Monogenetic causes of psychiatric disorders:a review

Background Because of rapid developments in genetic technology, more underlying genetic causes of psychiatric disorders can be detected which may contribute to better monitoring and treatment of co-morbidities than previously. Aim Review of monogenetic causes of psychiatric disorders. Methode Review of the literature. Resultats Research in people with monogenetic disorders will generate new knowledge and insights on psychopathology and cognitive function in general and pave the way to new treatment targets. In this article we discuss four monogenetic disorders that are relevant for clinical psychiatry and (educational) psychology: fragile X syndrome, tuberous sclerosis, Rett Syndrome, and Huntington's disease. Conclusion Given the multisystem nature of these genetic disorders, a well-coordinated, multidisciplinary approach by specialized expert centers is highly recommended

Pharmacological interventions for the MATRICS cognitive domains in schizophrenia: what's the evidence?

Schizophrenia is a disabling, chronic psychiatric disorder with a prevalence rate of 0.5-1% in the general population. Symptoms include positive (e.g. delusions, hallucinations), negative (e.g. blunted affect, social withdrawal), as well as cognitive symptoms (e.g. memory and attention problems). Although 75-85% of patients with schizophrenia report cognitive impairments, the underlying neuropharmacological mechanisms are not well understood and currently no effective treatment is available for these impairments. This has led to the MATRICS initiative (Measurement and Treatment Research to Improve Cognition in Schizophrenia), which established seven cognitive domains that are fundamentally impaired in schizophrenia. These domains include verbal learning and memory, visual learning and memory, working memory, attention and vigilance, processing speed, reasoning and problem solving, and social cognition. Recently, a growing number of studies have been conducted trying to identify the underlying neuropharmacological mechanisms of cognitive impairments in schizophrenia patients. Specific cognitive impairments seem to arise from different underlying neuropharmacological mechanisms. However, most review articles describe cognition in general and an overview of the mechanisms involved in these seven separate cognitive domains is currently lacking. Therefore, we reviewed the underlying neuropharmacological mechanisms focussing on the domains as established by the MATRICS initiative which are considered most crucial in schizophrenia

Neurobiological perspective of 22q11.2 deletion syndrome

22q11.2 deletion syndrome is characterised by a well defined microdeletion that is associated with a high risk of neuropsychiatric disorders, including intellectual disability, schizophrenia, attention-deficit hyperactivity disorder, autism spectrum disorder, anxiety disorders, seizures and epilepsy, and early-onset Parkinson's disease. Preclinical and clinical data reveal substantial variability of the neuropsychiatric phenotype despite the shared underlying deletion in this genetic model. Factors that might explain this variability include genetic background effects, additional rare pathogenic variants, and potential regulatory functions of some genes in the 22q11.2 deletion region. These factors might also be relevant to the pathophysiology of these neuropsychiatric disorders in the general population. We review studies that might provide insight into pathophysiological mechanisms underlying the expression of neuropsychiatric disorders in 22q11.2 deletion syndrome, and potential implications for these common disorders in the general (non-deleted) population. The recurrent hemizygous 22q11.2 deletion, associated with 22q11.2 deletion syndrome, has attracted attention as a genetic model for common neuropsychiatric disorders because of its association with substantially increased risk of such disorders.1 Studying such a model has many advantages. First, 22q11.2 deletion has been genetically well characterised.2 Second, most genes present in the region typically deleted at the 22q11.2 locus are expressed in the brain.3–5 Third, genetic diagnosis might be made early in life, long before recognisable neuropsychiatric disorders have emerged. Thus, this genetic condition offers a unique opportunity for early intervention, and monitoring individuals with 22q11.2 deletion syndrome throughout life could provide important information on factors contributing to disease risk and protection. Despite the commonly deleted region being shared by about 90% of individuals with 22q11.2 deletion syndrome, neuropsychiatric outcomes are highly variable between individuals and across the lifespan. A clear link remains to be established between genotype and phenotype.3,5 In this Review, we summarise preclinical and clinical studies investigating biological mechanisms in 22q11.2 deletion syndrome, with a focus on those that might provide insight into mechanisms underlying neuropsychiatric disorders in 22q11.2 deletion syndrome and in the general population

