@article {703, title = {COL4A1 mutations as a potential novel cause of autosomal dominant CAKUT in humans.}, journal = {Hum Genet}, volume = {138}, year = {2019}, month = {2019 Oct}, pages = {1105-1115}, abstract = {

Congenital anomalies of the kidney and urinary tract (CAKUT) are the most common cause of chronic kidney disease (~ 45\%) that manifests before 30~years of age. The genetic locus containing COL4A1 (13q33-34) has been implicated in vesicoureteral reflux (VUR), but mutations in COL4A1 have not been reported in CAKUT. We hypothesized that COL4A1 mutations cause CAKUT in humans. We performed whole exome sequencing (WES) in 550 families with CAKUT. As negative control cohorts we used WES sequencing data from patients with nephronophthisis (NPHP) with no genetic cause identified (n = 257) and with nephrotic syndrome (NS) due to monogenic causes (n = 100). We identified a not previously reported heterozygous missense variant in COL4A1 in three siblings with isolated VUR. When examining 549 families with CAKUT, we identified nine additional different heterozygous missense mutations in COL4A1 in 11 individuals from 11 unrelated families with CAKUT, while no COL4A1 mutations were identified in a control cohort with NPHP and only one in the cohort with NS. Most individuals (12/14) had isolated CAKUT with no extrarenal features. The predominant phenotype was VUR (9/14). There were no clinical features of the COL4A1-related disorders (e.g., HANAC syndrome, porencephaly, tortuosity of retinal arteries). Whereas COL4A1-related disorders are typically caused by glycine substitutions in the collagenous domain (84.4\% of variants), only one variant in our cohort is a glycine substitution within the collagenous domain (1/10). We identified heterozygous COL4A1 mutations as a potential novel autosomal dominant cause of CAKUT that is allelic to the established COL4A1-related disorders and predominantly caused by non-glycine substitutions.

}, keywords = {Alleles, Amino Acid Substitution, Collagen Type IV, Computational Biology, Congenital Abnormalities, Databases, Genetic, DNA Mutational Analysis, Evolution, Molecular, Female, Genetic Association Studies, Genetic Loci, Genomics, Heterozygote, Humans, Kidney, Kidney Diseases, Cystic, Male, Mutation, Nephrotic Syndrome, Phenotype, Urinary Tract, Web Browser, Whole Exome Sequencing}, issn = {1432-1203}, doi = {10.1007/s00439-019-02042-4}, author = {Kitzler, Thomas M and Schneider, Ronen and Kohl, Stefan and Kolvenbach, Caroline M and Connaughton, Dervla M and Dai, Rufeng and Mann, Nina and Nakayama, Makiko and Majmundar, Amar J and Wu, Chen-Han W and Kari, Jameela A and El Desoky, Sherif M and Senguttuvan, Prabha and Bogdanovic, Radovan and Staji{\'c}, Natasa and Valivullah, Zaheer and Lek, Monkol and Mane, Shrikant and Lifton, Richard P and Tasic, Velibor and Shril, Shirlee and Hildebrandt, Friedhelm} } @article {411, title = {denovo-db: a compendium of human de novo variants.}, journal = {Nucleic Acids Res}, volume = {45}, year = {2017}, month = {2017 01 04}, pages = {D804-D811}, abstract = {

Whole-exome and whole-genome sequencing have facilitated the large-scale discovery of de novo variants in human disease. To date, most de novo discovery through next-generation sequencing focused on congenital heart disease and neurodevelopmental disorders (NDDs). Currently, de novo variants are one of the most significant risk factors for NDDs with a substantial overlap of genes involved in more than one NDD. To facilitate better usage of published data, provide standardization of annotation, and improve accessibility, we created denovo-db (http://denovo-db.gs.washington.edu), a database for human de novo variants. As of July 2016, denovo-db contained 40 different studies and 32,991 de novo variants from 23,098 trios. Database features include basic variant information (chromosome location, change, type); detailed annotation at the transcript and protein levels; severity scores; frequency; validation status; and, most importantly, the phenotype of the individual with the variant. We included a feature on our browsable website to download any query result, including a downloadable file of the full database with additional variant details. denovo-db provides necessary information for researchers to compare their data to other individuals with the same phenotype and also to controls allowing for a better understanding of the biology of de novo variants and their contribution to disease.

