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Wang Y, He Y, Shi Y, Qian DC, Gray KJ, Winn R, Martin AR. Aspiring toward equitable benefits from genomic advances to individuals of ancestrally diverse backgrounds. Am J Hum Genet 2024; 111:809-824. [PMID: 38642557 PMCID: PMC11080611 DOI: 10.1016/j.ajhg.2024.04.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2023] [Revised: 04/01/2024] [Accepted: 04/01/2024] [Indexed: 04/22/2024] Open
Abstract
Advancements in genomic technologies have shown remarkable promise for improving health trajectories. The Human Genome Project has catalyzed the integration of genomic tools into clinical practice, such as disease risk assessment, prenatal testing and reproductive genomics, cancer diagnostics and prognostication, and therapeutic decision making. Despite the promise of genomic technologies, their full potential remains untapped without including individuals of diverse ancestries and integrating social determinants of health (SDOHs). The NHGRI launched the 2020 Strategic Vision with ten bold predictions by 2030, including "individuals from ancestrally diverse backgrounds will benefit equitably from advances in human genomics." Meeting this goal requires a holistic approach that brings together genomic advancements with careful consideration to healthcare access as well as SDOHs to ensure that translation of genetics research is inclusive, affordable, and accessible and ultimately narrows rather than widens health disparities. With this prediction in mind, this review delves into the two paramount applications of genetic testing-reproductive genomics and precision oncology. When discussing these applications of genomic advancements, we evaluate current accessibility limitations, highlight challenges in achieving representativeness, and propose paths forward to realize the ultimate goal of their equitable applications.
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Affiliation(s)
- Ying Wang
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA.
| | - Yixuan He
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Yue Shi
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA; Reproductive Medicine Center, the First Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong 510080, China
| | - David C Qian
- Department of Thoracic Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Kathryn J Gray
- Department of Obstetrics and Gynecology, University of Washington, Seattle, WA, USA
| | - Robert Winn
- Virginia Commonwealth University Massey Cancer Center, Richmond, VA, USA
| | - Alicia R Martin
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA.
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2
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Ma H, Zhu L, Yang X, Ao M, Zhang S, Guo M, Dai X, Ma X, Zhang X. Genetic and phenotypic analysis of 225 Chinese children with developmental delay and/or intellectual disability using whole-exome sequencing. BMC Genomics 2024; 25:391. [PMID: 38649797 PMCID: PMC11034079 DOI: 10.1186/s12864-024-10279-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2023] [Accepted: 04/02/2024] [Indexed: 04/25/2024] Open
Abstract
Developmental delay (DD), or intellectual disability (ID) is a very large group of early onset disorders that affects 1-2% of children worldwide, which have diverse genetic causes that should be identified. Genetic studies can elucidate the pathogenesis underlying DD/ID. In this study, whole-exome sequencing (WES) was performed on 225 Chinese DD/ID children (208 cases were sequenced as proband-parent trio) who were classified into seven phenotype subgroups. The phenotype and genomic data of patients with DD/ID were further retrospectively analyzed. There were 96/225 (42.67%; 95% confidence interval [CI] 36.15-49.18%) patients were found to have causative single nucleotide variants (SNVs) and small insertions/deletions (Indels) associated with DD/ID based on WES data. The diagnostic yields among the seven subgroups ranged from 31.25 to 71.43%. Three specific clinical features, hearing loss, visual loss, and facial dysmorphism, can significantly increase the diagnostic yield of WES in patients with DD/ID (P = 0.005, P = 0.005, and P = 0.039, respectively). Of note, hearing loss (odds ratio [OR] = 1.86%; 95% CI = 1.00-3.46, P = 0.046) or abnormal brainstem auditory evoked potential (BAEP) (OR = 1.91, 95% CI = 1.02-3.50, P = 0.042) was independently associated with causative genetic variants in DD/ID children. Our findings enrich the variation spectrums of SNVs/Indels associated with DD/ID, highlight the value genetic testing for DD/ID children, stress the importance of BAEP screen in DD/ID children, and help to facilitate early diagnose, clinical management and reproductive decisions, improve therapeutic response to medical treatment.
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Affiliation(s)
- Heqian Ma
- The School of Public Health, Guilin Medical University, 1 Zhiyuan Road, Lingui District, 541199, Guilin, PR China
| | - Lina Zhu
- Faculty of Pediatrics, The Chinese PLA General Hospital, 100700, Beijing, China
- National Engineering Laboratory for Birth Defects Prevention and Control of Key Technology, 100700, Beijing, China
- Beijing Key Laboratory of Pediatric Organ Failure, 100700, Beijing, China
| | - Xiao Yang
- Faculty of Pediatrics, The Chinese PLA General Hospital, 100700, Beijing, China
- National Engineering Laboratory for Birth Defects Prevention and Control of Key Technology, 100700, Beijing, China
- Beijing Key Laboratory of Pediatric Organ Failure, 100700, Beijing, China
| | - Meng Ao
- The School of Public Health, Guilin Medical University, 1 Zhiyuan Road, Lingui District, 541199, Guilin, PR China
| | - Shunxiang Zhang
- The School of Public Health, Guilin Medical University, 1 Zhiyuan Road, Lingui District, 541199, Guilin, PR China
| | - Meizhen Guo
- The School of Public Health, Guilin Medical University, 1 Zhiyuan Road, Lingui District, 541199, Guilin, PR China
| | - Xuelin Dai
- The School of Public Health, Guilin Medical University, 1 Zhiyuan Road, Lingui District, 541199, Guilin, PR China
| | - Xiuwei Ma
- Faculty of Pediatrics, The Chinese PLA General Hospital, 100700, Beijing, China.
- National Engineering Laboratory for Birth Defects Prevention and Control of Key Technology, 100700, Beijing, China.
- Beijing Key Laboratory of Pediatric Organ Failure, 100700, Beijing, China.
| | - Xiaoying Zhang
- The School of Public Health, Guilin Medical University, 1 Zhiyuan Road, Lingui District, 541199, Guilin, PR China.
- The Guangxi Key Laboratory of Environmental Exposomics and Entire Lifecycle Heath, 1 Zhiyuan Road, Lingui District, 541199, Guilin, PR China.
- Guangxi Health Commission Key Laboratory of Entire Lifecycle Health and Care, 1 Zhiyuan Road, Lingui District, 541199, Guilin, PR China.
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3
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Baldridge D, Kaster L, Sancimino C, Srivastava S, Molholm S, Gupta A, Oh I, Lanzotti V, Grewal D, Riggs ER, Savatt JM, Hauck R, Sveden A, Constantino JN, Piven J, Gurnett CA, Chopra M, Hazlett H, Payne PRO. The Brain Gene Registry: a data snapshot. J Neurodev Disord 2024; 16:17. [PMID: 38632549 PMCID: PMC11022437 DOI: 10.1186/s11689-024-09530-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/17/2023] [Accepted: 03/27/2024] [Indexed: 04/19/2024] Open
Abstract
Monogenic disorders account for a large proportion of population-attributable risk for neurodevelopmental disabilities. However, the data necessary to infer a causal relationship between a given genetic variant and a particular neurodevelopmental disorder is often lacking. Recognizing this scientific roadblock, 13 Intellectual and Developmental Disabilities Research Centers (IDDRCs) formed a consortium to create the Brain Gene Registry (BGR), a repository pairing clinical genetic data with phenotypic data from participants with variants in putative brain genes. Phenotypic profiles are assembled from the electronic health record (EHR) and a battery of remotely administered standardized assessments collectively referred to as the Rapid Neurobehavioral Assessment Protocol (RNAP), which include cognitive, neurologic, and neuropsychiatric assessments, as well as assessments for attention deficit hyperactivity disorder (ADHD) and autism spectrum disorder (ASD). Co-enrollment of BGR participants in the Clinical Genome Resource's (ClinGen's) GenomeConnect enables display of variant information in ClinVar. The BGR currently contains data on 479 participants who are 55% male, 6% Asian, 6% Black or African American, 76% white, and 12% Hispanic/Latine. Over 200 genes are represented in the BGR, with 12 or more participants harboring variants in each of these genes: CACNA1A, DNMT3A, SLC6A1, SETD5, and MYT1L. More than 30% of variants are de novo and 43% are classified as variants of uncertain significance (VUSs). Mean standard scores on cognitive or developmental screens are below average for the BGR cohort. EHR data reveal developmental delay as the earliest and most common diagnosis in this sample, followed by speech and language disorders, ASD, and ADHD. BGR data has already been used to accelerate gene-disease validity curation of 36 genes evaluated by ClinGen's BGR Intellectual Disability (ID)-Autism (ASD) Gene Curation Expert Panel. In summary, the BGR is a resource for use by stakeholders interested in advancing translational research for brain genes and continues to recruit participants with clinically reported variants to establish a rich and well-characterized national resource to promote research on neurodevelopmental disorders.
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Affiliation(s)
- Dustin Baldridge
- Department of Pediatrics, Washington University School of Medicine in St. Louis, St. Louis, MO, USA.
| | - Levi Kaster
- Institute for Informatics, Data Science and Biostatistics, Washington University School of Medicine in St. Louis, St. Louis, MO, USA
| | - Catherine Sancimino
- Department of Pediatrics, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Siddharth Srivastava
- Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
- Rosamund Stone Zander Translational Neuroscience Center, Boston Children's Hospital, Boston, MA, USA
| | - Sophie Molholm
- Departments of Pediatrics and Neuroscience, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Aditi Gupta
- Institute for Informatics, Data Science and Biostatistics, Washington University School of Medicine in St. Louis, St. Louis, MO, USA
| | - Inez Oh
- Institute for Informatics, Data Science and Biostatistics, Washington University School of Medicine in St. Louis, St. Louis, MO, USA
| | - Virginia Lanzotti
- Department of Psychiatry, Washington University School of Medicine in St. Louis, St. Louis, MO, USA
| | - Daleep Grewal
- Institute for Informatics, Data Science and Biostatistics, Washington University School of Medicine in St. Louis, St. Louis, MO, USA
| | - Erin Rooney Riggs
- Autism and Developmental Medicine Institute, Geisinger, Danville, PA, USA
| | | | - Rachel Hauck
- Institute for Informatics, Data Science and Biostatistics, Washington University School of Medicine in St. Louis, St. Louis, MO, USA
| | - Abigail Sveden
- Rosamund Stone Zander Translational Neuroscience Center, Boston Children's Hospital, Boston, MA, USA
| | - John N Constantino
- Division of Behavioral and Mental Health, Departments of Psychiatry and Pediatrics, Children's Healthcare of Atlanta, Emory University, Atlanta, GA, USA
| | - Joseph Piven
- The Carolina Institute for Developmental Disabilities, University of North Carolina, Chapel Hill, NC, USA
| | - Christina A Gurnett
- Department of Neurology, Washington University School of Medicine in St. Louis, St. Louis, MO, USA
| | - Maya Chopra
- Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
- Rosamund Stone Zander Translational Neuroscience Center, Boston Children's Hospital, Boston, MA, USA
| | - Heather Hazlett
- The Carolina Institute for Developmental Disabilities, University of North Carolina, Chapel Hill, NC, USA
| | - Philip R O Payne
- Institute for Informatics, Data Science and Biostatistics, Washington University School of Medicine in St. Louis, St. Louis, MO, USA
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4
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Abolhassani A, Fattahi Z, Beheshtian M, Fadaee M, Vazehan R, Ahangari F, Dehdahsi S, Faraji Zonooz M, Parsimehr E, Kalhor Z, Peymani F, Mozaffarpour Nouri M, Babanejad M, Noudehi K, Fatehi F, Zamanian Najafabadi S, Afroozan F, Yazdan H, Bozorgmehr B, Azarkeivan A, Sadat Mahdavi S, Nikuei P, Fatehi F, Jamali P, Ashrafi MR, Karimzadeh P, Habibi H, Kahrizi K, Nafissi S, Kariminejad A, Najmabadi H. Clinical application of next generation sequencing for Mendelian disease diagnosis in the Iranian population. NPJ Genom Med 2024; 9:12. [PMID: 38374194 PMCID: PMC10876633 DOI: 10.1038/s41525-024-00393-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2023] [Accepted: 01/29/2024] [Indexed: 02/21/2024] Open
Abstract
Next-generation sequencing (NGS) has been proven to be one of the most powerful diagnostic tools for rare Mendelian disorders. Several studies on the clinical application of NGS in unselected cohorts of Middle Eastern patients have reported a high diagnostic yield of up to 48%, correlated with a high level of consanguinity in these populations. We evaluated the diagnostic utility of NGS-based testing across different clinical indications in 1436 patients from Iran, representing the first study of its kind in this highly consanguineous population. A total of 1075 exome sequencing and 361 targeted gene panel sequencing were performed over 8 years at a single clinical genetics laboratory, with the majority of cases tested as proband-only (91.6%). The overall diagnostic rate was 46.7%, ranging from 24% in patients with an abnormality of prenatal development to over 67% in patients with an abnormality of the skin. We identified 660 pathogenic or likely pathogenic variants, including 241 novel variants, associated with over 342 known genetic conditions. The highly consanguineous nature of this cohort led to the diagnosis of autosomal recessive disorders in the majority of patients (79.1%) and allowed us to determine the shared carrier status of couples for suspected recessive phenotypes in their deceased child(ren) when direct testing was not possible. We also highlight the observations of recessive inheritance of genes previously associated only with dominant disorders and provide an expanded genotype-phenotype spectrum for multiple less-characterized genes. We present the largest mutational spectrum of known Mendelian disease, including possible founder variants, throughout the Iranian population, which can serve as a unique resource for clinical genomic studies locally and beyond.
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Affiliation(s)
- Ayda Abolhassani
- Kariminejad - Najmabadi Pathology & Genetics Center, Tehran, Iran
| | - Zohreh Fattahi
- Kariminejad - Najmabadi Pathology & Genetics Center, Tehran, Iran
- Genetics Research Center, University of Social Welfare and Rehabilitation Sciences, Tehran, Iran
| | | | - Mahsa Fadaee
- Kariminejad - Najmabadi Pathology & Genetics Center, Tehran, Iran
| | - Raheleh Vazehan
- Kariminejad - Najmabadi Pathology & Genetics Center, Tehran, Iran
| | - Fatemeh Ahangari
- Kariminejad - Najmabadi Pathology & Genetics Center, Tehran, Iran
| | - Shima Dehdahsi
- Kariminejad - Najmabadi Pathology & Genetics Center, Tehran, Iran
| | | | - Elham Parsimehr
- Kariminejad - Najmabadi Pathology & Genetics Center, Tehran, Iran
| | - Zahra Kalhor
- Kariminejad - Najmabadi Pathology & Genetics Center, Tehran, Iran
| | - Fatemeh Peymani
- Kariminejad - Najmabadi Pathology & Genetics Center, Tehran, Iran
| | | | - Mojgan Babanejad
- Genetics Research Center, University of Social Welfare and Rehabilitation Sciences, Tehran, Iran
| | - Khadijeh Noudehi
- Kariminejad - Najmabadi Pathology & Genetics Center, Tehran, Iran
| | - Fatemeh Fatehi
- Kariminejad - Najmabadi Pathology & Genetics Center, Tehran, Iran
| | | | - Fariba Afroozan
- Kariminejad - Najmabadi Pathology & Genetics Center, Tehran, Iran
| | - Hilda Yazdan
- Kariminejad - Najmabadi Pathology & Genetics Center, Tehran, Iran
| | - Bita Bozorgmehr
- Kariminejad - Najmabadi Pathology & Genetics Center, Tehran, Iran
| | - Azita Azarkeivan
- Kariminejad - Najmabadi Pathology & Genetics Center, Tehran, Iran
| | | | - Pooneh Nikuei
- Molecular Medicine Research Center, Hormozgan Health Institute, Hormozgan University of Medical Sciences, Bandar Abbas, Iran
- Nasle Salem Genetic Counseling Center, Bandar Abbas, Iran
| | - Farzad Fatehi
- Department of Neurology, Neuromuscular Research Center, Shariati Hospital, Tehran University of Medical Sciences, Tehran, Iran
| | - Payman Jamali
- Genetic Counseling Center, Shahroud Welfare Organization, Semnan, Iran
| | | | - Parvaneh Karimzadeh
- Pediatric Neurology Department, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Haleh Habibi
- Hamedan University of Medical Science, Hamedan, Iran
| | - Kimia Kahrizi
- Genetics Research Center, University of Social Welfare and Rehabilitation Sciences, Tehran, Iran
| | - Shahriar Nafissi
- Department of Neurology, Neuromuscular Research Center, Shariati Hospital, Tehran University of Medical Sciences, Tehran, Iran
| | | | - Hossein Najmabadi
- Kariminejad - Najmabadi Pathology & Genetics Center, Tehran, Iran.
- Genetics Research Center, University of Social Welfare and Rehabilitation Sciences, Tehran, Iran.
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5
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van Slobbe M, van Haeringen A, Vissers LELM, Bijlsma EK, Rutten JW, Suerink M, Nibbeling EAR, Ruivenkamp CAL, Koene S. Reanalysis of whole-exome sequencing (WES) data of children with neurodevelopmental disorders in a standard patient care context. Eur J Pediatr 2024; 183:345-355. [PMID: 37889289 PMCID: PMC10858114 DOI: 10.1007/s00431-023-05279-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/25/2023] [Revised: 09/20/2023] [Accepted: 10/11/2023] [Indexed: 10/28/2023]
Abstract
This study aims to inform future genetic reanalysis management by evaluating the yield of whole-exome sequencing (WES) reanalysis in standard patient care in the Netherlands. Single-center data of 159 patients with a neurodevelopmental disorder (NDD), in which WES analysis and reanalysis were performed between January 1, 2014, and December 31, 2021, was retrospectively collected. Patients were included if they were under the age of 18 years at initial analysis and if this initial analysis did not result in a diagnosis. Demographic, phenotypic, and genotypic characteristics of patients were collected and analyzed. The primary outcomes of our study were (i) diagnostic yield at reanalysis, (ii) reasons for detecting a new possibly causal variant at reanalysis, (iii) unsolicited findings, and (iv) factors associated with positive result of reanalysis. In addition, we conducted a questionnaire study amongst the 7 genetic department in the Netherlands creating an overview of used techniques, yield, and organization of WES reanalysis. The single-center data show that in most cases, WES reanalysis was initiated by the clinical geneticist (65%) or treating physician (30%). The mean time between initial WES analysis and reanalysis was 3.7 years. A new (likely) pathogenic variant or VUS with a clear link to the phenotype was found in 20 initially negative cases, resulting in a diagnostic yield of 12.6%. In 75% of these patients, the diagnosis had clinical consequences, as for example, a screening plan for associated signs and symptoms could be devised. Most (32%) of the (likely) causal variants identified at WES reanalysis were discovered due to a newly described gene-disease association. In addition to the 12.6% diagnostic yield based on new diagnoses, reclassification of a variant of uncertain significance found at initial analysis led to a definite diagnosis in three patients. Diagnostic yield was higher in patients with dysmorphic features compared to patients without clear dysmorphic features (yield 27% vs. 6%; p = 0.001). CONCLUSIONS Our results show that WES reanalysis in patients with NDD in standard patient care leads to a substantial increase in genetic diagnoses. In the majority of newly diagnosed patients, the diagnosis had clinical consequences. Knowledge about the clinical impact of WES reanalysis, clinical characteristics associated with higher yield, and the yield per year after a negative WES in larger clinical cohorts is warranted to inform guidelines for genetic reanalysis. These guidelines will be of great value for pediatricians, pediatric rehabilitation specialists, and pediatric neurologists in daily care of patients with NDD. WHAT IS KNOWN • Whole exome sequencing can cost-effectively identify a genetic cause of intellectual disability in about 30-40% of patients. • WES reanalysis in a research setting can lead to a definitive diagnosis in 10-20% of previously exome negative cases. WHAT IS NEW • WES reanalysis in standard patient care resulted in a diagnostic yield of 13% in previously exome negative children with NDD. • The presence of dysmorphic features is associated with an increased diagnostic yield of WES reanalysis.
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Affiliation(s)
- Michelle van Slobbe
- Department of Clinical Genetics, Leiden University Medical Centre, Leiden, The Netherlands
| | - Arie van Haeringen
- Department of Clinical Genetics, Leiden University Medical Centre, Leiden, The Netherlands
| | - Lisenka E L M Vissers
- Department of Human Genetics, Donders Centre for Neuroscience, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Emilia K Bijlsma
- Department of Clinical Genetics, Leiden University Medical Centre, Leiden, The Netherlands
| | - Julie W Rutten
- Department of Clinical Genetics, Leiden University Medical Centre, Leiden, The Netherlands
| | - Manon Suerink
- Department of Clinical Genetics, Leiden University Medical Centre, Leiden, The Netherlands
| | - Esther A R Nibbeling
- Department of Clinical Genetics, Leiden University Medical Centre, Leiden, The Netherlands
| | - Claudia A L Ruivenkamp
- Department of Clinical Genetics, Leiden University Medical Centre, Leiden, The Netherlands
| | - Saskia Koene
- Department of Clinical Genetics, Leiden University Medical Centre, Leiden, The Netherlands.
