1
|
Copeland I, Wonkam-Tingang E, Gupta-Malhotra M, Hashmi SS, Han Y, Jajoo A, Hall NJ, Hernandez PP, Lie N, Liu D, Xu J, Rosenfeld J, Haldipur A, Desire Z, Coban-Akdemir ZH, Scott DA, Li Q, Chao HT, Zaske AM, Lupski JR, Milewicz DM, Shete S, Posey JE, Hanchard NA. Exome sequencing implicates ancestry-related Mendelian variation at SYNE1 in childhood-onset essential hypertension. JCI Insight 2024; 9:e172152. [PMID: 38716726 DOI: 10.1172/jci.insight.172152] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2023] [Accepted: 03/19/2024] [Indexed: 05/12/2024] Open
Abstract
Childhood-onset essential hypertension (COEH) is an uncommon form of hypertension that manifests in childhood or adolescence and, in the United States, disproportionately affects children of African ancestry. The etiology of COEH is unknown, but its childhood onset, low prevalence, high heritability, and skewed ancestral demography suggest the potential to identify rare genetic variation segregating in a Mendelian manner among affected individuals and thereby implicate genes important to disease pathogenesis. However, no COEH genes have been reported to date. Here, we identify recessive segregation of rare and putatively damaging missense variation in the spectrin domain of spectrin repeat containing nuclear envelope protein 1 (SYNE1), a cardiovascular candidate gene, in 3 of 16 families with early-onset COEH without an antecedent family history. By leveraging exome sequence data from an additional 48 COEH families, 1,700 in-house trios, and publicly available data sets, we demonstrate that compound heterozygous SYNE1 variation in these COEH individuals occurred more often than expected by chance and that this class of biallelic rare variation was significantly enriched among individuals of African genetic ancestry. Using in vitro shRNA knockdown of SYNE1, we show that reduced SYNE1 expression resulted in a substantial decrease in the elasticity of smooth muscle vascular cells that could be rescued by pharmacological inhibition of the downstream RhoA/Rho-associated protein kinase pathway. These results provide insights into the molecular genetics and underlying pathophysiology of COEH and suggest a role for precision therapeutics in the future.
Collapse
Affiliation(s)
- Ian Copeland
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas, USA
| | - Edmond Wonkam-Tingang
- Childhood Complex Disease Genomics Section, National Human Genome Research Institute, NIH, Bethesda, USA
| | | | - S Shahrukh Hashmi
- Department of Pediatrics, McGovern Medical School, The University of Texas Health Science Center at Houston, Houston, Texas, USA
| | - Yixing Han
- Childhood Complex Disease Genomics Section, National Human Genome Research Institute, NIH, Bethesda, USA
| | - Aarti Jajoo
- Childhood Complex Disease Genomics Section, National Human Genome Research Institute, NIH, Bethesda, USA
| | - Nancy J Hall
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas, USA
- US Department of Agriculture Agricultural Research Service Children's Nutrition Research Center, Baylor College of Medicine, Houston, Texas, USA
| | - Paula P Hernandez
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas, USA
- US Department of Agriculture Agricultural Research Service Children's Nutrition Research Center, Baylor College of Medicine, Houston, Texas, USA
| | - Natasha Lie
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas, USA
- Childhood Complex Disease Genomics Section, National Human Genome Research Institute, NIH, Bethesda, USA
- US Department of Agriculture Agricultural Research Service Children's Nutrition Research Center, Baylor College of Medicine, Houston, Texas, USA
| | - Dan Liu
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas, USA
| | - Jun Xu
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas, USA
| | - Jill Rosenfeld
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas, USA
- Baylor Genetics, Houston, Texas, USA
| | - Aparna Haldipur
- Childhood Complex Disease Genomics Section, National Human Genome Research Institute, NIH, Bethesda, USA
| | - Zelene Desire
- Childhood Complex Disease Genomics Section, National Human Genome Research Institute, NIH, Bethesda, USA
| | - Zeynep H Coban-Akdemir
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas, USA
- Human Genetics Center, The University of Texas Health Science Center at Houston, Houston, Texas, USA
| | - Daryl A Scott
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas, USA
- Texas Children's Hospital, Houston, Texas, USA
- Department of Molecular Physiology and Biophysics
| | - Qing Li
- Childhood Complex Disease Genomics Section, National Human Genome Research Institute, NIH, Bethesda, USA
| | - Hsiao-Tuan Chao
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas, USA
- Division of Neurology and Developmental Neuroscience, Department of Pediatrics; and
- Department of Neuroscience, Baylor College of Medicine, Houston, Texas, USA
- Cain Pediatric Neurology Research Foundation Laboratories, Jan and Dan Duncan Neurological Research Institute, Texas Children's Hospital and Baylor College of Medicine, Houston, Texas, USA
- McNair Medical Institute, The Robert and Janice McNair Foundation, Houston, Texas, USA
| | - Ana M Zaske
- Department of Pediatrics, McGovern Medical School, The University of Texas Health Science Center at Houston, Houston, Texas, USA
| | - James R Lupski
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas, USA
- Texas Children's Hospital, Houston, Texas, USA
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, Texas, USA
| | - Dianna M Milewicz
- Department of Internal Medicine, McGovern Medical School, The University of Texas Health Science Center at Houston, Houston, Texas, USA
| | - Sanjay Shete
- The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Jennifer E Posey
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas, USA
- McNair Medical Institute, The Robert and Janice McNair Foundation, Houston, Texas, USA
| | - Neil A Hanchard
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas, USA
- Childhood Complex Disease Genomics Section, National Human Genome Research Institute, NIH, Bethesda, USA
| |
Collapse
|
2
|
Lemire G, Sanchis-Juan A, Russell K, Baxter S, Chao KR, Singer-Berk M, Groopman E, Wong I, England E, Goodrich J, Pais L, Austin-Tse C, DiTroia S, O'Heir E, Ganesh VS, Wojcik MH, Evangelista E, Snow H, Osei-Owusu I, Fu J, Singh M, Mostovoy Y, Huang S, Garimella K, Kirkham SL, Neil JE, Shao DD, Walsh CA, Argilli E, Le C, Sherr EH, Gleeson JG, Shril S, Schneider R, Hildebrandt F, Sankaran VG, Madden JA, Genetti CA, Beggs AH, Agrawal PB, Bujakowska KM, Place E, Pierce EA, Donkervoort S, Bönnemann CG, Gallacher L, Stark Z, Tan TY, White SM, Töpf A, Straub V, Fleming MD, Pollak MR, Õunap K, Pajusalu S, Donald KA, Bruwer Z, Ravenscroft G, Laing NG, MacArthur DG, Rehm HL, Talkowski ME, Brand H, O'Donnell-Luria A. Exome copy number variant detection, analysis, and classification in a large cohort of families with undiagnosed rare genetic disease. Am J Hum Genet 2024; 111:863-876. [PMID: 38565148 PMCID: PMC11080278 DOI: 10.1016/j.ajhg.2024.03.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2023] [Revised: 03/09/2024] [Accepted: 03/11/2024] [Indexed: 04/04/2024] Open
Abstract
Copy number variants (CNVs) are significant contributors to the pathogenicity of rare genetic diseases and, with new innovative methods, can now reliably be identified from exome sequencing. Challenges still remain in accurate classification of CNV pathogenicity. CNV calling using GATK-gCNV was performed on exomes from a cohort of 6,633 families (15,759 individuals) with heterogeneous phenotypes and variable prior genetic testing collected at the Broad Institute Center for Mendelian Genomics of the Genomics Research to Elucidate the Genetics of Rare Diseases consortium and analyzed using the seqr platform. The addition of CNV detection to exome analysis identified causal CNVs for 171 families (2.6%). The estimated sizes of CNVs ranged from 293 bp to 80 Mb. The causal CNVs consisted of 140 deletions, 15 duplications, 3 suspected complex structural variants (SVs), 3 insertions, and 10 complex SVs, the latter two groups being identified by orthogonal confirmation methods. To classify CNV variant pathogenicity, we used the 2020 American College of Medical Genetics and Genomics/ClinGen CNV interpretation standards and developed additional criteria to evaluate allelic and functional data as well as variants on the X chromosome to further advance the framework. We interpreted 151 CNVs as likely pathogenic/pathogenic and 20 CNVs as high-interest variants of uncertain significance. Calling CNVs from existing exome data increases the diagnostic yield for individuals undiagnosed after standard testing approaches, providing a higher-resolution alternative to arrays at a fraction of the cost of genome sequencing. Our improvements to the classification approach advances the systematic framework to assess the pathogenicity of CNVs.
