Is There a Dose-Response Relationship Between Cannabis Use and Violence? A Longitudinal Study in Individuals with Severe Mental Disorders.

Introduction: Recent longitudinal studies point toward the existence of a positive relationship between cannabis use and violence in people with severe mental disorders (SMD). However, the existence of a dose-response relationship between the frequency/severity of cannabis use and violence has seldom been investigated. Therefore, this study aims to determine if such a relationship exists in a psychiatric population. Methods: To do so, a total of 98 outpatients (81 males and 17 females, all over 18 years of age) with SMD were recruited at the Institut universitaire de santé mentale de Montréal (Montréal, Canada) and included in the analyses. Clinical evaluations were conducted every 3 months for a year. Substance use, violent behaviors, and potential covariables were assessed through self-reported assessments, urinary testing, as well as clinical, criminal, and police records. Using generalized estimating equations, the association between cannabis use frequency (nonusers, occasional, regular, and frequent users) and violence was investigated, as well as the association between the severity of cannabis use and violent behaviors. Results: It was found that cannabis use frequency and severity were significant predictors of violent behaviors. After adjustment for time, age, sex, ethnicity, diagnoses, impulsivity, and use of alcohol and stimulants, odds ratios were of 1.91 (p<0.001) between each frequency profile and 1.040 (p<0.001) for each increase of one point of the severity of cannabis use score (ranging from 0 to 79). Conclusions: Despite the high attrition rate, these findings may have important implications for clinicians as cannabis use may have serious consequences in psychiatric populations. Nevertheless, the mechanisms underlying this association remain unclear.

Enhancing Predictive Power: Integrating a Linear Support Vector Classifier with Logistic Regression for Patient Outcome Prognosis in Virtual Reality Therapy for Treatment-Resistant Schizophrenia.

(1) Background: Approximately 30% of schizophrenia patients are known to be treatment-resistant. For these cases, more personalized approaches must be developed. Virtual reality therapeutic approaches such as avatar therapy (AT) are currently undergoing investigations to address these patients' needs. To further tailor the therapeutic trajectory of patients presenting with this complex presentation of schizophrenia, quantitative insight about the therapeutic process is warranted. The aim of the study is to combine a classification model with a regression model with the aim of predicting the therapeutic outcomes of patients based on the interactions taking place during their first immersive session of virtual reality therapy. (2) Methods: A combination of a Linear Support Vector Classifier and logistic regression was conducted over a dataset comprising 162 verbatims of the immersive sessions of 18 patients who previously underwent AT. As a testing dataset, 17 participants, unknown to the dataset, had their first immersive session presented to the combinatory model to predict their clinical outcome. (3) Results: The model accurately predicted the clinical outcome for 15 out of the 17 participants. Classification of the therapeutic interactions achieved an accuracy of 63%. (4) Conclusion: To our knowledge, this is the first attempt to predict the outcome of psychotherapy patients based on the content of their interactions with their therapist. These results are important as they open the door to personalization of psychotherapy based on quantitative information about the interactions taking place during AT.

Amelioration of Cognitive and Olfactory System Deficits in APOE4 Transgenic Mice with DHA Treatment.

Olfactory dysfunction and atrophy of olfactory brain regions are observed early in mild cognitive impairment and Alzheimer disease. Despite substantial evidence showing neuroprotective effects in MCI/AD with treatment of docosahexaenoic acid (DHA), an omega-3 fatty acid, few studies have assessed DHA and its effects on the olfactory system deficits. We therefore performed structural (MRI), functional (olfactory behavior, novel object recognition), and molecular (markers of apoptosis and inflammation) assessments of APOE4 and wild-type mice ± DHA treatment at 3, 6, and 12 months of age. Our results demonstrate that APOE4 mice treated with the control diet show recognition memory deficits, abnormal olfactory habituation, and discrimination abilities and an increase in IBA-1 immunoreactivity in the olfactory bulb. These phenotypes were not present in APOE4 mice treated with a DHA diet. Alterations in some brain regions' weights and/or volumes were observed in the APOPE4 mice and may be due to caspase activation and/or neuroinflammatory events. These results suggest that the consumption of a diet rich in DHA may provide some benefit to E4 carriers but may not alleviate all symptoms.

Avatar Intervention for Cannabis Use Disorder in Individuals with Severe Mental Disorders: A Pilot Study.

