@article {595, title = {Insights into genetics, human biology and disease gleaned from family based genomic studies.}, journal = {Genet Med}, volume = {21}, year = {2019}, month = {2019 04}, pages = {798-812}, abstract = {

Identifying genes and variants contributing to rare disease phenotypes and Mendelian conditions informs biology and medicine, yet potential phenotypic consequences for variation of >75\% of the ~20,000 annotated genes in the human genome are lacking. Technical advances to assess rare variation genome-wide, particularly exome sequencing (ES), enabled establishment in the United States of the National Institutes of Health (NIH)-supported Centers for Mendelian Genomics (CMGs) and have facilitated collaborative studies resulting in~novel "disease gene" discoveries. Pedigree-based genomic studies and rare variant analyses in families with suspected Mendelian conditions have led to the elucidation of hundreds of novel disease genes and highlighted the impact of de novo mutational events, somatic variation underlying nononcologic traits, incompletely penetrant alleles, phenotypes with high locus heterogeneity, and multilocus pathogenic variation. Herein, we highlight CMG collaborative discoveries that have contributed to understanding both rare and common diseases and discuss opportunities for future discovery in single-locus Mendelian disorder genomics. Phenotypic annotation of all human genes; development of bioinformatic tools and analytic methods; exploration of non-Mendelian modes of inheritance including reduced penetrance, multilocus variation, and oligogenic inheritance; construction of allelic series at a locus; enhanced data sharing worldwide; and integration with clinical genomics are explored. Realizing the full contribution of rare disease research to functional annotation of the human genome, and further illuminating human biology and health, will lay the foundation for the Precision Medicine Initiative.

}, keywords = {Databases, Genetic, Genetic Diseases, Inborn, Genetic Heterogeneity, Genetic Predisposition to Disease, Genome, Human, Genomics, Humans, National Institutes of Health (U.S.), Pedigree, United States, Whole Exome Sequencing}, issn = {1530-0366}, doi = {10.1038/s41436-018-0408-7}, author = {Posey, Jennifer E and O{\textquoteright}Donnell-Luria, Anne H and Chong, Jessica X and Harel, Tamar and Jhangiani, Shalini N and Coban Akdemir, Zeynep H and Buyske, Steven and Pehlivan, Davut and Carvalho, Claudia M B and Baxter, Samantha and Sobreira, Nara and Liu, Pengfei and Wu, Nan and Rosenfeld, Jill A and Kumar, Sushant and Avramopoulos, Dimitri and White, Janson J and Doheny, Kimberly F and Witmer, P Dane and Boehm, Corinne and Sutton, V Reid and Muzny, Donna M and Boerwinkle, Eric and G{\"u}nel, Murat and Nickerson, Deborah A and Mane, Shrikant and MacArthur, Daniel G and Gibbs, Richard A and Hamosh, Ada and Lifton, Richard P and Matise, Tara C and Rehm, Heidi L and Gerstein, Mark and Bamshad, Michael J and Valle, David and Lupski, James R} } @article {199, title = {Assessment of incidental findings in 232 whole-exome sequences from the Baylor-Hopkins Center for Mendelian Genomics.}, journal = {Genet Med}, volume = {17}, year = {2015}, month = {2015 Oct}, pages = {782-8}, abstract = {

PURPOSE: In March 2013 the American College of Medical Genetics and Genomics published a list of 56 genes with the recommendation that pathogenic and likely pathogenic variants detected incidentally by clinical sequencing be reported to patients. As an initial step in determining the practical consequences of this recommendation in the research setting, we searched for variants in these genes in 232 whole-exome sequences from the Baylor-Hopkins Center for Mendelian Genomics.

METHODS: We identified rare, nonsynonymous, and splicing single-nucleotide variants and insertions/deletions and assessed variant classification using the Human Gene Mutation, Emory, and ClinVar databases. We analyzed the burden of mutation in each of the 56 genes and determined which variants should be reported to patients.

RESULTS: Our filtering resulted in 249 distinct variants, with a mean of 1.69 variants per individual. Half of these were novel missense mutations not classified by any of the three reference databases. Of 101 variants listed in the Human Gene Mutation Database, 48 were also in ClinVar and 3 were also in Emory; half of these shared variants were classified discordantly between databases. Some genes consistently had greater variation than others. In total, 0.86\% of individuals had a reportable incidental variant.

CONCLUSION: These observations demonstrate some current challenges of assessing phenotypic consequences of incidental variants for counseling patients.