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6
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Sullivan JA, Spillmann RC, Schoch K, Walley N, Alkelai A, Stong N, Shea PR, Petrovski S, Jobanputra V, McConkie-Rosell A, Shashi V. The best of both worlds: Blending cutting-edge research with clinical processes for a productive exome clinic. Clin Genet 2024; 105:62-71. [PMID: 37853563 DOI: 10.1111/cge.14437] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2023] [Revised: 09/29/2023] [Accepted: 10/04/2023] [Indexed: 10/20/2023]
Abstract
Genomic medicine has been transformed by next-generation sequencing (NGS), inclusive of exome sequencing (ES) and genome sequencing (GS). Currently, ES is offered widely in clinical settings, with a less prevalent alternative model consisting of hybrid programs that incorporate research ES along with clinical patient workflows. We were among the earliest to implement a hybrid ES clinic, have provided diagnoses to 45% of probands, and have identified several novel candidate genes. Our program is enabled by a cost-effective investment by the health system and is unique in encompassing all the processes that have been variably included in other hybrid/clinical programs. These include careful patient selection, utilization of a phenotype-agnostic bioinformatics pipeline followed by manual curation of variants and phenotype integration by clinicians, close collaborations between the clinicians and the bioinformatician, pursuit of interesting variants, communication of results to patients in categories that are predicated upon the certainty of a diagnosis, and tracking changes in results over time and the underlying mechanisms for such changes. Due to its effectiveness, scalability to GS and its resource efficiency, specific elements of our paradigm can be incorporated into existing clinical settings, or the entire hybrid model can be implemented within health systems that have genomic medicine programs, to provide NGS in a scientifically rigorous, yet pragmatic setting.
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Affiliation(s)
- Jennifer A Sullivan
- Department of Pediatrics, Division of Medical Genetics, Duke University, Durham, North Carolina, USA
| | - Rebecca C Spillmann
- Department of Pediatrics, Division of Medical Genetics, Duke University, Durham, North Carolina, USA
| | - Kelly Schoch
- Department of Pediatrics, Division of Medical Genetics, Duke University, Durham, North Carolina, USA
| | - Nicole Walley
- Department of Pediatrics, Division of Medical Genetics, Duke University, Durham, North Carolina, USA
| | - Anna Alkelai
- Institute for Genomic Medicine, Columbia University Medical Center, New York, New York, USA
- Regeneron Genetics Center, Regeneron Pharmaceuticals, Tarrytown, New York, USA
| | - Nicholas Stong
- Institute for Genomic Medicine, Columbia University Medical Center, New York, New York, USA
- Predictive Sciences, Bristol Myers Squibb, Summit, New Jersey, USA
| | - Patrick R Shea
- Institute for Genomic Medicine, Columbia University Medical Center, New York, New York, USA
- Genomics and Bioinformatics Analysis Resource, Columbia University, New York, New York, USA
| | - Slavè Petrovski
- Institute for Genomic Medicine, Columbia University Medical Center, New York, New York, USA
- Department of Medicine, University of Melbourne, Austin Health, Melbourne, Victoria, Australia
| | - Vaidehi Jobanputra
- Department of Pathology and Cell Biology, Columbia University Irving Medical Center, New York, New York, USA
| | - Allyn McConkie-Rosell
- Department of Pediatrics, Division of Medical Genetics, Duke University, Durham, North Carolina, USA
| | - Vandana Shashi
- Department of Pediatrics, Division of Medical Genetics, Duke University, Durham, North Carolina, USA
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7
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Jain V, Foo SH, Chooi S, Moss C, Goodwin R, Berland S, Clarke AJ, Davies SJ, Corrin S, Murch O, Doyle S, Graham GE, Greenhalgh L, Holder SE, Johnson D, Kumar A, Ladda RL, Sell S, Begtrup A, Lynch SA, McCann E, Østern R, Pottinger C, Splitt M, Fry AE. Börjeson-Forssman-Lehmann syndrome: delineating the clinical and allelic spectrum in 14 new families. Eur J Hum Genet 2023; 31:1421-1429. [PMID: 37704779 PMCID: PMC10689765 DOI: 10.1038/s41431-023-01447-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2023] [Revised: 05/15/2023] [Accepted: 08/03/2023] [Indexed: 09/15/2023] Open
Abstract
Börjeson-Forssman-Lehmann syndrome (BFLS) is an X-linked intellectual disability syndrome caused by variants in the PHF6 gene. We ascertained 19 individuals from 15 families with likely pathogenic or pathogenic PHF6 variants (11 males and 8 females). One family had previously been reported. Six variants were novel. We analysed the clinical and genetic findings in our series and compared them with reported BFLS patients. Affected males had classic features of BFLS including intellectual disability, distinctive facies, large ears, gynaecomastia, hypogonadism and truncal obesity. Carrier female relatives of affected males were unaffected or had only mild symptoms. The phenotype of affected females with de novo variants overlapped with the males but included linear skin hyperpigmentation and a higher frequency of dental, retinal and cortical brain anomalies. Complications observed in our series included keloid scarring, digital fibromas, absent vaginal orifice, neuropathy, umbilical hernias, and talipes. Our analysis highlighted sex-specific differences in PHF6 variant types and locations. Affected males often have missense variants or small in-frame deletions while affected females tend to have truncating variants or large deletions/duplications. Missense variants were found in a minority of affected females and clustered in the highly constrained PHD2 domain of PHF6. We propose recommendations for the evaluation and management of BFLS patients. These results further delineate and extend the genetic and phenotypic spectrum of BFLS.
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Affiliation(s)
- Vani Jain
- All Wales Medical Genomics Service, University Hospital of Wales, Heath Park, Cardiff, CF14 4XW, UK.
| | - Seow Hoong Foo
- Department of Dermatology, Birmingham Women's and Children's NHS Foundation Trust, Birmingham, B4 6NH, UK
- Department of Dermatology, Gleneagles Hospital Medini, Nusajaya, 79250, Johor, Malaysia
| | - Stephen Chooi
- School of Medicine, Cardiff University, Heath Park Campus, Cardiff, CF14 4YS, UK
| | - Celia Moss
- Department of Dermatology, Birmingham Women's and Children's NHS Foundation Trust, Birmingham, B4 6NH, UK
- University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK
| | - Richard Goodwin
- Department of Dermatology, Royal Gwent Hospital, Newport, NP20 2UB, UK
| | - Siren Berland
- Department of Medical Genetics, Haukeland University Hospital, 5021, Bergen, Norway
| | - Angus J Clarke
- All Wales Medical Genomics Service, University Hospital of Wales, Heath Park, Cardiff, CF14 4XW, UK
- Division of Cancer and Genetics, Cardiff University, Cardiff, CF14 4XN, UK
| | - Sally J Davies
- All Wales Medical Genomics Service, University Hospital of Wales, Heath Park, Cardiff, CF14 4XW, UK
| | - Sian Corrin
- All Wales Medical Genomics Service, University Hospital of Wales, Heath Park, Cardiff, CF14 4XW, UK
| | - Oliver Murch
- All Wales Medical Genomics Service, University Hospital of Wales, Heath Park, Cardiff, CF14 4XW, UK
| | - Samantha Doyle
- Department of Medical Genetics, Our Lady's Children's Hospital, Crumlin, Dublin, D12 N512, Ireland
- Department of Clinical Genetics, The National Maternity Hospital, Holles Street, Dublin, D02 YH21, Ireland
| | - Gail E Graham
- Department of Genetics, Children's Hospital of Eastern Ontario, Ottawa, Ontario, K1H 8L1, Canada
| | - Lynn Greenhalgh
- Liverpool Centre for Genomic Medicine, Liverpool Women's Hospital, Liverpool, L8 7SS, UK
| | - Susan E Holder
- North West Thames Regional Genetic Service, Kennedy Galton Centre, Northwick Park Hospital, Harrow, HA1 3UJ, UK
| | - Diana Johnson
- Department of Clinical Genetics, Northern General Hospital, Sheffield, S5 7AU, UK
| | - Ajith Kumar
- North East Thames Regional Genetics Service, Great Ormond Street Hospital, London, WC1N 3JH, UK
| | - Roger L Ladda
- Department of Pediatrics, Division of Human Genetics, Penn State Health Children's Hospital, Hershey, Pennsylvania, 17033, USA
| | - Susan Sell
- Department of Pediatrics, Division of Human Genetics, Penn State Health Children's Hospital, Hershey, Pennsylvania, 17033, USA
| | | | - Sally A Lynch
- Department of Medical Genetics, Our Lady's Children's Hospital, Crumlin, Dublin, D12 N512, Ireland
| | - Emma McCann
- Liverpool Centre for Genomic Medicine, Liverpool Women's Hospital, Liverpool, L8 7SS, UK
| | - Rune Østern
- Department of Medical Genetics, St. Olavs Hospital, Trondheim University Hospital, 7030, Trondheim, Norway
| | - Caroline Pottinger
- All Wales Medical Genomics Service, University Hospital of Wales, Heath Park, Cardiff, CF14 4XW, UK
| | - Miranda Splitt
- Northern Genetics Service, Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle upon Tyne, NE1 3BZ, UK
| | - Andrew E Fry
- All Wales Medical Genomics Service, University Hospital of Wales, Heath Park, Cardiff, CF14 4XW, UK.
- Division of Cancer and Genetics, Cardiff University, Cardiff, CF14 4XN, UK.
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Chaudhri EN, Abbott JM, Islam NN, Weber CA, Coban MA, Bilgili A, Squire JD, Mantia S, Wierenga KJ, Caulfield TR. Statistical Mechanics Metrics in Pairing and Parsing In Silico and Phenotypic Data of a Novel Genetic NFκB1 (c.T638A) Variant. Genes (Basel) 2023; 14:1855. [PMID: 37895204 PMCID: PMC10606260 DOI: 10.3390/genes14101855] [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: 08/21/2023] [Revised: 09/19/2023] [Accepted: 09/21/2023] [Indexed: 10/29/2023] Open
Abstract
(1) Background: Mutations in NFκB1, a transcriptional regulator of immunomodulating proteins, are a known cause of inborn errors of immunity. Our proband is a 22-year-old male with a diagnosis of common variable immunodeficiency (CVID), cytopenias with massive splenomegaly, and nodular regenerative hyperplasia of the liver. Genetic studies identified a novel, single-point mutation variant in NFκB1, c. T638A p. V213E. (2) Methods: Next-generation panel sequencing of the patient uncovered a novel single-point mutation in the NFκB1 gene that was modeled using the I-TASSER homology-modeling software, and molecular dynamics were assessed using the YASARA2 software (version 20.14.24). (3) Results: This variant replaces valine with glutamic acid at position 213 in the NFκB1 sequence. Molecular modeling and molecular dynamic studies showed altered dynamics in and around the rel homology domain, ankyrin regions, and death domain of the protein. We postulate that these changes alter overall protein function. (4) Conclusions: This case suggests the pathogenicity of a novel variant using protein-modeling techniques and molecular dynamic simulations.
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Affiliation(s)
- Eman N. Chaudhri
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL 32224, USA; (E.N.C.); (J.M.A.); (N.N.I.); (C.A.W.); (A.B.)
- College of Medicine, Alfaisal University, Riyadh 11533, Saudi Arabia
| | - Jessica M. Abbott
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL 32224, USA; (E.N.C.); (J.M.A.); (N.N.I.); (C.A.W.); (A.B.)
| | - Naeyma N. Islam
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL 32224, USA; (E.N.C.); (J.M.A.); (N.N.I.); (C.A.W.); (A.B.)
| | - Caleb A. Weber
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL 32224, USA; (E.N.C.); (J.M.A.); (N.N.I.); (C.A.W.); (A.B.)
| | - Mathew A. Coban
- Department of Cancer Biology, Mayo Clinic, Jacksonville, FL 32224, USA;
| | - Ahmet Bilgili
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL 32224, USA; (E.N.C.); (J.M.A.); (N.N.I.); (C.A.W.); (A.B.)
| | | | - Sarah Mantia
- Department of Clinical Genomics, Mayo Clinic, Jacksonville, FL 32224, USA (K.J.W.)
| | - Klaas J. Wierenga
- Department of Clinical Genomics, Mayo Clinic, Jacksonville, FL 32224, USA (K.J.W.)
| | - Thomas R. Caulfield
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL 32224, USA; (E.N.C.); (J.M.A.); (N.N.I.); (C.A.W.); (A.B.)
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9
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Chung CCY, Hue SPY, Ng NYT, Doong PHL, Chu ATW, Chung BHY. Meta-analysis of the diagnostic and clinical utility of exome and genome sequencing in pediatric and adult patients with rare diseases across diverse populations. Genet Med 2023; 25:100896. [PMID: 37191093 DOI: 10.1016/j.gim.2023.100896] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2022] [Revised: 05/07/2023] [Accepted: 05/10/2023] [Indexed: 05/17/2023] Open
Abstract
PURPOSE This meta-analysis aims to compare the diagnostic and clinical utility of exome sequencing (ES) vs genome sequencing (GS) in pediatric and adult patients with rare diseases across diverse populations. METHODS A meta-analysis was conducted to identify studies from 2011 to 2021. RESULTS One hundred sixty-one studies across 31 countries/regions were eligible, featuring 50,417 probands of diverse populations. Diagnostic rates of ES (0.38, 95% CI 0.36-0.40) and GS (0.34, 95% CI 0.30-0.38) were similar (P = .1). Within-cohort comparison illustrated 1.2-times odds of diagnosis by GS over ES (95% CI 0.79-1.83, P = .38). GS studies discovered a higher range of novel genes than ES studies; yet, the rate of variant of unknown significance did not differ (P = .78). Among high-quality studies, clinical utility of GS (0.77, 95% CI 0.64-0.90) was higher than that of ES (0.44, 95% CI 0.30-0.58) (P < .01). CONCLUSION This meta-analysis provides an important update to demonstrate the similar diagnostic rates between ES and GS and the higher clinical utility of GS over ES. With the newly published recommendations for clinical interpretation of variants found in noncoding regions of the genome and the trend of decreasing variant of unknown significance and GS cost, it is expected that GS will be more widely used in clinical settings.
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Affiliation(s)
| | - Shirley P Y Hue
- Hong Kong Genome Institute, Hong Kong Special Administrative Region
| | - Nicole Y T Ng
- Department of Paediatrics and Adolescent Medicine, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region
| | - Phoenix H L Doong
- Department of Paediatrics and Adolescent Medicine, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region
| | - Annie T W Chu
- Hong Kong Genome Institute, Hong Kong Special Administrative Region.
| | - Brian H Y Chung
- Hong Kong Genome Institute, Hong Kong Special Administrative Region; Department of Paediatrics and Adolescent Medicine, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region.
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10
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Hopkins CE, McCormick K, Brock T, Wood M, Ruggiero S, Mcbride K, Kim C, Lawson JA, Helbig I, Bainbridge MN. Clinical variants in Caenorhabditis elegans expressing human STXBP1 reveal a novel class of pathogenic variants and classify variants of uncertain significance. GENETICS IN MEDICINE OPEN 2023; 1:100823. [PMID: 38827422 PMCID: PMC11141691 DOI: 10.1016/j.gimo.2023.100823] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/04/2024]
Abstract
Purpose Modeling disease variants in animals is useful for drug discovery, understanding disease pathology, and classifying variants of uncertain significance (VUS) as pathogenic or benign. Methods Using Clustered Regularly Interspaced Short Palindromic Repeats, we performed a Whole-gene Humanized Animal Model procedure to replace the coding sequence of the animal model's unc-18 ortholog with the coding sequence for the human STXBP1 gene. Next, we used Clustered Regularly Interspaced Short Palindromic Repeats to introduce precise point variants in the Whole-gene Humanized Animal Model-humanized STXBP1 locus from 3 clinical categories (benign, pathogenic, and VUS). Twenty-six phenotypic features extracted from video recordings were used to train machine learning classifiers on 25 pathogenic and 32 benign variants. Results Using multiple models, we were able to obtain a diagnostic sensitivity near 0.9. Twenty-three VUS were also interrogated and 8 of 23 (34.8%) were observed to be functionally abnormal. Interestingly, unsupervised clustering identified 2 distinct subsets of known pathogenic variants with distinct phenotypic features; both p.Tyr75Cys and p.Arg406Cys cluster away from other variants and show an increase in swim speed compared with hSTXBP1 worms. This leads to the hypothesis that the mechanism of disease for these 2 variants may differ from most STXBP1-mutated patients and may account for some of the clinical heterogeneity observed in the patient population. Conclusion We have demonstrated that automated analysis of a small animal system is an effective, scalable, and fast way to understand functional consequences of variants in STXBP1 and identify variant-specific intensities of aberrant activity suggesting a genotype-to-phenotype correlation is likely to occur in human clinical variations of STXBP1.
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Affiliation(s)
| | | | | | | | - Sarah Ruggiero
- Division of Neurology, Children’s Hospital of Philadelphia, Philadelphia, PA
- The Epilepsy NeuroGenetics Initiative (ENGIN), Children’s Hospital of Philadelphia, Philadelphia, PA
- Department of Biomedical and Health Informatics (DBHi), Children’s Hospital of Philadelphia, Philadelphia, PA
- University of Pennsylvania, Neuroscience Program, Philadelphia, PA
| | | | | | | | - Ingo Helbig
- Division of Neurology, Children’s Hospital of Philadelphia, Philadelphia, PA
- The Epilepsy NeuroGenetics Initiative (ENGIN), Children’s Hospital of Philadelphia, Philadelphia, PA
- Department of Biomedical and Health Informatics (DBHi), Children’s Hospital of Philadelphia, Philadelphia, PA
- University of Pennsylvania, Neuroscience Program, Philadelphia, PA
| | - Matthew N. Bainbridge
- Codified Genomics, LLC, Houston, TX
- Rady Children’s Institute for Genomic Medicine, San Diego, CA
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11
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Slavotinek A, Rego S, Sahin-Hodoglugil N, Kvale M, Lianoglou B, Yip T, Hoban H, Outram S, Anguiano B, Chen F, Michelson J, Cilio RM, Curry C, Gallagher RC, Gardner M, Kuperman R, Mendelsohn B, Sherr E, Shieh J, Strober J, Tam A, Tenney J, Weiss W, Whittle A, Chin G, Faubel A, Prasad H, Mavura Y, Van Ziffle J, Devine WP, Hodoglugil U, Martin PM, Sparks TN, Koenig B, Ackerman S, Risch N, Kwok PY, Norton ME. Diagnostic yield of pediatric and prenatal exome sequencing in a diverse population. NPJ Genom Med 2023; 8:10. [PMID: 37236975 PMCID: PMC10220040 DOI: 10.1038/s41525-023-00353-0] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2022] [Accepted: 04/28/2023] [Indexed: 05/28/2023] Open
Abstract
The diagnostic yield of exome sequencing (ES) has primarily been evaluated in individuals of European ancestry, with less focus on underrepresented minority (URM) and underserved (US) patients. We evaluated the diagnostic yield of ES in a cohort of predominantly US and URM pediatric and prenatal patients suspected to have a genetic disorder. Eligible pediatric patients had multiple congenital anomalies and/or neurocognitive disabilities and prenatal patients had one or more structural anomalies, disorders of fetal growth, or fetal effusions. URM and US patients were prioritized for enrollment and underwent ES at a single academic center. We identified definitive positive or probable positive results in 201/845 (23.8%) patients, with a significantly higher diagnostic rate in pediatric (26.7%) compared to prenatal patients (19.0%) (P = 0.01). For both pediatric and prenatal patients, the diagnostic yield and frequency of inconclusive findings did not differ significantly between URM and non-URM patients or between patients with US status and those without US status. Our results demonstrate a similar diagnostic yield of ES between prenatal and pediatric URM/US patients and non-URM/US patients for positive and inconclusive results. These data support the use of ES to identify clinically relevant variants in patients from diverse populations.
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Affiliation(s)
- Anne Slavotinek
- Department of Pediatrics, University of California, San Francisco, San Francisco, CA, USA.
