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Genetic pleiotropy is abundant across spatially distributed brain characteristics derived from one neuroimaging modality (e.g. structural, functional or diffusion magnetic resonance imaging [MRI]). A better understanding of pleiotropy across modalities could inform us on the integration of brain function, micro- and macrostructure. Here we show extensive genetic overlap across neuroimaging modalities at a locus and gene level in the UK Biobank (N = 34,029) and ABCD Study (N = 8607). When jointly analysing phenotypes derived from structural, functional and diffusion MRI in a genome-wide association study (GWAS) with the Multivariate Omnibus Statistical Test (MOSTest), we boost the discovery of loci and genes beyond previously identified effects for each modality individually. Cross-modality genes are involved in fundamental biological processes and predominantly expressed during prenatal brain development. We additionally boost prediction of psychiatric disorders by conditioning independent GWAS on our multimodal multivariate GWAS. These findings shed light on the shared genetic mechanisms underlying variation in brain morphology, functional connectivity, and tissue composition.

Satisfaction with the detection process of autism and its determinants was investigated using data from the Autism Spectrum Disorder in the European Union (2015–2018) network. A total of 1342 family members, including 1278 parents, completed an online survey collecting information about their experience and satisfaction with the early detection of autism in their child. Overall, the level of satisfaction varied considerably from one respondent to another. Difficulty in finding information about detection services, lack of professional guidance and support in response to first concerns, finding a diagnostic service on one’s own, and a delay of more than 4 months between the confirmation of concerns and the first appointment with a specialist were all experiences individually associated with greater odds of being less satisfied. Using a dominance analysis approach, we further identified professional guidance and support in response to first concerns as the most important predictor of the level of satisfaction. These findings highlight the aspects of the process that need to be improved to enhance the experience of the detection process and are therefore relevant to guide health administrations toward actions to be implemented to this effect.

The Autism Spectrum Disorders in the European Union (ASDEU) survey investigated local services’ use experiences of autistic adults, carers and professionals with interventions for autistic adults. The majority of the 697 participants experienced recommended considerations prior to deciding on intervention and during the intervention plan and implementation. Psychosocial interventions were the most commonly experienced interventions, while pharmacological interventions NOT recommended for core autistic symptoms were reported by fairly large proportions of participants. Family interventions were experienced slightly more commonly by carers than adults or professionals. Less than the 26% of autistic adult responders who had experienced challenging behaviors reported receiving an intervention to change them. These results provide insights for improving gaps in service provision of interventions among autistic adults.

Early services for ASD need to canvas the opinions of both parents and professionals. These opinions are seldom compared in the same research study. This study aims to ascertain the views of families and professionals on early detection, diagnosis and intervention services for young children with ASD. An online survey compiled and analysed data from 2032 respondents across 14 European countries (60.9% were parents; 39.1% professionals). Using an ordinal scale from 1 to 7, parents’ opinions were more negative (mean = 4.6; SD 2.2) compared to those of professionals (mean = 4.9; SD 1.5) when reporting satisfaction with services. The results suggest services should take into account child’s age, delays in accessing services, and active stakeholders’ participation when looking to improve services.

