Johannes Rentzsch

Brain-derived neurotrophic factor serum concentrations are increased in drug-naïve schizophrenic patients with chronic cannabis abuse and multiple substance abuse

Neurotrophins such as nerve growth factor (NGF) and brain-derived neurotrophic factor (BDNF) are critically implicated in development and maintenance of function of neurons. Neurodevelopment is reported to be impaired in schizophrenia and vulnerable schizophrenic brains may be more sensitive to toxic influences. Thus, cannabis as a neurotoxin, may be more harmful to schizophrenic brains than to non-schizophrenic brains when used chronically. And neurotoxic events may promote disease-onset and lead to exaggerated release of neurotrophins. We investigated 157 drug-naive first-episode schizophrenic patients and found significantly elevated BDNF serum concentrations (by up to 34%) in patients with chronic cannabis abuse (n = 35, p < 0.001) or multiple substance abuse (n = 20, p < 0.001) prior to disease onset. Drug-naive schizophrenic patients without cannabis consumption showed similar results to normal controls and cannabis controls without schizophrenia. Thus, raised BDNF serum levels are not related to schizophrenia and/or substance abuse itself but may reflect a cannabis-related idiosyncratic damage of the schizophrenic brain. In line with this hypothesis, disease onset was 5.2 years earlier in the cannabis-consuming group (p = 0.0111).

Effects of acute oral Δ9-tetrahydrocannabinol and standardized cannabis extract on the auditory P300 event-related potential in healthy volunteers

Reduced amplitudes of auditory evoked P300 are a robust finding in schizophrenic patients, indicating deficient attentional resource allocation and active working memory. Delta9-Tetrahydrocannabinol (Delta9-THC), the main active constituent of Cannabis sativa, has been known to acutely impair cognitive abilities in several domains, particularly in memory and attention. Given the psychotic-like effects of Delta9-THC, a cannabinoid hypothesis of schizophrenia has been proposed. This prospective, double-blind, placebo-controlled cross-over study investigated the acute effects of cannabinoids on P300 amplitude in 20 healthy volunteers (age 28.2+/-3.1 years, 10 male) by comparing Delta9-THC and standardized cannabis extract containing Delta9-THC and cannabidiol (CBD). P300 waves were recorded during a choice reaction task. As expected, Delta9-THC revealed a significant reduction of P300 amplitude at midline frontal, central, and parietal electrodes. CBD has been known to abolish many of the psychotropic effects of Delta9-THC, but, unexpectedly, failed to demonstrate a reversal of Delta9-THC-induced P300 reduction. Moreover, there were no correlations between cannabinoid plasma concentrations and P300 parameters. These data suggest that Delta(9)-THC may lead to acute impairment of attentional functioning and working memory. It can be speculated whether the lack of effect of CBD may be due to an insufficient dose used or to an involvement of neurotransmitter systems in P300 generation which are not influenced by CBD.

Differential impact of heavy cannabis use on sensory gating in schizophrenic patients and otherwise healthy controls

Cannabis abuse may precipitate the onset of schizophrenia and a dysfunction of the endocannabinoid system may be involved in the pathology of schizophrenia. Nevertheless, only few studies have addressed the neurobiological consequences of cannabis abuse for the development and course of schizophrenia. We measured the long-term effect of chronic cannabis abuse on the inhibitory function of the brain by the auditory P50 sensory gating in schizophrenic (n=15) and otherwise healthy chronic cannabis abusers (i.e. cannabis controls; n=11) and compared it to that of schizophrenic patients (n=12) and healthy controls (n=18) without cannabis or other drug abuse. All study subjects had to be abstinent from cannabis for at least 28 days. The main finding of our study was a P50 sensory gating deficit in cannabis controls that was correlated with the number of years with daily consumption (r=0.81; p=0.003). In contrast, we found no differences in P50 sensory gating between schizophrenic cannabis-abusers and non-abusers or healthy controls and no correlation with the number of years with daily consumption in those groups. To our knowledge this is the first study comparing the influence of chronic cannabis abuse in schizophrenic and otherwise healthy abusers on the inhibitory function of the brain. Our data provide some evidence that chronic cannabis abuse may affect sensory cortical circuits even after prolonged abstinence and they point to a possible differential effect in schizophrenic and otherwise healthy users.