Cannabis use disorder (CUD) is a complex issue, even more so when it is comorbid with a severe mental disorder (SMD). Available interventions are at best slightly effective, and their effects are not maintained over time. Therefore, the integration of virtual reality (VR) may increase efficacy; however, it has not yet been investigated in the treatment of CUD. A novel approach, avatar intervention for CUD, uses existing therapeutic techniques from other recommended therapies (e.g., cognitive behavioral methods, motivational interviewing) and allows participants to practice them in real-time. During immersive sessions, participants are invited to interact with an avatar representing a significant person related to their drug use. This pilot clinical trial aimed to evaluate the short-term efficacity of avatar intervention for CUD on 19 participants with a dual diagnosis of SMD and CUD. Results showed a significant moderate reduction in the quantity of cannabis use (Cohen's d = 0.611, p = 0.004), which was confirmed via urinary quantification of cannabis use. Overall, this unique intervention shows promising results. Longer-term results, as well as comparison with classical interventions in a larger sample, are warranted through a future single-blind randomized controlled trial.

Unsupervised Machine Learning Driven Analysis of Verbatims of Treatment-Resistant Schizophrenia Patients Having Followed Avatar Therapy.

(1) Background: The therapeutic mechanisms underlying psychotherapeutic interventions for individuals with treatment-resistant schizophrenia are mostly unknown. One of these treatment techniques is avatar therapy (AT), in which the patient engages in immersive sessions while interacting with an avatar representing their primary persistent auditory verbal hallucination. The aim of this study was to conduct an unsupervised machine-learning analysis of verbatims of treatment-resistant schizophrenia patients that have followed AT. The second aim of the study was to compare the data clusters obtained from the unsupervised machine-learning analysis with previously conducted qualitative analysis. (2) Methods: A k-means algorithm was performed over the immersive-session verbatims of 18 patients suffering from treatment-resistant schizophrenia who followed AT to cluster interactions of the avatar and the patient. Data were pre-processed using vectorization and data reduction. (3): Results: Three clusters of interactions were identified for the avatar's interactions whereas four clusters were identified for the patient's interactions. (4) Conclusion: This study was the first attempt to conduct unsupervised machine learning on AT and provided a quantitative insight into the inner interactions that take place during immersive sessions. The use of unsupervised machine learning could yield a better understanding of the type of interactions that take place in AT and their clinical implications.

Specific olfactory deficit patterns observed in seniors and associated with cognitive decline.

Olfactory dysfunction is a common symptom in neurodegenerative disorders and is regarded as a potential early predictor of impending cognitive decline. This study was undertaken in order to determine if olfactory dysfunction observed in the elderly is due to a general loss of smell or the inability to detect specific odours, and if misidentification of odours correlates with cognitive scores. Seniors for the Olfactory Response and Cognition in Aging (ORCA) sub-study were recruited from the Quebec Nutrition and Successful Aging (NuAge) cohort. The University of Pennsylvania smell identification test (UPSIT) was performed to measure olfactory function and the telephone Mini Mental State Examination (t-MMSE) and the French version of the Telephone Interview for Cognitive Status Modified (F-TICS-m) for cognitive status. The results demonstrate that seniors exhibit specific olfactory loss and had severe difficulty in particular in identifying lemon, pizza, fruit punch, cheddar cheese and lime. Furthermore, there was a significant difference in the ability to detect certain odours between the sexes. Results also showed that misidentification of certain scents was associated with cognitive scores, and when the sexes were assessed separately sex-specific misidentification of cognitive-associated odours was observed. The relationship between the cognitive scores and scent misidentification suggests that impending cognitive decline may be highlighted by the inability to smell specific odours. Our study provides additional support for the testing of olfactory function in the elderly and suggests that loss of smell for particular scents may become a useful diagnostic tool.

Dyadic Interactions of Treatment-Resistant Schizophrenia Patients Having Followed Virtual Reality Therapy: A Content Analysis.

(1) Background: Very little is known about the inner therapeutic processes of psychotherapy interventions for patients suffering from treatment-resistant schizophrenia. Avatar therapy (AT) is one such modalities in which the patient is undergoing immersive sessions in which they interact with an Avatar representing their main persistent auditory verbal hallucination. The aim of this study is to identify the most prevalent dyadic interactions between the patient and the Avatar in AT for patient's suffering from TRS. (2) Methods: A content analysis of 256 verbatims originating from 32 patients who completed AT between 2017 and 2022 at the Institut universitaire en santé mentale de Montréal was conducted to identify dyadic interactions between the patients and their Avatar. (3) Results: Five key dyads were identified to occur on average more than 10 times for each participant during the immersive sessions across their AT: (Avatar: Reinforcement, Patient: Self-affirmation), (Avatar: Provocation, Patient: Self-affirmation), (Avatar: Coping mechanisms, Patient: Prevention), (Patient: Self-affirmation, Avatar: Reinforcement), and (Patient: Self-appraisal, Avatar: Reinforcement). (4) Conclusion: These dyads offer a first qualitative insight to the interpersonal dynamics and patient-avatar relationships taking place during AT. Future studies on the implication of such dyadic interactions with the therapeutic outcome of AT should be conducted considering the importance of dyadic relationships in psychotherapy.