Contains fulltext : 208684.pdf (publisher's version ) (Open Access), The brain is the most complex of human organs, and the pathophysiology underlying abnormal brain function in psychiatric disorders is largely unknown. Despite the rapid development of diagnostic tools and treatments in most areas of medicine, our understanding of mental disorders and their treatment has made limited progress during the last decades. While recent advances in genetics and neuroscience have a large potential, the complexity and multidimensionality of the brain processes hinder the discovery of disease mechanisms that would link genetic findings to clinical symptoms and behavior. This applies also to schizophrenia, for which genome-wide association studies have identified a large number of genetic risk loci, spanning hundreds of genes with diverse functionalities. Importantly, the multitude of the associated variants and their prevalence in the healthy population limit the potential of a reductionist functional genetics approach as a stand-alone solution to discover the disease pathology. In this review, we outline the key concepts of a "biophysical psychiatry," an approach that employs large-scale mechanistic, biophysics-founded computational modelling to increase transdisciplinary understanding of the pathophysiology and strive toward robust predictions. We discuss recent scientific advances that allow a synthesis of previously disparate fields of psychiatry, neurophysiology, functional genomics, and computational modelling to tackle open questions regarding the pathophysiology of heritable mental disorders. We argue that the complexity of the increasing amount of genetic data exceeds the capabilities of classical experimental assays and requires computational approaches. Biophysical psychiatry, based on modelling diseased brain networks using existing and future knowledge of basic genetic, biochemical, and functional properties on a single neuron to a microcircuit level, may allow a leap forward in deriving interpretable biomarkers and move the field

Contains fulltext : 208684.pdf (publisher's version ) (Open Access), The brain is the most complex of human organs, and the pathophysiology underlying abnormal brain function in psychiatric disorders is largely unknown. Despite the rapid development of diagnostic tools and treatments in most areas of medicine, our understanding of mental disorders and their treatment has made limited progress during the last decades. While recent advances in genetics and neuroscience have a large potential, the complexity and multidimensionality of the brain processes hinder the discovery of disease mechanisms that would link genetic findings to clinical symptoms and behavior. This applies also to schizophrenia, for which genome-wide association studies have identified a large number of genetic risk loci, spanning hundreds of genes with diverse functionalities. Importantly, the multitude of the associated variants and their prevalence in the healthy population limit the potential of a reductionist functional genetics approach as a stand-alone solution to discover the disease pathology. In this review, we outline the key concepts of a "biophysical psychiatry," an approach that employs large-scale mechanistic, biophysics-founded computational modelling to increase transdisciplinary understanding of the pathophysiology and strive toward robust predictions. We discuss recent scientific advances that allow a synthesis of previously disparate fields of psychiatry, neurophysiology, functional genomics, and computational modelling to tackle open questions regarding the pathophysiology of heritable mental disorders. We argue that the complexity of the increasing amount of genetic data exceeds the capabilities of classical experimental assays and requires computational approaches. Biophysical psychiatry, based on modelling diseased brain networks using existing and future knowledge of basic genetic, biochemical, and functional properties on a single neuron to a microcircuit level, may allow a leap forward in deriving interpretable biomarkers and move the field

Contains fulltext : 208684.pdf (publisher's version ) (Open Access), The brain is the most complex of human organs, and the pathophysiology underlying abnormal brain function in psychiatric disorders is largely unknown. Despite the rapid development of diagnostic tools and treatments in most areas of medicine, our understanding of mental disorders and their treatment has made limited progress during the last decades. While recent advances in genetics and neuroscience have a large potential, the complexity and multidimensionality of the brain processes hinder the discovery of disease mechanisms that would link genetic findings to clinical symptoms and behavior. This applies also to schizophrenia, for which genome-wide association studies have identified a large number of genetic risk loci, spanning hundreds of genes with diverse functionalities. Importantly, the multitude of the associated variants and their prevalence in the healthy population limit the potential of a reductionist functional genetics approach as a stand-alone solution to discover the disease pathology. In this review, we outline the key concepts of a "biophysical psychiatry," an approach that employs large-scale mechanistic, biophysics-founded computational modelling to increase transdisciplinary understanding of the pathophysiology and strive toward robust predictions. We discuss recent scientific advances that allow a synthesis of previously disparate fields of psychiatry, neurophysiology, functional genomics, and computational modelling to tackle open questions regarding the pathophysiology of heritable mental disorders. We argue that the complexity of the increasing amount of genetic data exceeds the capabilities of classical experimental assays and requires computational approaches. Biophysical psychiatry, based on modelling diseased brain networks using existing and future knowledge of basic genetic, biochemical, and functional properties on a single neuron to a microcircuit level, may allow a leap forward in deriving interpretable biomarkers and move the field

