Complexin2 modulates working memory-related neural activity in patients with schizophrenia

The specific contribution of risk or candidate gene variants to the complex phenotype of schizophrenia is largely unknown. Studying the effects of such variants on brain function can provide insight into disease-associated mechanisms on a neural systems level. Previous studies found common variants in the complexin2 (CPLX2) gene to be highly associated with cognitive dysfunction in schizophrenia patients. Similarly, cognitive functioning was found to be impaired in Cplx2 gene-deficient mice if they were subjected to maternal deprivation or mild brain trauma during puberty. Here, we aimed to study seven common CPLX2 single-nucleotide polymorphisms (SNPs) and their neurogenetic risk mechanisms by investigating their relationship to a schizophrenia-related functional neuroimaging intermediate phenotype. We examined functional MRI and genotype data collected from 104 patients with DSM-IV-diagnosed schizophrenia and 122 healthy controls who participated in the Mind Clinical Imaging Consortium study of schizophrenia. Seven SNPs distributed over the whole CPLX2 gene were tested for association with working memory-elicited neural activity in a frontoparietal neural network. Three CPLX2 SNPs were significantly associated with increased neural activity in the dorsolateral prefrontal cortex and intraparietal sulcus in the schizophrenia sample, but showed no association in healthy controls. Since increased working memory-related neural activity in individuals with or at risk for schizophrenia has been interpreted as ‘neural inefficiency,’ these findings suggest that certain variants of CPLX2 may contribute to impaired brain function in schizophrenia, possibly combined with other deleterious genetic variants, adverse environmental events, or developmental insults.National Institutes of Health (U.S.) (Grant NIH/NCRR P41RR14075)United States. Dept. of Energy (Grant DE-FG02-99ER6276)Mind Research NetworkFunction BIRN (Grants U24RR021992-01 and NIH.NCRR MO1 RR025758-01)Brain & Behavior Research Foundation (Young Investigator Grant)Deutsche Forschungsgemeinschaft (Research Fellowship)Morphometry BIRN (Grant 1U24, RR021382A

The Impact of Genome-Wide Supported Schizophrenia Risk Variants in the Neurogranin Gene on Brain Structure and Function

The neural mechanisms underlying genetic risk for schizophrenia, a highly heritable psychiatric condition, are still under investigation. New schizophrenia risk genes discovered through genome-wide association studies (GWAS), such as neurogranin (NRGN), can be used to identify these mechanisms. In this study we examined the association of two common NRGN risk single nucleotide polymorphisms (SNPs) with functional and structural brain-based intermediate phenotypes for schizophrenia. We obtained structural, functional MRI and genotype data of 92 schizophrenia patients and 114 healthy volunteers from the multisite Mind Clinical Imaging Consortium study. Two schizophrenia-associated NRGN SNPs (rs12807809 and rs12541) were tested for association with working memory-elicited dorsolateral prefrontal cortex (DLPFC) activity and surface-wide cortical thickness. NRGN rs12541 risk allele homozygotes (TT) displayed increased working memory-related activity in several brain regions, including the left DLPFC, left insula, left somatosensory cortex and the cingulate cortex, when compared to non-risk allele carriers. NRGN rs12807809 non-risk allele (C) carriers showed reduced cortical gray matter thickness compared to risk allele homozygotes (TT) in an area comprising the right pericalcarine gyrus, the right cuneus, and the right lingual gyrus. Our study highlights the effects of schizophrenia risk variants in the NRGN gene on functional and structural brain-based intermediate phenotypes for schizophrenia. These results support recent GWAS findings and further implicate NRGN in the pathophysiology of schizophrenia by suggesting that genetic NRGN risk variants contribute to subtle changes in neural functioning and anatomy that can be quantified with neuroimaging methods.National Institutes of Health (U.S.) (NIH/NCRR P41RR14075)United States. Dept. of Energy (DE-FG02-99ER62764)Biomedical Informatics Research Network (Mind Research Network, Morphometry 1U24, RR021382A