Multimodal Imaging: Genetic and Environmental Effects in Neuropsychiatry

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In order to better understand how the genetic risk for schizophrenia operates at the cognitive, behavioral and neural systems level, our recent work under this project has focused on understanding the biological correlates of both polygenic illness risk and gene-by-environment interactions. Ongoing studies in these areas permit better understanding of heritable, trait-related abnormalities in schizophrenia, of the underlying molecular biology responsible for such abnormalities, and of strategies for resolving some of the illness heterogeneity that makes biological research so challenging. Schizophrenia is highly heritable but, like other psychiatric disorders, its genetic architecture is quite complex. The field has identified numerous genetic markers that are statistically associated with illness in large case-control genome-wide association studies but whose contributions to schizophrenia risk biology remain unclear. Considerable additional work is needed to translate these findings into a better understanding of the molecular pathways leading to system-level dysfunction in schizophrenia. This is exemplified by one of the first genes reaching genome-wide association level significance, ZNF804a, which has continued to be an important locus of schizophrenia risk, but it remains unknown how variation in this gene might confer schizophrenia risk. Following preclinical support for ZNF804a-mediated dopamine receptor regulation, we have employed dopamine receptor PET imaging in a large cohort of healthy volunteers genotyped for the ZNF804a risk locus and identified significant and specific associations between genotype and D2 dopamine receptor availability in the striatum, providing novel evidence that this gene has implications for the dopamine system in the living human brain (Hegarty et al., 2021). Current work employs various strategies beyond single-gene effects, including the use of polygenic scores. These scores, which summarize genetic associations across the genome with a given disorder or trait, are an emerging tool for investigations of broad genetic influences on illness and behavior. For instance, we have shown that in schizophrenia, a profile of polygenic scores separately derived for schizophrenia, ADHD, educational attainment, and cognitive ability predicts distinct trajectories of cognitive development prior to the onset of acute illness. In recent studies examining a set of ancient DNA sequence variants across the genome, we have found that cumulatively, these variants are associated with subtle differences in brain structure and function, including less striatal dopamine synthesis, that may be associated with diminished expression of schizophrenia phenotypes in addition to reduced illness risk and severity (Gregory and Berman, 2022; Gregory et al., 2021). Recent collaborative methodological experimentation has helped develop new data-driven ways of analyzing neuroimaging genetics questions, which will aid discovery of more complex gene-brain relationships despite the multidimensional nature of these data types (Ghosal et al., 2022). In conjunction with genetic factors underlying risk for schizophrenia, environmental influences have been identified as illness risk factors in epidemiological and twin studies, and delineating gene-environment interactions is likely crucial to better understanding the causes of schizophrenia. Recent research has highlighted two environmental variables that show association with schizophrenia: urbanicity and early life complications. For example, we have demonstrated that whether an individual was raised in an urban environment significantly modifies effects of dopamine-related genes on how the prefrontal cortex responds to working memory demands. We have further replicated this finding in two additional datasets and posit that urban upbringing may alter brain function in a way that meaningfully intersects with dopaminergic neurogenetic mechanisms. Other work suggests that the predictive strength of most strongly associated chromosomal location from the recent schizophrenia genome-wide association study is greatly amplified when there is a history of clinically significant obstetrical complications. These data suggest that traditional univariate approaches must be buttressed by gene-by-environment experimentation to more fully elaborate genetic risk architecture in schizophrenia.