In rare disease (RD) research there is a huge need to systematically collect biomaterials, phenotypic and genomic data in a standardized way and to make them Findable, Accessible, Interoperable and Reusable (FAIR). RD-Connect is a 6 years global infrastructure project initiated in November 2012 that links genomic data with patient registries, biobanks, and clinical bioinformatics tools to create a central research resource for RDs. Here we present RD-Connect Registry & Biobank Finder, a tool that helps RD researchers to find RD biobanks and registries and provide information on the availability and accessibility of content in each database. The Finder concentrates information that is currently sparse on different repositories (inventories, websites, scientific journals, technical reports, etc.), including aggregated data and metadata from participating databases. Aggregated data provided by the Finder, if appropriately checked, can be used by researchers who are trying to estimate the prevalence of a RD, to organize a clinical trial on a RD, or to estimate the volume of patients seen by different clinical centers. The Finder is also a portal to other RD-Connect tools, providing a link to the RD-Connect Sample Catalogue, a large inventory of RD biological samples available in participating biobanks for RD research. There are several kinds of users and potential uses for the RD-Connect Registry & Biobank Finder, including researchers collaborating with academia and the industry, dealing with the questions of basic, translational and/or clinical research. As of November 2017 the Finder is populated with aggregated data for 222 registries and 21 biobanks.

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.

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.

The transcription factor TCF4 was confirmed in several large genome-wide association studies as one of the most significant schizophrenia (SZ) susceptibility genes. Transgenic mice moderately overexpressing Tcf4 in forebrain (Tcf4tg) display deficits in fear memory and sensorimotor gating. As second hit, we exposed Tcf4tg animals to isolation rearing (IR), chronic social defeat (SD), enriched environment (EE), or handling control (HC) conditions and examined mice with heterozygous deletion of the exon 4 (Tcf4Ex4δ+/−) to unravel gene-dosage effects. We applied multivariate statistics for behavioral profiling and demonstrate that IR and SD cause strong cognitive deficits of Tcf4tg mice, whereas EE masked the genetic vulnerability. We observed enhanced long-term depression in Tcf4tg mice and enhanced long-term potentiation in Tcf4Ex4δ+/− mice indicating specific gene-dosage effects. Tcf4tg mice showed higher density of immature spines during development as assessed by STED nanoscopy and proteomic analyses of synaptosomes revealed concurrently increased levels of proteins involved in synaptic function and metabolic pathways. We conclude that environmental stress and Tcf4 misexpression precipitate cognitive deficits in 2-hit mouse models of relevance for schizophrenia.