Changes in Quality of Life in Treatment-Resistant Schizophrenia Patients Undergoing Avatar Therapy: A Content Analysis.

Avatar Therapy has a significant impact on symptoms, beliefs, and quality of life of patients with treatment-resistant schizophrenia. However, little is known about how these changes are implemented into their lives and to which aspects of their lives these improvements relate. Ten consecutive patients enrolled in an ongoing clinical trial were assessed using semi-guided interviews before as well as three months after Avatar Therapy. These encounters have been recorded and transcribed so that the discourse could be thoroughly analyzed, leading to the generation of an extensive theme grid. As the cases were analyzed, the grid was adapted in a back-and-forth manner until data saturation occurred. The content analysis allowed the identification of nine main themes representing different aspects of the patients' lives, each of which was subdivided into more specific codes. By analyzing the evolution of their frequency, it was observed that, following therapy, patients presented with fewer psychotic symptoms, better self-esteem, more hobbies and projects, and an overall improved lifestyle and mood. Finally, investigating the impact of Avatar Therapy on quality of life allows for a deeper understanding of how people with treatment-resistant schizophrenia can achieve meaningful changes and move towards a certain recovery process.

Multimodal CRISPR perturbations of GWAS loci associated with coronary artery disease in vascular endothelial cells.

Genome-wide association studies have identified >250 genetic variants associated with coronary artery disease (CAD), but the causal variants, genes and molecular mechanisms remain unknown at most loci. We performed pooled CRISPR screens to test the impact of sequences at or near CAD-associated genetic variants on vascular endothelial cell functions. Using CRISPR knockout, inhibition and activation, we targeted 1998 variants at 83 CAD loci to assess their effect on three adhesion proteins (E-selectin, ICAM1, VCAM1) and three key endothelial functions (nitric oxide and reactive oxygen species production, calcium signalling). At a false discovery rate ≤10%, we identified significant CRISPR perturbations near 42 variants located within 26 CAD loci. We used base editing to validate a putative causal variant in the promoter of the FES gene. Although a few of the loci include genes previously characterized in endothelial cells (e.g. AIDA, ARHGEF26, ADAMTS7), most are implicated in endothelial dysfunction for the first time. Detailed characterization of one of these new loci implicated the RNA helicase DHX38 in vascular endothelial cell senescence. While promising, our results also highlighted several limitations in using CRISPR perturbations to functionally dissect GWAS loci, including an unknown false negative rate and potential off-target effects.

Olfactory Dysfunction Associated with Cognitive Decline in an Elderly Population.

BACKGROUND: In many neurological disorders, including Alzheimer disease, early olfactory dysfunction is observed. OBJECTIVE: In order to determine if deficits in olfactory memory are present in the elderly and if olfactory dysfunction correlates with cognitive impairment in the aging population, olfactory testing has been done on seniors from the NuAge cohort accepting to participate in the Olfactory Response Cognition and Aging (ORCA) secondary sub-study. The t-Mini Mental Statement Examination and the Telephone Interview for Cognitive Status tests were done to assess cognition levels. RESULTS: Overall, 94% of the ORCA cohort displayed olfactory dysfunction. Deficits in olfactory memory were also present. A correlation was observed between olfactory function and cognitive test scores. Moreover, in women who smoked, there was an association between olfactory memory and cognitive scores. CONCLUSION: Our results suggest that olfactory dysfunction may predict impending cognitive decline and highlights the need for olfactory training in seniors to improve olfaction and overall well-being.

Implementation of a machine learning algorithm for automated thematic annotations in avatar: A linear support vector classifier approach.

