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Clozapine is an atypical antipsychotic metabolized by CYP1A2, CYP2D6, and CYP2C19 enzymes. Among 66 adult schizophrenia patients treated with clozapine-based combination therapies, we explored the impact of genotype-predicted CYP1A2, CYP2D6, and CYP2C19 activity on dose-adjusted clozapine concentrations and symptom severity, with and without correction for inhibitors and inducers of these enzymes. Uncorrected activity scores were not associated with dose-adjusted clozapine concentrations or symptom severity. CYP1A2 and CYP2D6 activity scores corrected for known inducers (i.e., smoking) and inhibitors (e.g., concomitant medications) were associated with dose-adjusted clozapine levels and in the case of CYP1A2, symptom severity. However, smoking status and certain inhibitors of clozapine metabolism (i.e., esomeprazole) explained significantly more variance in dose-adjusted clozapine levels relative to corrected activity scores. These findings highlight the clinical importance of nongenetic factors (smoking, concomitant medications) and suggest that the added utility of CYP1A2, CYP2D6, and CYP2C19 activity scores to guide clozapine dosing is currently limited.

Cognitive functioning in affective psychosis and schizoaffective disorder is much less studied compared with schizophrenia. To quantitatively undertake a meta-analysis of the available data that directly compares cognitive functioning across schizophrenia, schizoaffective disorder and affective psychosis. Following a thorough literature review, 31 studies that compared the performances of people with schizophrenia (1979 participants) with that of those with affective psychosis or schizoaffective disorder (1314 participants) were included. To determine the effect of demographic and clinical confounders, meta-regression and subgroup analyses were conducted. In 6 of 12 cognitive domains, people with schizophrenia performed worse than people with schizoaffective disorder or affective psychosis. However, the between-group differences were small and the distribution of effect sizes showed substantial heterogeneity. The between-group differences were driven by a higher percentage of males, more severe negative symptoms and younger age at onset of illness in the schizophrenia samples. Neuropsychological data do not provide evidence for categorical differences between schizophrenia and other groups. However, a subgroup of individuals with schizophrenia who have more severe negative symptoms may be cognitively more impaired than those with affective psychosis/schizoaffective disorder.

The heterogeneity of schizophrenia has defied efforts to derive reproducible and definitive anatomical maps of structural brain changes associated with the disorder. We aimed to map deviations from normative ranges of brain structure for individual patients and evaluate whether the loci of individual deviations recapitulated group-average brain maps of schizophrenia pathology. For each of 48 white matter tracts and 68 cortical regions, normative percentiles of variation in fractional anisotropy (FA) and cortical thickness (CT) were established using diffusion-weighted and structural MRI from healthy adults (n = 195). Individuals with schizophrenia (n = 322) were classified as either within the normative range for healthy individuals of the same age and sex (5–95% percentiles), infra-normal (<5% percentile) or supra-normal (>95% percentile). Repeating this classification for each tract and region yielded a deviation map for each individual. Compared to the healthy comparison group, the schizophrenia group showed widespread reductions in FA and CT, involving virtually all white matter tracts and cortical regions. Paradoxically, however, no more than 15–20% of patients deviated from the normative range for any single tract or region. Furthermore, 79% of patients showed infra-normal deviations for at least one locus (healthy individuals: 59 ± 2%, p < 0.001). Thus, while infra-normal deviations were common among patients, their anatomical loci were highly inconsistent between individuals. Higher polygenic risk for schizophrenia associated with a greater number of regions with infra-normal deviations in CT (r = −0.17, p = 0.006). We conclude that anatomical loci of schizophrenia-related changes are highly heterogeneous across individuals to the extent that group-consensus pathological maps are not representative of most individual patients. Normative modeling can aid in parsing schizophrenia heterogeneity and guiding personalized interventions.

Iron has been increasingly implicated in the pathology of neurodegenerative diseases. In the past decade, development of the new magnetic resonance imaging technique, quantitative susceptibility mapping (QSM), has enabled for the more comprehensive investigation of iron distribution in the brain. The aim of this systematic review was to provide a synthesis of the findings from existing QSM studies in neurodegenerative diseases. We identified 80 records by searching MEDLINE, Embase, Scopus, and PsycInfo databases. The disorders investigated in these studies included Alzheimer's disease, Parkinson's disease, amyotrophic lateral sclerosis, Wilson's disease, Huntington's disease, Friedreich's ataxia, spinocerebellar ataxia, Fabry disease, myotonic dystrophy, pantothenate-kinase-associated neurodegeneration, and mitochondrial membrane protein-associated neurodegeneration. As a general pattern, QSM revealed increased magnetic susceptibility (suggestive of increased iron content) in the brain regions associated with the pathology of each disorder, such as the amygdala and caudate nucleus in Alzheimer's disease, the substantia nigra in Parkinson's disease, motor cortex in amyotrophic lateral sclerosis, basal ganglia in Huntington's disease, and cerebellar dentate nucleus in Friedreich's ataxia. Furthermore, the increased magnetic susceptibility correlated with disease duration and severity of clinical features in some disorders. Although the number of studies is still limited in most of the neurodegenerative diseases, the existing evidence suggests that QSM can be a promising tool in the investigation of neurodegeneration.

