Association between age of cannabis initiation and gray matter covariance networks in recent onset psychosis

Brain structural changes and molecular analyses in children with benign epilepsy with centrotemporal spikes

BACKGROUND

Benign epilepsy with centrotemporal spikes (BECTS) is a common childhood epilepsy syndrome, accompanied by behavioral problems and cognitive impairments. Previous studies of BECTS-related brain structures applied univariate analysis and showed inconsistent results. And neurotransmitter patterns associated with brain structural alterations were still unclear.

METHODS

Structural images of twenty-one drug-naïve children with BECTS and thirty-five healthy controls (HCs) were scanned. Segmented gray matter volume (GMV) images were decomposed into independent components (ICs) using the source-based morphometry method. Then spatial correlation analyses were applied to examine possible relationships between GMV changes and neurotransmitter systems.

RESULTS

Compared with HCs, drug-naïve children with BECTS showed increased volume in one GMV component (IC7), including bilateral precentral gyrus, bilateral supplementary motor area, left superior frontal cortex, bilateral middle/ inferior frontal cortex and bilateral anterior/ middle cingulate cortex. A positive correlation was observed between one GMV component (IC6) and seizure frequency. There were significantly positive correlations between abnormal GMV in IC7 and serotonergic, GABAergic and glutamatergic systems.

CONCLUSION

These findings provided further evidence of changed GMV in drug-naïve children with BECTS related to their behavioral problems and cognitive impairments, and associated neurotransmitters which could help to better understand neurobiological mechanisms and underlying molecular mechanisms of BECTS.

IMPACT

The article provides further evidence of changed gray matter volume in drug-naïve children with BECTS related to their behavioral problems and cognitive impairments as well as associated neurotransmitters. Most literature to date has applied univariate analysis and showed inconsistent results, and neurotransmitter patterns associated with brain structural alterations were still unclear. Therefore, this article uses multivariate method and JuSpace toolbox to fill the gap. Significantly increased gray matter volume was found in drug-naïve children with BECTS compared with healthy controls. Abnormal gray matter volume was significantly correlated with clinical data and specific neurotransmitters.

Abnormal developmental of structural covariance networks in young adults with heavy cannabis use: a 3-year follow-up study

Heavy cannabis use (HCU) exerts adverse effects on the brain. Structural covariance networks (SCNs) that illustrate coordinated regional maturation patterns are extensively employed to examine abnormalities in brain structure. Nevertheless, the unexplored aspect remains the developmental alterations of SCNs in young adults with HCU for three years, from the baseline (BL) to the 3-year follow-up (FU). These changes demonstrate dynamic development and hold potential as biomarkers. A total of 20 young adults with HCU and 22 matched controls were recruited. All participants underwent magnetic resonance imaging (MRI) scans at both the BL and FU and were evaluated using clinical measures. Both groups used cortical thickness (CT) and cortical surface area (CSA) to construct structural covariance matrices. Subsequently, global and nodal network measures of SCNs were computed based on these matrices. Regarding global network measures, the BL assessment revealed significant deviations in small-worldness and local efficiency of CT and CSA in young adults with HCU compared to controls. However, no significant differences between the two groups were observed at the FU evaluation. Young adults with HCU displayed changes in nodal network measures across various brain regions during the transition from BL to FU. These alterations included abnormal nodal degree, nodal efficiency, and nodal betweenness in widespread areas such as the entorhinal cortex, superior frontal gyrus, and parahippocampal cortex. These findings suggest that the topography of CT and CSA plays a role in the typical structural covariance topology of the brain. Furthermore, these results indicate the effect of HCU on the developmental changes of SCNs in young adults.

THC improves behavioural schizophrenia-like deficits that CBD fails to overcome: a comprehensive multilevel approach using the Poly I:C maternal immune activation

Prenatal infections and cannabis use during adolescence are well-recognized risk factors for schizophrenia. As inflammation and oxidative stress (OS) contribute to this disorder, anti-inflammatory drugs have been proposed as potential therapies. This study aimed to evaluate the association between delta-9-tetrahydrocannabinol (THC) and schizophrenia-like abnormalities in a maternal immune activation (MIA) model. Additionally, we assessed the preventive effect of cannabidiol (CBD), a non-psychotropic/anti-inflammatory cannabinoid. THC and/or CBD were administered to Saline- and MIA-offspring during periadolescence. At adulthood, THC-exposed MIA-offspring showed significant improvements in sensorimotor gating deficits. Structural and metabolic brain changes were evaluated by magnetic resonance imaging, revealing cortical shrinkage in Saline- and enlargement in MIA-offspring after THC-exposure. Additionally, MIA-offspring displayed enlarged ventricles and decreased hippocampus, which were partially reverted by both cannabinoids. CBD prevented THC-induced reduction in the corpus callosum, despite affecting white matter structure. Post-mortem studies revealed detrimental effects of THC, including increased inflammation and oxidative stress. CBD partially reverted these pro-inflammatory alterations and modulated THC's effects on the endocannabinoid system. In conclusion, contrary to expectations, THC exhibited greater behavioural and morphometric benefits, despite promoting a pro-inflammatory state that CBD partially reverted. Further research is needed to elucidate the underlying mechanisms involved in the observed benefits of THC.