- Institute for Human Genetics, University of California San Francisco, San Francisco, CA, USA.
| | - Shannon Rego
- Department of Pediatrics, University of California, San Francisco, San Francisco, CA, USA
- Institute for Human Genetics, University of California San Francisco, San Francisco, CA, USA
| | - Nuriye Sahin-Hodoglugil
- Institute for Human Genetics, University of California San Francisco, San Francisco, CA, USA
| | - Mark Kvale
- Institute for Human Genetics, University of California San Francisco, San Francisco, CA, USA
- Department of Epidemiology & Biostatistics, University of California San Francisco, San Francisco, CA, USA
| | - Billie Lianoglou
- Department of Surgery, University of California, San Francisco, San Francisco, CA, USA
| | - Tiffany Yip
- Department of Pediatrics, University of California, San Francisco, San Francisco, CA, USA
- Institute for Human Genetics, University of California San Francisco, San Francisco, CA, USA
| | - Hannah Hoban
- Department of Pediatrics, University of California, San Francisco, San Francisco, CA, USA
| | - Simon Outram
- Institute for Health & Aging, School of Nursing, University of California San Francisco, San Francisco, CA, USA
| | - Beatrice Anguiano
- Institute for Human Genetics, University of California San Francisco, San Francisco, CA, USA
- Institute for Health & Aging, School of Nursing, University of California San Francisco, San Francisco, CA, USA
| | - Flavia Chen
- Institute for Human Genetics, University of California San Francisco, San Francisco, CA, USA
| | - Jeremy Michelson
- Institute of Human Nutrition, Columbia University Medical Center, New York, NY, USA
| | - Roberta M Cilio
- Division of Pediatric Neurology, Department of Pediatrics, University of Louvain, Brussels, Belgium
| | - Cynthia Curry
- Genetic Medicine, University of California, San Francisco, Fresno, CA, USA
| | - Renata C Gallagher
- Department of Pediatrics, University of California, San Francisco, San Francisco, CA, USA
- Institute for Human Genetics, University of California San Francisco, San Francisco, CA, USA
| | - Marisa Gardner
- Department of Neurology, UCSF Benioff Children's Hospital Oakland, Oakland, CA, USA
| | - Rachel Kuperman
- Department of Neurology, UCSF Benioff Children's Hospital Oakland, Oakland, CA, USA
- Eysz, Inc, Piedmont, CA, USA
| | - Bryce Mendelsohn
- Division of Genetics, Kaiser Permanente Oakland Medical Center, Oakland, CA, USA
| | - Elliott Sherr
- Division of Child Neurology, Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - Joseph Shieh
- Department of Pediatrics, University of California, San Francisco, San Francisco, CA, USA
- Institute for Human Genetics, University of California San Francisco, San Francisco, CA, USA
| | - Jonathan Strober
- Division of Child Neurology, Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - Allison Tam
- Department of Pediatrics, University of California, San Francisco, San Francisco, CA, USA
| | - Jessica Tenney
- Department of Pediatrics, University of California, San Francisco, San Francisco, CA, USA
| | - William Weiss
- Division of Child Neurology, Zuckerberg San Francisco General Hospital, San Francisco, San Francisco, CA, USA
| | - Amy Whittle
- Division of Pediatrics, Zuckerberg San Francisco General Hospital, San Francisco, San Francisco, CA, USA
| | - Garrett Chin
- Institute for Human Genetics, University of California San Francisco, San Francisco, CA, USA
| | - Amanda Faubel
- Department of Surgery, University of California, San Francisco, San Francisco, CA, USA
| | - Hannah Prasad
- Institute for Human Genetics, University of California San Francisco, San Francisco, CA, USA
| | - Yusuph Mavura
- Institute for Human Genetics, University of California San Francisco, San Francisco, CA, USA
- Department of Epidemiology & Biostatistics, University of California San Francisco, San Francisco, CA, USA
| | - Jessica Van Ziffle
- Department of Pathology, University of California San Francisco, San Francisco, CA, USA
| | - W Patrick Devine
- Department of Pathology, University of California San Francisco, San Francisco, CA, USA
| | - Ugur Hodoglugil
- Genomic Medicine Laboratory, University of California San Francisco, San Francisco, CA, USA
| | - Pierre-Marie Martin
- Institute for Human Genetics, University of California San Francisco, San Francisco, CA, USA
| | - Teresa N Sparks
- Institute for Human Genetics, University of California San Francisco, San Francisco, CA, USA
- Division of Maternal Fetal Medicine, Department of Obstetrics, Gynecology, and Reproductive Sciences, San Francisco, USA
| | - Barbara Koenig
- Institute for Human Genetics, University of California San Francisco, San Francisco, CA, USA
- Program in Bioethics, University of California, San Francisco, San Francisco, CA, USA
| | - Sara Ackerman
- Institute for Health & Aging, School of Nursing, University of California San Francisco, San Francisco, CA, USA
- Department of Social & Behavioral Sciences, School of Nursing, University of California San Francisco, San Francisco, CA, USA
| | - Neil Risch
- Institute for Human Genetics, University of California San Francisco, San Francisco, CA, USA
- Department of Epidemiology & Biostatistics, University of California San Francisco, San Francisco, CA, USA
| | - Pui-Yan Kwok
- Cardiovascular Research Institute, University of California San Francisco, San Francisco, CA, USA
| | - Mary E Norton
- Institute for Human Genetics, University of California San Francisco, San Francisco, CA, USA
- Division of Maternal Fetal Medicine, Department of Obstetrics, Gynecology, and Reproductive Sciences, San Francisco, USA
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12
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Carter MT, Srour M, Au PYB, Buhas D, Dyack S, Eaton A, Inbar-Feigenberg M, Howley H, Kawamura A, Lewis SME, McCready E, Nelson TN, Vallance H. Genetic and metabolic investigations for neurodevelopmental disorders: position statement of the Canadian College of Medical Geneticists (CCMG). J Med Genet 2023; 60:523-532. [PMID: 36822643 DOI: 10.1136/jmg-2022-108962] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2022] [Accepted: 01/27/2023] [Indexed: 02/25/2023]
Abstract
PURPOSE AND SCOPE The aim of this position statement is to provide recommendations for clinicians regarding the use of genetic and metabolic investigations for patients with neurodevelopmental disorders (NDDs), specifically, patients with global developmental delay (GDD), intellectual disability (ID) and/or autism spectrum disorder (ASD). This document also provides guidance for primary care and non-genetics specialists caring for these patients while awaiting consultation with a clinical geneticist or metabolic specialist. METHODS OF STATEMENT DEVELOPMENT A multidisciplinary group reviewed existing literature and guidelines on the use of genetic and metabolic investigations for the diagnosis of NDDs and synthesised the evidence to make recommendations relevant to the Canadian context. The statement was circulated for comment to the Canadian College of Medical Geneticists (CCMG) membership-at-large and to the Canadian Pediatric Society (Mental Health and Developmental Disabilities Committee); following incorporation of feedback, it was approved by the CCMG Board of Directors on 1 September 2022. RESULTS AND CONCLUSIONS Chromosomal microarray is recommended as a first-tier test for patients with GDD, ID or ASD. Fragile X testing should also be done as a first-tier test when there are suggestive clinical features or family history. Metabolic investigations should be done if there are clinical features suggestive of an inherited metabolic disease, while the patient awaits consultation with a metabolic physician. Exome sequencing or a comprehensive gene panel is recommended as a second-tier test for patients with GDD or ID. Genetic testing is not recommended for patients with NDDs in the absence of GDD, ID or ASD, unless accompanied by clinical features suggestive of a syndromic aetiology or inherited metabolic disease.
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Affiliation(s)
| | - Myriam Srour
- Division of Neurology, McGill University Health Centre, Montreal, Québec, Canada
- Department of Pediatrics, McGill University, Montréal, QC, Canada
| | - Ping-Yee Billie Au
- Department of Medical Genetics, Alberta Children's Hospital, Calgary, Alberta, Canada
| | - Daniela Buhas
- Division of Medical Genetics, Department of Specialized Medicine, McGill University Health Centre, McGill University, Montreal, Québec, Canada
- Department of Human Genetics, McGill University, Montreal, QC, Canada
| | - Sarah Dyack
- Division of Medical Genetics, IWK Health Centre, Halifax, Nova Scotia, Canada
- Department of Pediatrics, Dalhousie University, Halifax, NS, Canada
| | - Alison Eaton
- Department of Medical Genetics, Stollery Children's Hospital, Edmonton, Alberta, Canada
- Department of Medical Genetics, University of Alberta, Edmonton, AB, Canada
| | - Michal Inbar-Feigenberg
- Division of Clinical and Metabolic Genetics, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Heather Howley
- Office of Research Services, CHEO Research Institute, Ottawa, Ontario, Canada
| | - Anne Kawamura
- Division of Developmental Pediatrics, Holland Bloorview Kids Rehabilitation Hospital, Toronto, Ontario, Canada
- Department of Paediatrics, University of Toronto, Toronto, ON, Canada
- Mental Health and Developmental Disability Committee, Canadian Pediatric Society, Ottawa, ON, Canada
- Canadian Paediatric Society, Toronto, Ontario, Canada
| | - Suzanne M E Lewis
- Department of Medical Genetics, BC Children's and Women's Hospital, Vancouver, British Columbia, Canada
| | - Elizabeth McCready
- Department of Pathology and Molecular Medicine, McMaster University, McMaster University, Hamilton, ON, Canada, Hamilton, Ontario, Canada
- Hamilton Regional Laboratory Medicine Program, Hamilton Health Sciences Centre, Hamilton, ON, Canada
| | - Tanya N Nelson
- Department of Pathology and Laboratory Medicine, BC Children's Hospital, University of British Columbia, Vancouver, British Columbia, Canada
| | - Hilary Vallance
- Department of Pathology and Laboratory Medicine, BC Children's Hospital, University of British Columbia, Vancouver, British Columbia, Canada
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13
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Evaluation of Individuals with Non-Syndromic Global Developmental Delay and Intellectual Disability. CHILDREN 2023; 10:children10030414. [PMID: 36979972 PMCID: PMC10047567 DOI: 10.3390/children10030414] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/29/2022] [Revised: 02/11/2023] [Accepted: 02/16/2023] [Indexed: 02/24/2023]
Abstract
Global Developmental Delay (GDD) and Intellectual Disability (ID) are two of the most common presentations encountered by physicians taking care of children. GDD/ID is classified into non-syndromic GDD/ID, where GDD/ID is the sole evident clinical feature, or syndromic GDD/ID, where there are additional clinical features or co-morbidities present. Careful evaluation of children with GDD and ID, starting with detailed history followed by a thorough examination, remain the cornerstone for etiologic diagnosis. However, when initial history and examination fail to identify a probable underlying etiology, further genetic testing is warranted. In recent years, genetic testing has been shown to be the single most important diagnostic modality for clinicians evaluating children with non-syndromic GDD/ID. In this review, we discuss different genetic testing currently available, review common underlying copy-number variants and molecular pathways, explore the recent evidence and recommendations for genetic evaluation and discuss an approach to the diagnosis and management of children with non-syndromic GDD and ID.
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14
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Ediae GU, Lemire G, Chisholm C, Hartley T, Eaton A, Osmond M, Rojas SK, Huang L, Gillespie M, Sawyer SL, Boycott KM. The implementation of an enhanced clinical model to improve the diagnostic yield of exome sequencing for patients with a rare genetic disease: A Canadian experience. Am J Med Genet A 2023; 191:338-347. [PMID: 36331261 DOI: 10.1002/ajmg.a.63022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2022] [Revised: 09/30/2022] [Accepted: 10/03/2022] [Indexed: 11/06/2022]
Abstract
The introduction of clinical exome sequencing (ES) has provided a unique opportunity to decrease the diagnostic odyssey for patients living with a rare genetic disease (RGD). ES has been shown to provide a diagnosis in 29%-57% of patients with a suspected RGD, with as many as 70% remaining undiagnosed. There is a need to advance the clinical model of care by more formally integrating approaches that were previously considered research into an enhanced diagnostic workflow. We developed an Exome Clinic, which set out to evaluate a workflow for improving the diagnostic yield of ES for patients with an undiagnosed RGD. Here, we report the outcomes of 47 families who underwent clinical ES in the first year of the clinic. The diagnostic yield from clinical ES was 40% (19/47). Families who remained undiagnosed after ES had the opportunity for follow-up studies that included phenotyping and candidate variant segregation in relatives, genomic matchmaking, and ES reanalysis. This enhanced diagnostic workflow increased the diagnostic yield to 55% (26/47), predominantly through the resolution of variants and genes of uncertain significance. We advocate that this approach be integrated into mainstream clinical practice and highlight the importance of a coordinated translational approach for patients with RGD.
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Affiliation(s)
- Grace Uwaila Ediae
- Children's Hospital of Eastern Ontario Research Institute, University of Ottawa, Ottawa, Ontario, Canada.,Regional Genetics Program, Children's Hospital of Eastern Ontario Ottawa, Ottawa, Ontario, Canada
| | - Gabrielle Lemire
- Children's Hospital of Eastern Ontario Research Institute, University of Ottawa, Ottawa, Ontario, Canada.,Regional Genetics Program, Children's Hospital of Eastern Ontario Ottawa, Ottawa, Ontario, Canada
| | - Caitlin Chisholm
- Regional Genetics Program, Children's Hospital of Eastern Ontario Ottawa, Ottawa, Ontario, Canada
| | - Taila Hartley
- Children's Hospital of Eastern Ontario Research Institute, University of Ottawa, Ottawa, Ontario, Canada
| | - Alison Eaton
- Children's Hospital of Eastern Ontario Research Institute, University of Ottawa, Ottawa, Ontario, Canada.,Regional Genetics Program, Children's Hospital of Eastern Ontario Ottawa, Ottawa, Ontario, Canada
| | - Matthew Osmond
- Children's Hospital of Eastern Ontario Research Institute, University of Ottawa, Ottawa, Ontario, Canada
| | - Samantha K Rojas
- Children's Hospital of Eastern Ontario Research Institute, University of Ottawa, Ottawa, Ontario, Canada.,Regional Genetics Program, Children's Hospital of Eastern Ontario Ottawa, Ottawa, Ontario, Canada
| | - Lijia Huang
- Regional Genetics Program, Children's Hospital of Eastern Ontario Ottawa, Ottawa, Ontario, Canada.,Department of Pathology and Laboratory Medicine, University of Ottawa, Ottawa, Ontario, Canada
| | - Meredith Gillespie
- Children's Hospital of Eastern Ontario Research Institute, University of Ottawa, Ottawa, Ontario, Canada
| | | | - Sarah L Sawyer
- Children's Hospital of Eastern Ontario Research Institute, University of Ottawa, Ottawa, Ontario, Canada.,Regional Genetics Program, Children's Hospital of Eastern Ontario Ottawa, Ottawa, Ontario, Canada
| | - Kym M Boycott
- Children's Hospital of Eastern Ontario Research Institute, University of Ottawa, Ottawa, Ontario, Canada.,Regional Genetics Program, Children's Hospital of Eastern Ontario Ottawa, Ottawa, Ontario, Canada
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15
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Lahiri S, Reys B, Wunder J, Pirzadeh-Miller S. Genetic variants with discordant classifications: An assessment of genetic counselor attitudes and practices. J Genet Couns 2023; 32:100-110. [PMID: 35978490 DOI: 10.1002/jgc4.1626] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2021] [Revised: 07/22/2022] [Accepted: 07/27/2022] [Indexed: 11/11/2022]
Abstract
Discordant variant classifications (DVCs) can impact patient care and pose challenges for clinicians. A survey-based study was conducted to examine genetic counselor (GC) attitudes and practices related to DVCs. Most GCs (202/229, 88%) in the study provide direct patient care across clinical specialties; review patients' genetic test results to determine if reported genetic variants have DVCs (176/202, 88%); and inform patients of known DVCs that impact medical management (165/202, 82%). DVC review, which takes 41 min (range: 5-240) on average per week, is typically prompted by the identification of a variant of uncertain significance (VUS) (160/176, 90%) and is primarily conducted using public databases (176/176, 100%). While most GCs felt it would not be ethical to knowingly provide different medical management recommendations to patients with the same genetic variant (152/229, 66%), they also stated they would rely on the variant classification on the test report (141/229, 61%) and/or the patient's personal/family history (188/229, 82%) to determine which classification to follow if a DVC is identified. Both factors are patient-specific and, inherently, could lead to differing recommendations. When posed with a hypothetical scenario in which two patients have the same genetic variant, but test reports show a DVC (pathogenic vs VUS), most GCs (179/229, 78.2%) stated they would make the same recommendation for both patients regardless of management guidelines. One-third (52/179, 29.1%) cited patient-specific factors, such as personal/family history, would impact their recommendations. Disagreements about whether the pathogenic or VUS classification should be used to make medical management recommendations were noted. Differing practices and opinions on how to manage patients with DVCs, as well as the fact that most GCs (209/229, 91.3%) have consulted with colleagues on this matter, highlight the need for more professional guidance to ensure equitable patient care.
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Affiliation(s)
- Sayoni Lahiri
- Cancer Genetics Program, UT Southwestern Medical Center, Dallas, Texas, USA
| | - Brian Reys
- Cancer Genetics Program, UT Southwestern Medical Center, Dallas, Texas, USA
| | - Julia Wunder
- Oncology-Abstraction, Tempus Labs, Inc., Chicago, Illinois, USA
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16
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Abstract
Exome sequencing (ES) and genome sequencing (GS) have radically transformed the diagnostic approach to undiagnosed rare/ultrarare Mendelian diseases. Next-generation sequencing (NGS), the technology integral for ES, GS, and most large (100+) gene panels, has enabled previously unimaginable diagnoses, changes in medical management, new treatments, and accurate reproductive risk assessments for patients, as well as new disease gene discoveries. Yet, challenges remain, as most individuals remain undiagnosed with current NGS. Improved NGS technology has resulted in long-read sequencing, which may resolve diagnoses in some patients who do not obtain a diagnosis with current short-read ES and GS, but its effectiveness is unclear, and it is expensive. Other challenges that persist include the resolution of variants of uncertain significance, the urgent need for patients with ultrarare disorders to have access to therapeutics, the need for equity in patient access to NGS-based testing, and the study of ethical concerns. However, the outlook for undiagnosed disease resolution is bright, due to continual advancements in the field.
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Affiliation(s)
- Jennifer A Sullivan
- Division of Medical Genetics, Department of Pediatrics, Duke University School of Medicine, Durham, North Carolina, USA;
| | - Kelly Schoch
- Division of Medical Genetics, Department of Pediatrics, Duke University School of Medicine, Durham, North Carolina, USA;
| | - Rebecca C Spillmann
- Division of Medical Genetics, Department of Pediatrics, Duke University School of Medicine, Durham, North Carolina, USA;
| | - Vandana Shashi
- Division of Medical Genetics, Department of Pediatrics, Duke University School of Medicine, Durham, North Carolina, USA;
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17
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Hopkins CE, Brock T, Caulfield TR, Bainbridge M. Phenotypic screening models for rapid diagnosis of genetic variants and discovery of personalized therapeutics. Mol Aspects Med 2022; 91:101153. [PMID: 36411139 PMCID: PMC10073243 DOI: 10.1016/j.mam.2022.101153] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2022] [Revised: 10/22/2022] [Accepted: 10/23/2022] [Indexed: 11/19/2022]
Abstract
Precision medicine strives for highly individualized treatments for disease under the notion that each individual's unique genetic makeup and environmental exposures imprints upon them not only a disposition to illness, but also an optimal therapeutic approach. In the realm of rare disorders, genetic predisposition is often the predominant mechanism driving disease presentation. For such, mostly, monogenic disorders, a causal gene to phenotype association is likely. As a result, it becomes important to query the patient's genome for the presence of pathogenic variations that are likely to cause the disease. Determining whether a variant is pathogenic or not is critical to these analyses and can be challenging, as many disease-causing variants are novel and, ergo, have no available functional data to help categorize them. This problem is exacerbated by the need for rapid evaluation of pathogenicity, since many genetic diseases present in young children who will experience increased morbidity and mortality without rapid diagnosis and therapeutics. Here, we discuss the utility of animal models, with a focus mainly on C. elegans, as a contrast to tissue culture and in silico approaches, with emphasis on how these systems are used in determining pathogenicity of variants with uncertain significance and then used to screen for novel therapeutics.
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Affiliation(s)
| | | | - Thomas R Caulfield
- Mayo Clinic, Department of Neuroscience, Department of Computational Biology, Department of Clinical Genomics, Jacksonville, FL, 32224, Rochester, MN, 55905, USA
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18
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Macken WL, Falabella M, McKittrick C, Pizzamiglio C, Ellmers R, Eggleton K, Woodward CE, Patel Y, Labrum R, Phadke R, Reilly MM, DeVile C, Sarkozy A, Footitt E, Davison J, Rahman S, Houlden H, Bugiardini E, Quinlivan R, Hanna MG, Vandrovcova J, Pitceathly RDS. Specialist multidisciplinary input maximises rare disease diagnoses from whole genome sequencing. Nat Commun 2022; 13:6324. [PMID: 36344503 PMCID: PMC9640711 DOI: 10.1038/s41467-022-32908-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2022] [Accepted: 08/24/2022] [Indexed: 11/09/2022] Open
Abstract
Diagnostic whole genome sequencing (WGS) is increasingly used in rare diseases. However, standard, semi-automated WGS analysis may overlook diagnoses in complex disorders. Here, we show that specialist multidisciplinary analysis of WGS, following an initial 'no primary findings' (NPF) report, improves diagnostic rates and alters management. We undertook WGS in 102 adults with diagnostically challenging primary mitochondrial disease phenotypes. NPF cases were reviewed by a genomic medicine team, thus enabling bespoke informatic approaches, co-ordinated phenotypic validation, and functional work. We enhanced the diagnostic rate from 16.7% to 31.4%, with management implications for all new diagnoses, and detected strong candidate disease-causing variants in a further 3.9% of patients. This approach presents a standardised model of care that supports mainstream clinicians and enhances diagnostic equity for complex disorders, thereby facilitating access to the potential benefits of genomic healthcare. This research was made possible through access to the data and findings generated by the 100,000 Genomes Project: http://www.genomicsengland.co.uk .