Collapse
Affiliation(s)
- Gabrielle Lemire
- Broad Institute Center for Mendelian Genomics, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Division of Genetics and Genomics, Boston Children's Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA; Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA.
| | - Alba Sanchis-Juan
- Broad Institute Center for Mendelian Genomics, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Harvard Medical School, Boston, MA, USA; Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Kathryn Russell
- Broad Institute Center for Mendelian Genomics, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Samantha Baxter
- Broad Institute Center for Mendelian Genomics, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Katherine R Chao
- Broad Institute Center for Mendelian Genomics, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Moriel Singer-Berk
- Broad Institute Center for Mendelian Genomics, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Emily Groopman
- Broad Institute Center for Mendelian Genomics, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Division of Genetics and Genomics, Boston Children's Hospital, Boston, MA, USA
| | - Isaac Wong
- Broad Institute Center for Mendelian Genomics, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Eleina England
- Broad Institute Center for Mendelian Genomics, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Division of Genetics and Genomics, Boston Children's Hospital, Boston, MA, USA
| | - Julia Goodrich
- Broad Institute Center for Mendelian Genomics, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Lynn Pais
- Broad Institute Center for Mendelian Genomics, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Division of Genetics and Genomics, Boston Children's Hospital, Boston, MA, USA; Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Christina Austin-Tse
- Broad Institute Center for Mendelian Genomics, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Stephanie DiTroia
- Broad Institute Center for Mendelian Genomics, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Division of Genetics and Genomics, Boston Children's Hospital, Boston, MA, USA; Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Emily O'Heir
- Broad Institute Center for Mendelian Genomics, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Division of Genetics and Genomics, Boston Children's Hospital, Boston, MA, USA; Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Vijay S Ganesh
- Broad Institute Center for Mendelian Genomics, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Division of Genetics and Genomics, Boston Children's Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA; Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA; Department of Neurology, Brigham and Women's Hospital, Boston, MA, USA
| | - Monica H Wojcik
- Broad Institute Center for Mendelian Genomics, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Division of Genetics and Genomics, Boston Children's Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA; The Manton Center for Orphan Disease Research, Boston Children's Hospital, Boston, MA, USA
| | - Emily Evangelista
- Broad Institute Center for Mendelian Genomics, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Hana Snow
- Broad Institute Center for Mendelian Genomics, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Ikeoluwa Osei-Owusu
- Broad Institute Center for Mendelian Genomics, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Jack Fu
- Broad Institute Center for Mendelian Genomics, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Harvard Medical School, Boston, MA, USA; Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Mugdha Singh
- Broad Institute Center for Mendelian Genomics, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Division of Genetics and Genomics, Boston Children's Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA; Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Yulia Mostovoy
- Broad Institute Center for Mendelian Genomics, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Steve Huang
- Broad Institute Center for Mendelian Genomics, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Kiran Garimella
- Broad Institute Center for Mendelian Genomics, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Samantha L Kirkham
- Division of Genetics and Genomics, Boston Children's Hospital, Boston, MA, USA
| | - Jennifer E Neil
- Division of Genetics and Genomics, Boston Children's Hospital, Boston, MA, USA; Howard Hughes Medical Institute, Boston Children's Hospital, Boston, MA, USA
| | - Diane D Shao
- Division of Genetics and Genomics, Boston Children's Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA; Department of Neurology, Boston Children's Hospital, Boston, MA, USA
| | - Christopher A Walsh
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Division of Genetics and Genomics, Boston Children's Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA; Howard Hughes Medical Institute, Boston Children's Hospital, Boston, MA, USA
| | - Emanuela Argilli
- Department of Neurology, University of California, San Francisco, San Francisco, CA, USA; Institute of Human Genetics and Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Carolyn Le
- Department of Neurology, University of California, San Francisco, San Francisco, CA, USA; Institute of Human Genetics and Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Elliott H Sherr
- Department of Neurology, University of California, San Francisco, San Francisco, CA, USA; Institute of Human Genetics and Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Joseph G Gleeson
- Department of Neurosciences, University of California, San Diego, La Jolla, CA, USA; Rady Children's Institute for Genomic Medicine, San Diego, CA, USA
| | - Shirlee Shril
- Harvard Medical School, Boston, MA, USA; Department of Pediatrics, Boston Children's Hospital, Boston, MA, USA
| | - Ronen Schneider
- Harvard Medical School, Boston, MA, USA; Department of Pediatrics, Boston Children's Hospital, Boston, MA, USA
| | - Friedhelm Hildebrandt
- Harvard Medical School, Boston, MA, USA; Department of Pediatrics, Boston Children's Hospital, Boston, MA, USA
| | - Vijay G Sankaran
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Harvard Medical School, Boston, MA, USA; Division of Hematology/Oncology, Boston Children's Hospital and Department of Pediatric Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Jill A Madden
- Division of Genetics and Genomics, Boston Children's Hospital, Boston, MA, USA; The Manton Center for Orphan Disease Research, Boston Children's Hospital, Boston, MA, USA
| | - Casie A Genetti
- Division of Genetics and Genomics, Boston Children's Hospital, Boston, MA, USA; The Manton Center for Orphan Disease Research, Boston Children's Hospital, Boston, MA, USA
| | - Alan H Beggs
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Division of Genetics and Genomics, Boston Children's Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA; The Manton Center for Orphan Disease Research, Boston Children's Hospital, Boston, MA, USA
| | - Pankaj B Agrawal
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Division of Genetics and Genomics, Boston Children's Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA; The Manton Center for Orphan Disease Research, Boston Children's Hospital, Boston, MA, USA
| | - Kinga M Bujakowska
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Harvard Medical School, Boston, MA, USA; Ocular Genomics Institute, Department of Ophthalmology, Massachusetts Eye and Ear, Boston, MA, USA
| | - Emily Place
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Harvard Medical School, Boston, MA, USA; Ocular Genomics Institute, Department of Ophthalmology, Massachusetts Eye and Ear, Boston, MA, USA
| | - Eric A Pierce
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Harvard Medical School, Boston, MA, USA; Ocular Genomics Institute, Department of Ophthalmology, Massachusetts Eye and Ear, Boston, MA, USA
| | - Sandra Donkervoort
- Neuromuscular and Neurogenetic Disorders of Childhood Section, Neurogenetics Branch, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Carsten G Bönnemann
- Neuromuscular and Neurogenetic Disorders of Childhood Section, Neurogenetics Branch, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Lyndon Gallacher
- Department of Paediatrics, University of Melbourne, Parkville, VIC, Australia; Victorian Clinical Genetics Services, Murdoch Children's Research Institute, Parkville, VIC, Australia
| | - Zornitza Stark
- Department of Paediatrics, University of Melbourne, Parkville, VIC, Australia; Victorian Clinical Genetics Services, Murdoch Children's Research Institute, Parkville, VIC, Australia
| | - Tiong Yang Tan
- Department of Paediatrics, University of Melbourne, Parkville, VIC, Australia; Victorian Clinical Genetics Services, Murdoch Children's Research Institute, Parkville, VIC, Australia
| | - Susan M White
- Department of Paediatrics, University of Melbourne, Parkville, VIC, Australia; Victorian Clinical Genetics Services, Murdoch Children's Research Institute, Parkville, VIC, Australia
| | - Ana Töpf
- John Walton Muscular Dystrophy Research Centre, Newcastle University and Newcastle Hospitals NHS Foundation Trust, Newcastle upon Tyne, UK
| | - Volker Straub
- John Walton Muscular Dystrophy Research Centre, Newcastle University and Newcastle Hospitals NHS Foundation Trust, Newcastle upon Tyne, UK
| | - Mark D Fleming
- Harvard Medical School, Boston, MA, USA; Department of Pathology, Boston Children's Hospital, Boston, MA, USA
| | - Martin R Pollak
- Harvard Medical School, Boston, MA, USA; Division of Nephrology, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Katrin Õunap
- Department of Clinical Genetics, Genetics and Personalized Medicine Clinic, Tartu University Hospital, Tartu, Estonia; Department of Genetics and Personalized Medicine, Institute of Clinical Medicine, Faculty of Medicine, University of Tartu, Tartu, Estonia
| | - Sander Pajusalu
- Department of Clinical Genetics, Genetics and Personalized Medicine Clinic, Tartu University Hospital, Tartu, Estonia; Department of Genetics and Personalized Medicine, Institute of Clinical Medicine, Faculty of Medicine, University of Tartu, Tartu, Estonia
| | - Kirsten A Donald
- Department of Paediatrics and Child Health, Red Cross War Memorial Children's Hospital, Cape Town, South Africa; Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Zandre Bruwer
- Department of Paediatrics and Child Health, Red Cross War Memorial Children's Hospital, Cape Town, South Africa; Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Gianina Ravenscroft
- University of Western Australia Centre for Medical Research, Harry Perkins Institute of Medical Research, QEII Medical Centre, Nedlands, WA, Australia
| | - Nigel G Laing
- University of Western Australia Centre for Medical Research, Harry Perkins Institute of Medical Research, QEII Medical Centre, Nedlands, WA, Australia
| | - Daniel G MacArthur
- Broad Institute Center for Mendelian Genomics, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Centre for Population Genomics, Garvan Institute of Medical Research and UNSW, Sydney, NSW, Australia; Centre for Population Genomics, Murdoch Children's Research Institute, Melbourne, VIC, Australia
| | - Heidi L Rehm
- Broad Institute Center for Mendelian Genomics, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Harvard Medical School, Boston, MA, USA; Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Michael E Talkowski
- Broad Institute Center for Mendelian Genomics, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Harvard Medical School, Boston, MA, USA; Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Harrison Brand
- Broad Institute Center for Mendelian Genomics, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Harvard Medical School, Boston, MA, USA; Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Anne O'Donnell-Luria
- Broad Institute Center for Mendelian Genomics, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Division of Genetics and Genomics, Boston Children's Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA; Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA; The Manton Center for Orphan Disease Research, Boston Children's Hospital, Boston, MA, USA.
