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Riviello FN, Daponte A, Ponzi E, Ficarella R, Orsini P, Bucci R, Ventura M, Antonacci F, Catacchio CR, Gentile M. A Rare Case of Concurrent 2q34q36 Duplication and 2q37 Deletion in a Neonate with Syndromic Features. Genes (Basel) 2023; 14:2194. [PMID: 38137016 PMCID: PMC10742419 DOI: 10.3390/genes14122194] [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: 11/09/2023] [Revised: 12/02/2023] [Accepted: 12/07/2023] [Indexed: 12/24/2023] Open
Abstract
Large-scale genomic structural variations can have significant clinical implications, depending on the specific altered genomic region. Briefly, 2q37 microdeletion syndrome is a prevalent subtelomeric deletion disorder characterized by variable-sized deletions. Affected patients exhibit a wide range of clinical manifestations, including short stature, facial dysmorphism, and features of autism spectrum disorder, among others. Conversely, isolated duplications of proximal chromosome 2q are rare and lack a distinct phenotype. In this report, we provide an extensive molecular analysis of a 15-day-old newborn referred for syndromic features. Our analysis reveals an 8.5 Mb microdeletion at 2q37.1, which extends to the telomere, in conjunction with an 8.6 Mb interstitial microduplication at 2q34q36.1. Our findings underscore the prominence of 2q37 terminal deletions as commonly reported genomic anomalies. We compare our patient's phenotype with previously reported cases in the literature to contribute to a more refined classification of 2q37 microdeletion syndrome and assess the potential impact of 2q34q36.1 microduplication. We also investigate multiple hypotheses to clarify the genetic mechanisms responsible for the observed genomic rearrangement.
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Affiliation(s)
- Francesco Nicola Riviello
- U.O.C. Laboratorio di Genetica Medica, PO Di Venere—ASL Bari, 70012 Bari, Italy; (F.N.R.); (E.P.); (R.F.); (P.O.); (R.B.)
| | - Alessia Daponte
- Dipartimento di Bioscienze, Biotecnologie e Ambiente, Università degli Studi di Bari “Aldo Moro”, 70125 Bari, Italy; (A.D.); (M.V.); (F.A.)
| | - Emanuela Ponzi
- U.O.C. Laboratorio di Genetica Medica, PO Di Venere—ASL Bari, 70012 Bari, Italy; (F.N.R.); (E.P.); (R.F.); (P.O.); (R.B.)
| | - Romina Ficarella
- U.O.C. Laboratorio di Genetica Medica, PO Di Venere—ASL Bari, 70012 Bari, Italy; (F.N.R.); (E.P.); (R.F.); (P.O.); (R.B.)
| | - Paola Orsini
- U.O.C. Laboratorio di Genetica Medica, PO Di Venere—ASL Bari, 70012 Bari, Italy; (F.N.R.); (E.P.); (R.F.); (P.O.); (R.B.)
| | - Roberta Bucci
- U.O.C. Laboratorio di Genetica Medica, PO Di Venere—ASL Bari, 70012 Bari, Italy; (F.N.R.); (E.P.); (R.F.); (P.O.); (R.B.)
| | - Mario Ventura
- Dipartimento di Bioscienze, Biotecnologie e Ambiente, Università degli Studi di Bari “Aldo Moro”, 70125 Bari, Italy; (A.D.); (M.V.); (F.A.)
| | - Francesca Antonacci
- Dipartimento di Bioscienze, Biotecnologie e Ambiente, Università degli Studi di Bari “Aldo Moro”, 70125 Bari, Italy; (A.D.); (M.V.); (F.A.)
| | - Claudia Rita Catacchio
- Dipartimento di Bioscienze, Biotecnologie e Ambiente, Università degli Studi di Bari “Aldo Moro”, 70125 Bari, Italy; (A.D.); (M.V.); (F.A.)
| | - Mattia Gentile
- U.O.C. Laboratorio di Genetica Medica, PO Di Venere—ASL Bari, 70012 Bari, Italy; (F.N.R.); (E.P.); (R.F.); (P.O.); (R.B.)
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Quaio CRDC, Ceroni JRM, Pereira MA, Teixeira ACB, Yamada RY, Cintra VP, Perrone E, De França M, Chen K, Minillo RM, Biondo CA, de Mello MRB, Moura LR, do Nascimento ATB, de Oliveira Pelegrino K, de Lima LB, do Amaral Virmond L, Moreno CA, Prota JRM, de Araujo Espolaor JG, Silva TYT, Moraes GHI, de Oliveira GS, Moura LMS, Caraciolo MP, Guedes RLM, Gretschischkin MC, Chazanas PLN, Nakamura CNI, de Souza Reis R, Toledo CM, Lage FSD, de Almeida GB, do Nascimento Júnior JB, Cardoso MA, de Paula Azevedo V, de Almeida TF, Cervato MC, de Oliveira Filho JB. The hospital Israelita Albert Einstein standards for constitutional sequence variants classification: version 2023. Hum Genomics 2023; 17:102. [PMID: 37968704 PMCID: PMC10652504 DOI: 10.1186/s40246-023-00549-6] [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: 08/03/2023] [Accepted: 11/02/2023] [Indexed: 11/17/2023] Open
Abstract
BACKGROUND Next-generation sequencing has had a significant impact on genetic disease diagnosis, but the interpretation of the vast amount of genomic data it generates can be challenging. To address this, the American College of Medical Genetics and Genomics and the Association for Molecular Pathology have established guidelines for standardized variant interpretation. In this manuscript, we present the updated Hospital Israelita Albert Einstein Standards for Constitutional Sequence Variants Classification, incorporating modifications from leading genetics societies and the ClinGen initiative. RESULTS First, we standardized the scientific publications, documents, and other reliable sources for this document to ensure an evidence-based approach. Next, we defined the databases that would provide variant information for the classification process, established the terminology for molecular findings, set standards for disease-gene associations, and determined the nomenclature for classification criteria. Subsequently, we defined the general rules for variant classification and the Bayesian statistical reasoning principles to enhance this process. We also defined bioinformatics standards for automated classification. Our workgroup adhered to gene-specific rules and workflows curated by the ClinGen Variant Curation Expert Panels whenever available. Additionally, a distinct set of specifications for criteria modulation was created for cancer genes, recognizing their unique characteristics. CONCLUSIONS The development of an internal consensus and standards for constitutional sequence variant classification, specifically adapted to the Brazilian population, further contributes to the continuous refinement of variant classification practices. The aim of these efforts from the workgroup is to enhance the reliability and uniformity of variant classification.
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Affiliation(s)
| | - José Ricardo Magliocco Ceroni
- Laboratório Clínico, Hospital Israelita Albert Einstein, Av. Albert Einstein 627, São Paulo, SP, CEP 05652-000, Brazil
| | - Michele Araújo Pereira
- Laboratório Clínico, Hospital Israelita Albert Einstein, Av. Albert Einstein 627, São Paulo, SP, CEP 05652-000, Brazil
- VarsOmics, Hospital Israelita Albert Einstein, São Paulo, SP, Brazil
| | | | - Renata Yoshiko Yamada
- Laboratório Clínico, Hospital Israelita Albert Einstein, Av. Albert Einstein 627, São Paulo, SP, CEP 05652-000, Brazil
| | - Vivian Pedigone Cintra
- Laboratório Clínico, Hospital Israelita Albert Einstein, Av. Albert Einstein 627, São Paulo, SP, CEP 05652-000, Brazil
| | - Eduardo Perrone
- Laboratório Clínico, Hospital Israelita Albert Einstein, Av. Albert Einstein 627, São Paulo, SP, CEP 05652-000, Brazil
| | - Marina De França
- Laboratório Clínico, Hospital Israelita Albert Einstein, Av. Albert Einstein 627, São Paulo, SP, CEP 05652-000, Brazil
| | - Kelin Chen
- Laboratório Clínico, Hospital Israelita Albert Einstein, Av. Albert Einstein 627, São Paulo, SP, CEP 05652-000, Brazil
| | - Renata Moldenhauer Minillo
- Laboratório Clínico, Hospital Israelita Albert Einstein, Av. Albert Einstein 627, São Paulo, SP, CEP 05652-000, Brazil
| | - Cheysa Arielly Biondo
- Laboratório Clínico, Hospital Israelita Albert Einstein, Av. Albert Einstein 627, São Paulo, SP, CEP 05652-000, Brazil
| | | | - Lais Rodrigues Moura
- Laboratório Clínico, Hospital Israelita Albert Einstein, Av. Albert Einstein 627, São Paulo, SP, CEP 05652-000, Brazil
| | | | - Karla de Oliveira Pelegrino
- Laboratório Clínico, Hospital Israelita Albert Einstein, Av. Albert Einstein 627, São Paulo, SP, CEP 05652-000, Brazil
| | - Larissa Barbosa de Lima
- Laboratório Clínico, Hospital Israelita Albert Einstein, Av. Albert Einstein 627, São Paulo, SP, CEP 05652-000, Brazil
| | - Luiza do Amaral Virmond
- Laboratório Clínico, Hospital Israelita Albert Einstein, Av. Albert Einstein 627, São Paulo, SP, CEP 05652-000, Brazil
| | - Carolina Araujo Moreno
- Laboratório Clínico, Hospital Israelita Albert Einstein, Av. Albert Einstein 627, São Paulo, SP, CEP 05652-000, Brazil
| | - Joana Rosa Marques Prota
- Laboratório Clínico, Hospital Israelita Albert Einstein, Av. Albert Einstein 627, São Paulo, SP, CEP 05652-000, Brazil
| | | | | | - Gabriel Hideki Izuka Moraes
- Laboratório Clínico, Hospital Israelita Albert Einstein, Av. Albert Einstein 627, São Paulo, SP, CEP 05652-000, Brazil
- VarsOmics, Hospital Israelita Albert Einstein, São Paulo, SP, Brazil
| | - Gustavo Santos de Oliveira
- Laboratório Clínico, Hospital Israelita Albert Einstein, Av. Albert Einstein 627, São Paulo, SP, CEP 05652-000, Brazil
- VarsOmics, Hospital Israelita Albert Einstein, São Paulo, SP, Brazil
| | - Livia Maria Silva Moura
- Laboratório Clínico, Hospital Israelita Albert Einstein, Av. Albert Einstein 627, São Paulo, SP, CEP 05652-000, Brazil
- VarsOmics, Hospital Israelita Albert Einstein, São Paulo, SP, Brazil
| | - Marcel Pinheiro Caraciolo
- Laboratório Clínico, Hospital Israelita Albert Einstein, Av. Albert Einstein 627, São Paulo, SP, CEP 05652-000, Brazil
- VarsOmics, Hospital Israelita Albert Einstein, São Paulo, SP, Brazil
| | - Rafael Lucas Muniz Guedes
- Laboratório Clínico, Hospital Israelita Albert Einstein, Av. Albert Einstein 627, São Paulo, SP, CEP 05652-000, Brazil
- VarsOmics, Hospital Israelita Albert Einstein, São Paulo, SP, Brazil
| | - Michel Chieregato Gretschischkin
- Laboratório Clínico, Hospital Israelita Albert Einstein, Av. Albert Einstein 627, São Paulo, SP, CEP 05652-000, Brazil
- VarsOmics, Hospital Israelita Albert Einstein, São Paulo, SP, Brazil
| | - Pedro Lui Nigro Chazanas
- Laboratório Clínico, Hospital Israelita Albert Einstein, Av. Albert Einstein 627, São Paulo, SP, CEP 05652-000, Brazil
- VarsOmics, Hospital Israelita Albert Einstein, São Paulo, SP, Brazil
| | - Carolina Naomi Izo Nakamura
- Laboratório Clínico, Hospital Israelita Albert Einstein, Av. Albert Einstein 627, São Paulo, SP, CEP 05652-000, Brazil
- VarsOmics, Hospital Israelita Albert Einstein, São Paulo, SP, Brazil
| | - Rodrigo de Souza Reis
- Laboratório Clínico, Hospital Israelita Albert Einstein, Av. Albert Einstein 627, São Paulo, SP, CEP 05652-000, Brazil
- VarsOmics, Hospital Israelita Albert Einstein, São Paulo, SP, Brazil
| | - Carmen Melo Toledo
- Laboratório Clínico, Hospital Israelita Albert Einstein, Av. Albert Einstein 627, São Paulo, SP, CEP 05652-000, Brazil
- VarsOmics, Hospital Israelita Albert Einstein, São Paulo, SP, Brazil
| | - Fernanda Stussi Duarte Lage
- Laboratório Clínico, Hospital Israelita Albert Einstein, Av. Albert Einstein 627, São Paulo, SP, CEP 05652-000, Brazil
- VarsOmics, Hospital Israelita Albert Einstein, São Paulo, SP, Brazil
| | - Giovanna Bloise de Almeida
- Laboratório Clínico, Hospital Israelita Albert Einstein, Av. Albert Einstein 627, São Paulo, SP, CEP 05652-000, Brazil
- VarsOmics, Hospital Israelita Albert Einstein, São Paulo, SP, Brazil
| | - José Bandeira do Nascimento Júnior
- Laboratório Clínico, Hospital Israelita Albert Einstein, Av. Albert Einstein 627, São Paulo, SP, CEP 05652-000, Brazil
- VarsOmics, Hospital Israelita Albert Einstein, São Paulo, SP, Brazil
| | - Milena Andreuzo Cardoso
- Laboratório Clínico, Hospital Israelita Albert Einstein, Av. Albert Einstein 627, São Paulo, SP, CEP 05652-000, Brazil
- VarsOmics, Hospital Israelita Albert Einstein, São Paulo, SP, Brazil
| | - Victor de Paula Azevedo
- Laboratório Clínico, Hospital Israelita Albert Einstein, Av. Albert Einstein 627, São Paulo, SP, CEP 05652-000, Brazil
- VarsOmics, Hospital Israelita Albert Einstein, São Paulo, SP, Brazil
| | - Tatiana Ferreira de Almeida
- Laboratório Clínico, Hospital Israelita Albert Einstein, Av. Albert Einstein 627, São Paulo, SP, CEP 05652-000, Brazil
| | - Murilo Castro Cervato
- Laboratório Clínico, Hospital Israelita Albert Einstein, Av. Albert Einstein 627, São Paulo, SP, CEP 05652-000, Brazil
- VarsOmics, Hospital Israelita Albert Einstein, São Paulo, SP, Brazil
| | - Joao Bosco de Oliveira Filho
- Laboratório Clínico, Hospital Israelita Albert Einstein, Av. Albert Einstein 627, São Paulo, SP, CEP 05652-000, Brazil.
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Zhou R, Jiao J, Wang Y, Meng L, Li Y, Xu Y, Hu P, Xu Z. Systematic analysis of copy number variants of uncertain significance partially overlapping with the haploinsufficient or triplosensitive genes in clinical testing. Ann Med 2023; 55:2276824. [PMID: 37917952 PMCID: PMC10623895 DOI: 10.1080/07853890.2023.2276824] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/07/2023] [Accepted: 10/24/2023] [Indexed: 11/04/2023] Open
Abstract
Background: Copy number variants of uncertain significance (VUS) has brought much distress for patients and great counselling challenges for clinicians. Of these, a special type of VUS (HT-VUS), harbouring one or both breakpoints within the established haploinsufficient or triplosensitive genes, were considered to be more likely to cause clinical effects compared with other types of VUS.Methods: We retrospectively evaluated the properties and clinical significance of those HT-VUS samples in clinical testing for chromosome microarray analysis (CMA).Results: A total of 7150 samples were selected for HT-VUS screening, and 75 (1.05%) subjects with 75 HT-VUS were found. The majority of these HT-VUS were heterozygous duplications and chromosome X had the most HT-VUS. The prevalence of HT-VUS was 0.90% (28/3116) for prenatal low-risk samples, 1.18% (26/2196) for prenatal high-risk samples, 1.37% (10/728) for postnatal samples and 0.99% (11/1110) for early pregnancy loss samples. However, the incidence of HT-VUS was not statistically different between different groups.Conclusions: HT-VUS (deletions or duplications) involving introns and HT-VUS (duplications) including terminal coding exons (either the first or last exons) might be clinically neutral. Our study will be helpful for both interpretation and genetic counselling in the future.
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Affiliation(s)
- Ran Zhou
- Department of Prenatal Diagnosis, Women’s Hospital of Nanjing Medical University, Nanjing Maternity and Child Health Care Hospital, Nanjing, China
| | - Jiao Jiao
- Department of Prenatal Diagnosis, Women’s Hospital of Nanjing Medical University, Nanjing Maternity and Child Health Care Hospital, Nanjing, China
| | - Yan Wang
- Department of Prenatal Diagnosis, Women’s Hospital of Nanjing Medical University, Nanjing Maternity and Child Health Care Hospital, Nanjing, China
| | - Lulu Meng
- Department of Prenatal Diagnosis, Women’s Hospital of Nanjing Medical University, Nanjing Maternity and Child Health Care Hospital, Nanjing, China
| | - Yiming Li
- Department of Prenatal Diagnosis, Women’s Hospital of Nanjing Medical University, Nanjing Maternity and Child Health Care Hospital, Nanjing, China
| | - Yiyun Xu
- Department of Prenatal Diagnosis, Women’s Hospital of Nanjing Medical University, Nanjing Maternity and Child Health Care Hospital, Nanjing, China
| | - Ping Hu
- Department of Prenatal Diagnosis, Women’s Hospital of Nanjing Medical University, Nanjing Maternity and Child Health Care Hospital, Nanjing, China
| | - Zhengfeng Xu
- Department of Prenatal Diagnosis, Women’s Hospital of Nanjing Medical University, Nanjing Maternity and Child Health Care Hospital, Nanjing, China
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Walker LC, Hoya MDL, Wiggins GAR, Lindy A, Vincent LM, Parsons MT, Canson DM, Bis-Brewer D, Cass A, Tchourbanov A, Zimmermann H, Byrne AB, Pesaran T, Karam R, Harrison SM, Spurdle AB. Using the ACMG/AMP framework to capture evidence related to predicted and observed impact on splicing: Recommendations from the ClinGen SVI Splicing Subgroup. Am J Hum Genet 2023; 110:1046-1067. [PMID: 37352859 PMCID: PMC10357475 DOI: 10.1016/j.ajhg.2023.06.002] [Citation(s) in RCA: 44] [Impact Index Per Article: 44.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2023] [Revised: 06/01/2023] [Accepted: 06/02/2023] [Indexed: 06/25/2023] Open
Abstract
The American College of Medical Genetics and Genomics (ACMG)/Association for Molecular Pathology (AMP) framework for classifying variants uses six evidence categories related to the splicing potential of variants: PVS1, PS3, PP3, BS3, BP4, and BP7. However, the lack of guidance on how to apply such codes has contributed to variation in the specifications developed by different Clinical Genome Resource (ClinGen) Variant Curation Expert Panels. The ClinGen Sequence Variant Interpretation Splicing Subgroup was established to refine recommendations for applying ACMG/AMP codes relating to splicing data and computational predictions. We utilized empirically derived splicing evidence to (1) determine the evidence weighting of splicing-related data and appropriate criteria code selection for general use, (2) outline a process for integrating splicing-related considerations when developing a gene-specific PVS1 decision tree, and (3) exemplify methodology to calibrate splice prediction tools. We propose repurposing the PVS1_Strength code to capture splicing assay data that provide experimental evidence for variants resulting in RNA transcript(s) with loss of function. Conversely, BP7 may be used to capture RNA results demonstrating no splicing impact for intronic and synonymous variants. We propose that the PS3/BS3 codes are applied only for well-established assays that measure functional impact not directly captured by RNA-splicing assays. We recommend the application of PS1 based on similarity of predicted RNA-splicing effects for a variant under assessment in comparison with a known pathogenic variant. The recommendations and approaches for consideration and evaluation of RNA-assay evidence described aim to help standardize variant pathogenicity classification processes when interpreting splicing-based evidence.
