@article {923, title = {Alternative genomic diagnoses for individuals with a clinical diagnosis of Dubowitz syndrome.}, journal = {Am J Med Genet A}, volume = {185}, year = {2021}, month = {2021 01}, pages = {119-133}, abstract = {

Dubowitz syndrome (DubS) is considered a recognizable syndrome characterized by a distinctive facial appearance and deficits in growth and development. There have been over 200 individuals reported with Dubowitz or a "Dubowitz-like" condition, although no single gene has been implicated as responsible for its cause. We have performed exome (ES) or genome sequencing (GS) for 31 individuals clinically diagnosed with DubS. After genome-wide sequencing, rare variant filtering and computational and Mendelian genomic analyses, a presumptive molecular diagnosis was made in 13/27 (48\%) families. The molecular diagnoses included biallelic variants in SKIV2L, SLC35C1, BRCA1, NSUN2; de novo variants in ARID1B, ARID1A, CREBBP, POGZ, TAF1, HDAC8, and copy-number variation at1p36.11(ARID1A), 8q22.2(VPS13B), Xp22, and Xq13(HDAC8). Variants of unknown significance in known disease genes, and also in genes of uncertain significance, were observed in 7/27 (26\%) additional families. Only one gene, HDAC8, could explain the phenotype in more than one family (N = 2). All but two of the genomic diagnoses were for genes discovered, or for conditions recognized, since the introduction of next-generation sequencing. Overall, the DubS-like clinical phenotype is associated with extensive locus heterogeneity and the molecular diagnoses made are for emerging clinical conditions sharing characteristic features that overlap the DubS phenotype.

}, issn = {1552-4833}, doi = {10.1002/ajmg.a.61926}, author = {Dyment, David A and O{\textquoteright}Donnell-Luria, Anne and Agrawal, Pankaj B and Coban Akdemir, Zeynep and Aleck, Kyrieckos A and Antaki, Danny and Al Sharhan, Hind and Au, Ping-Yee B and Aydin, Hatip and Beggs, Alan H and Bilguvar, Kaya and Boerwinkle, Eric and Brand, Harrison and Brownstein, Catherine A and Buyske, Steve and Chodirker, Bernard and Choi, Jungmin and Chudley, Albert E and Clericuzio, Carol L and Cox, Gerald F and Curry, Cynthia and de Boer, Elke and de Vries, Bert B A and Dunn, Kathryn and Dutmer, Cullen M and England, Eleina M and Fahrner, Jill A and Geckinli, Bilgen B and Genetti, Casie A and Gezdirici, Alper and Gibson, William T and Gleeson, Joseph G and Greenberg, Cheryl R and Hall, April and Hamosh, Ada and Hartley, Taila and Jhangiani, Shalini N and Karaca, Ender and Kernohan, Kristin and Lauzon, Julie L and Lewis, M E Suzanne and Lowry, R Brian and L{\'o}pez-Gir{\'a}ldez, Francesc and Matise, Tara C and McEvoy-Venneri, Jennifer and McInnes, Brenda and Mhanni, Aziz and Garcia Minaur, Sixto and Moilanen, Jukka and Nguyen, An and Nowaczyk, Malgorzata J M and Posey, Jennifer E and {\~O}unap, Katrin and Pehlivan, Davut and Pajusalu, Sander and Penney, Lynette S and Poterba, Timothy and Prontera, Paolo and Doriqui, Maria Juliana Rodovalho and Sawyer, Sarah L and Sobreira, Nara and Stanley, Valentina and Torun, Deniz and Wargowski, David and Witmer, P Dane and Wong, Isaac and Xing, Jinchuan and Zaki, MAH S and Zhang, Yeting and Boycott, Kym M and Bamshad, Michael J and Nickerson, Deborah A and Blue, Elizabeth E and Innes, A Micheil} } @article {920, title = {KMT2B-related disorders: expansion of the phenotypic spectrum and long-term efficacy of deep brain stimulation.}, journal = {Brain}, volume = {143}, year = {2020}, month = {2020 12 05}, pages = {3242-3261}, abstract = {