| |
Collapse
|
3
|
Abou-Karam R, Cheng F, Gady S, Fahed AC. The Role of Genetics in Advancing Cardiometabolic Drug Development. Curr Atheroscler Rep 2024; 26:153-162. [PMID: 38451435 DOI: 10.1007/s11883-024-01195-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/22/2024] [Indexed: 03/08/2024]
Abstract
PURPOSE OF REVIEW The objective of this review is to explore the role of genetics in cardiometabolic drug development. The declining costs of sequencing and the availability of large-scale genomic data have deepened our understanding of cardiometabolic diseases, revolutionizing drug discovery and development methodologies. We highlight four key areas in which genetics is empowering drug development for cardiometabolic disease: (1) identifying drug candidates, (2) anticipating drug target failures, (3) silencing and editing genes, and (4) enriching clinical trials. RECENT FINDINGS Identifying novel drug targets through genetic discovery studies and the use of genetic variants as indicators of potential drug efficacy and safety have become critical components of cardiometabolic drug discovery. We highlight the successes of genetically-informed therapeutic strategies, such as PCSK9 and ANGPTL3 inhibitors in lipid lowering and the emerging role of polygenic risk scores in improving the efficiency of clinical trials. Additionally, we explore the potential of gene silencing and editing technologies, such as antisense oligonucleotides and small interfering RNA, showcasing their promise in addressing diseases refractory to conventional treatments. In this review, we highlight four use cases that demonstrate the vital role of genetics in cardiometabolic drug development: (1) identifying drug candidates, (2) anticipating drug target failures, (3) silencing and editing genes, and (4) enriching clinical trials. Through these advances, genetics has paved the way to increased efficiency of drug development as well as the discovery of more personalized and effective treatments for cardiometabolic disease.
Collapse
Affiliation(s)
- Roukoz Abou-Karam
- Cardiovascular Research Center, Department of Medicine, Massachusetts General Hospital, Harvard Medical School, 185 Cambridge Street|CPZN 3.128, Boston, MA, 02114, USA
- Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Fangzhou Cheng
- Cardiovascular Research Center, Department of Medicine, Massachusetts General Hospital, Harvard Medical School, 185 Cambridge Street|CPZN 3.128, Boston, MA, 02114, USA
- Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Shoshana Gady
- Cardiovascular Research Center, Department of Medicine, Massachusetts General Hospital, Harvard Medical School, 185 Cambridge Street|CPZN 3.128, Boston, MA, 02114, USA
- Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Akl C Fahed
- Cardiovascular Research Center, Department of Medicine, Massachusetts General Hospital, Harvard Medical School, 185 Cambridge Street|CPZN 3.128, Boston, MA, 02114, USA.
- Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
| |
Collapse
|
4
|
Mahmoud M, Harting J, Corbitt H, Chen X, Jhangiani SN, Doddapaneni H, Meng Q, Han T, Lambert C, Zhang S, Baybayan P, Henno G, Shen H, Hu J, Han Y, Riegler C, Metcalf G, Henno G, Chinn IK, Eberle MA, Kingan S, Farinholt T, Carvalho CM, Gibbs RA, Kronenberg Z, Muzny D, Sedlazeck FJ. Closing the gap: Solving complex medically relevant genes at scale. medRxiv 2024:2024.03.14.24304179. [PMID: 38562723 PMCID: PMC10984040 DOI: 10.1101/2024.03.14.24304179] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Abstract
Comprehending the mechanism behind human diseases with an established heritable component represents the forefront of personalized medicine. Nevertheless, numerous medically important genes are inaccurately represented in short-read sequencing data analysis due to their complexity and repetitiveness or the so-called 'dark regions' of the human genome. The advent of PacBio as a long-read platform has provided new insights, yet HiFi whole-genome sequencing (WGS) cost remains frequently prohibitive. We introduce a targeted sequencing and analysis framework, Twist Alliance Dark Genes Panel (TADGP), designed to offer phased variants across 389 medically important yet complex autosomal genes. We highlight TADGP accuracy across eleven control samples and compare it to WGS. This demonstrates that TADGP achieves variant calling accuracy comparable to HiFi-WGS data, but at a fraction of the cost. Thus, enabling scalability and broad applicability for studying rare diseases or complementing previously sequenced samples to gain insights into these complex genes. TADGP revealed several candidate variants across all cases and provided insight into LPA diversity when tested on samples from rare disease and cardiovascular disease cohorts. In both cohorts, we identified novel variants affecting individual disease-associated genes (e.g., IKZF1, KCNE1). Nevertheless, the annotation of the variants across these 389 medically important genes remains challenging due to their underrepresentation in ClinVar and gnomAD. Consequently, we also offer an annotation resource to enhance the evaluation and prioritization of these variants. Overall, we can demonstrate that TADGP offers a cost-efficient and scalable approach to routinely assess the dark regions of the human genome with clinical relevance.
Collapse
Affiliation(s)
- Medhat Mahmoud
- Baylor College of Medicine, Human Genome Sequencing Center, Houston, Texas, USA
| | - John Harting
- Pacific Biosciences, Menlo Park, California, USA
| | | | - Xiao Chen
- Pacific Biosciences, Menlo Park, California, USA
| | | | - Harsha Doddapaneni
- Baylor College of Medicine, Human Genome Sequencing Center, Houston, Texas, USA
| | - Qingchang Meng
- Baylor College of Medicine, Human Genome Sequencing Center, Houston, Texas, USA
| | - Tina Han
- Twist Bioscience, South San Francisco, USA
| | | | - Siyuan Zhang
- Pacific Biosciences, Menlo Park, California, USA
| | | | - Geoff Henno
- Pacific Biosciences, Menlo Park, California, USA
| | - Hua Shen
- Baylor College of Medicine, Human Genome Sequencing Center, Houston, Texas, USA
| | - Jianhong Hu
- Baylor College of Medicine, Human Genome Sequencing Center, Houston, Texas, USA
| | - Yi Han
- Baylor College of Medicine, Human Genome Sequencing Center, Houston, Texas, USA
| | | | - Ginger Metcalf
- Baylor College of Medicine, Human Genome Sequencing Center, Houston, Texas, USA
| | - Geoff Henno
- Pacific Biosciences, Menlo Park, California, USA
| | - Ivan K. Chinn
- Department of Pediatrics, Section of Immunology Allergy and Rheumatology, Center for Human Immunobiology, Texas Children’s Hospital and Baylor College of Medicine, Houston, Texas, USA
| | | | - Sarah Kingan
- Pacific Biosciences, Menlo Park, California, USA
| | | | | | - Richard A. Gibbs
- Baylor College of Medicine, Human Genome Sequencing Center, Houston, Texas, USA
| | | | - Donna Muzny
- Baylor College of Medicine, Human Genome Sequencing Center, Houston, Texas, USA
| | - Fritz J. Sedlazeck
- Baylor College of Medicine, Human Genome Sequencing Center, Houston, Texas, USA
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas, USA
- Department of Computer Science, Rice University, Houston, Texas, USA
| |
Collapse
|
5
|
Maxwell E, Moore R, Niendorf K, Field T. Further defining the roles and impact of genetic counselors in the biotechnology and pharmaceutical industry. J Genet Couns 2024. [PMID: 38477026 DOI: 10.1002/jgc4.1861] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2023] [Revised: 11/15/2023] [Accepted: 12/10/2023] [Indexed: 03/14/2024]
Abstract
As personalized medicine has gained traction, drug development models in the biotechnology and pharmaceutical industry (BPI) have increasingly sought to address medical conditions with a genetic component, creating an opportunity for genetic counselors (GCs) to fill new roles and utilize their unique training to contribute to drug development. Despite the potential for GCs in BPI, literature around the role of GCs in this industry has been limited. Our mixed methods study aimed to assess how the roles of GCs in BPI have evolved since 2016, investigate the value of and opportunity for GCs in this industry, and further characterize their motivation and job satisfaction. Participants were recruited via social media advertising, snowball sampling, and email listservs from the National Society of Genetic Counseling (NSGC), the Canadian Association of Genetic Counselors (CAGC), and the American Board of Genetic Counseling (ABGC). Survey (n = 20) and interview (n = 6) data indicates many aspects of GC roles in BPI are consistent with the 2016 study. However, there is evidence of roles becoming more varied and with increasing recognition of the value of GCs, opportunities for involvement in BPI are growing. Furthermore, combined study data found that GCs are motivated by the flexibility of BPI roles as well as the opportunity to contribute to rare disease treatment development and that they are overall satisfied with most aspects of their jobs. Interview data also found that genetic counseling training has the potential to improve clinical trial design and outcomes by making drug development more patient-centric. Finally, combined study data found that while GCs continue to utilize Accreditation Council of Genetic Counseling (ACGC) practice-based competencies (PBCs), business-related training may benefit GCs seeking to enter BPI. Together, these findings are critical for informing genetic counseling training programs, employers within BPI, and GCs interested in entering these positions.
