@article {810, title = {Missed diagnoses: Clinically relevant lessons learned through medical mysteries solved by the Undiagnosed Diseases Network.}, journal = {Mol Genet Genomic Med}, volume = {8}, year = {2020}, month = {2020 10}, pages = {e1397}, abstract = {

BACKGROUND: Resources within the Undiagnosed Diseases Network (UDN), such as genome sequencing (GS) and model organisms aid in diagnosis and identification of new disease genes, but are currently difficult to access by clinical providers. While these resources do contribute to diagnoses in many cases, they are not always necessary to reach diagnostic resolution. The UDN experience has been that participants can also receive diagnoses through the thoughtful and customized application of approaches and resources that are readily available in clinical settings.

METHODS: The UDN Genetic Counseling and Testing Working Group collected case vignettes that illustrated how clinically available methods resulted in diagnoses. The case vignettes were classified into three themes; phenotypic considerations, selection of genetic testing, and evaluating exome/GS variants and data.

RESULTS: We present 12 participants that illustrate how clinical practices such as phenotype-driven genomic investigations, consideration of variable expressivity, selecting the relevant tissue of interest for testing, utilizing updated testing platforms, and recognition of alternate transcript nomenclature resulted in diagnoses.

CONCLUSION: These examples demonstrate that when a diagnosis is elusive, an iterative patient-specific approach utilizing assessment options available to clinical providers may solve a portion of cases. However, this does require increased provider time commitment, a particular challenge in the current practice of genomics.

}, keywords = {Adolescent, Child, Child, Preschool, Databases, Factual, Diagnosis, Computer-Assisted, Female, Genetic Diseases, Inborn, Genetic Testing, Humans, Information Dissemination, Male, Middle Aged, Missed Diagnosis, National Institutes of Health (U.S.), Phenotype, Precision Medicine, Undiagnosed Diseases, United States, Young Adult}, issn = {2324-9269}, doi = {10.1002/mgg3.1397}, author = {Cope, Heidi and Spillmann, Rebecca and Rosenfeld, Jill A and Brokamp, Elly and Signer, Rebecca and Schoch, Kelly and Kelley, Emily G and Sullivan, Jennifer A and Macnamara, Ellen and Lincoln, Sharyn and Golden-Grant, Katie and Orengo, James P and Clark, Gary and Burrage, Lindsay C and Posey, Jennifer E and Punetha, Jaya and Robertson, Amy and Cogan, Joy and Phillips, John A and Martinez-Agosto, Julian and Shashi, Vandana} } @article {735, title = {Detailed genetic characteristics of an international large cohort of patients with Stargardt disease: ProgStar study report 8.}, journal = {Br J Ophthalmol}, volume = {103}, year = {2019}, month = {2019 03}, pages = {390-397}, abstract = {

BACKGROUND/AIMS: To describe the genetic characteristics of the cohort enrolled in the international multicentre progression of Stargardt disease~1 (STGD1) studies (ProgStar) and to~determine geographic differences based on the allele frequency.

METHODS: 345 participants with a clinical diagnosis of STGD1 and harbouring at least one disease-causing ABCA4 variant were enrolled from 9 centres in the USA and Europe. All variants were reviewed and analysis was performed including allele frequency in public databases and pathogenicity predictions. Participants with multiple likely pathogenic variants were classified into four national subgroups (USA, UK, France, Germany), with subsequent comparison analysis of the allele frequency for each prevalent allele.

RESULTS: 211 likely pathogenic variants were identified in the total cohort, including missense (63\%), splice site alteration (18\%), stop (9\%) and others. 50 variants were novel. Exclusively missense variants were detected in 139 (50\%) of 279 patients with multiple pathogenic variants. The three most prevalent variants of these patients with multiple pathogenic variants were p.G1961E (15\%), p.G863A (7\%)~and~c.5461-10 T>C (5\%). Subgroup analysis revealed a statistically significant difference between the four recruiting nations in the allele frequency of nine variants.

CONCLUSIONS: There is a large spectrum of ABCA4 sequence variants, including 50 novel variants, in a well-characterised cohort thereby further adding to the unique allelic heterogeneity in STGD1. Approximately half of the cohort harbours missense variants only, indicating a relatively mild phenotype of the ProgStar cohort. There are significant differences in allele frequencies between nations, although the three most prevalent variants are shared as frequent variants.

}, keywords = {Adolescent, Adult, Age of Onset, Aged, ATP-Binding Cassette Transporters, Child, Child, Preschool, Cohort Studies, Databases, Factual, DNA Mutational Analysis, Female, Gene Frequency, Genotyping Techniques, Geography, Humans, Internationality, Macular Degeneration, Male, Middle Aged, Mutation, Polymerase Chain Reaction}, issn = {1468-2079}, doi = {10.1136/bjophthalmol-2018-312064}, author = {Fujinami, Kaoru and Strauss, Rupert W and Chiang, John Pei-Wen and Audo, Isabelle S and Bernstein, Paul S and Birch, David G and Bomotti, Samantha M and Cideciyan, Artur V and Ervin, Ann-Margret and Marino, Meghan J and Sahel, Jos{\'e}-Alain and Mohand-Said, Saddek and Sunness, Janet S and Traboulsi, Elias I and West, Sheila and Wojciechowski, Robert and Zrenner, Eberhart and Michaelides, Michel and Scholl, Hendrik P N} } @article {398, title = {Genome-Wide Association Studies and Meta-Analyses for Congenital Heart Defects.}, journal = {Circ Cardiovasc Genet}, volume = {10}, year = {2017}, month = {2017 Jun}, pages = {e001449}, abstract = {

BACKGROUND: Maternal and inherited (ie, case) genetic factors likely contribute to the pathogenesis of congenital heart defects, but it is unclear whether individual common variants confer a large risk.

