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Galer PD, Ganesan S, Lewis-Smith D, McKeown SE, Pendziwiat M, Helbig KL, Ellis CA, Rademacher A, Smith L, Poduri A, Seiffert S, von Spiczak S, Muhle H, van Baalen A, Thomas RH, Krause R, Weber Y, Helbig I, Thomas RH, Krause R, Weber Y, Helbig I. Semantic Similarity Analysis Reveals Robust Gene-Disease Relationships in Developmental and Epileptic Encephalopathies. Am J Hum Genet 2020; 107:683-697. [PMID: 32853554 PMCID: PMC7536581 DOI: 10.1016/j.ajhg.2020.08.003] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2020] [Accepted: 07/31/2020] [Indexed: 12/21/2022] Open
Abstract
More than 100 genetic etiologies have been identified in developmental and epileptic encephalopathies (DEEs), but correlating genetic findings with clinical features at scale has remained a hurdle because of a lack of frameworks for analyzing heterogenous clinical data. Here, we analyzed 31,742 Human Phenotype Ontology (HPO) terms in 846 individuals with existing whole-exome trio data and assessed associated clinical features and phenotypic relatedness by using HPO-based semantic similarity analysis for individuals with de novo variants in the same gene. Gene-specific phenotypic signatures included associations of SCN1A with “complex febrile seizures” (HP: 0011172; p = 2.1 × 10−5) and “focal clonic seizures” (HP: 0002266; p = 8.9 × 10−6), STXBP1 with “absent speech” (HP: 0001344; p = 1.3 × 10−11), and SLC6A1 with “EEG with generalized slow activity” (HP: 0010845; p = 0.018). Of 41 genes with de novo variants in two or more individuals, 11 genes showed significant phenotypic similarity, including SCN1A (n = 16, p < 0.0001), STXBP1 (n = 14, p = 0.0021), and KCNB1 (n = 6, p = 0.011). Including genetic and phenotypic data of control subjects increased phenotypic similarity for all genetic etiologies, whereas the probability of observing de novo variants decreased, emphasizing the conceptual differences between semantic similarity analysis and approaches based on the expected number of de novo events. We demonstrate that HPO-based phenotype analysis captures unique profiles for distinct genetic etiologies, reflecting the breadth of the phenotypic spectrum in genetic epilepsies. Semantic similarity can be used to generate statistical evidence for disease causation analogous to the traditional approach of primarily defining disease entities through similar clinical features.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | - Rhys H Thomas
- Translational and Clinical Research Institute, Newcastle University, Newcastle-upon-Tyne NE1 7RU, UK; Royal Victoria Infirmary, Newcastle-upon-Tyne NE1 4LP, UK
| | - Roland Krause
- Luxembourg Centre for Systems Biomedicine, University of Luxembourg, 4367 Belvaux, Luxembourg
| | - Yvonne Weber
- Department of Neurology and Epileptology, Hertie Institute for Clinical Brain Research, University of Tübingen, 72076 Tübingen, Germany; Department of Epileptology and Neurology, University of Aachen, 52074 Aachen, Germany
| | - Ingo Helbig
- Division of Neurology, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA; The Epilepsy NeuroGenetics Initiative (ENGIN), Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA; Department of Biomedical and Health Informatics (DBHi), Children's Hospital of Philadelphia, Philadelphia, PA 19146, USA; Department of Neurology, University of Pennsylvania, Philadelphia, PA 19104, USA.
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Mandl KD, Glauser T, Krantz ID, Avillach P, Bartels A, Beggs AH, Biswas S, Bourgeois FT, Corsmo J, Dauber A, Devkota B, Fleisher GR, Heath AP, Helbig I, Hirschhorn JN, Kilbourn J, Kong SW, Kornetsky S, Majzoub JA, Marsolo K, Martin LJ, Nix J, Schwarzhoff A, Stedman J, Strauss A, Sund KL, Taylor DM, White PS, Marsh E, Grimberg A, Hawkes C. The Genomics Research and Innovation Network: creating an interoperable, federated, genomics learning system. Genet Med 2020; 22:371-380. [PMID: 31481752 PMCID: PMC7000325 DOI: 10.1038/s41436-019-0646-3] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2019] [Accepted: 08/20/2019] [Indexed: 12/17/2022] Open
Abstract
PURPOSE Clinicians and researchers must contextualize a patient's genetic variants against population-based references with detailed phenotyping. We sought to establish globally scalable technology, policy, and procedures for sharing biosamples and associated genomic and phenotypic data on broadly consented cohorts, across sites of care. METHODS Three of the nation's leading children's hospitals launched the Genomic Research and Innovation Network (GRIN), with federated information technology infrastructure, harmonized biobanking protocols, and material transfer agreements. Pilot studies in epilepsy and short stature were completed to design and test the collaboration model. RESULTS Harmonized, broadly consented institutional review board (IRB) protocols were approved and used for biobank enrollment, creating ever-expanding, compatible biobanks. An open source federated query infrastructure was established over genotype-phenotype databases at the three hospitals. Investigators securely access the GRIN platform for prep to research queries, receiving aggregate counts of patients with particular phenotypes or genotypes in each biobank. With proper approvals, de-identified data is exported to a shared analytic workspace. Investigators at all sites enthusiastically collaborated on the pilot studies, resulting in multiple publications. Investigators have also begun to successfully utilize the infrastructure for grant applications. CONCLUSIONS The GRIN collaboration establishes the technology, policy, and procedures for a scalable genomic research network.
