Clinically Responsive Genomic Analysis Pipelines: Elements to Improve Detection Rate and Efficiency

Samantha Leigh Sundercombe¹, Marina Berbic², Carey-Anne Evans³, Corrina Cliffe⁴, George Elakis⁴, Suzanna E L Temple⁵, Arthavan Selvanathan⁶, Lisa Ewans⁷, Nila Quayum⁴, Cheng-Yee Nixon⁸, Kerith-Rae Dias⁹, Sarah Lang⁴, Anna Richards⁴, Shuxiang Goh⁸, Meredith Wilson¹⁰, David Mowat¹¹, Rani Sachdev¹¹, Sarah Sandaradura¹⁰, Maie Walsh¹², Michelle A Farrar¹³, Rebecca Walsh⁴, Janice Fletcher⁴, Edwin P Kirk¹⁴, Guus M Teunisse³, Deborah Schofield¹⁵, Michael Francis Buckley⁴, Ying Zhu¹⁶, Tony Roscioli¹⁷

Affiliations

¹ NSW Health Pathology Randwick Genomics, Prince of Wales Hospital, Randwick, New South Wales, Australia. Electronic address: samantha.sundercombe@health.nsw.gov.au.
² NSW Health Pathology Randwick Genomics, Prince of Wales Hospital, Randwick, New South Wales, Australia; School of Women's and Children's Health, University of New South Wales Sydney, Kensington, New South Wales, Australia.
³ Neuroscience Research Australia (NeuRA), Randwick, New South Wales, Australia.
⁴ NSW Health Pathology Randwick Genomics, Prince of Wales Hospital, Randwick, New South Wales, Australia.
⁵ NSW Health Pathology Randwick Genomics, Prince of Wales Hospital, Randwick, New South Wales, Australia; Neuroscience Research Australia (NeuRA), Randwick, New South Wales, Australia; Centre for Clinical Genetics, Sydney Children's Hospital, Sydney, Randwick, New South Wales, Australia.
⁶ NSW Health Pathology Randwick Genomics, Prince of Wales Hospital, Randwick, New South Wales, Australia; Neuroscience Research Australia (NeuRA), Randwick, New South Wales, Australia; Discipline of Child and Adolescent Health, The University of Sydney, New South Wales, Australia.
⁷ Department of Medical Genomics, Royal Prince Alfred Hospital, Sydney, New South Wales, Australia; Central Clinical School, Sydney Medical School, The University of Sydney, New South Wales, Australia.
⁸ NSW Health Pathology Randwick Genomics, Prince of Wales Hospital, Randwick, New South Wales, Australia; Neuroscience Research Australia (NeuRA), Randwick, New South Wales, Australia.
⁹ Neuroscience Research Australia (NeuRA), Randwick, New South Wales, Australia; Prince of Wales Clinical School, Faculty of Medicine, University of New South Wales Sydney, Kensington, New South Wales, Australia.
¹⁰ Department of Clinical Genetics, Children's Hospital at Westmead, Sydney, Westmead, New South Wales, Australia.
¹¹ Centre for Clinical Genetics, Sydney Children's Hospital, Sydney, Randwick, New South Wales, Australia.
¹² Genetic Medicine Department, Royal Melbourne Hospital, Parkville, Victoria, Australia.
¹³ School of Women's and Children's Health, University of New South Wales Sydney, Kensington, New South Wales, Australia; Neurology Department, Sydney Children's Hospital, Sydney, Randwick, New South Wales, Australia.
¹⁴ NSW Health Pathology Randwick Genomics, Prince of Wales Hospital, Randwick, New South Wales, Australia; School of Women's and Children's Health, University of New South Wales Sydney, Kensington, New South Wales, Australia; Centre for Clinical Genetics, Sydney Children's Hospital, Sydney, Randwick, New South Wales, Australia.
¹⁵ Centre for Economic Impacts of Genomic Medicine, Macquarie Business School, Macquarie University, Macquarie Park, New South Wales, Australia.
¹⁶ NSW Health Pathology Randwick Genomics, Prince of Wales Hospital, Randwick, New South Wales, Australia; Neuroscience Research Australia (NeuRA), Randwick, New South Wales, Australia; Genetics of Learning Disability Service, Hunter Genetics, Waratah Newcastle, New South Wales, Australia.
¹⁷ NSW Health Pathology Randwick Genomics, Prince of Wales Hospital, Randwick, New South Wales, Australia; Neuroscience Research Australia (NeuRA), Randwick, New South Wales, Australia; Centre for Clinical Genetics, Sydney Children's Hospital, Sydney, Randwick, New South Wales, Australia. Electronic address: tony.roscioli@health.nsw.gov.au.

PMID: 33962052
DOI: 10.1016/j.jmoldx.2021.04.007

Free article

Clinically Responsive Genomic Analysis Pipelines: Elements to Improve Detection Rate and Efficiency

Samantha Leigh Sundercombe et al. J Mol Diagn. 2021 Jul.

Free article

. 2021 Jul;23(7):894-905.

doi: 10.1016/j.jmoldx.2021.04.007. Epub 2021 May 5.