Floating-Harbor syndrome (FHS) is a rare autosomal dominant syndrome characterized by short stature with delayed bone age, retarded speech development, intellectual disability and dysmorphic facial features. Recently, dominant mutations almost exclusively clustered in the final exon of the Snf2-related CREBBP activator protein (SRCAP) gene were identified to cause FHS. Here, we report a boy with short stature, speech delay, mild intellectual disability, dysmorphic features, and with genetically confirmed FHS. To the best of our knowledge, this is the first molecularly confirmed case with this syndrome reported in Romania. An intensive program of cognitive and speech stimulation, as well as yearly neurological, psychological, ophthalmological, otorhinolaryngological, pediatric and endocrinological monitoring for our patient were designed. We propose a checklist of clinical features suggestive of FHS, based on the main clinical features, in order to facilitate the diagnosis and clinical management of this rare condition.

Floating-Harbor syndrome (FHS) is a rare autosomal dominant syndrome characterized by short stature with delayed bone age, retarded speech development, intellectual disability and dysmorphic facial features. Recently, dominant mutations almost exclusively clustered in the final exon of the Snf2-related CREBBP activator protein (SRCAP) gene were identified to cause FHS. Here, we report a boy with short stature, speech delay, mild intellectual disability, dysmorphic features, and with genetically confirmed FHS. To the best of our knowledge, this is the first molecularly confirmed case with this syndrome reported in Romania. An intensive program of cognitive and speech stimulation, as well as yearly neurological, psychological, ophthalmological, otorhinolaryngological, pediatric and endocrinological monitoring for our patient were designed. We propose a checklist of clinical features suggestive of FHS, based on the main clinical features, in order to facilitate the diagnosis and clinical management of this rare condition.

Item does not contain fulltext, Little is known about use of early interventions for autism spectrum disorder in Europe. Parents of children with autism spectrum disorder aged 7 years or younger (N = 1680) were recruited through parent organisations in 18 European countries and completed an online survey about the interventions their child received. There was considerable variation in use of interventions, and in some countries more than 20% of children received no intervention at all. The most frequently reported interventions were speech and language therapy (64%) and behavioural, developmental and relationship-based interventions (55%). In some parts of Europe, use of behavioural, developmental and relationship-based interventions was associated with higher parental educational level and time passed since diagnosis, rather than with child characteristics. These findings highlight the need to monitor use of intervention for children with autism spectrum disorder in Europe in order to contrast inequalities.

Item does not contain fulltext, Little is known about use of early interventions for autism spectrum disorder in Europe. Parents of children with autism spectrum disorder aged 7 years or younger (N = 1680) were recruited through parent organisations in 18 European countries and completed an online survey about the interventions their child received. There was considerable variation in use of interventions, and in some countries more than 20% of children received no intervention at all. The most frequently reported interventions were speech and language therapy (64%) and behavioural, developmental and relationship-based interventions (55%). In some parts of Europe, use of behavioural, developmental and relationship-based interventions was associated with higher parental educational level and time passed since diagnosis, rather than with child characteristics. These findings highlight the need to monitor use of intervention for children with autism spectrum disorder in Europe in order to contrast inequalities.

Little is known about use of early interventions for autism spectrum disorder in Europe. Parents of children with autism spectrum disorder aged 7 years or younger (N = 1680) were recruited through parent organisations in 18 European countries and completed an online survey about the interventions their child received. There was considerable variation in use of interventions, and in some countries more than 20% of children received no intervention at all. The most frequently reported interventions were speech and language therapy (64%) and behavioural, developmental and relationship-based interventions (55%). In some parts of Europe, use of behavioural, developmental and relationship-based interventions was associated with higher parental educational level and time passed since diagnosis, rather than with child characteristics. These findings highlight the need to monitor use of intervention for children with autism spectrum disorder in Europe in order to contrast inequalities.