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Zhang Y, Du Q, Gao H, Pan Y, Liu N, Qiu C, Liu X. Prenatal risk assessment of Xp21.1 duplication involving the DMD gene by optical genome mapping. Life Sci Alliance 2024; 7:e202402780. [PMID: 39117454 PMCID: PMC11310561 DOI: 10.26508/lsa.202402780] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2024] [Revised: 08/01/2024] [Accepted: 08/01/2024] [Indexed: 08/10/2024] Open
Abstract
Structural variants (SVs) of unknown significance are great challenges for prenatal risk assessment, especially when involving dose-sensitive genes such as DMD The pathogenicities of 5'-terminal DMD duplications in the database remain controversial. Four prenatal cases with Xp21.1 duplications were identified by routine prenatal genomic testing, encompassing the 5'-UTR to exons 1-2 in family 1 and family 2, and to exons 1-9 in family 3. The duplication in family 4 was non-contiguous covering the 5'-UTR to exon 1 and exons 3-7. All were traced to unaffected males in the family pedigrees. A new genome-wide approach of optical genome mapping was performed in families 1, 2, and 3 to delineate the breakpoints and orientation of the duplicated fragments. The extra copies were tandemly inserted into the upstream of DMD, preserving the integrity of ORF from the second copy. The pathogenicities were thus reclassified as likely benign. Our data highlight the importance of structural delineation by optical genome mapping in prenatal risk assessment of incidentally identified SVs involving DMD and other similar large dose-sensitive genes.
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Affiliation(s)
- Yuanyuan Zhang
- Department of Clinical Genetics, Shengjing Hospital of China Medical University, Shenyang, China
| | - Qiang Du
- Center of Reproductive Medicine, Shengjing Hospital of China Medical University, Shenyang, China
| | - Haiming Gao
- Department of Clinical Genetics, Shengjing Hospital of China Medical University, Shenyang, China
| | - Yujie Pan
- Department of Clinical Genetics, Shengjing Hospital of China Medical University, Shenyang, China
| | - Ningyang Liu
- Department of Laboratory Medicine, Shengjing Hospital of China Medical University, Shenyang, China
| | - Chuang Qiu
- Department of Orthopedics, Shengjing Hospital of China Medical University, Shenyang, China
| | - Xiaoliang Liu
- Department of Clinical Genetics, Shengjing Hospital of China Medical University, Shenyang, China
- Key Laboratory of Reproductive Health, Liaoning Research Institute of Reproductive Health and Development, Reproductive Hospital of China Medical University, Shenyang, China
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Rugerio-Martínez CI, Ramos D, Segura-Olvera A, Murillo-Melo NM, Tapia-Guerrero YS, Argüello-García R, Leyva-García N, Hernández-Hernández O, Cisneros B, Suárez-Sánchez R. Dp71 Point Mutations Induce Protein Aggregation, Loss of Nuclear Lamina Integrity and Impaired Braf35 and Ibraf Function in Neuronal Cells. Int J Mol Sci 2022; 23:ijms231911876. [PMID: 36233175 PMCID: PMC9570083 DOI: 10.3390/ijms231911876] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2022] [Revised: 10/04/2022] [Accepted: 10/04/2022] [Indexed: 11/16/2022] Open
Abstract
Dystrophin Dp71 is the most abundant product of the Duchenne muscular dystrophy gene in the nervous system, and mutations impairing its function have been associated with the neurodevelopmental symptoms present in a third of DMD patients. Dp71 is required for the clustering of neurotransmitter receptors and the neuronal differentiation of cultured cells; nonetheless, its precise role in neuronal cells remains to be poorly understood. In this study, we analyzed the effect of two pathogenic DMD gene point mutations on the Dp71 function in neurons. We engineered C272Y and E299del mutations to express GFP-tagged Dp71 protein variants in N1E-115 and SH-SY5Y neuronal cells. Unexpectedly, the ectopic expression of Dp71 mutants resulted in protein aggregation, which may be mechanistically caused by the effect of the mutations on Dp71 structure, as predicted by protein modeling and molecular dynamics simulations. Interestingly, Dp71 mutant variants acquired a dominant negative function that, in turn, dramatically impaired the distribution of different Dp71 protein partners, including β-dystroglycan, nuclear lamins A/C and B1, the high-mobility group (HMG)-containing protein (BRAF35) and the BRAF35-family-member inhibitor of BRAF35 (iBRAF). Further analysis of Dp71 mutants provided evidence showing a role for Dp71 in modulating both heterochromatin marker H3K9me2 organization and the neuronal genes’ expression, via its interaction with iBRAF and BRAF5.
