Gina L O'Grady1,2, Monkol Lek1,3,4, Shireen R Lamande5,6, Leigh Waddell1, Emily C Oates1,2, Jaya Punetha7, Roula Ghaoui1,2, Sarah A Sandaradura1,2, Heather Best1,2, Simranpreet Kaur1, Mark Davis8, Nigel G Laing8,9,10, Francesco Muntoni11, Eric Hoffman7, Daniel G MacArthur3,4, Nigel F Clarke1,2, Sandra Cooper1,2, Kathryn North1,5,12. 1. Institute for Neuroscience and Muscle Research, Kids Research Institute, Children's Hospital at Westmead, Westmead, New South Wales, Australia. 2. Discipline of Paediatrics and Child Health, Faculty of Medicine, University of Sydney, Sydney, New South Wales, Australia. 3. Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA. 4. Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA. 5. Murdoch Childrens Research Institute, Melbourne, Victoria, Australia. 6. Department of Paediatrics, University of Melbourne, Parkville, Victoria, Australia. 7. Research Center for Genetic Medicine, Children's National Medical Center, Washington, DC. 8. Department of Diagnostic Genomics, PathWest Laboratory Medicine, QEII Medical Centre, Nedlands, Western Australia, Australia. 9. Centre for Medical Research, University of Western Australia, Perth, Western Australia, Australia. 10. Neurogenetic Unit, Harry Perkins Institute of Medical Research, Nedlands, Western Australia, Australia. 11. Dubowitz Neuromuscular Centre, UCL Institute of Child Health and Great Ormond Street Hospital for Children, London, United Kingdom. 12. Department of Paediatrics, Faculty of Medicine, University of Melbourne, Melbourne, Victoria, Australia.
Abstract
OBJECTIVE: To evaluate the diagnostic outcomes in a large cohort of congenital muscular dystrophy (CMD) patients using traditional and next generation sequencing (NGS) technologies. METHODS: A total of 123 CMD patients were investigated using the traditional approaches of histology, immunohistochemical analysis of muscle biopsy, and candidate gene sequencing. Undiagnosed patients available for further testing were investigated using NGS. RESULTS: Muscle biopsy and immunohistochemical analysis found deficiencies of laminin α2, α-dystroglycan, or collagen VI in 50% of patients. Candidate gene sequencing and chromosomal microarray established a genetic diagnosis in 32% (39 of 123). Of 85 patients presenting in the past 20 years, 28 of 51 who lacked a confirmed genetic diagnosis (55%) consented to NGS studies, leading to confirmed diagnoses in a further 11 patients. Using the combination of approaches, a confirmed genetic diagnosis was achieved in 51% (43 of 85). The diagnoses within the cohort were heterogeneous. Forty-five of 59 probands with confirmed or probable diagnoses had variants in genes known to cause CMD (76%), and 11 of 59 (19%) had variants in genes associated with congenital myopathies, reflecting overlapping features of these conditions. One patient had a congenital myasthenic syndrome, and 2 had microdeletions. Within the cohort, 5 patients had variants in novel (PIGY and GMPPB) or recently published genes (GFPT1 and MICU1), and 7 had variants in TTN or RYR1, large genes that are technically difficult to Sanger sequence. INTERPRETATION: These data support NGS as a first-line tool for genetic evaluation of patients with a clinical phenotype suggestive of CMD, with muscle biopsy reserved as a second-tier investigation. Ann Neurol 2016;80:101-111.