Avatar Therapy (AT) is a modern therapeutic alternative for patients with schizophrenia suffering from persistent auditory verbal hallucinations. Its intrinsic therapeutical process is currently qualitatively analyzed via human coders that annotate session transcripts. This process is time and resource demanding. This creates a need to find potential algorithms that can operate on small datasets and perform such annotations. The first objective of this study is to conduct the automated text classification of interactions in AT and the second objective is to assess if this classification is comparable to the classification done by human coders. A Linear Support Vector Classifier was implemented to perform automated theme classifications on Avatar Therapy session transcripts with the use of a limited dataset with an accuracy of 66.02% and substantial classification agreement of 0.647. These results open the door to additional research such as predicting the outcome of a therapy.

Prediction of quality of life in schizophrenia using machine learning models on data from Clinical Antipsychotic Trials of Intervention Effectiveness (CATIE) schizophrenia trial.

While research focus remains mainly on psychotic symptoms, it is questionable whether we are placing enough emphasis on improving the quality of life (QoL) of schizophrenia patients. To date, the predictive power of QoL remained limited. Therefore, this study aimed to accurately predict the QoL within schizophrenia using supervised learning methods. The authors report findings from participants of a large randomized, double-blind clinical trial for schizophrenia treatment. Potential predictors of QoL included all available and non-redundant variables from the dataset. By optimizing parameters, three linear LASSO regressions were calculated (N = 697, 692, and 786), including 44, 47, and 41 variables, with adjusted R-squares ranging from 0.31 to 0.36. Best predictors included social and emotion-related symptoms, neurocognition (processing speed), education, female gender, treatment attitudes, and mental, emotional, and physical health. These results demonstrate that machine learning is an excellent predictive tool to process clinical data. It appears that the patient's perception of their treatment has an important impact on patients' QoL and that interventions should consider this aspect.Trial registration: ClinicalTrials.gov Identifier: NCT00014001.

Pharmacist-led transitions of care between hospitals, primary care clinics, and community pharmacies.

BACKGROUND: Pharmacist-led transitions of care (TOC) interventions have been described as some of the most promising interventions to reduce medication-related harm (MRH) in older adults. This study analyzed the feasibility of pharmacist-led TOC interventions between hospitals, multidisciplinary primary care clinics (PCC), and community pharmacies. METHODS: Adults aged 65 years and older at risk of MRH in three regions of Quebec, Canada, with contrasting contexts of care based on university affiliation were recruited in this multicenter, single arm, and prospective intervention cohort. The hospital pharmacist developed the pharmaceutical care plan in collaboration with the hospital physician and transferred this plan with the hospitalization summary, at hospital discharge, to the PCC family physician and to the community and PCC pharmacists. A consultation with the community pharmacist was scheduled within seven days of hospital discharge and with the PCC pharmacist when appropriate. Feasibility outcomes included the time to complete the interventions and their location. RESULTS: The 123 eligible patients had a mean age of 78.5 years, and 63.4% were females. The most frequent inclusion criterion was 10 medications or more, including one high-risk medication for 90 patients (73%). Recruitment in one region was stopped after three months due to unsuccessful recruitment of key PCC. The hospital pharmacist interventions took a median of 165 min. The first consultations of the PCC and community pharmacists took a median of 15 and 50 min. Among the 96 patients with a post-discharge pharmacist follow-up, 23 (24.0%) had a consultation with a PCC pharmacist, with 65.2% of the consultations conducted at the PCC. The community pharmacists conducted a consultation with 88 patients (93%), with more than 70% of consultations conducted by phone. CONCLUSION: Our study showed the feasibility of pharmacist-led TOC interventions between hospitals, PCC, and community pharmacies and detailed the novel role that PCC pharmacists played in optimizing TOC interventions.

Use of Automated Thematic Annotations for Small Data Sets in a Psychotherapeutic Context: Systematic Review of Machine Learning Algorithms.

