Translational Potential of Neuroimaging Genomic Analyses to Diagnosis and Treatment in Mental Disorders

Abstract

Imaging genomics focuses on characterizing genomic influence on the variation of neurobiological traits, holding promise for illuminating the pathogenesis, reforming the diagnostic system, and precision medicine of mental disorders. This paper aims to provide an overall picture of the current status of neuroimaging-genomic analyses in mental disorders, and how we can increase their translational potential into clinical practice. The review is organized around three perspectives: 1) toward reliability, generalizability, and interpretability, where we summarize the multivariate models and discuss the considerations and tradeoffs of using these methods and how reliable findings may be reached, to serve as ground for further delineation; 2) toward improved diagnosis, where we outline the advantages and challenges of constructing a dimensional transdiagnostic model and how imaging genomic analyses map into this framework to aid in deconstructing heterogeneity and achieving an optimal stratification of patients that better inform treatment planning; and 3) toward improved treatment. Here, we highlight recent efforts and progress in elucidating the functional annotations that bridge between genomic risk and neurobiological abnormalities, in detecting genomic predisposition and prodromal neurodevelopmental changes, as well as in identifying imaging genomic biomarkers for predicting treatment response. Providing an overview of the challenges and promises, this review hopefully motivates imaging genomic studies with multivariate, dimensional, and transdiagnostic designs for generalizable and interpretable findings that facilitate the development of personalized treatment.