Schizophrenia is a highly heritable disorder that typically develops in early adult life. Structural imaging studies have indicated that patients with the illness, and to some extent their unaffected relatives, have subtle deficits in several brain regions, including prefrontal and temporal lobes. It is, however, not known how this inherited vulnerability leads to psychosis. This study used a covert verbal initiation fMRI task previously shown to elicit frontal and temporal activity (the Hayling sentence completion task) to examine this issue. A large (n = 69) number of young participants at high risk of developing schizophrenia for genetic reasons took part, together with a matched group of healthy controls (n = 21). At the time of investigation, none had any psychotic disorder, but on detailed interview some of the high-risk participants (n = 27) reported isolated psychotic symptoms. The study aimed to determine: (i) whether there were activation differences that occurred in all subjects with a genetic risk of schizophrenia (i.e. 'trait' effects); and (ii) whether there were activation differences that only occurred in those at high risk who had isolated psychotic symptoms ('state' effects). No activation differences were found in regions commonly reported to be abnormal in the established illness, namely the dorsolateral prefrontal cortex or in the temporal lobes, but group differences of apparent genetic cause were evident in medial prefrontal, thalamic and cerebellar regions. In addition, differences in activation in those with symptoms were found in the intraparietal sulcus. No significant differences in performance were found between the groups, and all subjects were antipsychotic naïve. These findings therefore suggest that vulnerability to schizophrenia may be inherited as a disruption in a fronto-thalamic-cerebellar network, and the earliest changes specific to the psychotic state may be related to hyperactivation in the parietal lobe.
Background. Our understanding of the complex relationship between schizophrenia symptomatology and etiological factors can be improved by studying brain-based correlates of schizophrenia. Research showed that impairments in value processing and executive functioning, which have been associated with prefrontal brain areas [particularly the medial orbitofrontal cortex (MOFC)], are linked to negative symptoms. Here we tested the hypothesis that MOFC thickness is associated with negative symptom severity. Results. Meta-analytical results showed that left, but not right, MOFC thickness was significantly associated with negative symptom severity (β std = −0.075; p = 0.019) after accounting for age, gender, and site. This effect remained significant (p = 0.036) in a model including overall illness severity. Covarying for duration of illness, age of onset, antipsychotic medication or handedness weakened the association of negative symptoms with left MOFC thickness. As part of a secondary analysis including 10 other prefrontal regions further associations in the left lateral orbitofrontal gyrus and pars opercularis emerged.Conclusions. Using an unusually large cohort and a meta-analytical approach, our findings point towards a link between prefrontal thinning and negative symptom severity in schizophrenia. This finding provides further insight into the relationship between structural brain abnormalities and negative symptoms in schizophrenia.
Major depressive disorder is a leading cause of disability and significant mortality, yet mechanistic understanding remains limited. Over the past decade evidence has accumulated from case-control studies that depressive illness is associated with blunted reward activation in the basal ganglia and other regions such as the medial prefrontal cortex. However it is unclear whether this finding can be replicated in a large number of subjects. The functional anatomy of the medial prefrontal cortex and basal ganglia has been extensively studied and the former has excitatory glutamatergic projections to the latter. Reduced effect of glutamatergic projections from the prefrontal cortex to the nucleus accumbens has been argued to underlie motivational disorders such as depression, and many prominent theories of major depressive disorder propose a role for abnormal cortico-limbic connectivity. However, it is unclear whether there is abnormal reward-linked effective connectivity between the medial prefrontal cortex and basal ganglia related to depression. While resting state connectivity abnormalities have been frequently reported in depression, it has not been possible to directly link these findings to reward-learning studies. Here, we tested two main hypotheses. First, mood symptoms are associated with blunted striatal reward prediction error signals in a large community-based sample of recovered and currently ill patients, similar to reports from a number of studies. Second, event-related directed medial prefrontal cortex to basal ganglia effective connectivity is abnormally increased or decreased related to the severity of mood symptoms. Using a Research Domain Criteria approach, data were acquired from a large community-based sample of subjects who participated in a probabilistic reward learning task during event-related functional MRI. Computational modelling of behaviour, model-free and model-based functional MRI, and effective connectivity dynamic causal modelling analyses were used to test hypotheses. Increased depressive symptom severity was related to decreased reward signals in areas which included the nucleus accumbens in 475 participants. Decreased reward-related effective connectivity from the medial prefrontal cortex to striatum was associated with increased depressive symptom severity in 165 participants. Decreased striatal activity may have been due to decreased cortical to striatal connectivity consistent with glutamatergic and cortical-limbic related theories of depression and resulted in reduced direct pathway basal ganglia output. Further study of basal ganglia pathophysiology is required to better understand these abnormalities in patients with depressive symptoms and syndromes.
