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High-throughput experimental methods such as medical sequencing and genome-wide association studies (GWAS) identify increasingly large numbers of potential relations between genetic variants and diseases. Both biological complexity (millions of potential gene-disease associations) and the accelerating rate of data production necessitate computational approaches to prioritize and rationalize potential gene-disease relations. Here, we use concept profile technology to expose from the biomedical literature both explicitly stated gene-disease relations (the explicitome) and a much larger set of implied gene-disease associations (the implicitome). Implicit relations are largely unknown to, or are even unintended by the original authors, but they vastly extend the reach of existing biomedical knowledge for identification and interpretation of gene-disease associations. The implicitome can be used in conjunction with experimental data resources to rationalize both known and novel associations. We demonstrate the usefulness of the implicitome by rationalizing known and novel gene-disease associations, including those from GWAS. To facilitate the re-use of implicit gene-disease associations, we publish our data in compliance with FAIR Data Publishing recommendations [] using nanopublications. An online tool () is available to explore established and potential gene-disease associations in the context of other biomedical relations. [ABSTRACT FROM AUTHOR]

A genetic contribution to a broad range of epilepsies has been postulated, and particularly copy number variations (CNVs) have emerged as significant genetic risk factors. However, the role of CNVs in patients with epilepsies with complex phenotypes is not known. Therefore, we investigated the role of CNVs in patients with unclassified epilepsies and complex phenotypes. A total of 222 patients from three European countries, including patients with structural lesions on magnetic resonance imaging (MRI), dysmorphic features, and multiple congenital anomalies, were clinically evaluated and screened for CNVs. MRI findings including acquired or developmental lesions and patient characteristics were subdivided and analyzed in subgroups. MRI data were available for 88.3% of patients, of whom 41.6% had abnormal MRI findings. Eighty-eight rare CNVs were discovered in 71 out of 222 patients (31.9%). Segregation of all identified variants could be assessed in 42 patients, 11 of which were de novo. The frequency of all structural variants and de novo variants was not statistically different between patients with or without MRI abnormalities or MRI subcategories. Patients with dysmorphic features were more likely to carry a rare CNV. Genome-wide screening methods for rare CNVs may provide clues for the genetic etiology in patients with a broader range of epilepsies than previously anticipated, including in patients with various brain anomalies detectable by MRI. Performing genome-wide screens for rare CNVs can be a valuable contribution to the routine diagnostic workup in patients with a broad range of childhood epilepsies. [ABSTRACT FROM AUTHOR]