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em BORIS: Bern Open Repository and Information System - Berna - Suiça


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The current status of child and adolescent psychiatric genetics appears promising in light of the initiation of genome-wide association studies (GWAS) for diverse polygenic disorders and the molecular elucidation of monogenic Rett syndrome, for which recent functional studies provide hope for pharmacological treatment strategies. Within the last 50 years, tremendous progress has been made in linking genetic variation to behavioral phenotypes and psychiatric disorders. We summarize the major findings of the Human Genome Project and dwell on largely unsuccessful candidate gene and linkage studies. GWAS for the first time offer the possibility to detect single nucleotide polymorphisms and copy number variants without a priori hypotheses as to their molecular etiology. At the same time it is becoming increasingly clear that very large sample sizes are required in order to enable genome wide significant findings, thus necessitating further large-scaled ascertainment schemes for the successful elucidation of the molecular genetics of childhood and adolescent psychiatric disorders. We conclude by reflecting on different scenarios for future research into the molecular basis of early onset psychiatric disorders. This review represents the introductory article of this special issue of the European Child and Adolescent Psychiatry.

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It is now generally accepted that complex mental disorders are the results of interplay between genetic and environmental factors. This holds out the prospect that by studying G x E interplay we can explain individual variation in vulnerability and resilience to environmental hazards in the development of mental disorders. Furthermore studying G x E findings may give insights in neurobiological mechanisms of psychiatric disorder and so improve individualized treatment and potentially prevention. In this paper, we provide an overview of the state of field with regard to G x E in mental disorders. Strategies for G x E research are introduced. G x E findings from selected mental disorders with onset in childhood or adolescence are reviewed [such as depressive disorders, attention-deficit/hyperactivity disorder (ADHD), obesity, schizophrenia and substance use disorders]. Early seminal studies provided evidence for G x E in the pathogenesis of depression implicating 5-HTTLPR, and conduct problems implicating MAOA. Since then G x E effects have been seen across a wide range of mental disorders (e.g., ADHD, anxiety, schizophrenia, substance abuse disorder) implicating a wide range of measured genes and measured environments (e.g., pre-, peri- and postnatal influences of both a physical and a social nature). To date few of these G x E effects have been sufficiently replicated. Indeed meta-analyses have raised doubts about the robustness of even the most well studied findings. In future we need larger, sufficiently powered studies that include a detailed and sophisticated characterization of both phenotype and the environmental risk.

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Statistical models have been recently introduced in computational orthopaedics to investigate the bone mechanical properties across several populations. A fundamental aspect for the construction of statistical models concerns the establishment of accurate anatomical correspondences among the objects of the training dataset. Various methods have been proposed to solve this problem such as mesh morphing or image registration algorithms. The objective of this study is to compare a mesh-based and an image-based statistical appearance model approaches for the creation of nite element(FE) meshes. A computer tomography (CT) dataset of 157 human left femurs was used for the comparison. For each approach, 30 finite element meshes were generated with the models. The quality of the obtained FE meshes was evaluated in terms of volume, size and shape of the elements. Results showed that the quality of the meshes obtained with the image-based approach was higher than the quality of the mesh-based approach. Future studies are required to evaluate the impact of this finding on the final mechanical simulations.