Authors

Affiliations

¹ NSW Health Pathology Randwick Genomics, Prince of Wales Hospital, Randwick, New South Wales, Australia. Electronic address: samantha.sundercombe@health.nsw.gov.au.
² NSW Health Pathology Randwick Genomics, Prince of Wales Hospital, Randwick, New South Wales, Australia; School of Women's and Children's Health, University of New South Wales Sydney, Kensington, New South Wales, Australia.
³ Neuroscience Research Australia (NeuRA), Randwick, New South Wales, Australia.
⁴ NSW Health Pathology Randwick Genomics, Prince of Wales Hospital, Randwick, New South Wales, Australia.
⁵ NSW Health Pathology Randwick Genomics, Prince of Wales Hospital, Randwick, New South Wales, Australia; Neuroscience Research Australia (NeuRA), Randwick, New South Wales, Australia; Centre for Clinical Genetics, Sydney Children's Hospital, Sydney, Randwick, New South Wales, Australia.
⁶ NSW Health Pathology Randwick Genomics, Prince of Wales Hospital, Randwick, New South Wales, Australia; Neuroscience Research Australia (NeuRA), Randwick, New South Wales, Australia; Discipline of Child and Adolescent Health, The University of Sydney, New South Wales, Australia.
⁷ Department of Medical Genomics, Royal Prince Alfred Hospital, Sydney, New South Wales, Australia; Central Clinical School, Sydney Medical School, The University of Sydney, New South Wales, Australia.
⁸ NSW Health Pathology Randwick Genomics, Prince of Wales Hospital, Randwick, New South Wales, Australia; Neuroscience Research Australia (NeuRA), Randwick, New South Wales, Australia.
⁹ Neuroscience Research Australia (NeuRA), Randwick, New South Wales, Australia; Prince of Wales Clinical School, Faculty of Medicine, University of New South Wales Sydney, Kensington, New South Wales, Australia.
¹⁰ Department of Clinical Genetics, Children's Hospital at Westmead, Sydney, Westmead, New South Wales, Australia.
¹¹ Centre for Clinical Genetics, Sydney Children's Hospital, Sydney, Randwick, New South Wales, Australia.
¹² Genetic Medicine Department, Royal Melbourne Hospital, Parkville, Victoria, Australia.
¹³ School of Women's and Children's Health, University of New South Wales Sydney, Kensington, New South Wales, Australia; Neurology Department, Sydney Children's Hospital, Sydney, Randwick, New South Wales, Australia.
¹⁴ NSW Health Pathology Randwick Genomics, Prince of Wales Hospital, Randwick, New South Wales, Australia; School of Women's and Children's Health, University of New South Wales Sydney, Kensington, New South Wales, Australia; Centre for Clinical Genetics, Sydney Children's Hospital, Sydney, Randwick, New South Wales, Australia.
¹⁵ Centre for Economic Impacts of Genomic Medicine, Macquarie Business School, Macquarie University, Macquarie Park, New South Wales, Australia.
¹⁶ NSW Health Pathology Randwick Genomics, Prince of Wales Hospital, Randwick, New South Wales, Australia; Neuroscience Research Australia (NeuRA), Randwick, New South Wales, Australia; Genetics of Learning Disability Service, Hunter Genetics, Waratah Newcastle, New South Wales, Australia.
¹⁷ NSW Health Pathology Randwick Genomics, Prince of Wales Hospital, Randwick, New South Wales, Australia; Neuroscience Research Australia (NeuRA), Randwick, New South Wales, Australia; Centre for Clinical Genetics, Sydney Children's Hospital, Sydney, Randwick, New South Wales, Australia. Electronic address: tony.roscioli@health.nsw.gov.au.

PMID: 33962052
DOI: 10.1016/j.jmoldx.2021.04.007

Abstract

Massively parallel sequencing has markedly improved mendelian diagnostic rates. This study assessed the effects of custom alterations to a diagnostic genomic bioinformatic pipeline in response to clinical need and derived practice recommendations relative to diagnostic rates and efficiency. The Genomic Annotation and Interpretation Application (GAIA) bioinformatics pipeline was designed to detect panel, exome, and genome sample integrity and prioritize gene variants in mendelian disorders. Reanalysis of selected negative cases was performed after improvements to the pipeline. GAIA improvements and their effect on sensitivity are described, including addition of a PubMed search for gene-disease associations not in the Online Mendelian Inheritance of Man database, inclusion of a process for calling low-quality variants (known as QPatch), and gene symbol nomenclature consistency checking. The new pipeline increased the diagnostic rate and reduced staff costs, resulting in a saving of US$844.34 per additional diagnosis. Recommendations for genomic analysis pipeline requirements are summarized. Clinically responsive bioinformatics pipeline improvements increase diagnostic sensitivity and increase cost-effectiveness.

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Clinically Responsive Genomic Analysis Pipelines: Elements to Improve Detection Rate and Efficiency

Affiliations

Clinically Responsive Genomic Analysis Pipelines: Elements to Improve Detection Rate and Efficiency

Authors

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Abstract

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MeSH terms

LinkOut - more resources

Full Text Sources

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Medical