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Affiliation(s)
- William L Macken
- Department of Neuromuscular Diseases, UCL Queen Square Institute of Neurology, London, UK
- NHS Highly Specialised Service for Rare Mitochondrial Disorders, Queen Square Centre for Neuromuscular Diseases, The National Hospital for Neurology and Neurosurgery, London, UK
| | - Micol Falabella
- Department of Neuromuscular Diseases, UCL Queen Square Institute of Neurology, London, UK
| | - Caroline McKittrick
- Department of Neuromuscular Diseases, UCL Queen Square Institute of Neurology, London, UK
| | - Chiara Pizzamiglio
- Department of Neuromuscular Diseases, UCL Queen Square Institute of Neurology, London, UK
- NHS Highly Specialised Service for Rare Mitochondrial Disorders, Queen Square Centre for Neuromuscular Diseases, The National Hospital for Neurology and Neurosurgery, London, UK
| | - Rebecca Ellmers
- Neurogenetics Unit, Rare and Inherited Disease Laboratory, North Thames Genomic Laboratory Hub, London, UK
| | - Kelly Eggleton
- Neurogenetics Unit, Rare and Inherited Disease Laboratory, North Thames Genomic Laboratory Hub, London, UK
| | - Cathy E Woodward
- NHS Highly Specialised Service for Rare Mitochondrial Disorders, Queen Square Centre for Neuromuscular Diseases, The National Hospital for Neurology and Neurosurgery, London, UK
- Neurogenetics Unit, Rare and Inherited Disease Laboratory, North Thames Genomic Laboratory Hub, London, UK
| | - Yogen Patel
- Neurogenetics Unit, Rare and Inherited Disease Laboratory, North Thames Genomic Laboratory Hub, London, UK
| | - Robyn Labrum
- NHS Highly Specialised Service for Rare Mitochondrial Disorders, Queen Square Centre for Neuromuscular Diseases, The National Hospital for Neurology and Neurosurgery, London, UK
- Neurogenetics Unit, Rare and Inherited Disease Laboratory, North Thames Genomic Laboratory Hub, London, UK
| | - Rahul Phadke
- Dubowitz Neuromuscular Centre, Great Ormond Street Hospital for Children NHS Foundation Trust, London, UK
| | - Mary M Reilly
- Department of Neuromuscular Diseases, UCL Queen Square Institute of Neurology, London, UK
| | - Catherine DeVile
- Department of Neurosciences, Great Ormond Street Hospital for Children NHS Foundation Trust, London, UK
| | - Anna Sarkozy
- Dubowitz Neuromuscular Centre, Great Ormond Street Hospital for Children NHS Foundation Trust, London, UK
| | - Emma Footitt
- Metabolic Unit, Great Ormond Street Hospital for Children NHS Foundation Trust, London, UK
| | - James Davison
- Metabolic Unit, Great Ormond Street Hospital for Children NHS Foundation Trust, London, UK
- National Institute for Health and Care Research Great Ormond Street Hospital Biomedical Research Centre, London, UK
| | - Shamima Rahman
- Metabolic Unit, Great Ormond Street Hospital for Children NHS Foundation Trust, London, UK
- Mitochondrial Research Group, UCL Great Ormond Street Institute of Child Health, London, UK
| | - Henry Houlden
- Department of Neuromuscular Diseases, UCL Queen Square Institute of Neurology, London, UK
| | - Enrico Bugiardini
- Department of Neuromuscular Diseases, UCL Queen Square Institute of Neurology, London, UK
- NHS Highly Specialised Service for Rare Mitochondrial Disorders, Queen Square Centre for Neuromuscular Diseases, The National Hospital for Neurology and Neurosurgery, London, UK
| | - Rosaline Quinlivan
- Department of Neuromuscular Diseases, UCL Queen Square Institute of Neurology, London, UK
- NHS Highly Specialised Service for Rare Mitochondrial Disorders, Queen Square Centre for Neuromuscular Diseases, The National Hospital for Neurology and Neurosurgery, London, UK
- Dubowitz Neuromuscular Centre, Great Ormond Street Hospital for Children NHS Foundation Trust, London, UK
| | - Michael G Hanna
- Department of Neuromuscular Diseases, UCL Queen Square Institute of Neurology, London, UK
- NHS Highly Specialised Service for Rare Mitochondrial Disorders, Queen Square Centre for Neuromuscular Diseases, The National Hospital for Neurology and Neurosurgery, London, UK
| | - Jana Vandrovcova
- Department of Neuromuscular Diseases, UCL Queen Square Institute of Neurology, London, UK.
| | - Robert D S Pitceathly
- Department of Neuromuscular Diseases, UCL Queen Square Institute of Neurology, London, UK.
- NHS Highly Specialised Service for Rare Mitochondrial Disorders, Queen Square Centre for Neuromuscular Diseases, The National Hospital for Neurology and Neurosurgery, London, UK.
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19
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Evaluating use of changing technologies for rapid next-generation sequencing in pediatrics. Pediatr Res 2022; 92:1364-1369. [PMID: 35115709 PMCID: PMC10024604 DOI: 10.1038/s41390-022-01965-5] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/04/2021] [Revised: 01/17/2022] [Accepted: 01/20/2022] [Indexed: 02/03/2023]
Abstract
BACKGROUND Rapid next-generation sequencing (NGS) offers the potential to shorten the diagnostic process and improve the care of acutely ill children. The goal of this study was to report our findings, including benefits and limitations, of a targeted NGS panel and rapid genome sequencing (rGS) in neonatal and pediatric acute clinical care settings. METHODS Retrospective analysis of patient characteristics, diagnostic yields, turnaround time, and changes in management for infants and children receiving either RapSeq, a targeted NGS panel for 4500+ genes, or rGS, at the University of Utah Hospital and Primary Children's Hospital, from 2015 to 2020. RESULTS Over a 5-year period, 142 probands underwent rapid NGS: 66 received RapSeq and 76 rGS. Overall diagnostic yield was 39%. In the majority of diagnostic cases, there were one or more changes in clinical care management. Of note, 7% of diagnoses identified by rGS would not have been identified by RapSeq. CONCLUSIONS Our results indicate that rapid NGS impacts acute pediatric care in real-life clinical settings. Although affected by patient selection criteria, diagnostic yields were similar to those from clinical trial settings. Future studies are needed to determine relative advantages, including cost, turnaround time, and benefits for patients, of each approach in specific clinical circumstances. IMPACT The use of comprehensive Mendelian gene panels and genome sequencing in the clinical setting allows for early diagnosis of patients in neonatal, pediatric, and cardiac intensive care units and impactful change in management. Diagnoses led to significant changes in management for several patients in lower acuity inpatient units supporting further exploration of the utility of rapid sequencing in these settings. This study reviews the limitations of comparing sequencing platforms in the clinical setting and the variables that should be considered in evaluating diagnostic rates across studies.
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20
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Baker EK, Ulm EA, Belonis A, Brightman DS, Hallinan BE, Leslie ND, Miethke AG, Vawter-Lee M, Wu Y, Pena LDM. Clinically available testing options resulting in diagnosis in post-exome clinic at one medical center. Front Genet 2022; 13:887698. [PMID: 35937981 PMCID: PMC9355124 DOI: 10.3389/fgene.2022.887698] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2022] [Accepted: 06/28/2022] [Indexed: 11/27/2022] Open
Abstract
Exome sequencing (ES) became clinically available in 2011 and promised an agnostic, unbiased next-generation sequencing (NGS) platform for patients with symptoms believed to have a genetic etiology. The diagnostic yield of ES has been estimated to be between 25–40% and may be higher in specific clinical scenarios. Those who remain undiagnosed may have no molecular findings of interest on ES, variants of uncertain significance in genes that are linked to human disease, or variants of uncertain significance in candidate genes that are not definitively tied to human disease. Recent evidence suggests that a post-exome evaluation consisting of clinical re-phenotyping, functional studies of candidate variants in known genes, and variant reevaluation can lead to a diagnosis in 5–15% of additional cases. In this brief research study, we present our experience on post-exome evaluations in a cohort of patients who are believed to have a genetic etiology for their symptoms. We have reached a full or partial diagnosis in approximately 18% (6/33) of cases that have completed evaluations to date. We accomplished this by utilizing NGS-based methods that are available on a clinical basis. A sample of these cases highlights the utility of ES reanalysis with updated phenotyping allowing for the discovery of new genes, re-adjudication of known variants, incorporating updated phenotypic information, utilizing functional testing such as targeted RNA sequencing, and deploying other NGS-based testing methods such as gene panels and genome sequencing to reach a diagnosis.
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Affiliation(s)
- Elizabeth K. Baker
- Division of Human Genetics, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, United States
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, United States
| | - Elizabeth A. Ulm
- Division of Human Genetics, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, United States
| | - Alyce Belonis
- Division of Human Genetics, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, United States
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, United States
| | - Diana S. Brightman
- Division of Human Genetics, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, United States
| | - Barbara E. Hallinan
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, United States
- Division of Neurology, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, United States
| | - Nancy D. Leslie
- Division of Human Genetics, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, United States
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, United States
| | - Alexander G. Miethke
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, United States
- Division of Gastroenterology, Hepatology and Nutrition, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, United States
| | - Marissa Vawter-Lee
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, United States
- Division of Neurology, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, United States
| | - Yaning Wu
- Division of Human Genetics, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, United States
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, United States
| | - Loren D. M. Pena
- Division of Human Genetics, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, United States
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, United States
- *Correspondence: Loren D. M. Pena,
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21
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Markello C, Huang C, Rodriguez A, Carroll A, Chang PC, Eizenga J, Markello T, Haussler D, Paten B. A complete pedigree-based graph workflow for rare candidate variant analysis. Genome Res 2022; 32:893-903. [PMID: 35483961 PMCID: PMC9104704 DOI: 10.1101/gr.276387.121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2021] [Accepted: 03/24/2022] [Indexed: 11/24/2022]
Abstract
Methods that use a linear genome reference for genome sequencing data analysis are reference-biased. In the field of clinical genetics for rare diseases, a resulting reduction in genotyping accuracy in some regions has likely prevented the resolution of some cases. Pangenome graphs embed population variation into a reference structure. Although pangenome graphs have helped to reduce reference mapping bias, further performance improvements are possible. We introduce VG-Pedigree, a pedigree-aware workflow based on the pangenome-mapping tool of Giraffe and the variant calling tool DeepTrio using a specially trained model for Giraffe-based alignments. We demonstrate mapping and variant calling improvements in both single-nucleotide variants (SNVs) and insertion and deletion (indel) variants over those produced by alignments created using BWA-MEM to a linear-reference and Giraffe mapping to a pangenome graph containing data from the 1000 Genomes Project. We have also adapted and upgraded deleterious-variant (DV) detecting methods and programs into a streamlined workflow. We used these workflows in combination to detect small lists of candidate DVs among 15 family quartets and quintets of the Undiagnosed Diseases Program (UDP). All candidate DVs that were previously diagnosed using the Mendelian models covered by the previously published methods were recapitulated by these workflows. The results of these experiments indicate that a slightly greater absolute count of DVs are detected in the proband population than in their matched unaffected siblings.
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Affiliation(s)
- Charles Markello
- UC Santa Cruz Genomics Institute, Santa Cruz, California 95060, USA
| | - Charles Huang
- Undiagnosed Diseases Program, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland 20894, USA
| | - Alex Rodriguez
- Undiagnosed Diseases Program, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland 20894, USA
| | - Andrew Carroll
- Google Incorporated, Mountain View, California 94043, USA
| | - Pi-Chuan Chang
- Google Incorporated, Mountain View, California 94043, USA
| | - Jordan Eizenga
- UC Santa Cruz Genomics Institute, Santa Cruz, California 95060, USA
| | - Thomas Markello
- Undiagnosed Diseases Program, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland 20894, USA
| | - David Haussler
- UC Santa Cruz Genomics Institute, Santa Cruz, California 95060, USA
- Howard Hughes Medical Institute, University of California, Santa Cruz, California 95064, USA
| | - Benedict Paten
- UC Santa Cruz Genomics Institute, Santa Cruz, California 95060, USA
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22
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Global Regulatory and Public Health Initiatives to Advance Pediatric Drug Development for Rare Diseases. Ther Innov Regul Sci 2022; 56:964-975. [PMID: 35471559 PMCID: PMC9040360 DOI: 10.1007/s43441-022-00409-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2022] [Accepted: 04/07/2022] [Indexed: 12/17/2022]
Abstract
The literature thoroughly describes the challenges of pediatric drug development for rare diseases. This includes (1) generating interest from sponsors, (2) small numbers of children affected by a particular disease, (3) difficulties with study design, (4) lack of definitive outcome measures and assessment tools, (5) the need for additional safeguards for children as a vulnerable population, and (6) logistical hurdles to completing trials, especially with the need for longer term follow-up to establish safety and efficacy. There has also been an increasing awareness of the need to engage patients and their families in drug development processes and to address inequities in access to pediatric clinical trials. The year 2020 ushered in yet another challenge—the COVID-19 pandemic. The pediatric drug development ecosystem continues to evolve to meet these challenges. This article will focus on several key factors including recent regulatory approaches and public health policies to facilitate pediatric rare disease drug development, emerging trends in product development (biologics, molecularly targeted therapies), innovations in trial design/endpoints and data collection, and current efforts to increase patient engagement and promote equity. Finally, lessons learned from COVID-19 about building adaptable pediatric rare disease drug development processes will be discussed.
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23
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Amore G, Butera A, Spoto G, Valentini G, Saia MC, Salpietro V, Calì F, Di Rosa G, Nicotera AG. KCNQ2-Related Neonatal Epilepsy Treated With Vitamin B6: A Report of Two Cases and Literature Review. Front Neurol 2022; 13:826225. [PMID: 35401395 PMCID: PMC8992372 DOI: 10.3389/fneur.2022.826225] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Accepted: 02/28/2022] [Indexed: 11/13/2022] Open
Abstract
Potassium Voltage-Gated Channel Subfamily Q Member 2 (KCNQ2) gene has been initially associated with "Benign familial neonatal epilepsy" (BFNE). Amounting evidence arising by next-generation sequencing techniques have led to the definition of new phenotypes, such as neonatal epileptic encephalopathy (NEE), expanding the spectrum of KCNQ2-related epilepsies. Pyridoxine (PN) dependent epilepsies (PDE) are a heterogeneous group of autosomal recessive disorders associated with neonatal-onset seizures responsive to treatment with vitamin B6 (VitB6). Few cases of neonatal seizures due to KCNQ2 pathogenic variants have been reported as successfully responding to VitB6. We reported two cases of KCNQ2-related neonatal epilepsies involving a 5-year-old male with a paternally inherited heterozygous mutation (c.1639C>T; p.Arg547Trp), and a 10-year-old female with a de novo heterozygous mutation (c.740C>T; p.Ser247Leu). Both children benefited from VitB6 treatment. Although the mechanisms explaining the efficacy of VitB6 in such patients remain unclear, this treatment option in neonatal-onset seizures is easily taken into account in Neonatal Intensive Care Units (NICUs). Further studies should be conducted to better define clinical guidelines and treatment protocols.
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Affiliation(s)
- Greta Amore
- Department of Human Pathology of the Adult and Developmental Age "Gaetano Barresi", Unit of Child Neurology and Psychiatry, University of Messina, Messina, Italy
| | - Ambra Butera
- Department of Human Pathology of the Adult and Developmental Age "Gaetano Barresi", Unit of Child Neurology and Psychiatry, University of Messina, Messina, Italy
| | - Giulia Spoto
- Department of Human Pathology of the Adult and Developmental Age "Gaetano Barresi", Unit of Child Neurology and Psychiatry, University of Messina, Messina, Italy
| | - Giulia Valentini
- Department of Human Pathology of the Adult and Developmental Age "Gaetano Barresi", Unit of Child Neurology and Psychiatry, University of Messina, Messina, Italy
| | - Maria Concetta Saia
- Department of Human Pathology of the Adult and Developmental Age "Gaetano Barresi", Unit of Child Neurology and Psychiatry, University of Messina, Messina, Italy
| | - Vincenzo Salpietro
- Department of Neuromuscular Disorders, Institute of Neurology, University College London, London, United Kingdom.,Pediatric Neurology and Muscular Diseases Unit, Scientific Institute for Research, Hospitalization and Healthcare (IRCCS) Istituto Giannina Gaslini, Genoa, Italy.,Department of Neurosciences, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health, University of Genoa, Genoa, Italy
| | - Francesco Calì
- Oasi Research Institute-Scientific Institute for Research, Hospitalization and Healthcare (IRCCS), Troina, Italy
| | - Gabriella Di Rosa
- Department of Human Pathology of the Adult and Developmental Age "Gaetano Barresi", Unit of Child Neurology and Psychiatry, University of Messina, Messina, Italy
| | - Antonio Gennaro Nicotera
- Department of Human Pathology of the Adult and Developmental Age "Gaetano Barresi", Unit of Child Neurology and Psychiatry, University of Messina, Messina, Italy
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24
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Elliott AM, Adam S, du Souich C, Lehman A, Nelson TN, van Karnebeek C, Alderman E, Armstrong L, Aubertin G, Blood K, Boelman C, Boerkoel C, Bretherick K, Brown L, Chijiwa C, Clarke L, Couse M, Creighton S, Watts-Dickens A, Gibson WT, Gill H, Tarailo-Graovac M, Hamilton S, Heran H, Horvath G, Huang L, Hulait GK, Koehn D, Lee HK, Lewis S, Lopez E, Louie K, Niederhoffer K, Matthews A, Meagher K, Peng JJ, Patel MS, Race S, Richmond P, Rupps R, Salvarinova R, Seath K, Selby K, Steinraths M, Stockler S, Tang K, Tyson C, van Allen M, Wasserman W, Mwenifumbo J, Friedman JM. Genome-wide Sequencing and the Clinical Diagnosis of Genetic Disease: The CAUSES Study. HGG ADVANCES 2022; 3:100108. [PMID: 35599849 PMCID: PMC9117924 DOI: 10.1016/j.xhgg.2022.100108] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2021] [Accepted: 04/11/2022] [Indexed: 12/02/2022] Open
Abstract
Genome-wide sequencing (GWS) is a standard of care for diagnosis of suspected genetic disorders, but the proportion of patients found to have pathogenic or likely pathogenic variants ranges from less than 30% to more than 60% in reported studies. It has been suggested that the diagnostic rate can be improved by interpreting genomic variants in the context of each affected individual’s full clinical picture and by regular follow-up and reinterpretation of GWS laboratory results. Trio exome sequencing was performed in 415 families and trio genome sequencing in 85 families in the CAUSES study. The variants observed were interpreted by a multidisciplinary team including laboratory geneticists, bioinformaticians, clinical geneticists, genetic counselors, pediatric subspecialists, and the referring physician, and independently by a clinical laboratory using standard American College of Medical Genetics and Genomics (ACMG) criteria. Individuals were followed for an average of 5.1 years after testing, with clinical reassessment and reinterpretation of the GWS results as necessary. The multidisciplinary team established a diagnosis of genetic disease in 43.0% of the families at the time of initial GWS interpretation, and longitudinal follow-up and reinterpretation of GWS results produced new diagnoses in 17.2% of families whose initial GWS interpretation was uninformative or uncertain. Reinterpretation also resulted in rescinding a diagnosis in four families (1.9%). Of the families studied, 33.6% had ACMG pathogenic or likely pathogenic variants related to the clinical indication. Close collaboration among clinical geneticists, genetic counselors, laboratory geneticists, bioinformaticians, and individuals’ primary physicians, with ongoing follow-up, reanalysis, and reinterpretation over time, can improve the clinical value of GWS.
