA General Hospital, Beijing 100853, China
Abstract
The current study aimed to evaluate the susceptibility to regional brain atrophy and its biological mechanism in Alzheimer’s disease (AD). We conducted data-driven meta-analyses to combine 3,118 structural magnetic resonance images from three datasets to obtain robust atrophy patterns. Then we introduced a set of radiogenomic analyses to investigate the biological basis of the atrophy patterns in AD. Our results showed that the hippocampus and amygdala exhibit the most severe atrophy, followed by the temporal, frontal, and occipital lobes in mild cognitive impairment (MCI) and AD. The extent of atrophy in MCI was less severe than that in AD. A series of biological processes related to the glutamate signaling pathway, cellular stress response, and synapse structure and function were investigated through gene set enrichment analysis. Our study contributes to understanding the manifestations of atrophy and a deeper understanding of the pathophysiological processes that contribute to atrophy, providing new insight for further clinical research on AD.
Keywords
Alzheimer’s disease; Structural magnetic resonance imaging; Meta-analysis; Brain atrophy; Gene set enrichment analysis
