Brain volume in male patients with recent onset schizophrenia with and without cannabis use disorders.

BACKGROUND: Schizophrenia is highly comorbid with cannabis use disorders (CUDs), and this comorbidity is associated with an unfavourable course. Early onset or frequent cannabis use may influence brain structure. A key question is whether comorbid CUDs modulate brain morphology alterations associated with schizophrenia. METHODS: We used surface-based analysis to measure the brain volume, cortical thickness and cortical surface area of a priori-defined brain regions (hippocampus, amygdala, thalamus, caudate, putamen, orbitofrontal cortex, anterior cingulate cortex, insula, parahippocampus and fusiform gyrus) in male patients with schizophrenia or related disorders with and without comorbid CUDs and matched healthy controls. Associations between age at onset and frequency of cannabis use with regional grey matter volume were explored. RESULTS: We included 113 patients with (CUD, n = 80) and without (NCUD, n = 33) CUDs and 84 controls in our study. As expected, patients with schizophrenia (with or without a CUD) had smaller volumes of most brain regions (amygdala, putamen, insula, parahippocampus and fusiform gyrus) than healthy controls, and differences in cortical volume were mainly driven by cortical thinning. Compared with the NCUD group, the CUD group had a larger volume of the putamen, possibly driven by polysubstance use. No associations between age at onset and frequency of use with regional grey matter volumes were found. LIMITATIONS: We were unable to correct for possible confounding effects of smoking or antipsychotic medication. CONCLUSION: Patients with psychotic disorders and comorbid CUDs have larger putamen volumes than those without CUDs. Future studies should elaborate whether a large putamen represents a risk factor for the development of CUDs or whether (poly)substance use causes changes in putamen volume.

Relationship between working-memory network function and substance use: a 3-year longitudinal fMRI study in heavy cannabis users and controls.

Deficient executive functions play an important role in the development of addiction. Working-memory may therefore be a powerful predictor of the course of drug use, but chronic substance use may also impair working-memory. The aim of this 3-year longitudinal neuro-imaging study was to investigate the relationship between substance use (e.g. alcohol, cannabis, nicotine, illegal psychotropic drugs) and working-memory network function over time in heavy cannabis users and controls. Forty-nine participants performed an n-back working-memory task at baseline and at 3-year follow-up. At follow-up, there were 22 current heavy cannabis users, 4 abstinent heavy cannabis users and 23 non-cannabis-using controls. Tensor-independent component analysis (Tensor-ICA) was used to investigate individual differences in working-memory network functionality over time. Within the group of cannabis users, cannabis-related problems remained stable, whereas alcohol-related problems, nicotine dependence and illegal psychotropic substance use increased over time. At both measurements, behavioral performance and network functionality during the n-back task did not differ between heavy cannabis users and controls. Although n-back accuracy improved, working-memory network function remained stable over time. Within the group of cannabis users, working-memory network functionality was not associated with substance use. These results suggest that sustained moderate to heavy levels of cannabis, nicotine, alcohol and illegal psychotropic substance use do not change working-memory network functionality. Moreover, baseline network functionality did not predict cannabis use and related problems three years later, warranting longitudinal studies in more chronic or dependent cannabis users.

Grey Matter Changes Associated with Heavy Cannabis Use: A Longitudinal sMRI Study.

Cannabis is the most frequently used illicit drug worldwide. Cross-sectional neuroimaging studies suggest that chronic cannabis exposure and the development of cannabis use disorders may affect brain morphology. However, cross-sectional studies cannot make a conclusive distinction between cause and consequence and longitudinal neuroimaging studies are lacking. In this prospective study we investigate whether continued cannabis use and higher levels of cannabis exposure in young adults are associated with grey matter reductions. Heavy cannabis users (N = 20, age baseline M = 20.5, SD = 2.1) and non-cannabis using healthy controls (N = 22, age baseline M = 21.6, SD = 2.45) underwent a comprehensive psychological assessment and a T1- structural MRI scan at baseline and 3 years follow-up. Grey matter volumes (orbitofrontal cortex, anterior cingulate cortex, insula, striatum, thalamus, amygdala, hippocampus and cerebellum) were estimated using the software package SPM (VBM-8 module). Continued cannabis use did not have an effect on GM volume change at follow-up. Cross-sectional analyses at baseline and follow-up revealed consistent negative correlations between cannabis related problems and cannabis use (in grams) and regional GM volume of the left hippocampus, amygdala and superior temporal gyrus. These results suggests that small GM volumes in the medial temporal lobe are a risk factor for heavy cannabis use or that the effect of cannabis on GM reductions is limited to adolescence with no further damage of continued use after early adulthood. Long-term prospective studies starting in early adolescence are needed to reach final conclusions.

Structural MRI Differences between Patients with and without First Rank Symptoms: A Delusion?

OBJECTIVE: It has been suggested that specific psychotic symptom clusters may be explained by patterns of biological abnormalities. The presence of first rank symptoms (FRS) has been associated with cognitive abnormalities, e.g., deficits in self-monitoring or in the experience of agency, suggesting that a specific network of neural abnormalities might underlie FRS. Here, we investigate differences in cortical and subcortical brain volume between patients with and without FRS. METHODS: Three independent patient samples (referred to as A, B, and C) with different mean ages and in different illness stages were included, leading to a total of 348 patients within the schizophrenia-spectrum. All underwent magnetic resonance imaging of the brain. In addition, the presence of FRS was established using a diagnostic interview. Patients with (FRS+, A: n = 63, B: n = 129, and C: n = 96) and without FRS (FRS-, A: n = 35, B: n = 17, and C: n = 8) were compared on global and local cortical volumes as well as subcortical volumes, using a whole brain (cerebrum) approach. RESULTS: Nucleus accumbens volume was significantly smaller in FRS+ as compared with FRS- in sample A (p < 0.005). Furthermore, FRS+ showed a smaller volume of the pars-opercularis relative to FRS- in sample B (p < 0.001). No further significant differences were found in cortical and subcortical volumes between FRS+ and FRS- in either one of the three samples after correction for multiple comparison. CONCLUSION: Brain volume differences between patients with and without FRS are, when present, subtle, and not consistent between three independent samples. Brain abnormalities related to FRS may be too subtle to become visible through structural brain imaging.