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Neuhofer CM, Prokisch H. Digenic Inheritance in Rare Disorders and Mitochondrial Disease-Crossing the Frontier to a More Comprehensive Understanding of Etiology. Int J Mol Sci 2024; 25:4602. [PMID: 38731822 PMCID: PMC11083678 DOI: 10.3390/ijms25094602] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2024] [Revised: 04/10/2024] [Accepted: 04/12/2024] [Indexed: 05/13/2024] Open
Abstract
Our understanding of rare disease genetics has been shaped by a monogenic disease model. While the traditional monogenic disease model has been successful in identifying numerous disease-associated genes and significantly enlarged our knowledge in the field of human genetics, it has limitations in explaining phenomena like phenotypic variability and reduced penetrance. Widening the perspective beyond Mendelian inheritance has the potential to enable a better understanding of disease complexity in rare disorders. Digenic inheritance is the simplest instance of a non-Mendelian disorder, characterized by the functional interplay of variants in two disease-contributing genes. Known digenic disease causes show a range of pathomechanisms underlying digenic interplay, including direct and indirect gene product interactions as well as epigenetic modifications. This review aims to systematically explore the background of digenic inheritance in rare disorders, the approaches and challenges when investigating digenic inheritance, and the current evidence for digenic inheritance in mitochondrial disorders.
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Affiliation(s)
- Christiane M. Neuhofer
- Institute of Human Genetics, University Medical Center, Technical University of Munich, Trogerstr. 32, 81675 Munich, Germany
- Institute of Neurogenomics, Computational Health Center, Helmholtz Centre Munich Neuherberg, Ingolstädter Landstraße 1, 85764 Oberschleißheim, Germany
- Institute of Human Genetics, Salzburger Landeskliniken, University Hospital of the Paracelsus Medical University, Müllner Hauptstraße 48, 5020 Salzburg, Austria
| | - Holger Prokisch
- Institute of Human Genetics, University Medical Center, Technical University of Munich, Trogerstr. 32, 81675 Munich, Germany
- Institute of Neurogenomics, Computational Health Center, Helmholtz Centre Munich Neuherberg, Ingolstädter Landstraße 1, 85764 Oberschleißheim, Germany
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Zhong J, Wang C, Zhang D, Yao X, Zhao Q, Huang X, Lin F, Xue C, Wang Y, He R, Li XY, Li Q, Wang M, Zhao S, Afridi SK, Zhou W, Wang Z, Xu Y, Xu Z. PCDHA9 as a candidate gene for amyotrophic lateral sclerosis. Nat Commun 2024; 15:2189. [PMID: 38467605 PMCID: PMC10928119 DOI: 10.1038/s41467-024-46333-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2023] [Accepted: 02/23/2024] [Indexed: 03/13/2024] Open
Abstract
Amyotrophic lateral sclerosis (ALS) is a devastating neurodegenerative disease. To identify additional genetic factors, we analyzed exome sequences in a large cohort of Chinese ALS patients and found a homozygous variant (p.L700P) in PCDHA9 in three unrelated patients. We generated Pcdhα9 mutant mice harboring either orthologous point mutation or deletion mutation. These mice develop progressive spinal motor loss, muscle atrophy, and structural/functional abnormalities of the neuromuscular junction, leading to paralysis and early lethality. TDP-43 pathology is detected in the spinal motor neurons of aged mutant mice. Mechanistically, we demonstrate that Pcdha9 mutation causes aberrant activation of FAK and PYK2 in aging spinal cord, and dramatically reduced NKA-α1 expression in motor neurons. Our single nucleus multi-omics analysis reveals disturbed signaling involved in cell adhesion, ion transport, synapse organization, and neuronal survival in aged mutant mice. Together, our results present PCDHA9 as a potential ALS gene and provide insights into its pathogenesis.
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Affiliation(s)
- Jie Zhong
- State Key Laboratory of Molecular Developmental Biology, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, 100101, China
- University of Chinese Academy of Sciences, Beijing, 100101, China
| | - Chaodong Wang
- Department of Neurology, Xuanwu Hospital, Capital Medical University, National Clinical Research Center for Geriatric Disease, Beijing, 100053, China.
| | - Dan Zhang
- State Key Laboratory of Molecular Developmental Biology, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, 100101, China
- University of Chinese Academy of Sciences, Beijing, 100101, China
| | - Xiaoli Yao
- Department of Neurology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, 510080, China
| | - Quanzhen Zhao
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, 610041, China
| | - Xusheng Huang
- Department of Neurology, The First Medical Center, Chinese PLA General Hospital, Beijing, 100853, China
| | - Feng Lin
- Department of Neurology, Fujian Medical University Union Hospital, Fuzhou, 350001, China
| | - Chun Xue
- State Key Laboratory of Molecular Developmental Biology, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, 100101, China
- University of Chinese Academy of Sciences, Beijing, 100101, China
| | - Yaqing Wang
- State Key Laboratory of Molecular Developmental Biology, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, 100101, China
- University of Chinese Academy of Sciences, Beijing, 100101, China
| | - Ruojie He
- Department of Neurology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, 510080, China
| | - Xu-Ying Li
- Department of Neurology, Xuanwu Hospital, Capital Medical University, National Clinical Research Center for Geriatric Disease, Beijing, 100053, China
| | - Qibin Li
- Shenzhen Clabee Biotechnology Incorporation, Shenzhen, 518057, China
| | - Mingbang Wang
- Shanghai Key Laboratory of Birth Defects, Division of Neonatology, Children's Hospital of Fudan University, National Center for Children's Health, Shanghai, 201102, China
| | - Shaoli Zhao
- State Key Laboratory of Molecular Developmental Biology, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, 100101, China
- University of Chinese Academy of Sciences, Beijing, 100101, China
| | - Shabbir Khan Afridi
- State Key Laboratory of Molecular Developmental Biology, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, 100101, China
- University of Chinese Academy of Sciences, Beijing, 100101, China
| | - Wenhao Zhou
- Shanghai Key Laboratory of Birth Defects, Division of Neonatology, Children's Hospital of Fudan University, National Center for Children's Health, Shanghai, 201102, China
| | - Zhanjun Wang
- Department of Neurology, Xuanwu Hospital, Capital Medical University, National Clinical Research Center for Geriatric Disease, Beijing, 100053, China
| | - Yanming Xu
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, 610041, China.
| | - Zhiheng Xu
- State Key Laboratory of Molecular Developmental Biology, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, 100101, China.
- University of Chinese Academy of Sciences, Beijing, 100101, China.
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Geng Z, Li W, Yang P, Zhang S, Wu S, Xiong J, Sun K, Zhu D, Chen S, Zhang B. Whole exome sequencing reveals genetic landscape associated with left ventricular outflow tract obstruction in Chinese Han population. Front Genet 2023; 14:1267368. [PMID: 38164514 PMCID: PMC10757952 DOI: 10.3389/fgene.2023.1267368] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2023] [Accepted: 11/29/2023] [Indexed: 01/03/2024] Open
Abstract
Left ventricular outflow tract obstruction (LVOTO), a major form of outflow tract malformation, accounts for a substantial portion of congenital heart defects (CHDs). Unlike its prevalence, the genetic architecture of LVOTO remains largely unknown. To unveil the genetic mutations and risk genes potentially associated with LVOTO, we enrolled a cohort of 106 LVOTO patients and 100 healthy controls and performed a whole-exome sequencing (WES). 71,430 rare deleterious mutations were found in LVOTO patients. By using gene-based burden testing, we further found 32 candidate genes enriched in LVOTO patient including known pathological genes such as GATA5 and GATA6. Most variants of 32 risk genes occur simultaneously rather exclusively suggesting polygenic inherence of LVOTO and 14 genes out of 32 risk genes interact with previously discovered CHD genes. Single cell RNA-seq further revealed dynamic expressions of GATA5, GATA6, FOXD3 and MYO6 in endocardium and neural crest lineage indicating the mutations of these genes lead to LVOTO possibly through different lineages. These findings uncover the genetic architecture of LVOTO which advances the current understanding of LVOTO genetics.
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Affiliation(s)
- Zilong Geng
- Key Laboratory of Systems Biomedicine, Ministry of Education, Shanghai Center for Systems Biomedicine, Shanghai Jiao Tong University, Shanghai, China
| | - Wenjuan Li
- Department of Pediatric Cardiology, Xinhua Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Ping Yang
- Key Laboratory of Systems Biomedicine, Ministry of Education, Shanghai Center for Systems Biomedicine, Shanghai Jiao Tong University, Shanghai, China
| | - Shasha Zhang
- Key Laboratory of Systems Biomedicine, Ministry of Education, Shanghai Center for Systems Biomedicine, Shanghai Jiao Tong University, Shanghai, China
| | - Shuo Wu
- Key Laboratory of Systems Biomedicine, Ministry of Education, Shanghai Center for Systems Biomedicine, Shanghai Jiao Tong University, Shanghai, China
| | - Junhao Xiong
- Key Laboratory of Systems Biomedicine, Ministry of Education, Shanghai Center for Systems Biomedicine, Shanghai Jiao Tong University, Shanghai, China
| | - Kun Sun
- Department of Pediatric Cardiology, Xinhua Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Dan Zhu
- Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, China
| | - Sun Chen
- Department of Pediatric Cardiology, Xinhua Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Bing Zhang
- Key Laboratory of Systems Biomedicine, Ministry of Education, Shanghai Center for Systems Biomedicine, Shanghai Jiao Tong University, Shanghai, China
- Department of Pediatric Cardiology, Xinhua Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
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Falk I, Zhao M, Nait Saada J, Guo Q. Learning the kernel for rare variant genetic association test. Front Genet 2023; 14:1245238. [PMID: 37886683 PMCID: PMC10598548 DOI: 10.3389/fgene.2023.1245238] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2023] [Accepted: 09/14/2023] [Indexed: 10/28/2023] Open
Abstract
Introduction: Compared to Genome-Wide Association Studies (GWAS) for common variants, single-marker association analysis for rare variants is underpowered. Set-based association analyses for rare variants are powerful tools that capture some of the missing heritability in trait association studies. Methods: We extend the convex-optimized SKAT (cSKAT) test set procedure which learns from data the optimal convex combination of kernels, to the full Generalised Linear Model (GLM) setting with arbitrary non-genetic covariates. We call this extended cSKAT (ecSKAT) and show that the resulting optimization problem is a quadratic programming problem that can be solved with no additional cost compared to cSKAT. Results: We show that a modified objective is related to an upper bound for the p-value through a decreasing exponential term in the objective function, indicating that optimizing this objective function is a principled way of learning the combination of kernels. We evaluate the performance of the proposed method on continuous and binary traits using simulation studies and illustrate its application using UK Biobank Whole Exome Sequencing data on hand grip strength and systemic lupus erythematosus rare variant association analysis. Discussion: Our proposed ecSKAT method enables correcting for important confounders in association studies such as age, sex or population structure for both quantitative and binary traits. Simulation studies showed that ecSKAT can recover sensible weights and achieve higher power across different sample sizes and misspecification settings. Compared to the burden test and SKAT method, ecSKAT gives a lower p-value for the genes tested in both quantitative and binary traits in the UKBiobank cohort.
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Affiliation(s)
- Isak Falk
- Department of Computer Science, University College London, London, United Kingdom
- Computational Statistics and Machine Learning, Italian Institute of Technology, Genoa, Italy
| | | | | | - Qi Guo
- BenevolentAI, London, United Kingdom
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Boutry S, Helaers R, Lenaerts T, Vikkula M. Rare variant association on unrelated individuals in case-control studies using aggregation tests: existing methods and current limitations. Brief Bioinform 2023; 24:bbad412. [PMID: 37974506 DOI: 10.1093/bib/bbad412] [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: 02/14/2023] [Revised: 10/14/2023] [Accepted: 10/28/2023] [Indexed: 11/19/2023] Open
Abstract
Over the past years, progress made in next-generation sequencing technologies and bioinformatics have sparked a surge in association studies. Especially, genome-wide association studies (GWASs) have demonstrated their effectiveness in identifying disease associations with common genetic variants. Yet, rare variants can contribute to additional disease risk or trait heterogeneity. Because GWASs are underpowered for detecting association with such variants, numerous statistical methods have been recently proposed. Aggregation tests collapse multiple rare variants within a genetic region (e.g. gene, gene set, genomic loci) to test for association. An increasing number of studies using such methods successfully identified trait-associated rare variants and led to a better understanding of the underlying disease mechanism. In this review, we compare existing aggregation tests, their statistical features and scope of application, splitting them into the five classical classes: burden, adaptive burden, variance-component, omnibus and other. Finally, we describe some limitations of current aggregation tests, highlighting potential direction for further investigations.
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Affiliation(s)
- Simon Boutry
- Human Molecular Genetics, de Duve Institute, University of Louvain, Avenue Hippocrate 74 (+5) bte B1.74.06, 1200 Brussels, Belgium
- Interuniversity Institute of Bioinformatics in Brussels, Université Libre de Bruxelles-Vrije Universiteit Brussels, 1050 Brussels, Belgium
| | - Raphaël Helaers
- Human Molecular Genetics, de Duve Institute, University of Louvain, Avenue Hippocrate 74 (+5) bte B1.74.06, 1200 Brussels, Belgium
| | - Tom Lenaerts
- Interuniversity Institute of Bioinformatics in Brussels, Université Libre de Bruxelles-Vrije Universiteit Brussels, 1050 Brussels, Belgium
- Machine Learning Group, Université Libre de Bruxelles, 1050 Brussels, Belgium
- Artificial Intelligence laboratory, Vrije Universiteit Brussel, 1050 Brussels, Belgium
| | - Miikka Vikkula
- Human Molecular Genetics, de Duve Institute, University of Louvain, Avenue Hippocrate 74 (+5) bte B1.74.06, 1200 Brussels, Belgium
- WELBIO department, WEL Research Institute, avenue Pasteur, 6, 1300 Wavre, Belgium
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Boutry S, Helaers R, Lenaerts T, Vikkula M. Excalibur: A new ensemble method based on an optimal combination of aggregation tests for rare-variant association testing for sequencing data. PLoS Comput Biol 2023; 19:e1011488. [PMID: 37708232 PMCID: PMC10522036 DOI: 10.1371/journal.pcbi.1011488] [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: 01/30/2023] [Revised: 09/26/2023] [Accepted: 09/04/2023] [Indexed: 09/16/2023] Open
Abstract
The development of high-throughput next-generation sequencing technologies and large-scale genetic association studies produced numerous advances in the biostatistics field. Various aggregation tests, i.e. statistical methods that analyze associations of a trait with multiple markers within a genomic region, have produced a variety of novel discoveries. Notwithstanding their usefulness, there is no single test that fits all needs, each suffering from specific drawbacks. Selecting the right aggregation test, while considering an unknown underlying genetic model of the disease, remains an important challenge. Here we propose a new ensemble method, called Excalibur, based on an optimal combination of 36 aggregation tests created after an in-depth study of the limitations of each test and their impact on the quality of result. Our findings demonstrate the ability of our method to control type I error and illustrate that it offers the best average power across all scenarios. The proposed method allows for novel advances in Whole Exome/Genome sequencing association studies, able to handle a wide range of association models, providing researchers with an optimal aggregation analysis for the genetic regions of interest.