Heterozygous mutations in KMT2B are associated with an early-onset, progressive and often complex dystonia (DYT28). Key characteristics of typical disease include focal motor features at disease presentation, evolving through a caudocranial pattern into generalized dystonia, with prominent oromandibular, laryngeal and cervical involvement. Although KMT2B-related disease is emerging as one of the most common causes of early-onset genetic dystonia, much remains to be understood about the full spectrum of the disease. We describe a cohort of 53 patients with KMT2B mutations, with detailed delineation of their clinical phenotype and molecular genetic features. We report new disease presentations, including atypical patterns of dystonia evolution and a subgroup of patients with a non-dystonic neurodevelopmental phenotype. In addition to the previously reported systemic features, our study has identified co-morbidities, including the risk of status dystonicus, intrauterine growth retardation, and endocrinopathies. Analysis of this study cohort (n = 53) in tandem with published cases (n = 80) revealed that patients with chromosomal deletions and protein truncating variants had a significantly higher burden of systemic disease (with earlier onset of dystonia) than those with missense variants. Eighteen individuals had detailed longitudinal data available after insertion of deep brain stimulation for medically refractory dystonia. Median age at deep brain stimulation was 11.5 years (range: 4.5-37.0 years). Follow-up after deep brain stimulation ranged from 0.25 to 22 years. Significant improvement of motor function and disability (as assessed by the Burke Fahn Marsden{\textquoteright}s Dystonia Rating Scales, BFMDRS-M and BFMDRS-D) was evident at 6 months, 1 year and last follow-up (motor, P = 0.001, P = 0.004, and P = 0.012; disability, P = 0.009, P = 0.002 and P = 0.012). At 1 year post-deep brain stimulation, >50\% of subjects showed BFMDRS-M and BFMDRS-D improvements of >30\%. In the long-term deep brain stimulation cohort (deep brain stimulation inserted for >5 years, n = 8), improvement of >30\% was maintained in 5/8 and 3/8 subjects for the BFMDRS-M and BFMDRS-D, respectively. The greatest BFMDRS-M improvements were observed for trunk (53.2\%) and cervical (50.5\%) dystonia, with less clinical impact on laryngeal dystonia. Improvements in gait dystonia decreased from 20.9\% at 1 year to 16.2\% at last assessment; no patient maintained a fully independent gait. Reduction of BFMDRS-D was maintained for swallowing (52.9\%). Five patients developed mild parkinsonism following deep brain stimulation. KMT2B-related disease comprises an expanding continuum from infancy to adulthood, with early evidence of genotype-phenotype correlations. Except for laryngeal dysphonia, deep brain stimulation provides a significant improvement in quality of life and function with sustained clinical benefit depending on symptoms distribution.

