Unveiling Promising Neuroimaging Biomarkers for Schizophrenia Through Clinical and Genetic Perspectives
Jing Guo1 · Changyi He1 · Huimiao Song1 · Huiwu Gao1 · Shi Yao2 · Shan‑Shan Dong1 · Tie‑Lin Yang11 Key Laboratory of Biomedical Information Engineering of Ministry of Education, Biomedical Informatics and Genomics Center, School of Life Science and Technology, Xi’an Jiaotong University, Xi’an 710049, China
2 Guangdong Key Laboratory of Age-Related Cardiac and Cerebral Diseases, Afliated Hospital of Guangdong Medical University, Zhanjiang 524000, China
Abstract
Schizophrenia is a complex and serious brain disorder. Neuroscientists have become increasingly interested in using magnetic resonance-based brain imaging-derived phenotypes (IDPs) to investigate the etiology of psychiatric disorders. IDPs capture valuable clinical advantages and hold biological significance in identifying brain abnormalities. In this review, we aim to discuss current and prospective approaches to identify potential biomarkers for schizophrenia using clinical multimodal neuroimaging and imaging genetics. We first described IDPs through their phenotypic classification and neuroimaging genomics. Secondly, we discussed the applications of multimodal neuroimaging by clinical evidence in observational studies and randomized controlled trials. Thirdly, considering the genetic evidence of IDPs, we discussed how can utilize neuroimaging data as an intermediate phenotype to make association inferences by polygenic risk scores and Mendelian randomization. Finally, we discussed machine learning as an optimum approach for validating biomarkers. Together, future research efforts focused on neuroimaging biomarkers aim to enhance our understanding of schizophrenia.
Keywords
Schizophrenia; Biomarkers; Brain imagingderived phenotypes; Multimodal neuroimaging; Imaging genomics
