Data calibration and reduction allows to visualize behavioural profiles of psychosocial influences in mice towards clinical domains.

Psychosocial stress-particularly in combination with genetic vulnerability-is a critical environmental risk factor for psychiatric diseases in humans. Isolation rearing (IR) and social defeat (SD) paradigms model psychosocial risk factors in rodents, while enriched environment (EE) protects them from behavioural deficits. Studying the influence of various environmental conditions, e.g., on genetic mouse models can help to dissect the complex gene-environment relationships underlying human psychiatric diseases. Such studies may require analysing multiple mouse cohorts; however, the comparability of behavioural experiments is challenging and often compromised by practical limitations such as group sizes and influences of handling. Therefore, protocol standardization as well as appropriate statistical normalization is necessary to compare different experiments. In this study, we analysed two independent cohorts to compare the behavioural profiles of wild-type male mice subjected to IR and SD. In both cases, EE conditions served as a reference. Multivariate statistics was applied to merge the data from individual measures into broader categories (such as curiosity, anxiety and fear memory) by estimating their calibrated joint effect within a category. Plotting and overlaying these calibrated effect sizes in a single graph allowed intuitive comparison of IR and SD behavioural profiles. This approach allows analysing multiple behavioural tests at once, which is more relevant to psychiatric syndromes than focusing on single behavioural measures. Our method revealed that motivation and fear memory are impaired by both conditions, whereas ambulation and pain sensitivity are affected only by IR and curiosity is mainly diminished upon SD. Thus, IR could be a paradigm of choice in studies focusing on positive symptoms, while SD might be more relevant for negative and cognitive symptoms.

RD-Connect, NeurOmics and EURenOmics: collaborative European initiative for rare diseases.

Although individually uncommon, rare diseases (RDs) collectively affect 6-8% of the population. The unmet need of the rare disease community was recognized by the European Commission which in 2012 funded three flagship projects, RD-Connect, NeurOmics, and EURenOmics, to help move the field forward with the ambition of advancing -omics research and data sharing at their core in line with the goals of IRDiRC (International Rare Disease Research Consortium). NeurOmics and EURenOmics generate -omics data and improve diagnosis and therapy in rare renal and neurological diseases, with RD-Connect developing an infrastructure to facilitate the sharing, systematic integration and analysis of these data. Here, we summarize the achievements of these three projects, their impact on the RD community and their vision for the future. We also report from the Joint Outreach Day organized by the three projects on the 3rd of May 2017 in Berlin. The workshop stimulated an open, multi-stakeholder discussion on the challenges of the rare diseases, and highlighted the cross-project cooperation and the common goal: the use of innovative genomic technologies in rare disease research.