BackgroundMagnetic resonance imaging (MRI) has demonstrated abnormalities of brain structure, particularly of the temporal lobes, in schizophrenia. These are thought to be neurodevelopmental in origin, but when they become evident is unknown.AimsTo determine iftemporal lobe volumes reduce during the development of symptoms of schizophrenia in initially well people at high riskofthis disorder.MethodA group of 66 people who had at least two first— or second-degree relatives with schizophrenia and a control group of 20 healthy people had a structural MRI scan ofthe whole brain which was repeated after approximately 2 years. Regions of interest, specifically the amygdala-hippocampus complex and the temporal lobes, were traced semi-automatically by three masked raters with good inter— and intrarater reliabilityResultsRegional brain volume changes over 2 years did notdiffer between high-risk and healthy participants. Within the high-risk group, the 19 people with psychotic symptoms (12 at first assessment) had a mean reduction of 2163 mm3 intherighttemporal lobe compared with 97 mm3 in the 47 without symptoms (P⩵0.02).ConclusionsOur findings suggest that people at high risk of schizophrenia with psychotic symptoms show reductions in temporal lobe volumes.
BackgroundMagnetic resonance imaging (MRI) has demonstrated abnormalities of brain structure, particularly of the temporal lobes, in schizophrenia. These are thought to be neurodevelopmental in origin, but when they become evident is unknown.
Our findings indicate that variation in the NETRIN1 signaling pathway may confer risk for major depressive disorder through effects on a number of white matter tracts.
The brain-age-gap estimate (brainAGE) quantifies the difference between chronological age and age predicted by applying machine-learning models to neuroimaging data and is considered a biomarker of brain health. Understanding sex differences in brainAGE is a significant step toward precision medicine. Global and local brainAGE (G-brainAGE and L-brainAGE, respectively) were computed by applying machine learning algorithms to brain structural magnetic resonance imaging data from 1113 healthy young adults (54.45% females; age range: 22-37 years) participating in the Human Connectome Project. Sex differences were determined in G-brainAGE and L-brainAGE. Random forest regression was used to determine sex-specific associations between G-brainAGE and non-imaging measures pertaining to sociodemographic characteristics and mental, physical, and cognitive functions. L-brainAGE showed sex-specific differences; in females, compared to males, L-brainAGE was higher in the cerebellum and brainstem and lower in the prefrontal cortex and insula. Although sex differences in G-brainAGE were minimal, associations between G-brainAGE and non-imaging measures differed between sexes with the exception of poor sleep quality, which was common to both. While univariate relationships were small, the most important predictor of higher G-brainAGE was selfidentification as non-white in males and systolic blood pressure in females. The results demonstrate the value of applying sex-specific analyses and machine learning methods to advance our understanding of sex-related differences in factors that influence the rate of brain aging and provide a foundation for targeted interventions.
Evidence supports the involvement of oxytocin in social behavior. The oxytocin receptor gene (OXTR) has been associated with differences in social brain function and risk for autism. Motivated by recent work, we investigated the effect of variation in the common functional rs2268498 T/C polymorphism in the promoter region of OXTR on neural responses to fear expressions. 46 healthy subjects were divided into genotype groups of C carriers (n = 32) and TT homozygous (n = 14) and neural activity was measured during the recognition of fear and neutral expressions. Results showed that during the recognition of fear expressions, the TT genotype group exhibited increased responding in the inferior occipital gyrus, considered important for face processing, compared to carriers of the C allele (P < 0.005; cluster corrected for whole brain), an effect not found for neutral faces. These results indicate the impact of this OXTR genetic variant on individual differences in social affective neural processing.
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