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Affiliation(s)
- Logan C Walker
- Department of Pathology and Biomedical Science, University of Otago, Christchurch, New Zealand
| | - Miguel de la Hoya
- Molecular Oncology Laboratory, CIBERONC, Hospital Clinico San Carlos, IdISSC (Instituto de Investigación Sanitaria del Hospital Clínico San Carlos), Madrid, Spain
| | - George A R Wiggins
- Department of Pathology and Biomedical Science, University of Otago, Christchurch, New Zealand
| | | | | | - Michael T Parsons
- Population Health Program, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Daffodil M Canson
- Population Health Program, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | | | | | | | | | - Alicia B Byrne
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | | | | | - Steven M Harrison
- Ambry Genetics, Aliso Viejo, CA, USA; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
| | - Amanda B Spurdle
- Population Health Program, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia; Faculty of Medicine, The University of Queensland, Brisbane, QLD, Australia
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5
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Walker LC, de la Hoya M, Wiggins GA, Lindy A, Vincent LM, Parsons M, Canson DM, Bis-Brewer D, Cass A, Tchourbanov A, Zimmermann H, Byrne AB, Pesaran T, Karam R, Harrison SM, Spurdle AB. APPLICATION OF THE ACMG/AMP FRAMEWORK TO CAPTURE EVIDENCE RELEVANT TO PREDICTED AND OBSERVED IMPACT ON SPLICING: RECOMMENDATIONS FROM THE CLINGEN SVI SPLICING SUBGROUP. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.02.24.23286431. [PMID: 36865205 PMCID: PMC9980257 DOI: 10.1101/2023.02.24.23286431] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/01/2023]
Abstract
The American College of Medical Genetics and Genomics (ACMG) and the Association for Molecular Pathology (AMP) framework for classifying variants uses six evidence categories related to the splicing potential of variants: PVS1 (null variant in a gene where loss-of-function is the mechanism of disease), PS3 (functional assays show damaging effect on splicing), PP3 (computational evidence supports a splicing effect), BS3 (functional assays show no damaging effect on splicing), BP4 (computational evidence suggests no splicing impact), and BP7 (silent change with no predicted impact on splicing). However, the lack of guidance on how to apply such codes has contributed to variation in the specifications developed by different Clinical Genome Resource (ClinGen) Variant Curation Expert Panels. The ClinGen Sequence Variant Interpretation (SVI) Splicing Subgroup was established to refine recommendations for applying ACMG/AMP codes relating to splicing data and computational predictions. Our study utilised empirically derived splicing evidence to: 1) determine the evidence weighting of splicing-related data and appropriate criteria code selection for general use, 2) outline a process for integrating splicing-related considerations when developing a gene-specific PVS1 decision tree, and 3) exemplify methodology to calibrate bioinformatic splice prediction tools. We propose repurposing of the PVS1_Strength code to capture splicing assay data that provide experimental evidence for variants resulting in RNA transcript(s) with loss of function. Conversely BP7 may be used to capture RNA results demonstrating no impact on splicing for both intronic and synonymous variants, and for missense variants if protein functional impact has been excluded. Furthermore, we propose that the PS3 and BS3 codes are applied only for well-established assays that measure functional impact that is not directly captured by RNA splicing assays. We recommend the application of PS1 based on similarity of predicted RNA splicing effects for a variant under assessment in comparison to a known Pathogenic variant. The recommendations and approaches for consideration and evaluation of RNA assay evidence described aim to help standardise variant pathogenicity classification processes and result in greater consistency when interpreting splicing-based evidence.
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6
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Genome screening, reporting, and genetic counseling for healthy populations. Hum Genet 2023; 142:181-192. [PMID: 36331656 PMCID: PMC9638226 DOI: 10.1007/s00439-022-02480-7] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2022] [Accepted: 08/16/2022] [Indexed: 11/06/2022]
Abstract
Rapid advancements of genome sequencing (GS) technologies have enhanced our understanding of the relationship between genes and human disease. To incorporate genomic information into the practice of medicine, new processes for the analysis, reporting, and communication of GS data are needed. Blood samples were collected from adults with a PCR-confirmed SARS-CoV-2 (COVID-19) diagnosis (target N = 1500). GS was performed. Data were filtered and analyzed using custom pipelines and gene panels. We developed unique patient-facing materials, including an online intake survey, group counseling presentation, and consultation letters in addition to a comprehensive GS report. The final report includes results generated from GS data: (1) monogenic disease risks; (2) carrier status; (3) pharmacogenomic variants; (4) polygenic risk scores for common conditions; (5) HLA genotype; (6) genetic ancestry; (7) blood group; and, (8) COVID-19 viral lineage. Participants complete pre-test genetic counseling and confirm preferences for secondary findings before receiving results. Counseling and referrals are initiated for clinically significant findings. We developed a genetic counseling, reporting, and return of results framework that integrates GS information across multiple areas of human health, presenting possibilities for the clinical application of comprehensive GS data in healthy individuals.
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Ding X, Zhao R, Dai Y, Zhang Y, Lin S, Ye J. Comprehensive Analysis of Copy Number Variations on Glycoside Hydrolase 45 Genes among Different Bursaphelenchus xylophilus Strains. Int J Mol Sci 2022; 23:ijms232315323. [PMID: 36499649 PMCID: PMC9735991 DOI: 10.3390/ijms232315323] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2022] [Revised: 11/29/2022] [Accepted: 12/02/2022] [Indexed: 12/12/2022] Open
Abstract
Bursaphelenchus xylophilus is considered the most dangerous quarantine pest in China. It causes enormous economic and ecological losses in many countries from Asia and Europe. The glycoside hydrolase 45 gene family has been demonstrated in early studies to contribute to the cell wall degradation ability of B. xylophilus during its infection. However, the copy number variation (CNV) of the GH45 gene and its association with B. xylophilus pathogenicity were not fully elucidated. In this study, we found that the GH45 gene with two copies is the most predominant type among 259 B. xylophilus strains collected from China and Japan. Additionally, 18 strains are identified as GH45 genes with a single copy, and only two strains are verified to have three copies. Subsequent expression analysis and inoculation test suggest that the copy numbers of the GH45 gene are correlated with gene expression as well as the B. xylophilus pathogenicity. B. xylophilus strains with more copies of the GH45 gene usually exhibit more abundant expression and cause more severe wilt symptoms on pine trees. The aforementioned results indicated the potential regulatory effects of CNV in B. xylophilus and provided novel information to better understand the molecular pathogenesis of this devastating pest.
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Affiliation(s)
- Xiaolei Ding
- Co-Innovation Center for Sustainable Forestry in Southern China, College of Forestry, Nanjing Forestry University, Nanjing 210037, China
- Jiangsu Key Laboratory for Prevention and Management of Invasive Species, Nanjing 210037, China
- Correspondence:
| | - Ruiwen Zhao
- Co-Innovation Center for Sustainable Forestry in Southern China, College of Forestry, Nanjing Forestry University, Nanjing 210037, China
- Jiangsu Key Laboratory for Prevention and Management of Invasive Species, Nanjing 210037, China
| | - Yonglin Dai
- Co-Innovation Center for Sustainable Forestry in Southern China, College of Forestry, Nanjing Forestry University, Nanjing 210037, China
| | - Yue Zhang
- Co-Innovation Center for Sustainable Forestry in Southern China, College of Forestry, Nanjing Forestry University, Nanjing 210037, China
- Jiangsu Key Laboratory for Prevention and Management of Invasive Species, Nanjing 210037, China
| | - Sixi Lin
- Co-Innovation Center for Sustainable Forestry in Southern China, College of Forestry, Nanjing Forestry University, Nanjing 210037, China
- Jiangsu Key Laboratory for Prevention and Management of Invasive Species, Nanjing 210037, China
| | - Jianren Ye
- Co-Innovation Center for Sustainable Forestry in Southern China, College of Forestry, Nanjing Forestry University, Nanjing 210037, China
- Jiangsu Key Laboratory for Prevention and Management of Invasive Species, Nanjing 210037, China
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Trost B, Thiruvahindrapuram B, Chan AJS, Engchuan W, Higginbotham EJ, Howe JL, Loureiro LO, Reuter MS, Roshandel D, Whitney J, Zarrei M, Bookman M, Somerville C, Shaath R, Abdi M, Aliyev E, Patel RV, Nalpathamkalam T, Pellecchia G, Hamdan O, Kaur G, Wang Z, MacDonald JR, Wei J, Sung WWL, Lamoureux S, Hoang N, Selvanayagam T, Deflaux N, Geng M, Ghaffari S, Bates J, Young EJ, Ding Q, Shum C, D'Abate L, Bradley CA, Rutherford A, Aguda V, Apresto B, Chen N, Desai S, Du X, Fong MLY, Pullenayegum S, Samler K, Wang T, Ho K, Paton T, Pereira SL, Herbrick JA, Wintle RF, Fuerth J, Noppornpitak J, Ward H, Magee P, Al Baz A, Kajendirarajah U, Kapadia S, Vlasblom J, Valluri M, Green J, Seifer V, Quirbach M, Rennie O, Kelley E, Masjedi N, Lord C, Szego MJ, Zawati MH, Lang M, Strug LJ, Marshall CR, Costain G, Calli K, Iaboni A, Yusuf A, Ambrozewicz P, Gallagher L, Amaral DG, Brian J, Elsabbagh M, Georgiades S, Messinger DS, Ozonoff S, Sebat J, Sjaarda C, Smith IM, Szatmari P, Zwaigenbaum L, Kushki A, Frazier TW, Vorstman JAS, Fakhro KA, Fernandez BA, Lewis MES, Weksberg R, Fiume M, Yuen RKC, Anagnostou E, Sondheimer N, Glazer D, Hartley DM, Scherer SW. Genomic architecture of autism from comprehensive whole-genome sequence annotation. Cell 2022; 185:4409-4427.e18. [PMID: 36368308 PMCID: PMC10726699 DOI: 10.1016/j.cell.2022.10.009] [Citation(s) in RCA: 67] [Impact Index Per Article: 33.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2022] [Revised: 08/30/2022] [Accepted: 10/07/2022] [Indexed: 11/11/2022]
Abstract
Fully understanding autism spectrum disorder (ASD) genetics requires whole-genome sequencing (WGS). We present the latest release of the Autism Speaks MSSNG resource, which includes WGS data from 5,100 individuals with ASD and 6,212 non-ASD parents and siblings (total n = 11,312). Examining a wide variety of genetic variants in MSSNG and the Simons Simplex Collection (SSC; n = 9,205), we identified ASD-associated rare variants in 718/5,100 individuals with ASD from MSSNG (14.1%) and 350/2,419 from SSC (14.5%). Considering genomic architecture, 52% were nuclear sequence-level variants, 46% were nuclear structural variants (including copy-number variants, inversions, large insertions, uniparental isodisomies, and tandem repeat expansions), and 2% were mitochondrial variants. Our study provides a guidebook for exploring genotype-phenotype correlations in families who carry ASD-associated rare variants and serves as an entry point to the expanded studies required to dissect the etiology in the ∼85% of the ASD population that remain idiopathic.
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Affiliation(s)
- Brett Trost
- The Centre for Applied Genomics, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada; Genetics and Genome Biology Program, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
| | | | - Ada J S Chan
- The Centre for Applied Genomics, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada; Genetics and Genome Biology Program, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
| | - Worrawat Engchuan
- The Centre for Applied Genomics, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada; Genetics and Genome Biology Program, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
| | - Edward J Higginbotham
- The Centre for Applied Genomics, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada; Genetics and Genome Biology Program, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
| | - Jennifer L Howe
- The Centre for Applied Genomics, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
| | - Livia O Loureiro
- The Centre for Applied Genomics, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada; Genetics and Genome Biology Program, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
| | - Miriam S Reuter
- The Centre for Applied Genomics, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada; Genetics and Genome Biology Program, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada; CGEn, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
| | - Delnaz Roshandel
- Genetics and Genome Biology Program, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
| | - Joe Whitney
- The Centre for Applied Genomics, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
| | - Mehdi Zarrei
- The Centre for Applied Genomics, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada; Genetics and Genome Biology Program, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
| | | | - Cherith Somerville
- Ted Rogers Centre for Heart Research, The Hospital for Sick Children, Toronto, ON M5G 1X8, Canada
| | - Rulan Shaath
- The Centre for Applied Genomics, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
| | - Mona Abdi
- Department of Human Genetics, Sidra Medicine, Doha, Qatar; College of Health and Life Sciences, Hamad Bin Khalifa University, Doha, Qatar
| | - Elbay Aliyev
- Department of Human Genetics, Sidra Medicine, Doha, Qatar
| | - Rohan V Patel
- The Centre for Applied Genomics, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
| | - Thomas Nalpathamkalam
- The Centre for Applied Genomics, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
| | - Giovanna Pellecchia
- The Centre for Applied Genomics, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
| | - Omar Hamdan
- The Centre for Applied Genomics, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
| | - Gaganjot Kaur
- The Centre for Applied Genomics, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
| | - Zhuozhi Wang
- The Centre for Applied Genomics, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
| | - Jeffrey R MacDonald
- The Centre for Applied Genomics, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
| | - John Wei
- The Centre for Applied Genomics, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
| | - Wilson W L Sung
- The Centre for Applied Genomics, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
| | - Sylvia Lamoureux
- The Centre for Applied Genomics, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
| | - Ny Hoang
- Genetics and Genome Biology Program, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada; Autism Research Unit, The Hospital for Sick Children, Toronto, ON M5G 1X8, Canada; Department of Molecular Genetics, University of Toronto, Toronto, ON M5S 1A8, Canada; Department of Genetic Counselling, The Hospital for Sick Children, Toronto, ON M5G 1X8, Canada
| | - Thanuja Selvanayagam
- Genetics and Genome Biology Program, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada; Autism Research Unit, The Hospital for Sick Children, Toronto, ON M5G 1X8, Canada; Department of Genetic Counselling, The Hospital for Sick Children, Toronto, ON M5G 1X8, Canada
| | - Nicole Deflaux
- Verily Life Sciences, South San Francisco, CA 94080, USA
| | - Melissa Geng
- Genetics and Genome Biology Program, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada; Department of Molecular Genetics, University of Toronto, Toronto, ON M5S 1A8, Canada
| | - Siavash Ghaffari
- The Centre for Applied Genomics, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada; Genetics and Genome Biology Program, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
| | - John Bates
- Verily Life Sciences, South San Francisco, CA 94080, USA
| | - Edwin J Young
- Genome Diagnostics, Department of Paediatric Medicine, The Hospital for Sick Children, Toronto, ON M5G 1X8, Canada; Department of Laboratory Medicine and Pathobiology, The Hospital for Sick Children, Toronto, ON M5G 1X8, Canada
| | - Qiliang Ding
- Ted Rogers Centre for Heart Research, The Hospital for Sick Children, Toronto, ON M5G 1X8, Canada
| | - Carole Shum
- The Centre for Applied Genomics, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada; Genetics and Genome Biology Program, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
| | - Lia D'Abate
- The Centre for Applied Genomics, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada; Genetics and Genome Biology Program, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
| | - Clarrisa A Bradley
- Genetics and Genome Biology Program, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada; Neurosciences and Mental Health, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
| | - Annabel Rutherford
- The Centre for Applied Genomics, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada; Genetics and Genome Biology Program, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada; Department of Molecular Genetics, University of Toronto, Toronto, ON M5S 1A8, Canada
| | - Vernie Aguda
- The Centre for Applied Genomics, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
| | - Beverly Apresto
- The Centre for Applied Genomics, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
| | - Nan Chen
- The Centre for Applied Genomics, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
| | - Sachin Desai
- The Centre for Applied Genomics, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
| | - Xiaoyan Du
- The Centre for Applied Genomics, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
| | - Matthew L Y Fong
- The Centre for Applied Genomics, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
| | - Sanjeev Pullenayegum
- The Centre for Applied Genomics, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
| | - Kozue Samler
- The Centre for Applied Genomics, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
| | - Ting Wang
- The Centre for Applied Genomics, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
| | - Karen Ho
- The Centre for Applied Genomics, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
| | - Tara Paton
- The Centre for Applied Genomics, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
| | - Sergio L Pereira
- The Centre for Applied Genomics, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
| | - Jo-Anne Herbrick
- The Centre for Applied Genomics, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
| | - Richard F Wintle
- The Centre for Applied Genomics, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
| | | | | | | | | | | | | | | | | | | | | | | | | | - Olivia Rennie
- The Centre for Applied Genomics, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
| | - Elizabeth Kelley
- Department of Psychology, Queen's University, Kingston, ON K7L 3N6, Canada; Department of Psychiatry, Queen's University, Kingston, ON K7L 7X3, Canada
| | - Nina Masjedi
- Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, CA 90024, USA
| | - Catherine Lord
- Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, CA 90024, USA
| | - Michael J Szego
- Department of Molecular Genetics, University of Toronto, Toronto, ON M5S 1A8, Canada; Department of Family and Community Medicine, University of Toronto, Toronto, ON M5G 1V7, Canada; Dalla Lana School of Public Health, University of Toronto, Toronto, ON M5T 3M7, Canada
| | - Ma'n H Zawati
- Department of Human Genetics, McGill University, Montreal, QC H3A 0C7, Canada
| | - Michael Lang
- Department of Human Genetics, McGill University, Montreal, QC H3A 0C7, Canada
| | - Lisa J Strug
- Genetics and Genome Biology Program, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada; Department of Statistical Sciences, University of Toronto, Toronto, ON M5S 3G3, Canada
| | - Christian R Marshall
- Genome Diagnostics, Department of Paediatric Medicine, The Hospital for Sick Children, Toronto, ON M5G 1X8, Canada; Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON M5S 1A8, Canada
| | - Gregory Costain
- Genetics and Genome Biology Program, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada; Division of Clinical and Metabolic Genetics, The Hospital for Sick Children, Toronto, ON M5G 1X8, Canada; Department of Pediatrics, University of Toronto, Toronto, ON M5G 1X8, Canada
| | - Kristina Calli
- Department of Medical Genetics, University of British Columbia, Vancouver, BC V6H 3N1, Canada; BC Children's Hospital Research Institute, Vancouver, BC V5Z 4H4, Canada
| | - Alana Iaboni
- Holland Bloorview Kids Rehabilitation Hospital, Toronto, ON M4G 1R8, Canada
| | - Afiqah Yusuf
- Montreal Neurological Institute, McGill University, Montreal, QC H3A 2B4, Canada
| | - Patricia Ambrozewicz
- Autism Research Unit, The Hospital for Sick Children, Toronto, ON M5G 1X8, Canada; Department of Psychology, The Hospital for Sick Children, Toronto, ON M5G 1X8, Canada
| | - Louise Gallagher
- Department of Psychiatry, School of Medicine, Trinity College Dublin, Dublin 2, Ireland; Department of Psychiatry, The Hospital for Sick Children, Toronto, ON M5G 1X8, Canada; Child, Youth and Family Services, The Centre for Addiction and Mental Health, Toronto, ON M6J 1H4, Canada; Department of Psychiatry, University of Toronto, Toronto, ON M5T 1R8, Canada
| | - David G Amaral
- MIND Institute, University of California, Davis, Sacramento, CA 95817, USA; Department of Psychiatry and Behavioral Sciences, University of California, Davis, Sacramento, CA 95817, USA
| | - Jessica Brian
- Department of Pediatrics, University of Toronto, Toronto, ON M5G 1X8, Canada; Holland Bloorview Kids Rehabilitation Hospital, Toronto, ON M4G 1R8, Canada
| | - Mayada Elsabbagh
- Montreal Neurological Institute, McGill University, Montreal, QC H3A 2B4, Canada
| | - Stelios Georgiades
- Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, ON L8N 3K7, Canada
| | | | - Sally Ozonoff
- MIND Institute, University of California, Davis, Sacramento, CA 95817, USA; Department of Psychiatry and Behavioral Sciences, University of California, Davis, Sacramento, CA 95817, USA
| | - Jonathan Sebat
- Department of Psychiatry and Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, CA 92093, USA
| | - Calvin Sjaarda
- Department of Psychiatry, Queen's University, Kingston, ON K7L 7X3, Canada; Queen's Genomics Lab at Ongwanada, Queen's University, Kingston, ON K7M 8A6, Canada
| | - Isabel M Smith
- Department of Pediatrics, Dalhousie University, Halifax, NS B3H 4R2, Canada; IWK Health Centre, Halifax, NS B3K 6R8, Canada
| | - Peter Szatmari
- Department of Psychiatry, The Hospital for Sick Children, Toronto, ON M5G 1X8, Canada; Department of Psychiatry, University of Toronto, Toronto, ON M5T 1R8, Canada; Centre for Addiction and Mental Health, Toronto, ON M6J 1H4, Canada
| | - Lonnie Zwaigenbaum
- Department of Pediatrics, University of Alberta, Edmonton, AB T6G 1C9, Canada
| | - Azadeh Kushki
- Holland Bloorview Kids Rehabilitation Hospital, Toronto, ON M4G 1R8, Canada; Institute of Biomedical Engineering, University of Toronto, Toronto, ON M5S 3G9, Canada
| | - Thomas W Frazier
- Autism Speaks, Princeton, NJ 08540, USA; Department of Psychology, John Carroll University, Cleveland, OH 44118, USA
| | - Jacob A S Vorstman
- Genetics and Genome Biology Program, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada; Department of Psychiatry, University of Toronto, Toronto, ON M5T 1R8, Canada
| | - Khalid A Fakhro
- Department of Human Genetics, Sidra Medicine, Doha, Qatar; College of Health and Life Sciences, Hamad Bin Khalifa University, Doha, Qatar; Department of Genetic Medicine, Weill Cornell Medical College in Qatar, Doha, Qatar
| | - Bridget A Fernandez
- Department of Pediatrics, Children's Hospital Los Angeles, Los Angeles, CA 90027, USA; Keck School of Medicine of USC, University of Southern California, Los Angeles, CA 90033, USA
| | - M E Suzanne Lewis
- Department of Medical Genetics, University of British Columbia, Vancouver, BC V6H 3N1, Canada; BC Children's Hospital Research Institute, Vancouver, BC V5Z 4H4, Canada
| | - Rosanna Weksberg
- Division of Clinical and Metabolic Genetics, The Hospital for Sick Children, Toronto, ON M5G 1X8, Canada; Department of Pediatrics, University of Toronto, Toronto, ON M5G 1X8, Canada
| | | | - Ryan K C Yuen
- Genetics and Genome Biology Program, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada; Department of Molecular Genetics, University of Toronto, Toronto, ON M5S 1A8, Canada
| | - Evdokia Anagnostou
- Department of Pediatrics, University of Toronto, Toronto, ON M5G 1X8, Canada; Holland Bloorview Kids Rehabilitation Hospital, Toronto, ON M4G 1R8, Canada
| | - Neal Sondheimer
- Genetics and Genome Biology Program, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada; Department of Molecular Genetics, University of Toronto, Toronto, ON M5S 1A8, Canada; Department of Pediatrics, University of Toronto, Toronto, ON M5G 1X8, Canada
| | - David Glazer
- Verily Life Sciences, South San Francisco, CA 94080, USA
| | | | - Stephen W Scherer
- The Centre for Applied Genomics, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada; Genetics and Genome Biology Program, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada; Department of Molecular Genetics, University of Toronto, Toronto, ON M5S 1A8, Canada; McLaughlin Centre, Toronto, ON M5G 0A4, Canada.