Collapse
Affiliation(s)
- Emily Maxwell
- Genetic Counseling Program, MGH Institute of Health Professions, Boston, Massachusetts, USA
- Fred Hutchinson Cancer Institute, Seattle, Washington, USA
| | - Rebekah Moore
- AstraZeneca Pharmaceuticals, One MedImmune Way, Gaithersburg, Maryland, USA
| | - Kristin Niendorf
- Genetic Counseling Program, Indiana State University, Terre Haute, Indiana, USA
| | - Tessa Field
- Spark Therapeutics, Philadelphia, Pennsylvania, USA
| |
Collapse
|
6
|
Yamamoto S, Kanca O, Wangler MF, Bellen HJ. Integrating non-mammalian model organisms in the diagnosis of rare genetic diseases in humans. Nat Rev Genet 2024; 25:46-60. [PMID: 37491400 DOI: 10.1038/s41576-023-00633-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/26/2023] [Indexed: 07/27/2023]
Abstract
Next-generation sequencing technology has rapidly accelerated the discovery of genetic variants of interest in individuals with rare diseases. However, showing that these variants are causative of the disease in question is complex and may require functional studies. Use of non-mammalian model organisms - mainly fruitflies (Drosophila melanogaster), nematode worms (Caenorhabditis elegans) and zebrafish (Danio rerio) - enables the rapid and cost-effective assessment of the effects of gene variants, which can then be validated in mammalian model organisms such as mice and in human cells. By probing mechanisms of gene action and identifying interacting genes and proteins in vivo, recent studies in these non-mammalian model organisms have facilitated the diagnosis of numerous genetic diseases and have enabled the screening and identification of therapeutic options for patients. Studies in non-mammalian model organisms have also shown that the biological processes underlying rare diseases can provide insight into more common mechanisms of disease and the biological functions of genes. Here, we discuss the opportunities afforded by non-mammalian model organisms, focusing on flies, worms and fish, and provide examples of their use in the diagnosis of rare genetic diseases.
Collapse
Affiliation(s)
- Shinya Yamamoto
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
- Jan and Dan Duncan Neurological Research Institute, Texas Children's Hospital, Houston, TX, USA
- Department of Neuroscience, Baylor College of Medicine, Houston, TX, USA
| | - Oguz Kanca
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
- Jan and Dan Duncan Neurological Research Institute, Texas Children's Hospital, Houston, TX, USA
| | - Michael F Wangler
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA.
- Jan and Dan Duncan Neurological Research Institute, Texas Children's Hospital, Houston, TX, USA.
| | - Hugo J Bellen
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA.
- Jan and Dan Duncan Neurological Research Institute, Texas Children's Hospital, Houston, TX, USA.
- Department of Neuroscience, Baylor College of Medicine, Houston, TX, USA.
| |
Collapse
|
7
|
Sullivan JA, Spillmann RC, Schoch K, Walley N, Alkelai A, Stong N, Shea PR, Petrovski S, Jobanputra V, McConkie-Rosell A, Shashi V. The best of both worlds: Blending cutting-edge research with clinical processes for a productive exome clinic. Clin Genet 2024; 105:62-71. [PMID: 37853563 DOI: 10.1111/cge.14437] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2023] [Revised: 09/29/2023] [Accepted: 10/04/2023] [Indexed: 10/20/2023]
Abstract
Genomic medicine has been transformed by next-generation sequencing (NGS), inclusive of exome sequencing (ES) and genome sequencing (GS). Currently, ES is offered widely in clinical settings, with a less prevalent alternative model consisting of hybrid programs that incorporate research ES along with clinical patient workflows. We were among the earliest to implement a hybrid ES clinic, have provided diagnoses to 45% of probands, and have identified several novel candidate genes. Our program is enabled by a cost-effective investment by the health system and is unique in encompassing all the processes that have been variably included in other hybrid/clinical programs. These include careful patient selection, utilization of a phenotype-agnostic bioinformatics pipeline followed by manual curation of variants and phenotype integration by clinicians, close collaborations between the clinicians and the bioinformatician, pursuit of interesting variants, communication of results to patients in categories that are predicated upon the certainty of a diagnosis, and tracking changes in results over time and the underlying mechanisms for such changes. Due to its effectiveness, scalability to GS and its resource efficiency, specific elements of our paradigm can be incorporated into existing clinical settings, or the entire hybrid model can be implemented within health systems that have genomic medicine programs, to provide NGS in a scientifically rigorous, yet pragmatic setting.
Collapse
Affiliation(s)
- Jennifer A Sullivan
- Department of Pediatrics, Division of Medical Genetics, Duke University, Durham, North Carolina, USA
| | - Rebecca C Spillmann
- Department of Pediatrics, Division of Medical Genetics, Duke University, Durham, North Carolina, USA
| | - Kelly Schoch
- Department of Pediatrics, Division of Medical Genetics, Duke University, Durham, North Carolina, USA
| | - Nicole Walley
- Department of Pediatrics, Division of Medical Genetics, Duke University, Durham, North Carolina, USA
| | - Anna Alkelai
- Institute for Genomic Medicine, Columbia University Medical Center, New York, New York, USA
- Regeneron Genetics Center, Regeneron Pharmaceuticals, Tarrytown, New York, USA
| | - Nicholas Stong
- Institute for Genomic Medicine, Columbia University Medical Center, New York, New York, USA
- Predictive Sciences, Bristol Myers Squibb, Summit, New Jersey, USA
| | - Patrick R Shea
- Institute for Genomic Medicine, Columbia University Medical Center, New York, New York, USA
- Genomics and Bioinformatics Analysis Resource, Columbia University, New York, New York, USA
| | - Slavè Petrovski
- Institute for Genomic Medicine, Columbia University Medical Center, New York, New York, USA
- Department of Medicine, University of Melbourne, Austin Health, Melbourne, Victoria, Australia
| | - Vaidehi Jobanputra
- Department of Pathology and Cell Biology, Columbia University Irving Medical Center, New York, New York, USA
| | - Allyn McConkie-Rosell
- Department of Pediatrics, Division of Medical Genetics, Duke University, Durham, North Carolina, USA
| | - Vandana Shashi
- Department of Pediatrics, Division of Medical Genetics, Duke University, Durham, North Carolina, USA
| |
Collapse
|
8
|
Emani PS, Geradi MN, Gürsoy G, Grasty MR, Miranker A, Gerstein MB. Assessing and mitigating privacy risks of sparse, noisy genotypes by local alignment to haplotype databases. Genome Res 2023; 33:gr.278322.123. [PMID: 38097386 PMCID: PMC10760520 DOI: 10.1101/gr.278322.123] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2023] [Accepted: 11/18/2023] [Indexed: 01/04/2024]
Abstract
Single nucleotide polymorphisms (SNPs) from omics data create a reidentification risk for individuals and their relatives. Although the ability of thousands of SNPs (especially rare ones) to identify individuals has been repeatedly shown, the availability of small sets of noisy genotypes, from environmental DNA samples or functional genomics data, motivated us to quantify their informativeness. We present a computational tool suite, termed Privacy Leakage by Inference across Genotypic HMM Trajectories (PLIGHT), using population-genetics-based hidden Markov models (HMMs) of recombination and mutation to find piecewise alignment of small, noisy SNP sets to reference haplotype databases. We explore cases in which query individuals are either known to be in the database, or not, and consider several genotype queries, including those from environmental sample swabs from known individuals and from simulated "mosaics" (two-individual composites). Using PLIGHT on a database with ∼5000 haplotypes, we find for common, noise-free SNPs that only ten are sufficient to identify individuals, ∼20 can identify both components in two-individual mosaics, and 20-30 can identify first-order relatives. Using noisy environmental-sample-derived SNPs, PLIGHT identifies individuals in a database using ∼30 SNPs. Even when the individuals are not in the database, local genotype matches allow for some phenotypic information leakage based on coarse-grained SNP imputation. Finally, by quantifying privacy leakage from sparse SNP sets, PLIGHT helps determine the value of selectively sanitizing released SNPs without explicit assumptions about population membership or allele frequency. To make this practical, we provide a sanitization tool to remove the most identifying SNPs from genomic data.