}, keywords = {Adolescent, Adult, Child, Child, Preschool, Chromosome Deletion, Cohort Studies, Computer Simulation, Deep Brain Stimulation, Disease Progression, Dystonic Disorders, Endocrine System Diseases, Female, Fetal Growth Retardation, Gait Disorders, Neurologic, Histone-Lysine N-Methyltransferase, Humans, Laryngeal Diseases, Male, Mutation, Mutation, Missense, Phenotype, Quality of Life, Treatment Outcome, Young Adult}, issn = {1460-2156}, doi = {10.1093/brain/awaa304}, author = {Cif, Laura and Demailly, Diane and Lin, Jean-Pierre and Barwick, Katy E and Sa, Mario and Abela, Lucia and Malhotra, Sony and Chong, Wui K and Steel, Dora and Sanchis-Juan, Alba and Ngoh, Adeline and Trump, Natalie and Meyer, Esther and Vasques, Xavier and Rankin, Julia and Allain, Meredith W and Applegate, Carolyn D and Attaripour IsfAHni, Sanaz and Baleine, Julien and Balint, Bettina and Bassetti, Jennifer A and Baple, Emma L and Bhatia, Kailash P and Blanchet, Catherine and Burglen, Lydie and Cambonie, Gilles and Seng, Emilie Chan and Bastaraud, Sandra Chantot and Cyprien, Fabienne and Coubes, Christine and d{\textquoteright}Hardemare, Vincent and Doja, Asif and Dorison, Nathalie and Doummar, Diane and Dy-Hollins, Marisela E and Farrelly, Ellyn and FitzPatrick, David R and Fearon, Conor and Fieg, Elizabeth L and Fogel, Brent L and Forman, Eva B and Fox, Rachel G and Gahl, William A and Galosi, Serena and Gonzalez, Victoria and Graves, Tracey D and Gregory, Allison and Hallett, Mark and Hasegawa, Harutomo and Hayflick, Susan J and Hamosh, Ada and Hully, Marie and Jansen, Sandra and Jeong, Suh Young and Krier, Joel B and Krystal, Sidney and Kumar, Kishore R and Laurencin, Chlo{\'e} and Lee, Hane and Lesca, Gaetan and Fran{\c c}ois, Laurence Lion and Lynch, Timothy and MAHnt, Neil and Martinez-Agosto, Julian A and Milesi, Christophe and Mills, Kelly A and Mondain, Michel and Morales-Briceno, Hugo and Ostergaard, John R and Pal, Swasti and Pallais, Juan C and Pavillard, Fr{\'e}d{\'e}rique and Perrigault, Pierre-Francois and Petersen, Andrea K and Polo, Gustavo and Poulen, Gaetan and Rinne, Tuula and Roujeau, Thomas and Rogers, Caleb and Roubertie, Agathe and SAHgian, Michelle and Schaefer, Elise and Selim, Laila and Selway, Richard and Sharma, Nutan and Signer, Rebecca and Soldatos, Ariane G and Stevenson, David A and Stewart, Fiona and Tchan, Michel and Verma, Ishwar C and de Vries, Bert B A and Wilson, Jenny L and Wong, Derek A and Zaitoun, Raghda and Zhen, Dolly and Znaczko, Anna and Dale, Russell C and de Gusm{\~a}o, Claudio M and Friedman, Jennifer and Fung, Victor S C and King, Mary D and Mohammad, Shekeeb S and Rohena, Luis and Waugh, Jeff L and Toro, Camilo and Raymond, F Lucy and Topf, Maya and Coubes, Philippe and Gorman, Kathleen M and Kurian, Manju A} } @article {768, title = {The utility of exome sequencing for fetal pleural effusions.}, journal = {Prenat Diagn}, volume = {40}, year = {2020}, month = {2020 04}, pages = {590-595}, abstract = {

OBJECTIVE: We sought to evaluate the performance of exome sequencing (ES) in determining an underlying genetic etiology for cases of fetal pleural effusions.

STUDY DESIGN: We examined a prospective cohort series of fetal pleural effusions visualized sonographically between 1 April 2016 and 31 August 2017. Fetal pleural effusions attributed to twin sharing, anemia, or structural anomalies were excluded, as were all cases with a genetic diagnosis established by karyotype or chromosomal microarray analysis. The remaining cases with pleural effusions of unclear etiology were offered ES. ES was performed by clinical sequencing and/or sequencing under the Baylor-Hopkins Center for Mendelian Genomics{\textquoteright} (BHCMG) research platform. All cases were evaluated for novel genes or phenotypic expansion of disease-causing genes.

RESULTS: ES was performed on six probands affected by pleural effusions. A pathogenic variant was identified in one case (16.7\%). Four additional cases had variants of uncertain significance (VUS) in candidate genes of pathological interest. Neither clinical nor candidate genes were evident in the final case.

CONCLUSION: ES should be considered in the evaluation of prenatally detected idiopathic pleural effusions when other diagnostic workup for a genetic etiology has failed.