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Affiliation(s)
- Alison M Elliott
- Department of Medical Genetics, University of British Columbia, Vancouver, BC, Canada
- BC Children's Hospital Research Institute, Vancouver, BC, Canada
- Women's Health Research Institute, Vancouver, BC, Canada
| | - Shelin Adam
- Department of Medical Genetics, University of British Columbia, Vancouver, BC, Canada
- BC Children's Hospital Research Institute, Vancouver, BC, Canada
| | - Christèle du Souich
- Department of Medical Genetics, University of British Columbia, Vancouver, BC, Canada
- BC Children's Hospital Research Institute, Vancouver, BC, Canada
| | - Anna Lehman
- Department of Medical Genetics, University of British Columbia, Vancouver, BC, Canada
- BC Children's Hospital Research Institute, Vancouver, BC, Canada
| | - Tanya N Nelson
- Division of Genome Diagnostics, Department of Pathology and Laboratory Medicine, BC Children's and Women's Hospitals, Vancouver, BC, Canada
| | - Clara van Karnebeek
- Department of Pediatrics, Center for Molecular Medicine and Therapeutics, University of British Columbia, Vancouver, BC, Canada
- Department of Pediatrics, Emma Children's Hospital, Amsterdam, University Medical Centers, University of Amsterdam, Amsterdam, the Netherlands
| | - Emily Alderman
- Department of Medical Genetics, University of British Columbia, Vancouver, BC, Canada
| | - Linlea Armstrong
- Department of Medical Genetics, University of British Columbia, Vancouver, BC, Canada
- BC Children's Hospital Research Institute, Vancouver, BC, Canada
| | - Gudrun Aubertin
- Department of Medical Genetics, University of British Columbia, Vancouver, BC, Canada
| | - Katherine Blood
- Department of Medical Genetics, University of British Columbia, Vancouver, BC, Canada
| | - Cyrus Boelman
- BC Children's Hospital Research Institute, Vancouver, BC, Canada
- Division of Neurology, Department of Pediatrics, University of British Columbia, Vancouver, BC, Canada
| | - Cornelius Boerkoel
- Department of Medical Genetics, University of British Columbia, Vancouver, BC, Canada
- BC Children's Hospital Research Institute, Vancouver, BC, Canada
| | - Karla Bretherick
- Division of Genome Diagnostics, Department of Pathology and Laboratory Medicine, BC Children's and Women's Hospitals, Vancouver, BC, Canada
| | - Lindsay Brown
- Division of Genome Diagnostics, Department of Pathology and Laboratory Medicine, BC Children's and Women's Hospitals, Vancouver, BC, Canada
| | - Chieko Chijiwa
- Department of Medical Genetics, University of British Columbia, Vancouver, BC, Canada
| | - Lorne Clarke
- Department of Medical Genetics, University of British Columbia, Vancouver, BC, Canada
- BC Children's Hospital Research Institute, Vancouver, BC, Canada
| | - Madeline Couse
- Department of Medical Genetics, University of British Columbia, Vancouver, BC, Canada
| | - Susan Creighton
- Department of Medical Genetics, University of British Columbia, Vancouver, BC, Canada
| | - Abby Watts-Dickens
- Department of Medical Genetics, University of British Columbia, Vancouver, BC, Canada
| | - William T Gibson
- Department of Medical Genetics, University of British Columbia, Vancouver, BC, Canada
- BC Children's Hospital Research Institute, Vancouver, BC, Canada
| | - Harinder Gill
- Department of Medical Genetics, University of British Columbia, Vancouver, BC, Canada
| | | | - Sara Hamilton
- Department of Medical Genetics, University of British Columbia, Vancouver, BC, Canada
| | - Harindar Heran
- Department of Medical Genetics, University of British Columbia, Vancouver, BC, Canada
| | - Gabriella Horvath
- BC Children's Hospital Research Institute, Vancouver, BC, Canada
- Division of Biochemical Diseases, Department of Pediatrics, University of British Columbia, Vancouver, BC, Canada
| | - Lijia Huang
- Division of Genome Diagnostics, Department of Pathology and Laboratory Medicine, BC Children's and Women's Hospitals, Vancouver, BC, Canada
| | - Gurdip K Hulait
- Department of Medical Genetics, University of British Columbia, Vancouver, BC, Canada
| | - David Koehn
- Department of Medical Genetics, University of British Columbia, Vancouver, BC, Canada
| | - Hyun Kyung Lee
- Department of Medical Genetics, University of British Columbia, Vancouver, BC, Canada
| | - Suzanne Lewis
- Department of Medical Genetics, University of British Columbia, Vancouver, BC, Canada
- BC Children's Hospital Research Institute, Vancouver, BC, Canada
| | - Elena Lopez
- Department of Medical Genetics, University of British Columbia, Vancouver, BC, Canada
- BC Children's Hospital Research Institute, Vancouver, BC, Canada
| | - Kristal Louie
- Department of Medical Genetics, University of British Columbia, Vancouver, BC, Canada
| | - Karen Niederhoffer
- Department of Medical Genetics, University of British Columbia, Vancouver, BC, Canada
| | - Allison Matthews
- Division of Genome Diagnostics, Department of Pathology and Laboratory Medicine, BC Children's and Women's Hospitals, Vancouver, BC, Canada
| | - Kirsten Meagher
- Department of Medical Genetics, University of British Columbia, Vancouver, BC, Canada
| | - Junran J Peng
- BC Children's Hospital Research Institute, Vancouver, BC, Canada
| | - Millan S Patel
- Department of Medical Genetics, University of British Columbia, Vancouver, BC, Canada
- BC Children's Hospital Research Institute, Vancouver, BC, Canada
| | - Simone Race
- Division of Biochemical Diseases, Department of Pediatrics, University of British Columbia, Vancouver, BC, Canada
| | - Phillip Richmond
- BC Children's Hospital Research Institute, Vancouver, BC, Canada
| | - Rosemarie Rupps
- Department of Medical Genetics, University of British Columbia, Vancouver, BC, Canada
| | - Ramona Salvarinova
- BC Children's Hospital Research Institute, Vancouver, BC, Canada
- Division of Biochemical Diseases, Department of Pediatrics, University of British Columbia, Vancouver, BC, Canada
| | - Kimberly Seath
- Department of Medical Genetics, University of British Columbia, Vancouver, BC, Canada
| | - Kathryn Selby
- BC Children's Hospital Research Institute, Vancouver, BC, Canada
- Division of Neurology, Department of Pediatrics, University of British Columbia, Vancouver, BC, Canada
| | - Michelle Steinraths
- Department of Medical Genetics, University of British Columbia, Vancouver, BC, Canada
| | - Sylvia Stockler
- BC Children's Hospital Research Institute, Vancouver, BC, Canada
- Division of Biochemical Diseases, Department of Pediatrics, University of British Columbia, Vancouver, BC, Canada
| | - Kaoru Tang
- Department of Medical Genetics, University of British Columbia, Vancouver, BC, Canada
| | - Christine Tyson
- Division of Genome Diagnostics, Department of Pathology and Laboratory Medicine, BC Children's and Women's Hospitals, Vancouver, BC, Canada
| | - Margot van Allen
- Department of Medical Genetics, University of British Columbia, Vancouver, BC, Canada
- BC Children's Hospital Research Institute, Vancouver, BC, Canada
| | - Wyeth Wasserman
- Department of Medical Genetics, University of British Columbia, Vancouver, BC, Canada
- BC Children's Hospital Research Institute, Vancouver, BC, Canada
- Department of Pediatrics, Center for Molecular Medicine and Therapeutics, University of British Columbia, Vancouver, BC, Canada
| | - Jill Mwenifumbo
- BC Children's Hospital Research Institute, Vancouver, BC, Canada
| | - Jan M Friedman
- Department of Medical Genetics, University of British Columbia, Vancouver, BC, Canada
- BC Children's Hospital Research Institute, Vancouver, BC, Canada
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25
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Cloney T, Gallacher L, Pais LS, Tan NB, Yeung A, Stark Z, Brown NJ, McGillivray G, Delatycki MB, de Silva MG, Downie L, Stutterd CA, Elliott J, Compton AG, Lovgren A, Oertel R, Francis D, Bell KM, Sadedin S, Lim SC, Helman G, Simons C, Macarthur DG, Thorburn DR, O'Donnell-Luria AH, Christodoulou J, White SM, Tan TY. Lessons learnt from multifaceted diagnostic approaches to the first 150 families in Victoria's Undiagnosed Diseases Program. J Med Genet 2021; 59:748-758. [PMID: 34740920 DOI: 10.1136/jmedgenet-2021-107902] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2021] [Accepted: 09/14/2021] [Indexed: 01/18/2023]
Abstract
BACKGROUND Clinical exome sequencing typically achieves diagnostic yields of 30%-57.5% in individuals with monogenic rare diseases. Undiagnosed diseases programmes implement strategies to improve diagnostic outcomes for these individuals. AIM We share the lessons learnt from the first 3 years of the Undiagnosed Diseases Program-Victoria, an Australian programme embedded within a clinical genetics service in the state of Victoria with a focus on paediatric rare diseases. METHODS We enrolled families who remained without a diagnosis after clinical genomic (panel, exome or genome) sequencing between 2016 and 2018. We used family-based exome sequencing (family ES), family-based genome sequencing (family GS), RNA sequencing (RNA-seq) and high-resolution chromosomal microarray (CMA) with research-based analysis. RESULTS In 150 families, we achieved a diagnosis or strong candidate in 64 (42.7%) (37 in known genes with a consistent phenotype, 3 in known genes with a novel phenotype and 24 in novel disease genes). Fifty-four diagnoses or strong candidates were made by family ES, six by family GS with RNA-seq, two by high-resolution CMA and two by data reanalysis. CONCLUSION We share our lessons learnt from the programme. Flexible implementation of multiple strategies allowed for scalability and response to the availability of new technologies. Broad implementation of family ES with research-based analysis showed promising yields post a negative clinical singleton ES. RNA-seq offered multiple benefits in family ES-negative populations. International data sharing strategies were critical in facilitating collaborations to establish novel disease-gene associations. Finally, the integrated approach of a multiskilled, multidisciplinary team was fundamental to having diverse perspectives and strategic decision-making.
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Affiliation(s)
- Thomas Cloney
- Victorian Clinical Genetics Services, Murdoch Children's Research Institute, Melbourne, Victoria, Australia.,Department of Paediatrics, The University of Melbourne, Melbourne, Victoria, Australia
| | - Lyndon Gallacher
- Victorian Clinical Genetics Services, Murdoch Children's Research Institute, Melbourne, Victoria, Australia.,Department of Paediatrics, The University of Melbourne, Melbourne, Victoria, Australia
| | - Lynn S Pais
- Center for Mendelian Genomics, Eli and Edythe L Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA.,Division of Genetics and Genomics, Boston Children's Hospital, Boston, Massachusetts, USA
| | - Natalie B Tan
- Victorian Clinical Genetics Services, Murdoch Children's Research Institute, Melbourne, Victoria, Australia.,Department of Paediatrics, The University of Melbourne, Melbourne, Victoria, Australia
| | - Alison Yeung
- Victorian Clinical Genetics Services, Murdoch Children's Research Institute, Melbourne, Victoria, Australia.,Department of Paediatrics, The University of Melbourne, Melbourne, Victoria, Australia
| | - Zornitza Stark
- Victorian Clinical Genetics Services, Murdoch Children's Research Institute, Melbourne, Victoria, Australia.,Department of Paediatrics, The University of Melbourne, Melbourne, Victoria, Australia
| | - Natasha J Brown
- Victorian Clinical Genetics Services, Murdoch Children's Research Institute, Melbourne, Victoria, Australia.,Department of Paediatrics, The University of Melbourne, Melbourne, Victoria, Australia
| | - George McGillivray
- Victorian Clinical Genetics Services, Murdoch Children's Research Institute, Melbourne, Victoria, Australia
| | - Martin B Delatycki
- Victorian Clinical Genetics Services, Murdoch Children's Research Institute, Melbourne, Victoria, Australia.,Department of Paediatrics, The University of Melbourne, Melbourne, Victoria, Australia
| | - Michelle G de Silva
- Victorian Clinical Genetics Services, Murdoch Children's Research Institute, Melbourne, Victoria, Australia
| | - Lilian Downie
- Victorian Clinical Genetics Services, Murdoch Children's Research Institute, Melbourne, Victoria, Australia.,Department of Paediatrics, The University of Melbourne, Melbourne, Victoria, Australia
| | - Chloe A Stutterd
- Victorian Clinical Genetics Services, Murdoch Children's Research Institute, Melbourne, Victoria, Australia.,Department of Paediatrics, The University of Melbourne, Melbourne, Victoria, Australia
| | - Justine Elliott
- Victorian Clinical Genetics Services, Murdoch Children's Research Institute, Melbourne, Victoria, Australia
| | - Alison G Compton
- Department of Paediatrics, The University of Melbourne, Melbourne, Victoria, Australia.,Brain and Mitochondrial Research Group, Murdoch Children's Research Institute, Melbourne, Victoria, Australia
| | - Alysia Lovgren
- Center for Mendelian Genomics, Eli and Edythe L Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA.,Analytic and Translational Genomics Unit, Massachusetts General Hospital, Boston, Massachusetts, USA.,Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts, USA
| | - Ralph Oertel
- Victorian Clinical Genetics Services, Murdoch Children's Research Institute, Melbourne, Victoria, Australia
| | - David Francis
- Victorian Clinical Genetics Services, Murdoch Children's Research Institute, Melbourne, Victoria, Australia
| | - Katrina M Bell
- Victorian Clinical Genetics Services, Murdoch Children's Research Institute, Melbourne, Victoria, Australia.,Bioinformatics, Murdoch Children's Research Institute, Melbourne, Victoria, Australia
| | - Simon Sadedin
- Victorian Clinical Genetics Services, Murdoch Children's Research Institute, Melbourne, Victoria, Australia.,Department of Paediatrics, The University of Melbourne, Melbourne, Victoria, Australia
| | - Sze Chern Lim
- Victorian Clinical Genetics Services, Murdoch Children's Research Institute, Melbourne, Victoria, Australia
| | - Guy Helman
- Brain and Mitochondrial Research Group, Murdoch Children's Research Institute, Melbourne, Victoria, Australia
| | - Cas Simons
- Victorian Clinical Genetics Services, Murdoch Children's Research Institute, Melbourne, Victoria, Australia.,Translational Bioinformatics, Murdoch Children's Research Institute, Melbourne, Victoria, Australia
| | - Daniel G Macarthur
- Center for Mendelian Genomics, Eli and Edythe L Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA.,Centre for Population Genomics, Garvan Institute of Medical Research, Sydney, New South Wales, Australia.,Centre for Population Genomics, Murdoch Children's Research Institute, Melbourne, Victoria, Australia
| | - David R Thorburn
- Victorian Clinical Genetics Services, Murdoch Children's Research Institute, Melbourne, Victoria, Australia.,Department of Paediatrics, The University of Melbourne, Melbourne, Victoria, Australia.,Brain and Mitochondrial Research Group, Murdoch Children's Research Institute, Melbourne, Victoria, Australia
| | - Anne H O'Donnell-Luria
- Center for Mendelian Genomics, Eli and Edythe L Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA.,Division of Genetics and Genomics, Boston Children's Hospital, Boston, Massachusetts, USA.,Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - John Christodoulou
- Victorian Clinical Genetics Services, Murdoch Children's Research Institute, Melbourne, Victoria, Australia.,Department of Paediatrics, The University of Melbourne, Melbourne, Victoria, Australia.,Neurodevelopmental Genomics Research Group, Murdoch Children's Research Institute, Melbourne, Victoria, Australia
| | - Susan M White
- Victorian Clinical Genetics Services, Murdoch Children's Research Institute, Melbourne, Victoria, Australia.,Department of Paediatrics, The University of Melbourne, Melbourne, Victoria, Australia
| | - Tiong Yang Tan
- Victorian Clinical Genetics Services, Murdoch Children's Research Institute, Melbourne, Victoria, Australia .,Department of Paediatrics, The University of Melbourne, Melbourne, Victoria, Australia
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26
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Brockman DG, Austin-Tse CA, Pelletier RC, Harley C, Patterson C, Head H, Leonard CE, O'Brien K, Mahanta LM, Lebo MS, Lu CY, Natarajan P, Khera AV, Aragam KG, Kathiresan S, Rehm HL, Udler MS. Randomized prospective evaluation of genome sequencing versus standard-of-care as a first molecular diagnostic test. Genet Med 2021; 23:1689-1696. [PMID: 33976420 PMCID: PMC8488861 DOI: 10.1038/s41436-021-01193-y] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2020] [Revised: 04/14/2021] [Accepted: 04/15/2021] [Indexed: 11/09/2022] Open
Abstract
PURPOSE To evaluate the diagnostic yield and clinical relevance of clinical genome sequencing (cGS) as a first genetic test for patients with suspected monogenic disorders. METHODS We conducted a prospective randomized study with pediatric and adult patients recruited from genetics clinics at Massachusetts General Hospital who were undergoing planned genetic testing. Participants were randomized into two groups: standard-of-care genetic testing (SOC) only or SOC and cGS. RESULTS Two hundred four participants were enrolled, 202 were randomized to one of the intervention arms, and 99 received cGS. In total, cGS returned 16 molecular diagnoses that fully or partially explained the indication for testing in 16 individuals (16.2% of the cohort, 95% confidence interval [CI] 8.9-23.4%), which was not significantly different from SOC (18.2%, 95% CI 10.6-25.8%, P = 0.71). An additional eight molecular diagnoses reported by cGS had uncertain relevance to the participant's phenotype. Nevertheless, referring providers considered 20/24 total cGS molecular diagnoses (83%) to be explanatory for clinical features or worthy of additional workup. CONCLUSION cGS is technically suitable as a first genetic test. In our cohort, diagnostic yield was not significantly different from SOC. Further studies addressing other variant types and implementation challenges are needed to support feasibility and utility of broad-scale cGS adoption.
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Affiliation(s)
- Deanna G Brockman
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA.
- Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA, USA.
| | - Christina A Austin-Tse
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Laboratory for Molecular Medicine, Partners Personalized Medicine, Cambridge, MA, USA
- Department of Pathology, Massachusetts General Hospital, Boston, MA, USA
| | - Renée C Pelletier
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA, USA
| | - Caroline Harley
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Candace Patterson
- Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA, USA
| | - Holly Head
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Courtney Elizabeth Leonard
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA, USA
| | - Kimberly O'Brien
- Laboratory for Molecular Medicine, Partners Personalized Medicine, Cambridge, MA, USA
| | - Lisa M Mahanta
- Laboratory for Molecular Medicine, Partners Personalized Medicine, Cambridge, MA, USA
| | - Matthew S Lebo
- Laboratory for Molecular Medicine, Partners Personalized Medicine, Cambridge, MA, USA
| | - Christine Y Lu
- Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, USA
| | - Pradeep Natarajan
- Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA, USA
- Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
| | - Amit V Khera
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA, USA
| | - Krishna G Aragam
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA, USA
| | - Sekar Kathiresan
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA, USA
| | - Heidi L Rehm
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Miriam S Udler
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA, USA
- Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Diabetes Unit, Massachusetts General Hospital, Boston, MA, USA
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27
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Sapp JC, Facio FM, Cooper D, Lewis KL, Modlin E, van der Wees P, Biesecker LG. A systematic literature review of disclosure practices and reported outcomes for medically actionable genomic secondary findings. Genet Med 2021; 23:2260-2269. [PMID: 34433902 PMCID: PMC9017985 DOI: 10.1038/s41436-021-01295-7] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2021] [Revised: 07/15/2021] [Accepted: 07/20/2021] [Indexed: 01/14/2023] Open
Abstract
Purpose: Secondary findings (SF) are present in 1–4% of individuals undergoing genome/exome sequencing. A review of how SF are disclosed and what outcomes result from their receipt is urgent and timely. Methods: We conducted a systematic literature review of SF disclosure practices and outcomes after receipt including cascade testing, family and provider communication, and healthcare actions. Of the 1,184 non-duplicate records screened we summarize findings from 27 included research articles describing SF disclosure practices, outcomes after receipt, or both. Results: The included articles reported 709 unique SF index recipients/families. Referrals and/or recommendations were provided 647 SF recipients and outcome data were available for 236. At least one recommended evaluation was reported for 146 SF recipients; 16 reports of treatment or prophylactic surgery were identified. We found substantial variations in how the constructs of interest were defined and described. Conclusion: Variation in how SF disclosure and outcomes were described limited our ability to compare findings. We conclude the literature provided limited insight into how the ACMG guidelines have been translated into precision health outcomes for SF recipients. Robust studies of SF recipients are needed and should be prioritized for future research.
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Affiliation(s)
- Julie C Sapp
- Center for Precision Health Research, National Human Genome Research Institute, Bethesda, MD, USA. .,Translational Health Sciences, George Washington University School of Medicine and Health Sciences, Washington, DC, USA.
| | - Flavia M Facio
- Center for Precision Health Research, National Human Genome Research Institute, Bethesda, MD, USA
| | - Diane Cooper
- National Institutes of Health Library, National Institutes of Health Clinical Center, Bethesda, MD, USA
| | - Katie L Lewis
- Center for Precision Health Research, National Human Genome Research Institute, Bethesda, MD, USA
| | - Emily Modlin
- Center for Precision Health Research, National Human Genome Research Institute, Bethesda, MD, USA
| | - Philip van der Wees
- Translational Health Sciences, George Washington University School of Medicine and Health Sciences, Washington, DC, USA.,Radboud University Medical Center, IQ Healthcare and Rehabilitation, Nijmegen, Netherlands
| | - Leslie G Biesecker
- Center for Precision Health Research, National Human Genome Research Institute, Bethesda, MD, USA
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28
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Narayanan DL, Udyawar D, Kaur P, Sharma S, Suresh N, Nampoothiri S, do Rosario MC, Somashekar PH, Rao LP, Kausthubham N, Majethia P, Pande S, Ramesh Bhat Y, Shrikiran A, Bielas S, Girisha KM, Shukla A. Multilocus disease-causing genomic variations for Mendelian disorders: role of systematic phenotyping and implications on genetic counselling. Eur J Hum Genet 2021; 29:1774-1780. [PMID: 34276053 PMCID: PMC8633282 DOI: 10.1038/s41431-021-00933-7] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2020] [Revised: 04/24/2021] [Accepted: 06/22/2021] [Indexed: 11/09/2022] Open
Abstract
Multilocus disease-causing genomic variations (MGVs) and multiple genetic diagnoses (MGDs) are increasingly being recognised in individuals and families with Mendelian disorders. This can be mainly attributed to the widespread use of genomic tests for the evaluation of these disorders. We conducted a retrospective study of families evaluated over the last 6 years at our centre to identify families with MGVs and MGDs. MGVs were observed in fourteen families. We observed five different consequences: (i) individuals with MGVs presenting as blended phenotypes (ii) individuals with MGVs presenting with distinct phenotypes (iii) individuals with MGVs with age-dependent penetrance (iv) individuals with MGVs with one phenotype obscured by another more predominant phenotype (v) two distinct phenotypes in different individuals in families with MGVs. Consanguinity was present in eight (8/14, 57.1%) of them. Thirteen families had two Mendelian disorders and one had three Mendelian disorders. The risk of recurrence of one or more conditions in these families ranged from 25% to 75%. Our findings underline the importance of the role of a clinical geneticist in systematic phenotyping, challenges in genetic counselling and risk estimation in families with MGVs and MGDs, especially in highly inbred populations.
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Affiliation(s)
- Dhanya Lakshmi Narayanan
- Department of Medical Genetics, Kasturba Medical College, Manipal, Manipal Academy of Higher Education, Manipal, India
| | - Divya Udyawar
- Department of Medical Genetics, Kasturba Medical College, Manipal, Manipal Academy of Higher Education, Manipal, India
| | - Parneet Kaur
- Department of Medical Genetics, Kasturba Medical College, Manipal, Manipal Academy of Higher Education, Manipal, India
| | - Suvasini Sharma
- Department of Pediatrics (Neurology division), Lady Hardinge Medical College and Kalawati Saran Children's Hospital, New Delhi, India
| | - Narayanaswamy Suresh
- Department of Pediatrics (Neurology division), Lady Hardinge Medical College and Kalawati Saran Children's Hospital, New Delhi, India
| | - Sheela Nampoothiri
- Department of Pediatric Genetics, Amrita Institute of Medical Sciences and Research Centre, Cochin, India
| | - Michelle C do Rosario
- Department of Medical Genetics, Kasturba Medical College, Manipal, Manipal Academy of Higher Education, Manipal, India
| | - Puneeth H Somashekar
- Department of Medical Genetics, Kasturba Medical College, Manipal, Manipal Academy of Higher Education, Manipal, India
| | - Lakshmi Priya Rao
- Department of Medical Genetics, Kasturba Medical College, Manipal, Manipal Academy of Higher Education, Manipal, India
| | - Neethukrishna Kausthubham
- Department of Medical Genetics, Kasturba Medical College, Manipal, Manipal Academy of Higher Education, Manipal, India
| | - Purvi Majethia
- Department of Medical Genetics, Kasturba Medical College, Manipal, Manipal Academy of Higher Education, Manipal, India
| | - Shruti Pande
- Department of Medical Genetics, Kasturba Medical College, Manipal, Manipal Academy of Higher Education, Manipal, India
| | - Y Ramesh Bhat
- Department of Pediatrics, Kasturba Medical College, Manipal, Manipal Academy of Higher Education, Manipal, India
| | - Aroor Shrikiran
- Department of Pediatrics, Kasturba Medical College, Manipal, Manipal Academy of Higher Education, Manipal, India
| | - Stephanie Bielas
- Department of Human Genetics, University of Michigan Medical School, Ann Arbor, MI, USA
| | - Katta Mohan Girisha
- Department of Medical Genetics, Kasturba Medical College, Manipal, Manipal Academy of Higher Education, Manipal, India
| | - Anju Shukla
- Department of Medical Genetics, Kasturba Medical College, Manipal, Manipal Academy of Higher Education, Manipal, India.