Collapse
Affiliation(s)
- Prashant S Emani
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, Connecticut 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, Connecticut 06520, USA
| | - Maya N Geradi
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, Connecticut 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, Connecticut 06520, USA
| | - Gamze Gürsoy
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, Connecticut 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, Connecticut 06520, USA
| | - Monica R Grasty
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, Connecticut 06520, USA
| | - Andrew Miranker
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, Connecticut 06520, USA
| | - Mark B Gerstein
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, Connecticut 06520, USA;
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, Connecticut 06520, USA
- Department of Computer Science, Yale University, New Haven, Connecticut 06520, USA
- Department of Statistics and Data Science, Yale University, New Haven, Connecticut 06520, USA
| |
Collapse
|
9
|
Opoku P, Osei-Tutu A, Oti-Boadi M. Psychosocial impacts of caring for a child with a genetic disorder in Accra, Ghana. J Community Genet 2023; 14:565-574. [PMID: 37581869 PMCID: PMC10725383 DOI: 10.1007/s12687-023-00662-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2022] [Accepted: 08/08/2023] [Indexed: 08/16/2023] Open
Abstract
Caregivers caring for a child with a genetic condition may experience psychosocial distress, which may be compounded by the context in which the caring takes place. Few studies have examined psychosocial distress and support among caregivers caring for a child with a genetic disorder in low-middle-income countries such as Ghana. The purpose of the current study was to investigate the psychosocial impacts of caring for a child with a genetic disorder in an urban setting in Ghana's capital, Accra. We conducted individual interviews among 17 caregivers who were taking care of children with various genetic disorders including, albinism, Edward's syndrome, osteogenesis imperfecta, sickle cell disease, and spondyloepiphyseal dysplasia congenita. Thematic analysis of the data revealed three main themes on the psychosocial impacts, including: (1) self-blame, guilt, and shame; (2) sleep and mood disturbances; and (3) discrimination and stigmatization. We observed three themes about support: (1) psychological support; (2) family and community support; and (3) institutional support. Participants reported limited support from professionals such as psychologists. Discussion focuses on the supportive care needs of caregivers and implications for genetic counselling awareness, advocacy, and training.
Collapse
Affiliation(s)
- Paul Opoku
- Department of Psychology, University of Ghana, Accra, Ghana
| | | | | |
Collapse
|
10
|
Alsentzer E, Finlayson SG, Li MM, Kobren SN, Kohane IS. Simulation of undiagnosed patients with novel genetic conditions. Nat Commun 2023; 14:6403. [PMID: 37828001 PMCID: PMC10570269 DOI: 10.1038/s41467-023-41980-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2022] [Accepted: 09/26/2023] [Indexed: 10/14/2023] Open
Abstract
Rare Mendelian disorders pose a major diagnostic challenge and collectively affect 300-400 million patients worldwide. Many automated tools aim to uncover causal genes in patients with suspected genetic disorders, but evaluation of these tools is limited due to the lack of comprehensive benchmark datasets that include previously unpublished conditions. Here, we present a computational pipeline that simulates realistic clinical datasets to address this deficit. Our framework jointly simulates complex phenotypes and challenging candidate genes and produces patients with novel genetic conditions. We demonstrate the similarity of our simulated patients to real patients from the Undiagnosed Diseases Network and evaluate common gene prioritization methods on the simulated cohort. These prioritization methods recover known gene-disease associations but perform poorly on diagnosing patients with novel genetic disorders. Our publicly-available dataset and codebase can be utilized by medical genetics researchers to evaluate, compare, and improve tools that aid in the diagnostic process.
Collapse
Grants
- U01 HG007690 NHGRI NIH HHS
- U54 NS108251 NINDS NIH HHS
- U01 HG010219 NHGRI NIH HHS
- U01 HG007672 NHGRI NIH HHS
- U01 HG010233 NHGRI NIH HHS
- U01 HG010230 NHGRI NIH HHS
- U01 HG007943 NHGRI NIH HHS
- U01 HG010217 NHGRI NIH HHS
- U01 HG007942 NHGRI NIH HHS
- U01 HG010215 NHGRI NIH HHS
- U01 HG007708 NHGRI NIH HHS
- T32 HG002295 NHGRI NIH HHS
- T32 GM007753 NIGMS NIH HHS
- U01 HG007674 NHGRI NIH HHS
- U01 TR001395 NCATS NIH HHS
- U01 HG007709 NHGRI NIH HHS
- U54 NS093793 NINDS NIH HHS
- U01 HG007530 NHGRI NIH HHS
- U01 TR002471 NCATS NIH HHS
- U01 HG007703 NHGRI NIH HHS
- UDN research reported in this manuscript was supported by the NIH Common Fund, through the Office of Strategic Coordination/Office of the NIH Director under Award Number(s) U01HG007709, U01HG010219, U01HG010230, U01HG010217, U01HG010233, U01HG010215, U01HG007672, U01HG007690, U01HG007708, U01HG007703, U01HG007674, U01HG007530, U01HG007942, U01HG007943, U01TR001395, U01TR002471, U54NS108251, and U54NS093793.
- E.A. is supported by a Microsoft Research PhD Fellowship.
- S.F. is supported by award Number T32GM007753 from the National Institute of General Medical Sciences.
- M.L. is supported by T32HG002295 from the National Human Genome Research Institute and a National Science Foundation Graduate Research Fellowship.
Collapse
Affiliation(s)
- Emily Alsentzer
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, 02115, USA
- Program in Health Sciences and Technology, MIT, Cambridge, MA, 02139, USA
| | - Samuel G Finlayson
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, 02115, USA
- Program in Health Sciences and Technology, MIT, Cambridge, MA, 02139, USA
- Department of Pediatrics, Division of Genetic Medicine, Seattle Children's Hospital, Seattle, WA, 98105, USA
- Division of Medical Genetics, Department of Medicine, University of Washington, Seattle, WA, 98105, USA
| | - Michelle M Li
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, 02115, USA
- Bioinformatics and Integrative Genomics, Harvard Medical School, Boston, MA, 02115, USA
| | - Shilpa N Kobren
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, 02115, USA.
| | - Isaac S Kohane
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, 02115, USA.
| |
Collapse
|
11
|
Lemire G, Sanchis-Juan A, Russell K, Baxter S, Chao KR, Singer-Berk M, Groopman E, Wong I, England E, Goodrich J, Pais L, Austin-Tse C, DiTroia S, O’Heir E, Ganesh VS, Wojcik MH, Evangelista E, Snow H, Osei-Owusu I, Fu J, Singh M, Mostovoy Y, Huang S, Garimella K, Kirkham SL, Neil JE, Shao DD, Walsh CA, Argili E, Le C, Sherr EH, Gleeson J, Shril S, Schneider R, Hildebrandt F, Sankaran VG, Madden JA, Genetti CA, Beggs AH, Agrawal PB, Bujakowska KM, Place E, Pierce EA, Donkervoort S, Bönnemann CG, Gallacher L, Stark Z, Tan T, White SM, Töpf A, Straub V, Fleming MD, Pollak MR, Õunap K, Pajusalu S, Donald KA, Bruwer Z, Ravenscroft G, Laing NG, MacArthur DG, Rehm HL, Talkowski ME, Brand H, O’Donnell-Luria A. Exome copy number variant detection, analysis and classification in a large cohort of families with undiagnosed rare genetic disease. medRxiv 2023:2023.10.05.23296595. [PMID: 37873196 PMCID: PMC10593084 DOI: 10.1101/2023.10.05.23296595] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/25/2023]
Abstract
Copy number variants (CNVs) are significant contributors to the pathogenicity of rare genetic diseases and with new innovative methods can now reliably be identified from exome sequencing. Challenges still remain in accurate classification of CNV pathogenicity. CNV calling using GATK-gCNV was performed on exomes from a cohort of 6,633 families (15,759 individuals) with heterogeneous phenotypes and variable prior genetic testing collected at the Broad Institute Center for Mendelian Genomics of the GREGoR consortium. Each family's CNV data was analyzed using the seqr platform and candidate CNVs classified using the 2020 ACMG/ClinGen CNV interpretation standards. We developed additional evidence criteria to address situations not covered by the current standards. The addition of CNV calling to exome analysis identified causal CNVs for 173 families (2.6%). The estimated sizes of CNVs ranged from 293 bp to 80 Mb with estimates that 44% would not have been detected by standard chromosomal microarrays. The causal CNVs consisted of 141 deletions, 15 duplications, 4 suspected complex structural variants (SVs), 3 insertions and 10 complex SVs, the latter two groups being identified by orthogonal validation methods. We interpreted 153 CNVs as likely pathogenic/pathogenic and 20 CNVs as high interest variants of uncertain significance. Calling CNVs from existing exome data increases the diagnostic yield for individuals undiagnosed after standard testing approaches, providing a higher resolution alternative to arrays at a fraction of the cost of genome sequencing. Our improvements to the classification approach advances the systematic framework to assess the pathogenicity of CNVs.