}, issn = {1097-0223}, doi = {10.1002/pd.5650}, author = {Jelin, Angie C and Sobreira, Nara and Wohler, Elizabeth and Solomon, Benjamin and Sparks, Teresa and Sagaser, Katelynn G and Forster, Katherine R and Miller, Jena and Witmer, P Dane and Hamosh, Ada and Valle, David and Blakemore, Karin} } @article {722, title = {Enabling Global Clinical Collaborations on Identifiable Patient Data: The Minerva Initiative.}, journal = {Front Genet}, volume = {10}, year = {2019}, month = {2019}, pages = {611}, abstract = {

The clinical utility of computational phenotyping for both genetic and rare diseases is increasingly appreciated; however, its true potential is yet to be fully realized. Alongside the growing clinical and research availability of sequencing technologies, precise deep and scalable phenotyping is required to serve unmet need in genetic and rare diseases. To improve the lives of individuals affected with rare diseases through deep phenotyping, global big data interrogation is necessary to aid our understanding of disease biology, assist diagnosis, and develop targeted treatment strategies. This includes the application of cutting-edge machine learning methods to image data. As with most digital tools employed in health care, there are ethical and data governance challenges associated with using identifiable personal image data. There are also risks with failing to deliver on the patient benefits of these new technologies, the biggest of which is posed by data siloing. The Minerva Initiative has been designed to enable the public good of deep phenotyping while mitigating these ethical risks. Its open structure, enabling collaboration and data sharing between individuals, clinicians, researchers and private enterprise, is key for delivering precision public health.

}, issn = {1664-8021}, doi = {10.3389/fgene.2019.00611}, author = {Nellaker, Christoffer and Alkuraya, Fowzan S and Baynam, Gareth and Bernier, Raphael A and Bernier, Francois P J and Boulanger, Vanessa and Brudno, Michael and Brunner, Han G and Clayton-Smith, Jill and Cogn{\'e}, Benjamin and Dawkins, Hugh J S and deVries, Bert B A and Douzgou, Sofia and Dudding-Byth, Tracy and Eichler, Evan E and Ferlaino, Michael and Fieggen, Karen and Firth, Helen V and FitzPatrick, David R and Gration, Dylan and Groza, Tudor and Haendel, Melissa and Hallowell, Nina and Hamosh, Ada and Hehir-Kwa, Jayne and Hitz, Marc-Phillip and Hughes, Mark and Kini, Usha and Kleefstra, Tjitske and Kooy, R Frank and Krawitz, Peter and K{\"u}ry, S{\'e}bastien and Lees, Melissa and Lyon, Gholson J and Lyonnet, Stanislas and Marcadier, Julien L and Meyn, Stephen and Moslerov{\'a}, Veronika and Politei, Juan M and Poulton, Cathryn C and Raymond, F Lucy and Reijnders, Margot R F and Robinson, Peter N and Romano, Corrado and Rose, Catherine M and Sainsbury, David C G and Schofield, Lyn and Sutton, Vernon R and Turnovec, Marek and Van Dijck, Anke and Van Esch, Hilde and Wilkie, Andrew O M} } @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 {676, title = {Pathogenic Variants in NUP214 Cause "Plugged" Nuclear Pore Channels and Acute Febrile Encephalopathy.}, journal = {Am J Hum Genet}, volume = {105}, year = {2019}, month = {2019 Jul 03}, pages = {48-64}, abstract = {

We report biallelic missense and frameshift pathogenic variants in the gene encoding human nucleoporin NUP214 causing acute febrile encephalopathy. Clinical symptoms include neurodevelopmental regression, seizures, myoclonic jerks, progressive microcephaly, and cerebellar atrophy. NUP214 and NUP88 protein levels were reduced in primary skin fibroblasts derived from affected individuals, while the total number and density of nuclear pore complexes remained normal. Nuclear transport assays exhibited defects in the classical protein import and mRNA export pathways in affected cells. Direct surface imaging of fibroblast nuclei by scanning electron microscopy revealed a large increase in the presence of central particles (known as "plugs") in the nuclear pore channels of affected cells. This observation suggests that large transport cargoes may be delayed in passage through the nuclear pore channel, affecting its selective barrier function. Exposure of fibroblasts from affected individuals to heat shock resulted in a marked delay in their stress response, followed by a surge in apoptotic cell death. This suggests a mechanistic link between decreased cell survival in cell culture and severe fever-induced brain damage in affected individuals. Our study provides evidence by direct imaging at the single nuclear pore level of functional changes linked to a human disease.