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9
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Zhang W, Yao Z, Guo R, Li H, Zhao S, Li W, Zhang X, Hao C. Molecular identification of T-box transcription factor 6 and prognostic assessment in patients with congenital scoliosis: A single-center study. Front Med (Lausanne) 2022; 9:941468. [PMID: 36035411 PMCID: PMC9403053 DOI: 10.3389/fmed.2022.941468] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2022] [Accepted: 07/14/2022] [Indexed: 11/24/2022] Open
Abstract
Background Congenital scoliosis (CS) is characterized by vertebral malformations. The precise etiology of CS is not fully defined. A compound inheritance of TBX6 was identified in 10% of patients with CS in Han Chinese and formed a distinguishable subtype named TBX6-associated congenital scoliosis (TACS). Methods To investigate the variants and risk haplotype of TBX6, we recruited 121 patients with CS at Beijing Children’s Hospital. We collected the clinical characteristics and surgical treatment options and followed their postoperative prognoses. Results Eight patients (6.6%) were molecularly diagnosed with TACS and carried the previously defined pathogenic TBX6 compound heterozygous variants. All the eight patients with TACS had the typical TACS clinical feature of hemivertebrae in the lower part of the spine. These patients received posterior hemivertebra resection combined with segmental fusion. Follow-ups revealed satisfactory correction without postoperative complications. Conclusion We observed a 6.6% prevalence of TACS in our CS cohort. Follow-ups further highlighted that surgical treatment of hemivertebra resection combined with segmental fusion performed well with prognosis for patients with TACS. This could provide valuable information for CS individuals with compound heterozygosity in TBX6.
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Affiliation(s)
- Wenyan Zhang
- Beijing Key Laboratory for Genetics of Birth Defects, Beijing Pediatric Research Institute, Beijing, China
- Ministry of Education of the People’s Republic of China (MOE) Key Laboratory of Major Diseases in Children, National Center for Children’s Health, Beijing Children’s Hospital, Capital Medical University, Beijing, China
| | - Ziming Yao
- Department of Orthopedics, National Center for Children’s Health, Beijing Children’s Hospital, Capital Medical University, Beijing, China
| | - Ruolan Guo
- Beijing Key Laboratory for Genetics of Birth Defects, Beijing Pediatric Research Institute, Beijing, China
- Ministry of Education of the People’s Republic of China (MOE) Key Laboratory of Major Diseases in Children, National Center for Children’s Health, Beijing Children’s Hospital, Capital Medical University, Beijing, China
- Henan Key Laboratory of Pediatric Inherited and Metabolic Diseases, Henan Children’s Hospital, Zhengzhou Hospital of Beijing Children’s Hospital, Zhengzhou, China
| | - Haichong Li
- Department of Orthopedics, National Center for Children’s Health, Beijing Children’s Hospital, Capital Medical University, Beijing, China
| | - Shuang Zhao
- Beijing Key Laboratory for Genetics of Birth Defects, Beijing Pediatric Research Institute, Beijing, China
- Ministry of Education of the People’s Republic of China (MOE) Key Laboratory of Major Diseases in Children, National Center for Children’s Health, Beijing Children’s Hospital, Capital Medical University, Beijing, China
| | - Wei Li
- Beijing Key Laboratory for Genetics of Birth Defects, Beijing Pediatric Research Institute, Beijing, China
- Ministry of Education of the People’s Republic of China (MOE) Key Laboratory of Major Diseases in Children, National Center for Children’s Health, Beijing Children’s Hospital, Capital Medical University, Beijing, China
- Henan Key Laboratory of Pediatric Inherited and Metabolic Diseases, Henan Children’s Hospital, Zhengzhou Hospital of Beijing Children’s Hospital, Zhengzhou, China
| | - Xuejun Zhang
- Department of Orthopedics, National Center for Children’s Health, Beijing Children’s Hospital, Capital Medical University, Beijing, China
- *Correspondence: Xuejun Zhang,
| | - Chanjuan Hao
- Beijing Key Laboratory for Genetics of Birth Defects, Beijing Pediatric Research Institute, Beijing, China
- Ministry of Education of the People’s Republic of China (MOE) Key Laboratory of Major Diseases in Children, National Center for Children’s Health, Beijing Children’s Hospital, Capital Medical University, Beijing, China
- Henan Key Laboratory of Pediatric Inherited and Metabolic Diseases, Henan Children’s Hospital, Zhengzhou Hospital of Beijing Children’s Hospital, Zhengzhou, China
- Chanjuan Hao,
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10
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Collins RL, Glessner JT, Porcu E, Lepamets M, Brandon R, Lauricella C, Han L, Morley T, Niestroj LM, Ulirsch J, Everett S, Howrigan DP, Boone PM, Fu J, Karczewski KJ, Kellaris G, Lowther C, Lucente D, Mohajeri K, Nõukas M, Nuttle X, Samocha KE, Trinh M, Ullah F, Võsa U, Hurles ME, Aradhya S, Davis EE, Finucane H, Gusella JF, Janze A, Katsanis N, Matyakhina L, Neale BM, Sanders D, Warren S, Hodge JC, Lal D, Ruderfer DM, Meck J, Mägi R, Esko T, Reymond A, Kutalik Z, Hakonarson H, Sunyaev S, Brand H, Talkowski ME. A cross-disorder dosage sensitivity map of the human genome. Cell 2022; 185:3041-3055.e25. [PMID: 35917817 PMCID: PMC9742861 DOI: 10.1016/j.cell.2022.06.036] [Citation(s) in RCA: 128] [Impact Index Per Article: 64.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2020] [Revised: 03/17/2022] [Accepted: 06/20/2022] [Indexed: 02/06/2023]
Abstract
Rare copy-number variants (rCNVs) include deletions and duplications that occur infrequently in the global human population and can confer substantial risk for disease. In this study, we aimed to quantify the properties of haploinsufficiency (i.e., deletion intolerance) and triplosensitivity (i.e., duplication intolerance) throughout the human genome. We harmonized and meta-analyzed rCNVs from nearly one million individuals to construct a genome-wide catalog of dosage sensitivity across 54 disorders, which defined 163 dosage sensitive segments associated with at least one disorder. These segments were typically gene dense and often harbored dominant dosage sensitive driver genes, which we were able to prioritize using statistical fine-mapping. Finally, we designed an ensemble machine-learning model to predict probabilities of dosage sensitivity (pHaplo & pTriplo) for all autosomal genes, which identified 2,987 haploinsufficient and 1,559 triplosensitive genes, including 648 that were uniquely triplosensitive. This dosage sensitivity resource will provide broad utility for human disease research and clinical genetics.
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Affiliation(s)
- Ryan L Collins
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA; Program in Medical and Population Genetics, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142, USA; Division of Medical Sciences and Department of Medicine, Harvard Medical School, Boston, MA 02115, USA.
| | - Joseph T Glessner
- Department of Pediatrics, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA; Department of Pediatrics, Division of Human Genetics, Perelman School of Medicine, Philadelphia, PA 19104, USA
| | - Eleonora Porcu
- Center for Integrative Genomics, University of Lausanne, 1015 Lausanne, Switzerland; Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland
| | - Maarja Lepamets
- Estonian Genome Centre, Institute of Genomics, University of Tartu, 51010 Tartu, Estonia; Institute of Molecular and Cell Biology, University of Tartu, 51010 Tartu, Estonia
| | | | | | - Lide Han
- Division of Genetic Medicine, Department of Medicine, and Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Theodore Morley
- Division of Genetic Medicine, Department of Medicine, and Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | | | - Jacob Ulirsch
- Program in Medical and Population Genetics, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142, USA; Division of Medical Sciences and Department of Medicine, Harvard Medical School, Boston, MA 02115, USA; Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Selin Everett
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA; Program in Medical and Population Genetics, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142, USA
| | - Daniel P Howrigan
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA; Program in Medical and Population Genetics, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142, USA; Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Philip M Boone
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA; Program in Medical and Population Genetics, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142, USA; Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA; Division of Genetics and Genomics, Boston Children's Hospital, Boston, MA 02115, USA
| | - Jack Fu
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA; Program in Medical and Population Genetics, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142, USA; Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| | - Konrad J Karczewski
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA; Program in Medical and Population Genetics, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142, USA; Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Georgios Kellaris
- Advanced Center for Translational and Genetic Medicine, Stanley Manne Children's Research Institute, Lurie Children's Hospital, Chicago, IL 60611, USA; Departments of Pediatrics and Cell and Developmental Biology, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA
| | - Chelsea Lowther
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA; Program in Medical and Population Genetics, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142, USA; Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| | - Diane Lucente
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Kiana Mohajeri
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA; Program in Medical and Population Genetics, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142, USA; Division of Medical Sciences and Department of Medicine, Harvard Medical School, Boston, MA 02115, USA
| | - Margit Nõukas
- Estonian Genome Centre, Institute of Genomics, University of Tartu, 51010 Tartu, Estonia; Institute of Molecular and Cell Biology, University of Tartu, 51010 Tartu, Estonia
| | - Xander Nuttle
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA; Program in Medical and Population Genetics, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142, USA; Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| | - Kaitlin E Samocha
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA; Program in Medical and Population Genetics, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142, USA; Division of Medical Sciences and Department of Medicine, Harvard Medical School, Boston, MA 02115, USA; Human Genetics Programme, Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10, UK
| | - Mi Trinh
- Human Genetics Programme, Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10, UK
| | - Farid Ullah
- Advanced Center for Translational and Genetic Medicine, Stanley Manne Children's Research Institute, Lurie Children's Hospital, Chicago, IL 60611, USA; Departments of Pediatrics and Cell and Developmental Biology, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA
| | - Urmo Võsa
- Estonian Genome Centre, Institute of Genomics, University of Tartu, 51010 Tartu, Estonia
| | | | | | - Matthew E Hurles
- Human Genetics Programme, Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10, UK
| | | | - Erica E Davis
- Advanced Center for Translational and Genetic Medicine, Stanley Manne Children's Research Institute, Lurie Children's Hospital, Chicago, IL 60611, USA; Departments of Pediatrics and Cell and Developmental Biology, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA
| | - Hilary Finucane
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA; Program in Medical and Population Genetics, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142, USA; Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA
| | - James F Gusella
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA; Program in Medical and Population Genetics, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142, USA
| | | | - Nicholas Katsanis
- Advanced Center for Translational and Genetic Medicine, Stanley Manne Children's Research Institute, Lurie Children's Hospital, Chicago, IL 60611, USA; Departments of Pediatrics and Cell and Developmental Biology, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA
| | | | - Benjamin M Neale
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA; Program in Medical and Population Genetics, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142, USA; Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA
| | | | | | - Jennelle C Hodge
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN 46202, USA
| | - Dennis Lal
- Cologne Center for Genomics, University of Cologne, 51149 Cologne, Germany; Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, OH 44195, USA; Epilepsy Center, Neurological Institute, Cleveland Clinic, Cleveland, OH 44195, USA
| | - Douglas M Ruderfer
- Division of Genetic Medicine, Department of Medicine, and Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN 37232, USA; Center for Precision Medicine, Department of Biomedical Informatics, and Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | | | - Reedik Mägi
- Estonian Genome Centre, Institute of Genomics, University of Tartu, 51010 Tartu, Estonia
| | - Tõnu Esko
- Estonian Genome Centre, Institute of Genomics, University of Tartu, 51010 Tartu, Estonia
| | - Alexandre Reymond
- Center for Integrative Genomics, University of Lausanne, 1015 Lausanne, Switzerland
| | - Zoltán Kutalik
- Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland; Center for Primary Care and Public Health, University of Lausanne, 1015 Lausanne, Switzerland; Department of Computational Biology, University of Lausanne, 1015 Lausanne, Switzerland
| | - Hakon Hakonarson
- Department of Pediatrics, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA; Department of Pediatrics, Division of Human Genetics, Perelman School of Medicine, Philadelphia, PA 19104, USA
| | - Shamil Sunyaev
- Program in Medical and Population Genetics, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142, USA; Division of Medical Sciences and Department of Medicine, Harvard Medical School, Boston, MA 02115, USA; Division of Genetics, Brigham and Women's Hospital, Boston, MA 02115, USA
| | - Harrison Brand
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA; Program in Medical and Population Genetics, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142, USA; Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA; Pediatric Surgical Research Laboratories, Massachusetts General Hospital, Boston, MA 02114, USA.
| | - Michael E Talkowski
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA; Program in Medical and Population Genetics, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142, USA; Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA; Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA.
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11
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Drackley A, Brew C, Wlodaver A, Spencer S, Leuer K, Rathbun P, Charrow J, Wieneke X, Lee Yap K, Ing A. Utility and Outcomes of the 2019 American College of Medical Genetics and Genomics-Clinical Genome Resource Guidelines for Interpretation of Copy Number Variants with Borderline Classifications at an Academic Clinical Diagnostic Laboratory. J Mol Diagn 2022; 24:1100-1111. [PMID: 35868509 DOI: 10.1016/j.jmoldx.2022.06.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2022] [Revised: 06/06/2022] [Accepted: 06/27/2022] [Indexed: 11/26/2022] Open
Abstract
In 2019, American College of Medical Genetics and Genomics and the Clinical Genome Resource published updated technical standards for the interpretation and reporting of copy number variants (CNVs), introducing a semiquantitative classification system that aims to foster greater standardization and consistency between laboratories. Evaluation of these guidelines' performance will inform laboratories about the impact of their implementation into clinical practice. A total of 145 difficult-to-classify CNVs, originally assessed by an academic molecular diagnostic laboratory, were re-interpreted/classified according to the American College of Medical Genetics and Genomics-Clinical Genome Resource guidelines. Classifications between interpretation systems were then compared. The concordance rate was 60.7%, and significantly more variants of uncertain significance were obtained when using the guidelines (n = 98) versus the laboratory's classification system (n = 49; P < 0.001). The concordance rate was presumably impacted by the intentionally unclear nature of the selected variants. The difference in variant of uncertain significance rate was largely due to laboratory-specific practices for variant interpretation and reporting, as well as differences in utilization of general population data. Laboratory-specific policies and practices may need to be addressed for true standardization to be achieved. Challenges to consistent guideline utilization are centered around the general lack of high-quality curated data available for CNV interpretations and the inherent subjectivity in the selection of evidence criteria and application of evidence points. Multiple aspects of the guidelines were highlighted as potential opportunities for subsequent refinements to further improve classification standardization.
