A variety of neuroimaging approaches have been used to evaluate potential neural substrates of schizophrenia (Kahn et al., 2015). However, with the exception of offspring and sibling-based studies (Chung and Cannon, 2015), it has been difficult to disarticulate whether such associations may be a consequence of medication (ubiquitous in most samples) or disorder expression as opposed to a marker of risk (Tost et al., 2010). SCZ-PRS can be leveraged to probe whether such neural metrics, or perhaps even novel ones (masked for example by medication usage), may be associated with genetic liability to schizophrenia within healthy populations unexposed to antipsychotic medication or disease course. Most commonly studied in this context are metrics of brain structure (e.g., cortical thickness, cortical gyrification, and gray matter volume), which have produced mixed evidence that increased schizophrenia genomic liability may be associated with reduced cortical thickness and volume (French et al., 2015, Van der Auwera et al., 2017). Other studies have begun to link SCZ PRS to functional imaging phenotypes such as reward- and working memory-related brain function; however results thus far have been mixed