The association between clinical, sociodemographic, familial, and environmental factors and treatment resistance in schizophrenia:A machine-learning-based approach

Background: Prediction of treatment resistance in schizophrenia (TRS) would be helpful to reduce the duration of ineffective treatment and avoid delays in clozapine initiation. We applied machine learning to identify clinical, sociodemographic, familial, and environmental variables that are associated with TRS and could potentially predict TRS in the future. Study design: Baseline and follow-up data on trait(-like) variables from the Genetic Risk and Outcome of Psychosis (GROUP) study were used. For the main analysis, we selected patients with non-affective psychotic disorders who met TRS (n = 200) or antipsychotic-responsive criteria (n = 423) throughout the study. For a sensitivity analysis, we only selected patients who met TRS (n = 76) or antipsychotic-responsive criteria (n = 123) at follow-up but not at baseline. Random forest models were trained to predict TRS in both datasets. SHapley Additive exPlanation values were used to examine the variables' contributions to the prediction. Study results: Premorbid functioning, age at onset, and educational degree were most consistently associated with TRS across both analyses. Marital status, current household, intelligence quotient, number of moves, and family loading score for substance abuse also consistently contributed to the prediction of TRS in the main or sensitivity analysis. The diagnostic performance of our models was modest (area under the curve: 0.66–0.69). Conclusions: We demonstrate that various clinical, sociodemographic, familial, and environmental variables are associated with TRS. Our models only showed modest performance in predicting TRS. Prospective large multi-centre studies are needed to validate our findings and investigate whether the model's performance can be improved by adding data from different modalities.</p

Updated clinical practice recommendations for managing adults with 22q11.2 deletion syndrome

This review aimed to update the clinical practice guidelines for managing adults with 22q11.2 deletion syndrome (22q11.2DS). The 22q11.2 Society recruited expert clinicians worldwide to revise the original clinical practice guidelines for adults in a stepwise process according to best practices: (1) a systematic literature search (1992-2021), (2) study selection and synthesis by clinical experts from 8 countries, covering 24 subspecialties, and (3) formulation of consensus recommendations based on the literature and further shaped by patient advocate survey results. Of 2441 22q11.2DS-relevant publications initially identified, 2344 received full-text review, with 2318 meeting inclusion criteria (clinical care relevance to 22q11.2DS) including 894 with potential relevance to adults. The evidence base remains limited. Thus multidisciplinary recommendations represent statements of current best practice for this evolving field, informed by the available literature. These recommendations provide guidance for the recognition, evaluation, surveillance, and management of the many emerging and chronic 22q11.2DS-associated multisystem morbidities relevant to adults. The recommendations also address key genetic counseling and psychosocial considerations for the increasing numbers of adults with this complex condition

Transition from Child and Adolescent to Adult Mental Health Services in Young People with Depression:On What Do Clinicians Base their Recommendation?

Background. Clinicians in Child and Adolescent Mental Healthcare Services (CAMHS) face the challenge to determine who is at risk of persistence of depressive problems into adulthood and requires continued treatment after reaching the CAMHS upper age limit of care-provision. We assessed whether risk factors for persistence were related to CAMHS clinicians' transition recommendations. Methods. Within the wider MILESTONE cohort study, 203 CAMHS users were classified with unipolar depressive disorder by their clinician, and 185 reported clinical levels of depressive problems on the DSM-oriented Depressive Problems scale of the Achenbach Youth Self Report. Logistic regression models were fitted to both subsamples to assess the relationship between clinicians' transition recommendations and risk factors for persistent depression. Results. Only clinician-rated severity of psychopathology was related to a recommendation to continue treatment for those classified with unipolar depressive disorder (N=203; OR=1.45, 95% CI (1.03-2.03), p=.044) and for those with self-reported depressive problems on the Achenbach DSM-oriented Depressive Problems scale (N=185; OR=1.62, 95% CI (1.12-2.34), p=.012). Conclusion. Transition recommendations and need for continued treatment are based on clinical expertise, rather than self-reported problems and needs