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Affiliation(s)
- Andy Drackley
- Department of Pathology and Laboratory Medicine, Ann & Robert H. Lurie Children's Hospital of Chicago, Chicago, Illinois; Center for Genomics, Ann & Robert H. Lurie Children's Hospital of Chicago, Chicago, Illinois; Division of Genetics, Birth Defects and Metabolism, Ann & Robert H. Lurie Children's Hospital of Chicago, Chicago, Illinois; Northwestern University Feinberg School of Medicine, Chicago, Illinois
| | - Casey Brew
- Department of Pathology and Laboratory Medicine, Ann & Robert H. Lurie Children's Hospital of Chicago, Chicago, Illinois; Center for Genomics, Ann & Robert H. Lurie Children's Hospital of Chicago, Chicago, Illinois; Division of Genetics, Birth Defects and Metabolism, Ann & Robert H. Lurie Children's Hospital of Chicago, Chicago, Illinois; Northwestern University Feinberg School of Medicine, Chicago, Illinois
| | - Alissa Wlodaver
- Department of Pathology and Laboratory Medicine, Ann & Robert H. Lurie Children's Hospital of Chicago, Chicago, Illinois; Center for Genomics, Ann & Robert H. Lurie Children's Hospital of Chicago, Chicago, Illinois
| | - Sara Spencer
- Department of Obstetrics and Gynecology, Northwestern Medicine, Chicago, Illinois; Northwestern University Feinberg School of Medicine, Chicago, Illinois
| | - Katrin Leuer
- Department of Pathology and Laboratory Medicine, Ann & Robert H. Lurie Children's Hospital of Chicago, Chicago, Illinois; Center for Genomics, Ann & Robert H. Lurie Children's Hospital of Chicago, Chicago, Illinois; Northwestern University Feinberg School of Medicine, Chicago, Illinois
| | - Pamela Rathbun
- Department of Pathology and Laboratory Medicine, Ann & Robert H. Lurie Children's Hospital of Chicago, Chicago, Illinois; Center for Genomics, Ann & Robert H. Lurie Children's Hospital of Chicago, Chicago, Illinois; Northwestern University Feinberg School of Medicine, Chicago, Illinois
| | - Joel Charrow
- Department of Pathology and Laboratory Medicine, Ann & Robert H. Lurie Children's Hospital of Chicago, Chicago, Illinois; Division of Genetics, Birth Defects and Metabolism, Ann & Robert H. Lurie Children's Hospital of Chicago, Chicago, Illinois; Northwestern University Feinberg School of Medicine, Chicago, Illinois
| | - Xuwen Wieneke
- Department of Pathology and Laboratory Medicine, Ann & Robert H. Lurie Children's Hospital of Chicago, Chicago, Illinois; Center for Genomics, Ann & Robert H. Lurie Children's Hospital of Chicago, Chicago, Illinois
| | - Kai Lee Yap
- Department of Pathology and Laboratory Medicine, Ann & Robert H. Lurie Children's Hospital of Chicago, Chicago, Illinois; Center for Genomics, Ann & Robert H. Lurie Children's Hospital of Chicago, Chicago, Illinois; Northwestern University Feinberg School of Medicine, Chicago, Illinois.
| | - Alexander Ing
- Department of Pathology and Laboratory Medicine, Ann & Robert H. Lurie Children's Hospital of Chicago, Chicago, Illinois; Center for Genomics, Ann & Robert H. Lurie Children's Hospital of Chicago, Chicago, Illinois; Division of Genetics, Birth Defects and Metabolism, Ann & Robert H. Lurie Children's Hospital of Chicago, Chicago, Illinois; Northwestern University Feinberg School of Medicine, Chicago, Illinois.
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12
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Zhang K, Lin G, Han D, Han Y, Peng R, Li J. Adaptation of ACMG-ClinGen Technical Standards for Copy Number Variant Interpretation Concordance. Front Genet 2022; 13:829728. [PMID: 35360839 PMCID: PMC8960312 DOI: 10.3389/fgene.2022.829728] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2021] [Accepted: 01/24/2022] [Indexed: 12/18/2022] Open
Abstract
This study aimed to evaluate inter-laboratory classification concordance for copy number variants (CNVs) with a semiquantitative point-based scoring metric recommended by the American College of Medical Genetics and Genomics (ACMG) and Clinical Genome Resources (ClinGen). A total of 234 CNVs distributed by the National Center of Clinical Laboratories (NCCLs), and 72 CNVs submitted by different laboratories, were distributed to nine clinical laboratories performing routine clinical CNV testing in China and independently classified across laboratories. The overall inter-laboratory complete classification concordance rate of the 234 distributed CNVs increased from 18% (41/234) to 76% (177/234) using the scoring metric compared to the laboratory's previous method. The overall inter-laboratory complete classification concordance rate of the 72 submitted CNVs was 65% (47/72) using the scoring metrics. The 82 variants that initially did not reach complete concordance classification and 1 additional CNV deletion were reviewed; 34 reached complete agreement, and the overall post-review complete concordance rate was 85% (260/306). Additionally, the overall percentage of classification discordance possibly impacting medical management [i.e., pathogenic (P) or likely pathogenic (LP) vs. variant of uncertain significance (VUS)] was 11% (35/306). The causes of initial and final discordance in the classification were identified. The ACMG-ClinGen framework has promoted consistency in interpreting the clinical significance of CNVs. Continuous training among laboratories, further criteria and additional clarification of the standards, sharing classifications and supporting evidence through public database, and ongoing work for dosage sensitive genes/regions curation will be beneficial for harmonization of CNVs classification.
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13
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Benet-Pagès A, Rosenbloom KR, Nassar LR, Lee CM, Raney BJ, Clawson H, Schmelter D, Casper J, Gonzalez JN, Perez G, Lee BT, Zweig AS, James Kent W, Haeussler M, Kuhn RM. Variant Interpretation: UCSC Genome Browser Recommended Track Sets. Hum Mutat 2022; 43:998-1011. [PMID: 35088925 PMCID: PMC9288501 DOI: 10.1002/humu.24335] [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: 05/22/2021] [Revised: 11/30/2021] [Accepted: 01/25/2022] [Indexed: 11/11/2022]
Abstract
The UCSC Genome Browser has been an important tool for genomics and clinical genetics since the sequence of the human genome was first released in 2000. As it has grown in scope to display more types of data it has also grown more complicated. The data, which are dispersed at many locations worldwide, are collected into one view on the Browser, where the graphical interface presents the data in one location. This supports the expertise of the researcher to interpret variants in the genome. Because the analysis of Single Nucleotide Variants (SNVs) and Copy Number Variants (CNVs) require interpretation of data at very different genomic scales, different data resources are required. We present here several Recommended Track Sets designed to facilitate the interpretation of variants in the clinic, offering quick access to datasets relevant to the appropriate scale. This article is protected by copyright. All rights reserved.
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Affiliation(s)
- Anna Benet-Pagès
- Genomics Institute, University of California Santa Cruz, Santa Cruz, CA, 95064, USA.,Medical Genetics Center (MGZ), Munich, Germany
| | - Kate R Rosenbloom
- Genomics Institute, University of California Santa Cruz, Santa Cruz, CA, 95064, USA
| | - Luis R Nassar
- Genomics Institute, University of California Santa Cruz, Santa Cruz, CA, 95064, USA
| | - Christopher M Lee
- Genomics Institute, University of California Santa Cruz, Santa Cruz, CA, 95064, USA
| | - Brian J Raney
- Genomics Institute, University of California Santa Cruz, Santa Cruz, CA, 95064, USA
| | - Hiram Clawson
- Genomics Institute, University of California Santa Cruz, Santa Cruz, CA, 95064, USA
| | - Daniel Schmelter
- Genomics Institute, University of California Santa Cruz, Santa Cruz, CA, 95064, USA
| | - Jonathan Casper
- Genomics Institute, University of California Santa Cruz, Santa Cruz, CA, 95064, USA
| | | | - Gerardo Perez
- Genomics Institute, University of California Santa Cruz, Santa Cruz, CA, 95064, USA
| | - Brian T Lee
- Genomics Institute, University of California Santa Cruz, Santa Cruz, CA, 95064, USA
| | - Ann S Zweig
- Genomics Institute, University of California Santa Cruz, Santa Cruz, CA, 95064, USA
| | - W James Kent
- Genomics Institute, University of California Santa Cruz, Santa Cruz, CA, 95064, USA
| | | | - Robert M Kuhn
- Genomics Institute, University of California Santa Cruz, Santa Cruz, CA, 95064, USA
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14
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Wang Z, Guo Y, Liu S, Meng Q. Genome-Wide Assessment Characteristics of Genes Overlapping Copy Number Variation Regions in Duroc Purebred Population. Front Genet 2021; 12:753748. [PMID: 34721540 PMCID: PMC8552909 DOI: 10.3389/fgene.2021.753748] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2021] [Accepted: 09/23/2021] [Indexed: 11/13/2022] Open
Abstract
Copy number variations (CNVs) are important structural variations that can cause significant phenotypic diversity. Reliable CNVs mapping can be achieved by identification of CNVs from different genetic backgrounds. Investigations on the characteristics of overlapping between CNV regions (CNVRs) and protein-coding genes (CNV genes) or miRNAs (CNV-miRNAs) can reveal the potential mechanisms of their regulation. In this study, we used 50 K SNP arrays to detect CNVs in Duroc purebred pig. A total number of 211 CNVRs were detected with a total length of 118.48 Mb, accounting for 5.23% of the autosomal genome sequence. Of these CNVRs, 32 were gains, 175 losses, and four contained both types (loss and gain within the same region). The CNVRs we detected were non-randomly distributed in the swine genome and were significantly enriched in the segmental duplication and gene density region. Additionally, these CNVRs were overlapping with 1,096 protein-coding genes (CNV-genes), and 39 miRNAs (CNV-miRNAs), respectively. The CNV-genes were enriched in terms of dosage-sensitive gene list. The expression of the CNV genes was significantly higher than that of the non-CNV genes in the adult Duroc prostate. Of all detected CNV genes, 22.99% genes were tissue-specific (TSI > 0.9). Strong negative selection had been underway in the CNV-genes as the ones that were located entirely within the loss CNVRs appeared to be evolving rapidly as determined by the median dN plus dS values. Non-CNV genes tended to be miRNA target than CNV-genes. Furthermore, CNV-miRNAs tended to target more genes compared to non-CNV-miRNAs, and a combination of two CNV-miRNAs preferentially synergistically regulated the same target genes. We also focused our efforts on examining CNV genes and CNV-miRNAs functions, which were also involved in the lipid metabolism, including DGAT1, DGAT2, MOGAT2, miR143, miR335, and miRLET7. Further molecular experiments and independent large studies are needed to confirm our findings.
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Affiliation(s)
- Zhipeng Wang
- College of Animal Science and Technology, Northeast Agricultural University, Harbin, China.,Bioinformatics Center, Northeast Agricultural University, Harbin, China
| | - Yuanyuan Guo
- College of Animal Science and Technology, Northeast Agricultural University, Harbin, China.,Bioinformatics Center, Northeast Agricultural University, Harbin, China
| | - Shengwei Liu
- College of Animal Science and Technology, Northeast Agricultural University, Harbin, China.,Bioinformatics Center, Northeast Agricultural University, Harbin, China
| | - Qingli Meng
- Beijing Breeding Swine Center, Beijing, China
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15
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Thaxton C, Good ME, DiStefano MT, Luo X, Andersen EF, Thorland E, Berg J, Martin CL, Rehm HL, Riggs ER. Utilizing ClinGen gene-disease validity and dosage sensitivity curations to inform variant classification. Hum Mutat 2021; 43:1031-1040. [PMID: 34694049 PMCID: PMC9035475 DOI: 10.1002/humu.24291] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2021] [Revised: 10/12/2021] [Accepted: 10/19/2021] [Indexed: 11/05/2022]
Abstract
Understanding whether there is enough evidence to implicate a gene's role in a given disease, as well as the mechanisms by which variants in this gene might cause this disease, is essential to determine clinical relevance. The National Institutes of Health-funded Clinical Genome Resource (ClinGen) has developed evaluation frameworks to assess both the strength of evidence supporting a relationship between a gene and disease (gene-disease validity), and whether loss (haploinsufficiency) or gain (triplosensitivity) of individual genes or genomic regions is a mechanism for disease (dosage sensitivity). ClinGen actively applies these frameworks across multiple disease domains, and makes this information publicly available via its website (https://www.clinicalgenome.org/) for use in multiple applications, including clinical variant classification. Here, we describe how the results of these curation processes can be utilized to inform the appropriate application of pathogenicity criteria for both sequence and copy number variants, as well as to guide test development and inform genomic filtering pipelines.
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Affiliation(s)
- Courtney Thaxton
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Molly E Good
- Autism & Developmental Medicine Institute, Geisinger, Danville, Pennsylvania, USA
| | | | - Xi Luo
- Department of Pediatric/Hematology-Oncology, Baylor College of Medicine, Houston, Texas, USA
| | - Erica F Andersen
- Department of Pathology, University of Utah, Salt Lake City, Utah, USA.,ARUP Laboratories, Salt Lake City, Utah, USA
| | - Erik Thorland
- Genomics Laboratory, Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota, USA
| | - Jonathan Berg
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Christa Lese Martin
- Autism & Developmental Medicine Institute, Geisinger, Danville, Pennsylvania, USA
| | - Heidi L Rehm
- Broad Center for Mendelian Genomics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
| | - Erin R Riggs
- Autism & Developmental Medicine Institute, Geisinger, Danville, Pennsylvania, USA
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16
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Fan C, Wang Z, Sun Y, Sun J, Liu X, Kang L, Xu Y, Yang M, Dai W, Song L, Wei X, Xiang J, Huang H, Zhou M, Zeng F, Huang L, Xu Z, Peng Z. AutoCNV: a semiautomatic CNV interpretation system based on the 2019 ACMG/ClinGen Technical Standards for CNVs. BMC Genomics 2021; 22:721. [PMID: 34615484 PMCID: PMC8496072 DOI: 10.1186/s12864-021-08011-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2021] [Accepted: 09/08/2021] [Indexed: 11/24/2022] Open
Abstract
Background The American College of Medical Genetics and Genomics (ACMG) and the Clinical Genome Resource (ClinGen) presented technical standards for interpretation and reporting of constitutional copy-number variants in 2019 (the standards). Although ClinGen developed a web-based CNV classification calculator based on scoring metrics, it can only track and tally points that have been assigned based on observed evidence. Here, we developed AutoCNV (a semiautomatic automated CNV interpretation system) based on the standards, which can automatically generate predictions on 18 and 16 criteria for copy number loss and gain, respectively. Results We assessed the performance of AutoCNV using 72 CNVs evaluated by external independent reviewers and 20 illustrative case examples. Using AutoCNV, it showed that 100 % (72/72) and 95 % (19/20) of CNVs were consistent with the reviewers’ and ClinGen-verified classifications, respectively. AutoCNV only required an average of less than 5 milliseconds to obtain the result for one CNV with automated scoring. We also applied AutoCNV for the interpretation of CNVs from the ClinVar database and the dbVar database. We also developed a web-based version of AutoCNV (wAutoCNV). Conclusions AutoCNV may serve to assist users in conducting in-depth CNV interpretation, to accelerate and facilitate the interpretation process of CNVs and to improve the consistency and reliability of CNV interpretation. Supplementary Information The online version contains supplementary material available at 10.1186/s12864-021-08011-4.
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Affiliation(s)
- Chunna Fan
- College of Life Sciences, University of Chinese Academy of Sciences, 100049, Beijing, China.,Tianjin Medical Laboratory, BGI-Tianjin, BGI-Shenzhen, 300308, Tianjin, China.,Binhai Genomics Institute, BGI-Tianjin, BGI-Shenzhen, 300308, Tianjin, China
| | - Zhonghua Wang
- Tianjin Medical Laboratory, BGI-Tianjin, BGI-Shenzhen, 300308, Tianjin, China.,Binhai Genomics Institute, BGI-Tianjin, BGI-Shenzhen, 300308, Tianjin, China
| | - Yan Sun
- BGI Genomics, BGI-Shenzhen, 518083, Shenzhen, China
| | - Jun Sun
- Tianjin Medical Laboratory, BGI-Tianjin, BGI-Shenzhen, 300308, Tianjin, China.,Binhai Genomics Institute, BGI-Tianjin, BGI-Shenzhen, 300308, Tianjin, China
| | - Xi Liu
- Tianjin Medical Laboratory, BGI-Tianjin, BGI-Shenzhen, 300308, Tianjin, China.,Binhai Genomics Institute, BGI-Tianjin, BGI-Shenzhen, 300308, Tianjin, China
| | - Licheng Kang
- Tianjin Medical Laboratory, BGI-Tianjin, BGI-Shenzhen, 300308, Tianjin, China.,Binhai Genomics Institute, BGI-Tianjin, BGI-Shenzhen, 300308, Tianjin, China
| | - Yingshuo Xu
- Tianjin Medical Laboratory, BGI-Tianjin, BGI-Shenzhen, 300308, Tianjin, China.,Binhai Genomics Institute, BGI-Tianjin, BGI-Shenzhen, 300308, Tianjin, China
| | - Manqiu Yang
- Tianjin Medical Laboratory, BGI-Tianjin, BGI-Shenzhen, 300308, Tianjin, China.,Binhai Genomics Institute, BGI-Tianjin, BGI-Shenzhen, 300308, Tianjin, China
| | - Wentao Dai
- Tianjin Medical Laboratory, BGI-Tianjin, BGI-Shenzhen, 300308, Tianjin, China.,Binhai Genomics Institute, BGI-Tianjin, BGI-Shenzhen, 300308, Tianjin, China
| | - Lijie Song
- Tianjin Medical Laboratory, BGI-Tianjin, BGI-Shenzhen, 300308, Tianjin, China.,Binhai Genomics Institute, BGI-Tianjin, BGI-Shenzhen, 300308, Tianjin, China
| | - Xiaoming Wei
- BGI-Wuhan Clinical Laboratories, BGI-Shenzhen, 490079, Wuhan, China
| | - Jiale Xiang
- BGI Genomics, BGI-Shenzhen, 518083, Shenzhen, China
| | - Hui Huang
- BGI Genomics, BGI-Shenzhen, 518083, Shenzhen, China
| | - Meizhen Zhou
- BGI Genomics, BGI-Shenzhen, 518083, Shenzhen, China
| | - Fanwei Zeng
- BGI Genomics, BGI-Shenzhen, 518083, Shenzhen, China.,Department of Biology, Faculty of Science, University of Copenhagen, DK-2200, Copenhagen, Denmark
| | - Lin Huang
- BGI Genomics, BGI-Shenzhen, 518083, Shenzhen, China
| | - Zhengfeng Xu
- State Key Laboratory of Reproductive Medicine, Department of Prenatal Diagnosis, Women's Hospital of Nanjing Medical University, Nanjing Maternity and Child Health Care Hospital, 210004, Nanjing, China.
| | - Zhiyu Peng
- BGI Genomics, BGI-Shenzhen, 518083, Shenzhen, China.
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17
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Strunz T, Kellner M, Kiel C, Weber BHF. Assigning Co-Regulated Human Genes and Regulatory Gene Clusters. Cells 2021; 10:2395. [PMID: 34572044 PMCID: PMC8470523 DOI: 10.3390/cells10092395] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2021] [Revised: 08/30/2021] [Accepted: 09/10/2021] [Indexed: 12/12/2022] Open
Abstract
Elucidating the role of genetic variation in the regulation of gene expression is key to understanding the pathobiology of complex diseases which, in consequence, is crucial in devising targeted treatment options. Expression quantitative trait locus (eQTL) analysis correlates a genetic variant with the strength of gene expression, thus defining thousands of regulated genes in a multitude of human cell types and tissues. Some eQTL may not act independently of each other but instead may be regulated in a coordinated fashion by seemingly independent genetic variants. To address this issue, we combined the approaches of eQTL analysis and colocalization studies. Gene expression was determined in datasets comprising 49 tissues from the Genotype-Tissue Expression (GTEx) project. From about 33,000 regulated genes, over 14,000 were found to be co-regulated in pairs and were assembled across all tissues to almost 15,000 unique clusters containing up to nine regulated genes affected by the same eQTL signal. The distance of co-regulated eGenes was, on average, 112 kilobase pairs. Of 713 genes known to express clinical symptoms upon haploinsufficiency, 231 (32.4%) are part of at least one of the identified clusters. This calls for caution should treatment approaches aim at an upregulation of a haploinsufficient gene. In conclusion, we present an unbiased approach to identifying co-regulated genes in and across multiple tissues. Knowledge of such common effects is crucial to appreciate implications on biological pathways involved, specifically when a treatment option targets a co-regulated disease gene.