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Affiliation(s)
- Simon Boutry
- Human Molecular Genetics, de Duve Institute, University of Louvain, Brussels, Belgium
- Interuniversity Institute of Bioinformatics in Brussels, Université Libre de Bruxelles-Vrije Universiteit Brussels, Brussels, Belgium
| | - Raphaël Helaers
- Human Molecular Genetics, de Duve Institute, University of Louvain, Brussels, Belgium
| | - Tom Lenaerts
- Interuniversity Institute of Bioinformatics in Brussels, Université Libre de Bruxelles-Vrije Universiteit Brussels, Brussels, Belgium
- Machine Learning Group, Université Libre de Bruxelles, Brussels, Belgium
- Artificial Intelligence laboratory, Vrije Universiteit Brussel, Brussels, Belgium
| | - Miikka Vikkula
- Human Molecular Genetics, de Duve Institute, University of Louvain, Brussels, Belgium
- WELBIO department, WEL Research Institute, Wavre, Belgium
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7
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Massart A, Danger R, Olsen C, Emond MJ, Viklicky O, Jacquemin V, Soblet J, Duerinckx S, Croes D, Perazzolo C, Hruba P, Daneels D, Caljon B, Sever MS, Pascual J, Miglinas M, Pirson I, Ghisdal L, Smits G, Giral M, Abramowicz D, Abramowicz M, Brouard S. An exome-wide study of renal operational tolerance. Front Med (Lausanne) 2023; 9:976248. [PMID: 37265662 PMCID: PMC10230038 DOI: 10.3389/fmed.2022.976248] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2022] [Accepted: 10/31/2022] [Indexed: 06/03/2023] Open
Abstract
Background Renal operational tolerance is a rare and beneficial state of prolonged renal allograft function in the absence of immunosuppression. The underlying mechanisms are unknown. We hypothesized that tolerance might be driven by inherited protein coding genetic variants with large effect, at least in some patients. Methods We set up a European survey of over 218,000 renal transplant recipients and collected DNAs from 40 transplant recipients who maintained good allograft function without immunosuppression for at least 1 year. We performed an exome-wide association study comparing the distribution of moderate to high impact variants in 36 tolerant patients, selected for genetic homogeneity using principal component analysis, and 192 controls, using an optimal sequence-kernel association test adjusted for small samples. Results We identified rare variants of HOMER2 (3/36, FDR 0.0387), IQCH (5/36, FDR 0.0362), and LCN2 (3/36, FDR 0.102) in 10 tolerant patients vs. 0 controls. One patient carried a variant in both HOMER2 and LCN2. Furthermore, the three genes showed an identical variant in two patients each. The three genes are expressed at the primary cilium, a key structure in immune responses. Conclusion Rare protein coding variants are associated with operational tolerance in a sizable portion of patients. Our findings have important implications for a better understanding of immune tolerance in transplantation and other fields of medicine.ClinicalTrials.gov, identifier: NCT05124444.
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Affiliation(s)
- Annick Massart
- Human Genetics Unit, Institut de Recherche Interdisciplinaire en Biologie Humaine et Moléculaire (IRIBHM), Université Libre de Bruxelles (ULB), Brussels, Belgium
- Interuniversity Institute of Bioinformatics in Brussels (IB2), Université Libre de Bruxelles - Vrije Universiteit Brussel (ULB-VUB), Brussels, Belgium
- Department of Nephrology, Antwerp University Hospital and Laboratory of Experimental Medicine, University of Antwerp, Antwerp, Belgium
| | - Richard Danger
- CHU Nantes, Nantes Université, INSERM, Center for Research in Transplantation and Translational Immunology, CR2TI, UMR 1064, ITUN, Nantes, France
| | - Catharina Olsen
- Interuniversity Institute of Bioinformatics in Brussels (IB2), Université Libre de Bruxelles - Vrije Universiteit Brussel (ULB-VUB), Brussels, Belgium
- Brussels Interuniversity Genomics High Throughput Core (BRIGHTcore), VUB-ULB, Brussels, Belgium
- Center for Medical Genetics, Reproduction and Genetics, Reproduction Genetics and Regenerative Medicine, Vrije Universiteit Brussel, UZ Brussel, Brussels, Belgium
| | - Mary J. Emond
- Department of Biostatistics, University of Washington, Seattle, WA, United States
| | - Ondrej Viklicky
- Transplant Laboratory, Institute for Clinical and Experimental Medicine, Prague, Czechia
| | - Valérie Jacquemin
- Human Genetics Unit, Institut de Recherche Interdisciplinaire en Biologie Humaine et Moléculaire (IRIBHM), Université Libre de Bruxelles (ULB), Brussels, Belgium
- Interuniversity Institute of Bioinformatics in Brussels (IB2), Université Libre de Bruxelles - Vrije Universiteit Brussel (ULB-VUB), Brussels, Belgium
| | - Julie Soblet
- Interuniversity Institute of Bioinformatics in Brussels (IB2), Université Libre de Bruxelles - Vrije Universiteit Brussel (ULB-VUB), Brussels, Belgium
- Department of Genetics, Hôpital Erasme, ULB Center of Human Genetics, Université Libre de Bruxelles, Brussels, Belgium
- Department of Genetics, Hôpital Universitaire des Enfants Reine Fabiola, ULB Center of Human Genetics, Université Libre de Bruxelles, Brussels, Belgium
| | - Sarah Duerinckx
- Human Genetics Unit, Institut de Recherche Interdisciplinaire en Biologie Humaine et Moléculaire (IRIBHM), Université Libre de Bruxelles (ULB), Brussels, Belgium
- Interuniversity Institute of Bioinformatics in Brussels (IB2), Université Libre de Bruxelles - Vrije Universiteit Brussel (ULB-VUB), Brussels, Belgium
| | - Didier Croes
- Interuniversity Institute of Bioinformatics in Brussels (IB2), Université Libre de Bruxelles - Vrije Universiteit Brussel (ULB-VUB), Brussels, Belgium
- Brussels Interuniversity Genomics High Throughput Core (BRIGHTcore), VUB-ULB, Brussels, Belgium
- Center for Medical Genetics, Reproduction and Genetics, Reproduction Genetics and Regenerative Medicine, Vrije Universiteit Brussel, UZ Brussel, Brussels, Belgium
- Center for Human Genetics, Clinique Universitaires Saint Luc, Brussels, Belgium
| | - Camille Perazzolo
- Human Genetics Unit, Institut de Recherche Interdisciplinaire en Biologie Humaine et Moléculaire (IRIBHM), Université Libre de Bruxelles (ULB), Brussels, Belgium
| | - Petra Hruba
- Transplant Laboratory, Institute for Clinical and Experimental Medicine, Prague, Czechia
| | - Dorien Daneels
- Interuniversity Institute of Bioinformatics in Brussels (IB2), Université Libre de Bruxelles - Vrije Universiteit Brussel (ULB-VUB), Brussels, Belgium
- Brussels Interuniversity Genomics High Throughput Core (BRIGHTcore), VUB-ULB, Brussels, Belgium
- Center for Medical Genetics, Reproduction and Genetics, Reproduction Genetics and Regenerative Medicine, Vrije Universiteit Brussel, UZ Brussel, Brussels, Belgium
| | - Ben Caljon
- Brussels Interuniversity Genomics High Throughput Core (BRIGHTcore), VUB-ULB, Brussels, Belgium
- Center for Medical Genetics, Reproduction and Genetics, Reproduction Genetics and Regenerative Medicine, Vrije Universiteit Brussel, UZ Brussel, Brussels, Belgium
| | - Mehmet Sukru Sever
- Istanbul Tip Fakültesi, Istanbul School of Medicine, Internal Medicine, Nephrology, Istanbul, Türkiye
| | - Julio Pascual
- Department of Nephrology, Hospital del Mar, Institute Mar for Medical Research, Barcelona, Spain
- Department of Nephrology, Hospital Universitario 12 de Octubre, Madrid, Spain
| | - Marius Miglinas
- Nephrology Center, Santaros Klinikos, Medical Faculty, Vilnius University, Vilnius, Lithuania
| | | | - Isabelle Pirson
- Human Genetics Unit, Institut de Recherche Interdisciplinaire en Biologie Humaine et Moléculaire (IRIBHM), Université Libre de Bruxelles (ULB), Brussels, Belgium
| | - Lidia Ghisdal
- Department of Nephrology, Hospital Centre EpiCURA, Baudour, Belgium
| | - Guillaume Smits
- Interuniversity Institute of Bioinformatics in Brussels (IB2), Université Libre de Bruxelles - Vrije Universiteit Brussel (ULB-VUB), Brussels, Belgium
- Department of Genetics, Hôpital Erasme, ULB Center of Human Genetics, Université Libre de Bruxelles, Brussels, Belgium
| | - Magali Giral
- CHU Nantes, Nantes Université, INSERM, Center for Research in Transplantation and Translational Immunology, CR2TI, UMR 1064, ITUN, Nantes, France
- CHU Nantes, Centre d'Investigation Clinique en Biothérapie, Centre de Ressources Biologiques (CRB), Nantes, France
- LabEx IGO “Immunotherapy, Graft, Oncology”, Nantes, France
| | - Daniel Abramowicz
- Department of Nephrology, Antwerp University Hospital and Laboratory of Experimental Medicine, University of Antwerp, Antwerp, Belgium
| | - Marc Abramowicz
- Human Genetics Unit, Institut de Recherche Interdisciplinaire en Biologie Humaine et Moléculaire (IRIBHM), Université Libre de Bruxelles (ULB), Brussels, Belgium
- Interuniversity Institute of Bioinformatics in Brussels (IB2), Université Libre de Bruxelles - Vrije Universiteit Brussel (ULB-VUB), Brussels, Belgium
- Department of Genetic Medicine and Development, Faculty of Medicine, Université de Geneve, Geneva, Switzerland
| | - Sophie Brouard
- CHU Nantes, Nantes Université, INSERM, Center for Research in Transplantation and Translational Immunology, CR2TI, UMR 1064, ITUN, Nantes, France
- CHU Nantes, Centre d'Investigation Clinique en Biothérapie, Centre de Ressources Biologiques (CRB), Nantes, France
- LabEx IGO “Immunotherapy, Graft, Oncology”, Nantes, France
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Chen X, Chen Y, Yan K, Chen H, Qin Q, Yang L, Liu B, Cheng G, Cao Y, Wu B, Dong X, Qiao Z, Zhou W. Genetic background of idiopathic neurodevelopmental delay patients with significant brain deviation volume. Chin Med J (Engl) 2023; 136:807-814. [PMID: 36806579 PMCID: PMC10150856 DOI: 10.1097/cm9.0000000000002297] [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: 07/20/2022] [Indexed: 02/22/2023] Open
Abstract
BACKGROUND Significant brain volume deviation is an essential phenotype in children with neurodevelopmental delay (NDD), but its genetic basis has not been fully characterized. This study attempted to analyze the genetic factors associated with significant whole-brain deviation volume (WBDV). METHODS We established a reference curve based on 4222 subjects ranging in age from the first postnatal day to 18 years. We recruited only NDD patients without acquired etiologies or positive genetic results. Cranial magnetic resonance imaging (MRI) and clinical exome sequencing (2742 genes) data were acquired. A genetic burden test was performed, and the results were compared between patients with and without significant WBDV. Literature review analyses and BrainSpan analysis based on the human brain developmental transcriptome were performed to detect the potential role of genetic risk factors in human brain development. RESULTS We recruited a total of 253 NDD patients. Among them, 26 had significantly decreased WBDV (<-2 standard deviations [SDs]), and 14 had significantly increased WBDV (>+2 SDs). NDD patients with significant WBDV had higher rates of motor development delay (49.8% [106/213] vs . 75.0% [30/40], P = 0.003) than patients without significant WBDV. Genetic burden analyses found 30 genes with an increased allele frequency of rare variants in patients with significant WBDV. Analyses of the literature further demonstrated that these genes were not randomly identified: burden genes were more related to the brain development than background genes ( P = 1.656e -9 ). In seven human brain regions related to motor development, we observed burden genes had higher expression before 37-week gestational age than postnatal stages. Functional analyses found that burden genes were enriched in embryonic brain development, with positive regulation of synaptic growth at the neuromuscular junction, positive regulation of deoxyribonucleic acid templated transcription, and response to hormone, and these genes were shown to be expressed in neural progenitors. Based on single cell sequencing analyses, we found TUBB2B gene had elevated expression levels in neural progenitor cells, interneuron, and excitatory neuron and SOX15 had high expression in interneuron and excitatory neuron. CONCLUSION Idiopathic NDD patients with significant brain volume changes detected by MRI had an increased prevalence of motor development delay, which could be explained by the genetic differences characterized herein.
