BACKGROUND: Neurological disorders are clinically heterogeneous group of disorders and are major causes of disability and death. Several of these disorders are caused due to genetic aberration. A precise and confirmatory diagnosis in the patients in a timely manner is essential for appropriate therapeutic and management strategies. Due to the complexity of the clinical presentations across various neurological disorders, arriving at an accurate diagnosis remains a challenge. METHODS: We sequenced 1012 unrelated patients from India with suspected neurological disorders, using TruSight One panel. Genetic variations were identified using the Strand NGS software and interpreted using the StrandOmics platform. RESULTS: We were able to detect mutations in 197 genes in 405 (40%) cases and 178 mutations were novel. The highest diagnostic rate was observed among patients with muscular dystrophy (64%) followed by leukodystrophy and ataxia (43%, each). In our cohort, 26% of the patients who received definitive diagnosis were primarily referred with complex neurological phenotypes with no suggestive diagnosis. In terms of mutations types, 62.8% were truncating and in addition, 13.4% were structural variants, which are also likely to cause loss of function. CONCLUSION: In our study, we observed an improved performance of multi-gene panel testing, with an overall diagnostic yield of 40%. Furthermore, we show that NGS (next-generation sequencing)-based testing is comprehensive and can detect all types of variants including structural variants. It can be considered as a single-platform genetic test for neurological disorders that can provide a swift and definitive diagnosis in a cost-effective manner.
BACKGROUND:Neurological disorders are clinically heterogeneous group of disorders and are major causes of disability and death. Several of these disorders are caused due to genetic aberration. A precise and confirmatory diagnosis in the patients in a timely manner is essential for appropriate therapeutic and management strategies. Due to the complexity of the clinical presentations across various neurological disorders, arriving at an accurate diagnosis remains a challenge. METHODS: We sequenced 1012 unrelated patients from India with suspected neurological disorders, using TruSight One panel. Genetic variations were identified using the Strand NGS software and interpreted using the StrandOmics platform. RESULTS: We were able to detect mutations in 197 genes in 405 (40%) cases and 178 mutations were novel. The highest diagnostic rate was observed among patients with muscular dystrophy (64%) followed by leukodystrophy and ataxia (43%, each). In our cohort, 26% of the patients who received definitive diagnosis were primarily referred with complex neurological phenotypes with no suggestive diagnosis. In terms of mutations types, 62.8% were truncating and in addition, 13.4% were structural variants, which are also likely to cause loss of function. CONCLUSION: In our study, we observed an improved performance of multi-gene panel testing, with an overall diagnostic yield of 40%. Furthermore, we show that NGS (next-generation sequencing)-based testing is comprehensive and can detect all types of variants including structural variants. It can be considered as a single-platform genetic test for neurological disorders that can provide a swift and definitive diagnosis in a cost-effective manner.
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Authors: Yaping Yang; Donna M Muzny; Fan Xia; Zhiyv Niu; Richard Person; Yan Ding; Patricia Ward; Alicia Braxton; Min Wang; Christian Buhay; Narayanan Veeraraghavan; Alicia Hawes; Theodore Chiang; Magalie Leduc; Joke Beuten; Jing Zhang; Weimin He; Jennifer Scull; Alecia Willis; Megan Landsverk; William J Craigen; Mir Reza Bekheirnia; Asbjorg Stray-Pedersen; Pengfei Liu; Shu Wen; Wendy Alcaraz; Hong Cui; Magdalena Walkiewicz; Jeffrey Reid; Matthew Bainbridge; Ankita Patel; Eric Boerwinkle; Arthur L Beaudet; James R Lupski; Sharon E Plon; Richard A Gibbs; Christine M Eng Journal: JAMA Date: 2014-11-12 Impact factor: 56.272
Authors: Hane Lee; Joshua L Deignan; Naghmeh Dorrani; Samuel P Strom; Sibel Kantarci; Fabiola Quintero-Rivera; Kingshuk Das; Traci Toy; Bret Harry; Michael Yourshaw; Michelle Fox; Brent L Fogel; Julian A Martinez-Agosto; Derek A Wong; Vivian Y Chang; Perry B Shieh; Christina G S Palmer; Katrina M Dipple; Wayne W Grody; Eric Vilain; Stanley F Nelson Journal: JAMA Date: 2014-11-12 Impact factor: 56.272
Authors: Kelly D Farwell; Layla Shahmirzadi; Dima El-Khechen; Zöe Powis; Elizabeth C Chao; Brigette Tippin Davis; Ruth M Baxter; Wenqi Zeng; Cameron Mroske; Melissa C Parra; Stephanie K Gandomi; Ira Lu; Xiang Li; Hong Lu; Hsiao-Mei Lu; David Salvador; David Ruble; Monica Lao; Soren Fischbach; Jennifer Wen; Shela Lee; Aaron Elliott; Charles L M Dunlop; Sha Tang Journal: Genet Med Date: 2014-11-13 Impact factor: 8.822
Authors: Sue Richards; Nazneen Aziz; Sherri Bale; David Bick; Soma Das; Julie Gastier-Foster; Wayne W Grody; Madhuri Hegde; Elaine Lyon; Elaine Spector; Karl Voelkerding; Heidi L Rehm Journal: Genet Med Date: 2015-03-05 Impact factor: 8.822
Authors: Gemma L Carvill; Sinéad B Heavin; Simone C Yendle; Jacinta M McMahon; Brian J O'Roak; Joseph Cook; Adiba Khan; Michael O Dorschner; Molly Weaver; Sophie Calvert; Stephen Malone; Geoffrey Wallace; Thorsten Stanley; Ann M E Bye; Andrew Bleasel; Katherine B Howell; Sara Kivity; Mark T Mackay; Victoria Rodriguez-Casero; Richard Webster; Amos Korczyn; Zaid Afawi; Nathanel Zelnick; Tally Lerman-Sagie; Dorit Lev; Rikke S Møller; Deepak Gill; Danielle M Andrade; Jeremy L Freeman; Lynette G Sadleir; Jay Shendure; Samuel F Berkovic; Ingrid E Scheffer; Heather C Mefford Journal: Nat Genet Date: 2013-05-26 Impact factor: 38.330
Authors: Samuel P Strom; Hane Lee; Kingshuk Das; Eric Vilain; Stanley F Nelson; Wayne W Grody; Joshua L Deignan Journal: Genet Med Date: 2014-01-09 Impact factor: 8.822
Authors: Jorge Andres Olave-Rodriguez; Francisco Javier Bonilla-Escobar; Estephania Candelo; Lisa Ximena Rodriguez-Rojas Journal: Appl Clin Genet Date: 2021-12-16