Cannabinoids and the Endocannabinoid System in Early SARS-CoV-2 Infection and Long COVID-19-A Scoping Review

Coronavirus disease-19 (COVID-19) is a highly contagious illness caused by the SARS-CoV-2 virus. The clinical presentation of COVID-19 is variable, often including symptoms such as fever, cough, headache, fatigue, and an altered sense of smell and taste. Recently, post-acute "long" COVID-19 has emerged as a concern, with symptoms persisting beyond the acute infection. Vaccinations remain one of the most effective preventative methods against severe COVID-19 outcomes and the development of long-term COVID-19. However, individuals with underlying health conditions may not mount an adequate protective response to COVID-19 vaccines, increasing the likelihood of severe symptoms, hospitalization, and the development of long-term COVID-19 in high-risk populations. This review explores the potential therapeutic role of cannabinoids in limiting the susceptibility and severity of infection, both pre- and post-SARS-CoV-19 infection. Early in the SARS-CoV-19 infection, cannabinoids have been shown to prevent viral entry, mitigate oxidative stress, and alleviate the associated cytokine storm. Post-SARS-CoV-2 infection, cannabinoids have shown promise in treating symptoms associated with post-acute long COVID-19, including depression, anxiety, post-traumatic stress injury, insomnia, pain, and decreased appetite. While current research primarily focuses on potential treatments for the acute phase of COVID-19, there is a gap in research addressing therapeutics for the early and post-infectious phases. This review highlights the potential for future research to bridge this gap by investigating cannabinoids and the endocannabinoid system as a potential treatment strategy for both early and post-SARS-CoV-19 infection.

Consequences of adolescent drug use

Substance use in adolescence is a known risk factor for the development of neuropsychiatric and substance use disorders in adulthood. This is in part due to the fact that critical aspects of brain development occur during adolescence, which can be altered by drug use. Despite concerted efforts to educate youth about the potential negative consequences of substance use, initiation remains common amongst adolescents world-wide. Additionally, though there has been substantial research on the topic, many questions remain about the predictors and the consequences of adolescent drug use. In the following review, we will highlight some of the most recent literature on the neurobiological and behavioral effects of adolescent drug use in rodents, non-human primates, and humans, with a specific focus on alcohol, cannabis, nicotine, and the interactions between these substances. Overall, consumption of these substances during adolescence can produce long-lasting changes across a variety of structures and networks which can have enduring effects on behavior, emotion, and cognition.

Exploration of cannabis use and polygenic risk scores on the psychotic symptom progression of a FEP cohort

Cannabis use is highly prevalent in first-episode psychosis (FEP) and plays a critical role in its onset and prognosis, but the genetic underpinnings promoting both conditions are poorly understood. Current treatment strategies for cannabis cessation in FEP are clearly inefficacious. Here, we aimed to characterize the association between cannabis-related polygenic risk scores (PRS) on cannabis use and clinical course after a FEP. A cohort of 249 FEP individuals were evaluated during 12 months. Symptom severity was measured with the Positive and Negative Severity Scale and cannabis use with the EuropASI scale. Individual PRS for lifetime cannabis initiation (PRS_CI) and cannabis use disorder (PRS_CUD) were constructed. Current cannabis use was associated with increased positive symptoms. Cannabis initiation at younger ages conditioned the 12-month symptom progression. FEP patients with higher cannabis PRS_CUD reported increased baseline cannabis use. PRS_CI was associated with the course of negative and general symptomatology over follow-up. Cannabis use and symptom progression after a FEP were modulated by cannabis PRS, suggesting that lifetime initiation and use disorders may have partially independent genetic factors. These exploratory results may be the first step to identify those FEP patients more vulnerable to cannabis use and worse outcomes to ultimately develop tailored treatments.

Recommendations for Reducing the Risk of Cannabis Use-Related Adverse Psychosis Outcomes: A Public Mental Health-Oriented Evidence Review

Objective: Cannabis use is increasingly normalized; psychosis is a major adverse health outcome. We reviewed evidence on cannabis use-related risk factors for psychosis outcomes at different stages toward recommendations for risk reduction by individuals involved in cannabis use. Methods: We searched primary databases for pertinent literature/data 2016 onward, principally relying on reviews and high-quality studies which were narratively summarized and quality-graded; recommendations were developed by international expert consensus. Results: Genetic risks, and mental health/substance use problem histories elevate the risks for cannabis-related psychosis. Early age-of-use-onset, frequency-of-use, product composition (i.e., THC potency), use mode and other substance co-use all influence psychosis risks; the protective effects of CBD are uncertain. Continuous cannabis use may adversely affect psychosis-related treatment and medication effects. Risk factor combinations further amplify the odds of adverse psychosis outcomes. Conclusions: Reductions in the identified cannabis-related risks factors-short of abstinence-may decrease risks of related adverse psychosis outcomes, and thereby protect cannabis users' health.