BACKGROUND: A growing body of literature has detailed the use of qualitative analyses to measure the therapeutic processes and intrinsic effectiveness of psychotherapies, which yield small databases. Nonetheless, these approaches have several limitations and machine learning algorithms are needed. OBJECTIVE: The objective of this study is to conduct a systematic review of the use of machine learning for automated text classification for small data sets in the fields of psychiatry, psychology, and social sciences. This review will identify available algorithms and assess if automated classification of textual entities is comparable to the classification done by human evaluators. METHODS: A systematic search was performed in the electronic databases of Medline, Web of Science, PsycNet (PsycINFO), and Google Scholar from their inception dates to 2021. The fields of psychiatry, psychology, and social sciences were selected as they include a vast array of textual entities in the domain of mental health that can be reviewed. Additional records identified through cross-referencing were used to find other studies. RESULTS: This literature search identified 5442 articles that were eligible for our study after the removal of duplicates. Following abstract screening, 114 full articles were assessed in their entirety, of which 107 were excluded. The remaining 7 studies were analyzed. Classification algorithms such as naive Bayes, decision tree, and support vector machine classifiers were identified. Support vector machine is the most used algorithm and best performing as per the identified articles. Prediction classification scores for the identified algorithms ranged from 53%-91% for the classification of textual entities in 4-7 categories. In addition, 3 of the 7 studies reported an interjudge agreement statistic; these were consistent with agreement statistics for text classification done by human evaluators. CONCLUSIONS: A systematic review of available machine learning algorithms for automated text classification for small data sets in several fields (psychiatry, psychology, and social sciences) was conducted. We compared automated classification with classification done by human evaluators. Our results show that it is possible to automatically classify textual entities of a transcript based solely on small databases. Future studies are nevertheless needed to assess whether such algorithms can be implemented in the context of psychotherapies.

Diet enriched in omega-3 fatty acids alleviates olfactory system deficits in APOE4 transgenic mice.

Olfactory dysfunction is observed in several neurological disorders including Mild Cognitive Impairment (MCI) and Alzheimer disease (AD). These deficits occur early and correlate with global cognitive performance, depression and degeneration of olfactory regions in the brain. Despite extensive human studies, there has been little characterization of the olfactory system in models of AD. In order to determine if olfactory structural and/or molecular phenotypes are observed in a model expressing a genetic risk factor for AD, we assessed the olfactory bulb (OB) in APOE4 transgenic mice. A significant decrease in OB weight was observed at 12 months of age in APOE4 mice concurrent with inflammation and decreased NeuN expression. In order to determine if a diet rich in omega-3s may alleviate the olfactory system phenotypes observed, we assessed WT and APOE4 mice on a docosahexaenoic acid (DHA) diet. APOE4 mice on a DHA diet did not present with atrophy of the OB, and the alterations in NeuN and IBA-1 expression were alleviated. Furthermore, alterations in caspase mRNA and protein expression in the APOE4 OB were not observed with a DHA diet. Similar to the human AD condition, OB atrophy is an early phenotype in the APOE4 mice and concurrent with inflammation. These data support a link between the structural olfactory brain region atrophy and the olfactory dysfunction observed in AD and suggest that inflammation and cell death pathways may contribute to the olfactory deficits observed. Furthermore, the results suggest that diets enriched in DHA may provide benefit to APOE4 allele carriers.

The therapeutic processes of avatar therapy: A content analysis of the dialogue between treatment-resistant patients with schizophrenia and their avatar.

OBJECTIVE: Because the therapeutic processes of Avatar Therapy remain equivocal, the current study aims to further extend our previous findings by analysing the evolution of the avatars' and patients' speech and changes in patient responses as sessions progressed. DESIGN: Eighteen patients with treatment-resistant schizophrenia were selected from two clinical trials on Avatar Therapy. Three coders analysed both the avatars' and patients' discourse during immersive therapy sessions using content analysis methods. RESULTS: Our analyses enabled the categorization of the avatar discourse into confrontational techniques (e.g., provocation) and positive techniques (e.g., reinforcement). Patients responded to these utterances using coping mechanism or by expressing emotions, beliefs, self-perceptions or aspirations. Through identification of mutual changes in the interaction between the patient and their avatar, a shift was observed over the sessions from confrontation to a constructive dialogue. Assertiveness, emotional responses and prevention strategies seemed to be central to the therapeutic process, and these usually occur in response to positive techniques. CONCLUSION: Investigating AT's therapeutic process may help to identify components to achieve positive outcomes and can enable the development of more effective treatments. Further studies should explore the association between these themes and therapeutic response to help predict which patients will better respond to Avatar Therapy.

Pharmacist-led transitions of care for older adults at risk of drug-related problems: A feasibility study.