}, issn = {1537-6605}, doi = {10.1016/j.ajhg.2019.05.003}, author = {Fichtman, Boris and Harel, Tamar and Biran, Nitzan and Zagairy, Fadia and Applegate, Carolyn D and Salzberg, Yuval and Gilboa, Tal and Salah, Somaya and Shaag, Avraham and Simanovsky, Natalia and Ayoubieh, Houriya and Sobreira, Nara and Punzi, Giuseppe and Pierri, Ciro Leonardo and Hamosh, Ada and Elpeleg, Orly and Harel, Amnon and Edvardson, Simon} } @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 {428, title = {"Matching" consent to purpose: The example of the Matchmaker Exchange.}, journal = {Hum Mutat}, volume = {38}, year = {2017}, month = {2017 10}, pages = {1281-1285}, abstract = {

The Matchmaker Exchange (MME) connects rare disease clinicians and researchers to facilitate the sharing of data from undiagnosed patients for the purpose of novel gene discovery. Such sharing raises the odds that two or more similar patients with candidate genes in common may be found, thereby allowing their condition to be more readily studied and understood. Consent considerations for data sharing in MME included both the ethical and legal differences between clinical and research settings and the level of privacy risk involved in sharing varying amounts of rare disease patient data to enable patient matches. In this commentary, we discuss these consent considerations and the resulting MME Consent Policy as they may be relevant to other international data sharing initiatives.

}, keywords = {Databases, Genetic, Genetic Association Studies, Genetic Diseases, Inborn, Genomics, Humans, Information Dissemination, Patient Selection, Physicians, Rare Diseases, Research Personnel, Translational Medical Research}, issn = {1098-1004}, doi = {10.1002/humu.23278}, author = {Dyke, Stephanie O M and Knoppers, Bartha M and Hamosh, Ada and Firth, Helen V and Hurles, Matthew and Brudno, Michael and Boycott, Kym M and Philippakis, Anthony A and Rehm, Heidi L} } @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 {36, title = {KIF5A mutations cause an infantile onset phenotype including severe myoclonus with evidence of mitochondrial dysfunction.}, journal = {Ann Neurol}, volume = {80}, year = {2016}, month = {2016 Oct}, pages = {633-7}, abstract = {

Missense mutations in kinesin family member 5A (KIF5A) cause spastic paraplegia 10. We report on 2 patients with de novo stop-loss frameshift variants in KIF5A resulting in a novel phenotype that includes severe infantile onset myoclonus, hypotonia, optic nerve abnormalities, dysphagia, apnea, and early developmental arrest. We propose that alteration and elongation of the carboxy-terminus of the protein has a dominant-negative effect, causing mitochondrial dysfunction in the setting of an abnormal kinesin "motor." These results highlight the role of expanded testing and whole-exome sequencing in critically ill infants and emphasize the importance of accurate test interpretation. Ann Neurol 2016;80:633-637.