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Affiliation(s)
- Kenneth D Mandl
- Computational Health Informatics Program, Boston Children's Hospital, Boston, MA, USA.
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.
- Department of Pediatrics, Harvard Medical School, Boston, MA, USA.
| | - Tracy Glauser
- Division of Neurology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - Ian D Krantz
- Division of Human Genetics at the Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Pediatrics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Paul Avillach
- Computational Health Informatics Program, Boston Children's Hospital, Boston, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Anna Bartels
- Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
| | - Alan H Beggs
- Department of Pediatrics, Harvard Medical School, Boston, MA, USA
- The Manton Center for Orphan Disease Research, Division of Genetics and Genomics, Boston Children's Hospital, Boston, MA, USA
- Department of Pediatrics, Boston Children's Hospital, Boston, MA, USA
| | - Sawona Biswas
- Division of Human Genetics at the Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Florence T Bourgeois
- Computational Health Informatics Program, Boston Children's Hospital, Boston, MA, USA
- Department of Pediatrics, Harvard Medical School, Boston, MA, USA
- Department of Pediatrics, Boston Children's Hospital, Boston, MA, USA
| | - Jeremy Corsmo
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, USA
- Office of Research Compliance and Regulatory Affairs, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
| | - Andrew Dauber
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, USA
- Division of Endocrinology, Children's National Health System, Washington, DC, USA
| | - Batsal Devkota
- Center for Data-Driven Discovery in Biomedicine, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Gary R Fleisher
- Department of Pediatrics, Harvard Medical School, Boston, MA, USA
- Department of Pediatrics, Boston Children's Hospital, Boston, MA, USA
| | - Allison P Heath
- Center for Data-Driven Discovery in Biomedicine, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Ingo Helbig
- Department of Pediatrics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
- Department of Biomedical and Health Informatics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Division of Neurology, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Joel N Hirschhorn
- Department of Pediatrics, Harvard Medical School, Boston, MA, USA
- Division of Endocrinology, Boston Children's Hospital, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Judson Kilbourn
- Computational Health Informatics Program, Boston Children's Hospital, Boston, MA, USA
| | - Sek Won Kong
- Computational Health Informatics Program, Boston Children's Hospital, Boston, MA, USA
- Department of Pediatrics, Harvard Medical School, Boston, MA, USA
| | - Susan Kornetsky
- Research Administration, Boston Children's Hospital, Boston, MA, USA
| | - Joseph A Majzoub
- Department of Pediatrics, Harvard Medical School, Boston, MA, USA
- Department of Pediatrics, Boston Children's Hospital, Boston, MA, USA
- Division of Endocrinology, Boston Children's Hospital, Boston, MA, USA
| | - Keith Marsolo
- Department of Population Health Sciences, Duke University School of Medicine, Durham, NC, USA
| | - Lisa J Martin
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, USA
- Division of Human Genetics, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
| | - Jeremy Nix
- Division of Biomedical Informatics, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
| | | | - Jason Stedman
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Arnold Strauss
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, USA
- Division of Cardiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
| | - Kristen L Sund
- Division of Human Genetics, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
| | - Deanne M Taylor
- Department of Pediatrics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
- Department of Biomedical and Health Informatics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Peter S White
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, USA
- Division of Biomedical Informatics, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
- Department of Biomedical Informatics, University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - Eric Marsh
- Division of Neurology, The Children's Hospital of Philadelphia, The Perelman School of Medicine at The University of Pennsylvania, Philadelphia, PA, USA
| | - Adda Grimberg
- Division of Endocrinology and Diabetes, The Children's Hospital of Philadelphia, The Perelman School of Medicine at The University of Pennsylvania, Philadelphia, PA, USA
| | - Colin Hawkes
- Division of Endocrinology and Diabetes, The Children's Hospital of Philadelphia, The Perelman School of Medicine at The University of Pennsylvania, Philadelphia, PA, USA
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Helbig I, Ellis CA. Personalized medicine in genetic epilepsies - possibilities, challenges, and new frontiers. Neuropharmacology 2020; 172:107970. [PMID: 32413583 DOI: 10.1016/j.neuropharm.2020.107970] [Citation(s) in RCA: 31] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2019] [Revised: 01/05/2020] [Accepted: 01/16/2020] [Indexed: 12/13/2022]