Collapse
Affiliation(s)
- Gabrielle Lemire
- Broad Institute Center for Mendelian Genomics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Genetics and Genomics, Boston Children’s Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- These authors contributed equally
| | - Alba Sanchis-Juan
- Broad Institute Center for Mendelian Genomics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Harvard Medical School, Boston, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- These authors contributed equally
| | - Kathryn Russell
- Broad Institute Center for Mendelian Genomics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Samantha Baxter
- Broad Institute Center for Mendelian Genomics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Katherine R. Chao
- Broad Institute Center for Mendelian Genomics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Moriel Singer-Berk
- Broad Institute Center for Mendelian Genomics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Emily Groopman
- Broad Institute Center for Mendelian Genomics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Genetics and Genomics, Boston Children’s Hospital, Boston, MA, USA
| | - Isaac Wong
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Eleina England
- Broad Institute Center for Mendelian Genomics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Julia Goodrich
- Broad Institute Center for Mendelian Genomics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Lynn Pais
- Broad Institute Center for Mendelian Genomics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Genetics and Genomics, Boston Children’s Hospital, Boston, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Christina Austin-Tse
- Broad Institute Center for Mendelian Genomics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Stephanie DiTroia
- Broad Institute Center for Mendelian Genomics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Genetics and Genomics, Boston Children’s Hospital, Boston, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Emily O’Heir
- Broad Institute Center for Mendelian Genomics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Vijay S. Ganesh
- Broad Institute Center for Mendelian Genomics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Genetics and Genomics, Boston Children’s Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Neurology, Brigham and Women’s Hospital, Boston, MA, USA
| | - Monica H. Wojcik
- Broad Institute Center for Mendelian Genomics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Genetics and Genomics, Boston Children’s Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Emily Evangelista
- Broad Institute Center for Mendelian Genomics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Hana Snow
- Broad Institute Center for Mendelian Genomics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Ikeoluwa Osei-Owusu
- Broad Institute Center for Mendelian Genomics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Jack Fu
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Harvard Medical School, Boston, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Mugdha Singh
- Broad Institute Center for Mendelian Genomics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Genetics and Genomics, Boston Children’s Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Yulia Mostovoy
- Broad Institute Center for Mendelian Genomics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Steve Huang
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Kiran Garimella
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Samantha L. Kirkham
- Division of Genetics and Genomics, Boston Children’s Hospital, Boston, MA, USA
| | - Jennifer E. Neil
- Division of Genetics and Genomics, Boston Children’s Hospital, Boston, MA, USA
- Howard Hughes Medical Institute, Boston Children’s Hospital, Boston, MA, USA
| | - Diane D. Shao
- Division of Genetics and Genomics, Boston Children’s Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
- Department of Neurology, Boston Children’s Hospital, Boston, MA, USA
| | - Christopher A. Walsh
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Genetics and Genomics, Boston Children’s Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
- Howard Hughes Medical Institute, Boston Children’s Hospital, Boston, MA, USA
| | - Emanuela Argili
- Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
- Institute of Human Genetics and Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Carolyn Le
- Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
- Institute of Human Genetics and Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Elliott H. Sherr
- Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
- Institute of Human Genetics and Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Joseph Gleeson
- Department of Neurosciences, University of California San Diego, La Jolla, CA, USA
- Rady Children’s Institute for Genomic Medicine, San Diego, CA, USA
| | - Shirlee Shril
- Harvard Medical School, Boston, MA, USA
- Department of Pediatrics, Boston Children’s Hospital, Boston, MA, USA
| | - Ronen Schneider
- Harvard Medical School, Boston, MA, USA
- Department of Pediatrics, Boston Children’s Hospital, Boston, MA, USA
| | - Friedhelm Hildebrandt
- Harvard Medical School, Boston, MA, USA
- Department of Pediatrics, Boston Children’s Hospital, Boston, MA, USA
| | - Vijay G. Sankaran
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Harvard Medical School, Boston, MA, USA
- Division of Hematology/Oncology, Boston Children’s Hospital and Department of Pediatric Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts, USA
| | - Jill A. Madden
- Division of Genetics and Genomics, Boston Children’s Hospital, Boston, MA, USA
- The Manton Center for Orphan Disease Research, Boston Children’s Hospital, Boston, MA, USA
| | - Casie A. Genetti
- Division of Genetics and Genomics, Boston Children’s Hospital, Boston, MA, USA
- The Manton Center for Orphan Disease Research, Boston Children’s Hospital, Boston, MA, USA
| | - Alan H. Beggs
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Genetics and Genomics, Boston Children’s Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
- The Manton Center for Orphan Disease Research, Boston Children’s Hospital, Boston, MA, USA
| | - Pankaj B. Agrawal
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Genetics and Genomics, Boston Children’s Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
- The Manton Center for Orphan Disease Research, Boston Children’s Hospital, Boston, MA, USA
| | - Kinga M. Bujakowska
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Harvard Medical School, Boston, MA, USA
- Ocular Genomics Institute, Department of Ophthalmology, Massachusetts Eye and Ear Infirmary, Boston, MA, USA
| | - Emily Place
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Harvard Medical School, Boston, MA, USA
- Ocular Genomics Institute, Department of Ophthalmology, Massachusetts Eye and Ear Infirmary, Boston, MA, USA
| | - Eric A. Pierce
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Harvard Medical School, Boston, MA, USA
- Ocular Genomics Institute, Department of Ophthalmology, Massachusetts Eye and Ear Infirmary, Boston, MA, USA
| | - Sandra Donkervoort
- Neuromuscular and Neurogenetic Disorders of Childhood Section, Neurogenetics Branch, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Carsten G. Bönnemann
- Neuromuscular and Neurogenetic Disorders of Childhood Section, Neurogenetics Branch, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Lyndon Gallacher
- Department of Paediatrics, University of Melbourne, Parkville, Victoria, Australia
- Victorian Clinical Genetics Services, Murdoch Children’s Research Institute, Parkville, Victoria, Australia
| | - Zornitza Stark
- Department of Paediatrics, University of Melbourne, Parkville, Victoria, Australia
- Victorian Clinical Genetics Services, Murdoch Children’s Research Institute, Parkville, Victoria, Australia
| | - Tiong Tan
- Department of Paediatrics, University of Melbourne, Parkville, Victoria, Australia
- Victorian Clinical Genetics Services, Murdoch Children’s Research Institute, Parkville, Victoria, Australia
| | - Susan M. White
- Department of Paediatrics, University of Melbourne, Parkville, Victoria, Australia
- Victorian Clinical Genetics Services, Murdoch Children’s Research Institute, Parkville, Victoria, Australia
| | - Ana Töpf
- John Walton Muscular Dystrophy Research Centre, Newcastle University and Newcastle Hospitals NHS Foundation Trust, Newcastle upon Tyne, UK
| | - Volker Straub
- John Walton Muscular Dystrophy Research Centre, Newcastle University and Newcastle Hospitals NHS Foundation Trust, Newcastle upon Tyne, UK
| | - Mark D. Fleming
- Harvard Medical School, Boston, MA, USA
- Department of Pathology, Boston Children’s Hospital, Boston, MA, USA
| | - Martin R. Pollak
- Harvard Medical School, Boston, MA, USA
- Division of Nephrology, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Katrin Õunap
- Department of Clinical Genetics, Genetics and Personalized Medicine Clinic, Tartu University Hospital, Tartu, Estonia
- Department of Clinical Genetics, Institute of Clinical Medicine, Faculty of Medicine, University of Tartu, Tartu, Estonia
| | - Sander Pajusalu
- Department of Clinical Genetics, Genetics and Personalized Medicine Clinic, Tartu University Hospital, Tartu, Estonia
- Department of Clinical Genetics, Institute of Clinical Medicine, Faculty of Medicine, University of Tartu, Tartu, Estonia
| | - Kirsten A. Donald
- Department of Paediatrics and Child Health, Red Cross War Memorial Children’s Hospital, Cape Town, South Africa
- University of Cape Town, Cape Town, South Africa
| | - Zandre Bruwer
- Department of Paediatrics and Child Health, Red Cross War Memorial Children’s Hospital, Cape Town, South Africa