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29
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Berrios C, Hurley EA, Willig L, Thiffault I, Saunders C, Pastinen T, Goggin K, Farrow E. Challenges in genetic testing: clinician variant interpretation processes and the impact on clinical care. Genet Med 2021; 23:2289-2299. [PMID: 34257423 DOI: 10.1038/s41436-021-01267-x] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2021] [Revised: 06/23/2021] [Accepted: 06/24/2021] [Indexed: 01/24/2023] Open
Abstract
PURPOSE Efforts have been made to standardize laboratory variant interpretation, but clinicians are ultimately tasked with clinical correlation and application of genetic test results in patient care. This study aimed to explore processes clinicians utilize when reviewing and returning genetic test results, and how they impact patient care. METHODS Medical geneticists, genetic counselors, and nongenetics clinicians from two Midwestern states completed surveys (n = 98) and in-depth interviews (n = 29) on practices of reviewing and returning genetic test results. Retrospective chart review (n = 130) examined discordant interpretations and the impact on care. RESULTS Participants reported variable behaviors in both reviewing and returning results based on factors such as confidence, view of role, practice setting, and relationship with the lab. Providers did not report requesting changes to variant classifications from laboratories, but indicated relaying conflicting classifications to patients in some cases. Chart reviews revealed medically impactful differences in interpretation between laboratories and clinicians in 18 (13.8%) records. CONCLUSION Clinician practices for reviewing and integrating genetic test results into patient care vary within and between specialties and impact patient care. Strategies to better incorporate both laboratory and clinician expertise into interpretation of genetic results could result in improved care across providers and settings.
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Affiliation(s)
- Courtney Berrios
- Genomic Medicine Center, Children's Mercy Hospital, Kansas City, MO, USA. .,University of Missouri Kansas City School of Medicine, Kansas City, MO, USA.
| | - Emily A Hurley
- University of Missouri Kansas City School of Medicine, Kansas City, MO, USA.,Health Services and Outcomes Research, Children's Mercy Hospital, Kansas City, MO, USA.,University of Kansas Medical Center, Kansas City, MO, USA
| | - Laurel Willig
- Genomic Medicine Center, Children's Mercy Hospital, Kansas City, MO, USA.,University of Missouri Kansas City School of Medicine, Kansas City, MO, USA.,Nephrology, Children's Mercy Hospital, Kansas City, MO, USA
| | - Isabelle Thiffault
- Genomic Medicine Center, Children's Mercy Hospital, Kansas City, MO, USA.,University of Missouri Kansas City School of Medicine, Kansas City, MO, USA.,Department of Pathology and Laboratory Medicine, Children's Mercy Hospital, Kansas City, MO, USA
| | - Carol Saunders
- Genomic Medicine Center, Children's Mercy Hospital, Kansas City, MO, USA.,University of Missouri Kansas City School of Medicine, Kansas City, MO, USA.,Department of Pathology and Laboratory Medicine, Children's Mercy Hospital, Kansas City, MO, USA
| | - Tomi Pastinen
- Genomic Medicine Center, Children's Mercy Hospital, Kansas City, MO, USA.,University of Missouri Kansas City School of Medicine, Kansas City, MO, USA.,Pediatrics, Children's Mercy Hospital, Kansas City, MO, USA
| | - Kathy Goggin
- University of Missouri Kansas City School of Medicine, Kansas City, MO, USA.,Health Services and Outcomes Research, Children's Mercy Hospital, Kansas City, MO, USA.,University of Missouri Kansas City School of Pharmacy, Kansas City, MO, USA
| | - Emily Farrow
- Genomic Medicine Center, Children's Mercy Hospital, Kansas City, MO, USA.,University of Missouri Kansas City School of Medicine, Kansas City, MO, USA.,Pediatrics, Children's Mercy Hospital, Kansas City, MO, USA
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30
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Exome and genome sequencing for pediatric patients with congenital anomalies or intellectual disability: an evidence-based clinical guideline of the American College of Medical Genetics and Genomics (ACMG). Genet Med 2021; 23:2029-2037. [PMID: 34211152 DOI: 10.1038/s41436-021-01242-6] [Citation(s) in RCA: 205] [Impact Index Per Article: 68.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2021] [Revised: 05/26/2021] [Accepted: 05/26/2021] [Indexed: 01/22/2023] Open
Abstract
PURPOSE To develop an evidence-based clinical practice guideline for the use of exome and genome sequencing (ES/GS) in the care of pediatric patients with one or more congenital anomalies (CA) with onset prior to age 1 year or developmental delay (DD) or intellectual disability (ID) with onset prior to age 18 years. METHODS The Pediatric Exome/Genome Sequencing Evidence-Based Guideline Work Group (n = 10) used the Grading of Recommendations Assessment, Development and Evaluation (GRADE) evidence to decision (EtD) framework based on the recent American College of Medical Genetics and Genomics (ACMG) systematic review, and an Ontario Health Technology Assessment to develop and present evidence summaries and health-care recommendations. The document underwent extensive internal and external peer review, and public comment, before approval by the ACMG Board of Directors. RESULTS The literature supports the clinical utility and desirable effects of ES/GS on active and long-term clinical management of patients with CA/DD/ID, and on family-focused and reproductive outcomes with relatively few harms. Compared with standard genetic testing, ES/GS has a higher diagnostic yield and may be more cost-effective when ordered early in the diagnostic evaluation. CONCLUSION We strongly recommend that ES/GS be considered as a first- or second-tier test for patients with CA/DD/ID.
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Molina-Ramírez LP, Kyle C, Ellingford JM, Wright R, Taylor A, Bhaskar SS, Campbell C, Jackson H, Fairclough A, Rousseau A, Burghel GJ, Dutton L, Banka S, Briggs TA, Clayton-Smith J, Douzgou S, Jones EA, Kingston HM, Kerr B, Ealing J, Somarathi S, Chandler KE, Stuart HM, Burkitt-Wright EM, Newman WG, Bruce IA, Black GC, Gokhale D. Personalised virtual gene panels reduce interpretation workload and maintain diagnostic rates of proband-only clinical exome sequencing for rare disorders. J Med Genet 2021; 59:393-398. [PMID: 33879512 PMCID: PMC8961756 DOI: 10.1136/jmedgenet-2020-107303] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2020] [Revised: 01/17/2021] [Accepted: 02/14/2021] [Indexed: 01/20/2023]
Abstract
Purpose The increased adoption of genomic strategies in the clinic makes it imperative for diagnostic laboratories to improve the efficiency of variant interpretation. Clinical exome sequencing (CES) is becoming a valuable diagnostic tool, capable of meeting the diagnostic demand imposed by the vast array of different rare monogenic disorders. We have assessed a clinician-led and phenotype-based approach for virtual gene panel generation for analysis of targeted CES in patients with rare disease in a single institution. Methods Retrospective survey of 400 consecutive cases presumed by clinicians to have rare monogenic disorders, referred on singleton basis for targeted CES. We evaluated diagnostic yield and variant workload to characterise the usefulness of a clinician-led approach for generation of virtual gene panels that can incorporate up to three different phenotype-driven gene selection methods. Results Abnormalities of the nervous system (54.5%), including intellectual disability, head and neck (19%), skeletal system (16%), ear (15%) and eye (15%) were the most common clinical features reported in referrals. Combined phenotype-driven strategies for virtual gene panel generation were used in 57% of cases. On average, 7.3 variants (median=5) per case were retained for clinical interpretation. The overall diagnostic rate of proband-only CES using personalised phenotype-driven virtual gene panels was 24%. Conclusions Our results show that personalised virtual gene panels are a cost-effective approach for variant analysis of CES, maintaining diagnostic yield and optimising the use of resources for clinical genomic sequencing in the clinic.
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Affiliation(s)
- Leslie Patricia Molina-Ramírez
- Division of Evolution and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK.,North West Genomic Laboratory Hub, Manchester Centre for Genomic Medicine, Manchester University NHS Foundation Trust, Manchester, Greater Manchester, UK
| | - Claire Kyle
- North West Genomic Laboratory Hub, Manchester Centre for Genomic Medicine, Manchester University NHS Foundation Trust, Manchester, Greater Manchester, UK
| | - Jamie M Ellingford
- Division of Evolution and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK.,North West Genomic Laboratory Hub, Manchester Centre for Genomic Medicine, Manchester University NHS Foundation Trust, Manchester, Greater Manchester, UK
| | - Ronnie Wright
- North West Genomic Laboratory Hub, Manchester Centre for Genomic Medicine, Manchester University NHS Foundation Trust, Manchester, Greater Manchester, UK
| | - Algy Taylor
- North West Genomic Laboratory Hub, Manchester Centre for Genomic Medicine, Manchester University NHS Foundation Trust, Manchester, Greater Manchester, UK
| | - Sanjeev S Bhaskar
- North West Genomic Laboratory Hub, Manchester Centre for Genomic Medicine, Manchester University NHS Foundation Trust, Manchester, Greater Manchester, UK
| | - Christopher Campbell
- North West Genomic Laboratory Hub, Manchester Centre for Genomic Medicine, Manchester University NHS Foundation Trust, Manchester, Greater Manchester, UK
| | - Harriet Jackson
- North West Genomic Laboratory Hub, Manchester Centre for Genomic Medicine, Manchester University NHS Foundation Trust, Manchester, Greater Manchester, UK
| | - Adele Fairclough
- North West Genomic Laboratory Hub, Manchester Centre for Genomic Medicine, Manchester University NHS Foundation Trust, Manchester, Greater Manchester, UK
| | - Abigail Rousseau
- North West Genomic Laboratory Hub, Manchester Centre for Genomic Medicine, Manchester University NHS Foundation Trust, Manchester, Greater Manchester, UK
| | - George J Burghel
- North West Genomic Laboratory Hub, Manchester Centre for Genomic Medicine, Manchester University NHS Foundation Trust, Manchester, Greater Manchester, UK
| | - Laura Dutton
- North West Genomic Laboratory Hub, Manchester Centre for Genomic Medicine, Manchester University NHS Foundation Trust, Manchester, Greater Manchester, UK
| | - Siddharth Banka
- Division of Evolution and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK.,North West Genomic Laboratory Hub, Manchester Centre for Genomic Medicine, Manchester University NHS Foundation Trust, Manchester, Greater Manchester, UK
| | - Tracy A Briggs
- Division of Evolution and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK.,North West Genomic Laboratory Hub, Manchester Centre for Genomic Medicine, Manchester University NHS Foundation Trust, Manchester, Greater Manchester, UK
| | - Jill Clayton-Smith
- Division of Evolution and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK.,North West Genomic Laboratory Hub, Manchester Centre for Genomic Medicine, Manchester University NHS Foundation Trust, Manchester, Greater Manchester, UK
| | - Sofia Douzgou
- Division of Evolution and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK.,North West Genomic Laboratory Hub, Manchester Centre for Genomic Medicine, Manchester University NHS Foundation Trust, Manchester, Greater Manchester, UK
| | - Elizabeth A Jones
- Division of Evolution and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK.,Manchester Centre for Genomic Medicine, Manchester University NHS Foundation Trust, Manchester, UK
| | - Helen M Kingston
- North West Genomic Laboratory Hub, Manchester Centre for Genomic Medicine, Manchester University NHS Foundation Trust, Manchester, Greater Manchester, UK
| | - Bronwyn Kerr
- North West Genomic Laboratory Hub, Manchester Centre for Genomic Medicine, Manchester University NHS Foundation Trust, Manchester, Greater Manchester, UK
| | - John Ealing
- Manchester Centre for Genomic Medicine, Manchester University NHS Foundation Trust, Manchester, UK.,Department of Neurology, Salford Royal NHS Foundation Trust, Salford, Salford, UK
| | - Suresh Somarathi
- North West Genomic Laboratory Hub, Manchester Centre for Genomic Medicine, Manchester University NHS Foundation Trust, Manchester, Greater Manchester, UK
| | - Kate E Chandler
- Division of Evolution and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK.,North West Genomic Laboratory Hub, Manchester Centre for Genomic Medicine, Manchester University NHS Foundation Trust, Manchester, Greater Manchester, UK
| | - Helen M Stuart
- Division of Evolution and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK.,North West Genomic Laboratory Hub, Manchester Centre for Genomic Medicine, Manchester University NHS Foundation Trust, Manchester, Greater Manchester, UK
| | - Emma Mm Burkitt-Wright
- Division of Evolution and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK.,North West Genomic Laboratory Hub, Manchester Centre for Genomic Medicine, Manchester University NHS Foundation Trust, Manchester, Greater Manchester, UK
| | - William G Newman
- Division of Evolution and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK.,North West Genomic Laboratory Hub, Manchester Centre for Genomic Medicine, Manchester University NHS Foundation Trust, Manchester, Greater Manchester, UK
| | - Iain A Bruce
- Division of Infection, Immunity and Respiratory Medicine, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK.,Paediatric ENT Department, Royal Manchester Children's Hospital, Manchester University NHS Foundation Trust, Manchester, UK
| | - Graeme C Black
- Division of Evolution and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK .,North West Genomic Laboratory Hub, Manchester Centre for Genomic Medicine, Manchester University NHS Foundation Trust, Manchester, Greater Manchester, UK
| | - David Gokhale
- North West Genomic Laboratory Hub, Manchester Centre for Genomic Medicine, Manchester University NHS Foundation Trust, Manchester, Greater Manchester, UK
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Barp A, Mosca L, Sansone VA. Facilitations and Hurdles of Genetic Testing in Neuromuscular Disorders. Diagnostics (Basel) 2021; 11:diagnostics11040701. [PMID: 33919863 PMCID: PMC8070835 DOI: 10.3390/diagnostics11040701] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2021] [Revised: 04/11/2021] [Accepted: 04/12/2021] [Indexed: 12/11/2022] Open
Abstract
Neuromuscular disorders (NMDs) comprise a heterogeneous group of disorders that affect about one in every thousand individuals worldwide. The vast majority of NMDs has a genetic cause, with about 600 genes already identified. Application of genetic testing in NMDs can be useful for several reasons: correct diagnostic definition of a proband, extensive familial counselling to identify subjects at risk, and prenatal diagnosis to prevent the recurrence of the disease; furthermore, identification of specific genetic mutations still remains mandatory in some cases for clinical trial enrollment where new gene therapies are now approaching. Even though genetic analysis is catching on in the neuromuscular field, pitfalls and hurdles still remain and they should be taken into account by clinicians, as for example the use of next generation sequencing (NGS) where many single nucleotide variants of “unknown significance” can emerge, complicating the correct interpretation of genotype-phenotype relationship. Finally, when all efforts in terms of molecular analysis have been carried on, a portion of patients affected by NMDs still remain “not genetically defined”. In the present review we analyze the evolution of genetic techniques, from Sanger sequencing to NGS, and we discuss “facilitations and hurdles” of genetic testing which must always be balanced by clinicians, in order to ensure a correct diagnostic definition, but taking always into account the benefit that the patient could obtain especially in terms of “therapeutic offer”.
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Affiliation(s)
- Andrea Barp
- The NEMO Clinical Center in Milan, Neurorehabilitation Unit, University of Milan, Piazza Ospedale Maggiore 3, 20162 Milano, Italy;
- Correspondence:
| | - Lorena Mosca
- Medical Genetics Unit, ASST Grande Ospedale Metropolitano Niguarda, Piazza Ospedale Maggiore 3, 20162 Milano, Italy;
| | - Valeria Ada Sansone
- The NEMO Clinical Center in Milan, Neurorehabilitation Unit, University of Milan, Piazza Ospedale Maggiore 3, 20162 Milano, Italy;
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33
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Abstract
Neuromuscular disorders (NMDs) comprise a heterogeneous group of disorders that affect about one in every thousand individuals worldwide. The vast majority of NMDs has a genetic cause, with about 600 genes already identified. Application of genetic testing in NMDs can be useful for several reasons: correct diagnostic definition of a proband, extensive familial counselling to identify subjects at risk, and prenatal diagnosis to prevent the recurrence of the disease; furthermore, identification of specific genetic mutations still remains mandatory in some cases for clinical trial enrollment where new gene therapies are now approaching. Even though genetic analysis is catching on in the neuromuscular field, pitfalls and hurdles still remain and they should be taken into account by clinicians, as for example the use of next generation sequencing (NGS) where many single nucleotide variants of "unknown significance" can emerge, complicating the correct interpretation of genotype-phenotype relationship. Finally, when all efforts in terms of molecular analysis have been carried on, a portion of patients affected by NMDs still remain "not genetically defined". In the present review we analyze the evolution of genetic techniques, from Sanger sequencing to NGS, and we discuss "facilitations and hurdles" of genetic testing which must always be balanced by clinicians, in order to ensure a correct diagnostic definition, but taking always into account the benefit that the patient could obtain especially in terms of "therapeutic offer".
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Affiliation(s)
- Andrea Barp
- The NEMO Clinical Center in Milan, Neurorehabilitation Unit, University of Milan, Piazza Ospedale Maggiore 3, 20162 Milano, Italy
| | - Lorena Mosca
- Medical Genetics Unit, ASST Grande Ospedale Metropolitano Niguarda, Piazza Ospedale Maggiore 3, 20162 Milano, Italy
| | - Valeria Ada Sansone
- The NEMO Clinical Center in Milan, Neurorehabilitation Unit, University of Milan, Piazza Ospedale Maggiore 3, 20162 Milano, Italy
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Abstract
Neurodevelopmental disorders are the most prevalent chronic medical conditions encountered in pediatric primary care. In addition to identifying appropriate descriptive diagnoses and guiding families to evidence-based treatments and supports, comprehensive care for individuals with neurodevelopmental disorders includes a search for an underlying etiologic diagnosis, primarily through a genetic evaluation. Identification of an underlying genetic etiology can inform prognosis, clarify recurrence risk, shape clinical management, and direct patients and families to condition-specific resources and supports. Here we review the utility of genetic testing in patients with neurodevelopmental disorders and describe the three major testing modalities and their yields - chromosomal microarray, exome sequencing (with/without copy number variant calling), and FMR1 CGG repeat analysis for fragile X syndrome. Given the diagnostic yield of genetic testing and the potential for clinical and personal utility, there is consensus that genetic testing should be offered to all patients with global developmental delay, intellectual disability, and/or autism spectrum disorder. Despite this recommendation, data suggest that a minority of children with autism spectrum disorder and intellectual disability have undergone genetic testing. To address this gap in care, we describe a structured but flexible approach to facilitate integration of genetic testing into clinical practice across pediatric specialties and discuss future considerations for genetic testing in neurodevelopmental disorders to prepare pediatric providers to care for patients with such diagnoses today and tomorrow.
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Affiliation(s)
- Juliann M. Savatt
- Autism & Developmental Medicine Institute, Geisinger, Danville, PA, United States
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35
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Schoch K, Esteves C, Bican A, Spillmann R, Cope H, McConkie-Rosell A, Walley N, Fernandez L, Kohler JN, Bonner D, Reuter C, Stong N, Mulvihill JJ, Novacic D, Wolfe L, Abdelbaki A, Toro C, Tifft C, Malicdan M, Gahl W, Liu P, Newman J, Goldstein DB, Hom J, Sampson J, Wheeler MT, Cogan J, Bernstein JA, Adams DR, McCray AT, Shashi V. Clinical sites of the Undiagnosed Diseases Network: unique contributions to genomic medicine and science. Genet Med 2021; 23:259-271. [PMID: 33093671 PMCID: PMC7867619 DOI: 10.1038/s41436-020-00984-z] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2020] [Revised: 09/17/2020] [Accepted: 09/18/2020] [Indexed: 11/08/2022] Open
Abstract
PURPOSE The NIH Undiagnosed Diseases Network (UDN) evaluates participants with disorders that have defied diagnosis, applying personalized clinical and genomic evaluations and innovative research. The clinical sites of the UDN are essential to advancing the UDN mission; this study assesses their contributions relative to standard clinical practices. METHODS We analyzed retrospective data from four UDN clinical sites, from July 2015 to September 2019, for diagnoses, new disease gene discoveries and the underlying investigative methods. RESULTS Of 791 evaluated individuals, 231 received 240 diagnoses and 17 new disease-gene associations were recognized. Straightforward diagnoses on UDN exome and genome sequencing occurred in 35% (84/240). We considered these tractable in standard clinical practice, although genome sequencing is not yet widely available clinically. The majority (156/240, 65%) required additional UDN-driven investigations, including 90 diagnoses that occurred after prior nondiagnostic exome sequencing and 45 diagnoses (19%) that were nongenetic. The UDN-driven investigations included complementary/supplementary phenotyping, innovative analyses of genomic variants, and collaborative science for functional assays and animal modeling. CONCLUSION Investigations driven by the clinical sites identified diagnostic and research paradigms that surpass standard diagnostic processes. The new diagnoses, disease gene discoveries, and delineation of novel disorders represent a model for genomic medicine and science.