BACKGROUND: Transitions of care (TOC) is one of three key action areas identified in the World Health Organization (WHO)'s third Global Patient Safety Challenge, Medication Without Harm, released in 2017. Systematic reviews have shown that TOC interventions can improve health outcomes, although few studies have evaluated the role of the community pharmacist. OBJECTIVE: To evaluate the feasibility of a pharmacist-led TOC intervention for older adults at risk of drug-related problems. METHODS: Pragmatic feasibility study conducted in hospital and community pharmacies in a health region of Quebec, Canada. The interventions consisted of a pharmaceutical care plan developed by the hospital pharmacist and transferred at hospital discharge to the patients' community pharmacist, who completed patient consultations in the week following discharge and monthly for six months thereafter. Feasibility evaluations included recruitment, retention, time required, types of interventions, and modified classes of medications, based on clinical data entered in an electronic health record accessible to clinicians in all settings. RESULTS: Of the 90 recruited patients, 76 were discharged with a pharmaceutical care plan. The mean age of these 76 subjects was 79.5 years, and 52.6% were female. The most frequent inclusion criteria were 15 or more medications (57.9%), two or more emergency department visits (past three months), or one or more hospitalization (past twelve months) (42.1%). The hospital pharmacist interventions took a mean time of 222 min. The community pharmacist interventions took a mean time of 52 min and 32 min for the first and subsequent visits, respectively. Therapeutic goals were documented for 60.5% of patients. CONCLUSIONS: This study shows the feasibility of implementing a pharmacist-led TOC intervention in the Canadian context. Development of the TOC model in three health regions is currently being pursued along with the inclusion of primary care clinics who recently added pharmacists to their interdisciplinary teams.

Volumetric MRI demonstrates atrophy of the olfactory cortex in AD.

OBJECTIVE: Alzheimer disease (AD) is a chronic neurodegenerative disorder that affects millions of individuals worldwide. Symptoms include memory dysfunction and deficits in attention, planning, language, and overall cognitive function. Olfactory dysfunction is a common symptom of AD and evidence supports that it is an early marker. Furthermore, olfactory bulb and entorhinal cortex atrophy are well described in AD. However, in AD, no studies have assessed the olfactory cortex as a whole and if sex effects are observed. METHODS: Magnetic Resonance Imaging was used to scan 39 participants with an average age of 72 years and included men and women. AAL Single-Subject Atlas (implemented in PNEURO tool - PMOD 3.8) was used to determine the volume of the olfactory cortex and the hippocampus. Olfactory cortex volume was lower in both men and women AD cases compared with controls. This decrease was more apparent in the left olfactory cortex and was influenced by age. As expected, hippocampal volume was also significantly reduced in AD. However, this was only observed in the male cohort. A significant correlation was observed between levels of education and hippocampal volume in controls that were not detected in the AD participants. Asymmetry was observed in the olfactory cortex volume when comparing left and right volumes in both the control and AD participants, which was not observed in the hippocampus. RESULTS: These data highlight the importance of the role of olfactory cortical atrophy in the pathogenesis of AD and the interplay between the olfactory deficits and degeneration of olfactory regions in the brain.

Trans-ethnic and Ancestry-Specific Blood-Cell Genetics in 746,667 Individuals from 5 Global Populations.

Most loci identified by GWASs have been found in populations of European ancestry (EUR). In trans-ethnic meta-analyses for 15 hematological traits in 746,667 participants, including 184,535 non-EUR individuals, we identified 5,552 trait-variant associations at p < 5 × 10-9, including 71 novel associations not found in EUR populations. We also identified 28 additional novel variants in ancestry-specific, non-EUR meta-analyses, including an IL7 missense variant in South Asians associated with lymphocyte count in vivo and IL-7 secretion levels in vitro. Fine-mapping prioritized variants annotated as functional and generated 95% credible sets that were 30% smaller when using the trans-ethnic as opposed to the EUR-only results. We explored the clinical significance and predictive value of trans-ethnic variants in multiple populations and compared genetic architecture and the effect of natural selection on these blood phenotypes between populations. Altogether, our results for hematological traits highlight the value of a more global representation of populations in genetic studies.

Persistent cannabis use as an independent risk factor for violent behaviors in patients with schizophrenia.

Although recent studies have shown a moderately strong association between cannabis use and violence among people with severe mental disorders, the direction of this association has not been investigated prospectively in a population with schizophrenia. Therefore, this study aims to determine, using cross-lag models, whether a temporal relationship between cumulative cannabis use and violence exists in a population with schizophrenia. The authors reported findings covering an 18-month period from a randomized, double-blind clinical trial of antipsychotic medications for schizophrenia treatment. Among the 1460 patients enrolled in the trial, 965 were followed longitudinally. Although persistent cannabis use predicted subsequent violence, violence did not predict cannabis use. The relationship was therefore unidirectional and persisted when controlling for stimulants and alcohol use. Finally, a significant body of evidence suggests a link between persistent cannabis use and violence among people with mental illnesses. Studies to further investigate the mechanisms underlying this association should be conducted.