A. Paul Bevan

BACKGROUND: Human genome sequencing has transformed our understanding of genomic variation and its relevance to health and disease, and is now starting to enter clinical practice for the diagnosis of rare diseases. The question of whether and how some categories of genomic findings should be shared with individual research participants is currently a topic of international debate, and development of robust analytical workflows to identify and communicate clinically relevant variants is paramount. METHODS: The Deciphering Developmental Disorders (DDD) study has developed a UK-wide patient recruitment network involving over 180 clinicians across all 24 regional genetics services, and has performed genome-wide microarray and whole exome sequencing on children with undiagnosed developmental disorders and their parents. After data analysis, pertinent genomic variants were returned to individual research participants via their local clinical genetics team. FINDINGS: Around 80,000 genomic variants were identified from exome sequencing and microarray analysis in each individual, of which on average 400 were rare and predicted to be protein altering. By focusing only on de novo and segregating variants in known developmental disorder genes, we achieved a diagnostic yield of 27% among 1133 previously investigated yet undiagnosed children with developmental disorders, whilst minimising incidental findings. In families with developmentally normal parents, whole exome sequencing of the child and both parents resulted in a 10-fold reduction in the number of potential causal variants that needed clinical evaluation compared to sequencing only the child. Most diagnostic variants identified in known genes were novel and not present in current databases of known disease variation. INTERPRETATION: Implementation of a robust translational genomics workflow is achievable within a large-scale rare disease research study to allow feedback of potentially diagnostic findings to clinicians and research participants. Systematic recording of relevant clinical data, curation of a gene-phenotype knowledge base, and development of clinical decision support software are needed in addition to automated exclusion of almost all variants, which is crucial for scalable prioritisation and review of possible diagnostic variants. However, the resource requirements of development and maintenance of a clinical reporting system within a research setting are substantial. FUNDING: Health Innovation Challenge Fund, a parallel funding partnership between the Wellcome Trust and the UK Department of Health.

Twelve peroxovanadium (pV) compounds, each containing an oxo ligand, one or two peroxo anions, and an ancillary ligand in the inner coordination sphere of V, were synthesized, crystallized, and characterized by 51V NMR as > 95% pure. These compounds activated the insulin receptor kinase (IRK) of cultured hepatoma cells, stimulated lipogenesis in adipocytes, and inhibited the in situ dephosphorylation of autophosphorylated IRs and epidermal growth factor receptors of rat liver endosomes. The phosphotyrosine phosphatase inhibitory and IRK activating potencies of these compounds were linearly correlated (r = 0.74; p < 0.003), decayed in parallel in solution, and varied considerably with the ancillary ligands within these compounds. In vivo administration activated rat liver IRK in parallel with its tyrosine phosphorylation. Co-administration of insulin plus pV was markedly synergistic in both respects. pV administration significantly decreased circulating insulin and plasma glucose concentrations; the latter to levels seen after a dose of insulin yielding > or = 50% occupancy of IRs in vivo. Two compounds (mpV(pic) and mpV(2,6-pdc)) displayed relative specificity as phosphotyrosine phosphatase inhibitors by inhibiting IR dephosphorylation to a significantly greater degree than epidermal growth factor receptor dephosphorylation. Thus, pV compounds are the most potent phosphotyrosine phosphatase inhibitors described to date. Their capacity to activate IRK appears to derive from their phosphotyrosine phosphatase inhibitory activity. Their hypoglycemic action is due to a direct tissue effect.

Ensembl (http://www.ensembl.org/) is a bioinformatics project to organize biological information around the sequences of large genomes. It is a comprehensive source of stable automatic annotation of individual genomes, and of the synteny and orthology relationships between them. It is also a framework for integration of any biological data that can be mapped onto features derived from the genomic sequence. Ensembl is available as an interactive Web site, a set of flat files, and as a complete, portable open source software system for handling genomes. All data are provided without restriction, and code is freely available. Ensembl's aims are to continue to "widen" this biological integration to include other model organisms relevant to understanding human biology as they become available; to "deepen" this integration to provide an ever more seamless linkage between equivalent components in different species; and to provide further classification of functional elements in the genome that have been previously elusive.