OBJECTIVE: To evaluate the diagnostic outcomes in a large cohort of congenital muscular dystrophy (CMD) patients using traditional and next generation sequencing (NGS) technologies. METHODS: A total of 123 CMDpatients were investigated using the traditional approaches of histology, immunohistochemical analysis of muscle biopsy, and candidate gene sequencing. Undiagnosed patients available for further testing were investigated using NGS. RESULTS: Muscle biopsy and immunohistochemical analysis found deficiencies of laminin α2, α-dystroglycan, or collagen VI in 50% of patients. Candidate gene sequencing and chromosomal microarray established a genetic diagnosis in 32% (39 of 123). Of 85 patients presenting in the past 20 years, 28 of 51 who lacked a confirmed genetic diagnosis (55%) consented to NGS studies, leading to confirmed diagnoses in a further 11 patients. Using the combination of approaches, a confirmed genetic diagnosis was achieved in 51% (43 of 85). The diagnoses within the cohort were heterogeneous. Forty-five of 59 probands with confirmed or probable diagnoses had variants in genes known to cause CMD (76%), and 11 of 59 (19%) had variants in genes associated with congenital myopathies, reflecting overlapping features of these conditions. One patient had a congenital myasthenic syndrome, and 2 had microdeletions. Within the cohort, 5 patients had variants in novel (PIGY and GMPPB) or recently published genes (GFPT1 and MICU1), and 7 had variants in TTN or RYR1, large genes that are technically difficult to Sanger sequence. INTERPRETATION: These data support NGS as a first-line tool for genetic evaluation of patients with a clinical phenotype suggestive of CMD, with muscle biopsy reserved as a second-tier investigation. Ann Neurol 2016;80:101-111.
Authors: Samantha J Bryen; Himanshu Joshi; Frances J Evesson; Cyrille Girard; Roula Ghaoui; Leigh B Waddell; Alison C Testa; Beryl Cummings; Susan Arbuckle; Nicole Graf; Richard Webster; Daniel G MacArthur; Nigel G Laing; Mark R Davis; Reinhard Lührmann; Sandra T Cooper Journal: Am J Hum Genet Date: 2019-08-22 Impact factor: 11.025
Authors: Samantha J Bryen; Lisa J Ewans; Jason Pinner; Suzanna C MacLennan; Sandra Donkervoort; Diana Castro; Ana Töpf; Gina O'Grady; Beryl Cummings; Katherine R Chao; Ben Weisburd; Laurent Francioli; Fathimath Faiz; Adam M Bournazos; Ying Hu; Carla Grosmann; Denise M Malicki; Helen Doyle; Nanna Witting; John Vissing; Kristl G Claeys; Kathryn Urankar; Ana Beleza-Meireles; Julia Baptista; Sian Ellard; Marco Savarese; Mridul Johari; Anna Vihola; Bjarne Udd; Anirban Majumdar; Volker Straub; Carsten G Bönnemann; Daniel G MacArthur; Mark R Davis; Sandra T Cooper Journal: Hum Mutat Date: 2019-12-03 Impact factor: 4.878
Authors: Deborah Schofield; Khurshid Alam; Lyndal Douglas; Rupendra Shrestha; Daniel G MacArthur; Mark Davis; Nigel G Laing; Nigel F Clarke; Joshua Burns; Sandra T Cooper; Kathryn N North; Sarah A Sandaradura; Gina L O'Grady Journal: NPJ Genom Med Date: 2017-03-03 Impact factor: 8.617
Authors: Manuela Wiessner; Andreas Roos; Christopher J Munn; Ranjith Viswanathan; Tamieka Whyte; Dan Cox; Benedikt Schoser; Caroline Sewry; Helen Roper; Rahul Phadke; Chiara Marini Bettolo; Rita Barresi; Richard Charlton; Carsten G Bönnemann; Osório Abath Neto; Umbertina C Reed; Edmar Zanoteli; Cristiane Araújo Martins Moreno; Birgit Ertl-Wagner; Rolf Stucka; Christian De Goede; Tamiris Borges da Silva; Denisa Hathazi; Margherita Dell'Aica; René P Zahedi; Simone Thiele; Juliane Müller; Helen Kingston; Susanna Müller; Elizabeth Curtis; Maggie C Walter; Tim M Strom; Volker Straub; Kate Bushby; Francesco Muntoni; Laura E Swan; Hanns Lochmüller; Jan Senderek Journal: Am J Hum Genet Date: 2017-02-09 Impact factor: 11.025