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Affiliation(s)
- Tobias Strunz
- Institute of Human Genetics, University of Regensburg, 93053 Regensburg, Germany; (T.S.); (M.K.); (C.K.)
| | - Martin Kellner
- Institute of Human Genetics, University of Regensburg, 93053 Regensburg, Germany; (T.S.); (M.K.); (C.K.)
| | - Christina Kiel
- Institute of Human Genetics, University of Regensburg, 93053 Regensburg, Germany; (T.S.); (M.K.); (C.K.)
| | - Bernhard H. F. Weber
- Institute of Human Genetics, University of Regensburg, 93053 Regensburg, Germany; (T.S.); (M.K.); (C.K.)
- Institute of Clinical Human Genetics, University Hospital Regensburg, 93053 Regensburg, Germany
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18
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Chromosomal microarray analysis, including constitutional and neoplastic disease applications, 2021 revision: a technical standard of the American College of Medical Genetics and Genomics (ACMG). Genet Med 2021; 23:1818-1829. [PMID: 34131312 DOI: 10.1038/s41436-021-01214-w] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2021] [Revised: 05/04/2021] [Accepted: 05/04/2021] [Indexed: 11/08/2022] Open
Abstract
Chromosomal microarray technologies, including array comparative genomic hybridization and single-nucleotide polymorphism array, are widely applied in the diagnostic evaluation for both constitutional and neoplastic disorders. In a constitutional setting, this technology is accepted as the first-tier test for the evaluation of chromosomal imbalances associated with intellectual disability, autism, and/or multiple congenital anomalies. Furthermore, chromosomal microarray analysis is recommended for patients undergoing invasive prenatal diagnosis with one or more major fetal structural abnormalities identified by ultrasonographic examination, and in the evaluation of intrauterine fetal demise or stillbirth when further cytogenetic analysis is desired. This technology also provides important genomic data in the diagnosis, prognosis, and therapy of neoplastic disorders, including both hematologic malignancies and solid tumors. To assist clinical laboratories in the validation of chromosomal microarray methodologies for constitutional and neoplastic applications, the American College of Medical Genetics and Genomics (ACMG) Laboratory Quality Assurance Committee has developed these updated technical laboratory standards, which replace the ACMG technical standards and guidelines for microarray analysis in constitutional and neoplastic disorders previously published in 2013.
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19
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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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20
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Marcou CA, Pitel B, Hagen CE, Boczek NJ, Rowsey RA, Baughn LB, Hoppman NL, Thorland EC, Kearney HM. Limited diagnostic impact of duplications <1 Mb of uncertain clinical significance: a 10-year retrospective analysis of reporting practices at the Mayo Clinic. Genet Med 2020; 22:2120-2124. [PMID: 32820244 DOI: 10.1038/s41436-020-0932-0] [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: 03/11/2020] [Revised: 07/26/2020] [Accepted: 07/28/2020] [Indexed: 11/09/2022] Open
Abstract
PURPOSE Copy-number variants (CNVs) of uncertain clinical significance are routinely reported in a clinical setting only when exceeding predetermined reporting thresholds, typically based on CNV size. Given that very few genes are associated with triplosensitive phenotypes, it is not surprising that many interstitial duplications <1 Mb are found to be inherited and anticipated to be of limited or no clinical significance. METHODS In an effort to further refine our reporting criteria to maximize diagnostic yield while minimizing the return of uncertain variants, we performed a retrospective analysis of all clinical microarray cases reported in a 10-year window. A total of 1112 reported duplications had parental follow-up, and these were compared by size, RefSeq gene content, and inheritance pattern. De novo origin was used as a rough proxy for pathogenicity. RESULTS Approximately 6% of duplications 500 kb-1 Mb were de novo observations, compared with approximately 14% for 1-2 Mb duplications (p = 0.0005). On average, de novo duplications had higher gene counts than inherited duplications. CONCLUSION Our data reveal limited diagnostic utility for duplications of uncertain significance <1 Mb. Considerations for revised reporting criteria are discussed and are applicable to CNVs detected by any genome-wide exploratory methodology, including exome/genome sequencing.
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Affiliation(s)
- Cherisse A Marcou
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA.
| | - Beth Pitel
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
| | - Clinton E Hagen
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | - Nicole J Boczek
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
| | - Ross A Rowsey
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
| | - Linda B Baughn
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
| | - Nicole L Hoppman
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
| | - Erik C Thorland
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
| | - Hutton M Kearney
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
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21
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Qiao L, Wynn J, Yu L, Hernan R, Zhou X, Duron V, Aspelund G, Farkouh-Karoleski C, Zygumunt A, Krishnan US, Nees S, Khlevner J, Lim FY, Crombleholme T, Cusick R, Azarow K, Danko ME, Chung D, Warner BW, Mychaliska GB, Potoka D, Wagner AJ, Soffer S, Schindel D, McCulley DJ, Shen Y, Chung WK. Likely damaging de novo variants in congenital diaphragmatic hernia patients are associated with worse clinical outcomes. Genet Med 2020; 22:2020-2028. [PMID: 32719394 PMCID: PMC7710626 DOI: 10.1038/s41436-020-0908-0] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2019] [Revised: 07/06/2020] [Accepted: 07/08/2020] [Indexed: 11/29/2022] Open
Abstract
Purpose Congenital diaphragmatic hernia (CDH) is associated with significant mortality and long-term morbidity in some but not all individuals. We hypothesize monogenic factors that cause CDH are likely to have pleiotropic effects and be associated with worse clinical outcomes. Methods We enrolled and prospectively followed 647 newborns with CDH and performed genomic sequencing on 462 trios to identify de novo variants. We grouped cases into those with and without likely damaging (LD) variants and systematically assessed CDH clinical outcomes between the genetic groups. Results Complex cases with additional congenital anomalies had higher mortality than isolated cases (P=8×10−6). Isolated cases with LD variants had similar mortality to complex cases and much higher mortality than isolated cases without LD (P=3×10−3). The trend was similar with pulmonary hypertension at 1 month. Cases with LD variants had an estimated 12–17 points lower scores on neurodevelopmental assessments at 2 years compared to cases without LD variants, and this difference is similar in isolated and complex cases. Conclusion We found that the LD genetic variants are associated with higher mortality, worse pulmonary hypertension, and worse neurodevelopment outcomes compared to non-LD variants. Our results have important implications for prognosis, potential intervention and long-term follow up for children with CDH.
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Affiliation(s)
- Lu Qiao
- Department of Pediatrics, Columbia University Irving Medical Center, New York, NY, USA.,Department of Systems Biology, Columbia University Irving Medical Center, New York, NY, USA
| | - Julia Wynn
- Department of Pediatrics, Columbia University Irving Medical Center, New York, NY, USA
| | - Lan Yu
- Department of Pediatrics, Columbia University Irving Medical Center, New York, NY, USA
| | - Rebecca Hernan
- Department of Pediatrics, Columbia University Irving Medical Center, New York, NY, USA
| | - Xueya Zhou
- Department of Pediatrics, Columbia University Irving Medical Center, New York, NY, USA.,Department of Systems Biology, Columbia University Irving Medical Center, New York, NY, USA
| | - Vincent Duron
- Department of Surgery, Columbia University Irving Medical Center, New York, NY, USA
| | - Gudrun Aspelund
- Department of Surgery, Columbia University Irving Medical Center, New York, NY, USA
| | | | - Annette Zygumunt
- Department of Pediatrics, Columbia University Irving Medical Center, New York, NY, USA
| | - Usha S Krishnan
- Department of Pediatrics, Columbia University Irving Medical Center, New York, NY, USA
| | - Shannon Nees
- Department of Pediatrics, Columbia University Irving Medical Center, New York, NY, USA
| | - Julie Khlevner
- Department of Pediatrics, Columbia University Irving Medical Center, New York, NY, USA
| | | | | | - Robert Cusick
- Children's Hospital & Medical Center of Omaha, University of Nebraska College of Medicine, Omaha, NE, USA
| | - Kenneth Azarow
- Department of Surgery, Oregon Health & Science University, Portland, OR, USA
| | - Melissa Ellen Danko
- Monroe Carell Jr. Children's Hospital, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Dai Chung
- Monroe Carell Jr. Children's Hospital, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Brad W Warner
- Washington University, St. Louis Children's Hospital, St. Louis, MO, USA
| | - George B Mychaliska
- Division of Pediatric Surgery, Department of Surgery, University of Michigan School of Medicine, Ann Arbor, MI, USA
| | - Douglas Potoka
- Division of Pediatric Surgery, Department of Surgery, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Amy J Wagner
- Medical College of Wisconsin, Milwaukee, WI, USA
| | - Samuel Soffer
- Department of Surgery, Northwell Health, Great Neck, NY, USA
| | - David Schindel
- Children's Health Dallas, UT Southwestern Medical Center, Dallas, TX, USA
| | - David J McCulley
- Department of Pediatrics, University of Wisconsin-Madison, Madison, WI, USA
| | - Yufeng Shen
- Department of Systems Biology, Columbia University Irving Medical Center, New York, NY, USA. .,Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY, USA. .,JP Sulzberger Columbia Genome Center, Columbia University Irving Medical Center, New York, NY, USA.
| | - Wendy K Chung
- Department of Pediatrics, Columbia University Irving Medical Center, New York, NY, USA. .,Department of Medicine, Columbia University Irving Medical Center, New York, NY, USA. .,Herbert Irving Comprehensive Cancer Center, Columbia University Irving Medical Center, New York, NY, USA.
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22
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Harrison SM, Biesecker LG, Rehm HL. Overview of Specifications to the ACMG/AMP Variant Interpretation Guidelines. ACTA ACUST UNITED AC 2020; 103:e93. [PMID: 31479589 DOI: 10.1002/cphg.93] [Citation(s) in RCA: 64] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
The 2015 ACMG/AMP guidelines established a classification system for sequence variants; however, the broad scope of these guidelines necessitates specification of evidence types for specific genes or diseases of interest. Since publication of the guidelines, both general use and disease-focused specifications have emerged to aid in accurate application of ACMG/AMP evidence types. This article summarizes the approaches to, and rationale for, specifying three evidence categories (population frequency data, variant type and location, and case-level data), including available resources and a quantitative framework that can inform the specification process. © 2019 by John Wiley & Sons, Inc.
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Affiliation(s)
- Steven M Harrison
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts.,Department of Pathology, Harvard Medical School, Boston, Massachusetts
| | - Leslie G Biesecker
- Medical Genomics and Metabolic Genetics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland
| | - Heidi L Rehm
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts.,Department of Pathology, Harvard Medical School, Boston, Massachusetts.,Center for Genomic Medicine, Massachusetts General Hospital, Boston, Massachusetts
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23
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Yang X, Yang D, Deng Q, Fang F, Han J, Zhen L, Li D, Liao C. Risk factors associated with fetal pleural effusion in prenatal diagnosis: a retrospective study in a single institute in Southern China. J OBSTET GYNAECOL 2019; 40:443-447. [PMID: 31809620 DOI: 10.1080/01443615.2018.1503645] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
Abstract
The aim of this study was to analyse the factors associated with fetal pleural effusion over the past five years in a single institute in the South of China. Between January 2011 and May 2016, 129 foetuses with pleural effusion were referred to the Fetal Medicine Unit in Guangzhou's Women and Children's Medical Center. Seventy-nine women accepted an invasive procedure to rule out chromosomal abnormalities, fetal anaemia, intrauterine infections or some of the submicroscopic chromosomal abnormalities. Our results showed that chromosomal anomalies occurred in 15.2% (12/79) of cases including 8 Turner syndrome (45, X) (10.1%), 3 trisomy 21 (3.8%) and 1 trisomy 13 (1.3%). Pathological microdeletion or microduplication syndrome occurred in 3 out of 36 (8.3%) prenatal samples with normal karyotype and structural defects. Eight foetuses (10.1%) affected with haemoglobin Bart's disease showed pleural effusion at second or third trimester. Two cases (2.5%) were found to have an intrauterine infection. In conclusion, fetal pleural effusion has a close correlation with chromosomal abnormality. CMA may increase the detection rate of chromosomal aberrations, especially for micro-deletion or micro-duplication syndromes. In the South of China, Thalassemia must be considered when a fetal pleural effusion is detected.Impact statementWhat is already known on this subject? The aetiology of fetal pleural effusion includes a chromosomal abnormality, a congenital heart disease, congenital infections and a number of genetic syndromes.What do the results of this study add? This is the first retrospective study to analyse the aetiology of fetal pleural effusion in one institute in the South of China.What are the implications of these findings for clinical practice and/or further research? Besides the chromosomal abnormality, micro-deletion and micro-duplication syndromes were also detected in our study. We feel that thalassemia must be considered when fetal pleural effusion is detected in South China.
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Affiliation(s)
- Xin Yang
- Department of Prenatal Diagnosis Center, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, China
| | - Dan Yang
- Department of Prenatal Diagnosis Center, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, China
| | - Qiong Deng
- Department of Prenatal Diagnosis Center, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, China
| | - Fu Fang
- Department of Prenatal Diagnosis Center, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, China
| | - Jin Han
- Department of Prenatal Diagnosis Center, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, China
| | - Li Zhen
- Department of Prenatal Diagnosis Center, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, China
| | - Dongzhi Li
- Department of Prenatal Diagnosis Center, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, China
| | - Can Liao
- Department of Prenatal Diagnosis Center, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, China
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24
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Danos AM, Krysiak K, Barnell EK, Coffman AC, McMichael JF, Kiwala S, Spies NC, Sheta LM, Pema SP, Kujan L, Clark KA, Wollam AZ, Rao S, Ritter DI, Sonkin D, Raca G, Lin WH, Grisdale CJ, Kim RH, Wagner AH, Madhavan S, Griffith M, Griffith OL. Standard operating procedure for curation and clinical interpretation of variants in cancer. Genome Med 2019; 11:76. [PMID: 31779674 PMCID: PMC6883603 DOI: 10.1186/s13073-019-0687-x] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2019] [Accepted: 11/07/2019] [Indexed: 02/04/2023] Open
Abstract
Manually curated variant knowledgebases and their associated knowledge models are serving an increasingly important role in distributing and interpreting variants in cancer. These knowledgebases vary in their level of public accessibility, and the complexity of the models used to capture clinical knowledge. CIViC (Clinical Interpretation of Variants in Cancer - www.civicdb.org) is a fully open, free-to-use cancer variant interpretation knowledgebase that incorporates highly detailed curation of evidence obtained from peer-reviewed publications and meeting abstracts, and currently holds over 6300 Evidence Items for over 2300 variants derived from over 400 genes. CIViC has seen increased adoption by, and also undertaken collaboration with, a wide range of users and organizations involved in research. To enhance CIViC’s clinical value, regular submission to the ClinVar database and pursuit of other regulatory approvals is necessary. For this reason, a formal peer reviewed curation guideline and discussion of the underlying principles of curation is needed. We present here the CIViC knowledge model, standard operating procedures (SOP) for variant curation, and detailed examples to support community-driven curation of cancer variants.
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Affiliation(s)
- Arpad M Danos
- McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO, USA
| | - Kilannin Krysiak
- McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO, USA.,Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, MO, USA
| | - Erica K Barnell
- McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO, USA.,Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA
| | - Adam C Coffman
- McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO, USA
| | - Joshua F McMichael
- McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO, USA
| | - Susanna Kiwala
- McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO, USA
| | - Nicholas C Spies
- McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO, USA
| | - Lana M Sheta
- McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO, USA
| | - Shahil P Pema
- McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO, USA
| | - Lynzey Kujan
- McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO, USA
| | - Kaitlin A Clark
- McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO, USA
| | - Amber Z Wollam
- McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO, USA
| | - Shruti Rao
- Innovation Center for Biomedical Informatics, Georgetown University, Washington DC, USA
| | - Deborah I Ritter
- Department of Pediatrics, Texas Children's Hospital, Baylor College of Medicine, Houston, TX, USA
| | - Dmitriy Sonkin
- Biometric Research Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Rockville, MD, USA
| | - Gordana Raca
- Keck School of Medicine, University of Southern California, Los Angeles, California, USA
| | - Wan-Hsin Lin
- Department of Cancer Biology, Mayo Clinic, Jacksonville, Florida, USA
| | - Cameron J Grisdale
- Canada's Michael Smith Genome Sciences Centre, British Columbia Cancer Agency, Vancouver, BC, Canada
| | - Raymond H Kim
- Fred A. Litwin Family Center in Genetic Medicine, University Health Network, Toronto, ON, Canada
| | - Alex H Wagner
- McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO, USA.,Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA
| | - Subha Madhavan
- Innovation Center for Biomedical Informatics, Georgetown University, Washington DC, USA.,Georgetown Lombardi Comprehensive Cancer Center, Washington DC, USA
| | - Malachi Griffith
- McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO, USA. .,Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA. .,Siteman Cancer Center, Washington University School of Medicine, St. Louis, MO, USA. .,Department of Medicine, Washington University School of Medicine, St. Louis, MO, USA.
| | - Obi L Griffith
- McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO, USA. .,Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA. .,Siteman Cancer Center, Washington University School of Medicine, St. Louis, MO, USA. .,Department of Medicine, Washington University School of Medicine, St. Louis, MO, USA.
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25
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Technical standards for the interpretation and reporting of constitutional copy-number variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics (ACMG) and the Clinical Genome Resource (ClinGen). Genet Med 2019; 22:245-257. [PMID: 31690835 PMCID: PMC7313390 DOI: 10.1038/s41436-019-0686-8] [Citation(s) in RCA: 749] [Impact Index Per Article: 149.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2019] [Accepted: 10/18/2019] [Indexed: 11/21/2022] Open
Abstract
Copy number analysis to detect disease-causing losses and gains across the genome is recommended for the evaluation of individuals with neurodevelopmental disorders and/or multiple congenital anomalies, as well as for fetuses with ultrasound abnormalities. In the decade that this analysis has been in widespread clinical use, tremendous strides have been made in understanding the effects of copy number variants (CNVs) in both affected individuals and the general population. However, continued broad implementation of array- and next-generation sequencing-based technologies will expand the types of CNVs encountered in the clinical setting, as well as our understanding of their impact on human health. To assist clinical laboratories in the classification and reporting of CNVs, irrespective of the technology used to identify them, the American College of Medical Genetics and Genomics has developed the following professional standards in collaboration with the NIH-funded Clinical Genome Resource (ClinGen) project. This update introduces a quantitative, evidence-based scoring framework; encourages the implementation of the 5-tier classification system widely used in sequence variant classification; and recommends “uncoupling” the evidence-based classification of a variant from its potential implications for a particular individual. These professional standards will guide the evaluation of constitutional CNVs and encourage consistency and transparency across clinical laboratories.