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Affiliation(s)
- Xiang Chen
- Department of Neonatology, Children's Hospital of Fudan University, National Children's Medical Center, Shanghai 201102, China
| | - Yuxi Chen
- Institutes of Biomedical Sciences, Fudan University, Shanghai 200032, China
| | - Kai Yan
- Department of Neonatology, Children's Hospital of Fudan University, National Children's Medical Center, Shanghai 201102, China
| | - Huiyao Chen
- Institutes of Biomedical Sciences, Fudan University, Shanghai 200032, China
| | - Qian Qin
- Shanghai Key Laboratory of Birth Defects, The Translational Medicine Center of Children Development and Disease of Fudan University, Children's Hospital of Fudan University, National Children's Medical Center, Shanghai 201102, China
| | - Lin Yang
- Department of Pediatric Endocrinology and Inherited Metabolic Diseases, Children's Hospital of Fudan University, National Children's Medical Center, Shanghai 201102, China
| | - Bo Liu
- Shanghai Key Laboratory of Birth Defects, The Translational Medicine Center of Children Development and Disease of Fudan University, Children's Hospital of Fudan University, National Children's Medical Center, Shanghai 201102, China
| | - Guoqiang Cheng
- Department of Neonatology, Children's Hospital of Fudan University, National Children's Medical Center, Shanghai 201102, China
| | - Yun Cao
- Department of Neonatology, Children's Hospital of Fudan University, National Children's Medical Center, Shanghai 201102, China
| | - Bingbing Wu
- Shanghai Key Laboratory of Birth Defects, The Translational Medicine Center of Children Development and Disease of Fudan University, Children's Hospital of Fudan University, National Children's Medical Center, Shanghai 201102, China
| | - Xinran Dong
- Shanghai Key Laboratory of Birth Defects, The Translational Medicine Center of Children Development and Disease of Fudan University, Children's Hospital of Fudan University, National Children's Medical Center, Shanghai 201102, China
| | - Zhongwei Qiao
- Department of Radiology, Children's Hospital of Fudan University, National Children's Medical Center, Shanghai 201102, China
| | - Wenhao Zhou
- Department of Neonatology, Children's Hospital of Fudan University, National Children's Medical Center, Shanghai 201102, China
- Shanghai Key Laboratory of Birth Defects, The Translational Medicine Center of Children Development and Disease of Fudan University, Children's Hospital of Fudan University, National Children's Medical Center, Shanghai 201102, China
- State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Institutes of Brain Science, Fudan University, Shanghai 200433, China
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9
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Cardenas R, Prinsley P, Philpott C, Bhutta MF, Wilson E, Brewer DS, Jennings BA. Whole exome sequencing study identifies candidate loss of function variants and locus heterogeneity in familial cholesteatoma. PLoS One 2023; 18:e0272174. [PMID: 36920900 PMCID: PMC10016674 DOI: 10.1371/journal.pone.0272174] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2022] [Accepted: 02/08/2023] [Indexed: 03/16/2023] Open
Abstract
Cholesteatoma is a rare progressive disease of the middle ear. Most cases are sporadic, but some patients report a positive family history. Identifying functionally important gene variants associated with this disease has the potential to uncover the molecular basis of cholesteatoma pathology with implications for disease prevention, surveillance, or management. We performed an observational WES study of 21 individuals treated for cholesteatoma who were recruited from ten multiply affected families. These family studies were complemented with gene-level mutational burden analysis. We also applied functional enrichment analyses to identify shared properties and pathways for candidate genes and their products. Filtered data collected from pairs and trios of participants within the ten families revealed 398 rare, loss of function (LOF) variants co-segregating with cholesteatoma in 389 genes. We identified six genes DENND2C, DNAH7, NBEAL1, NEB, PRRC2C, and SHC2, for which we found LOF variants in two or more families. The parallel gene-level analysis of mutation burden identified a significant mutation burden for the genes in the DNAH gene family, which encode products involved in ciliary structure. Functional enrichment analyses identified common pathways for the candidate genes which included GTPase regulator activity, calcium ion binding, and degradation of the extracellular matrix. The number of candidate genes identified and the locus heterogeneity that we describe within and between multiply affected families suggest that the genetic architecture for familial cholesteatoma is complex.
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Affiliation(s)
- Ryan Cardenas
- Norwich Medical School, University of East Anglia, Norwich, United Kingdom
| | - Peter Prinsley
- ENT Department, James Paget University Hospitals NHS Foundation Trust, Great Yarmouth, Norfolk, United Kingdom
| | - Carl Philpott
- Norwich Medical School, University of East Anglia, Norwich, United Kingdom
| | - Mahmood F. Bhutta
- Department of Clinical and Experimental Medicine, Brighton and Sussex Medical School, Brighton, United Kingdom
- ENT Department, Royal Sussex County Hospital, Brighton, United Kingdom
| | - Emma Wilson
- Norwich Medical School, University of East Anglia, Norwich, United Kingdom
| | - Daniel S. Brewer
- Norwich Medical School, University of East Anglia, Norwich, United Kingdom
- Earlham Institute, Norwich Research Park, Norwich, United Kingdom
- * E-mail: (BAJ); (DSB)
| | - Barbara A. Jennings
- Norwich Medical School, University of East Anglia, Norwich, United Kingdom
- * E-mail: (BAJ); (DSB)
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10
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Hall JC, Paull D, Pébay A, Lidgerwood GE. Human pluripotent stem cells for the modelling of retinal pigment epithelium homeostasis and disease: A review. Clin Exp Ophthalmol 2022; 50:667-677. [PMID: 35739648 PMCID: PMC9546239 DOI: 10.1111/ceo.14128] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2022] [Revised: 06/06/2022] [Accepted: 06/19/2022] [Indexed: 12/05/2022]
Abstract
Human pluripotent stem cells (hPSCs), which include induced pluripotent stem cells and embryonic stem cells, are powerful tools for studying human development, physiology and disease, including those affecting the retina. Cells from selected individuals, or specific genetic backgrounds, can be differentiated into distinct cell types allowing the modelling of diseases in a dish for therapeutic development. hPSC‐derived retinal cultures have already been used to successfully model retinal pigment epithelium (RPE) degeneration for various retinal diseases including monogenic conditions and complex disease such as age‐related macular degeneration. Here, we will review the current knowledge gained in understanding the molecular events involved in retinal disease using hPSC‐derived retinal models, in particular RPE models. We will provide examples of various conditions to illustrate the scope of applications associated with the use of hPSC‐derived RPE models.
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Affiliation(s)
- Jenna C Hall
- Department of Anatomy and Physiology The University of Melbourne Parkville Victoria Australia
| | - Daniel Paull
- The New York Stem Cell Foundation Research Institute New York New York USA
| | - Alice Pébay
- Department of Anatomy and Physiology The University of Melbourne Parkville Victoria Australia
- Department of Surgery, Royal Melbourne Hospital The University of Melbourne Parkville Victoria Australia
| | - Grace E. Lidgerwood
- Department of Anatomy and Physiology The University of Melbourne Parkville Victoria Australia
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11
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Larrivée-Vanier S, Jean-Louis M, Magne F, Bui H, Rouleau GA, Spiegelman D, Samuels ME, Kibar Z, Van Vliet G, Deladoëy J. Whole-Exome Sequencing in Congenital Hypothyroidism Due to Thyroid Dysgenesis. Thyroid 2022; 32:486-495. [PMID: 35272499 PMCID: PMC9145262 DOI: 10.1089/thy.2021.0597] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
Abstract
Context: Congenital hypothyroidism due to thyroid dysgenesis (CHTD) is a predominantly sporadic and nonsyndromic (NS) condition of unknown etiology. NS-CHTD shows a 40-fold increase in relative risk among first-degree relatives (1 in 100 compared with a birth prevalence of 1 in 4000 in the general population), but a discordance rate between monozygotic (MZ) twins of 92%. This suggests a two-hit mechanism, combining a genetic predisposition (incomplete penetrance of inherited variants) with postzygotic events (accounting for MZ twin discordance). Objective: To evaluate whether whole-exome sequencing (WES) allows to identify new predisposing genes in NS-CHTD. Methods: We performed a case-control study by comparing the whole exome of 36 nonconsanguineous cases of NS-CHTD (33 with lingual thyroid ectopy and 3 with athyreosis, based on technetium pertechnetate scintigraphy at diagnosis) with that of 301 unaffected controls to assess for enrichment in rare protein-altering variants. We performed an unbiased approach using a gene-based burden with a false discovery rate correction. Moreover, we identified all rare pathogenic and likely pathogenic variants, based on in silico prediction tools, in 27 genes previously associated with congenital hypothyroidism (CH) (thyroid dysgenesis [TD] and dyshormonogenesis). Results: After correction for multiple testing, no enrichment in rare protein-altering variants was observed in NS-CHTD. Pathogenic or likely pathogenic variants (21 variants in 12 CH genes) were identified in 42% of cases. Eight percent of cases had variants in more than one gene (oligogenic group); these were not more severely affected than monogenic cases. Moreover, cases with protein-altering variants in dyshormonogenesis-related genes were not more severely affected than those without. Conclusions: No new predisposing genes were identified following an unbiased analysis of WES data in a well-characterized NS-CHTD cohort. Nonetheless, the discovery rate of rare pathogenic or likely pathogenic variants was 42%. Eight percent of the cases harbored multiple variants in genes associated with TD or dyshormonogenesis, but these variants did not explain the variability of hypothyroidism observed in dysgenesis. WES did not identify a genetic cause in NS-CHTD cases, confirming the complex etiology of this disease. Additional studies in larger cohorts and/or novel discovery approaches are required.
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Affiliation(s)
- Stéphanie Larrivée-Vanier
- Research Center of Centre Hospitalier Universitaire Sainte-Justine, Université de Montréal, Montréal, Canada
- Department of Biochemistry, Université de Montréal, Montréal, Canada
| | - Martineau Jean-Louis
- Research Center of Centre Hospitalier Universitaire Sainte-Justine, Université de Montréal, Montréal, Canada
| | - Fabien Magne
- Research Center of Centre Hospitalier Universitaire Sainte-Justine, Université de Montréal, Montréal, Canada
| | - Helen Bui
- Department of Endocrinology, McGill University Health Center, Montréal, Canada
| | - Guy A. Rouleau
- Montreal Neurological Institute, McGill University, Montréal, Canada
| | - Dan Spiegelman
- Montreal Neurological Institute, McGill University, Montréal, Canada
| | - Mark E. Samuels
- Research Center of Centre Hospitalier Universitaire Sainte-Justine, Université de Montréal, Montréal, Canada
- Department of Medicine, Université de Montréal, Montréal, Canada
| | - Zoha Kibar
- Research Center of Centre Hospitalier Universitaire Sainte-Justine, Université de Montréal, Montréal, Canada
- Department of Neurosciences, Université de Montréal, Montréal, Canada
| | - Guy Van Vliet
- Research Center of Centre Hospitalier Universitaire Sainte-Justine, Université de Montréal, Montréal, Canada
- Department of Pediatrics, Université de Montréal, Montréal, Canada
| | - Johnny Deladoëy
- Research Center of Centre Hospitalier Universitaire Sainte-Justine, Université de Montréal, Montréal, Canada
- Department of Pediatrics, Université de Montréal, Montréal, Canada
- Pediatric Institute of Southern Switzerland, Bellinzona, Switzerland
- Faculty of Biomedical Sciences, University of Southern Switzerland, Lugano, Switzerland
- Address correspondence to: Johnny Deladoëy, MD, PhD, Facoltà di Scienze Biomediche, Università della Svizzera Italiana, Campus Est, Lugano 6900, Switzerland
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12
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Koh HY, Haghighi A, Keywan C, Alexandrescu S, Plews-Ogan E, Haas EA, Brownstein CA, Vargas SO, Haynes RL, Berry GT, Holm IA, Poduri AH, Goldstein RD. Genetic Determinants of Sudden Unexpected Death in Pediatrics. Genet Med 2022; 24:839-850. [PMID: 35027292 PMCID: PMC9164313 DOI: 10.1016/j.gim.2021.12.004] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2021] [Revised: 12/07/2021] [Accepted: 12/08/2021] [Indexed: 02/06/2023] Open
Abstract
PURPOSE This study aimed to evaluate genetic contributions to sudden unexpected death in pediatrics (SUDP). METHODS We phenotyped and performed exome sequencing for 352 SUDP cases. We analyzed variants in 294 "SUDP genes" with mechanisms plausibly related to sudden death. In a subset of 73 cases with parental data (trios), we performed exome-wide analyses and conducted cohort-wide burden analyses. RESULTS In total, we identified likely contributory variants in 37 of 352 probands (11%). Analysis of SUDP genes identified pathogenic/likely pathogenic variants in 12 of 352 cases (SCN1A, DEPDC5 [2], GABRG2, SCN5A [2], TTN [2], MYBPC3, PLN, TNNI3, and PDHA1) and variants of unknown significance-favor-pathogenic in 17 of 352 cases. Exome-wide analyses of the 73 cases with family data additionally identified 4 de novo pathogenic/likely pathogenic variants (SCN1A [2], ANKRD1, and BRPF1) and 4 de novo variants of unknown significance-favor-pathogenic. Comparing cases with controls, we demonstrated an excess burden of rare damaging SUDP gene variants (odds ratio, 2.94; 95% confidence interval, 2.37-4.21) and of exome-wide de novo variants in the subset of 73 with trio data (odds ratio, 3.13; 95% confidence interval, 1.91-5.16). CONCLUSION We provide strong evidence for a role of genetic factors in SUDP, involving both candidate genes and novel genes for SUDP and expanding phenotypes of disease genes not previously associated with sudden death.