Differential effects of chronic cannabis use on preattentional cognitive functioning in abstinent schizophrenic patients and healthy subjects

INTRODUCTION A number of studies indicate a higher risk for psychosis as well as for neurocognitive deficits in healthy cannabis users. However, little is known about the impact of cannabis use on outcome in schizophrenia. In fact, there is growing evidence that cannabis-using schizophrenic patients may show preserved or even better neurocognitive performance compared to schizophrenic non-users. METHODS We measured mismatch negativity (MMN) to investigate preattentional neurocognitive functioning in long-term abstinent chronic cannabis users with (SZCA n=27) and without schizophrenia (COCA n=32) compared to schizophrenic patients (SZ n=26) and healthy controls (CO n=34) without any chronic drug use. RESULTS Healthy cannabis users showed reduced frontal MMN compared to controls (p=0.036). In contrast, cannabis-using schizophrenic patients showed increased frontal MMN compared to schizophrenic patients without cannabis use (p=0.038). Comparing non-cannabis users, schizophrenic patients showed reduced frontal MMN (p=0.001). No significant differences were found between CO and SZCA (p=0.27), and COCA and SZCA (p=0.50). CONCLUSION Results suggest that chronic cannabis use may have different effects on preattentional neurocognitive functioning in schizophrenic patients when compared to healthy subjects. This may be related to preexisting differences in the endocannabinoid system between schizophrenic patients and healthy subjects. However, due to the naturalistic design of the study, the results must be interpreted with caution.

Adequate antipsychotic treatment normalizes serum nerve growth factor concentrations in schizophrenia with and without cannabis or additional substance abuse

Neurotrophins such as nerve growth factor (NGF) and brain-derived neurotrophic factor (BDNF) are important for the development and maintenance of neuron function. Neurodevelopment is thought to be impaired in schizophrenia, and vulnerable schizophrenic brains may be more sensitive to toxic influences. Thus, cannabis as a neurotoxin (and other substances) may be more harmful to schizophrenic brains than to non-schizophrenic brains, when used chronically. In a previous study we demonstrated an earlier disease onset and significantly higher serum NGF concentrations in drug-naïve schizophrenic patients with previous long-term cannabis abuse than in schizophrenics without cannabis abuse or cannabis abusers without schizophrenia. We therefore investigated whether this difference is still observed after treatment. Serum NGF measured in 114 treated schizophrenic patients (schizophrenia alone, n=66; schizophrenia plus cannabis abuse, n=42; schizophrenia plus multiple substance abuse, n=6) no longer differed significantly among those groups and from the control groups (healthy controls, n=51; cannabis controls, n=24; multiple substance controls, n=6). These results were confirmed by an additional prospective study in 28 patients suffering from schizophrenia (S) or schizophrenia with cannabis abuse (SC). Previously elevated serum NGF levels in the drug-naïve state, also differing between the groups (S: 83.44+/-265.25 pg/ml; SC: 246.89+/-310.24 pg/ml, S versus SC: p=0.03) dropped to 10.72+/-14.13 pg/ml (S) and 34.19+/-38.96 pg/ml (SC) (S versus SC, p>0.05), respectively, after adequate antipsychotic treatment. We thus conclude that antipsychotic treatment leads to recovery of neural integrity, as indicated by renormalized NGF values.

COMT Val108/158Met genotype modulates human sensory gating.

BACKGROUND The catechol-O-methyltransferase (COMT) Val(108/158)Met polymorphism of the dopamine system is essential for prefrontal cortex processing capacity and efficiency. In addition, dopaminergic neurotransmission is also associated with the sensory gating phenomenon protecting the cerebral cortex from information overload. It is however unclear if COMT genotype as a predictor of prefrontal efficiency modulates sensory gating on the level of the auditory cortex, i.e. the gating of the auditory evoked P50 and N100 components. METHODS P50 and N100 gating and COMT Val(108/158)Met genotype were determined in 282 healthy subjects of German descent carefully screened for psychiatric or neurological disorders. RESULTS A significant effect of the COMT genotype was observed for N100 gating (F=4.510, df=2, p=0.012) but not for P50 gating (F=0.376, df=2, p=0.687). Contrast analysis showed that Met/Met individuals had poorer N100 gating compared to Val/Met (F=-12.931, p=0.003) and the Val/Val individuals (F=-11.056, p=0.057). CONCLUSION The results indicate that a high prefrontal efficiency as suggested by the COMT Met/Met genotype is associated with to a poor sensory gating of the N100 component. This would fit in a model where a high prefrontal processing capacity allows a pronounced afferent input of sensory information from the auditory cortex as reflected by a poor sensory gating. The more pronounced prefrontal contribution to the N100 compared to the P50 component may explain the exclusive genotype association with the N100 sensory gating. This preliminary model should be replicated and validated in future investigations.

Auditory Mismatch Negativity and Repetition Suppression Deficits in Schizophrenia Explained by Irregular Computation of Prediction Error

Background The predictive coding model is rapidly gaining attention in schizophrenia research. It posits the neuronal computation of residual variance (‘prediction error’) between sensory information and top-down expectation through multiple hierarchical levels. Event-related potentials (ERP) reflect cortical processing stages that are increasingly interpreted in the light of the predictive coding hypothesis. Both mismatch negativity (MMN) and repetition suppression (RS) measures are considered a prediction error correlates based on error detection and error minimization, respectively. Methods Twenty-five schizophrenia patients and 25 healthy controls completed auditory tasks designed to elicit MMN and RS responses that were investigated using repeated measures models and strong spatio-temporal a priori hypothesis based on previous research. Separate correlations were performed for controls and schizophrenia patients, using age and clinical variables as covariates. Results MMN and RS deficits were largely replicated in our sample of schizophrenia patients. Moreover, MMN and RS measures were strongly correlated in healthy controls, while no correlation was found in schizophrenia patients. Single-trial analyses indicated significantly lower signal-to-noise ratio during prediction error computation in schizophrenia. Conclusions This study provides evidence that auditory ERP components relevant for schizophrenia research can be reconciled in the light of the predictive coding framework. The lack of any correlation between the investigated measures in schizophrenia patients suggests a disruption of predictive coding mechanisms in general. More specifically, these results suggest that schizophrenia is associated with an irregular computation of residual variance between sensory input and top-down models, i.e. prediction error.

