@article {88, title = {A visual and curatorial approach to clinical variant prioritization and disease gene discovery in genome-wide diagnostics.}, journal = {Genome Med}, volume = {8}, year = {2016}, month = {2016 Feb 02}, pages = {13}, abstract = {

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{\textquoteright}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.

}, keywords = {Computational Biology, Diagnosis, Differential, Disease, Genetic Variation, Genome-Wide Association Study, Humans, Phenotype, Pilot Projects, Retrospective Studies, Software}, issn = {1756-994X}, doi = {10.1186/s13073-016-0261-8}, author = {James, Regis A and Campbell, Ian M and Chen, Edward S and Boone, Philip M and Rao, Mitchell A and Bainbridge, Matthew N and Lupski, James R and Yang, Yaping and Eng, Christine M and Posey, Jennifer E and Shaw, Chad A} } @article {151, title = {Non-coding genetic variants in human disease.}, journal = {Hum Mol Genet}, volume = {24}, year = {2015}, month = {2015 Oct 15}, pages = {R102-10}, abstract = {

Genetic variants, including single-nucleotide variants (SNVs) and copy number variants (CNVs), in the non-coding regions of the human genome can play an important role in human traits and complex diseases. Most of the genome-wide association study (GWAS) signals map to non-coding regions and potentially point to non-coding variants, whereas their functional interpretation is challenging. In this review, we discuss the human non-coding variants and their contributions to human diseases in the following four parts. (i) Functional annotations of non-coding SNPs mapped by GWAS: we discuss recent progress revealing some of the molecular mechanisms for GWAS signals affecting gene function. (ii) Technical progress in interpretation of non-coding variants: we briefly describe some of the technologies for functional annotations of non-coding variants, including the methods for genome-wide mapping of chromatin interaction, computational tools for functional predictions and the new genome editing technologies useful for dissecting potential functional consequences of non-coding variants. (iii) Non-coding CNVs in human diseases: we review our emerging understanding the role of non-coding CNVs in human disease. (iv) Compound inheritance of large genomic deletions and non-coding variants: compound inheritance at a locus consisting of coding variants plus non-coding ones is described.

}, keywords = {Animals, Disease, DNA Copy Number Variations, Genetic Variation, Genome-Wide Association Study, Humans, Polymorphism, Single Nucleotide, Regulatory Sequences, Nucleic Acid}, issn = {1460-2083}, doi = {10.1093/hmg/ddv259}, author = {Zhang, Feng and Lupski, James R} } @article {220, title = {A drosophila genetic resource of mutants to study mechanisms underlying human genetic diseases.}, journal = {Cell}, volume = {159}, year = {2014}, month = {2014 Sep 25}, pages = {200-214}, abstract = {

Invertebrate model systems are powerful tools for studying human disease owing to their genetic tractability and ease of screening. We conducted a mosaic genetic screen of lethal mutations on the Drosophila X chromosome to identify genes required for the development, function, and maintenance of the nervous system. We identified 165 genes, most of whose function has not been studied in vivo. In parallel, we investigated rare variant alleles in 1,929 human exomes from families with unsolved Mendelian disease. Genes that are essential in flies and have multiple human homologs were found to be likely to be associated with human diseases. Merging the human data sets with the fly genes allowed us to identify disease-associated mutations in six families and to provide insights into microcephaly associated with brain dysgenesis. This bidirectional synergism between fly genetics and human genomics facilitates the functional annotation of evolutionarily conserved genes involved in human health.

}, keywords = {Animals, Disease, Disease Models, Animal, Drosophila melanogaster, Genetic Testing, Humans, Inheritance Patterns, RNA Interference, X Chromosome}, issn = {1097-4172}, doi = {10.1016/j.cell.2014.09.002}, author = {Yamamoto, Shinya and Jaiswal, Manish and Charng, Wu-Lin and Gambin, Tomasz and Karaca, Ender and Mirzaa, Ghayda and Wiszniewski, Wojciech and Sandoval, Hector and Haelterman, Nele A and Xiong, Bo and Zhang, Ke and Bayat, Vafa and David, Gabriela and Li, Tongchao and Chen, Kuchuan and Gala, Upasana and Harel, Tamar and Pehlivan, Davut and Penney, Samantha and Vissers, Lisenka E L M and de Ligt, Joep and Jhangiani, Shalini N and Xie, Yajing and Tsang, Stephen H and Parman, Yesim and Sivaci, Merve and Battaloglu, Esra and Muzny, Donna and Wan, Ying-Wooi and Liu, Zhandong and Lin-Moore, Alexander T and Clark, Robin D and Curry, Cynthia J and Link, Nichole and Schulze, Karen L and Boerwinkle, Eric and Dobyns, William B and Allikmets, Rando and Gibbs, Richard A and Chen, Rui and Lupski, James R and Wangler, Michael F and Bellen, Hugo J} }