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Affiliation(s)
- Kelly Schoch
- Division of Medical Genetics, Department of Pediatrics, Duke Health, Durham, NC, USA
| | - Cecilia Esteves
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Anna Bican
- Vanderbilt Center for Undiagnosed Disease, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Pediatrics, Division of Medical Genetics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Rebecca Spillmann
- Division of Medical Genetics, Department of Pediatrics, Duke Health, Durham, NC, USA
| | - Heidi Cope
- Division of Medical Genetics, Department of Pediatrics, Duke Health, Durham, NC, USA
| | - Allyn McConkie-Rosell
- Division of Medical Genetics, Department of Pediatrics, Duke Health, Durham, NC, USA
| | - Nicole Walley
- Division of Medical Genetics, Department of Pediatrics, Duke Health, Durham, NC, USA
| | - Liliana Fernandez
- Stanford Center for Undiagnosed Diseases, Stanford University, Stanford, CA, USA
| | - Jennefer N Kohler
- Stanford Center for Undiagnosed Diseases, Stanford University, Stanford, CA, USA
| | - Devon Bonner
- Stanford Center for Undiagnosed Diseases, Stanford University, Stanford, CA, USA
| | - Chloe Reuter
- Stanford Center for Undiagnosed Diseases, Stanford University, Stanford, CA, USA
| | - Nicholas Stong
- Institute for Genomic Medicine, Columbia University Medical Center, New York, NY, USA
| | - John J Mulvihill
- Division of Genomic Medicine, National Human Genome Research Institute, Bethesda, MD, USA
- Undiagnosed Diseases Program, Common Fund, NIH Office of the Director, NIH, Bethesda, MD, USA
| | - Donna Novacic
- Undiagnosed Diseases Program, Common Fund, NIH Office of the Director, NIH, Bethesda, MD, USA
| | - Lynne Wolfe
- Undiagnosed Diseases Program, Common Fund, NIH Office of the Director, NIH, Bethesda, MD, USA
| | - Ayat Abdelbaki
- Undiagnosed Diseases Program, Common Fund, NIH Office of the Director, NIH, Bethesda, MD, USA
| | - Camilo Toro
- Undiagnosed Diseases Program, Common Fund, NIH Office of the Director, NIH, Bethesda, MD, USA
| | - Cyndi Tifft
- Undiagnosed Diseases Program, Common Fund, NIH Office of the Director, NIH, Bethesda, MD, USA
- Office of the Clinical Director, NHGRI, NIH, Bethesda, MD, USA
| | - May Malicdan
- Undiagnosed Diseases Program, Common Fund, NIH Office of the Director, NIH, Bethesda, MD, USA
- Medical Genetics Branch, NHGRI, NIH, Bethesda, MD, USA
| | - William Gahl
- Undiagnosed Diseases Program, Common Fund, NIH Office of the Director, NIH, Bethesda, MD, USA
- Medical Genetics Branch, NHGRI, NIH, Bethesda, MD, USA
| | - Pengfei Liu
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
- Baylor Genetics, Houston, TX, USA
| | - John Newman
- Vanderbilt Center for Undiagnosed Disease, Vanderbilt University Medical Center, Nashville, TN, USA
| | - David B Goldstein
- Institute for Genomic Medicine, Columbia University Medical Center, New York, NY, USA
| | - Jason Hom
- Stanford Center for Undiagnosed Diseases, Stanford University, Stanford, CA, USA
- Department of Medicine, Stanford School of Medicine, Stanford, CA, USA
| | - Jacinda Sampson
- Stanford Center for Undiagnosed Diseases, Stanford University, Stanford, CA, USA
- Department of Neurology, Stanford School of Medicine, Stanford, CA, USA
| | - Matthew T Wheeler
- Stanford Center for Undiagnosed Diseases, Stanford University, Stanford, CA, USA
- Department of Medicine, Stanford School of Medicine, Stanford, CA, USA
| | - Joy Cogan
- Vanderbilt Center for Undiagnosed Disease, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Pediatrics, Division of Medical Genetics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Jonathan A Bernstein
- Stanford Center for Undiagnosed Diseases, Stanford University, Stanford, CA, USA
- Department of Pediatrics, Stanford School of Medicine, Stanford, CA, USA
| | - David R Adams
- Undiagnosed Diseases Program, Common Fund, NIH Office of the Director, NIH, Bethesda, MD, USA
- Office of the Clinical Director, NHGRI, NIH, Bethesda, MD, USA
| | - Alexa T McCray
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Vandana Shashi
- Division of Medical Genetics, Department of Pediatrics, Duke Health, Durham, NC, USA.
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El Achkar CM, Harrer M, Smith L, Kelly M, Iqbal S, Maljevic S, Niturad CE, Vissers LELM, Poduri A, Yang E, Lal D, Lerche H, Møller RS, Olson HE. Characterization of the GABRB2-Associated Neurodevelopmental Disorders. Ann Neurol 2020; 89:573-586. [PMID: 33325057 DOI: 10.1002/ana.25985] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2020] [Revised: 11/30/2020] [Accepted: 12/01/2020] [Indexed: 11/09/2022]
Abstract
OBJECTIVE We aimed to characterize the phenotypic spectrum and functional consequences associated with variants in the gene GABRB2, coding for the γ-aminobutyric acid type A (GABAA ) receptor subunit β2. METHODS We recruited and systematically evaluated 25 individuals with variants in GABRB2, 17 of whom are newly described and 8 previously reported with additional clinical data. Functional analysis was performed using a Xenopus laevis oocyte model system. RESULTS Our cohort of 25 individuals from 22 families with variants in GABRB2 demonstrated a range of epilepsy phenotypes from genetic generalized epilepsy to developmental and epileptic encephalopathy. Fifty-eight percent of individuals had pharmacoresistant epilepsy; response to medications targeting the GABAergic pathway was inconsistent. Developmental disability (present in 84%) ranged from mild intellectual disability to severe global disability; movement disorders (present in 44%) included choreoathetosis, dystonia, and ataxia. Disease-associated variants cluster in the extracellular N-terminus and transmembrane domains 1-3, with more severe phenotypes seen in association with variants in transmembrane domains 1 and 2 and the allosteric binding site between transmembrane domains 2 and 3. Functional analysis of 4 variants in transmembrane domains 1 or 2 (p.Ile246Thr, p.Pro252Leu, p.Ile288Ser, p.Val282Ala) revealed strongly reduced amplitudes of GABA-evoked anionic currents. INTERPRETATION GABRB2-related epilepsy ranges broadly in severity from genetic generalized epilepsy to developmental and epileptic encephalopathies. Developmental disability and movement disorder are key features. The phenotypic spectrum is comparable to other GABAA receptor-encoding genes. Phenotypic severity varies by protein domain. Experimental evidence supports loss of GABAergic inhibition as the mechanism underlying GABRB2-associated neurodevelopmental disorders. ANN NEUROL 2021;89:573-586.
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Affiliation(s)
- Christelle M El Achkar
- Division of Epilepsy and Clinical Neurophysiology and Epilepsy Genetics Program, Department of Neurology, Boston Children's Hospital, Boston, MA.,Department of Neurology, Harvard Medical School, Boston, MA
| | - Merle Harrer
- Department of Neurology and Epileptology, Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany
| | - Lacey Smith
- Division of Epilepsy and Clinical Neurophysiology and Epilepsy Genetics Program, Department of Neurology, Boston Children's Hospital, Boston, MA
| | - McKenna Kelly
- Division of Epilepsy and Clinical Neurophysiology and Epilepsy Genetics Program, Department of Neurology, Boston Children's Hospital, Boston, MA.,Dartmouth Geisel School of Medicine, Hanover, NH
| | - Sumaiya Iqbal
- Center for Development of Therapeutics and Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA
| | - Snezana Maljevic
- Department of Neurology and Epileptology, Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany.,Florey Institute of Neuroscience and Mental Health, University of Melbourne, Melbourne, Australia
| | - Cristina E Niturad
- Department of Neurology and Epileptology, Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany
| | - Lisenka E L M Vissers
- Department of Human Genetics, Donders Institute for Brain, Cognition, and Behavior, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Annapurna Poduri
- Division of Epilepsy and Clinical Neurophysiology and Epilepsy Genetics Program, Department of Neurology, Boston Children's Hospital, Boston, MA.,Department of Neurology, Harvard Medical School, Boston, MA
| | - Edward Yang
- Department of Radiology, Boston Children's Hospital, Boston, MA
| | - Dennis Lal
- Cleveland Clinic Genomic Medicine Institute and Neurological Institute, Cleveland, OH
| | - Holger Lerche
- Department of Neurology and Epileptology, Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany
| | - Rikke S Møller
- Department of Epilepsy Genetics and Personalized Treatment, Danish Epilepsy Center Filadelfia, Dianalund, Denmark.,Department of Regional Health Research, University of Southern Denmark, Odense, Denmark
| | - Heather E Olson
- Division of Epilepsy and Clinical Neurophysiology and Epilepsy Genetics Program, Department of Neurology, Boston Children's Hospital, Boston, MA.,Department of Neurology, Harvard Medical School, Boston, MA
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Lundquist AL, Pelletier RC, Leonard CE, Williams WW, Armstrong KA, Rehm HL, Rhee EP. From Theory to Reality: Establishing a Successful Kidney Genetics Clinic in the Outpatient Setting. KIDNEY360 2020; 1:1099-1106. [PMID: 35368791 DOI: 10.34067/kid.0004262020] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/10/2020] [Accepted: 08/12/2020] [Indexed: 02/06/2023]
Abstract
Background Genetic testing in nephrology is increasingly described in the literature and several groups have suggested significant clinical benefit. However, studies to date have described experience from established genetic testing centers or from externally funded research programs. Methods We established a de novo kidney genetics clinic within an academic adult general nephrology practice. Key features of this effort included a pipeline for internal referrals, flexible scheduling, close coordination between the nephrologist and a genetic counselor, and utilization of commercial panel-based testing. Over the first year, we examined the outcomes of genetic testing, the time to return of genetic testing, and out-of-pocket cost to patients. Results Thirty patients were referred and 23 were evaluated over the course of five clinic sessions. Nineteen patients underwent genetic testing with new diagnoses in nine patients (47%), inconclusive results in three patients (16%), and clearance for kidney donation in two patients (11%). On average, return of genetic results occurred 55 days (range 9-174 days) from the day of sample submission and the average out-of-pocket cost to patients was $155 (range $0-$1623). Conclusions We established a kidney genetics clinic, without a pre-existing genetics infrastructure or dedicated research funding, that identified a new diagnosis in approximately 50% of patients tested. This study provides a clinical practice model for successfully incorporating genetic testing into ambulatory nephrology care with minimal capital investment and limited financial effect on patients.
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Affiliation(s)
- Andrew L Lundquist
- Division of Nephrology, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts
| | - Renee C Pelletier
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, Massachusetts
| | - Courtney E Leonard
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, Massachusetts
| | - Winfred W Williams
- Division of Nephrology, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts
| | - Katrina A Armstrong
- Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts
| | - Heidi L Rehm
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, Massachusetts.,Medical and Population Genetics, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, Massachusetts.,Department of Pathology, Harvard Medical School, Harvard, University, Boston, Massachusetts
| | - Eugene P Rhee
- Division of Nephrology, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts
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38
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Li C, Vandersluis S, Holubowich C, Ungar WJ, Goh ES, Boycott KM, Sikich N, Dhalla I, Ng V. Cost-effectiveness of genome-wide sequencing for unexplained developmental disabilities and multiple congenital anomalies. Genet Med 2020; 23:451-460. [PMID: 33110268 DOI: 10.1038/s41436-020-01012-w] [Citation(s) in RCA: 32] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2020] [Revised: 10/06/2020] [Accepted: 10/07/2020] [Indexed: 12/22/2022] Open
Abstract
PURPOSE Genetic testing is routine practice for individuals with unexplained developmental disabilities and multiple congenital anomalies. However, current testing pathways can be costly and time consuming, and the diagnostic yield low. Genome-wide sequencing, including exome sequencing (ES) and genome sequencing (GS), can improve diagnosis, but at a higher cost. This study aimed to assess the cost-effectiveness of genome-wide sequencing in Ontario, Canada. METHODS A cost-effectiveness analysis was conducted using a discrete event simulation from a public payer perspective. Six strategies involving ES or GS were compared. Outcomes reported were direct medical costs, number of molecular diagnoses, number of positive findings, and number of active treatment changes. RESULTS If ES was used as a second-tier test (after the current first-tier, chromosomal microarray, fails to provide a diagnosis), it would be less costly and more effective than standard testing (CAN$6357 [95% CI: 6179-6520] vs. CAN$8783 per patient [95% CI: 2309-31,123]). If ES was used after standard testing, it would cost an additional CAN$15,228 to identify the genetic diagnosis for one additional patient compared with standard testing. The results remained robust when parameters and assumptions were varied. CONCLUSION ES would likely be cost-saving if used earlier in the diagnostic pathway.
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Affiliation(s)
- Chunmei Li
- Ontario Health (Quality), Toronto, ON, Canada.
| | | | | | - Wendy J Ungar
- Program of Child Health Evaluative Sciences, The Hospital for Sick Children Research Institute, Toronto, ON, Canada.,Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, ON, Canada
| | - Elaine S Goh
- Laboratory Medicine and Genetics, Trillium Health Partners, Mississauga, ON, Canada
| | - Kym M Boycott
- Children's Hospital of Eastern Ontario Research Institute, University of Ottawa, Ottawa, ON, Canada
| | | | - Irfan Dhalla
- Ontario Health (Quality), Toronto, ON, Canada.,Unity Health Toronto, Toronto, ON, Canada
| | - Vivian Ng
- Ontario Health (Quality), Toronto, ON, Canada
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39
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Beyzaei Z, Geramizadeh B, Karimzadeh S. Diagnosis of hepatic glycogen storage disease patients with overlapping clinical symptoms by massively parallel sequencing: a systematic review of literature. Orphanet J Rare Dis 2020; 15:286. [PMID: 33054851 PMCID: PMC7557034 DOI: 10.1186/s13023-020-01573-8] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2020] [Accepted: 10/05/2020] [Indexed: 12/17/2022] Open
Abstract
Background Glycogen storage diseases (GSDs) with liver involvement are complex disorders with similar manifestations. Currently, the main diagnostic methods such as tissue diagnosis, either histopathology or enzyme assay, are invasive. Meanwhile, GSDs are diseases with significant genetic heterogeneity, and gene-sequencing methods can be more useful. This systematic review aims to review the literature to assess the value of massively parallel sequencing in the diagnosis of GSDs on patients with previously undiagnosed hepatic involvement. Methods Relevant studies identified in the MEDLINE/PubMed, EMBASE, Cochrane Library, Scopus, and Web of Science Core Collection databases up to July 2019 with no time and language restrictions. Publications were included in the review if they analyzed GSDs with hepatic involvement (GSD I, GSD III, GSD IV, GSD VI, GSD IX), using targeted gene sequencing (TGS) or exome sequencing (ES). Results Eleven studies were included in this systematic review. ES demonstrated a 93% diagnostic yield. These methods correctly distinguished all types of pathogenic variants. The diagnostic yield of the TGS method was around 79.7%. Conclusions According to our results, TGS analysis can be considered as the first-line diagnostic method with valuable results and ES can be used to diagnose complex cases of GSD with liver involvement. Overall, these molecular methods are considered as accurate diagnostic tools, which expedite correct diagnosis and treatment with significant cost-effectiveness by reducing unnecessary and inaccurate tests. PROSPERO registration CRD42020139931. Registered 8 January 2020.
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Affiliation(s)
- Zahra Beyzaei
- Transplant Research Center, Shiraz University of Medical Sciences, Shiraz, Iran
| | - Bita Geramizadeh
- Transplant Research Center, Shiraz University of Medical Sciences, Shiraz, Iran. .,Department of Pathology, Shiraz University of Medical Sciences, Zand St., Shiraz, Iran.
| | - Sara Karimzadeh
- Shiraz Medical School Library, Shiraz University of Medical Sciences, Shiraz, Iran
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Li D, Shen KM, Zackai EH, Bhoj EJ. Clinical variability of TUBB-associated disorders: Diagnosis through reanalysis. Am J Med Genet A 2020; 182:3035-3039. [PMID: 33016642 DOI: 10.1002/ajmg.a.61897] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2020] [Revised: 09/14/2020] [Accepted: 09/14/2020] [Indexed: 11/06/2022]
Abstract
A range of clinical findings have been associated with heterozygous mutations in the Beta Tubulin (TUBB) gene, including microcephaly, structural brain abnormalities, intellectual disability, and skin creases. We report a 5-year-old male who presented for evaluation of cleft palate, cardiac defects, growth retardation, hemivertebrae causing scoliosis, and preauricular skin tags. Previous clinical exome sequencing of this patient was nondiagnostic, but reanalysis in the research setting identified a de novo missense c. 925C>G p.(Arg309Gly) mutation in TUBB. This mutation was not found in population allele frequency databases, and was classified to be likely pathogenic. This patient shares some phenotypic characteristics with previous reported patients of TUBB mutations of the two TUBB-related phenotypes: "Cortical dysplasia, complex, with other brain malformations 6" [MIM 615771] and "Circumferential Skin Creases Kunze type (CSC-KT)" [MIM 156610], but has no excess skin creases or structural brain anomalies. We also report previously undescribed features, including transposition of the great arteries and vertebral fusion, thus representing phenotype expansion of TUBB-associated disorders.
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Affiliation(s)
- Dong Li
- Center for Applied Genomics, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA
| | - Kaitlyn M Shen
- Center for Applied Genomics, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA
| | - Elaine H Zackai
- Division of Human Genetics, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA
| | - Elizabeth J Bhoj
- Center for Applied Genomics, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.,Division of Human Genetics, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA
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Yang Y, Xiangwei W, Zhang X, Xiao J, Chen J, Yang X, Jia T, Yang Z, Jiang Y, Zhang Y. Phenotypic spectrum of patients with GABRB2 variants: from mild febrile seizures to severe epileptic encephalopathy. Dev Med Child Neurol 2020; 62:1213-1220. [PMID: 32686847 DOI: 10.1111/dmcn.14614] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 05/26/2020] [Indexed: 12/19/2022]
Abstract
AIM To characterize the different phenotypes of GABRB2-related epilepsy and to establish a genotype-phenotype correlation. METHOD We used next-generation sequencing to identify GABRB2 variants in 15 patients. RESULTS Eleven GABRB2 variants were novel and 12 were de novo. The age at the onset of seizures ranged from 1 day to 26 months. Nine patients had multiple seizure types, including focal seizures, generalized tonic-clonic seizures, myoclonic seizures, epileptic spasms, and atonic seizures. Seizures were fever-sensitive in 13 out of the 15 patients. Eleven patients displayed developmental delay, while 11 had abnormal video electroencephalography. Abnormalities in the brain images included dysplasia of the frontal and temporal cortex, dysplasia of the corpus callosum, and delayed myelination in four patients. One patient was diagnosed with febrile seizures, three with febrile seizures plus, three with Dravet syndrome, three with West syndrome, one with Ohtahara syndrome, three with developmental delays and epilepsy, and one with non-specific early-onset epileptic encephalopathy. INTERPRETATION The most common phenotypes of patients with GABRB2 variants include early onset of seizure and fever sensitivity. Febrile seizures and febrile seizures plus are new phenotypes of GABRB2 variants. The phenotypic spectrum of GABRB2 variants ranges from mild febrile seizures to severe epileptic encephalopathy.
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Affiliation(s)
- Ying Yang
- Department of Pediatrics, Peking University First Hospital, Beijing, China
| | - Wenshu Xiangwei
- Department of Pediatrics, Peking University First Hospital, Beijing, China
| | - Xiaoli Zhang
- Department of Pediatrics, The Third Affiliated Hospital of Zheng Zhou University, Zhengzhou, China
| | - Jiangxi Xiao
- Department of Radiology, Peking University First Hospital, Beijing, China
| | - Jiaoyang Chen
- Department of Pediatrics, Peking University First Hospital, Beijing, China
| | - Xiaoling Yang
- Department of Pediatrics, Peking University First Hospital, Beijing, China
| | - Tianming Jia
- Department of Pediatrics, The Third Affiliated Hospital of Zheng Zhou University, Zhengzhou, China
| | - Zhixian Yang
- Department of Pediatrics, Peking University First Hospital, Beijing, China
| | - Yuwu Jiang
- Department of Pediatrics, Peking University First Hospital, Beijing, China
| | - Yuehua Zhang
- Department of Pediatrics, Peking University First Hospital, Beijing, China
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Affiliation(s)
- Jan M Friedman
- Department of Medical Genetics, University of British Columbia, Vancouver, British Columbia, Canada
| | | | - John C Carey
- Department of Pediatrics, University of Utah Health, Salt Lake City
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Michelson DJ, Clark RD. Optimizing Genetic Diagnosis of Neurodevelopmental Disorders in the Clinical Setting. Clin Lab Med 2020; 40:231-256. [PMID: 32718497 DOI: 10.1016/j.cll.2020.05.001] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/15/2023]
Abstract
Progress in medical genetics has changed the practice of medicine in general and child neurology in particular. A genetic diagnosis has become critically important in determining optimal management of many neurodevelopmental disorders, making genetic testing a routine consideration of patient care in outpatient and inpatient settings. Today's child neurologists should be familiar with various genetic testing modalities and their appropriate use. Molecular genetic testing of children with unexplained developmental delays and/or congenital anomalies has a 20% to 30% chance of identifying a causative etiology. Newer methods have made genetic testing more widely available and sensitive but also more likely to produce ambiguous results.
