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Measurement(s) Cognition • Psychiatric Diagnosis • Development Technology Type(s) MRI • phenotypic battery • actigraphy • laboratory analysis Sample Characteristic - Organism Homo sapien Sample Characteristic - Environment Community-ascertained non-diagnostic sample Sample Characteristic - Location United States

Abstract Tourette syndrome (TS) is a neuropsychiatric disorder of complex genetic architecture involving multiple interacting genes. Here, we sought to elucidate the pathways that underlie the neurobiology of the disorder through genome-wide analysis. We analyzed genome-wide genotypic data of 3581 individuals with TS and 7682 ancestry-matched controls and investigated associations of TS with sets of genes that are expressed in particular cell types and operate in specific neuronal and glial functions. We employed a self-contained, set-based association method (SBA) as well as a competitive gene set method (MAGMA) using individual-level genotype data to perform a comprehensive investigation of the biological background of TS. Our SBA analysis identified three significant gene sets after Bonferroni correction, implicating ligand-gated ion channel signaling, lymphocytic, and cell adhesion and transsynaptic signaling processes. MAGMA analysis further supported the involvement of the cell adhesion and trans-synaptic signaling gene set. The lymphocytic gene set was driven by variants in FLT3, raising an intriguing hypothesis for the involvement of a neuroinflammatory element in TS pathogenesis. The indications of involvement of ligand-gated ion channel signaling reinforce the role of GABA in TS, while the association of cell adhesion and trans-synaptic signaling gene set provides additional support for the role of adhesion molecules in neuropsychiatric disorders. This study reinforces previous findings but also provides new insights into the neurobiology of TS.

Abstract Background Nearly half of all mental health disorders develop prior to the age of 15. Early assessments, diagnosis, and treatment are critical to shortening single episodes of care, reducing possible comorbidity and long-term disability. In Norway, approximately 20% of all children and adolescents are experiencing mental health problems. To address this, health officials in Norway have called for the integration of innovative approaches. A clinical decision support system (CDSS) is an innovative, computer-based program that provides health professionals with clinical decision support as they care for patients. CDSS use standardized clinical guidelines and big data to provide guidance and recommendations to clinicians in real-time. IDDEAS (Individualised Digital DEcision Assist System) is a CDSS for diagnosis and treatment of child and adolescent mental health disorders. The aim of IDDEAS is to enhance quality, competency, and efficiency in child and adolescent mental health services (CAMHS). Methods/design IDDEAS is a mixed-methods innovation and research project, which consists of four stages: 1) Assessment of Needs and Preparation of IDDEAS; 2) The Development of IDDEAS CDSS Model; 3) The Evaluation of the IDDEAS CDSS; and, 4) Implementation & Dissemination. Both qualitative and quantitative methods will be used for the evaluation of IDDEAS CDSS model. Child and adolescent psychologists and psychiatrists (n = 30) will evaluate the IDDEAS` usability, acceptability and relevance for diagnosis and treatment of attention-deficit/hyperactivity disorder. Discussion The IDDEAS CDSS model is the first guidelines and data-driven CDSS to improve efficiency of diagnosis and treatment of child and adolescent mental health disorders in Norway. Ultimately, IDDEAS will help to improve patient health outcomes and prevent long-term adverse outcomes by providing each patient with evidence-based, customized clinical care. Trial registration ISRCTN, ISRCTN12094788. Ongoing study, registered prospectively 8 April 2020 https://doi.org/10.1186/ISRCTN12094788

Abstract Background This paper is a systematic review and meta-analysis of the efficacy of available medications for the treatment of restricted/repetitive behavior (RRBs) in Autism Spectrum Disorder (ASD). Method We searched MEDLINE, Embase, PsycINFO, The Cochrane Library (Cochrane Database of Systematic Reviews (CDRS), the Cochrane Central Register of Controlled Trials (CENTRAL), database of Abstracts of Reviews of Effects (DARE)), Scopus, Epistimonikos, Clinicaltrials.gov, and included all randomized controlled trials published after 1993 that were directed at RRBs in patients with ASD of all ages. We extracted the relevant data from the published studies with a predefined data extraction form and assessed the risk of bias. The primary outcomes were change in restricted/repetitive behavior. We performed a meta-analysis using the random effect model and included studies with given mean and standard deviation. This study is registered with PROSPERO number CRD42018092660). Results We identified 14 randomized controlled trials that met initial inclusion criteria. After closer inspection, nine trials – involving 552 patients in total – were included in the final analysis. The meta-analysis found no significant difference between medications (including fluvoxamine, risperidone, fluoxetine, citalopram, oxytocin, N-Acetylcysteine, buspirone) and placebo in the treatment of RRBs in ASD (P = 0.20). Similarly, the sub-group meta-analysis also showed no significant difference between Selective Serotonin Reuptake Inhibitor (SSRIs) and placebo in the treatment of RRBs in ASD (P = 0.68). There was no evidence of publication bias. Conclusion This meta-analysis finds little support for the routine use of medications to treat restricted/repetitive behaviors in Autism Spectrum Disorder. Further research of large, balanced trials with precise assessment tools and long-term follow-up are needed. Trial registration The study protocol is registered in PROSPERO (Reference number: CRD42018092660) .