Changes in brain volume are a common finding in Magnetic Resonance Imaging (MRI) studies of people with psychosis and numerous longitudinal studies suggest that volume deficits progress with illness duration. However, a major unresolved question concerns whether these changes are driven by the underlying illness or represent iatrogenic effects of antipsychotic medication. In this study, 62 antipsychotic-naïve patients with first-episode psychosis (FEP) received either a second-generation antipsychotic (risperidone or paliperidone) or a placebo pill over a treatment period of 6 months. Both FEP groups received intensive psychosocial therapy. A healthy control group (n = 27) was also recruited. Structural MRI scans were obtained at baseline, 3 months and 12 months. Our primary aim was to differentiate illness-related brain volume changes from medication-related changes within the first 3 months of treatment. We secondarily investigated long-term effects at the 12-month timepoint. From baseline to 3 months, we observed a significant group x time interaction in the pallidum (p < 0.05 FWE-corrected), such that patients receiving antipsychotic medication showed increased volume, patients on placebo showed decreased volume, and healthy controls showed no change. Across the entire patient sample, a greater increase in pallidal grey matter volume over 3 months was associated with a greater reduction in symptom severity. Our findings indicate that psychotic illness and antipsychotic exposure exert distinct and spatially distributed effects on brain volume. Our results align with prior work in suggesting that the therapeutic efficacy of antipsychotic medications may be primarily mediated through their effects on the basal ganglia.

Brain structure reflects the influence of evolutionary processes that pit the costs of its anatomical wiring against the computational advantages conferred by its complexity. We show that cost-neutral ‘mutations’ of the human connectome almost inevitably degrade its complexity and disconnect high-strength connections to prefrontal network hubs. Conversely, restoring the peripheral location and strong connectivity of empirically observed hubs confers a wiring cost that the brain appears to minimize. Progressive cost-neutral randomization yields daughter networks that differ substantially from one another and results in a topologically unstable phenomenon consistent with a phase transition in complex systems. The fragility of hubs to disconnection shows a significant association with the acceleration of gray matter loss in schizophrenia. Together with effects on wiring cost, we suggest that fragile prefrontal hub connections and topological volatility act as evolutionary influences on brain networks whose optimal set point may be perturbed in neuropsychiatric disorders.

Cognitive control and working memory rely upon a common fronto-parietal network that includes the inferior frontal junction (IFJ), dorsolateral prefrontal cortex (dlPFC), pre-supplementary motor area/dorsal anterior cingulate cortex (pSMA/dACC), and intraparietal sulcus (IPS). This network is able to flexibly adapt its function in response to changing behavioral goals, mediating a wide range of cognitive demands. Here we apply dynamic causal modeling to functional magnetic resonance imaging data to characterize task-related alterations in the strength of network interactions across distinct cognitive processes. Evidence in favor of task-related connectivity dynamics was accrued across a very large space of possible network structures. Cognitive control and working memory demands were manipulated using a factorial combination of the multi-source interference task and a verbal 2-back working memory task, respectively. Both were found to alter the sensitivity of the IFJ to perceptual information, and to increase IFJ-to-pSMA/dACC connectivity. In contrast, increased connectivity from the pSMA/dACC to the IPS, as well as from the dlPFC to the IFJ, was uniquely driven by cognitive control demands; a task-induced negative influence of the dlPFC on the pSMA/dACC was specific to working memory demands. These results reflect a system of both shared and unique context-dependent dynamics within the fronto-parietal network. Mechanisms supporting cognitive engagement, response selection, and action evaluation may be shared across cognitive domains, while dynamic updating of task and context representations within this network are potentially specific to changing demands on cognitive control. •Cognitive control and working memory rely on a common frontoparietal brain network.•Dynamic causal modeling used to assess shared and differential connectivity•Shared: cognitive engagement in inferior frontal junction•Shared: altered lateral-to-medial interactions, guiding action selection/evaluation•CC: altered rostral-to-caudal connectivity, updating task/context representations