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Affiliation(s)
- Claudia Ivette Rugerio-Martínez
- Laboratorio de Medicina Genómica, Departamento de Genética, Instituto Nacional de Rehabilitación-Luis Guillermo Ibarra Ibarra, Ciudad de Mexico 14389, Mexico
- Departamento de Genética y Biología Molecular, Centro de Investigación y de Estudios Avanzados del Instituto Politécnico Nacional, Ciudad de Mexico 07360, Mexico
| | - Daniel Ramos
- Laboratorio de Medicina Genómica, Departamento de Genética, Instituto Nacional de Rehabilitación-Luis Guillermo Ibarra Ibarra, Ciudad de Mexico 14389, Mexico
| | - Abel Segura-Olvera
- Laboratorio de Medicina Genómica, Departamento de Genética, Instituto Nacional de Rehabilitación-Luis Guillermo Ibarra Ibarra, Ciudad de Mexico 14389, Mexico
| | - Nadia Mireya Murillo-Melo
- Laboratorio de Medicina Genómica, Departamento de Genética, Instituto Nacional de Rehabilitación-Luis Guillermo Ibarra Ibarra, Ciudad de Mexico 14389, Mexico
| | - Yessica Sarai Tapia-Guerrero
- Laboratorio de Medicina Genómica, Departamento de Genética, Instituto Nacional de Rehabilitación-Luis Guillermo Ibarra Ibarra, Ciudad de Mexico 14389, Mexico
| | - Raúl Argüello-García
- Departamento de Genética y Biología Molecular, Centro de Investigación y de Estudios Avanzados del Instituto Politécnico Nacional, Ciudad de Mexico 07360, Mexico
| | - Norberto Leyva-García
- Laboratorio de Medicina Genómica, Departamento de Genética, Instituto Nacional de Rehabilitación-Luis Guillermo Ibarra Ibarra, Ciudad de Mexico 14389, Mexico
| | - Oscar Hernández-Hernández
- Laboratorio de Medicina Genómica, Departamento de Genética, Instituto Nacional de Rehabilitación-Luis Guillermo Ibarra Ibarra, Ciudad de Mexico 14389, Mexico
| | - Bulmaro Cisneros
- Departamento de Genética y Biología Molecular, Centro de Investigación y de Estudios Avanzados del Instituto Politécnico Nacional, Ciudad de Mexico 07360, Mexico
| | - Rocío Suárez-Sánchez
- Laboratorio de Medicina Genómica, Departamento de Genética, Instituto Nacional de Rehabilitación-Luis Guillermo Ibarra Ibarra, Ciudad de Mexico 14389, Mexico
- Correspondence: or ; Tel.: +52-55-5999-1000 (ext. 14710)
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Cohen G, Asor AS, Ben-Shahar S, Goldfarb-Yaacobi R, Kaiser M, Rosenfeld R, Vinovezky M, Irge D, Furman Y, Reiss D, Litz-Philipsborn S, Sukenik-Halevy R. Large scale population screening for Duchenne muscular dystrophy - Predictable and unpredictable challenges. Prenat Diagn 2022; 42:1162-1172. [PMID: 35751502 PMCID: PMC9546335 DOI: 10.1002/pd.6201] [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: 02/25/2022] [Revised: 06/05/2022] [Accepted: 06/21/2022] [Indexed: 11/10/2022]
Abstract
Objective Large deletions and duplications account for 65%–80% of pathogenic Duchenne muscular dystrophy (DMD) variants. A nationwide carrier screening for DMD was initiated in Israel in 2020. We assessed the carrier rate and spectrum of variants detected in a cohort of women screened for DMD carrier status and analyzed screening efficacy and challenges related to DMD population screening. Methods A cohort of 12,362 women were tested at a single institute using multiplex ligation‐dependent probe amplification based copy number analysis of the 79 DMD exons. Consecutive sequencing of the primer region was performed when a single exon deletion was suspected. Results Deletions involving multiple exons were detected in seven cases and duplications involving multiple exons were found in four. Of these, nine were pathogenic based on previous reports and familial segregation testing, translating to a carrier rate of 1:1374. A family history was reported in three cases. Single exon deletions were suspected in 81 cases; further sequencing detected a single nucleotide variant affecting probe hybridization. These cases clustered according to ethnic origin. Discussion Population screening for DMD has a significant yield. Most carriers did not report a family history of dystrophinopathies. Screening should be adjusted for methodological limitations. Some cases may require extensive genetic counseling and work‐up.
