| Literature DB >> 30716456 |
Mingrui Xia1, Tianmei Si2, Xiaoyi Sun1, Qing Ma1, Bangshan Liu3, Li Wang2, Jie Meng4, Miao Chang5, Xiaoqi Huang6, Ziqi Chen6, Yanqing Tang5, Ke Xu7, Qiyong Gong6, Fei Wang5, Jiang Qiu4, Peng Xie8, Lingjiang Li9, Yong He10.
Abstract
Resting-state functional MRI (R-fMRI) studies have demonstrated widespread alterations in brain function in patients with major depressive disorder (MDD). However, a clear and consistent conclusion regarding a repeatable pattern of MDD-relevant alterations is still limited due to the scarcity of large-sample, multisite datasets. Here, we address this issue by including a large R-fMRI dataset with 1434 participants (709 patients with MDD and 725 healthy controls) from five centers in China. Individual functional activity maps that represent very local to long-range connections are computed using the amplitude of low-frequency fluctuations, regional homogeneity and distance-related functional connectivity strength. The reproducibility analyses involve different statistical strategies, global signal regression, across-center consistency, clinical variables, and sample size. We observed significant hypoactivity in the orbitofrontal, sensorimotor, and visual cortices and hyperactivity in the frontoparietal cortices in MDD patients compared to the controls. These alterations are not affected by different statistical analysis strategies, global signal regression and medication status and are generally reproducible across centers. However, these between-group differences are partially influenced by the episode status and the age of disease onset in patients, and the brain-clinical variable relationship exhibits poor cross-center reproducibility. Bootstrap analyses reveal that at least 400 subjects in each group are required to replicate significant alterations (an extent threshold of P < .05 and a height threshold of P < .001) at 50% reproducibility. Together, these results highlight reproducible patterns of functional alterations in MDD and relevant influencing factors, which provides crucial guidance for future neuroimaging studies of this disorder.Entities:
Keywords: ALFF; Brain network; Connectome; Depression; Psychoradiology; ReHo; Reliability
Mesh:
Year: 2019 PMID: 30716456 DOI: 10.1016/j.neuroimage.2019.01.074
Source DB: PubMed Journal: Neuroimage ISSN: 1053-8119 Impact factor: 6.556