In this review, Tam et al. (pages 1005–1012) discuss the recent progress in the detection and interpretation of copy number variations in schizophrenia. These previously unknown deletions and duplications in the genome of schizophrenia patients have begun to provide insight into the underlying susceptibility genetic factors, biological pathways and genetic architecture related to schizophrenia, and may continue to reveal information about other psychiatric disorders.
Wessman et al. (pages 990–996) analyzed the role of three genes (DTNBP1, DISC1, and NRG1) in a cluster of individuals from Finnish schizophrenia families using extensive clinical and neuropsychological data. They found that DTNBP1 is associated with a form of schizophrenia with prominent negative symptoms, generalized cognitive impairment, and few mood symptoms, while DISC1 is associated with a broader phenotype. Such differences could explain why, despite expensive studies, results on the role of these candidate genes in schizophrenia remain inconclusive.
Using genetically identical mice, Alter et al. (pages 1061–1066) report that fathers contribute to variability in offspring behavior even when they are not present for rearing. This model provides a potentially useful tool for the examination of mechanisms underlying non-genetic paternal inheritance thought to play a role in the development of mental disorders such as autism and schizophrenia.
Roussos et al. (pages 997–1004) evaluated the effects of a catechol-O-methyltransferase (COMT) polymorphism on prepulse inhibition and working memory in healthy adults who received placebo or tolcapone, a drug that increases dopamine levels in the prefrontal cortex by blocking the activity of COMT. The individuals with the higher activity variant of COMT, associated with poorer performance, improved with tolcapone. These data suggest that cognitive impairments associated with reduced resting prefrontal cortex dopamine levels, as may be associated with schizophrenia, might be treated by COMT inhibition.
Influence of Antipsychotic Use on Inflammatory Markers
Using data from the CATIE trial, a large, multicenter, comparative effectiveness study sponsored by the National Institute of Mental Health, Meyer et al. (pages 1013–1022) examined how changes in antipsychotic medication influence measures of inflammation. Their results confirm that antipsychotics with known metabolic risks also have negative effects on measures of inflammation, while more metabolically-neutral antipsychotics do not worsen these measures. Because inflammation contributes to many disease processes, these findings raise additional concerns about some of the second generation antipsychotic medications.
Predicting Psychosis via Cognitive Status
Riecher-Rössler et al. (pages 1023–1030) aimed to improve the prediction of transition to psychosis in individuals who are at significantly increased risk for this transition. The best predictors of transition over the seven year follow-up period were selected attenuated psychotic symptoms (suspiciousness), negative symptoms (anhedonia/asociality), and cognitive deficits (reduced speed of information processing). Overall predictive accuracy was 80.9% with a sensitivity of 83.3% and a specificity of 79.3%. The findings indicate that follow-up of at-risk individuals should exceed twelve months, and greater weight given to certain early symptoms and neurocognitive tests.
Metamemory Not Impaired in Schizophrenia
Bacon and Izaute (pages 1031–1037) explored the processes underlying patients' reflections on their own memory using theoretical and experimental models of metamemory, defined as the subjective awareness of one's own memory capacity. They observed that, in spite of their memory impairments, schizophrenia patients were as able as comparison subjects to rely on the products of memory retrieval in order to accurately monitor their awareness about what they do or do not know in an episodic memory paradigm.
Structural Abnormalities in Schizophrenia
Using structural neuroimaging in rats, Piontkewitz et al. (pages 1038–1046) show that in utero exposure to maternal infection during pregnancy, a well documented risk factor for schizophrenia, leads to the emergence in the offspring of hallmark structural abnormalities associated with schizophrenia, namely, enlarged ventricles and smaller hippocampus in adulthood. This neuroanatomical deterioration as well as its accompanying schizophrenia-like behavioral abnormalities was prevented in rats treated with clozapine during the asymptomatic period of adolescence.
Adolescent patients with psychosis have abnormalities in brain structure. Janssen et al. (pages 1047–1054) report that, in this population, cortical thickness was decreased in frontal and temporal regions compared to healthy controls.
Using novel brain mapping and machine-learning-based classification techniques, Sun et al. (pages 1055–1060) provide structural imaging evidence that psychotic patients present distinct patterns of cortical gray matter changes that can be discriminated from the normal pattern at an early stage of illness. The result suggests that machine-learning-based analysis techniques can potentially aid the search of neuroanatomic biomarkers for diagnosing psychotic disorders.
Some connectivity theories of schizophrenia suggest that the superior cerebellar penduncles might be the most affected region of the cerebellum. Using diffusion tensor imaging tractography, Kanaan et al. (pages 1067–1069) found that although the structural connectivity was impaired in the cerebellum of patients with schizophrenia, there were no tract-specific differences compared to matched healthy controls.
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