J Psychiatry Neurosci 2018;43(2):131-142
Xin Gao, MS*; Wenjing Zhang, PhD*; Li Yao, PhD; Yuan Xiao, PhD; Lu Liu, MS; Jieke Liu, PhD; Siyi Li, MS; Bo Tao, MS; Chandan Shah, MS; Qiyong Gong, MD, PhD; John A. Sweeney, PhD; Su Lui, MD, PhD*
Background: Neuroimaging studies have shown both structural and functional abnormalities in patients with schizophrenia. Recently, studies have begun to explore the association between structural and functional grey matter abnormalities. By conducting a meta-analysis on morphometric and functional imaging studies of grey matter alterations in drug-free patients, the present study aims to examine the degree of overlap between brain regions with anatomic and functional changes in patients with schizophrenia.
Methods: We performed a systematic search of PubMed, Embase, Web of Science and the Cochrane Library to identify relevant publications. A multimodal analysis was then conducted using Seed-based d Mapping software. Exploratory analyses included jackknife, subgroup and meta-regression analyses.
Results: We included 15 structural MRI studies comprising 486 drug-free patients and 485 healthy controls, and 16 functional MRI studies comprising 403 drug-free patients and 428 controls in our meta-analysis. Drug-free patients were examined to reduce pharmacological effects on the imaging data. Multimodal analysis showed considerable overlap between anatomic and functional changes, mainly in frontotemporal regions, bilateral medial posterior cingulate/paracingulate gyrus, bilateral insula, basal ganglia and left cerebellum. There were also brain regions showing only anatomic changes in the right superior frontal gyrus, left supramarginal gyrus, right lingual gyrus and functional alternations involving the right angular gyrus.
Limitations: The methodological aspects, patient characteristics and clinical variables of the included studies were heterogeneous, and we cannot exclude medication effects.
Conclusion: The present study showed overlapping anatomic and functional brain abnormalities mainly in the default mode (DMN) and auditory networks (AN) in drug-free patients with schizophrenia. However, the pattern of changes differed in these networks. Decreased grey matter was associated with decreased activation within the DMN, whereas it was associated with increased activation within the AN. These discrete patterns suggest different pathophysiological changes impacting structural and functional associations within different neural networks in patients with schizophrenia.
*These authors contributed equally to this work.
Submitted Nov. 9, 2016; Revised Aug. 29, 2017; Accepted Sept. 9, 2017; Online first Dec. 5, 2017
Acknowledgements: This research was partially supported by the National Natural Science Foundation of China (Grant Nos. 81371527, 81671664, 81621003), Program for Changjiang Scholars and Innovative Research Team (PCSIRT, Grant No. IRT1272), University of China.
Affiliations: From the Department of Radiology, Second Affiliated Hospital of Wenzhou Medical University, Wenzhou, China (Gao, Lui); the Department of Radiology, the Centre for Medical Imaging, West China Hospital of Sichuan University, Chengdu, Sichuan, China (Gao, Zhang, Yao, Xiao, Liu, Li, Tao, Shah, Gong, Lui); and the Department of Psychiatry, University of Texas Southwestern, Dallas, Tex, USA (Sweeney).
Competing interests: None declared.
Contributors: Q. Gong and S. Lui designed the study. X. Gao, L. Yao, L. Liu, J. Liu, S. Li and B. Tao acquired the data, which all authors analyzed. X. Gao, W. Zhang and S. Lui wrote the article which all authors reviewed. All authors approved the final version to be published and can certify that no other individuals not listed as authors have made substantial contributions to the paper.
Correspondence to: S. Lui, Radiology Department, the Second Affiliated Hospital and Yuying Children’s Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, China; Department of Radiology, the Center for Medical Imaging, West China Hospital of Sichuan University, Chengdu, Sichuan, China, 610041; firstname.lastname@example.org