What's already known about this topic?
Deletions and duplications account for 65%–80% of pathogenic Duchenne muscular dystrophy (DMD) variants. About two‐thirds of DMD pathogenic variants are inherited from a female carrier. A nationwide carrier screening for DMD was initiated in Israel in 2020.
What does this study add?
The carrier rate among 12,362 women tested for deletions and duplications in the DMD gene was 1:1374. Screening should be adjusted for methodological limitations and may require extensive genetic counseling and work‐up.
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Affiliation(s)
- Gal Cohen
- Meir Medical Center, Kfar Saba, Israel.,Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Atalia Shtorch Asor
- Meir Medical Center, Kfar Saba, Israel.,Genetics Institute, Meir Medical Center, Kfar Saba, Israel.,Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Shay Ben-Shahar
- Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel.,Clalit Innovation division, Clalit Health System, Tel Aviv, Israel
| | - Racheli Goldfarb-Yaacobi
- Meir Medical Center, Kfar Saba, Israel.,Genetics Institute, Meir Medical Center, Kfar Saba, Israel.,Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
| | | | | | | | - Dana Irge
- Meir Medical Center, Kfar Saba, Israel.,Genetics Institute, Meir Medical Center, Kfar Saba, Israel.,Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Yael Furman
- Meir Medical Center, Kfar Saba, Israel.,Genetics Institute, Meir Medical Center, Kfar Saba, Israel.,Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Dafni Reiss
- Meir Medical Center, Kfar Saba, Israel.,Genetics Institute, Meir Medical Center, Kfar Saba, Israel.,Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Shira Litz-Philipsborn
- Meir Medical Center, Kfar Saba, Israel.,Genetics Institute, Meir Medical Center, Kfar Saba, Israel.,Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Rivka Sukenik-Halevy
- Meir Medical Center, Kfar Saba, Israel.,Genetics Institute, Meir Medical Center, Kfar Saba, Israel.,Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
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Parodi S, Manneschi C, Verda D, Ferrari E, Muselli M. Logic Learning Machine and standard supervised methods for Hodgkin's lymphoma prognosis using gene expression data and clinical variables. Health Informatics J 2016; 24:54-65. [PMID: 27354395 DOI: 10.1177/1460458216655188] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Abstract
This study evaluates the performance of a set of machine learning techniques in predicting the prognosis of Hodgkin's lymphoma using clinical factors and gene expression data. Analysed samples from 130 Hodgkin's lymphoma patients included a small set of clinical variables and more than 54,000 gene features. Machine learning classifiers included three black-box algorithms ( k-nearest neighbour, Artificial Neural Network, and Support Vector Machine) and two methods based on intelligible rules (Decision Tree and the innovative Logic Learning Machine method). Support Vector Machine clearly outperformed any of the other methods. Among the two rule-based algorithms, Logic Learning Machine performed better and identified a set of simple intelligible rules based on a combination of clinical variables and gene expressions. Decision Tree identified a non-coding gene ( XIST) involved in the early phases of X chromosome inactivation that was overexpressed in females and in non-relapsed patients. XIST expression might be responsible for the better prognosis of female Hodgkin's lymphoma patients.
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Affiliation(s)
- Stefano Parodi
- National Research Council of Italy, Italy.,Rulex Inc, USA
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