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26
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Chau MHK, Cao Y, Kwok YKY, Chan S, Chan YM, Wang H, Yang Z, Wong HK, Leung TY, Choy KW. Characteristics and mode of inheritance of pathogenic copy number variants in prenatal diagnosis. Am J Obstet Gynecol 2019; 221:493.e1-493.e11. [PMID: 31207233 DOI: 10.1016/j.ajog.2019.06.007] [Citation(s) in RCA: 30] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2019] [Revised: 06/05/2019] [Accepted: 06/07/2019] [Indexed: 12/01/2022]
Abstract
BACKGROUND Microdeletions and microduplications can occur in any pregnancy independent of maternal age. The spectrum and features of pathogenic copy number variants including the size, genomic distribution, and mode of inheritance are not well studied. These characteristics have important clinical implications regarding expanding noninvasive prenatal screening for microdeletions and microduplications. OBJECTIVES The aim was to investigate the spectrum and characteristics of pathogenic copy number variants in prenatal genetic diagnosis and to provide recommendations for expanding the scope of noninvasive prenatal screening for microdeletions and microduplications. STUDY DESIGN This was a retrospective study of 1510 pregnant women who underwent invasive prenatal diagnostic testing by chromosomal microarray analysis. Prenatal samples were retrieved by amniocentesis or chorionic villus sampling and sent to our prenatal genetic diagnosis laboratory for chromosomal microarray analysis. The risk of carrying a fetus with pathogenic copy number variants is stratified by the patients' primary indication for invasive testing. We searched the literature for published prenatal chromosomal microarray data to generate a large cohort of 23,865 fetuses. The characteristics and spectrum of pathogenic copy number variants including the type of aberrations (gains or losses), genomic loci, sizes, and the mode of inheritance were studied. RESULTS Overall, 375 of 23,865 fetuses (1.6%) carried pathogenic copy number variants for any indication for invasive testing, and 44 of them (11.7%) involve 2 or more pathogenic copy number variants. A total of 428 pathogenic copy number variants were detected in these fetuses, of which 280 were deletions and 148 were duplications. Three hundred sixty (84.1%) were less than 5 Mb in size and 68 (15.9%) were between 5 and 10 Mb. The incidence of carrying a pathogenic copy number variant in the high-risk group is 1 in 36 and the low-risk group is 1 in 125. Parental inheritance study results were available for 311 pathogenic copy number variants, 71 (22.8%) were maternally inherited, 36 (11.6%) were paternally inherited, and 204 (65.6%) occurred de novo. CONCLUSION Collectively, pathogenic copy number variants are common in pregnancies. High-risk pregnancies should be offered invasive testing with chromosomal microarray analysis for the most comprehensive investigation. Detection limits on size, parental inheritance, and genomic distribution should be carefully considered before implementing copy number variant screening in expanded noninvasive prenatal screening.
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Affiliation(s)
- Matthew Hoi Kin Chau
- Department of Obstetrics and Gynaecology, The Chinese University of Hong Kong, Hong Kong, China
| | - Ye Cao
- Department of Obstetrics and Gynaecology, The Chinese University of Hong Kong, Hong Kong, China
| | - Yvonne Ka Yin Kwok
- Department of Obstetrics and Gynaecology, The Chinese University of Hong Kong, Hong Kong, China
| | - Samantha Chan
- Warwick Medical School at the University of Warwick, Coventry, United Kingdom
| | - Yiu Man Chan
- Department of Obstetrics and Gynaecology, The Chinese University of Hong Kong, Hong Kong, China
| | - Huilin Wang
- Department of Obstetrics and Gynaecology, The Chinese University of Hong Kong, Hong Kong, China; Department of Central Laboratory, Bao'an Maternity and Child Healthcare Hospital, Jinan University School of Medicine, Key Laboratory of Birth Defects Research, Birth Defects Prevention Research, and Transformation Team, Shenzhen, China; Shenzhen Research Institute, The Chinese University of Hong Kong, Shenzhen, China
| | - Zhenjun Yang
- Department of Obstetrics and Gynaecology, The Chinese University of Hong Kong, Hong Kong, China; Shenzhen Research Institute, The Chinese University of Hong Kong, Shenzhen, China
| | - Hoi Kin Wong
- Department of Obstetrics and Gynaecology, The Chinese University of Hong Kong, Hong Kong, China
| | - Tak Yeung Leung
- Department of Obstetrics and Gynaecology, The Chinese University of Hong Kong, Hong Kong, China; The Chinese University of Hong Kong-Baylor College of Medicine Joint Center for Medical Genetics, Hong Kong, China
| | - Kwong Wai Choy
- Department of Obstetrics and Gynaecology, The Chinese University of Hong Kong, Hong Kong, China; Shenzhen Research Institute, The Chinese University of Hong Kong, Shenzhen, China; The Chinese University of Hong Kong-Baylor College of Medicine Joint Center for Medical Genetics, Hong Kong, China.
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27
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Hu T, Kruszka P, Martinez AF, Ming JE, Shabason EK, Raam MS, Shaikh TH, Pineda-Alvarez DE, Muenke M. Cytogenetics and holoprosencephaly: A chromosomal microarray study of 222 individuals with holoprosencephaly. AMERICAN JOURNAL OF MEDICAL GENETICS PART C-SEMINARS IN MEDICAL GENETICS 2019; 178:175-186. [PMID: 30182442 DOI: 10.1002/ajmg.c.31622] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/06/2018] [Revised: 04/18/2018] [Accepted: 04/20/2018] [Indexed: 11/08/2022]
Abstract
Holoprosencephaly (HPE), a common developmental forebrain malformation, is characterized by failure of the cerebrum to completely divide into left and right hemispheres. The etiology of HPE is heterogeneous and a number of environmental and genetic factors have been identified. Cytogenetically visible alterations occur in 25% to 45% of HPE patients and cytogenetic techniques have long been used to study copy number variants (CNVs) in this disorder. The karyotype approach initially demonstrated several recurrent chromosomal anomalies, which led to the identification of HPE-specific loci and, eventually, several major HPE genes. More recently, higher-resolution cytogenetic techniques such as subtelomeric multiplex ligation-dependent probe amplification and chromosomal microarray have been used to analyze chromosomal anomalies. By using chromosomal microarray, we sought to identify submicroscopic chromosomal deletions and duplications in patients with HPE. In an analysis of 222 individuals with HPE, a deletion or duplication was detected in 107 individuals. Of these 107 individuals, 23 (21%) had variants that were classified as pathogenic or likely pathogenic by board-certified medical geneticists. We identified multiple patients with deletions in established HPE loci as well as three patients with deletions encompassed by 6q12-q14.3, a CNV previously reported by Bendavid et al. In addition, we identified a new locus, 16p13.2 that warrants further investigation for HPE association. Incidentally, we also found a case of Potocki-Lupski syndrome, a case of Phelan-McDermid syndrome, and multiple cases of 22q11.2 deletion syndrome within our cohort. These data confirm the genetically heterogeneous nature of HPE, and also demonstrate clinical utility of chromosomal microarray in diagnosing patients affected by HPE.
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Affiliation(s)
- Tommy Hu
- Medical Genetics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland
| | - Paul Kruszka
- Medical Genetics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland
| | - Ariel F Martinez
- Medical Genetics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland
| | - Jeffrey E Ming
- Division of Human Genetics, The Children's Hospital of Philadelphia, University of Pennsylvania School of Medicine, Philadelphia, Pennsylvania
| | - Emily K Shabason
- Medical Genetics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland.,Division of Developmental and Behavioral Pediatrics, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania
| | - Manu S Raam
- Medical Genetics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland.,General Pediatrics Services Shriners for Children Medical Center, Pasadena, California.,General Pediatrics Services Children's Hospital Los Angeles, Los Angeles, California
| | - Tamim H Shaikh
- Department of Pediatrics, University of Colorado School of Medicine, Aurora, Colorado.,Invitae Corporation, San Francisco, California
| | - Daniel E Pineda-Alvarez
- Medical Genetics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland.,Division of Developmental and Behavioral Pediatrics, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania
| | - Maximilian Muenke
- Medical Genetics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland
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28
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Riggs ER, Nelson T, Merz A, Ackley T, Bunke B, Collins CD, Collinson MN, Fan YS, Goodenberger ML, Golden DM, Haglund-Hazy L, Krgovic D, Lamb AN, Lewis Z, Li G, Liu Y, Meck J, Neufeld-Kaiser W, Runke CK, Sanmann JN, Stavropoulos DJ, Strong E, Su M, Tayeh MK, Kokalj Vokac N, Thorland EC, Andersen E, Martin CL. Copy number variant discrepancy resolution using the ClinGen dosage sensitivity map results in updated clinical interpretations in ClinVar. Hum Mutat 2019; 39:1650-1659. [PMID: 30095202 DOI: 10.1002/humu.23610] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2018] [Revised: 07/16/2018] [Accepted: 08/03/2018] [Indexed: 11/07/2022]
Abstract
Conflict resolution in genomic variant interpretation is a critical step toward improving patient care. Evaluating interpretation discrepancies in copy number variants (CNVs) typically involves assessing overlapping genomic content with focus on genes/regions that may be subject to dosage sensitivity (haploinsufficiency (HI) and/or triplosensitivity (TS)). CNVs containing dosage sensitive genes/regions are generally interpreted as "likely pathogenic" (LP) or "pathogenic" (P), and CNVs involving the same known dosage sensitive gene(s) should receive the same clinical interpretation. We compared the Clinical Genome Resource (ClinGen) Dosage Map, a publicly available resource documenting known HI and TS genes/regions, against germline, clinical CNV interpretations within the ClinVar database. We identified 251 CNVs overlapping known dosage sensitive genes/regions but not classified as LP or P; these were sent back to their original submitting laboratories for re-evaluation. Of 246 CNVs re-evaluated, an updated clinical classification was warranted in 157 cases (63.8%); no change was made to the current classification in 79 cases (32.1%); and 10 cases (4.1%) resulted in other types of updates to ClinVar records. This effort will add curated interpretation data into the public domain and allow laboratories to focus attention on more complex discrepancies.
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Affiliation(s)
- Erin R Riggs
- Autism & Developmental Medicine Institute, Geisinger, Danville, PA, USA
| | - Tristan Nelson
- Autism & Developmental Medicine Institute, Geisinger, Danville, PA, USA
| | - Andrew Merz
- Autism & Developmental Medicine Institute, Geisinger, Danville, PA, USA
| | - Todd Ackley
- Michigan Medical Genetics Laboratories (MMGL), University of Michigan, Ann Arbor, MI, USA
| | | | | | - Morag N Collinson
- Wessex Regional Genetics Laboratory, Salisbury NHS Foundation Trust, Salisbury, Wiltshire, UK
| | - Yao-Shan Fan
- University of Miami Miller School of Medicine, Miami, FL, USA
| | - McKinsey L Goodenberger
- Genomics Laboratory, Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
| | - Denae M Golden
- Human Genetics Laboratory, Munroe-Meyer Institute, University of Nebraska Medical Center, Omaha, NE, USA
| | - Linda Haglund-Hazy
- Michigan Medical Genetics Laboratories (MMGL), University of Michigan, Ann Arbor, MI, USA
| | - Danijela Krgovic
- University Medical Centre Maribor, Laboratory of Medical Genetics, Maribor, Slovenia.,Faculty of Medicine, University of Maribor, Maribor, Slovenia
| | - Allen N Lamb
- ARUP Laboratories, Salt Lake City, UT, USA.,University of Utah, Salt Lake City, UT, USA
| | - Zoe Lewis
- ARUP Laboratories, Salt Lake City, UT, USA
| | | | - Yajuan Liu
- Clinical Cytogenomics Laboratory, Department of Pathology, University of Washington School of Medicine, Seattle, WA, USA
| | | | - Whitney Neufeld-Kaiser
- Clinical Cytogenomics Laboratory, Department of Pathology, University of Washington School of Medicine, Seattle, WA, USA
| | - Cassandra K Runke
- Genomics Laboratory, Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
| | - Jennifer N Sanmann
- Human Genetics Laboratory, Munroe-Meyer Institute, University of Nebraska Medical Center, Omaha, NE, USA
| | | | - Emma Strong
- Genome Diagnostics, The Hospital for Sick Children, University of Toronto, Canada
| | - Meng Su
- University of Miami Miller School of Medicine, Miami, FL, USA
| | - Marwan K Tayeh
- Michigan Medical Genetics Laboratories (MMGL), University of Michigan, Ann Arbor, MI, USA
| | - Nadja Kokalj Vokac
- University Medical Centre Maribor, Laboratory of Medical Genetics, Maribor, Slovenia.,Faculty of Medicine, University of Maribor, Maribor, Slovenia
| | - Erik C Thorland
- Genomics Laboratory, Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
| | - Erica Andersen
- ARUP Laboratories, Salt Lake City, UT, USA.,University of Utah, Salt Lake City, UT, USA
| | - Christa L Martin
- Autism & Developmental Medicine Institute, Geisinger, Danville, PA, USA
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29
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Additive Diagnostic Yield of Homozygosity Regions Identified During Chromosomal microarray Testing in Children with Developmental Delay, Dysmorphic Features or Congenital Anomalies. Biochem Genet 2019; 58:74-101. [PMID: 31273557 DOI: 10.1007/s10528-019-09931-3] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2019] [Accepted: 06/27/2019] [Indexed: 11/26/2022]
Abstract
Chromosomal microarray (CMA) has emerged as a robust tool for identifying microdeletions and microduplications, termed copy number variants (CNVs). Nevertheless, data regarding its utility in different patient populations with developmental delay (DD), dysmorphic features (DF) and congenital anomalies (CA), is a matter of dense debate. Although regions of homozygosity (ROH) are not diagnostic of a specific condition, they may have pathogenic implications. Certain CNVs and ROH have ethnically specific occurrences and frequencies. We aimed to determine whether CMA testing offers additional diagnostic information over classical cytogenetics for identifying genomic imbalances in a pediatric cohort with idiopathic DD, DF, or CA. One hundred sixty-nine patients were offered cytogenetics and CMA simultaneously for etiological diagnosis of DD (n = 67), DF (n = 52) and CA (n = 50). CMA could identify additional, clinically significant anomalies as compared with cytogenetics. CMA detected 61 CNVs [21 (34.4%) pathogenic CNVs, 37 (60.7%) variants of uncertain clinical significance and 3 (4.9%) benign CNVs] in 44 patients. CMA identified one or more ROH in 116/169 (68.6%) patients. When considering pathogenic CNVs and aneuploidies as positive findings, 9/169 (5.3%) received a genetic diagnosis from cytogenetics, while 25/169 (14.8%) could have a genetic diagnosis from CMA. The identification of ROH was clinically significant in two cases (2/169), thereby, adding 1.2% to the diagnostic yield of CMA (16% vs. 5.3%, p < 0.001). CMA uncovers additional genetic diagnoses over cytogenetics, thereby, offering a much higher diagnostic yield. Our findings convincingly demonstrate the additive diagnostic value of clinically significant ROH identified during CMA testing, highlighting the need for careful clinical interpretation of these ROH.
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30
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Technical laboratory standards for interpretation and reporting of acquired copy-number abnormalities and copy-neutral loss of heterozygosity in neoplastic disorders: a joint consensus recommendation from the American College of Medical Genetics and Genomics (ACMG) and the Cancer Genomics Consortium (CGC). Genet Med 2019; 21:1903-1916. [PMID: 31138931 DOI: 10.1038/s41436-019-0545-7] [Citation(s) in RCA: 36] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2019] [Accepted: 05/05/2019] [Indexed: 12/11/2022] Open
Abstract
The detection of acquired copy-number abnormalities (CNAs) and copy-neutral loss of heterozygosity (CN-LOH) in neoplastic disorders by chromosomal microarray analysis (CMA) has significantly increased over the past few years with respect to both the number of laboratories utilizing this technology and the broader number of tumor types being assayed. This highlights the importance of standardizing the interpretation and reporting of acquired variants among laboratories. To address this need, a clinical laboratory-focused workgroup was established to draft recommendations for the interpretation and reporting of acquired CNAs and CN-LOH in neoplastic disorders. This project is a collaboration between the American College of Medical Genetics and Genomics (ACMG) and the Cancer Genomics Consortium (CGC). The recommendations put forth by the workgroup are based on literature review, empirical data, and expert consensus of the workgroup members. A four-tier evidence-based categorization system for acquired CNAs and CN-LOH was developed, which is based on the level of available evidence regarding their diagnostic, prognostic, and therapeutic relevance: tier 1, variants with strong clinical significance; tier 2, variants with some clinical significance; tier 3, clonal variants with no documented neoplastic disease association; and tier 4, benign or likely benign variants. These recommendations also provide a list of standardized definitions of terms used in the reporting of CMA findings, as well as a framework for the clinical reporting of acquired CNAs and CN-LOH, and recommendations for how to deal with suspected clinically significant germline variants.
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31
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Cicatiello R, Pignataro P, Izzo A, Mollo N, Pezone L, Maruotti GM, Sarno L, Sglavo G, Conti A, Genesio R, Nitsch L. Chromosomal Microarray Analysis versus Karyotyping in Fetuses with Increased Nuchal Translucency. Med Sci (Basel) 2019; 7:medsci7030040. [PMID: 30818867 PMCID: PMC6473420 DOI: 10.3390/medsci7030040] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2018] [Revised: 02/01/2019] [Accepted: 02/15/2019] [Indexed: 11/26/2022] Open
Abstract
We have carried out a retrospective study of chromosome anomalies associated with increased nuchal translucency (NT) in order to compare yield rates of karyotype, chromosome microarray analysis (CMA), and non-invasive prenatal testing (NIPT) in this condition. Presenting with increased NT or cystic hygroma ≥3.5 mm as an isolated sign, 249 fetuses underwent karyotype and/or CMA from 11 to 18 gestational weeks. Karyotype and fluorescence in situ hybridization (FISH) analyses detected 103 chromosomal anomalies including 95 aneuploidies and eight chromosomal rearrangements or derivatives. Further, seven pathogenic copy number variants (CNV), five likely pathogenic CNVs, and 15 variants of unknown significance (VOUS) were detected by CMA in fetuses with normal karyotype. Genetic testing is now facing new challenges due to results with uncertain clinical impacts. Additional investigations will be necessary to interpret these findings. More than 15% of the anomalies that we have diagnosed with invasive techniques could not be detected by NIPT. It is therefore definitely not recommended in the case of ultrasound anomalies. These results, while corroborating the use of CMA in fetuses with increased NT as a second tier after rapid aneuploidy testing, do not suggest a dismissal of karyotype analysis.
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Affiliation(s)
- Rita Cicatiello
- Dept. Molecular Medicine and Medical Biotechnology, School of Medicine, University of Naples Federico II, 80131 Naples, Italy.
| | - Piero Pignataro
- Dept. Molecular Medicine and Medical Biotechnology, School of Medicine, University of Naples Federico II, 80131 Naples, Italy.
| | - Antonella Izzo
- Dept. Molecular Medicine and Medical Biotechnology, School of Medicine, University of Naples Federico II, 80131 Naples, Italy.
| | - Nunzia Mollo
- Dept. Molecular Medicine and Medical Biotechnology, School of Medicine, University of Naples Federico II, 80131 Naples, Italy.
| | - Lucia Pezone
- Dept. Molecular Medicine and Medical Biotechnology, School of Medicine, University of Naples Federico II, 80131 Naples, Italy.
| | - Giuseppe Maria Maruotti
- Maternal-child Department, School of Medicine, University of Naples Federico II, 80131 Naples, Italy.
| | - Laura Sarno
- Maternal-child Department, School of Medicine, University of Naples Federico II, 80131 Naples, Italy.
| | - Gabriella Sglavo
- Maternal-child Department, School of Medicine, University of Naples Federico II, 80131 Naples, Italy.
| | - Anna Conti
- Dept. Molecular Medicine and Medical Biotechnology, School of Medicine, University of Naples Federico II, 80131 Naples, Italy.
| | - Rita Genesio
- Dept. Molecular Medicine and Medical Biotechnology, School of Medicine, University of Naples Federico II, 80131 Naples, Italy.
| | - Lucio Nitsch
- Dept. Molecular Medicine and Medical Biotechnology, School of Medicine, University of Naples Federico II, 80131 Naples, Italy.
- Institute of Experimental Endocrinology and Oncology, National Research Council, 80131 Naples, Italy.