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Affiliation(s)
- Hyun Yong Koh
- Robert's Program for Sudden Unexpected Death in Pediatrics, Boston Children's Hospital, Boston, MA; F.M. Kirby Neurobiology Center, Boston Children's Hospital, Boston, MA; Epilepsy Genetics Program, Department of Neurology, Boston Children's Hospital and Harvard Medical School, Boston, MA; Division of Genetics and Genomics, Department of Pediatrics and Manton Center for Orphan Diseases Research, Boston Children's Hospital, MA
| | - Alireza Haghighi
- Department of Genetics, Harvard Medical School, Boston, MA; Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA; Broad Institute of MIT and Harvard, Cambridge, MA
| | - Christine Keywan
- Robert's Program for Sudden Unexpected Death in Pediatrics, Boston Children's Hospital, Boston, MA
| | - Sanda Alexandrescu
- Robert's Program for Sudden Unexpected Death in Pediatrics, Boston Children's Hospital, Boston, MA; Departments of Pathology, Boston Children's Hospital and Harvard Medical School, Boston, MA
| | - Erin Plews-Ogan
- Robert's Program for Sudden Unexpected Death in Pediatrics, Boston Children's Hospital, Boston, MA; Harvard Medical School, Boston, MA
| | - Elisabeth A Haas
- Department of Research, Rady Children's Hospital-San Diego, San Diego, CA
| | - Catherine A Brownstein
- Robert's Program for Sudden Unexpected Death in Pediatrics, Boston Children's Hospital, Boston, MA; Division of Genetics and Genomics, Department of Pediatrics and Manton Center for Orphan Diseases Research, Boston Children's Hospital, MA; Department of Pediatrics, Harvard Medical School, Boston, MA
| | - Sara O Vargas
- Robert's Program for Sudden Unexpected Death in Pediatrics, Boston Children's Hospital, Boston, MA; Departments of Pathology, Boston Children's Hospital and Harvard Medical School, Boston, MA
| | - Robin L Haynes
- Departments of Pathology, Boston Children's Hospital and Harvard Medical School, Boston, MA
| | - Gerard T Berry
- Robert's Program for Sudden Unexpected Death in Pediatrics, Boston Children's Hospital, Boston, MA; Division of Genetics and Genomics, Department of Pediatrics and Manton Center for Orphan Diseases Research, Boston Children's Hospital, MA; Department of Pediatrics, Harvard Medical School, Boston, MA
| | - Ingrid A Holm
- Robert's Program for Sudden Unexpected Death in Pediatrics, Boston Children's Hospital, Boston, MA; Division of Genetics and Genomics, Department of Pediatrics and Manton Center for Orphan Diseases Research, Boston Children's Hospital, MA; Broad Institute of MIT and Harvard, Cambridge, MA; Department of Pediatrics, Harvard Medical School, Boston, MA
| | - Annapurna H Poduri
- Robert's Program for Sudden Unexpected Death in Pediatrics, Boston Children's Hospital, Boston, MA; F.M. Kirby Neurobiology Center, Boston Children's Hospital, Boston, MA; Epilepsy Genetics Program, Department of Neurology, Boston Children's Hospital and Harvard Medical School, Boston, MA; Broad Institute of MIT and Harvard, Cambridge, MA; Department of Neurology, Harvard Medical School, Boston, MA
| | - Richard D Goldstein
- Robert's Program for Sudden Unexpected Death in Pediatrics, Boston Children's Hospital, Boston, MA; Broad Institute of MIT and Harvard, Cambridge, MA; Department of Pediatrics, Harvard Medical School, Boston, MA; Division of General Pediatrics, Department of Pediatrics, Boston Children's Hospital, Boston, MA.
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13
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Wang YC, Wu Y, Choi J, Allington G, Zhao S, Khanfar M, Yang K, Fu PY, Wrubel M, Yu X, Mekbib KY, Ocken J, Smith H, Shohfi J, Kahle KT, Lu Q, Jin SC. Computational Genomics in the Era of Precision Medicine: Applications to Variant Analysis and Gene Therapy. J Pers Med 2022; 12:175. [PMID: 35207663 PMCID: PMC8878256 DOI: 10.3390/jpm12020175] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2021] [Revised: 01/18/2022] [Accepted: 01/24/2022] [Indexed: 02/04/2023] Open
Abstract
Rapid methodological advances in statistical and computational genomics have enabled researchers to better identify and interpret both rare and common variants responsible for complex human diseases. As we continue to see an expansion of these advances in the field, it is now imperative for researchers to understand the resources and methodologies available for various data types and study designs. In this review, we provide an overview of recent methods for identifying rare and common variants and understanding their roles in disease etiology. Additionally, we discuss the strategy, challenge, and promise of gene therapy. As computational and statistical approaches continue to improve, we will have an opportunity to translate human genetic findings into personalized health care.
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Affiliation(s)
- Yung-Chun Wang
- Department of Genetics, School of Medicine, Washington University, St. Louis, MO 63110, USA; (Y.-C.W.); (J.C.); (S.Z.); (M.K.); (K.Y.); (P.-Y.F.); (M.W.); (X.Y.)
| | - Yuchang Wu
- Department of Biostatistics & Medical Informatics, University of Wisconsin-Madison, Madison, WI 53706, USA;
| | - Julie Choi
- Department of Genetics, School of Medicine, Washington University, St. Louis, MO 63110, USA; (Y.-C.W.); (J.C.); (S.Z.); (M.K.); (K.Y.); (P.-Y.F.); (M.W.); (X.Y.)
| | - Garrett Allington
- Department of Pathology, Yale School of Medicine, New Haven, CT 06510, USA;
- Department of Neurosurgery, Massachusetts General Hospital, Boston, MA 02114, USA; (H.S.); (K.T.K.)
| | - Shujuan Zhao
- Department of Genetics, School of Medicine, Washington University, St. Louis, MO 63110, USA; (Y.-C.W.); (J.C.); (S.Z.); (M.K.); (K.Y.); (P.-Y.F.); (M.W.); (X.Y.)
| | - Mariam Khanfar
- Department of Genetics, School of Medicine, Washington University, St. Louis, MO 63110, USA; (Y.-C.W.); (J.C.); (S.Z.); (M.K.); (K.Y.); (P.-Y.F.); (M.W.); (X.Y.)
| | - Kuangying Yang
- Department of Genetics, School of Medicine, Washington University, St. Louis, MO 63110, USA; (Y.-C.W.); (J.C.); (S.Z.); (M.K.); (K.Y.); (P.-Y.F.); (M.W.); (X.Y.)
| | - Po-Ying Fu
- Department of Genetics, School of Medicine, Washington University, St. Louis, MO 63110, USA; (Y.-C.W.); (J.C.); (S.Z.); (M.K.); (K.Y.); (P.-Y.F.); (M.W.); (X.Y.)
| | - Max Wrubel
- Department of Genetics, School of Medicine, Washington University, St. Louis, MO 63110, USA; (Y.-C.W.); (J.C.); (S.Z.); (M.K.); (K.Y.); (P.-Y.F.); (M.W.); (X.Y.)
| | - Xiaobing Yu
- Department of Genetics, School of Medicine, Washington University, St. Louis, MO 63110, USA; (Y.-C.W.); (J.C.); (S.Z.); (M.K.); (K.Y.); (P.-Y.F.); (M.W.); (X.Y.)
- Department of Computer Science & Engineering, Washington University, St. Louis, MO 63130, USA
| | - Kedous Y. Mekbib
- Department of Neurosurgery, Yale University School of Medicine, New Haven, CT 06510, USA; (K.Y.M.); (J.O.); (J.S.)
| | - Jack Ocken
- Department of Neurosurgery, Yale University School of Medicine, New Haven, CT 06510, USA; (K.Y.M.); (J.O.); (J.S.)
| | - Hannah Smith
- Department of Neurosurgery, Massachusetts General Hospital, Boston, MA 02114, USA; (H.S.); (K.T.K.)
- Department of Neurosurgery, Yale University School of Medicine, New Haven, CT 06510, USA; (K.Y.M.); (J.O.); (J.S.)
| | - John Shohfi
- Department of Neurosurgery, Yale University School of Medicine, New Haven, CT 06510, USA; (K.Y.M.); (J.O.); (J.S.)
| | - Kristopher T. Kahle
- Department of Neurosurgery, Massachusetts General Hospital, Boston, MA 02114, USA; (H.S.); (K.T.K.)
- Division of Genetics and Genomics, Boston Children’s Hospital, Boston, MA 02115, USA
- Departments of Pediatrics and Neurology, Harvard Medical School, Boston, MA 02115, USA
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Qiongshi Lu
- Department of Biostatistics & Medical Informatics, University of Wisconsin-Madison, Madison, WI 53706, USA;
| | - Sheng Chih Jin
- Department of Genetics, School of Medicine, Washington University, St. Louis, MO 63110, USA; (Y.-C.W.); (J.C.); (S.Z.); (M.K.); (K.Y.); (P.-Y.F.); (M.W.); (X.Y.)
- Department of Pediatrics, School of Medicine, Washington University, St. Louis, MO 63110, USA
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14
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Bloom AJ, Mao X, Strickland A, Sasaki Y, Milbrandt J, DiAntonio A. Constitutively active SARM1 variants that induce neuropathy are enriched in ALS patients. Mol Neurodegener 2022; 17:1. [PMID: 34991663 PMCID: PMC8739729 DOI: 10.1186/s13024-021-00511-x] [Citation(s) in RCA: 43] [Impact Index Per Article: 21.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2021] [Accepted: 12/17/2021] [Indexed: 03/31/2023] Open
Abstract
Background In response to injury, neurons activate a program of organized axon self-destruction initiated by the NAD+ hydrolase, SARM1. In healthy neurons SARM1 is autoinhibited, but single amino acid changes can abolish autoinhibition leading to constitutively active SARM1 enzymes that promote degeneration when expressed in cultured neurons. Methods To investigate whether naturally occurring human variants might disrupt SARM1 autoinhibition and potentially contribute to risk for neurodegenerative disease, we assayed the enzymatic activity of all 42 rare SARM1 alleles identified among 8507 amyotrophic lateral sclerosis (ALS) patients and 9671 controls. We then intrathecally injected mice with virus expressing SARM1 constructs to test the capacity of an ALS-associated constitutively active SARM1 variant to promote neurodegeneration in vivo. Results Twelve out of 42 SARM1 missense variants or small in-frame deletions assayed exhibit constitutive NADase activity, including more than half of those that are unique to the ALS patients or that occur in multiple patients. There is a > 5-fold enrichment of constitutively active variants among patients compared to controls. Expression of constitutively active ALS-associated SARM1 alleles in cultured dorsal root ganglion (DRG) neurons is pro-degenerative and cytotoxic. Intrathecal injection of an AAV expressing the common SARM1 reference allele is innocuous to mice, but a construct harboring SARM1V184G, the constitutively active variant found most frequently among the ALS patients, causes axon loss, motor dysfunction, and sustained neuroinflammation. Conclusions These results implicate rare hypermorphic SARM1 alleles as candidate genetic risk factors for ALS and other neurodegenerative conditions. Supplementary Information The online version contains supplementary material available at 10.1186/s13024-021-00511-x.
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Affiliation(s)
- A Joseph Bloom
- Needleman Center for Neurometabolism and Axonal Therapeutics and Department of Genetics, Washington University School of Medicine in Saint Louis, St. Louis, MO, USA.
| | - Xianrong Mao
- Needleman Center for Neurometabolism and Axonal Therapeutics and Department of Genetics, Washington University School of Medicine in Saint Louis, St. Louis, MO, USA
| | - Amy Strickland
- Needleman Center for Neurometabolism and Axonal Therapeutics and Department of Genetics, Washington University School of Medicine in Saint Louis, St. Louis, MO, USA
| | - Yo Sasaki
- Needleman Center for Neurometabolism and Axonal Therapeutics and Department of Genetics, Washington University School of Medicine in Saint Louis, St. Louis, MO, USA
| | - Jeffrey Milbrandt
- Needleman Center for Neurometabolism and Axonal Therapeutics and Department of Genetics, Washington University School of Medicine in Saint Louis, St. Louis, MO, USA.
| | - Aaron DiAntonio
- Needleman Center for Neurometabolism and Axonal Therapeutics and Department of Developmental Biology, Washington University School of Medicine in Saint Louis, St. Louis, MO, USA.
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15
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He D, Shang L, Liu Q, Shen D, Sun X, Cai Z, Zhao X, Liu L, Yang X, Liu M, Zhang X, Cui L. Association of apolipoprotein E ε4 allele and amyotrophic lateral sclerosis in Chinese population. Amyotroph Lateral Scler Frontotemporal Degener 2021; 23:399-406. [PMID: 34279165 DOI: 10.1080/21678421.2021.1953077] [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: 10/20/2022]
Abstract
Background: Amyotrophic lateral sclerosis (ALS) has a complex genetic origin, and how immune dysregulation may contribute to ALS etiology remain unclear. Given the roles played by apolipoprotein E (APOE) signaling in neuroinflammation and neurodegeneration, an improved knowledge of the association between APOE genotypes and ALS risk in Chinese population may help to understand the underlying etiology of the disease. Methods: A retrospective case-control study with participants of Chinese ancestry was conducted, with a total of 683 ALS patients and 369 healthy controls analyzed for APOE genotypes using Sanger sequencing. In addition, 282 of these patients were further analyzed for known ALS risk variants and rare deleterious variants related to immune disorders via whole exome sequencing. Results: Among the 683 ALS patients analyzed (346 males, 337 females; mean age at onset [SD]: 51.9 [10.9]), 145 patients (21.1%) carried ε4, the proportion of which was significantly higher than 16.0% in controls (59/369; OR, 1.42; 95%CI, 1.02-1.98; p = 0.02). There is no evidence supporting the association between APOE genotypes and disease phenotypes. We also didn't find any enrichment of currently known ALS risk variants or variants in genes related to immune abnormality in specific APOE genotypes. Conclusion: Our study highlighted the importance of trans-ethnic studies in identifying genetic risk factors, and the relevance of APOE in ALS etiopathogenesis in Chinese population.