- University of Cape Town, Cape Town, South Africa
| | - Gianina Ravenscroft
- University of Western Australia, Harry Perkins Institute of Medical Research, QEII Medical Centre, Nedlands, Australia
| | - Nigel G. Laing
- University of Western Australia, Harry Perkins Institute of Medical Research, QEII Medical Centre, Nedlands, Australia
| | - Daniel G. MacArthur
- Broad Institute Center for Mendelian Genomics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Centre for Population Genomics, Garvan Institute, Sydney, Australia
- Centre for Population Genomics, Murdoch Children’s Research Institute, Melbourne, Australia
| | - Heidi L. Rehm
- Broad Institute Center for Mendelian Genomics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Harvard Medical School, Boston, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Michael E. Talkowski
- Broad Institute Center for Mendelian Genomics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Harvard Medical School, Boston, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Harrison Brand
- Broad Institute Center for Mendelian Genomics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Harvard Medical School, Boston, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Senior authors
| | - Anne O’Donnell-Luria
- Broad Institute Center for Mendelian Genomics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Genetics and Genomics, Boston Children’s Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
- Senior authors
| |
Collapse
|
12
|
Abdallah S, Sharifa M, I Kh Almadhoun MK, Khawar MM, Shaikh U, Balabel KM, Saleh I, Manzoor A, Mandal AK, Ekomwereren O, Khine WM, Oyelaja OT. The Impact of Artificial Intelligence on Optimizing Diagnosis and Treatment Plans for Rare Genetic Disorders. Cureus 2023; 15:e46860. [PMID: 37954711 PMCID: PMC10636514 DOI: 10.7759/cureus.46860] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/11/2023] [Indexed: 11/14/2023] Open
Abstract
Rare genetic disorders (RDs), characterized by their low prevalence and diagnostic complexities, present significant challenges to healthcare systems. This article explores the transformative impact of artificial intelligence (AI) and machine learning (ML) in addressing these challenges. It emphasizes the need for accurate and early diagnosis of RDs, often hindered by genetic and clinical heterogeneity. This article discusses how AI and ML are reshaping healthcare, providing examples of their effectiveness in disease diagnosis, prognosis, image analysis, and drug repurposing. It highlights AI's ability to efficiently analyze extensive datasets and expedite diagnosis, showcasing case studies like Face2Gene. Furthermore, the article explores how AI tailors treatment plans for RDs, leveraging ML and deep learning (DL) to create personalized therapeutic regimens. It emphasizes AI's role in drug discovery, including the identification of potential candidates for rare disease treatments. Challenges and limitations related to AI in healthcare, including ethical, legal, technical, and human aspects, are addressed. This article underscores the importance of data ethics, privacy, and algorithmic fairness, as well as the need for standardized evaluation techniques and transparency in AI research. It highlights second-generation AI systems that prioritize patient-centric care, efficient patient recruitment for clinical trials, and the significance of high-quality data. The integration of AI with telemedicine, the growth of health databases, and the potential for personalized therapeutic recommendations are identified as promising directions for the field. In summary, this article provides a comprehensive exploration of how AI and ML are revolutionizing the diagnosis and treatment of RDs, addressing challenges while considering ethical implications in this rapidly evolving healthcare landscape.
Collapse
Affiliation(s)
- Shenouda Abdallah
- Surgery, Jaber Al Ahmad Al Jaber Al Sabah Hospital, Kuwait City, KWT
| | | | | | | | - Unzla Shaikh
- Internal Medicine, Liaquat University of Medical and Health Sciences, Hyderabad, PAK
| | | | - Inam Saleh
- Pediatrics, University of Kentucky College of Medicine, Lexington, USA
| | - Amima Manzoor
- Internal Medicine, Jinnah Sindh Medical University, Karachi, PAK
| | - Arun Kumar Mandal
- General Medicine, Mahawai Basic Hospital/The Oda Foundation, Kalikot, NPL
- Medicine, Manipal College of Medical Sciences, Pokhara, NPL
| | - Osatohanmwen Ekomwereren
- Trauma and Orthopaedics, Royal Shrewsbury Hospital, Shrewsbury and Telford Hospital NHS Trust, Shrewsbury, GBR
| | - Wai Mon Khine
- Internal Medicine, Caribbean Medical School, St. Georges, GRD
| | | |
Collapse
|
13
|
Similuk M, Kuijpers T. Nature and nurture: understanding phenotypic variation in inborn errors of immunity. Front Cell Infect Microbiol 2023; 13:1183142. [PMID: 37780853 PMCID: PMC10538643 DOI: 10.3389/fcimb.2023.1183142] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2023] [Accepted: 08/17/2023] [Indexed: 10/03/2023] Open
Abstract
The overall disease burden of pediatric infection is high, with widely varying clinical outcomes including death. Among the most vulnerable children, those with inborn errors of immunity, reduced penetrance and variable expressivity are common but poorly understood. There are several genetic mechanisms that influence phenotypic variation in inborn errors of immunity, as well as a body of knowledge on environmental influences and specific pathogen triggers. Critically, recent advances are illuminating novel nuances for fundamental concepts on disease penetrance, as well as raising new areas of inquiry. The last few decades have seen the identification of almost 500 causes of inborn errors of immunity, as well as major advancements in our ability to characterize somatic events, the microbiome, and genotypes across large populations. The progress has not been linear, and yet, these developments have accumulated into an enhanced ability to diagnose and treat inborn errors of immunity, in some cases with precision therapy. Nonetheless, many questions remain regarding the genetic and environmental contributions to phenotypic variation both within and among families. The purpose of this review is to provide an updated summary of key concepts in genetic and environmental contributions to phenotypic variation within inborn errors of immunity, conceptualized as including dynamic, reciprocal interplay among factors unfolding across the key dimension of time. The associated findings, potential gaps, and implications for research are discussed in turn for each major influencing factor. The substantial challenge ahead will be to organize and integrate information in such a way that accommodates the heterogeneity within inborn errors of immunity to arrive at a more comprehensive and accurate understanding of how the immune system operates in health and disease. And, crucially, to translate this understanding into improved patient care for the millions at risk for serious infection and other immune-related morbidity.
Collapse
Affiliation(s)
- Morgan Similuk
- Centralized Sequencing Program, Division of Intramural Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, United States
| | - Taco Kuijpers
- Department of Pediatric Immunology, Rheumatology and Infectious Diseases, Emma Children’s Hospital, Amsterdam University Medical Center, University of Amsterdam, Amsterdam, Netherlands
| |
Collapse
|
14
|
Renaux A, Terwagne C, Cochez M, Tiddi I, Nowé A, Lenaerts T. A knowledge graph approach to predict and interpret disease-causing gene interactions. BMC Bioinformatics 2023; 24:324. [PMID: 37644440 PMCID: PMC10463539 DOI: 10.1186/s12859-023-05451-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2023] [Accepted: 08/22/2023] [Indexed: 08/31/2023] Open
Abstract
BACKGROUND Understanding the impact of gene interactions on disease phenotypes is increasingly recognised as a crucial aspect of genetic disease research. This trend is reflected by the growing amount of clinical research on oligogenic diseases, where disease manifestations are influenced by combinations of variants on a few specific genes. Although statistical machine-learning methods have been developed to identify relevant genetic variant or gene combinations associated with oligogenic diseases, they rely on abstract features and black-box models, posing challenges to interpretability for medical experts and impeding their ability to comprehend and validate predictions. In this work, we present a novel, interpretable predictive approach based on a knowledge graph that not only provides accurate predictions of disease-causing gene interactions but also offers explanations for these results. RESULTS We introduce BOCK, a knowledge graph constructed to explore disease-causing genetic interactions, integrating curated information on oligogenic diseases from clinical cases with relevant biomedical networks and ontologies. Using this graph, we developed a novel predictive framework based on heterogenous paths connecting gene pairs. This method trains an interpretable decision set model that not only accurately predicts pathogenic gene interactions, but also unveils the patterns associated with these diseases. A unique aspect of our approach is its ability to offer, along with each positive prediction, explanations in the form of subgraphs, revealing the specific entities and relationships that led to each pathogenic prediction. CONCLUSION Our method, built with interpretability in mind, leverages heterogenous path information in knowledge graphs to predict pathogenic gene interactions and generate meaningful explanations. This not only broadens our understanding of the molecular mechanisms underlying oligogenic diseases, but also presents a novel application of knowledge graphs in creating more transparent and insightful predictors for genetic research.