}, keywords = {Computational Biology, Databases, Nucleic Acid, Genetic Association Studies, Genetic Variation, Germ-Line Mutation, Humans, Molecular Sequence Annotation, Polymorphism, Single Nucleotide, Web Browser}, issn = {1362-4962}, doi = {10.1093/nar/gkw865}, author = {Turner, Tychele N and Yi, Qian and Krumm, Niklas and Huddleston, John and Hoekzema, Kendra and F Stessman, Holly A and Doebley, Anna-Lisa and Bernier, Raphael A and Nickerson, Deborah A and Eichler, Evan E} } @article {440, title = {Matchmaker Exchange.}, journal = {Curr Protoc Hum Genet}, volume = {95}, year = {2017}, month = {2017 10 18}, pages = {9.31.1-9.31.15}, abstract = {

In well over half of the individuals with rare disease who undergo clinical or research next-generation sequencing, the responsible gene cannot be determined. Some reasons for this relatively low yield include unappreciated phenotypic heterogeneity; locus heterogeneity; somatic and germline mosaicism; variants of uncertain functional significance; technically inaccessible areas of the genome; incorrect mode of inheritance investigated; and inadequate communication between clinicians and basic scientists with knowledge of particular genes, proteins, or biological systems. To facilitate such communication and improve the search for patients or model organisms with similar phenotypes and variants in specific candidate genes, we have developed the Matchmaker Exchange (MME). MME was created to establish a federated network connecting databases of genomic and phenotypic data using a common application programming interface (API). To date, seven databases can exchange data using the API (GeneMatcher, PhenomeCentral, DECIPHER, MyGene2, matchbox, Australian Genomics Health Alliance Patient Archive, and Monarch Initiative; the latter included for model organism matching). This article guides usage of the MME for rare disease gene discovery. {\textcopyright} 2017 by John Wiley \& Sons, Inc.

}, keywords = {Animals, Computational Biology, Databases, Genetic, Genetic Association Studies, Genetic Predisposition to Disease, Genomics, Humans, Rare Diseases, Software, Web Browser}, issn = {1934-8258}, doi = {10.1002/cphg.50}, author = {Sobreira, Nara L M and Arachchi, Harindra and Buske, Orion J and Chong, Jessica X and Hutton, Ben and Foreman, Julia and Schiettecatte, Fran{\c c}ois and Groza, Tudor and Jacobsen, Julius O B and Haendel, Melissa A and Boycott, Kym M and Hamosh, Ada and Rehm, Heidi L} } @article {105, title = {Gene discovery for Mendelian conditions via social networking: de novo variants in KDM1A cause developmental delay and distinctive facial features.}, journal = {Genet Med}, volume = {18}, year = {2016}, month = {2016 08}, pages = {788-95}, abstract = {

PURPOSE: The pace of Mendelian gene discovery is slowed by the "n-of-1 problem"-the difficulty of establishing the causality of a putatively pathogenic variant in a single person or family. Identification of an unrelated person with an overlapping phenotype and suspected pathogenic variant in the same gene can overcome this barrier, but it is often impeded by lack of a convenient or widely available way to share data on candidate variants/genes among families, clinicians, and researchers.

METHODS: Social networking among families, clinicians, and researchers was used to identify three children with variants of unknown significance in KDM1A and similar phenotypes.

RESULTS: De novo variants in KDM1A underlie a new syndrome characterized by developmental delay and distinctive facial features.

CONCLUSION: Social networking is a potentially powerful strategy to discover genes for rare Mendelian conditions, particularly those with nonspecific phenotypic features. To facilitate the efforts of families to share phenotypic and genomic information with each other, clinicians, and researchers, we developed the Repository for Mendelian Genomics Family Portal (RMD-FP; http://uwcmg.org/$\#$/family). Design and development of MyGene2 (http://www.mygene2.org), a Web-based tool that enables families, clinicians, and researchers to search for gene matches based on analysis of phenotype and exome data deposited into the RMD-FP, is under way.Genet Med 18 8, 788-795.

}, keywords = {Child, Child, Preschool, Databases, Factual, Developmental Disabilities, Female, Genetic Association Studies, Histone Demethylases, Humans, Information Dissemination, Male, Mutation, Missense, Phenotype, Social Networking, Web Browser}, issn = {1530-0366}, doi = {10.1038/gim.2015.161}, author = {Chong, Jessica X and Yu, Joon-Ho and Lorentzen, Peter and Park, Karen M and Jamal, Seema M and Tabor, Holly K and Rauch, Anita and Saenz, Margarita Sifuentes and Boltshauser, Eugen and Patterson, Karynne E and Nickerson, Deborah A and Bamshad, Michael J} } @article {139, title = {GeneMatcher: a matching tool for connecting investigators with an interest in the same gene.}, journal = {Hum Mutat}, volume = {36}, year = {2015}, month = {2015 Oct}, pages = {928-30}, abstract = {

Here, we describe an overview and update on GeneMatcher (http://www.genematcher.org), a freely accessible Web-based tool developed as part of the Baylor-Hopkins Center for Mendelian Genomics. We created GeneMatcher with the goal of identifying additional individuals with rare phenotypes who had variants in the same candidate disease gene. We also wanted to facilitate connections to basic scientists working on orthologous genes in model systems with the goal of connecting their work to human Mendelian phenotypes. Meeting these goals will enhance the identification of novel Mendelian genes. Launched in September, 2013, GeneMatcher now has 2,178 candidate genes from 486 submitters spread across 38 countries entered in the database (June 1, 2015). GeneMatcher is also part of the Matchmaker Exchange (http://matchmakerexchange.org/) with an Application Programing Interface enabling submitters to query other databases of genetic variants and phenotypes without having to create accounts and data entries in multiple systems.