Abstract
Identifying the optimal treatment based on specific characteristics of each patient is the main promise of precision medicine. In the field of epilepsy, the identification of more than 100 causative genes provides the enticing possibility of treatments targeted to specific disease etiologies. These conditions include classical examples, such as the use of vitamin B6 in antiquitin deficiency or the ketogenic diet in GLUT1 deficiency, where the disease mechanism can be directly addressed by the selection of a specific therapeutic compound. For epilepsies caused by channelopathies there have been advances in understanding how the selection of existing medications can be targeted to the functional consequences of genetic alterations. We discuss the examples of the use of sodium channel blockers such as phenytoin and oxcarbazepine in the sodium channelopathies, quinidine in KCNT1-related epilepsies, and strategies in GRIN-related epilepsies as examples of epilepsy precision medicine. Assessing the clinical response to targeted treatments of these conditions has been complicated by genetic and phenotypic heterogeneity, as well as by various neurological and non-neurological comorbidities. Moving forward, the development of standardized outcome measures will be critical to successful precision medicine trials in complex and heterogeneous disorders like the epilepsies. Finally, we address new frontiers in epilepsy precision medicine, including the need to match the growing volume of genetic data with high-throughput functional assays to assess the functional consequences of genetic variants and the ability to extract clinical data at large scale from electronic medical records and apply quantitative methods based on standardized phenotyping language.
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Affiliation(s)
- Ingo Helbig
- Division of Neurology, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA; The Epilepsy NeuroGenetics Initiative (ENGIN), Children's Hospital of Philadelphia, Philadelphia, USA; Department of Biomedical and Health Informatics (DBHi), Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA; Department of Neurology, University of Pennsylvania, Perelman School of Medicine, Philadelphia, PA, 19104, USA.
| | - Colin A Ellis
- The Epilepsy NeuroGenetics Initiative (ENGIN), Children's Hospital of Philadelphia, Philadelphia, USA; Department of Biomedical and Health Informatics (DBHi), Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA; Department of Neurology, University of Pennsylvania, Perelman School of Medicine, Philadelphia, PA, 19104, USA
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4
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Helbig I, Lopez-Hernandez T, Shor O, Galer P, Ganesan S, Pendziwiat M, Rademacher A, Ellis CA, Hümpfer N, Schwarz N, Seiffert S, Peeden J, Shen J, Štěrbová K, Hammer TB, Møller RS, Shinde DN, Tang S, Smith L, Poduri A, Krause R, Benninger F, Helbig KL, Haucke V, Weber YG. A Recurrent Missense Variant in AP2M1 Impairs Clathrin-Mediated Endocytosis and Causes Developmental and Epileptic Encephalopathy. Am J Hum Genet 2019; 104:1060-1072. [PMID: 31104773 PMCID: PMC6556875 DOI: 10.1016/j.ajhg.2019.04.001] [Citation(s) in RCA: 57] [Impact Index Per Article: 11.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2019] [Accepted: 03/29/2019] [Indexed: 11/17/2022] Open
Abstract
The developmental and epileptic encephalopathies (DEEs) are heterogeneous disorders with a strong genetic contribution, but the underlying genetic etiology remains unknown in a significant proportion of individuals. To explore whether statistical support for genetic etiologies can be generated on the basis of phenotypic features, we analyzed whole-exome sequencing data and phenotypic similarities by using Human Phenotype Ontology (HPO) in 314 individuals with DEEs. We identified a de novo c.508C>T (p.Arg170Trp) variant in AP2M1 in two individuals with a phenotypic similarity that was higher than expected by chance (p = 0.003) and a phenotype related to epilepsy with myoclonic-atonic seizures. We subsequently found the same de novo variant in two individuals with neurodevelopmental disorders and generalized epilepsy in a cohort of 2,310 individuals who underwent diagnostic whole-exome sequencing. AP2M1 encodes the μ-subunit of the adaptor protein complex 2 (AP-2), which is involved in clathrin-mediated endocytosis (CME) and synaptic vesicle recycling. Modeling of protein dynamics indicated that the p.Arg170Trp variant impairs the conformational activation and thermodynamic entropy of the AP-2 complex. Functional complementation of both the μ-subunit carrying the p.Arg170Trp variant in human cells and astrocytes derived from AP-2μ conditional knockout mice revealed a significant impairment of CME of transferrin. In contrast, stability, expression levels, membrane recruitment, and localization were not impaired, suggesting a functional alteration of the AP-2 complex as the underlying disease mechanism. We establish a recurrent pathogenic variant in AP2M1 as a cause of DEEs with distinct phenotypic features, and we implicate dysfunction of the early steps of endocytosis as a disease mechanism in epilepsy.