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Affiliation(s)
- Di He
- Department of Neurology, Peking Union Medical College Hospital (PUMCH), Chinese Academy of Medical Sciences and Peking Union Medical College (CAMS & PUMC), Beijing, China
| | - Liang Shang
- McKusick-Zhang Center for Genetic Medicine, State Key Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine, Peking Union Medical College, Beijing, China, and
| | - Qing Liu
- Department of Neurology, Peking Union Medical College Hospital (PUMCH), Chinese Academy of Medical Sciences and Peking Union Medical College (CAMS & PUMC), Beijing, China
| | - Dongchao Shen
- Department of Neurology, Peking Union Medical College Hospital (PUMCH), Chinese Academy of Medical Sciences and Peking Union Medical College (CAMS & PUMC), Beijing, China
| | - Xiaohan Sun
- Department of Neurology, Peking Union Medical College Hospital (PUMCH), Chinese Academy of Medical Sciences and Peking Union Medical College (CAMS & PUMC), Beijing, China
| | - Zhengyi Cai
- Department of Neurology, Peking Union Medical College Hospital (PUMCH), Chinese Academy of Medical Sciences and Peking Union Medical College (CAMS & PUMC), Beijing, China
| | - Ximeng Zhao
- McKusick-Zhang Center for Genetic Medicine, State Key Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine, Peking Union Medical College, Beijing, China, and
| | - Liyang Liu
- McKusick-Zhang Center for Genetic Medicine, State Key Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine, Peking Union Medical College, Beijing, China, and
| | - Xunzhe Yang
- Department of Neurology, Peking Union Medical College Hospital (PUMCH), Chinese Academy of Medical Sciences and Peking Union Medical College (CAMS & PUMC), Beijing, China
| | - Mingsheng Liu
- Department of Neurology, Peking Union Medical College Hospital (PUMCH), Chinese Academy of Medical Sciences and Peking Union Medical College (CAMS & PUMC), Beijing, China
| | - Xue Zhang
- Department of Neurology, Peking Union Medical College Hospital (PUMCH), Chinese Academy of Medical Sciences and Peking Union Medical College (CAMS & PUMC), Beijing, China.,McKusick-Zhang Center for Genetic Medicine, State Key Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine, Peking Union Medical College, Beijing, China, and.,Neuroscience Center, Chinese Academy of Medical Sciences and Peking Union Medical College (CAMS), Beijing, China
| | - Liying Cui
- Department of Neurology, Peking Union Medical College Hospital (PUMCH), Chinese Academy of Medical Sciences and Peking Union Medical College (CAMS & PUMC), Beijing, China.,Neuroscience Center, Chinese Academy of Medical Sciences and Peking Union Medical College (CAMS), Beijing, China
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16
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Chiara M, Mandreoli P, Tangaro MA, D'Erchia AM, Sorrentino S, Forleo C, Horner DS, Zambelli F, Pesole G. VINYL: Variant prIoritizatioN by survivaL analysis. Bioinformatics 2020; 36:5590-5599. [PMID: 33367501 DOI: 10.1093/bioinformatics/btaa1067] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2020] [Revised: 10/31/2020] [Accepted: 12/14/2020] [Indexed: 11/12/2022] Open
Abstract
MOTIVATION Clinical applications of genome re-sequencing technologies typically generate large amounts of data that need to be carefully annotated and interpreted to identify genetic variants potentially associated with pathological conditions. In this context, accurate and reproducible methods for the functional annotation and prioritization of genetic variants are of fundamental importance. RESULTS In this paper, we present VINYL, a flexible and fully automated system for the functional annotation and prioritization of genetic variants. Extensive analyses of both real and simulated datasets suggest that VINYL can identify clinically relevant genetic variants in a more accurate manner compared to equivalent state of the art methods, allowing a more rapid and effective prioritization of genetic variants in different experimental settings. As such we believe that VINYL can establish itself as a valuable tool to assist healthcare operators and researchers in clinical genomics investigations. AVAILABILITY VINYL is available at http://beaconlab.it/VINYL and https://github.com/matteo14c/VINYL. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Matteo Chiara
- Department of Biosciences, University of Milan, Milan, Italy.,Institute of Biomembranes, Bioenergetics and Molecular Biotechnologies, National Research Council, Bari, Italy
| | | | - Marco Antonio Tangaro
- Institute of Biomembranes, Bioenergetics and Molecular Biotechnologies, National Research Council, Bari, Italy
| | - Anna Maria D'Erchia
- Institute of Biomembranes, Bioenergetics and Molecular Biotechnologies, National Research Council, Bari, Italy.,Department of Biosciences, Biotechnology and Biopharmaceutics, University of Bari "Aldo Moro", Bari, Italy
| | - Sandro Sorrentino
- Cardiology Unit, Department of Emergency and Organ Transplantation, University of Bari "Aldo Moro", Bari, Italy
| | - Cinzia Forleo
- Cardiology Unit, Department of Emergency and Organ Transplantation, University of Bari "Aldo Moro", Bari, Italy
| | - David S Horner
- Department of Biosciences, University of Milan, Milan, Italy.,Institute of Biomembranes, Bioenergetics and Molecular Biotechnologies, National Research Council, Bari, Italy
| | - Federico Zambelli
- Department of Biosciences, University of Milan, Milan, Italy.,Institute of Biomembranes, Bioenergetics and Molecular Biotechnologies, National Research Council, Bari, Italy
| | - Graziano Pesole
- Institute of Biomembranes, Bioenergetics and Molecular Biotechnologies, National Research Council, Bari, Italy.,Department of Biosciences, Biotechnology and Biopharmaceutics, University of Bari "Aldo Moro", Bari, Italy
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17
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Perchard R, Murray PG, Payton A, Highton GL, Whatmore A, Clayton PE. Novel Mutations and Genes That Impact on Growth in Short Stature of Undefined Aetiology: The EPIGROW Study. J Endocr Soc 2020; 4:bvaa105. [PMID: 32939436 PMCID: PMC7482646 DOI: 10.1210/jendso/bvaa105] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/14/2020] [Accepted: 08/24/2020] [Indexed: 11/19/2022] Open
Abstract
BACKGROUND Children with short stature of undefined aetiology (SS-UA) may have undiagnosed genetic conditions. PURPOSE To identify mutations causing short stature (SS) and genes related to SS, using candidate gene sequence data from the European EPIGROW study. METHODS First, we selected exonic single nucleotide polymorphisms (SNPs), in cases and not controls, with minor allele frequency (MAF) < 2%, whose carriage fitted the mode of inheritance. Known mutations were identified using Ensembl and gene-specific databases. Variants were classified as pathogenic, likely pathogenic, or variant of uncertain significance using criteria from the American College of Medical Genetics and Genomics and the Association for Molecular Pathology. If predicted by ≥ 5/10 algorithms (eg, Polyphen2) to be deleterious, this was considered supporting evidence of pathogenicity. Second, gene-based burden testing determined the difference in SNP frequencies between cases and controls across all and then rare SNPs. For genotype/phenotype relationships, we used PLINK, based on haplotype, MAF > 2%, genotype present in > 75%, and Hardy Weinberg equilibrium P > 10-4. RESULTS First, a diagnostic yield of 10% (27/263) was generated by 2 pathogenic (nonsense in ACAN) and a further 25 likely pathogenic mutations, including previously known missense mutations in FANCB, IGFIR, MMP13, NPR2, OBSL1, and PTPN11. Second, genes related to SS: all methods identified PEX2. Another 7 genes (BUB1B, FANCM, CUL7, FANCA, PTCH1, TEAD3, BCAS3) were identified by both gene-based approaches and 6 (A2M, EFEMP1, PRKCH, SOS2, RNF135, ZBTB38) were identified by gene-based testing for all SNPs and PLINK. CONCLUSIONS Such panels improve diagnosis in SS-UA, extending known disease phenotypes. Fourteen genes related to SS included some known to cause growth disorders as well as novel targets.
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Affiliation(s)
- Reena Perchard
- Developmental Biology & Medicine, Faculty of Biology, Medicine & Health, University of Manchester and Manchester Academic Health Science Centre, Manchester, United Kingdom
| | - Philip George Murray
- Developmental Biology & Medicine, Faculty of Biology, Medicine & Health, University of Manchester and Manchester Academic Health Science Centre, Manchester, United Kingdom
- Department of Paediatric Endocrinology, Manchester University NHS Foundation Trust, Manchester, United Kingdom
| | - Antony Payton
- Informatics, Imaging & Data Science, Faculty of Biology, Medicine & Health, University of Manchester, Manchester, United Kingdom
| | - Georgina Lee Highton
- Developmental Biology & Medicine, Faculty of Biology, Medicine & Health, University of Manchester and Manchester Academic Health Science Centre, Manchester, United Kingdom
| | - Andrew Whatmore
- Developmental Biology & Medicine, Faculty of Biology, Medicine & Health, University of Manchester and Manchester Academic Health Science Centre, Manchester, United Kingdom
| | - Peter Ellis Clayton
- Developmental Biology & Medicine, Faculty of Biology, Medicine & Health, University of Manchester and Manchester Academic Health Science Centre, Manchester, United Kingdom
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18
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Eis PS, Bruno CD, Richmond TA, Koralnik IJ, Hanson BA, Major EO, Chow CR, Hendel-Chavez H, Stankoff B, Gasnault J, Taoufik Y, Hatchwell E. Germline Genetic Risk Variants for Progressive Multifocal Leukoencephalopathy. Front Neurol 2020; 11:186. [PMID: 32256442 PMCID: PMC7094807 DOI: 10.3389/fneur.2020.00186] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2020] [Accepted: 02/27/2020] [Indexed: 12/18/2022] Open
Abstract
Progressive multifocal leukoencephalopathy (PML) is a rare demyelinating disorder of the brain caused by reactivation of the JC virus (JCV), a polyomavirus that infects at least 60% of the population but is asymptomatic or results in benign symptoms in most people. PML occurs as a secondary disease in a variety of disorders or as a serious adverse event from immunosuppressant agents, but is mainly found in three groups: HIV-infected patients, patients with hematological malignancies, or multiple sclerosis (MS) patients on the immunosuppressant therapy natalizumab. It is severely debilitating and is deadly in ~50% HIV cases, ~90% of hematological malignancy cases, and ~24% of MS-natalizumab cases. A PML risk prediction test would have clinical utility in all at risk patient groups but would be particularly beneficial in patients considering therapy with immunosuppressant agents known to cause PML, such as natalizumab, rituximab, and others. While a JC antibody test is currently used in the clinical decision process for natalizumab, it is suboptimal because of its low specificity and requirement to periodically retest patients for seroconversion or to assess if a patient's JCV index has increased. Whereas a high specificity genetic risk prediction test comprising host genetic risk variants (i.e., germline variants occurring at higher frequency in PML patients compared to the general population) could be administered one time to provide clinicians with additional risk prediction information that is independent of JCV serostatus. Prior PML case reports support the hypothesis that PML risk is greater in patients with a genetically caused immunodeficiency disorder. To identify germline PML risk variants, we performed exome sequencing on 185 PML cases (70 in a discovery cohort and 115 in a replication cohort) and used the gnomAD variant database for interpretation. Our study yielded 19 rare variants (maximum allele frequency of 0.02 in gnomAD ethnically matched populations) that impact 17 immune function genes (10 are known to cause inborn errors of immunity). Modeling of these variants in a PML genetic risk test for MS patients considering natalizumab treatment indicates that at least a quarter of PML cases may be preventable.
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Affiliation(s)
- Peggy S Eis
- Population Bio, Inc., New York, NY, United States
| | | | - Todd A Richmond
- Richmond Bioinformatics Consulting, Seattle, WA, United States
| | - Igor J Koralnik
- Department of Neurology, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States
| | - Barbara A Hanson
- Department of Neurology, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States
| | - Eugene O Major
- Laboratory of Molecular Medicine and Neuroscience, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, United States
| | | | - Houria Hendel-Chavez
- Department of Hematology and Immunology, Hôpitaux Universitaires Paris-Sud, INSERM 1184, Faculté de Médecine Paris-Sud, Le Kremlin-Bicêtre, France
| | - Bruno Stankoff
- Department of Neurology, Hôpital Saint-Antoine, Paris, France
| | - Jacques Gasnault
- Department of Internal Medicine, Hôpitaux Universitaires Paris-Sud, Le Kremlin-Bicêtre, France
| | - Yassine Taoufik
- Department of Hematology and Immunology, Hôpitaux Universitaires Paris-Sud, INSERM 1184, Faculté de Médecine Paris-Sud, Le Kremlin-Bicêtre, France
| | - Eli Hatchwell
- Population Bio UK, Inc., Oxfordshire, United Kingdom
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19
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Newey PJ. Clinical genetic testing in endocrinology: Current concepts and contemporary challenges. Clin Endocrinol (Oxf) 2019; 91:587-607. [PMID: 31254405 DOI: 10.1111/cen.14053] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/11/2019] [Revised: 05/29/2019] [Accepted: 06/27/2019] [Indexed: 12/11/2022]
Abstract
Recent advances in DNA sequencing technology have led to an unprecedented period of disease-gene discovery offering many new opportunities for genetic testing in the clinical setting. Endocrinology has seen a rapid expansion in the taxonomy of monogenic disorders, which can be detected by an expanding portfolio of genetic tests in both diagnostic and predictive settings. Successful testing relies on many factors including the ability to identify those at increased risk of genetic disease in the busy clinic as well as a working knowledge of the various testing platforms and their limitations. The clinical utility of a given test is dependent upon many factors, which include the reliability of the genetic testing platform, the accuracy of the test result interpretation and knowledge of disease penetrance and expression. The increasing adoption of "high-content" genetic testing based on next-generation sequencing (NGS) to diagnose hereditary endocrine disorders brings a number of challenges including the potential for uncertain test results and/or genetic findings unrelated to the indication for testing. Therefore, it is increasingly important that the clinician is aware of the current evolution in genetic testing, and understands the different settings in which it may be employed. This review provides an overview of the genetic testing workflow, focusing on each of the major components required for successful testing in adult and paediatric endocrine settings. In addition, the challenges of variant interpretation are highlighted, as are issues related to informed consent, prenatal diagnosis and predictive testing. Finally, the future directions of genetic testing relevant to endocrinology are discussed.