}, keywords = {Apnea, Child, Preschool, Deglutition Disorders, Developmental Disabilities, Fatal Outcome, Female, Frameshift Mutation, Humans, Infant, Kinesins, Male, Mitochondrial Diseases, Muscle Hypotonia, Mutation, Myoclonus, Optic Nerve}, issn = {1531-8249}, doi = {10.1002/ana.24744}, author = {Duis, Jessica and Dean, Shannon and Applegate, Carolyn and Harper, Amy and Xiao, Rui and He, Weimin and Dollar, James D and Sun, Lisa R and Waberski, Marta Biderman and Crawford, Thomas O and Hamosh, Ada and Stafstrom, Carl E} } @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 {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 {149, title = {The Genetic Basis of Mendelian Phenotypes: Discoveries, Challenges, and Opportunities.}, journal = {Am J Hum Genet}, volume = {97}, year = {2015}, month = {2015 Aug 06}, pages = {199-215}, abstract = {

Discovering the genetic basis of a Mendelian phenotype establishes a causal link between genotype and phenotype, making possible carrier and population screening and direct diagnosis. Such discoveries also contribute to our knowledge of gene function, gene regulation, development, and biological mechanisms that can be used for developing new therapeutics. As of February 2015, 2,937 genes underlying 4,163 Mendelian phenotypes have been discovered, but the genes underlying \~{}50\% (i.e., 3,152) of all known Mendelian phenotypes are still unknown, and many more Mendelian conditions have yet to be recognized. This is a formidable gap in biomedical knowledge. Accordingly, in December 2011, the NIH established the Centers for Mendelian Genomics (CMGs) to provide the collaborative framework and infrastructure necessary for undertaking large-scale whole-exome sequencing and discovery of the genetic variants responsible for Mendelian phenotypes. In partnership with 529 investigators from 261 institutions in 36 countries, the CMGs assessed 18,863 samples from 8,838 families representing 579 known and 470 novel Mendelian phenotypes as of January 2015. This collaborative effort has identified 956 genes, including 375 not previously associated with human health, that underlie a Mendelian phenotype. These results provide insight into study design and analytical strategies, identify novel mechanisms of disease, and reveal the extensive clinical variability of Mendelian phenotypes. Discovering the gene underlying every Mendelian phenotype will require tackling challenges such as worldwide ascertainment and phenotypic characterization of families affected by Mendelian conditions, improvement in sequencing and analytical techniques, and pervasive sharing of phenotypic and genomic data among researchers, clinicians, and families.

}, keywords = {Genetic Diseases, Inborn, Genetics, Medical, Humans, Phenotype, Proteins}, issn = {1537-6605}, doi = {10.1016/j.ajhg.2015.06.009}, author = {Chong, Jessica X and Buckingham, Kati J and Jhangiani, Shalini N and Boehm, Corinne and Sobreira, Nara and Smith, Joshua D and Harrell, Tanya M and McMillin, Margaret J and Wiszniewski, Wojciech and Gambin, Tomasz and Coban Akdemir, Zeynep H and Doheny, Kimberly and Scott, Alan F and Avramopoulos, Dimitri and Chakravarti, Aravinda and Hoover-Fong, Julie and Mathews, Debra and Witmer, P Dane and Ling, Hua and Hetrick, Kurt and Watkins, Lee and Patterson, Karynne E and Reinier, Frederic and Blue, Elizabeth and Muzny, Donna and Kircher, Martin and Bilguvar, Kaya and L{\'o}pez-Gir{\'a}ldez, Francesc and Sutton, V Reid and Tabor, Holly K and Leal, Suzanne M and G{\"u}nel, Murat and Mane, Shrikant and Gibbs, Richard A and Boerwinkle, Eric and Hamosh, Ada and Shendure, Jay and Lupski, James R and Lifton, Richard P and Valle, David and Nickerson, Deborah A and Bamshad, Michael J} } @article {131, title = {The Matchmaker Exchange: a platform for rare disease gene discovery.}, journal = {Hum Mutat}, volume = {36}, year = {2015}, month = {2015 Oct}, pages = {915-21}, abstract = {

There are few better examples of the need for data sharing than in the rare disease community, where patients, physicians, and researchers must search for "the needle in a haystack" to uncover rare, novel causes of disease within the genome. Impeding the pace of discovery has been the existence of many small siloed datasets within individual research or clinical laboratory databases and/or disease-specific organizations, hoping for serendipitous occasions when two distant investigators happen to learn they have a rare phenotype in common and can "match" these cases to build evidence for causality. However, serendipity has never proven to be a reliable or scalable approach in science. As such, the Matchmaker Exchange (MME) was launched to provide a robust and systematic approach to rare disease gene discovery through the creation of a federated network connecting databases of genotypes and rare phenotypes using a common application programming interface (API). The core building blocks of the MME have been defined and assembled. Three MME services have now been connected through the API and are available for community use. Additional databases that support internal matching are anticipated to join the MME network as it continues to grow.