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Affiliation(s)
- Ingo Helbig
- Division of Neurology, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA; Department of Biomedical and Health Informatics, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA; Department of Neuropediatrics, Christian-Albrechts-University of Kiel, 24105 Kiel, Germany; Department of Neurology, University of Pennsylvania, Perelman School of Medicine, Philadelphia, PA 19104, USA.
| | | | - Oded Shor
- Department of Neurology, Rabin Medical Center, Petach Tikva 4941492, Israel; Sackler School of Medicine, Tel Aviv University, Tel Aviv 6997801, Israel
| | - Peter Galer
- Division of Neurology, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA; Department of Biomedical and Health Informatics, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Shiva Ganesan
- Division of Neurology, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA; Department of Biomedical and Health Informatics, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Manuela Pendziwiat
- Department of Neuropediatrics, Christian-Albrechts-University of Kiel, 24105 Kiel, Germany
| | - Annika Rademacher
- Department of Neuropediatrics, Christian-Albrechts-University of Kiel, 24105 Kiel, Germany
| | - Colin A Ellis
- Department of Neurology, University of Pennsylvania, Perelman School of Medicine, Philadelphia, PA 19104, USA
| | - Nadja Hümpfer
- Leibniz-Forschungsinstitut für Molekulare Pharmakologie, 13125 Berlin, Germany; Freie Universität Berlin, Faculty of Biology, Chemistry, Pharmacy, 14195 Berlin, Germany
| | - Niklas Schwarz
- Department of Neurology and Epileptology, Hertie Institute for Clinical Brain Research, University of Tübingen, 72076 Tübingen, Germany
| | - Simone Seiffert
- Department of Neurology and Epileptology, Hertie Institute for Clinical Brain Research, University of Tübingen, 72076 Tübingen, Germany
| | - Joseph Peeden
- East Tennessee Children's Hospital, University of Tennessee Department of Medicine, Knoxville, TN 37916, USA
| | - Joseph Shen
- Division of Genetics, Department of Pediatrics, University of California San Francisco, Fresno, CA 93701, USA
| | - Katalin Štěrbová
- Department of Child Neurology, Charles University 2nd Faculty of Medicine and University Hospital Motol, 150 06 Prague, Czech Republic
| | | | - Rikke S Møller
- Danish Epilepsy Centre Filadelfia, 4293 Dianalund, Denmark; Institute for Regional Health Services, University of Southern Denmark, 5230 Odense, Denmark
| | - Deepali N Shinde
- Division of Clinical Genomics, Ambry Genetics, Aliso Viejo, CA 92656, USA
| | - Sha Tang
- Division of Clinical Genomics, Ambry Genetics, Aliso Viejo, CA 92656, USA
| | - Lacey Smith
- Epilepsy Genetics Program, Department of Neurology, Boston Children's Hospital, Boston, MA 02115, USA
| | - Annapurna Poduri
- Epilepsy Genetics Program, Department of Neurology, Boston Children's Hospital, Boston, MA 02115, USA; Department of Neurology, Harvard Medical School, Boston, MA 02115, USA
| | - Roland Krause
- Luxembourg Centre for Systems Biomedicine, University of Luxembourg, 4365 Esch-sur-Alzette, Luxembourg
| | - Felix Benninger
- Department of Neurology, Rabin Medical Center, Petach Tikva 4941492, Israel; Sackler School of Medicine, Tel Aviv University, Tel Aviv 6997801, Israel
| | - Katherine L Helbig
- Division of Neurology, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA; Department of Biomedical and Health Informatics, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Volker Haucke
- Leibniz-Forschungsinstitut für Molekulare Pharmakologie, 13125 Berlin, Germany; Freie Universität Berlin, Faculty of Biology, Chemistry, Pharmacy, 14195 Berlin, Germany
| | - Yvonne G Weber
- Department of Neurology and Epileptology, Hertie Institute for Clinical Brain Research, University of Tübingen, 72076 Tübingen, Germany; Department of Neurosurgery, University of Tübingen, 72076 Tübingen, Germany
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