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Affiliation(s)
- Paul J Newey
- Division of Molecular & Clinical Medicine, Ninewells Hospital & Medical School, University of Dundee, Scotland, UK
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20
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Povysil G, Petrovski S, Hostyk J, Aggarwal V, Allen AS, Goldstein DB. Rare-variant collapsing analyses for complex traits: guidelines and applications. Nat Rev Genet 2019; 20:747-759. [PMID: 31605095 DOI: 10.1038/s41576-019-0177-4] [Citation(s) in RCA: 117] [Impact Index Per Article: 23.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/06/2019] [Indexed: 12/11/2022]
Abstract
The first phase of genome-wide association studies (GWAS) assessed the role of common variation in human disease. Advances optimizing and economizing high-throughput sequencing have enabled a second phase of association studies that assess the contribution of rare variation to complex disease in all protein-coding genes. Unlike the early microarray-based studies, sequencing-based studies catalogue the full range of genetic variation, including the evolutionarily youngest forms. Although the experience with common variants helped establish relevant standards for genome-wide studies, the analysis of rare variation introduces several challenges that require novel analysis approaches.
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Affiliation(s)
- Gundula Povysil
- Institute for Genomic Medicine, Columbia University Irving Medical Center, Columbia University, New York, NY, USA
| | - Slavé Petrovski
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK.,Department of Medicine, The University of Melbourne, Austin Health and Royal Melbourne Hospital, Melbourne, Victoria, Australia
| | - Joseph Hostyk
- Institute for Genomic Medicine, Columbia University Irving Medical Center, Columbia University, New York, NY, USA
| | - Vimla Aggarwal
- Institute for Genomic Medicine, Columbia University Irving Medical Center, Columbia University, New York, NY, USA
| | - Andrew S Allen
- Department of Biostatistics and Bioinformatics, Duke University, Durham, NC, USA
| | - David B Goldstein
- Institute for Genomic Medicine, Columbia University Irving Medical Center, Columbia University, New York, NY, USA.
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21
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Spectral Analysis of Codons in the DNA Sequence of Fragile X Syndrome. J Med Syst 2019; 43:261. [DOI: 10.1007/s10916-019-1408-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2019] [Accepted: 06/26/2019] [Indexed: 11/25/2022]
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22
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Yin J, Wu K, Ma Q, Dong H, Zhu Y, Hu L, Kong X. Revisiting Non-BRCA1/2 Familial Whole Exome Sequencing Datasets Implicates NCK1 as a Cancer Gene. Front Genet 2019; 10:527. [PMID: 31214250 PMCID: PMC6557995 DOI: 10.3389/fgene.2019.00527] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2019] [Accepted: 05/14/2019] [Indexed: 12/14/2022] Open
Abstract
Through linkage and candidate gene screening, many breast cancer (BC) predisposition genes have been identified in the past 20 years. However, the majority of genetic risks that contribute to familial BC remains undetermined. In this study, we revisited whole exome sequencing datasets from non-BRCA1/2 familial BC patients, to search for novel BC predisposition genes. Based on the infinite mutation model, we supposed that rare non-silent variants that cooccurred between familial and TCGA-germline datasets, might play a predisposition contributing role. In our analysis, we not only identified novel potential pathogenic variants from known cancer predisposition genes, such as MRE11, CTR9 but also identified novel candidate predisposition genes, such as NCK1. According to the TCGA mRNA expression dataset of BC, NCK1 was significantly upregulated in basal-like subtypes and downregulated in luminal subtypes. In vitro, NCK1 mutants (D73H and R42Q) transfected MCF7 cell lines, which attributed to the luminal subtype, were much more viable and invasive than the wild type. On the other side, our results also showed that overall survival and disease-free survival of patients with NCK1 variations might be dependent on the genomic context. In conclusion, genetic heterogeneity exists among non-BRCA1/2 BC pedigrees and NCK1 could be a novel BC predisposition gene.
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Affiliation(s)
- Jie Yin
- State Key Laboratory of Medical Genomics, Institute of Health Sciences, Shanghai Jiao Tong University School of Medicine and Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Kai Wu
- State Key Laboratory of Medical Genomics, Institute of Health Sciences, Shanghai Jiao Tong University School of Medicine and Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Qingyang Ma
- State Key Laboratory of Medical Genomics, Institute of Health Sciences, Shanghai Jiao Tong University School of Medicine and Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Hang Dong
- State Key Laboratory of Medical Genomics, Institute of Health Sciences, Shanghai Jiao Tong University School of Medicine and Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Yufei Zhu
- State Key Laboratory of Medical Genomics, Institute of Health Sciences, Shanghai Jiao Tong University School of Medicine and Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Landian Hu
- State Key Laboratory of Medical Genomics, Institute of Health Sciences, Shanghai Jiao Tong University School of Medicine and Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Xiangyin Kong
- State Key Laboratory of Medical Genomics, Institute of Health Sciences, Shanghai Jiao Tong University School of Medicine and Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, China
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23
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Cameron-Christie S, Wolock CJ, Groopman E, Petrovski S, Kamalakaran S, Povysil G, Vitsios D, Zhang M, Fleckner J, March RE, Gelfman S, Marasa M, Li Y, Sanna-Cherchi S, Kiryluk K, Allen AS, Fellström BC, Haefliger C, Platt A, Goldstein DB, Gharavi AG. Exome-Based Rare-Variant Analyses in CKD. J Am Soc Nephrol 2019; 30:1109-1122. [PMID: 31085678 DOI: 10.1681/asn.2018090909] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2018] [Accepted: 03/06/2019] [Indexed: 01/07/2023] Open
Abstract
BACKGROUND Studies have identified many common genetic associations that influence renal function and all-cause CKD, but these explain only a small fraction of variance in these traits. The contribution of rare variants has not been systematically examined. METHODS We performed exome sequencing of 3150 individuals, who collectively encompassed diverse CKD subtypes, and 9563 controls. To detect causal genes and evaluate the contribution of rare variants we used collapsing analysis, in which we compared the proportion of cases and controls carrying rare variants per gene. RESULTS The analyses captured five established monogenic causes of CKD: variants in PKD1, PKD2, and COL4A5 achieved study-wide significance, and we observed suggestive case enrichment for COL4A4 and COL4A3. Beyond known disease-associated genes, collapsing analyses incorporating regional variant intolerance identified suggestive dominant signals in CPT2 and several other candidate genes. Biallelic mutations in CPT2 cause carnitine palmitoyltransferase II deficiency, sometimes associated with rhabdomyolysis and acute renal injury. Genetic modifier analysis among cases with APOL1 risk genotypes identified a suggestive signal in AHDC1, implicated in Xia-Gibbs syndrome, which involves intellectual disability and other features. On the basis of the observed distribution of rare variants, we estimate that a two- to three-fold larger cohort would provide 80% power to implicate new genes for all-cause CKD. CONCLUSIONS This study demonstrates that rare-variant collapsing analyses can validate known genes and identify candidate genes and modifiers for kidney disease. In so doing, these findings provide a motivation for larger-scale investigation of rare-variant risk contributions across major clinical CKD categories.
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Affiliation(s)
- Sophia Cameron-Christie
- AstraZeneca Centre for Genomics Research, Discovery Sciences, R&D BioPharmaceuticals, AstraZeneca, Cambridge, UK
| | | | - Emily Groopman
- Division of Nephrology, Department of Medicine, Columbia University, New York, New York
| | - Slavé Petrovski
- AstraZeneca Centre for Genomics Research, Discovery Sciences, R&D BioPharmaceuticals, AstraZeneca, Cambridge, UK
| | | | - Gundula Povysil
- AstraZeneca Centre for Genomics Research, Discovery Sciences, R&D BioPharmaceuticals, AstraZeneca, Cambridge, UK.,Institute for Genomic Medicine, Columbia University Medical Center, New York, New York
| | - Dimitrios Vitsios
- AstraZeneca Centre for Genomics Research, Discovery Sciences, R&D BioPharmaceuticals, AstraZeneca, Cambridge, UK
| | - Mengqi Zhang
- Institute for Genomic Medicine, Columbia University Medical Center, New York, New York.,Department of Biostatistics and Bioinformatics, Duke University, Durham, North Carolina; and
| | - Jan Fleckner
- AstraZeneca Centre for Genomics Research, Discovery Sciences, R&D BioPharmaceuticals, AstraZeneca, Cambridge, UK
| | - Ruth E March
- Precision Medicine, R&D Oncology, AstraZeneca, Cambridge, UK
| | | | - Maddalena Marasa
- Division of Nephrology, Department of Medicine, Columbia University, New York, New York
| | - Yifu Li
- Division of Nephrology, Department of Medicine, Columbia University, New York, New York
| | - Simone Sanna-Cherchi
- Division of Nephrology, Department of Medicine, Columbia University, New York, New York
| | - Krzysztof Kiryluk
- Division of Nephrology, Department of Medicine, Columbia University, New York, New York
| | - Andrew S Allen
- Institute for Genomic Medicine, Columbia University Medical Center, New York, New York.,Department of Biostatistics and Bioinformatics, Duke University, Durham, North Carolina; and
| | - Bengt C Fellström
- Department of Medical Sciences, Uppsala University Hospital, Uppsala, Sweden; and
| | - Carolina Haefliger
- AstraZeneca Centre for Genomics Research, Discovery Sciences, R&D BioPharmaceuticals, AstraZeneca, Cambridge, UK
| | - Adam Platt
- AstraZeneca Centre for Genomics Research, Discovery Sciences, R&D BioPharmaceuticals, AstraZeneca, Cambridge, UK;
| | - David B Goldstein
- AstraZeneca Centre for Genomics Research, Discovery Sciences, R&D BioPharmaceuticals, AstraZeneca, Cambridge, UK; .,Department of Genetics and Development and.,Institute for Genomic Medicine, Columbia University Medical Center, New York, New York
| | - Ali G Gharavi
- Division of Nephrology, Department of Medicine, Columbia University, New York, New York; .,Institute for Genomic Medicine, Columbia University Medical Center, New York, New York
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24
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Ulirsch JC, Verboon JM, Kazerounian S, Guo MH, Yuan D, Ludwig LS, Handsaker RE, Abdulhay NJ, Fiorini C, Genovese G, Lim ET, Cheng A, Cummings BB, Chao KR, Beggs AH, Genetti CA, Sieff CA, Newburger PE, Niewiadomska E, Matysiak M, Vlachos A, Lipton JM, Atsidaftos E, Glader B, Narla A, Gleizes PE, O'Donohue MF, Montel-Lehry N, Amor DJ, McCarroll SA, O'Donnell-Luria AH, Gupta N, Gabriel SB, MacArthur DG, Lander ES, Lek M, Da Costa L, Nathan DG, Korostelev AA, Do R, Sankaran VG, Gazda HT. The Genetic Landscape of Diamond-Blackfan Anemia. Am J Hum Genet 2018; 103:930-947. [PMID: 30503522 PMCID: PMC6288280 DOI: 10.1016/j.ajhg.2018.10.027] [Citation(s) in RCA: 155] [Impact Index Per Article: 25.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2018] [Accepted: 10/29/2018] [Indexed: 01/19/2023] Open
Abstract
Diamond-Blackfan anemia (DBA) is a rare bone marrow failure disorder that affects 7 out of 1,000,000 live births and has been associated with mutations in components of the ribosome. In order to characterize the genetic landscape of this heterogeneous disorder, we recruited a cohort of 472 individuals with a clinical diagnosis of DBA and performed whole-exome sequencing (WES). We identified relevant rare and predicted damaging mutations for 78% of individuals. The majority of mutations were singletons, absent from population databases, predicted to cause loss of function, and located in 1 of 19 previously reported ribosomal protein (RP)-encoding genes. Using exon coverage estimates, we identified and validated 31 deletions in RP genes. We also observed an enrichment for extended splice site mutations and validated their diverse effects using RNA sequencing in cell lines obtained from individuals with DBA. Leveraging the size of our cohort, we observed robust genotype-phenotype associations with congenital abnormalities and treatment outcomes. We further identified rare mutations in seven previously unreported RP genes that may cause DBA, as well as several distinct disorders that appear to phenocopy DBA, including nine individuals with biallelic CECR1 mutations that result in deficiency of ADA2. However, no new genes were identified at exome-wide significance, suggesting that there are no unidentified genes containing mutations readily identified by WES that explain >5% of DBA-affected case subjects. Overall, this report should inform not only clinical practice for DBA-affected individuals, but also the design and analysis of rare variant studies for heterogeneous Mendelian disorders.
