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Baribeau DA, Vorstman JAS, Pearson TS. Selective Serotonin Reuptake Inhibitor Treatment Post Gene Therapy for an Ultrarare Neurometabolic Disorder (AADC Deficiency). J Am Acad Child Adolesc Psychiatry 2024; 63:571-573. [PMID: 38460745 DOI: 10.1016/j.jaac.2024.01.015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/26/2023] [Revised: 01/22/2024] [Accepted: 02/29/2024] [Indexed: 03/11/2024]
Abstract
A 7-year-old girl presented with persistent anxiety symptoms for several years following gene therapy for an ultrarare neurometabolic disorder (aromatic L-amino acid decarboxylase [AADC] deficiency). AADC is the final enzyme in the monoamine synthesis pathway (Figure 1).1 Its absence results in a severe combined deficiency in serotonin, dopamine, epinephrine, and norepinephrine, causing significant developmental delays, hypotonia, and dystonia. The incidence of AADC deficiency is estimated at ∼1 in 500,000,2 and ∼200 cases have been described.1 Recently available disease-modifying gene therapy for this condition dramatically improves motor symptoms, and received regulatory approval in some regions in 2022.2 There are no data to guide psychiatric care post gene therapy for AADC or other neurologic disorders to date.3.
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Affiliation(s)
- Danielle A Baribeau
- Holland Bloorview Kids Rehabilitation Hospital, Toronto, Ontario, Canada; The Hospital for Sick Children, Toronto, Ontario, Canada.
| | | | - Toni S Pearson
- Nationwide Children's Hospital, The Ohio State University, Columbus, Ohio
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2
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McLean A, Tchan M, Devery S, Smyth R, Shrestha R, Kumar KR, Tomlinson S, Tisch S, Wu KHC. Informing a value care model: lessons from an integrated adult neurogenomics clinic. Intern Med J 2023; 53:2198-2207. [PMID: 37092903 DOI: 10.1111/imj.16103] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2022] [Accepted: 04/17/2023] [Indexed: 04/25/2023]
Abstract
BACKGROUND Advances in genomics provide improved opportunities for diagnosis of complex neurogenetic disorders, yet the optimal approach to translate these benefits to the outpatient clinic is unclear. AIMS We retrospectively reviewed referral indications and outcomes of an integrated multidisciplinary team (MDT) clinic pathway for adults with suspected neurogenetic disorders. The associated cost implications were estimated. METHODS Consecutive patients who attended the neurogenomics clinic from January 2017 to April 2020 were included. The clinic comprised neurologists, clinical geneticists and genetic counsellors, who assessed each patient concurrently. RESULTS Ninety-nine new patients were referred spanning 45 different clinical diagnoses. Following MDT clinical assessment, 23% (23/99) of referral diagnoses were revised prior to molecular testing. Eighty-one patients (82%) underwent genetic testing, including 43 exome-based panels, 15 whole-genome sequencing, 14 single gene tests, 27 repeat-primed polymerase chain reaction testing and two chromosomal microarrays. Overall, 33/99 patients (33%) received a diagnosis, either a molecular diagnosis (n = 24, of which 22 were diagnostic and two were predictive) or a clinical diagnosis (n = 9). Of the clinical diagnosis cohort, five patients received a diagnosis without molecular testing and four patients whose negative testing (one diagnostic and three predictive) allowed exclusion of genetic differentials and, hence, confirmation of clinical diagnoses. The diagnostic rate following MDT and diagnostic testing was 30% (28/94), excluding the five predictive testing cases. MDT assessment aligned with eventual molecular diagnoses in 96% of cases. The estimated average costs were AU$1386 per patient undergoing MDT assessment and AU$4159 per diagnosis achieved. CONCLUSIONS We present an integrated multidisciplinary neurogenomics clinic pathway providing a diagnostic yield of 33% (30% excluding predictive testing cases), with costing implications. The relatively high diagnostic yield may be attributed to multidisciplinary input integrating accurate phenotyping of complex disorders and interpretation of genomic findings.