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32
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Aradhya S, Nussbaum RL. Genetics in mainstream medicine: Finally within grasp to influence healthcare globally. Mol Genet Genomic Med 2018; 6:473-480. [PMID: 29807392 PMCID: PMC6081234 DOI: 10.1002/mgg3.415] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2018] [Accepted: 04/24/2018] [Indexed: 01/02/2023] Open
Abstract
A modern genomics ecosystem has emerged. This commentary describes recent trends in clinical genomics that enable its successful integration in mainstream medicine. The rapid expansion of clinical genomics will have a positive impact on the healthcare of individuals worldwide.
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Affiliation(s)
- Swaroop Aradhya
- InvitaeSan FranciscoCalifornia
- Adjunct clinical associate professorStanford University School of MedicineStanfordCalifornia
| | - Robert L. Nussbaum
- InvitaeSan FranciscoCalifornia
- Volunteer facultyUniversity of California San FranciscoSan FranciscoCalifornia
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33
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Lacey CJ, Doudney K, Bridgman PG, George PM, Mulder RT, Zarifeh JJ, Kimber B, Cadzow MJ, Black MA, Merriman TR, Lehnert K, Bickley VM, Pearson JF, Cameron VA, Kennedy MA. Copy number variants implicate cardiac function and development pathways in earthquake-induced stress cardiomyopathy. Sci Rep 2018; 8:7548. [PMID: 29765130 PMCID: PMC5954162 DOI: 10.1038/s41598-018-25827-5] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2017] [Accepted: 04/25/2018] [Indexed: 02/07/2023] Open
Abstract
The pathophysiology of stress cardiomyopathy (SCM), also known as takotsubo syndrome, is poorly understood. SCM usually occurs sporadically, often in association with a stressful event, but clusters of cases are reported after major natural disasters. There is some evidence that this is a familial condition. We have examined three possible models for an underlying genetic predisposition to SCM. Our primary study cohort consists of 28 women who suffered SCM as a result of two devastating earthquakes that struck the city of Christchurch, New Zealand, in 2010 and 2011. To seek possible underlying genetic factors we carried out exome analysis, genotyping array analysis, and array comparative genomic hybridization on these subjects. The most striking finding was the observation of a markedly elevated rate of rare, heterogeneous copy number variants (CNV) of uncertain clinical significance (in 12/28 subjects). Several of these CNVs impacted on genes of cardiac relevance including RBFOX1, GPC5, KCNRG, CHODL, and GPBP1L1. There is no physical overlap between the CNVs, and the genes they impact do not appear to be functionally related. The recognition that SCM predisposition may be associated with a high rate of rare CNVs offers a novel perspective on this enigmatic condition.
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Affiliation(s)
- Cameron J Lacey
- Department of Psychological Medicine, University of Otago, Christchurch, New Zealand.
| | - Kit Doudney
- Molecular Pathology Laboratory, Canterbury Health Laboratories, Canterbury District Health Board, Christchurch, New Zealand
| | - Paul G Bridgman
- Department of Cardiology, Christchurch Hospital, Christchurch, New Zealand
| | - Peter M George
- Molecular Pathology Laboratory, Canterbury Health Laboratories, Canterbury District Health Board, Christchurch, New Zealand
- Department of Pathology and Biomedical Science, University of Otago, Christchurch, New Zealand
| | - Roger T Mulder
- Department of Psychological Medicine, University of Otago, Christchurch, New Zealand
| | - Julie J Zarifeh
- Psychiatric Consultation Service, Christchurch Hospital, Canterbury District Health Board, Christchurch, New Zealand
| | - Bridget Kimber
- Department of Psychological Medicine, University of Otago, Christchurch, New Zealand
| | - Murray J Cadzow
- Department of Biochemistry, University of Otago, Dunedin, New Zealand
| | - Michael A Black
- Department of Biochemistry, University of Otago, Dunedin, New Zealand
| | - Tony R Merriman
- Department of Biochemistry, University of Otago, Dunedin, New Zealand
| | - Klaus Lehnert
- School of Biological Sciences, University of Auckland, Auckland, New Zealand
| | - Vivienne M Bickley
- Molecular Pathology Laboratory, Canterbury Health Laboratories, Canterbury District Health Board, Christchurch, New Zealand
| | - John F Pearson
- Biostatistics and Computational Biology Unit, University of Otago, Christchurch, New Zealand
| | - Vicky A Cameron
- Christchurch Heart Institute, Department of Medicine, University of Otago, Christchurch, New Zealand
| | - Martin A Kennedy
- Department of Pathology and Biomedical Science, University of Otago, Christchurch, New Zealand.
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34
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Woodbury-Smith M, Deneault E, Yuen RKC, Walker S, Zarrei M, Pellecchia G, Howe JL, Hoang N, Uddin M, Marshall CR, Chrysler C, Thompson A, Szatmari P, Scherer SW. Mutations in RAB39B in individuals with intellectual disability, autism spectrum disorder, and macrocephaly. Mol Autism 2017; 8:59. [PMID: 29152164 PMCID: PMC5679329 DOI: 10.1186/s13229-017-0175-3] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2017] [Accepted: 10/16/2017] [Indexed: 12/14/2022] Open
Abstract
Background Autism spectrum disorder (ASD), a developmental disorder of early childhood onset, affects males four times more frequently than females, suggesting a role for the sex chromosomes. In this study, we describe a family with ASD in which a predicted pathogenic nonsense mutation in the X-chromosome gene RAB39B segregates with ASD phenotype. Methods Clinical phenotyping, microarray, and whole genome sequencing (WGS) were performed on the five members of this family. Maternal and female sibling X inactivation ratio was calculated, and phase was investigated. Mutant-induced pluripotent stem cells engineered for an exon 2 nonsense mutation were generated and differentiated into cortical neurons for expression and pathway analyses. Results Two males with an inherited RAB39B mutation both presented with macrocephaly, intellectual disability (ID), and ASD. Their female sibling with the same mutation presented with ID and a broad autism phenotype. In contrast, their transmitting mother has no neurodevelopmental diagnosis. Our investigation of phase indicated maternal preferential inactivation of the mutated allele, with no such bias observed in the female sibling. We offer the explanation that this bias in X inactivation may explain the absence of a neurocognitive phenotype in the mother. Our cellular knockout model of RAB39B revealed an impact on expression in differentiated neurons for several genes implicated in brain development and function, supported by our pathway enrichment analysis. Conclusions Penetrance for ASD is high among males but more variable among females with RAB39B mutations. A critical role for this gene in brain development and function is demonstrated.
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Affiliation(s)
- Marc Woodbury-Smith
- Institute of Neuroscience, Newcastle University, c/o Sir James Spence Institute, Queen Victoria Road, Newcastle upon Tyne, NE1 4LP UK.,Program in Genetics and Genome Biology, The Centre for Applied Genomics, The Hospital for Sick Children, Toronto, ON Canada
| | - Eric Deneault
- Program in Genetics and Genome Biology, The Centre for Applied Genomics, The Hospital for Sick Children, Toronto, ON Canada
| | - Ryan K C Yuen
- Program in Genetics and Genome Biology, The Centre for Applied Genomics, The Hospital for Sick Children, Toronto, ON Canada
| | - Susan Walker
- Program in Genetics and Genome Biology, The Centre for Applied Genomics, The Hospital for Sick Children, Toronto, ON Canada
| | - Mehdi Zarrei
- Program in Genetics and Genome Biology, The Centre for Applied Genomics, The Hospital for Sick Children, Toronto, ON Canada
| | - Giovanna Pellecchia
- Program in Genetics and Genome Biology, The Centre for Applied Genomics, The Hospital for Sick Children, Toronto, ON Canada
| | - Jennifer L Howe
- Program in Genetics and Genome Biology, The Centre for Applied Genomics, The Hospital for Sick Children, Toronto, ON Canada
| | - Ny Hoang
- Autism Research Unit, The Hospital for Sick Children, Toronto, ON Canada.,Centre for Addiction and Mental Health, The Hospital for Sick Children and University of Toronto, Toronto, ON Canada
| | - Mohammed Uddin
- Mohammed Bin Rashid University of Medicine and Health Sciences, Dubai, UAE
| | - Christian R Marshall
- Program in Genetics and Genome Biology, The Centre for Applied Genomics, The Hospital for Sick Children, Toronto, ON Canada
| | - Christina Chrysler
- Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, ON Canada
| | - Ann Thompson
- Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, ON Canada
| | - Peter Szatmari
- Centre for Addiction and Mental Health, The Hospital for Sick Children and University of Toronto, Toronto, ON Canada
| | - Stephen W Scherer
- Program in Genetics and Genome Biology, The Centre for Applied Genomics, The Hospital for Sick Children, Toronto, ON Canada.,McLaughlin Centre, University of Toronto, Toronto, ON Canada.,Department of Molecular Genetics, University of Toronto, Toronto, ON Canada
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35
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Woodbury-Smith M, Nicolson R, Zarrei M, Yuen RKC, Walker S, Howe J, Uddin M, Hoang N, Buchanan JA, Chrysler C, Thompson A, Szatmari P, Scherer SW. Variable phenotype expression in a family segregating microdeletions of the NRXN1 and MBD5 autism spectrum disorder susceptibility genes. NPJ Genom Med 2017. [PMID: 28649445 PMCID: PMC5482711 DOI: 10.1038/s41525-017-0020-9] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022] Open
Abstract
Autism spectrum disorder is a developmental condition of early childhood onset, which impacts socio-communicative functioning and is principally genetic in etiology. Currently, more than 50 genomic loci are deemed to be associated with susceptibility to autism spectrum disorder, showing de novo and inherited unbalanced copy number variants and smaller insertions and deletions (indels), more complex structural variants, as well as single-nucleotide variants deemed of pathological significance. However, the phenotypes associated with many of these genes are variable, and penetrance is largely unelaborated in clinical descriptions. This case report describes a family harboring two copy number variant microdeletions, which affect regions of NRXN1 and MBD5—each well-established in association with risk of autism spectrum disorder and other neurodevelopmental disorders. Although each copy number variant would likely be categorized as pathologically significant, both genomic alterations are transmitted in this family from an unaffected father to the proband, and shared by an unaffected sibling. This family case illustrates the importance of recognizing that phenotype can vary among exon overlapping variants of the same gene, and the need to evaluate penetrance of such variants in order to properly inform on risks.
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Affiliation(s)
- Marc Woodbury-Smith
- Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, ON, Canada.,Program in Genetics and Genome Biology, The Centre for Applied Genomics, The Hospital for Sick Children, Toronto, ON, Canada
| | - Rob Nicolson
- Department of Psychiatry, University of Western Ontario, London, ON, Canada
| | - Mehdi Zarrei
- Program in Genetics and Genome Biology, The Centre for Applied Genomics, The Hospital for Sick Children, Toronto, ON, Canada
| | - Ryan K C Yuen
- Program in Genetics and Genome Biology, The Centre for Applied Genomics, The Hospital for Sick Children, Toronto, ON, Canada
| | - Susan Walker
- Program in Genetics and Genome Biology, The Centre for Applied Genomics, The Hospital for Sick Children, Toronto, ON, Canada
| | - Jennifer Howe
- Program in Genetics and Genome Biology, The Centre for Applied Genomics, The Hospital for Sick Children, Toronto, ON, Canada
| | - Mohammed Uddin
- Program in Genetics and Genome Biology, The Centre for Applied Genomics, The Hospital for Sick Children, Toronto, ON, Canada
| | - Ny Hoang
- Autism Research Unit, The Hospital for Sick Children, Toronto, ON, Canada
| | - Janet A Buchanan
- Program in Genetics and Genome Biology, The Centre for Applied Genomics, The Hospital for Sick Children, Toronto, ON, Canada
| | - Christina Chrysler
- Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, ON, Canada
| | - Ann Thompson
- Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, ON, Canada
| | - Peter Szatmari
- Centre for Addiction and Mental Health, The Hospital for Sick Children & University of Toronto, Toronto, ON, Canada
| | - Stephen W Scherer
- Program in Genetics and Genome Biology, The Centre for Applied Genomics, The Hospital for Sick Children, Toronto, ON, Canada.,McLaughlin Centre and Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada
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36
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Dosage sensitivity is a major determinant of human copy number variant pathogenicity. Nat Commun 2017; 8:14366. [PMID: 28176757 PMCID: PMC5309798 DOI: 10.1038/ncomms14366] [Citation(s) in RCA: 83] [Impact Index Per Article: 11.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2016] [Accepted: 12/20/2016] [Indexed: 01/22/2023] Open
Abstract
Human copy number variants (CNVs) account for genome variation an order of magnitude larger than single-nucleotide polymorphisms. Although much of this variation has no phenotypic consequences, some variants have been associated with disease, in particular neurodevelopmental disorders. Pathogenic CNVs are typically very large and contain multiple genes, and understanding the cause of the pathogenicity remains a major challenge. Here we show that pathogenic CNVs are significantly enriched for genes involved in development and genes that have greater evolutionary copy number conservation across mammals, indicative of functional constraints. Conversely, genes found in benign CNV regions have more variable copy number. These evolutionary constraints are characteristic of genes in pathogenic CNVs and can only be explained by dosage sensitivity of those genes. These results implicate dosage sensitivity of individual genes as a common cause of CNV pathogenicity. These evolutionary metrics suggest a path to identifying disease genes in pathogenic CNVs. Copy number variants (CNVs) cause significant genomic variation in humans and may be benign or may cause disease. Here, the authors show that pathogenic CNVs are evolutionarily constrained compared with benign, pointing to dosage sensitivity as a potential cause of disease.
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37
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Oneda B, Rauch A. Microarrays in prenatal diagnosis. Best Pract Res Clin Obstet Gynaecol 2017; 42:53-63. [PMID: 28215395 DOI: 10.1016/j.bpobgyn.2017.01.003] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2016] [Revised: 12/13/2016] [Accepted: 01/04/2017] [Indexed: 01/09/2023]
Abstract
In prenatal diagnosis, chromosomal microarray (CMA) has not yet fully replaced conventional karyotyping but has rapidly become the recommended test in pregnancies with ultrasound abnormalities. In this review, we provide an overview of the published data concerning this technology and the controversies concerning its use in the prenatal setting. There is abundant evidence indicating the added detection of pathogenic abnormalities with CMA in comparison to the traditional karyotyping, especially in fetuses with multiple or isolated ultrasound abnormalities such as congenital heart disease, increased nuchal translucency, or oral cleft. On the other hand, there is also a risk to detect variants of unknown significance, late-onset disorders, and variants in susceptibility loci. However, it has been shown that pregnant couples tend to prefer a maximum of information about the health of their unborn child. Taken together, CMA has considerable diagnostic and prognostic values during pregnancy and should therefore be the test of choice.
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Affiliation(s)
- Beatrice Oneda
- Institute of Medical Genetics, University of Zurich, Zurich, Switzerland.
| | - Anita Rauch
- Institute of Medical Genetics, University of Zurich, Zurich, Switzerland
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38
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Hollenbeck D, Williams CL, Drazba K, Descartes M, Korf BR, Rutledge SL, Lose EJ, Robin NH, Carroll AJ, Mikhail FM. Clinical relevance of small copy-number variants in chromosomal microarray clinical testing. Genet Med 2016; 19:377-385. [PMID: 27632688 DOI: 10.1038/gim.2016.132] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2016] [Accepted: 07/21/2016] [Indexed: 11/09/2022] Open
Abstract
PURPOSE The 2010 consensus statement on diagnostic chromosomal microarray (CMA) testing recommended an array resolution ≥400 kb throughout the genome as a balance of analytical and clinical sensitivity. In spite of the clear evidence for pathogenicity of large copy-number variants (CNVs) in neurodevelopmental disorders and/or congenital anomalies, the significance of small, nonrecurrent CNVs (<500 kb) has not been well established in a clinical setting. METHODS We investigated the clinical significance of all nonpolymorphic small, nonrecurrent CNVs (<500 kb) in patients referred for CMA clinical testing over a period of 6 years, from 2009 to 2014 (a total of 4,417 patients). We excluded from our study patients with benign or likely benign CNVs and patients with only recurrent microdeletions/microduplications <500 kb. RESULTS In total, 383 patients (8.67%) were found to carry at least one small, nonrecurrent CNV, of whom 176 patients (3.98%) had one small CNV classified as a variant of uncertain significance (VUS), 45 (1.02%) had two or more small VUS CNVs, 20 (0.45%) had one small VUS CNV and a recurrent CNV, 113 (2.56%) had one small pathogenic or likely pathogenic CNV, 17 (0.38%) had two or more small pathogenic or likely pathogenic CNVs, and 12 (0.27%) had one small pathogenic or likely pathogenic CNV and a recurrent CNV. Within the pathogenic group, 80 of 142 patients (56% of all small pathogenic CNV cases) were found to have a single whole-gene or exonic deletion. The themes that emerged from our study are presented in the Discussion section. CONCLUSIONS Our study demonstrates the diagnostic clinical relevance of small, nonrecurrent CNVs <500 kb during CMA clinical testing and underscores the need for careful clinical interpretation of these CNVs.Genet Med 19 4, 377-385.
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Affiliation(s)
- Dana Hollenbeck
- Department of Genetics, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Crescenda L Williams
- Department of Genetics, University of Alabama at Birmingham, Birmingham, Alabama, USA.,Current address: Children's Health Hospital, Dallas, Texas, USA
| | - Kathryn Drazba
- Department of Genetics, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Maria Descartes
- Department of Genetics, University of Alabama at Birmingham, Birmingham, Alabama, USA.,Department of Pediatrics, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Bruce R Korf
- Department of Genetics, University of Alabama at Birmingham, Birmingham, Alabama, USA.,Department of Pediatrics, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - S Lane Rutledge
- Department of Genetics, University of Alabama at Birmingham, Birmingham, Alabama, USA.,Department of Pediatrics, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Edward J Lose
- Department of Genetics, University of Alabama at Birmingham, Birmingham, Alabama, USA.,Department of Pediatrics, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Nathaniel H Robin
- Department of Genetics, University of Alabama at Birmingham, Birmingham, Alabama, USA.,Department of Pediatrics, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Andrew J Carroll
- Department of Genetics, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Fady M Mikhail
- Department of Genetics, University of Alabama at Birmingham, Birmingham, Alabama, USA
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Mason-Suares H, Landry L, S. Lebo M. Detecting Copy Number Variation via Next Generation Technology. CURRENT GENETIC MEDICINE REPORTS 2016. [DOI: 10.1007/s40142-016-0091-4] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
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40
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Wang B, Ji T, Zhou X, Wang J, Wang X, Wang J, Zhu D, Zhang X, Sham PC, Zhang X, Ma X, Jiang Y. CNV analysis in Chinese children of mental retardation highlights a sex differentiation in parental contribution to de novo and inherited mutational burdens. Sci Rep 2016; 6:25954. [PMID: 27257017 PMCID: PMC4891738 DOI: 10.1038/srep25954] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2016] [Accepted: 04/06/2016] [Indexed: 12/28/2022] Open
Abstract
Rare copy number variations (CNVs) are a known genetic etiology in neurodevelopmental disorders (NDD). Comprehensive CNV analysis was performed in 287 Chinese children with mental retardation and/or development delay (MR/DD) and their unaffected parents. When compared with 5,866 ancestry-matched controls, 11~12% more MR/DD children carried rare and large CNVs. The increased CNV burden in MR/DD was predominantly due to de novo CNVs, the majority of which (62%) arose in the paternal germline. We observed a 2~3 fold increase of large CNV burden in the mothers of affected children. By implementing an evidence-based review approach, pathogenic structural variants were identified in 14.3% patients and 2.4% parents, respectively. Pathogenic CNVs in parents were all carried by mothers. The maternal transmission bias of deleterious CNVs was further replicated in a published dataset. Our study confirms the pathogenic role of rare CNVs in MR/DD, and provides additional evidence to evaluate the dosage sensitivity of some candidate genes. It also supports a population model of MR/DD that spontaneous mutations in males' germline are major contributor to the de novo mutational burden in offspring, with higher penetrance in male than female; unaffected carriers of causative mutations, mostly females, then contribute to the inherited mutational burden.