}, keywords = {Databases, Nucleic Acid, Exome, Female, Genetic Diseases, Inborn, Genomics, High-Throughput Nucleotide Sequencing, Humans, Incidental Findings, Male, Mutation, Polymorphism, Single Nucleotide}, issn = {1530-0366}, doi = {10.1038/gim.2014.196}, author = {Jurgens, Julie and Ling, Hua and Hetrick, Kurt and Pugh, Elizabeth and Schiettecatte, Fran{\c c}ois and Doheny, Kimberly and Hamosh, Ada and Avramopoulos, Dimitri and Valle, David and Sobreira, Nara} } @article {193, title = {New tools for Mendelian disease gene identification: PhenoDB variant analysis module; and GeneMatcher, a web-based tool for linking investigators with an interest in the same gene.}, journal = {Hum Mutat}, volume = {36}, year = {2015}, month = {2015 Apr}, pages = {425-31}, abstract = {

Identifying the causative variant from among the thousands identified by whole-exome sequencing or whole-genome sequencing is a formidable challenge. To make this process as efficient and flexible as possible, we have developed a Variant Analysis Module coupled to our previously described Web-based phenotype intake tool, PhenoDB (http://researchphenodb.net and http://phenodb.org). When a small number of candidate-causative variants have been identified in a study of a particular patient or family, a second, more difficult challenge becomes proof of causality for any given variant. One approach to this problem is to find other cases with a similar phenotype and mutations in the same candidate gene. Alternatively, it may be possible to develop biological evidence for causality, an approach that is assisted by making connections to basic scientists studying the gene of interest, often in the setting of a model organism. Both of these strategies benefit from an open access, online site where individual clinicians and investigators could post genes of interest. To this end, we developed GeneMatcher (http://genematcher.org), a freely accessible Website that enables connections between clinicians and researchers across the world who share an interest in the same gene(s).

}, keywords = {Computational Biology, Databases, Genetic, Genetic Association Studies, Genetic Diseases, Inborn, Genetic Variation, Genomics, Internet, Phenotype, Software, Web Browser}, issn = {1098-1004}, doi = {10.1002/humu.22769}, author = {Sobreira, Nara and Schiettecatte, Fran{\c c}ois and Boehm, Corinne and Valle, David and Hamosh, Ada} } @article {310, title = {PhenoDB: a new web-based tool for the collection, storage, and analysis of phenotypic features.}, journal = {Hum Mutat}, volume = {34}, year = {2013}, month = {2013 Apr}, pages = {566-71}, abstract = {

To interpret whole exome/genome sequence data for clinical and research purposes, comprehensive phenotypic information, knowledge of pedigree structure, and results of previous clinical testing are essential. With these requirements in mind and to meet the needs of the Centers for Mendelian Genomics project, we have developed PhenoDB (http://phenodb.net), a secure, Web-based portal for entry, storage, and analysis of phenotypic and other clinical information. The phenotypic features are organized hierarchically according to the major headings and subheadings of the Online Mendelian Inheritance in Man (OMIM{\textregistered}) clinical synopses, with further subdivisions according to structure and function. Every string allows for a free-text entry. All of the approximately 2,900 features use the preferred term from Elements of Morphology and are fully searchable and mapped to the Human Phenotype Ontology and Elements of Morphology. The PhenoDB allows for ascertainment of relevant information from a case in a family or cohort, which is then searchable by family, OMIM number, phenotypic feature, mode of inheritance, genes screened, and so on. The database can also be used to format phenotypic data for submission to dbGaP for appropriately consented individuals. PhenoDB was built using Django, an open source Web development tool, and is freely available through the Johns Hopkins McKusick-Nathans Institute of Genetic Medicine (http://phenodb.net).

}, keywords = {Databases, Factual, Genomics, Humans, Internet, Medical Informatics, Phenotype, Software}, issn = {1098-1004}, doi = {10.1002/humu.22283}, author = {Hamosh, Ada and Sobreira, Nara and Hoover-Fong, Julie and Sutton, V Reid and Boehm, Corinne and Schiettecatte, Fran{\c c}ois and Valle, David} } @article {325, title = {The Centers for Mendelian Genomics: a new large-scale initiative to identify the genes underlying rare Mendelian conditions.}, journal = {Am J Med Genet A}, volume = {158A}, year = {2012}, month = {2012 Jul}, pages = {1523-5}, abstract = {

Next generation exome sequencing (ES) and whole genome sequencing (WGS) are new powerful tools for discovering the gene(s) that underlie Mendelian disorders. To accelerate these discoveries, the National Institutes of Health has established three Centers for Mendelian Genomics (CMGs): the Center for Mendelian Genomics at the University of Washington; the Center for Mendelian Genomics at Yale University; and the Baylor-Johns Hopkins Center for Mendelian Genomics at Baylor College of Medicine and Johns Hopkins University. The CMGs will provide ES/WGS and extensive analysis expertise at no cost to collaborating investigators where the causal gene(s) for a Mendelian phenotype has yet to be uncovered. Over the next few years and in collaboration with the global human genetics community, the CMGs hope to facilitate the identification of the genes underlying a very large fraction of all Mendelian disorders; see http://mendelian.org.

}, keywords = {Academies and Institutes, Genetic Diseases, Inborn, Genetics, Medical, Genome, Human, Genome-Wide Association Study, Genomics, High-Throughput Nucleotide Sequencing, Humans}, issn = {1552-4833}, doi = {10.1002/ajmg.a.35470}, author = {Bamshad, Michael J and Shendure, Jay A and Valle, David and Hamosh, Ada and Lupski, James R and Gibbs, Richard A and Boerwinkle, Eric and Lifton, Richard P and Gerstein, Mark and G{\"u}nel, Murat and Mane, Shrikant and Nickerson, Deborah A} }