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Affiliation(s)
- Jacob C Ulirsch
- Division of Hematology/Oncology, The Manton Center for Orphan Disease Research, Boston Children's Hospital and Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02115, USA; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Program in Biological and Biomedical Sciences, Harvard Medical School, Boston, MA 02115, USA
| | - Jeffrey M Verboon
- Division of Hematology/Oncology, The Manton Center for Orphan Disease Research, Boston Children's Hospital and Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02115, USA; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Shideh Kazerounian
- Division of Genetics and Genomics, The Manton Center for Orphan Disease Research, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Michael H Guo
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Daniel Yuan
- Division of Genetics and Genomics, The Manton Center for Orphan Disease Research, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Leif S Ludwig
- Division of Hematology/Oncology, The Manton Center for Orphan Disease Research, Boston Children's Hospital and Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02115, USA; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Robert E Handsaker
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
| | - Nour J Abdulhay
- Division of Hematology/Oncology, The Manton Center for Orphan Disease Research, Boston Children's Hospital and Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02115, USA; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Claudia Fiorini
- Division of Hematology/Oncology, The Manton Center for Orphan Disease Research, Boston Children's Hospital and Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02115, USA; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Giulio Genovese
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Elaine T Lim
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Aaron Cheng
- Division of Hematology/Oncology, The Manton Center for Orphan Disease Research, Boston Children's Hospital and Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02115, USA; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Beryl B Cummings
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Program in Biological and Biomedical Sciences, Harvard Medical School, Boston, MA 02115, USA
| | - Katherine R Chao
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Alan H Beggs
- Division of Genetics and Genomics, The Manton Center for Orphan Disease Research, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Casie A Genetti
- Division of Genetics and Genomics, The Manton Center for Orphan Disease Research, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Colin A Sieff
- Division of Hematology/Oncology, The Manton Center for Orphan Disease Research, Boston Children's Hospital and Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02115, USA
| | - Peter E Newburger
- Department of Pediatrics, University of Massachusetts Medical School, Worcester, MA 01605, USA
| | - Edyta Niewiadomska
- Department of Pediatric Hematology/Oncology, Medical University of Warsaw, Warsaw, Poland
| | - Michal Matysiak
- Department of Pediatric Hematology/Oncology, Medical University of Warsaw, Warsaw, Poland
| | - Adrianna Vlachos
- Feinstein Institute for Medical Research, Manhasset, NY; Division of Hematology/Oncology and Stem Cell Transplantation, Cohen Children's Medical Center, New Hyde Park, NY; Hofstra Northwell School of Medicine, Hempstead, NY 11030, USA
| | - Jeffrey M Lipton
- Feinstein Institute for Medical Research, Manhasset, NY; Division of Hematology/Oncology and Stem Cell Transplantation, Cohen Children's Medical Center, New Hyde Park, NY; Hofstra Northwell School of Medicine, Hempstead, NY 11030, USA
| | - Eva Atsidaftos
- Feinstein Institute for Medical Research, Manhasset, NY; Division of Hematology/Oncology and Stem Cell Transplantation, Cohen Children's Medical Center, New Hyde Park, NY; Hofstra Northwell School of Medicine, Hempstead, NY 11030, USA
| | - Bertil Glader
- Department of Pediatrics, Stanford University School of Medicine, Stanford, CA 02114, USA
| | - Anupama Narla
- Department of Pediatrics, Stanford University School of Medicine, Stanford, CA 02114, USA
| | - Pierre-Emmanuel Gleizes
- Laboratory of Eukaryotic Molecular Biology, Center for Integrative Biology (CBI), University of Toulouse, CNRS, Toulouse, France
| | - Marie-Françoise O'Donohue
- Laboratory of Eukaryotic Molecular Biology, Center for Integrative Biology (CBI), University of Toulouse, CNRS, Toulouse, France
| | - Nathalie Montel-Lehry
- Laboratory of Eukaryotic Molecular Biology, Center for Integrative Biology (CBI), University of Toulouse, CNRS, Toulouse, France
| | - David J Amor
- Murdoch Children's Research Institute and Department of Paediatrics, University of Melbourne, Parkville, VIC, Australia
| | - Steven A McCarroll
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
| | - Anne H O'Donnell-Luria
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Division of Genetics and Genomics, The Manton Center for Orphan Disease Research, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, USA; Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Namrata Gupta
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Stacey B Gabriel
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Daniel G MacArthur
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Eric S Lander
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Monkol Lek
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Lydie Da Costa
- University Paris VII Denis DIDEROT, Faculté de Médecine Xavier Bichat, 75019 Paris, France; Laboratory of Excellence for Red Cell, LABEX GR-Ex, 75015 Paris, France
| | - David G Nathan
- Division of Hematology/Oncology, The Manton Center for Orphan Disease Research, Boston Children's Hospital and Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02115, USA
| | - Andrei A Korostelev
- RNA Therapeutics Institute, Department of Biochemistry and Molecular Pharmacology, University of Massachusetts Medical School, 368 Plantation Street, Worcester, MA 01605, USA
| | - Ron Do
- Department of Genetics and Genomic Sciences and The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Vijay G Sankaran
- Division of Hematology/Oncology, The Manton Center for Orphan Disease Research, Boston Children's Hospital and Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02115, USA; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Harvard Stem Cell Institute, Cambridge, MA 02138, USA.
| | - Hanna T Gazda
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Division of Genetics and Genomics, The Manton Center for Orphan Disease Research, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, USA.
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Guo MH, Plummer L, Chan YM, Hirschhorn JN, Lippincott MF. Burden Testing of Rare Variants Identified through Exome Sequencing via Publicly Available Control Data. Am J Hum Genet 2018; 103:522-534. [PMID: 30269813 DOI: 10.1016/j.ajhg.2018.08.016] [Citation(s) in RCA: 105] [Impact Index Per Article: 17.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2018] [Accepted: 08/27/2018] [Indexed: 12/30/2022] Open
Abstract
The genetic causes of many Mendelian disorders remain undefined. Factors such as lack of large multiplex families, locus heterogeneity, and incomplete penetrance hamper these efforts for many disorders. Previous work suggests that gene-based burden testing-where the aggregate burden of rare, protein-altering variants in each gene is compared between case and control subjects-might overcome some of these limitations. The increasing availability of large-scale public sequencing databases such as Genome Aggregation Database (gnomAD) can enable burden testing using these databases as controls, obviating the need for additional control sequencing for each study. However, there exist various challenges with using public databases as controls, including lack of individual-level data, differences in ancestry, and differences in sequencing platforms and data processing. To illustrate the approach of using public data as controls, we analyzed whole-exome sequencing data from 393 individuals with idiopathic hypogonadotropic hypogonadism (IHH), a rare disorder with significant locus heterogeneity and incomplete penetrance against control subjects from gnomAD (n = 123,136). We leveraged presumably benign synonymous variants to calibrate our approach. Through iterative analyses, we systematically addressed and overcame various sources of artifact that can arise when using public control data. In particular, we introduce an approach for highly adaptable variant quality filtering that leads to well-calibrated results. Our approach "re-discovered" genes previously implicated in IHH (FGFR1, TACR3, GNRHR). Furthermore, we identified a significant burden in TYRO3, a gene implicated in hypogonadotropic hypogonadism in mice. Finally, we developed a user-friendly software package TRAPD (Test Rare vAriants with Public Data) for performing gene-based burden testing against public databases.
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Cancer genetics, precision prevention and a call to action. Nat Genet 2018; 50:1212-1218. [PMID: 30158684 DOI: 10.1038/s41588-018-0202-0] [Citation(s) in RCA: 81] [Impact Index Per Article: 13.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2017] [Accepted: 06/05/2018] [Indexed: 01/10/2023]
Abstract
More than 15 years have passed since the identification, through linkage, of 'first-wave' susceptibility genes for common cancers (BRCA1, BRCA2, MLH1 and MSH2). These genes have strong frequency-penetrance profiles, such that the associated clinical utility probably remains relevant regardless of the context of ascertainment. 'Second-wave' genes, not tractable by linkage, were subsequently identified by mutation screening of candidate genes (PALB2, ATM, CHEK2, BRIP1, RAD51C and RAD51D). Their innately weaker frequency-penetrance profiles have rendered delineation of cancer associations, risks and variant pathogenicity challenging, thereby compromising their clinical application. Early germline exome-sequencing endeavors for common cancers did not yield the long-anticipated slew of 'next-wave' genes but instead implied a highly polygenic genomic architecture requiring much larger experiments to make any substantive inroads into gene discovery. As such, the 'genetic economics' of frequency penetrance clearly indicates that focused identification of carriers of first-wave-gene mutations is most impactful for cancer control. With screening, prevention and early detection at the forefront of the cancer management agenda, we propose that the time is nigh for the initiation of national population-testing programs to identify carriers of first-wave gene mutation carriers. To fully deliver a precision prevention program, long-term, large-scale mutation studies that capture longitudinal clinical data and serial biosamples are required.
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Elhawary NA, Jiffri EH, Jambi S, Mufti AH, Dannoun A, Kordi H, Khogeer A, Jiffri OH, Elhawary AN, Tayeb MT. Molecular characterization of exonic rearrangements and frame shifts in the dystrophin gene in Duchenne muscular dystrophy patients in a Saudi community. Hum Genomics 2018; 12:18. [PMID: 29631625 PMCID: PMC5891934 DOI: 10.1186/s40246-018-0152-8] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2018] [Accepted: 04/02/2018] [Indexed: 02/08/2023] Open
Abstract
BACKGROUND In individuals with Duchenne muscular dystrophy (DMD), exon skipping treatment to restore a wild-type phenotype or correct the frame shift of the mRNA transcript of the dystrophin (DMD) gene are mutation-specific. To explore the molecular characterization of DMD rearrangements and predict the reading frame, we simultaneously screened all 79 DMD gene exons of 45 unrelated male DMD patients using a multiplex ligation-dependent probe amplification (MLPA) assay for deletion/duplication patterns. Multiplex PCR was used to confirm single deletions detected by the MLPA. RESULTS There was an obvious diagnostic delay, with an extremely statistically significant difference between the age at initial symptoms and the age of clinical evaluation of DMD cases (t value, 10.3; 95% confidence interval 5.95-8.80, P < 0.0001); the mean difference between the two groups was 7.4 years. Overall, we identified 147 intragenic rearrangements: 46.3% deletions and 53.7% duplications. Most of the deletions (92.5%) were between exons 44 and 56, with exon 50 being the most frequently involved (19.1%). Eight new rearrangements, including a mixed deletion/duplication and double duplications, were linked to seven cases with DMD. Of all the cases, 17.8% had duplications with no hot spots. In addition, confirmation of the reading frame hypothesis helped account for new DMD rearrangements in this study. We found that 81% of our Saudi patients would potentially benefit from exon skipping, of which 42.9% had a mutation amenable to skipping of exon 51. CONCLUSIONS Our study could generate considerable data on mutational rearrangements that may promote future experimental therapies in Saudi Arabia.
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Affiliation(s)
- Nasser A Elhawary
- Department of Medical Genetics, Medicine College, Umm Al-Qura University, P.O. Box 57543, Mecca, 21955, Saudi Arabia.
- Department of Molecular Genetics, Faculty of Medicine, Ain Shams University, Cairo, 11566, Egypt.
| | - Essam H Jiffri
- Department of Medical Laboratory Technology, Faculty of Applied Medical Sciences, King Abdul-Aziz University, Jeddah, Saudi Arabia
| | - Samira Jambi
- Department of Pediatrics, Al Hada Military Hospital, Al Hada, Saudi Arabia
| | - Ahmad H Mufti
- Department of Medical Genetics, Medicine College, Umm Al-Qura University, P.O. Box 57543, Mecca, 21955, Saudi Arabia
| | - Anas Dannoun
- Department of Medical Genetics, Medicine College, Umm Al-Qura University, P.O. Box 57543, Mecca, 21955, Saudi Arabia
| | - Hassan Kordi
- Department of Medical Genetics, Medicine College, Umm Al-Qura University, P.O. Box 57543, Mecca, 21955, Saudi Arabia
| | - Asim Khogeer
- Department of Plan and Research, General Directorate of Health Affairs, Mecca Region, Ministry of Health, Mecca, Saudi Arabia
| | - Osama H Jiffri
- Department of Medical Laboratory Technology, Faculty of Applied Medical Sciences, King Abdul-Aziz University, Jeddah, Saudi Arabia
| | | | - Mohammed T Tayeb
- Department of Medical Genetics, Medicine College, Umm Al-Qura University, P.O. Box 57543, Mecca, 21955, Saudi Arabia
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Molecular characterization of exonic rearrangements and frame shifts in the dystrophin gene in Duchenne muscular dystrophy patients in a Saudi community. Hum Genomics 2018. [PMID: 29631625 DOI: 10.1186/s40246-018-0152-8]] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND In individuals with Duchenne muscular dystrophy (DMD), exon skipping treatment to restore a wild-type phenotype or correct the frame shift of the mRNA transcript of the dystrophin (DMD) gene are mutation-specific. To explore the molecular characterization of DMD rearrangements and predict the reading frame, we simultaneously screened all 79 DMD gene exons of 45 unrelated male DMD patients using a multiplex ligation-dependent probe amplification (MLPA) assay for deletion/duplication patterns. Multiplex PCR was used to confirm single deletions detected by the MLPA. RESULTS There was an obvious diagnostic delay, with an extremely statistically significant difference between the age at initial symptoms and the age of clinical evaluation of DMD cases (t value, 10.3; 95% confidence interval 5.95-8.80, P < 0.0001); the mean difference between the two groups was 7.4 years. Overall, we identified 147 intragenic rearrangements: 46.3% deletions and 53.7% duplications. Most of the deletions (92.5%) were between exons 44 and 56, with exon 50 being the most frequently involved (19.1%). Eight new rearrangements, including a mixed deletion/duplication and double duplications, were linked to seven cases with DMD. Of all the cases, 17.8% had duplications with no hot spots. In addition, confirmation of the reading frame hypothesis helped account for new DMD rearrangements in this study. We found that 81% of our Saudi patients would potentially benefit from exon skipping, of which 42.9% had a mutation amenable to skipping of exon 51. CONCLUSIONS Our study could generate considerable data on mutational rearrangements that may promote future experimental therapies in Saudi Arabia.
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Morimoto Y, Shimada-Sugimoto M, Otowa T, Yoshida S, Kinoshita A, Mishima H, Yamaguchi N, Mori T, Imamura A, Ozawa H, Kurotaki N, Ziegler C, Domschke K, Deckert J, Umekage T, Tochigi M, Kaiya H, Okazaki Y, Tokunaga K, Sasaki T, Yoshiura KI, Ono S. Whole-exome sequencing and gene-based rare variant association tests suggest that PLA2G4E might be a risk gene for panic disorder. Transl Psychiatry 2018; 8:41. [PMID: 29391400 PMCID: PMC5804028 DOI: 10.1038/s41398-017-0088-0] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/13/2017] [Revised: 11/09/2017] [Accepted: 11/30/2017] [Indexed: 12/31/2022] Open
Abstract
Panic disorder (PD) is characterized by recurrent and unexpected panic attacks, subsequent anticipatory anxiety, and phobic avoidance. Recent epidemiological and genetic studies have revealed that genetic factors contribute to the pathogenesis of PD. We performed whole-exome sequencing on one Japanese family, including multiple patients with panic disorder, which identified seven rare protein-altering variants. We then screened these genes in a Japanese PD case-control group (384 sporadic PD patients and 571 controls), resulting in the detection of three novel single nucleotide variants as potential candidates for PD (chr15: 42631993, T>C in GANC; chr15: 42342861, G>T in PLA2G4E; chr20: 3641457, G>C in GFRA4). Statistical analyses of these three genes showed that PLA2G4E yielded the lowest p value in gene-based rare variant association tests by Efficient and Parallelizable Association Container Toolbox algorithms; however, the p value did not reach the significance threshold in the Japanese. Likewise, in a German case-control study (96 sporadic PD patients and 96 controls), PLA2G4E showed the lowest p value but again did not reach the significance threshold. In conclusion, we failed to find any significant variants or genes responsible for the development of PD. Nonetheless, our results still leave open the possibility that rare protein-altering variants in PLA2G4E contribute to the risk of PD, considering the function of this gene.
