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.

People with schizophrenia and related psychotic disorders show abnormalities in several organ systems in addition to the central nervous system (CNS); and this contributes to excess mortality. However, it is unclear how strong the evidence is for alterations across multiple non-CNS systems at the onset of psychosis, how the alterations in non-CNS systems compare to findings in the CNS, or how they relate to symptoms. Here, we consider these questions, and suggest potential models to account for findings.First, we conduct a systematic meta-review to summarize effect sizes for both CNS (focusing on brain structural, neurophysiological, and neurochemical parameters) and non-CNS dysfunction (focusing on immune, cardiometabolic, and hypothalamic-pituitary-adrenal (HPA) systems) in first episode psychosis (FEP) to determine summary effect sizes for each organ system individually. To achieve this, Pubmed was systematically searched from 1990 to May 2017 for meta-analyses focusing on these parameters. Case control data was extracted for 165 studies making up these meta-analyses, comprising a total sample size of 13,440. Random effects meta-analyses were re-run and effect size magnitudes calculated for the following: immune parameters (IL-1β, sIL2R, IL-6, TNFα, TGFβ, CRP, and total lymphocyte count), effect size range for immune parameters: g = 0.61-1.62; summary effect size for immune alterations: g = 1.19 (95% CI:0.82-1.56); cardiometabolic parameters (fasting glucose, glucose following the oral glucose tolerance test, fasting insulin, insulin resistance, triglycerides, total cholesterol, and LDL cholesterol), effect size range for cardiometabolic parameters: g = 0.14-0.61, summary effect size for cardiometabolic alterations: g = 0.23 (95% CI: 0.15-0.31); HPA parameters (cortisol awakening response and prolactin), effect size range for HPA parameters: g = 0.62-0.74; summary effect size for HPA parameters: g = 0.68 (95% CI: 0.32-1.04); brain structural (total brain, total gray matter, total CSF, ventricular, thalamic, hippocampal, and caudate nucleus volumes), effect size range for brain structural alterations: g = 0.26-0.58, summary effect size for brain structural alterations: g = 0.40 (95% CI: 0.33-0.47); neurophysiological alterations (auditory P300 amplitude and duration deviant mismatch negativity), effect size range for neurophysiological alterations: g = 0.77-0.83, summary effect size for neurophysiological alterations: g = 0.80 (95% CI: 0.64-0.96); neurochemical alterations (N-acetyl aspartate concentrations within frontal lobe, temporal lobe, and thalamus), effect size range for neurochemical alterations: 0.35-0.50, summary effect size for neurochemical alterations: g = 0.43 (95% CI: 0.26-0.60). We then grouped the non-CNS organ systems together to give an effect size for overall non-CNS alterations (g = 0.58 (95% CI: 0.44-0.72)) and grouped CNS alterations together to give an effect size for overall CNS as well (g = 0.50 (95%CI: 0.44-0.56)). The robustness of data for these non-CNS and CNS parameters was asses...

Previous voxel-based morphometry studies of patients with primary blepharospasm documented gray matter volumetric differences of the striatum, cerebellum, thalamus, and parietal lobe areas. However, these results were inconsistent across studies, which recruited relatively small samples and did not always provide detailed clinical information on patients with blepharospasm. The objective of this study was to analyze whole-brain gray matter volume in a larger sample of patients with blepharospasm and to expand on previous works by evaluating whether clinical features of blepharospasm correlate to whole-brain gray matter changes. Voxel-based morphometry was performed on 25 patients with primary adult-onset blepharospasm and 24 healthy subjects (controls) matched for age, sex, and handedness. Clinical data were collected through a standardized interview. Severity of blepharospasm was measured using the Jankovic Rating Scale. Patients with blepharospasm had greater gray matter volume than controls in the right middle frontal gyrus, whereas patients with blepharospasm had smaller gray matter volume than controls in the left postcentral gyrus and left superior temporal gyrus. Spearman correlation analysis with Bonferroni correction failed to show significant correlations between gray matter volume and the explored clinical variables, comprising age at onset, disease duration, blepharospasm severity, presence of an effective geste antagoniste, and dose and duration of botulinum toxin treatment. Patients with blepharospasm exhibited gray matter volume differences exclusively in cortical regions highly relevant to sensory processing and cognitive modulation of motor behavior. Gray matter changes in the primary sensory cortex may represent a common trait of primary dystonias, including blepharospasm.

ObjectiveTreatment resistance is a challenge for the management of schizophrenia. It is not always clear whether inadequate response is secondary to medication ineffectiveness, as opposed to medication underexposure due to non-adherence or pharmacokinetic factors. We investigated the prevalence of subtherapeutic antipsychotic plasma levels in patients identified as treatment-resistant by their treating clinician.MethodBetween January 2012 and April 2017, antipsychotic plasma levels were measured in 99 individuals provisionally diagnosed with treatment-resistant schizophrenia by their treating clinicians, but not prescribed clozapine. Patients were followed up to determine whether they were subsequently admitted to hospital.ResultsThirty-five per cent of plasma levels were subtherapeutic, and of these, 34% were undetectable. Black ethnicity (P = 0.006) and lower dose (P < 0.001) were significantly associated with subtherapeutic/undetectable plasma levels. Individuals with subtherapeutic/undetectable levels were significantly more likely to be admitted to hospital (P = 0.02).ConclusionA significant proportion of patients considered treatment-resistant have subtherapeutic antipsychotic plasma levels, and this is associated with subsequent admission. The presence of subtherapeutic plasma levels may suggest a need to address adherence or pharmacokinetic factors as opposed to commencing clozapine treatment. While antipsychotic levels are not recommended for the routine adjustment of dosing, they may assist with the assessment of potential treatment resistance in schizophrenia.