Search

Background: Genome-wide data are increasingly important in the clinical evaluation of human disease. However, the large number of variants observed in individual patients challenges the efficiency and accuracy of diagnostic review. Recent work has shown that systematic integration of clinical phenotype data with genotype information can improve diagnostic workflows and prioritization of filtered rare variants. We have developed visually interactive, analytically transparent analysis software that leverages existing disease catalogs, such as the Online Mendelian Inheritance in Man database (OMIM) and the Human Phenotype Ontology (HPO), to integrate patient phenotype and variant data into ranked diagnostic alternatives. Methods: Our tool, "OMIM Explorer" (http://www.omimexplorer.com), extends the biomedical application of semantic similarity methods beyond those reported in previous studies. The tool also provides a simple interface for translating free-text clinical notes into HPO terms, enabling clinical providers and geneticists to contribute phenotypes to the diagnostic process. The visual approach uses semantic similarity with multidimensional scaling to collapse high-dimensional phenotype and genotype data from an individual into a graphical format that contextualizes the patient within a low-dimensional disease map. The map proposes a differential diagnosis and algorithmically suggests potential alternatives for phenotype queries-in essence, generating a computationally assisted differential diagnosis informed by the individual's personal genome. Visual interactivity allows the user to filter and update variant rankings by interacting with intermediate results. The tool also implements an adaptive approach for disease gene discovery based on patient phenotypes. Results: We retrospectively analyzed pilot cohort data from the Baylor Miraca Genetics Laboratory, demonstrating performance of the tool and workflow in the re-analysis of clinical exomes. Our tool assigned to clinically reported variants a median rank of 2, placing causal variants in the top 1 % of filtered candidates across the 47 cohort cases with reported molecular diagnoses of exome variants in OMIM Morbidmap genes. Our tool outperformed Phen-Gen, eXtasy, PhenIX, PHIVE, and hiPHIVE in the prioritization of these clinically reported variants. Conclusions: Our integrative paradigm can improve efficiency and, potentially, the quality of genomic medicine by more effectively utilizing available phenotype information, catalog data, and genomic knowledge. [ABSTRACT FROM AUTHOR]

Most spontaneous DNA double-strand breaks (DSBs) result from replication-fork breakage. Break-induced replication (BIR), a genome rearrangement-prone repair mechanism that requires the Pol32/POLD3 subunit of eukaryotic DNA Polδ, was proposed to repair broken forks, but how genome destabilization is avoided was unknown. We show that broken fork repair initially uses error-prone Pol32-dependent synthesis, but that mutagenic synthesis is limited to within a few kilobases from the break by Mus81 endonuclease and a converging fork. Mus81 suppresses template switches between both homologous sequences and diverged human Alu repetitive elements, highlighting its importance for stability of highly repetitive genomes. We propose that lack of a timely converging fork or Mus81 may propel genome instability observed in cancer. [ABSTRACT FROM AUTHOR]

Curation and interpretation of copy number variants identified by genome-wide testing is challenged by the large number of events harbored in each personal genome. Conventional determination of phenotypic relevance relies on patterns of higher frequency in affected individuals versus controls; however, an increasing amount of ascertained variation is rare or private to clans. Consequently, frequency data have less utility to resolve pathogenic from benign. One solution is disease-specific algorithms that leverage gene knowledge together with variant frequency to aid prioritization. We used large-scale resources including Gene Ontology, protein-protein interactions and other annotation systems together with a broad set of 83 genes with known associations to epilepsy to construct a pathogenicity score for the phenotype. We evaluated the score for all annotated human genes and applied Bayesian methods to combine the derived pathogenicity score with frequency information from our diagnostic laboratory. Analysis determined Bayes factors and posterior distributions for each gene. We applied our method to subjects with abnormal chromosomal microarray results and confirmed epilepsy diagnoses gathered by electronic medical record review. Genes deleted in our subjects with epilepsy had significantly higher pathogenicity scores and Bayes factors compared to subjects referred for non-neurologic indications. We also applied our scores to identify a recently validated epilepsy gene in a complex genomic region and to reveal candidate genes for epilepsy. We propose a potential use in clinical decision support for our results in the context of genome-wide screening. Our approach demonstrates the utility of integrative data in medical genomics. [ABSTRACT FROM AUTHOR]

Summary De novo copy number variants (dnCNVs) arising at multiple loci in a personal genome have usually been considered to reflect cancer somatic genomic instabilities. We describe a multiple dnCNV (MdnCNV) phenomenon in which individuals with genomic disorders carry five to ten constitutional dnCNVs. These CNVs originate from independent formation incidences, are predominantly tandem duplications or complex gains, exhibit breakpoint junction features reminiscent of replicative repair, and show increased de novo point mutations flanking the rearrangement junctions. The active CNV mutation shower appears to be restricted to a transient perizygotic period. We propose that a defect in the CNV formation process is responsible for the “CNV-mutator state,” and this state is dampened after early embryogenesis. The constitutional MdnCNV phenomenon resembles chromosomal instability in various cancers. Investigations of this phenomenon may provide unique access to understanding genomic disorders, structural variant mutagenesis, human evolution, and cancer biology. [ABSTRACT FROM AUTHOR]