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Affiliation(s)
- Yoshiro Morimoto
- 0000 0000 8902 2273grid.174567.6Department of Neuropsychiatry, Unit of Translation Medicine, Nagasaki University Graduate School of Biomedical Sciences, Nagasaki, Japan ,0000 0000 8902 2273grid.174567.6Department of Human Genetics, Nagasaki University Graduate School of Biomedical Sciences, Nagasaki, Japan
| | - Mihoko Shimada-Sugimoto
- 0000 0001 2151 536Xgrid.26999.3dDepartment of Human Genetics, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Takeshi Otowa
- grid.440938.2Graduate School of Clinical Psychology, Professional Degree Program in Clinical Psychology, Teikyo Heisei University, Tokyo, Japan
| | - Shintaro Yoshida
- 0000 0000 8902 2273grid.174567.6Department of Human Genetics, Nagasaki University Graduate School of Biomedical Sciences, Nagasaki, Japan
| | - Akira Kinoshita
- 0000 0000 8902 2273grid.174567.6Department of Human Genetics, Nagasaki University Graduate School of Biomedical Sciences, Nagasaki, Japan
| | - Hiroyuki Mishima
- 0000 0000 8902 2273grid.174567.6Department of Human Genetics, Nagasaki University Graduate School of Biomedical Sciences, Nagasaki, Japan
| | - Naohiro Yamaguchi
- 0000 0000 8902 2273grid.174567.6Department of Neuropsychiatry, Unit of Translation Medicine, Nagasaki University Graduate School of Biomedical Sciences, Nagasaki, Japan
| | | | - Akira Imamura
- 0000 0000 8902 2273grid.174567.6Department of Neuropsychiatry, Unit of Translation Medicine, Nagasaki University Graduate School of Biomedical Sciences, Nagasaki, Japan
| | - Hiroki Ozawa
- 0000 0000 8902 2273grid.174567.6Department of Neuropsychiatry, Unit of Translation Medicine, Nagasaki University Graduate School of Biomedical Sciences, Nagasaki, Japan
| | - Naohiro Kurotaki
- 0000 0000 8902 2273grid.174567.6Department of Neuropsychiatry, Unit of Translation Medicine, Nagasaki University Graduate School of Biomedical Sciences, Nagasaki, Japan
| | - Christiane Ziegler
- 0000 0001 1958 8658grid.8379.5Department of Psychiatry, Psychosomatics, and Psychotherapy, Center of Mental Health, University of Würzburg, Würzburg, Germany ,grid.5963.9Department of Psychiatry and Psychotherapy, Medical Center–University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Katharina Domschke
- 0000 0001 1958 8658grid.8379.5Department of Psychiatry, Psychosomatics, and Psychotherapy, Center of Mental Health, University of Würzburg, Würzburg, Germany ,grid.5963.9Department of Psychiatry and Psychotherapy, Medical Center–University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Jürgen Deckert
- 0000 0001 1958 8658grid.8379.5Department of Psychiatry, Psychosomatics, and Psychotherapy, Center of Mental Health, University of Würzburg, Würzburg, Germany
| | - Tadashi Umekage
- 0000 0001 2151 536Xgrid.26999.3dDivision for Environment, Health and Safety, The University of Tokyo, Tokyo, Japan
| | - Mamoru Tochigi
- 0000 0000 9239 9995grid.264706.1Department of Neuropsychiatry, Teikyo University School of Medicine, Tokyo, Japan
| | - Hisanobu Kaiya
- Panic Disorder Research Center, Warakukai Med. Corp, Tokyo, Japan
| | - Yuji Okazaki
- Department of Psychiatry, Koseikai Michino-o Hospital, Nagasaki, Japan
| | - Katsushi Tokunaga
- 0000 0001 2151 536Xgrid.26999.3dDepartment of Human Genetics, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Tsukasa Sasaki
- 0000 0001 2151 536Xgrid.26999.3dDepartment of Physical and Health Education, Graduate School of Education, The University of Tokyo, Tokyo, Japan
| | - Koh-ichiro Yoshiura
- 0000 0000 8902 2273grid.174567.6Department of Human Genetics, Nagasaki University Graduate School of Biomedical Sciences, Nagasaki, Japan
| | - Shinji Ono
- Department of Neuropsychiatry, Unit of Translation Medicine, Nagasaki University Graduate School of Biomedical Sciences, Nagasaki, Japan. .,Department of Human Genetics, Nagasaki University Graduate School of Biomedical Sciences, Nagasaki, Japan. .,Aino-Ariake Hospital, Unzen, Nagasaki, Japan.
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Sanna-Cherchi S, Khan K, Westland R, Krithivasan P, Fievet L, Rasouly HM, Ionita-Laza I, Capone VP, Fasel DA, Kiryluk K, Kamalakaran S, Bodria M, Otto EA, Sampson MG, Gillies CE, Vega-Warner V, Vukojevic K, Pediaditakis I, Makar GS, Mitrotti A, Verbitsky M, Martino J, Liu Q, Na YJ, Goj V, Ardissino G, Gigante M, Gesualdo L, Janezcko M, Zaniew M, Mendelsohn CL, Shril S, Hildebrandt F, van Wijk JAE, Arapovic A, Saraga M, Allegri L, Izzi C, Scolari F, Tasic V, Ghiggeri GM, Latos-Bielenska A, Materna-Kiryluk A, Mane S, Goldstein DB, Lifton RP, Katsanis N, Davis EE, Gharavi AG. Exome-wide Association Study Identifies GREB1L Mutations in Congenital Kidney Malformations. Am J Hum Genet 2017; 101:789-802. [PMID: 29100090 DOI: 10.1016/j.ajhg.2017.09.018] [Citation(s) in RCA: 55] [Impact Index Per Article: 7.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2017] [Accepted: 09/22/2017] [Indexed: 01/02/2023] Open
Abstract
Renal agenesis and hypodysplasia (RHD) are major causes of pediatric chronic kidney disease and are highly genetically heterogeneous. We conducted whole-exome sequencing in 202 case subjects with RHD and identified diagnostic mutations in genes known to be associated with RHD in 7/202 case subjects. In an additional affected individual with RHD and a congenital heart defect, we found a homozygous loss-of-function (LOF) variant in SLIT3, recapitulating phenotypes reported with Slit3 inactivation in the mouse. To identify genes associated with RHD, we performed an exome-wide association study with 195 unresolved case subjects and 6,905 control subjects. The top signal resided in GREB1L, a gene implicated previously in Hoxb1 and Shha signaling in zebrafish. The significance of the association, which was p = 2.0 × 10-5 for novel LOF, increased to p = 4.1 × 10-6 for LOF and deleterious missense variants combined, and augmented further after accounting for segregation and de novo inheritance of rare variants (joint p = 2.3 × 10-7). Finally, CRISPR/Cas9 disruption or knockdown of greb1l in zebrafish caused specific pronephric defects, which were rescued by wild-type human GREB1L mRNA, but not mRNA containing alleles identified in case subjects. Together, our study provides insight into the genetic landscape of kidney malformations in humans, presents multiple candidates, and identifies SLIT3 and GREB1L as genes implicated in the pathogenesis of RHD.
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Affiliation(s)
| | - Kamal Khan
- Center for Human Disease Modeling, Duke University, Durham, NC 27701, USA
| | - Rik Westland
- Division of Nephrology, Columbia University, New York, NY 10032, USA; Department of Pediatric Nephrology, VU University Medical Center, Amsterdam 1007 MB, the Netherlands
| | - Priya Krithivasan
- Division of Nephrology, Columbia University, New York, NY 10032, USA
| | - Lorraine Fievet
- Center for Human Disease Modeling, Duke University, Durham, NC 27701, USA
| | - Hila Milo Rasouly
- Division of Nephrology, Columbia University, New York, NY 10032, USA
| | | | | | - David A Fasel
- Division of Nephrology, Columbia University, New York, NY 10032, USA
| | - Krzysztof Kiryluk
- Division of Nephrology, Columbia University, New York, NY 10032, USA
| | - Sitharthan Kamalakaran
- Institute for Genomic Medicine, Columbia University Medical Center, New York, NY 10032, USA
| | - Monica Bodria
- Division of Nephrology, Dialysis, Transplantation, and Laboratory on Pathophysiology of Uremia, Istituto G. Gaslini, Genoa 16147, Italy
| | - Edgar A Otto
- University of Michigan School of Medicine, Department of Internal Medicine-Nephrology, Ann Arbor, MI 48109, USA
| | - Matthew G Sampson
- University of Michigan School of Medicine, Department of Pediatrics-Nephrology, Ann Arbor, MI 48109, USA
| | - Christopher E Gillies
- University of Michigan School of Medicine, Department of Pediatrics-Nephrology, Ann Arbor, MI 48109, USA
| | - Virginia Vega-Warner
- University of Michigan School of Medicine, Department of Pediatrics-Nephrology, Ann Arbor, MI 48109, USA
| | - Katarina Vukojevic
- Department of Anatomy, Histology, and Embryology, School of Medicine, University of Split, Split 21000, Croatia
| | - Igor Pediaditakis
- Center for Human Disease Modeling, Duke University, Durham, NC 27701, USA
| | - Gabriel S Makar
- Division of Nephrology, Columbia University, New York, NY 10032, USA
| | - Adele Mitrotti
- Division of Nephrology, Columbia University, New York, NY 10032, USA
| | - Miguel Verbitsky
- Division of Nephrology, Columbia University, New York, NY 10032, USA
| | - Jeremiah Martino
- Division of Nephrology, Columbia University, New York, NY 10032, USA
| | - Qingxue Liu
- Division of Nephrology, Columbia University, New York, NY 10032, USA
| | - Young-Ji Na
- Division of Nephrology, Columbia University, New York, NY 10032, USA
| | - Vinicio Goj
- Pediatric Unit, Fatebenefratelli Hospital, Milan 20121, Italy
| | - Gianluigi Ardissino
- Pediatric Nephrology and Dialysis Unit, Fondazione Ca' Granda IRCCS Ospedale Maggiore Policlinico Milano, 20122 Milan, Italy
| | - Maddalena Gigante
- Department of Medical and Surgical Sciences, University of Foggia, Foggia 71121, Italy
| | - Loreto Gesualdo
- Section of Nephrology, Department of Emergency and Organ Transplantation, University of Bari, Bari 70121, Italy
| | - Magdalena Janezcko
- Department of Medical Genetics, Chair of Pediatrics, Jagiellonian University, Collegium Medicum, Krakow 31-008, Poland
| | | | - Cathy Lee Mendelsohn
- Department of Urology, Pathology and Cell Biology, Genetics and Development, Columbia University, New York, NY 10032, USA
| | - Shirlee Shril
- Department of Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Friedhelm Hildebrandt
- Department of Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Joanna A E van Wijk
- Department of Pediatric Nephrology, VU University Medical Center, Amsterdam 1007 MB, the Netherlands
| | - Adela Arapovic
- Department of Pediatrics, University Hospital of Split, Split 21000, Croatia
| | - Marijan Saraga
- Department of Pediatrics, University Hospital of Split, Split 21000, Croatia; School of Medicine, University of Split, Split 21000, Croatia
| | - Landino Allegri
- Department of Medicine and Surgery, University of Parma, Parma 43100, Italy
| | - Claudia Izzi
- Cattedra di Nefrologia, Università di Brescia, Seconda Divisione di Nefrologia Azienda Ospedaliera Spedali Civili di Brescia Presidio di Montichiari, Brescia 25018, Italy; Dipartimento Ostetrico Ginecologico, Azienda Ospedaliera Spedali Civili di Brescia, Brescia 25018, Italy
| | - Francesco Scolari
- Cattedra di Nefrologia, Università di Brescia, Seconda Divisione di Nefrologia Azienda Ospedaliera Spedali Civili di Brescia Presidio di Montichiari, Brescia 25018, Italy
| | - Velibor Tasic
- Department of Pediatric Nephrology, University Children's Hospital, Medical Faculty of Skopje, Skopje 1000, Macedonia
| | - Gian Marco Ghiggeri
- Division of Nephrology, Dialysis, Transplantation, and Laboratory on Pathophysiology of Uremia, Istituto G. Gaslini, Genoa 16147, Italy
| | - Anna Latos-Bielenska
- Department of Medical Genetics, Poznan University of Medical Sciences, and Center for Medical Genetics GENESIS, Poznan 61-701, Poland
| | - Anna Materna-Kiryluk
- Department of Medical Genetics, Poznan University of Medical Sciences, and Center for Medical Genetics GENESIS, Poznan 61-701, Poland
| | - Shrikant Mane
- Department of Human Genetics, Yale University School of Medicine, New Haven, CT 06510, USA
| | - David B Goldstein
- Institute for Genomic Medicine, Columbia University Medical Center, New York, NY 10032, USA
| | - Richard P Lifton
- Department of Human Genetics, Yale University School of Medicine, New Haven, CT 06510, USA; Howard Hughes Medical Institute, Chevy Chase, MD 20815, USA
| | - Nicholas Katsanis
- Center for Human Disease Modeling, Duke University, Durham, NC 27701, USA
| | - Erica E Davis
- Center for Human Disease Modeling, Duke University, Durham, NC 27701, USA.
| | - Ali G Gharavi
- Division of Nephrology, Columbia University, New York, NY 10032, USA
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