Neurophysiological Effects of Cannabinoids: Implications for Psychosis Research

It is widely accepted that there is a close relationship between cannabis use, the endocannabinoid system, and psychosis. In particular, cannabis use has the potential to trigger the onset of psychosis in vulnerable individuals and to exacerbate psychotic symptomatology in schizophrenia patients, including positive, negative, and cognitive symptoms. With regard to the cognitive dysfunctions as a core feature of schizophrenia, overlapping deficits in the domains of attention, memory, and executive functioning have been observed between chronic cannabis use and the disease. In this overview, we report on human clinical and experimental studies investigating the acute and chronic effects of cannabinoids on specific neurophysiological measures, i.e., the P50 suppression, the mismatch negativity, and the P300 potential, that consistently showed characteristic abnormalities in schizophrenia. Based on the results, we discuss some explanations on the putative mechanisms involving the endocannabinoid system and its interactions with other neuromodulators that might form the neural substrates underlying cannabis-induced cognitive impairments and help understand the neurobiology underpinning the development of cognitive deficits in schizophrenia.

Comparison of Midlatency Auditory Sensory Gating at Short and Long Interstimulus Intervals

Rationale: Suppression of P50, N100 and P200 auditory evoked responses in a dual-click procedure is considered an index for the multistage sensory gating process. Whereas most studies use a protocol with long interstimulus intervals of 8–12 s between the stimuli pairs, there is also evidence that sensory gating occurs at much lower intervals. The aim of the study was to investigate whether a simple modified dual-click protocol with short interstimulus intervals elicts similar sensory gating ratios compared to the classic protocol. Methods: P50, N100 and P200 amplitudes and sensory gating ratios were measured in 23 healthy subjects with 2 different dual-click protocols in 1 session: (1) a simple oddball modified with short interstimulus intervals of about 2.8 s (ISI2), and (2), the classic used with long intervals of about 8 s (ISI8). Results: The amplitudes of the P50, N100 and P200 responses were mostly comparable and correlated between both protocols. Mean sensory gating ratios (ISI8/ISI2) were as follows: P50, 35.4/36.4%; N40P50, 36.1/39.9%; N100, 44.4/48.4%; P200, 46.8/43.3%; N100P200, 45.3/41.8%; all differences between protocols, p > 0.1. P50 ratio scores did not show a sufficient correlation between protocols [intraclass correlation coefficient (ICC) P50, 0.13; N40P50, 0.0] compared to N100 (ICC, 0.79), P200 (ICC, 0.6) and N100P200 (ICC, 0.61). Conclusion: Our results contradict the assumption that long interstimulus intervals of about 8 s are absolutely necessary to elicit a marked sensory gating phenomenon for P50, N100 and P200 auditory responses (at least when using a protocol with a simple attention task). However, because only healthy subjects were investigated, no prediction can be made for psychiatric patients, in whom neuronal processing may be different.

Critical Evaluation of Auditory Event-Related Potential Deficits in Schizophrenia: Evidence From Large-Scale Single-Subject Pattern Classification

Event-related potential (ERP) deficits associated with auditory oddball and click-conditioning paradigms are among the most consistent findings in schizophrenia and are discussed as potential biomarkers. However, it is unclear to what extend these ERP deficits distinguish between schizophrenia patients and healthy controls on a single-subject level, which is of high importance for potential translation to clinical routine. Here, we investigated 144 schizophrenia patients and 144 matched controls with an auditory click-conditioning/oddball paradigm. P50 and N1 gating ratios as well as target-locked N1 and P3 components were submitted to conventional general linear models and to explorative machine learning algorithms. Repeated-measures ANOVAs revealed significant between-group differences for the oddball-locked N1 and P3 components but not for any gating measure. Machine learning-assisted analysis achieved 77.7% balanced classification accuracy using a combination of target-locked N1 and P3 amplitudes as classifiers. The superiority of machine learning over repeated-measures analysis for classifying schizophrenia patients was in the range of about 10% as quantified by receiver operating characteristics. For the first time, our study provides large-scale single-subject classification data on auditory click-conditioning and oddball paradigms in schizophrenia. Although our study exemplifies how automated inference may substantially improve classification accuracy, our data also show that the investigated ERP measures show comparably poor discriminatory properties in single subjects, thus illustrating the need to establish either new analytical approaches for these paradigms or other paradigms to investigate the disorder.