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Affiliation(s)
- Binbin Wang
- Department of Pediatrics, Peking University First Hospital, Beijing, China.,National Research Institute of Family Planning, Beijing, China
| | - Taoyun Ji
- Department of Pediatrics, Peking University First Hospital, Beijing, China
| | - Xueya Zhou
- MOE Key Laboratory of Bioinformatics, Bioinformatics Division and Center for Synthetic and Systems Biology, TNLIST/Department of Automation, Tsinghua University, Beijing, China.,Department of Psychiatry and Centre for Genomic Sciences, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China
| | - Jing Wang
- Department of Medical Genetics, The Capital Medical University, Beijing, China
| | - Xi Wang
- National Research Institute of Family Planning, Beijing, China
| | - Jingmin Wang
- Department of Pediatrics, Peking University First Hospital, Beijing, China
| | | | - Xuejun Zhang
- Institute of Dermatology and Department of Dermatology at No.1 Hospital, Anhui Medical University, Heifei, Anhui, China
| | - Pak Chung Sham
- Department of Psychiatry and Centre for Genomic Sciences, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China
| | - Xuegong Zhang
- MOE Key Laboratory of Bioinformatics, Bioinformatics Division and Center for Synthetic and Systems Biology, TNLIST/Department of Automation, Tsinghua University, Beijing, China
| | - Xu Ma
- National Research Institute of Family Planning, Beijing, China
| | - Yuwu Jiang
- Department of Pediatrics, Peking University First Hospital, Beijing, China
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Yang X, Li R, Fu F, Zhang Y, Li D, Liao C. Submicroscopic chromosomal abnormalities in fetuses with increased nuchal translucency and normal karyotype. J Matern Fetal Neonatal Med 2016; 30:194-198. [DOI: 10.3109/14767058.2016.1168394] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
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42
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Cappuccio G, Vitiello F, Casertano A, Fontana P, Genesio R, Bruzzese D, Ginocchio VM, Mormile A, Nitsch L, Andria G, Melis D. New insights in the interpretation of array-CGH: autism spectrum disorder and positive family history for intellectual disability predict the detection of pathogenic variants. Ital J Pediatr 2016; 42:39. [PMID: 27072107 PMCID: PMC4830019 DOI: 10.1186/s13052-016-0246-7] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/20/2015] [Accepted: 03/15/2016] [Indexed: 12/08/2022] Open
Abstract
BACKGROUND Array-CGH (aCGH) is presently used into routine clinical practice for diagnosis of patients with intellectual disability (ID), multiple congenital anomalies (MCA), and autism spectrum disorder (ASD). ACGH could detect small chromosomal imbalances, copy number variations (CNVs), and closely define their size and gene content. ACGH detects pathogenic imbalances in 14-20 % of patients with ID. The aims of this study were: to establish clinical clues potentially associated with pathogenic CNVs and to identify cytogenetic indicators to predict the pathogenicity of the variants of uncertain significance (VOUS) in a large cohort of paediatric patients. METHODS We enrolled 214 patients referred for either: ID, and/or ASD and/or MCA to genetic services at the Federico II University of Naples, Department of Translational Medicine. For each patient we collected clinical and imaging data. All the patients were tested with aCGH or as first-tier test or as part of a wider diagnostic work-up. RESULTS Pathologic data were detected in 65 individuals (30 %) and 46 CNVs revealed a known syndrome. The pathological CNVs were usually deletions showing the highest gene-dosage content. The positive family history for ID/ASD/MCA and ASD were good indicators for detecting pathological chromosomal rearrangements. Other clinical features as eyes anomalies, hearing loss, neurological signs, cutaneous dyscromia and endocrinological problems seem to be potential predictors of pathological CNVs. Among patients carrying VOUS we analyzed genetic features including CNVs size, presence of deletion or duplication, genic density, multiple CNVs, to clinical features. Higher gene density was found in patients affected by ID. This result suggest that higher gene content has more chances to include pathogenic gene involved and causing ID in these patients. CONCLUSION Our study suggest the use of aCGH as first-tier test in patients with neurdevelopmental phenotypes. The inferred results have been used for building a flow-chart to be applied for children with ID.
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Affiliation(s)
- Gerarda Cappuccio
- Department of Translational Medical Sciences, Section of Pediatrics, Federico II University, Via Sergio Pansini 5, 80131, Naples, Italy
| | - Francesco Vitiello
- Department of Translational Medical Sciences, Section of Pediatrics, Federico II University, Via Sergio Pansini 5, 80131, Naples, Italy
| | - Alberto Casertano
- Department of Translational Medical Sciences, Section of Pediatrics, Federico II University, Via Sergio Pansini 5, 80131, Naples, Italy
| | - Paolo Fontana
- Department of Translational Medical Sciences, Section of Pediatrics, Federico II University, Via Sergio Pansini 5, 80131, Naples, Italy
| | - Rita Genesio
- Department of Molecular Medicine and Medical Biotechnology, Federico II University, Naples, Italy
| | - Dario Bruzzese
- Preventive Medical Sciences, Federico II University, Naples, Italy
| | | | - Angela Mormile
- Department of Molecular Medicine and Medical Biotechnology, Federico II University, Naples, Italy
| | - Lucio Nitsch
- Department of Molecular Medicine and Medical Biotechnology, Federico II University, Naples, Italy
| | - Generoso Andria
- Department of Translational Medical Sciences, Section of Pediatrics, Federico II University, Via Sergio Pansini 5, 80131, Naples, Italy
| | - Daniela Melis
- Department of Translational Medical Sciences, Section of Pediatrics, Federico II University, Via Sergio Pansini 5, 80131, Naples, Italy.
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Harrison SM, Riggs ER, Maglott DR, Lee JM, Azzariti DR, Niehaus A, Ramos EM, Martin CL, Landrum MJ, Rehm HL. Using ClinVar as a Resource to Support Variant Interpretation. ACTA ACUST UNITED AC 2016; 89:8.16.1-8.16.23. [PMID: 27037489 DOI: 10.1002/0471142905.hg0816s89] [Citation(s) in RCA: 69] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
ClinVar is a freely accessible, public archive of reports of the relationships among genomic variants and phenotypes. To facilitate evaluation of the clinical significance of each variant, ClinVar aggregates submissions of the same variant, displays supporting data from each submission, and determines if the submitted clinical interpretations are conflicting or concordant. The unit describes how to (1) identify sequence and structural variants of interest in ClinVar by multiple searching approaches, including Variation Viewer and (2) understand the display of submissions to ClinVar and the evidence supporting each interpretation. By following this protocol, ClinVar users will be able to learn how to incorporate the wealth of resources and knowledge in ClinVar into variant curation and interpretation.
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Affiliation(s)
- Steven M Harrison
- Laboratory for Molecular Medicine, Partners HealthCare Personalized Medicine, Cambridge, Massachusetts.,Harvard Medical School, Boston, Massachusetts
| | | | - Donna R Maglott
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Rockville, Maryland
| | - Jennifer M Lee
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Rockville, Maryland
| | - Danielle R Azzariti
- Laboratory for Molecular Medicine, Partners HealthCare Personalized Medicine, Cambridge, Massachusetts
| | - Annie Niehaus
- National Human Genome Research Institute, National Institutes of Health, Rockville, Maryland
| | - Erin M Ramos
- National Human Genome Research Institute, National Institutes of Health, Rockville, Maryland
| | | | - Melissa J Landrum
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Rockville, Maryland.,These authors contributed equally to this work
| | - Heidi L Rehm
- Laboratory for Molecular Medicine, Partners HealthCare Personalized Medicine, Cambridge, Massachusetts.,Harvard Medical School, Boston, Massachusetts.,These authors contributed equally to this work
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44
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Mc Cormack A, Claxton K, Ashton F, Asquith P, Atack E, Mazzaschi R, Moverley P, O'Connor R, Qorri M, Sheath K, Love DR, George AM. Microarray testing in clinical diagnosis: an analysis of 5,300 New Zealand patients. Mol Cytogenet 2016; 9:29. [PMID: 27034718 PMCID: PMC4815202 DOI: 10.1186/s13039-016-0237-9] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2016] [Accepted: 03/17/2016] [Indexed: 11/14/2022] Open
Abstract
Background The use of Microarray (array CGH) analysis has become a widely accepted front-line test replacing G banded chromosome studies for patients with an unexplained phenotype. We detail our findings of over 5300 cases. Results Of 5369 pre and postnatal samples, copy number variants (CNVs) were detected in 28.3 %, of which ~40 % were deletions and ~60 % were duplications. 96.8 % of cases with a CNV <5 Mb would not have been detected by G banding. At least 4.9 % were determined to meet the minimum criteria for a known syndrome. Chromosome 17 provided the greatest proportion of pathogenic CNVs with 65 % classified as (likely) pathogenic. X chromosome CNVs were the most commonly detected accounting for 4.2 % of cases, 0.7 % of these being classified as cryptic (likely) pathogenic CNVs. Conclusions Microarray analysis as a primary testing strategy has led to a significant increase in the detection of CNVs (~29 % overall), with ~9 % carrying pathogenic CNVs and one syndromic case identified per 20 referred patients. We suggest these frequencies are consistent with other heterogeneous studies. Conversely, (likely) pathogenic X chromosome CNVs appear to be greater compared with previous studies.
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Affiliation(s)
- Adrian Mc Cormack
- Diagnostic Genetics, LabPLUS, Auckland City Hospital, PO Box 110031, Auckland, 1148 New Zealand
| | - Karen Claxton
- Diagnostic Genetics, LabPLUS, Auckland City Hospital, PO Box 110031, Auckland, 1148 New Zealand
| | - Fern Ashton
- Diagnostic Genetics, LabPLUS, Auckland City Hospital, PO Box 110031, Auckland, 1148 New Zealand
| | - Philip Asquith
- Diagnostic Genetics, LabPLUS, Auckland City Hospital, PO Box 110031, Auckland, 1148 New Zealand
| | - Edward Atack
- Diagnostic Genetics, LabPLUS, Auckland City Hospital, PO Box 110031, Auckland, 1148 New Zealand
| | - Roberto Mazzaschi
- Diagnostic Genetics, LabPLUS, Auckland City Hospital, PO Box 110031, Auckland, 1148 New Zealand
| | - Paula Moverley
- Diagnostic Genetics, LabPLUS, Auckland City Hospital, PO Box 110031, Auckland, 1148 New Zealand ; Present address: Pacific Edge Ltd, 87 St David St, North Dunedin, 9016 New Zealand
| | - Rachel O'Connor
- Diagnostic Genetics, LabPLUS, Auckland City Hospital, PO Box 110031, Auckland, 1148 New Zealand
| | - Methat Qorri
- Diagnostic Genetics, LabPLUS, Auckland City Hospital, PO Box 110031, Auckland, 1148 New Zealand
| | - Karen Sheath
- Diagnostic Genetics, LabPLUS, Auckland City Hospital, PO Box 110031, Auckland, 1148 New Zealand
| | - Donald R Love
- Diagnostic Genetics, LabPLUS, Auckland City Hospital, PO Box 110031, Auckland, 1148 New Zealand
| | - Alice M George
- Diagnostic Genetics, LabPLUS, Auckland City Hospital, PO Box 110031, Auckland, 1148 New Zealand
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Van Opstal D, de Vries F, Govaerts L, Boter M, Lont D, van Veen S, Joosten M, Diderich K, Galjaard RJ, Srebniak MI. Benefits and burdens of using a SNP array in pregnancies at increased risk for the common aneuploidies. Hum Mutat 2015; 36:319-26. [PMID: 25504762 DOI: 10.1002/humu.22742] [Citation(s) in RCA: 48] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2014] [Accepted: 12/09/2014] [Indexed: 11/09/2022]
Abstract
We present the nature of pathogenic SNP array findings in pregnancies without ultrasound (US) abnormalities and show the additional diagnostic value of SNP array as compared with rapid aneuploidy detection and karyotyping. 1,330 prenatal samples were investigated with a 0.5-Mb SNP array after the exclusion of the most common aneuploidies. In 2.7% (36/1,330) of the cases, pathogenic chromosome aberrations were found; a microscopically detectable abnormality in 0.7% and a submicroscopic aberration in 2%. Our results show that in addition to the age- or screening-related aneuploidy risk, in pregnancies without US abnormalities, there is a risk of 1:148 (9/1,330) for a (sub)microscopic abnormality associated with an early-onset often severe disease, 1:222 (6/1,330) for a submicroscopic aberration causing an early-onset disease, 1:74 (18/1,330) for carrying a susceptibility locus for a neurodevelopmental disorder, and 1:443 (3/1,330) for a late-onset disorder (hereditary neuropathy with liability to pressure palsies in all three cases). These risk figures are important for adequate pretest counseling so that prospective parents can make informed individualized choices between targeted prenatal testing and broad testing with SNP array. Based on our results, we believe if invasive testing is performed, SNP array should be the preferred cytogenetic technique irrespective of the indication.
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Affiliation(s)
- Diane Van Opstal
- Department of Clinical Genetics, Erasmus Medical Center, Rotterdam, The Netherlands
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Srebniak MI, Diderich KE, Joosten M, Govaerts LC, Knijnenburg J, de Vries FA, Boter M, Lont D, Knapen MF, de Wit MC, Go AT, Galjaard RJH, Van Opstal D. Prenatal SNP array testing in 1000 fetuses with ultrasound anomalies: causative, unexpected and susceptibility CNVs. Eur J Hum Genet 2015; 24:645-51. [PMID: 26328504 DOI: 10.1038/ejhg.2015.193] [Citation(s) in RCA: 51] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2014] [Revised: 06/29/2015] [Accepted: 07/22/2015] [Indexed: 11/09/2022] Open
Abstract
To evaluate the diagnostic value of single-nucleotide polymorphism (SNP) array testing in 1033 fetuses with ultrasound anomalies we investigated the prevalence and genetic nature of pathogenic findings. We reclassified all pathogenic findings into three categories: causative findings; unexpected diagnoses (UD); and susceptibility loci (SL) for neurodevelopmental disorders. After exclusion of trisomy 13, 18, 21, sex-chromosomal aneuploidy and triploidies, in 76/1033 (7.4%) fetuses a pathogenic chromosome abnormality was detected by genomic SNP array: in 19/1033 cases (1.8%) a microscopically detectable abnormality was found and in 57/1033 (5.5%) fetuses a pathogenic submicroscopic chromosome abnormality was detected. 58% (n=44) of all these pathogenic chromosome abnormalities involved a causative finding, 35% (n=27) a SL for neurodevelopmental disorder, and 6% (n=5) a UD of an early-onset untreatable disease. In 0.3% of parental samples an incidental pathogenic finding was encountered. Our results confirm that a genomic array should be the preferred first-tier technique in fetuses with ultrasound anomalies. All UDs involved early-onset diseases, which is beneficial for the patients to know. It also seems that UDs occur at a comparable frequency among microscopic and submicroscopic pathogenic findings. SL were more often detected than in pregnancies without ultrasound anomalies.
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Affiliation(s)
| | - Karin Em Diderich
- Department of Clinical Genetics, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Marieke Joosten
- Department of Clinical Genetics, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Lutgarde Cp Govaerts
- Department of Clinical Genetics, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Jeroen Knijnenburg
- Department of Clinical Genetics, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Femke At de Vries
- Department of Clinical Genetics, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Marjan Boter
- Department of Clinical Genetics, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Debora Lont
- Department of Clinical Genetics, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Maarten Fcm Knapen
- Department of Obstetrics and Gynecology, Erasmus Medical Center, Rotterdam, The Netherlands.,Foundation Prenatal Screening Southwest region of the Netherlands, Rotterdam, The Netherlands
| | - Merel C de Wit
- Department of Obstetrics and Gynecology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Attie Tji Go
- Department of Obstetrics and Gynecology, Erasmus Medical Center, Rotterdam, The Netherlands
| | | | - Diane Van Opstal
- Department of Clinical Genetics, Erasmus Medical Center, Rotterdam, The Netherlands
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Martin CL, Warburton D. Detection of Chromosomal Aberrations in Clinical Practice: From Karyotype to Genome Sequence. Annu Rev Genomics Hum Genet 2015; 16:309-26. [DOI: 10.1146/annurev-genom-090413-025346] [Citation(s) in RCA: 41] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Affiliation(s)
- Christa Lese Martin
- Autism & Developmental Medicine Institute, Geisinger Health System, Danville, Pennsylvania 17822;
| | - Dorothy Warburton
- Department of Clinical Genetics and Development, Columbia University Medical Center, New York, NY 10032;
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48
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Noor A, Stavropoulos DJ. Current Tools for Interpretation of Genomic Copy Number Variants. CURRENT GENETIC MEDICINE REPORTS 2015. [DOI: 10.1007/s40142-015-0078-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
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49
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Poot M, Haaf T. Mechanisms of Origin, Phenotypic Effects and Diagnostic Implications of Complex Chromosome Rearrangements. Mol Syndromol 2015; 6:110-34. [PMID: 26732513 DOI: 10.1159/000438812] [Citation(s) in RCA: 63] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/23/2015] [Indexed: 01/08/2023] Open
Abstract
Complex chromosome rearrangements (CCRs) are currently defined as structural genome variations that involve more than 2 chromosome breaks and result in exchanges of chromosomal segments. They are thought to be extremely rare, but their detection rate is rising because of improvements in molecular cytogenetic technology. Their population frequency is also underestimated, since many CCRs may not elicit a phenotypic effect. CCRs may be the result of fork stalling and template switching, microhomology-mediated break-induced repair, breakage-fusion-bridge cycles, or chromothripsis. Patients with chromosomal instability syndromes show elevated rates of CCRs due to impaired DNA double-strand break responses during meiosis. Therefore, the putative functions of the proteins encoded by ATM, BLM, WRN, ATR, MRE11, NBS1, and RAD51 in preventing CCRs are discussed. CCRs may exert a pathogenic effect by either (1) gene dosage-dependent mechanisms, e.g. haploinsufficiency, (2) mechanisms based on disruption of the genomic architecture, such that genes, parts of genes or regulatory elements are truncated, fused or relocated and thus their interactions disturbed - these mechanisms will predominantly affect gene expression - or (3) mixed mutation mechanisms in which a CCR on one chromosome is combined with a different type of mutation on the other chromosome. Such inferred mechanisms of pathogenicity need corroboration by mRNA sequencing. Also, future studies with in vitro models, such as inducible pluripotent stem cells from patients with CCRs, and transgenic model organisms should substantiate current inferences regarding putative pathogenic effects of CCRs. The ramifications of the growing body of information on CCRs for clinical and experimental genetics and future treatment modalities are briefly illustrated with 2 cases, one of which suggests KDM4C (JMJD2C) as a novel candidate gene for mental retardation.
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Affiliation(s)
- Martin Poot
- Department of Human Genetics, University of Würzburg, Würzburg, Germany
| | - Thomas Haaf
- Department of Human Genetics, University of Würzburg, Würzburg, Germany
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50
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Ormond KE, Rashkin M, Faucett WA. Standardizing Variant Interpretation in Genomic Sequencing: Implications for Genetic Counseling Practice. CURRENT GENETIC MEDICINE REPORTS 2015. [DOI: 10.1007/s40142-015-0073-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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