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Affiliation(s)
- Alison McLean
- St Vincent's Clinical School, UNSW, Sydney, New South Wales, Australia
- St Vincent's Clinical Genomics, St Vincent's Hospital, New South Wales, Sydney, Australia
| | - Michel Tchan
- St Vincent's Clinical Genomics, St Vincent's Hospital, New South Wales, Sydney, Australia
- Department of Genetic Medicine, Westmead Hospital, Sydney, New South Wales, Australia
- Discipline of Genetic Medicine, University of Sydney, Sydney, New South Wales, Australia
| | - Sophie Devery
- St Vincent's Clinical Genomics, St Vincent's Hospital, New South Wales, Sydney, Australia
| | - Renee Smyth
- St Vincent's Clinical Genomics, St Vincent's Hospital, New South Wales, Sydney, Australia
| | - Rupendra Shrestha
- Centre for Economic Impacts of Genomic Medicine, Macquarie University, Sydney, New South Wales, Australia
| | - Kishore R Kumar
- St Vincent's Clinical Genomics, St Vincent's Hospital, New South Wales, Sydney, Australia
- Molecular Medicine in Neurology, Concord Repatriation General Hospital and the University of Sydney, Sydney, New South Wales, Australia
- Kinghorn Centre for Clinical Genomics, Garvan Institute of Medical Research, Sydney, New South Wales, Australia
| | - Susan Tomlinson
- School of Medicine, University of Notre Dame, Sydney, New South Wales, Australia
- Department of Neurology, St Vincent's Hospital, Sydney, New South Wales, Australia
- Faculty of Medicine, University of Sydney, Sydney, New South Wales, Australia
| | - Stephen Tisch
- St Vincent's Clinical School, UNSW, Sydney, New South Wales, Australia
- School of Medicine, University of Notre Dame, Sydney, New South Wales, Australia
- Department of Neurology, St Vincent's Hospital, Sydney, New South Wales, Australia
| | - Kathy H C Wu
- St Vincent's Clinical School, UNSW, Sydney, New South Wales, Australia
- St Vincent's Clinical Genomics, St Vincent's Hospital, New South Wales, Sydney, Australia
- Discipline of Genetic Medicine, University of Sydney, Sydney, New South Wales, Australia
- School of Medicine, University of Notre Dame, Sydney, New South Wales, Australia
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Waung MW, Ma F, Wheeler AG, Zai CC, So J. The Diagnostic Landscape of Adult Neurogenetic Disorders. BIOLOGY 2023; 12:1459. [PMID: 38132285 PMCID: PMC10740572 DOI: 10.3390/biology12121459] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/01/2023] [Revised: 11/11/2023] [Accepted: 11/16/2023] [Indexed: 12/23/2023]
Abstract
Neurogenetic diseases affect individuals across the lifespan, but accurate diagnosis remains elusive for many patients. Adults with neurogenetic disorders often undergo a long diagnostic odyssey, with multiple specialist evaluations and countless investigations without a satisfactory diagnostic outcome. Reasons for these diagnostic challenges include: (1) clinical features of neurogenetic syndromes are diverse and under-recognized, particularly those of adult-onset, (2) neurogenetic syndromes may manifest with symptoms that span multiple neurological and medical subspecialties, and (3) a positive family history may not be present or readily apparent. Furthermore, there is a large gap in the understanding of how to apply genetic diagnostic tools in adult patients, as most of the published literature focuses on the pediatric population. Despite these challenges, accurate genetic diagnosis is imperative to provide affected individuals and their families guidance on prognosis, recurrence risk, and, for an increasing number of disorders, offer targeted treatment. Here, we provide a framework for recognizing adult neurogenetic syndromes, describe the current diagnostic approach, and highlight studies using next-generation sequencing in different neurological disease cohorts. We also discuss diagnostic pitfalls, barriers to achieving a definitive diagnosis, and emerging technology that may increase the diagnostic yield of testing.
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Affiliation(s)
- Maggie W. Waung
- Division of General Neurology, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, CA 94158, USA
| | - Fion Ma
- Institute for Human Genetics, University of California San Francisco School of Medicine, San Francisco, CA 94143, USA
| | - Allison G. Wheeler
- Institute for Human Genetics, University of California San Francisco School of Medicine, San Francisco, CA 94143, USA
- Department of Neurology, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Clement C. Zai
- Tanenbaum Centre for Pharmacogenetics, Molecular Brain Science, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON M5T 1R8, Canada
- Department of Psychiatry, Institute of Medical Science, Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON M5S 1A8, Canada
| | - Joyce So
- Division of Medical Genetics, Department of Pediatrics, University of California, San Francisco, CA 94158, USA
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