}, keywords = {Computational Biology, Databases, Genetic, Genetic Predisposition to Disease, Genetic Variation, Humans, Information Dissemination, Phenotype, Rare Diseases, Software, User-Computer Interface, Web Browser}, issn = {1098-1004}, doi = {10.1002/humu.22844}, author = {Sobreira, Nara and Schiettecatte, Fran{\c c}ois and Valle, David and Hamosh, Ada} } @article {146, title = {GeneMatcher aids in the identification of a new malformation syndrome with intellectual disability, unique facial dysmorphisms, and skeletal and connective tissue abnormalities caused by de novo variants in HNRNPK.}, journal = {Hum Mutat}, volume = {36}, year = {2015}, month = {2015 Oct}, pages = {1009-1014}, abstract = {

We report a new syndrome due to loss-of-function variants in the heterogeneous nuclear ribonucleoprotein K gene (HNRNPK). We describe two probands: one with a de novo frameshift (NM_002140.3: c.953+1dup), and the other with a de novo splice donor site variant (NM_002140.3: c.257G>A). Both probands have intellectual disability, a shared unique craniofacial phenotype, and connective tissue and skeletal abnormalities. The identification of this syndrome was made possible by a new online tool, GeneMatcher, which facilitates connections between clinicians and researchers based on shared interest in candidate genes. This report demonstrates that new Web-based approaches can be effective in helping investigators solve exome sequencing projects, and also highlights the newer paradigm of "reverse phenotyping," where characterization of syndromic features follows the identification of genetic variants.

}, keywords = {Abnormalities, Multiple, Adolescent, Child, Craniofacial Abnormalities, Databases, Genetic, Genetic Predisposition to Disease, Heterogeneous-Nuclear Ribonucleoprotein K, Humans, Information Dissemination, Intellectual Disability, Male, Muscular Atrophy, Phenotype, Polymorphism, Single Nucleotide, Ribonucleoproteins, Software, Web Browser}, issn = {1098-1004}, doi = {10.1002/humu.22837}, author = {Au, P Y Billie and You, Jing and Caluseriu, Oana and Schwartzentruber, Jeremy and Majewski, Jacek and Bernier, Francois P and Ferguson, Marcia and Valle, David and Parboosingh, Jillian S and Sobreira, Nara and Innes, A Micheil and Kline, Antonie D} } @article {136, title = {The Matchmaker Exchange API: automating patient matching through the exchange of structured phenotypic and genotypic profiles.}, journal = {Hum Mutat}, volume = {36}, year = {2015}, month = {2015 Oct}, pages = {922-7}, abstract = {

Despite the increasing prevalence of clinical sequencing, the difficulty of identifying additional affected families is a key obstacle to solving many rare diseases. There may only be a handful of similar patients worldwide, and their data may be stored in diverse clinical and research databases. Computational methods are necessary to enable finding similar patients across the growing number of patient repositories and registries. We present the Matchmaker Exchange Application Programming Interface (MME API), a protocol and data format for exchanging phenotype and genotype profiles to enable matchmaking among patient databases, facilitate the identification of additional cohorts, and increase the rate with which rare diseases can be researched and diagnosed. We designed the API to be straightforward and flexible in order to simplify its adoption on a large number of data types and workflows. We also provide a public test data set, curated from the literature, to facilitate implementation of the API and development of new matching algorithms. The initial version of the API has been successfully implemented by three members of the Matchmaker Exchange and was immediately able to reproduce previously identified matches and generate several new leads currently being validated. The API is available at https://github.com/ga4gh/mme-apis.

}, keywords = {Algorithms, Computational Biology, Databases, Genetic, Genetic Predisposition to Disease, Genotype, Humans, Information Dissemination, Phenotype, Rare Diseases, Web Browser}, issn = {1098-1004}, doi = {10.1002/humu.22850}, author = {Buske, Orion J and Schiettecatte, Fran{\c c}ois and Hutton, Benjamin and Dumitriu, Sergiu and Misyura, Andriy and Huang, Lijia and Hartley, Taila and Girdea, Marta and Sobreira, Nara and Mungall, Chris and Brudno, Michael} } @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} }