Interaction between catechol-O-methyltransferase (COMT) Val158Met genotype and genetic vulnerability to schizophrenia during explicit processing of aversive facial stimuli.

BACKGROUND: Emotion dysregulation is a key feature of schizophrenia, a brain disorder strongly associated with genetic risk and aberrant dopamine signalling. Dopamine is inactivated by catechol-O-methyltransferase (COMT), whose gene contains a functional polymorphism (COMT Val158Met) associated with differential activity of the enzyme and with brain physiology of emotion processing. The aim of the present study was to investigate whether genetic risk for schizophrenia and COMT Val158Met genotype interact on brain activity during implicit and explicit emotion processing. METHOD: A total of 25 patients with schizophrenia, 23 healthy siblings of patients and 24 comparison subjects genotyped for COMT Val158Met underwent functional magnetic resonance imaging during implicit and explicit processing of facial stimuli with negative emotional valence. RESULTS: We found a main effect of diagnosis in the right amygdala, with decreased activity in patients and siblings compared with control subjects. Furthermore, a genotype × diagnosis interaction was found in the left middle frontal gyrus, such that the effect of genetic risk for schizophrenia was evident in the context of the Val/Val genotype only, i.e. the phenotype of reduced activity was present especially in Val/Val patients and siblings. Finally, a complete inversion of the COMT effect between patients and healthy subjects was found in the left striatum during explicit processing. CONCLUSIONS: Overall, these results suggest complex interactions between genetically determined dopamine signalling and risk for schizophrenia on brain activity in the prefrontal cortex during emotion processing. On the other hand, the effects in the striatum may represent state-related epiphenomena of the disorder itself.

Evidence that hippocampal-parahippocampal dysfunction is related to genetic risk for schizophrenia.

BACKGROUND: Abnormalities in hippocampal-parahippocampal (H-PH) function are prominent features of schizophrenia and have been associated with deficits in episodic memory. However, it remains unclear whether these abnormalities represent a phenotype related to genetic risk for schizophrenia or whether they are related to disease state. METHOD: We investigated H-PH-mediated behavior and physiology, using blood oxygenation level-dependent functional magnetic resonance imaging (BOLD fMRI), during episodic memory in a sample of patients with schizophrenia, clinically unaffected siblings and healthy subjects. RESULTS: Patients with schizophrenia and unaffected siblings displayed abnormalities in episodic memory performance. During an fMRI memory encoding task, both patients and siblings demonstrated a similar pattern of reduced H-PH engagement compared with healthy subjects. CONCLUSIONS: Our findings suggest that the pathophysiological mechanism underlying the inability of patients with schizophrenia to properly engage the H-PH during episodic memory is related to genetic risk for the disorder. Therefore, H-PH dysfunction can be assumed as a schizophrenia susceptibility-related phenotype.

Catechol-O-methyltransferase Val(158)Met association with parahippocampal physiology during memory encoding in schizophrenia.

BACKGROUND: Catechol-O-methyltransferase (COMT) Val158Met has been associated with activity of the mesial temporal lobe during episodic memory and it may weakly increase risk for schizophrenia. However, how this variant affects parahippocampal and hippocampal physiology when dopamine transmission is perturbed is unclear. The aim of the present study was to compare the effects of the COMT Val158Met genotype on parahippocampal and hippocampal physiology during encoding of recognition memory in patients with schizophrenia and in healthy subjects. METHOD: Using blood oxygen level-dependent (BOLD) functional magnetic resonance imaging (fMRI), we studied 28 patients with schizophrenia and 33 healthy subjects matched for a series of sociodemographic and genetic variables while they performed a recognition memory task. RESULTS: We found that healthy subjects had greater parahippocampal and hippocampal activity during memory encoding compared to patients with schizophrenia. We also found different activity of the parahippocampal region between healthy subjects and patients with schizophrenia as a function of the COMT genotype, in that the predicted COMT Met allele dose effect had an opposite direction in controls and patients. CONCLUSIONS: Our results demonstrate a COMT Val158Met genotype by diagnosis interaction in parahippocampal activity during memory encoding and may suggest that modulation of dopamine signaling interacts with other disease-related processes in determining the phenotype of parahippocampal physiology in schizophrenia.

DRD2 co-expression network and a related polygenic index predict imaging, behavioral and clinical phenotypes linked to schizophrenia.

Genetic risk for schizophrenia (SCZ) is determined by many genetic loci whose compound biological effects are difficult to determine. We hypothesized that co-expression pathways of SCZ risk genes are associated with system-level brain function and clinical phenotypes of SCZ. We examined genetic variants related to the dopamine D2 receptor gene DRD2 co-expression pathway and associated them with working memory (WM) behavior, the related brain activity and treatment response. Using two independent post-mortem prefrontal messenger RNA (mRNA) data sets (total N=249), we identified a DRD2 co-expression pathway enriched for SCZ risk genes. Next, we identified non-coding single-nucleotide polymorphisms (SNPs) associated with co-expression of this pathway. These SNPs were associated with regulatory genetic loci in the dorsolateral prefrontal cortex (P<0.05). We summarized their compound effect on co-expression into a Polygenic Co-expression Index (PCI), which predicted DRD2 pathway co-expression in both mRNA data sets (all P<0.05). We associated the PCI with brain activity during WM performance in two independent samples of healthy individuals (total N=368) and 29 patients with SCZ who performed the n-back task. Greater predicted DRD2 pathway prefrontal co-expression was associated with greater prefrontal activity and longer WM reaction times (all corrected P<0.05), thus indicating inefficient WM processing. Blind prediction of treatment response to antipsychotics in two independent samples of patients with SCZ suggested better clinical course of patientswith greater PCI (total N=87; P<0.05). The findings on this DRD2 co-expression pathway are a proof of concept that gene co-expression can parse SCZ risk genes into biological pathways associated with intermediate phenotypes as well as with clinically meaningful information.