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Affiliation(s)
- David Joshua Michelson
- Division of Child Neurology, Department of Pediatrics, Loma Linda University School of Medicine, Coleman Pavilion Room A, 1175 Campus Street, Loma Linda, CA 92354, USA.
| | - Robin Dawn Clark
- Division of Medical Genetics, Department of Pediatrics, Loma Linda University School of Medicine, Coleman Pavilion Room A, 1175 Campus Street, Loma Linda, CA 92354, USA
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Yokoi T, Enomoto Y, Tsurusaki Y, Harada N, Saito T, Nagai JI, Naruto T, Kurosawa K. An efficient genetic test flow for multiple congenital anomalies and intellectual disability. Pediatr Int 2020; 62:556-561. [PMID: 31955471 DOI: 10.1111/ped.14159] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/07/2019] [Revised: 04/10/2019] [Accepted: 01/16/2020] [Indexed: 11/29/2022]
Abstract
BACKGROUND Genetic testing has enabled the diagnosis of multiple congenital anomalies and/or intellectual disabilities. However, because of the phenotypic variability in these disorders, selection of an appropriate genetic test can be difficult and complex. For clinical examination, particularly in clinical facilities, a simple and standardized system is needed. METHODS We compared microarray comparative genomic hybridization and clinical exome sequencing with regard to diagnostic yield, cost, and time required to reach a definitive diagnosis. After first performing G-banding for 200 patients with multiple congenital anomalies and/or intellectual disability, as a subsequent genetic test, microarray and clinical exome sequencing were compared with regard to diagnostic yield, cost, and time required. RESULTS There was no obvious difference in the diagnostic rate between the two methods; however, clinical exome sequencing was superior in terms of cost and time. In addition, clinical exome sequencing could sufficiently identify copy number variants, and even smaller copy number variants could be identified. CONCLUSIONS Clinical exome sequencing should be implemented earlier as a genetic test for undiagnosed patients with multiple congenital anomalies and/or intellectual disabilities. Our results can be used to establish inspection methods in clinical facilities.
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Affiliation(s)
- Takayuki Yokoi
- Division of Medical Genetics, Kanagawa Children's Medical Center, Yokohama, Japan.,Clinical Research Institute, Kanagawa Children's Medical Center, Yokohama, Japan
| | - Yumi Enomoto
- Department of Clinical Laboratory, Kanagawa Children's Medical Center, Yokohama, Japan
| | - Yoshinori Tsurusaki
- Department of Clinical Laboratory, Kanagawa Children's Medical Center, Yokohama, Japan
| | - Noriaki Harada
- Department of Pediatrics, Jikei University School of Medicine, Tokyo, Japan
| | - Toshiyuki Saito
- Department of Pediatrics, Jikei University School of Medicine, Tokyo, Japan
| | - Jun-Ichi Nagai
- Department of Pediatrics, Jikei University School of Medicine, Tokyo, Japan
| | - Takuya Naruto
- Department of Pediatrics and Developmental Biology, Tokyo Medical and Dental University Graduate School, Tokyo, Japan
| | - Kenji Kurosawa
- Division of Medical Genetics, Kanagawa Children's Medical Center, Yokohama, Japan
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Malinowski J, Miller DT, Demmer L, Gannon J, Pereira EM, Schroeder MC, Scheuner MT, Tsai ACH, Hickey SE, Shen J. Systematic evidence-based review: outcomes from exome and genome sequencing for pediatric patients with congenital anomalies or intellectual disability. Genet Med 2020; 22:986-1004. [PMID: 32203227 PMCID: PMC7222126 DOI: 10.1038/s41436-020-0771-z] [Citation(s) in RCA: 39] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2020] [Revised: 02/24/2020] [Accepted: 02/25/2020] [Indexed: 12/31/2022] Open
Abstract
Purpose Exome and genome sequencing (ES/GS) are performed frequently in patients with congenital anomalies, developmental delay, or intellectual disability (CA/DD/ID), but the impact of results from ES/GS on clinical management and patient outcomes is not well characterized. A systematic evidence review (SER) can support future evidence-based guideline development for use of ES/GS in this patient population. Methods We undertook an SER to identify primary literature from January 2007 to March 2019 describing health, clinical, reproductive, and psychosocial outcomes resulting from ES/GS in patients with CA/DD/ID. A narrative synthesis of results was performed. Results We retrieved 2654 publications for full-text review from 7178 articles. Only 167 articles met our inclusion criteria, and these were primarily case reports or small case series of fewer than 20 patients. The most frequently reported outcomes from ES/GS were changes to clinical management or reproductive decision-making. Two studies reported on the reduction of mortality or morbidity or impact on quality of life following ES/GS. Conclusion There is evidence that ES/GS for patients with CA/DD/ID informs clinical and reproductive decision-making, which could lead to improved outcomes for patients and their family members. Further research is needed to generate evidence regarding health outcomes to inform robust guidelines regarding ES/GS in the care of patients with CA/DD/ID.
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Affiliation(s)
| | - David T Miller
- Division of Genetics and Genomics, Boston Children's Hospital, Boston, MA, USA
| | - Laurie Demmer
- Atrium Health's Levine Children's Hospital, Charlotte, NC, USA
| | - Jennifer Gannon
- Division of Clinical Genetics, Children's Mercy Hospital, Kansas City, MO, USA.,Department of Pediatrics, University of Missouri, Kansas City, MO, USA
| | - Elaine Maria Pereira
- Division of Clinical Genetics, Department of Pediatrics, Columbia University Medical Center, New York, NY, USA
| | - Molly C Schroeder
- Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, MO, USA
| | - Maren T Scheuner
- Division of Medical Genetics, Department of Pediatrics and Division of Hematology-Oncology, Department of Medicine, University of California, San Francisco, CA, USA.,San Francisco VA Healthcare System, San Francisco, CA, USA
| | - Anne Chun-Hui Tsai
- Section of Clinical Genetics and Metabolism, Department of Pediatrics, University of Colorado, Aurora, CO, USA
| | - Scott E Hickey
- Department of Pediatrics, The Ohio State University College of Medicine, Columbus, OH, USA
| | - Jun Shen
- Department of Pathology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
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Genome-Wide Sequencing for Unexplained Developmental Disabilities or Multiple Congenital Anomalies: A Health Technology Assessment. ONTARIO HEALTH TECHNOLOGY ASSESSMENT SERIES 2020; 20:1-178. [PMID: 32194879 PMCID: PMC7080457] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
BACKGROUND People with unexplained developmental disabilities or multiple congenital anomalies might have had many biochemical, metabolic, and genetic tests for a period of years without receiving a diagnosis. A genetic diagnosis can help these people and their families better understand their condition and may help them to connect with others who have the same condition. Ontario Health (Quality), in collaboration with the Canadian Agency for Drugs and Technologies in Health (CADTH) conducted a health technology assessment about the use of genome-wide sequencing for patients with unexplained developmental disabilities or multiple congenital anomalies. Ontario Health (Quality) evaluated the effectiveness, cost-effectiveness, and budget impact of publicly funding genome-wide sequencing. We also conducted interviews with patients and examined the quantitative evidence of preferences and values literature to better understand the patient preferences and values for these tests. METHODS Ontario Health (Quality) performed a systematic literature search of the clinical evidence. We assessed the risk of bias of each included study using the Risk of Bias Assessment tool for Non-randomized Studies (RoBANS) and the quality of the body of evidence according to the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) Working Group criteria. We also performed a search of the quantitative evidence and undertook direct patient engagement to ascertain patient preferences for genetic testing for unexplained developmental disabilities or multiple congenital anomalies. CADTH performed a review of qualitative literature about patient perspectives and experiences, and a review of ethical issues.Ontario Health (Quality) performed an economic literature review of genome-wide sequencing in people with unexplained developmental disabilities or multiple congenital anomalies. Although we found eight published cost-effectiveness studies, none completely addressed our research question. Therefore, we conducted a primary economic evaluation using a discrete event simulation model. Owing to its high cost and early stage of clinical implementation, whole exome sequencing is primarily used for people who do not have a diagnosis from standard testing (referred to here as whole exome sequencing after standard testing; standard testing includes chromosomal microarray and targeted single-gene tests or gene panels). Therefore, in our first analysis, we evaluated the cost-effectiveness of whole exome sequencing after standard testing versus standard testing alone. In our second analysis, we explored the cost-effectiveness of whole exome and whole genome sequencing used at various times in the diagnostic pathway (e.g., first tier, second tier, after standard testing) versus standard testing. We also estimated the budget impact of publicly funding genome-wide sequencing in Ontario for the next 5 years. RESULTS Forty-four studies were included in the clinical evidence review. The overall diagnostic yield of genome-wide sequencing for people with unexplained development disability and multiple congenital anomalies was 37%, but we are very uncertain about this estimate (GRADE: Very Low). Compared with standard genetic testing of chromosomal microarray and targeted single-gene tests or gene panels, genome-wide sequencing could have a higher diagnostic yield (GRADE: Low). As well, for some who are tested, genome-wide sequencing prompts some changes to medications, treatments, and referrals to specialists (GRADE: Very Low).Whole exome sequencing after standard testing cost an additional $3,261 per patient but was more effective than standard testing alone. For every 1,000 persons tested, using whole exome sequencing after standard testing would lead to an additional 240 persons with a molecular diagnosis, 272 persons with any positive finding, and 46 persons with active treatment change (modifications to medications, procedures, or treatment). The resulting incremental cost-effectiveness ratios (ICERs) were $13,591 per additional molecular diagnosis. The use of genome-wide sequencing early in the diagnostic pathway (e.g., as a first- or second-tier test) can save on costs and improve diagnostic yields over those of standard testing. Results remained robust when parameters and assumptions were varied.Our budget impact analysis showed that, if whole exome sequencing after standard testing continues to be funded through Ontario's Out-of-Country Prior Approval Program, its budget impact would range from $4 to $5 million in years 1 to 5. If whole exome sequencing becomes publicly funded in Ontario (not through the Out-of-Country Prior Approval Program), the budget impact would be about $9 million yearly. We also found that using whole exome sequencing as a second-tier test would lead to cost savings ($3.4 million per 1,000 persons tested yearly).Participants demonstrated consistent motivations for and expectations of obtaining a diagnosis for unexplained developmental delay or congenital anomalies through genome-wide sequencing. Patients and families greatly value the support and information they receive through genetic counselling when considering genome-wide sequencing and learning of a diagnosis. CONCLUSIONS Genome-wide sequencing could have a higher diagnostic yield than standard testing for people with unexplained developmental disabilities or multiple congenital anomalies. Genome-wide sequencing can also prompt some changes to medications, treatments, and referrals to specialists for some people tested; however, we are very uncertain about this. Genome-wide sequencing could be a cost-effective strategy when used after standard testing to diagnose people with unexplained developmental disabilities or multiple congenital anomalies. It could also lead to cost savings when used earlier in the diagnostic pathway. Patients and families consistently noted a benefit from seeking a diagnosis through genetic testing.
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Biswas S, Medne L, Devkota B, Bedoukian E, Berrodin D, Izumi K, Deardorff MA, Tarpinian J, Leonard J, Pyle L, Gray C, Montgomery J, Williams T, Fortunato S, Weatherly J, McEldrew D, Kaur M, Raible SE, Wilkens A, Spinner NB, Skraban C, Krantz ID. A Centralized Approach for Practicing Genomic Medicine. Pediatrics 2020; 145:peds.2019-0855. [PMID: 32102930 PMCID: PMC9921770 DOI: 10.1542/peds.2019-0855] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 12/17/2019] [Indexed: 11/24/2022] Open
Abstract
Next-generation sequencing has revolutionized the diagnostic process, making broadscale testing affordable and applicable to almost all specialties; however, there remain several challenges in its widespread implementation. Barriers such as lack of infrastructure or expertise within local health systems and complex result interpretation or counseling make it harder for frontline clinicians to incorporate genomic testing in their existing workflow. The general population is more informed and interested in pursuing genetic testing, and this has been coupled with the increasing accessibility of direct-to-consumer testing. As a result of these changes, primary care physicians and nongenetics specialty providers find themselves seeing patients for whom genetic testing would be beneficial but managing genetic test results that are out of their scope of practice. In this report, we present a practical and centralized approach to providing genomic services through an independent, enterprise-wide clinical service model. We present 4 years of clinical experience, with >3400 referrals, toward designing and implementing the clinical service, maximizing resources, identifying barriers, and improving patient care. We provide a framework that can be implemented at other institutions to support and integrate genomic services across the enterprise.
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Affiliation(s)
- Sawona Biswas
- Roberts Individualized Medical Genetics Center, Division of Human Genetics, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania
| | - Livija Medne
- Roberts Individualized Medical Genetics Center, Division of Human Genetics, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania
| | - Batsal Devkota
- Roberts Individualized Medical Genetics Center, Division of Human Genetics, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania,Department of Biomedical and Health Informatics, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania
| | - Emma Bedoukian
- Roberts Individualized Medical Genetics Center, Division of Human Genetics, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania
| | - Donna Berrodin
- Roberts Individualized Medical Genetics Center, Division of Human Genetics, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania
| | - Kosuke Izumi
- Roberts Individualized Medical Genetics Center, Division of Human Genetics, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania,Departments of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Matthew A. Deardorff
- Roberts Individualized Medical Genetics Center, Division of Human Genetics, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania,Departments of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Jennifer Tarpinian
- Roberts Individualized Medical Genetics Center, Division of Human Genetics, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania
| | - Jacqueline Leonard
- Roberts Individualized Medical Genetics Center, Division of Human Genetics, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania
| | - Loiusa Pyle
- Roberts Individualized Medical Genetics Center, Division of Human Genetics, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania,Departments of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Christopher Gray
- Roberts Individualized Medical Genetics Center, Division of Human Genetics, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania
| | - Jasmine Montgomery
- Roberts Individualized Medical Genetics Center, Division of Human Genetics, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania
| | - Tyrah Williams
- Roberts Individualized Medical Genetics Center, Division of Human Genetics, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania
| | - Sierra Fortunato
- Roberts Individualized Medical Genetics Center, Division of Human Genetics, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania
| | - Jamila Weatherly
- Roberts Individualized Medical Genetics Center, Division of Human Genetics, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania
| | - Deborah McEldrew
- Roberts Individualized Medical Genetics Center, Division of Human Genetics, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania
| | - Manindar Kaur
- Roberts Individualized Medical Genetics Center, Division of Human Genetics, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania
| | - Sarah E. Raible
- Roberts Individualized Medical Genetics Center, Division of Human Genetics, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania
| | | | - Nancy B. Spinner
- Division of Genomic Diagnostics, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania,Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Cara Skraban
- Roberts Individualized Medical Genetics Center, Division of Human Genetics, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania,Departments of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Ian D. Krantz
- Roberts Individualized Medical Genetics Center, Division of Human Genetics, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania,Departments of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
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Ashrafi MR, Amanat M, Garshasbi M, Kameli R, Nilipour Y, Heidari M, Rezaei Z, Tavasoli AR. An update on clinical, pathological, diagnostic, and therapeutic perspectives of childhood leukodystrophies. Expert Rev Neurother 2019; 20:65-84. [PMID: 31829048 DOI: 10.1080/14737175.2020.1699060] [Citation(s) in RCA: 38] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Abstract
Introduction: Leukodystrophies constitute heterogenous group of rare heritable disorders primarily affecting the white matter of central nervous system. These conditions are often under-appreciated among physicians. The first clinical manifestations of leukodystrophies are often nonspecific and can occur in different ages from neonatal to late adulthood periods. The diagnosis is, therefore, challenging in most cases.Area covered: Herein, the authors discuss different aspects of leukodystrophies. The authors used MEDLINE, EMBASE, and GOOGLE SCHOLAR to provide an extensive update about epidemiology, classifications, pathology, clinical findings, diagnostic tools, and treatments of leukodystrophies. Comprehensive evaluation of clinical findings, brain magnetic resonance imaging, and genetic studies play the key roles in the early diagnosis of individuals with leukodystrophies. No cure is available for most heritable white matter disorders but symptomatic treatments can significantly decrease the burden of events. New genetic methods and stem cell transplantation are also under investigation to further increase the quality and duration of life in affected population.Expert opinion: The improvements in molecular diagnostic tools allow us to identify the meticulous underlying etiology of leukodystrophies and result in higher diagnostic rates, new classifications of leukodystrophies based on genetic information, and replacement of symptomatic managements with more specific targeted therapies.Abbreviations: 4H: Hypomyelination, hypogonadotropic hypogonadism and hypodontia; AAV: Adeno-associated virus; AD: autosomal dominant; AGS: Aicardi-Goutieres syndrome; ALSP: Axonal spheroids and pigmented glia; APGBD: Adult polyglucosan body disease; AR: autosomal recessive; ASO: Antisense oligonucleotide therapy; AxD: Alexander disease; BAEP: Brainstem auditory evoked potentials; CAA: Cerebral amyloid angiopathy; CADASIL: Cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy; CARASAL: Cathepsin A-related arteriopathy with strokes and leukoencephalopathy; CARASIL: Cerebral autosomal recessive arteriopathy with subcortical infarcts and leukoencephalopathy; CGH: Comparative genomic hybridization; ClC2: Chloride Ion Channel 2; CMTX: Charcot-Marie-Tooth disease, X-linked; CMV: Cytomegalovirus; CNS: central nervous system; CRISP/Cas9: Clustered regularly interspaced short palindromic repeat/CRISPR-associated 9; gRNA: Guide RNA; CTX: Cerebrotendinous xanthomatosis; DNA: Deoxyribonucleic acid; DSB: Double strand breaks; DTI: Diffusion tensor imaging; FLAIR: Fluid attenuated inversion recovery; GAN: Giant axonal neuropathy; H-ABC: Hypomyelination with atrophy of basal ganglia and cerebellum; HBSL: Hypomyelination with brainstem and spinal cord involvement and leg spasticity; HCC: Hypomyelination with congenital cataracts; HEMS: Hypomyelination of early myelinated structures; HMG CoA: Hydroxy methylglutaryl CoA; HSCT: Hematopoietic stem cell transplant; iPSC: Induced pluripotent stem cells; KSS: Kearns-Sayre syndrome; L-2-HGA: L-2-hydroxy glutaric aciduria; LBSL: Leukoencephalopathy with brainstem and spinal cord involvement and elevated lactate; LCC: Leukoencephalopathy with calcifications and cysts; LTBL: Leukoencephalopathy with thalamus and brainstem involvement and high lactate; MELAS: Mitochondrial myopathy, encephalopathy, lactic acidosis, and stroke; MERRF: Myoclonic epilepsy with ragged red fibers; MLC: Megalencephalic leukoencephalopathy with subcortical cysts; MLD: metachromatic leukodystrophy; MRI: magnetic resonance imaging; NCL: Neuronal ceroid lipofuscinosis; NGS: Next generation sequencing; ODDD: Oculodentodigital dysplasia; PCWH: Peripheral demyelinating neuropathy-central-dysmyelinating leukodystrophy-Waardenburg syndrome-Hirschprung disease; PMD: Pelizaeus-Merzbacher disease; PMDL: Pelizaeus-Merzbacher-like disease; RNA: Ribonucleic acid; TW: T-weighted; VWM: Vanishing white matter; WES: whole exome sequencing; WGS: whole genome sequencing; X-ALD: X-linked adrenoleukodystrophy; XLD: X-linked dominant; XLR: X-linked recessive.
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Affiliation(s)
- Mahmoud Reza Ashrafi
- Myelin Disorders Clinic, Department of Pediatric Neurology, Children's Medical Center, Pediatrics Center of Excellence, Tehran University of Medical Sciences, Tehran, Iran
| | - Man Amanat
- Faculty of Medicine, Students' Scientific Research Center, Tehran University of Medical Sciences, Tehran, Iran
| | - Masoud Garshasbi
- Department of Medical Genetics, Faculty of Medical Sciences, Tarbiat Modares University, Tehran, Iran
| | - Reyhaneh Kameli
- Myelin Disorders Clinic, Department of Pediatric Neurology, Children's Medical Center, Pediatrics Center of Excellence, Tehran University of Medical Sciences, Tehran, Iran
| | - Yalda Nilipour
- Pediatric pathology research center, research institute for children's health, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Morteza Heidari
- Myelin Disorders Clinic, Department of Pediatric Neurology, Children's Medical Center, Pediatrics Center of Excellence, Tehran University of Medical Sciences, Tehran, Iran
| | - Zahra Rezaei
- Myelin Disorders Clinic, Department of Pediatric Neurology, Children's Medical Center, Pediatrics Center of Excellence, Tehran University of Medical Sciences, Tehran, Iran
| | - Ali Reza Tavasoli
- Myelin Disorders Clinic, Department of Pediatric Neurology, Children's Medical Center, Pediatrics Center of Excellence, Tehran University of Medical Sciences, Tehran, Iran
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Mendelsohn BA. Imaging the Whole Genome in Diagnosing Neurologic Disorders. JAMA Neurol 2019; 76:1419-1420. [PMID: 31589280 DOI: 10.1001/jamaneurol.2019.3117] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]
Affiliation(s)
- Bryce A Mendelsohn
- Department of Genetics, Oakland Medical Center, Kaiser Permanente, Oakland, California
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Variant interpretation is a component of clinical practice among genetic counselors in multiple specialties. Genet Med 2019; 22:785-792. [PMID: 31754268 PMCID: PMC7127982 DOI: 10.1038/s41436-019-0705-9] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2019] [Accepted: 11/07/2019] [Indexed: 12/27/2022] Open
Abstract
PURPOSE Genomic testing is routinely utilized across clinical settings and can have significant variant interpretation challenges. The extent of genetic counselor (GC) engagement in variant interpretation in clinical practice is unknown. This study aimed to explore clinical GCs' variant interpretation practice across specialties, understand outcomes of this practice, and identify resource and educational needs. METHODS An online survey was administered to National Society of Genetic Counselors members providing clinical counseling. RESULTS Respondents (n = 239) represented all major clinical specialties. The majority (68%) reported reviewing evidence documented by the laboratory for most (>60%) variants reported; 45.5% report seeking additional evidence. Prenatal GCs were less likely to independently assess reported evidence. Most respondents (67%) report having reached a different conclusion about a variant's classification than the testing laboratory, though infrequently. Time was the most commonly reported barrier (72%) to performing variant interpretation, though the majority (97%) indicated that this practice had an important impact on patient care. When presented with three hypothetical scenarios, evidence typically used for variant interpretation was generally applied correctly. CONCLUSION This study is the first to document variant interpretation practice broadly across clinical GC specialties. Our results suggest that variant interpretation should be considered a practice-based competency for GCs.
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