Whole-brain anatomical connectivity in living humans can be modeled as a network with diffusion-MRI and tractography. Network nodes are associated with distinct grey-matter regions, while white-matter fiber bundles serve as interconnecting network links. However, the lack of a gold standard for regional parcellation in brain MRI makes the definition of nodes arbitrary, meaning that network nodes are defined using templates employing either random or anatomical parcellation criteria. Consequently, the number of nodes included in networks studied by different authors has varied considerably, from less than 100 up to more than 104. Here, we systematically and quantitatively assess the behavior, structure and topological attributes of whole-brain anatomical networks over a wide range of nodal scales, a variety of grey-matter parcellations as well as different diffusion-MRI acquisition protocols. We show that simple binary decisions about network organization, such as whether small-worldness or scale-freeness is evident, are unaffected by spatial scale, and that the estimates of various organizational parameters (e.g. small-worldness, clustering, path length, and efficiency) are consistent across different parcellation scales at the same resolution (i.e. the same number of nodes). However, these parameters vary considerably as a function of spatial scale; for example small-worldness exhibited a difference of 95% between the widely-used automated anatomical labeling (AAL) template (∼100 nodes) and a 4000-node random parcellation (σAAL=1.9 vs. σ4000=53.6±2.2). These findings indicate that any comparison of network parameters across studies must be made with reference to the spatial scale of the nodal parcellation.

Abstract Introduction Clarifying the role of neuroinflammation in schizophrenia is subject to its detection in the living brain. Free-water (FW) imaging is an in vivo diffusion-weighted magnetic resonance imaging (dMRI) technique that measures water molecules freely diffusing in the brain and is hypothesized to detect inflammatory processes. Here, we aimed to establish a link between peripheral markers of inflammation and FW in brain white matter. Methods All data were obtained from the Australian Schizophrenia Research Bank (ASRB) across 5 Australian states and territories. We first tested for the presence of peripheral cytokine deregulation in schizophrenia, using a large sample (N = 1143) comprising the ASRB. We next determined the extent to which individual variation in 8 circulating pro-/anti-inflammatory cytokines related to FW in brain white matter, imaged in a subset (n = 308) of patients and controls. Results Patients with schizophrenia showed reduced interleukin-2 (IL-2) (t = −3.56, P = .0004) and IL-12(p70) (t = −2.84, P = .005) and increased IL-6 (t = 3.56, P = .0004), IL-8 (t = 3.8, P = .0002), and TNFα (t = 4.30, P < .0001). Higher proinflammatory signaling of IL-6 (t = 3.4, P = .0007) and TNFα (t = 2.7, P = .0007) was associated with higher FW levels in white matter. The reciprocal increases in serum cytokines and FW were spatially widespread in patients encompassing most major fibers; conversely, in controls, the relationship was confined to the anterior corpus callosum and thalamic radiations. No relationships were observed with alternative dMRI measures, including the fractional anisotropy and tissue-related FA. Conclusions We report widespread deregulation of cytokines in schizophrenia and identify inflammation as a putative mechanism underlying increases in brain FW levels.

While the biological substrates of brain and behavioural changes in persons with schizophrenia remain unclear, increasing evidence implicates that inflammation is involved. In schizophrenia, including first-episode psychosis and anti-psychotic naïve patients, there are numerous reports of increased peripheral inflammation, cognitive deficits and neuropathologies such as cortical thinning. Research defining the relationship between inflammation and schizophrenia symptomatology and neuropathology is needed. Therefore, we analysed the level of C-reactive protein (CRP), a peripheral inflammation marker, and its relationship with cognitive functioning in a cohort of 644 controls and 499 schizophrenia patients. In a subset of individuals who underwent MRI scanning (99 controls and 194 schizophrenia cases), we tested if serum CRP was associated with cortical thickness. CRP was significantly increased in schizophrenia patients compared to controls, co-varying for age, sex, overweight/obesity and diabetes (p < 0.006E-10). In schizophrenia, increased CRP was mildly associated with worse performance in attention, controlling for age, sex and education (R =− 0.15, p = 0.001). Further, increased CRP was associated with reduced cortical thickness in three regions related to attention: the caudal middle frontal, the pars opercularis and the posterior cingulate cortices, which remained significant after controlling for multiple comparisons (all p < 0.05). Together, these findings indicate that increased peripheral inflammation is associated with deficits in cognitive function and brain structure in schizophrenia, especially reduced attention and reduced cortical thickness in associated brain regions. Using CRP as a biomarker of peripheral inflammation in persons with schizophrenia may help to identify vulnerable patients and those that may benefit from adjunctive anti-inflammatory treatments.