}, keywords = {Database Management Systems, Databases, Genetic, Genetic Association Studies, Genetic Predisposition to Disease, Humans, Information Dissemination, Rare Diseases, Software}, issn = {1098-1004}, doi = {10.1002/humu.22858}, author = {Philippakis, Anthony A and Azzariti, Danielle R and Beltran, Sergi and Brookes, Anthony J and Brownstein, Catherine A and Brudno, Michael and Brunner, Han G and Buske, Orion J and Carey, Knox and Doll, Cassie and Dumitriu, Sergiu and Dyke, Stephanie O M and den Dunnen, Johan T and Firth, Helen V and Gibbs, Richard A and Girdea, Marta and Gonzalez, Michael and Haendel, Melissa A and Hamosh, Ada and Holm, Ingrid A and Huang, Lijia and Hurles, Matthew E and Hutton, Ben and Krier, Joel B and Misyura, Andriy and Mungall, Christopher J and Paschall, Justin and Paten, Benedict and Robinson, Peter N and Schiettecatte, Fran{\c c}ois and Sobreira, Nara L and Swaminathan, Ganesh J and Taschner, Peter E and Terry, Sharon F and Washington, Nicole L and Z{\"u}chner, Stephan and Boycott, Kym M and Rehm, Heidi L} } @article {130, title = {Mutations in SPATA5 Are Associated with Microcephaly, Intellectual Disability, Seizures, and Hearing Loss.}, journal = {Am J Hum Genet}, volume = {97}, year = {2015}, month = {2015 Sep 03}, pages = {457-64}, abstract = {

Using whole-exome sequencing, we have identified in ten families 14 individuals with microcephaly, developmental delay, intellectual disability, hypotonia, spasticity, seizures, sensorineural hearing loss, cortical visual impairment, and rare autosomal-recessive predicted pathogenic variants in spermatogenesis-associated protein 5 (SPATA5). SPATA5 encodes a ubiquitously expressed member of the ATPase associated with diverse activities (AAA) protein family and is involved in mitochondrial morphogenesis during early spermatogenesis. It might also play a role in post-translational modification during cell differentiation in neuronal development. Mutations in SPATA5 might affect brain development and function, resulting in microcephaly, developmental delay, and intellectual disability.

}, keywords = {Abnormalities, Multiple, Amino Acid Sequence, ATPases Associated with Diverse Cellular Activities, Base Sequence, Exome, Female, Gene Frequency, Genes, Recessive, Hearing Loss, Homeodomain Proteins, Humans, Intellectual Disability, Male, Microcephaly, Molecular Sequence Data, Mutation, Seizures, Sequence Alignment, Sequence Analysis, DNA}, issn = {1537-6605}, doi = {10.1016/j.ajhg.2015.07.014}, author = {Tanaka, Akemi J and Cho, Megan T and Millan, Francisca and Juusola, Jane and Retterer, Kyle and Joshi, Charuta and Niyazov, Dmitriy and Garnica, Adolfo and Gratz, Edward and Deardorff, Matthew and Wilkins, Alisha and Ortiz-Gonzalez, Xilma and Mathews, Katherine and Panzer, Karin and Brilstra, Eva and van Gassen, Koen L I and Volker-Touw, Catharina M L and van Binsbergen, Ellen and Sobreira, Nara and Hamosh, Ada and McKnight, Dianalee and Monaghan, Kristin G and Chung, Wendy K} } @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} }