Multiparametric assessment of sensorimotor abnormalities in vulnerable populations: A window of opportunity

This commentary suggests that neuroscience research on young healthy heavy cannabis users and patients with cannabis-induced psychosis using multimodal assessment of sensorimotor dysfunction (e.g. neuroimaging, clinical rating scales, and instrumental assessments) may help to identify both biological resistance and vulnerability without constraints and confounder factors imposed by antipsychotic treatment or disease chronicity.

A network approach to relationships between cannabis use characteristics and psychopathology in the general population

Cannabis use characteristics, such as earlier initiation and frequent use, have been associated with an increased risk for developing psychotic experiences and psychotic disorders. However, little is known how these characteristics relate to specific aspects of sub-clinical psychopathology in the general population. Here, we explore the relationships between cannabis use characteristics and psychopathology in a large general population sample (N = 2,544, mean age 29.2 years, 47% women) by employing a network approach. This allows for the identification of unique associations between two cannabis use characteristics (lifetime cumulative frequency of cannabis use, age of cannabis use initiation), and specific psychotic experiences and affective symptoms, while controlling for early risk factors (childhood trauma, urban upbringing). We found particularly pronounced unique positive associations between frequency of cannabis use and specific delusional experiences (persecutory delusions and thought broadcasting). Age of cannabis use initiation was negatively related to visual hallucinatory experiences and irritability, implying that these experiences become more likely the earlier use is initiated. Earlier initiation, but not lifetime frequency of cannabis use, was related to early risk factors. These findings suggest that cannabis use characteristics may contribute differentially to risk for specific psychotic experiences and affective symptoms in the general population.

Pattern of predictive features of continued cannabis use in patients with recent-onset psychosis and clinical high-risk for psychosis

Continued cannabis use (CCu) is an important predictor for poor long-term outcomes in psychosis and clinically high-risk patients, but no generalizable model has hitherto been tested for its ability to predict CCu in these vulnerable patient groups. In the current study, we investigated how structured clinical and cognitive assessments and structural magnetic resonance imaging (sMRI) contributed to the prediction of CCu in a group of 109 patients with recent-onset psychosis (ROP). We tested the generalizability of our predictors in 73 patients at clinical high-risk for psychosis (CHR). Here, CCu was defined as any cannabis consumption between baseline and 9-month follow-up, as assessed in structured interviews. All patients reported lifetime cannabis use at baseline. Data from clinical assessment alone correctly classified 73% (p < 0.001) of ROP and 59 % of CHR patients. The classifications of CCu based on sMRI and cognition were non-significant (ps > 0.093), and their addition to the interview-based predictor via stacking did not improve prediction significantly, either in the ROP or CHR groups (ps > 0.065). Lower functioning, specific substance use patterns, urbanicity and a lack of other coping strategies contributed reliably to the prediction of CCu and might thus represent important factors for guiding preventative efforts. Our results suggest that it may be possible to identify by clinical measures those psychosis-spectrum patients at high risk for CCu, potentially allowing to improve clinical care through targeted interventions. However, our model needs further testing in larger samples including more diverse clinical populations before being transferred into clinical practice.

Structural covariance networks in schizophrenia: A systematic review Part I

BACKGROUND

Schizophrenia is proposed as a disorder of dysconnectivity. However, examination of complexities of dysconnectivity has been challenging. Structural covariance networks (SCN) provide important insights into the nature of dysconnectivity. This systematic review examines the SCN studies that employed statistical approaches to elucidate covariation of regional morphometric variations.

METHODS

A systematic search of literature was conducted for peer-reviewed publications using different keywords and keyword combinations for schizophrenia. Fifty-two studies met the criteria.

RESULTS

Early SCN studies began using correlational structure of selected regions. Over the last 3 decades, methodological approaches have grown increasingly sophisticated from examining selected brain regions using correlation tests on small sample sizes to recent approaches that use advanced statistical methods to examine covariance structure of whole-brain parcellations on larger samples. Although the results are not fully consistent across all studies, a pattern of fronto-temporal, fronto-parietal and fronto-thalamic covariation is reported. Attempts to associate SCN alterations with functional connectivity, to differentiate between disease-related and neurodevelopment-related morphometric changes, and to develop "causality-based" models are being reported. Clinical correlation with outcome, psychotic symptoms, neurocognitive and social cognitive performance are also reported.

CONCLUSIONS

Application of advanced statistical methods are beginning to provide insights into interesting patterns of regional covariance including correlations with clinical and cognitive data. Although these findings appear similar to morphometric studies, SCNs have the advantage of highlighting topology of these regions and their relationship to the disease and associated variables. Further studies are needed to investigate neurobiological underpinnings of shared covariance, and causal links to clinical domains.