Progress this past year in understanding how schizophrenia risk genetics operate at the cognitive and neural systems level has been manifold, with important advances in (1) identifying novel phenotypes that distinguish both people with schizophrenia and unaffected family members from unrelated healthy individuals and in (2) discovering associations between specific risk genes and schizophrenia-linked brain phenotypes. Ongoing studies in these two veins permit both better understanding of heritable, trait-related abnormalities in schizophrenia and the underlying molecular biology responsible for such abnormalities, respectively. With regard to novel phenotypes, we have developed and employed a new fMRI paradigm based on the Digit Symbol Substitution Test, a measure of processing speed that is particularly challenging for individuals with schizophrenia and has been forwarded as one of the most sensitive standard neurocognitive measurements distinguishing people with and without schizophrenia. This has allowed us to identify a pattern of under-activated prefrontal cortex that is seen in schizophrenia and in unaffected siblings. This potential endophenotype was replicated in a second sample, paving the way for future genetic association work aimed at understanding how DNA sequence variation translates to functional brain dynamics affected by illness. Similarly, in line with hypotheses of GABAergic disruption in schizophrenia primarily founded on post-mortem brain tissue investigations, we have shown that at least one measure of in vivo levels of GABA, a critical inhibitory neurotransmitter, measured in the dorsal anterior cingulate with MRS is reduced in both individuals with schizophrenia and their unaffected siblings. Moreover, this measure appears to be moderately heritable within families, possibly constituting an intermediate phenotype of modest effect size. This is in contrast to an important negative finding in which we confirmed an absence of MRS measured glutamate levels in the same brain region. Efforts to elaborate on these observations and, in the case of GABA, determine underlying genetic mechanisms are ongoing. In parallel, genetic work aimed at elucidating links between risk genes and risk-associated cognitive and neural signatures has been accelerating. This work offers the opportunity to provide biological validation to putative risk genes, thereby identifying the most promising causative molecular targets a critical step for advancing research on a polygenic, heterogeneous illness such as schizophrenia. Earlier work by our group was able to establish a coherent, latent structure within our extensive cognitive measurements, identifying not only six domain composite factors, but also a higher order factor reflecting general cognitive ability, also called g. Recently, we identified an exciting and novel association between this general cognitive composite and a genetic variant related to sodium channel biology that helps to explain the cognitive impairment in our sample of people with schizophrenia and in their unaffected siblings. We subsequently demonstrated the molecular functionality of this variant through analyses of gene transcript expression in post-mortem brain tissue. Then, by leveraging our fMRI assays of brain function, we were able to successfully tie this same variation in the SCN2A gene to the heritable intermediate phenotype first described by this group prefrontal inefficiency during the Nback task. SCN2A genotype effects have now been confirmed in 531 healthy individuals from 3 different sites and extended, showing with resting state fMRI that those with the cognitively advantaged allele may have greater interregional correspondence between two brain structures discussed above that support higher cognitive function: the dorsolateral prefrontal cortex and dorsal anterior cingulate. We have similarly executed an incisive investigation of NKCC1, a gene that is important in the establishment of GABA as an inhibitory neurotransmitter early in development, showing not only that variation in this gene can modestly increase risk for schizophrenia, but also that it modulates mRNA transcription and confers differential general cognitive function (g) and prefrontal efficiency during working memory, as measured by fMRI. Our collaborative work has been especially productive this year, including a notable discovery that a genetic locus previously associated with educational attainment, strongly and consistently predicted broad cognitive ability. Additionally, new findings are consistent with gene-gene interactions in particular interactions between genes for the dopamine D2 and serotonin 5-HT2A receptors affecting prefrontal function and biasing response to antipsychotic treatment. Innovative approaches to understanding gene-by-environment interactions are also underway, including studies of urban exposure during childhood, an epidemiological risk factor for schizophrenia. For instance, we have now been able to identify robust interactions between COMT genotype and urbanicity impacting prefrontal fMRI signal in two independent cohorts. These data mark a major step forward in characterizing the coalescence of genetic and environmental factors on systems-level brain function, and studies are underway to better define how these factors operate in the context of schizophrenia illness.
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