METHODS AND RESULTS: To evaluate the relationship between individual common maternal/inherited genotypes and risk for heart defects, we conducted genome-wide association studies in 5 cohorts. Three cohorts were recruited at the Children{\textquoteright}s Hospital of Philadelphia: 670 conotruncal heart defect (CTD) case-parent trios, 317 left ventricular obstructive tract defect (LVOTD) case-parent trios, and 406 CTD cases (n=406) and 2976 pediatric controls. Two cohorts were recruited through the Pediatric Cardiac Genomics Consortium: 355 CTD trios and 192 LVOTD trios. We also conducted meta-analyses using the genome-wide association study results from the CTD cohorts, the LVOTD cohorts, and from the combined CTD and LVOTD cohorts. In the individual genome-wide association studies, several genome-wide significant associations (<=5{\texttimes}10) were observed. In our meta-analyses, 1 genome-wide significant association was detected: the case genotype for rs72820264, an intragenetic single-nucleotide polymorphism associated with LVOTDs (=2.1{\texttimes}10).

CONCLUSIONS: We identified 1 novel candidate region associated with LVOTDs and report on several additional regions with suggestive evidence for association with CTD and LVOTD. These studies were constrained by the relatively small samples sizes and thus have limited power to detect small to moderate associations. Approaches that minimize the multiple testing burden (eg, gene or pathway based) may, therefore, be required to uncover common variants contributing to the risk of these relatively rare conditions.

}, keywords = {Cohort Studies, Databases, Factual, Female, Gene Frequency, Genome-Wide Association Study, Genotype, Heart Defects, Congenital, Humans, Introns, Male, Membrane Proteins, Polymorphism, Single Nucleotide}, issn = {1942-3268}, doi = {10.1161/CIRCGENETICS.116.001449}, author = {Agopian, A J and Goldmuntz, Elizabeth and Hakonarson, Hakon and Sewda, Anshuman and Taylor, Deanne and Mitchell, Laura E} } @article {363, title = {International Cooperation to Enable the Diagnosis of All Rare Genetic Diseases.}, journal = {Am J Hum Genet}, volume = {100}, year = {2017}, month = {2017 May 04}, pages = {695-705}, abstract = {

Provision of a molecularly confirmed diagnosis in a timely manner for children and adults with rare genetic diseases shortens their "diagnostic odyssey," improves disease management, and fosters genetic counseling with respect to recurrence risks while assuring reproductive choices. In a general clinical genetics setting, the current diagnostic rate is approximately 50\%, but for those who do not receive a molecular diagnosis after the initial genetics evaluation, that rate is much lower. Diagnostic success for these more challenging affected individuals depends to a large extent on progress in the discovery of genes associated with, and mechanisms underlying, rare diseases. Thus, continued research is required for moving toward a more complete catalog of disease-related genes and variants. The International Rare Diseases Research Consortium (IRDiRC) was established in 2011 to bring together researchers and organizations invested in rare disease research to develop a means of achieving molecular diagnosis for all rare diseases. Here, we review the current and future bottlenecks to gene discovery and suggest strategies for enabling progress in this regard. Each successful discovery will define potential diagnostic, preventive, and therapeutic opportunities for the corresponding rare disease, enabling precision medicine for this patient population.

}, keywords = {Databases, Factual, Exome, Genome, Human, Humans, International Cooperation, Rare Diseases}, issn = {1537-6605}, doi = {10.1016/j.ajhg.2017.04.003}, author = {Boycott, Kym M and Rath, Ana and Chong, Jessica X and Hartley, Taila and Alkuraya, Fowzan S and Baynam, Gareth and Brookes, Anthony J and Brudno, Michael and Carracedo, Angel and den Dunnen, Johan T and Dyke, Stephanie O M and Estivill, Xavier and Goldblatt, Jack and Gonthier, Catherine and Groft, Stephen C and Gut, Ivo and Hamosh, Ada and Hieter, Philip and H{\"o}hn, Sophie and Hurles, Matthew E and Kaufmann, Petra and Knoppers, Bartha M and Krischer, Jeffrey P and Macek, Milan and Matthijs, Gert and Olry, Annie and Parker, Samantha and Paschall, Justin and Philippakis, Anthony A and Rehm, Heidi L and Robinson, Peter N and Sham, Pak-Chung and Stefanov, Rumen and Taruscio, Domenica and Unni, Divya and Vanstone, Megan R and Zhang, Feng and Brunner, Han and Bamshad, Michael J and Lochm{\"u}ller, Hanns} } @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 {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} }