Collapse
Affiliation(s)
- Alexandre Renaux
- Interuniversity Institute of Bioinformatics in Brussels, Université Libre de Bruxelles - Vrije Universiteit Brussel, Brussels, Belgium
- Machine Learning Group, Université Libre de Bruxelles, Brussels, Belgium
- Artificial Intelligence lab, Vrije Universiteit Brussel, Brussels, Belgium
| | - Chloé Terwagne
- Interuniversity Institute of Bioinformatics in Brussels, Université Libre de Bruxelles - Vrije Universiteit Brussel, Brussels, Belgium
- Machine Learning Group, Université Libre de Bruxelles, Brussels, Belgium
| | - Michael Cochez
- Computer Science, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Discovery Lab, Elsevier, Amsterdam, The Netherlands
| | - Ilaria Tiddi
- Computer Science, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Ann Nowé
- Interuniversity Institute of Bioinformatics in Brussels, Université Libre de Bruxelles - Vrije Universiteit Brussel, Brussels, Belgium
- Artificial Intelligence lab, Vrije Universiteit Brussel, Brussels, Belgium
| | - Tom Lenaerts
- Interuniversity Institute of Bioinformatics in Brussels, Université Libre de Bruxelles - Vrije Universiteit Brussel, Brussels, Belgium
- Machine Learning Group, Université Libre de Bruxelles, Brussels, Belgium
- Artificial Intelligence lab, Vrije Universiteit Brussel, Brussels, Belgium
| |
Collapse
|
15
|
Wojcik MH, Lemire G, Zaki MS, Wissman M, Win W, White S, Weisburd B, Waddell LB, Verboon JM, VanNoy GE, Töpf A, Tan TY, Straub V, Stenton SL, Snow H, Singer-Berk M, Silver J, Shril S, Seaby EG, Schneider R, Sankaran VG, Sanchis-Juan A, Russell KA, Reinson K, Ravenscroft G, Pierce EA, Place EM, Pajusalu S, Pais L, Õunap K, Osei-Owusu I, Okur V, Oja KT, O'Leary M, O'Heir E, Morel C, Marchant RG, Mangilog BE, Madden JA, MacArthur D, Lovgren A, Lerner-Ellis JP, Lin J, Laing N, Hildebrandt F, Groopman E, Goodrich J, Gleeson JG, Ghaoui R, Genetti CA, Gazda HT, Ganesh VS, Ganapathy M, Gallacher L, Fu J, Evangelista E, England E, Donkervoort S, DiTroia S, Cooper ST, Chung WK, Christodoulou J, Chao KR, Cato LD, Bujakowska KM, Bryen SJ, Brand H, Bonnemann C, Beggs AH, Baxter SM, Agrawal PB, Talkowski M, Austin-Tse C, Rehm HL, O'Donnell-Luria A. Unique Capabilities of Genome Sequencing for Rare Disease Diagnosis. medRxiv 2023:2023.08.08.23293829. [PMID: 38328047 PMCID: PMC10849673 DOI: 10.1101/2023.08.08.23293829] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/09/2024]
Abstract
Background Causal variants underlying rare disorders may remain elusive even after expansive gene panels or exome sequencing (ES). Clinicians and researchers may then turn to genome sequencing (GS), though the added value of this technique and its optimal use remain poorly defined. We therefore investigated the advantages of GS within a phenotypically diverse cohort. Methods GS was performed for 744 individuals with rare disease who were genetically undiagnosed. Analysis included review of single nucleotide, indel, structural, and mitochondrial variants. Results We successfully solved 218/744 (29.3%) cases using GS, with most solves involving established disease genes (157/218, 72.0%). Of all solved cases, 148 (67.9%) had previously had non-diagnostic ES. We systematically evaluated the 218 causal variants for features requiring GS to identify and 61/218 (28.0%) met these criteria, representing 8.2% of the entire cohort. These included small structural variants (13), copy neutral inversions and complex rearrangements (8), tandem repeat expansions (6), deep intronic variants (15), and coding variants that may be more easily found using GS related to uniformity of coverage (19). Conclusion We describe the diagnostic yield of GS in a large and diverse cohort, illustrating several types of pathogenic variation eluding ES or other techniques. Our results reveal a higher diagnostic yield of GS, supporting the utility of a genome-first approach, with consideration of GS as a secondary or tertiary test when higher-resolution structural variant analysis is needed or there is a strong clinical suspicion for a condition and prior targeted genetic testing has been negative.
Collapse
|
16
|
Serrano JG, O'Leary M, VanNoy GE, Mangilog BE, Holm IA, Fraiman YS, Rehm HL, O'Donnell-Luria A, Wojcik MH. Advancing Understanding of Inequities in Rare Disease Genomics. Clin Ther 2023; 45:745-753. [PMID: 37517917 PMCID: PMC10527807 DOI: 10.1016/j.clinthera.2023.06.010] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2023] [Revised: 05/07/2023] [Accepted: 06/02/2023] [Indexed: 08/01/2023]
Abstract
PURPOSE Advances in genomic research have facilitated rare disease diagnosis for thousands of individuals. Unfortunately, the benefits of advanced genetic diagnostic technology are not distributed equitably among the population, as has been seen in many other health care contexts. Quantifying and describing inequities in genetic diagnostic yield is inherently challenging due to barriers to both clinical and research genetic testing. We therefore present an implementation protocol developed to expand access to our rare disease genomic research study and to further understand existing inequities. METHODS AND FINDINGS The Rare Genomes Project (RGP) at the Broad Institute of MIT and Harvard offers research genome sequencing to individuals with rare disease who remain genetically undiagnosed through direct interaction with the individual or family. This presents an opportunity for diagnosis beyond the clinical context, thus eliminating many barriers to access. An initial goal of RGP was to equalize access to genomic sequencing by decoupling testing access from proximity to a major medical center and physician referral. However, study participants over the initial 3 years of this project were predominantly white and well resourced. To further understand and address the lack of diversity within RGP, we developed a novel protocol embedded within the larger RGP study, in an approach informed by an implementation science framework. The aims of this protocol were: (1) to diversify recruitment and enrollment within RGP; (2) understand the process and context of implementing genomic medicine for rare disease diagnosis; and (3) investigate the value of a diagnosis for underserved populations. IMPLICATIONS Improved understanding of existing inequities and potential strategies to address them are needed to advance equity in rare disease genetic diagnosis and research. In addition to the moral imperative of equity in genomic medicine, this approach is critical in order to fully understand the genomic underpinnings of rare disease.
Collapse
Affiliation(s)
- Jillian G Serrano
- Broad Center for Mendelian Genomics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
| | - Melanie O'Leary
- Broad Center for Mendelian Genomics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
| | - Grace E VanNoy
- Broad Center for Mendelian Genomics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
| | - Brian E Mangilog
- Broad Center for Mendelian Genomics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
| | - Ingrid A Holm
- Division of Genetics and Genomics, Department of Pediatrics, Boston Children's Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Yarden S Fraiman
- Division of Newborn Medicine, Department of Pediatrics, Boston Children's Hospital and Harvard Medical School, Boston, Massachusetts, USA; Department of Neonatology, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA
| | - Heidi L Rehm
- Broad Center for Mendelian Genomics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA; Center for Genomic Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Anne O'Donnell-Luria
- Broad Center for Mendelian Genomics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA; Division of Genetics and Genomics, Department of Pediatrics, Boston Children's Hospital and Harvard Medical School, Boston, Massachusetts, USA; Center for Genomic Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Monica H Wojcik
- Broad Center for Mendelian Genomics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA; Division of Genetics and Genomics, Department of Pediatrics, Boston Children's Hospital and Harvard Medical School, Boston, Massachusetts, USA; Division of Newborn Medicine, Department of Pediatrics, Boston Children's Hospital and Harvard Medical School, Boston, Massachusetts, USA.
| |
Collapse
|
17
|
Trieschmann G, Wilhelm C, Berweck S, Zech M. De novo retinoic acid receptor beta (RARB) variant associated with microphthalmia and dystonia. Eur J Med Genet 2023; 66:104802. [PMID: 37321544 DOI: 10.1016/j.ejmg.2023.104802] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2023] [Revised: 05/30/2023] [Accepted: 06/12/2023] [Indexed: 06/17/2023]
Abstract
BACKGROUND Definition of the individual genotypes that cause a Mendelian phenotype is of great importance both to clinical diagnostics and disease characterization. Heterozygous de novo gain-of-function missense variants in RARB are associated with syndromic microphthalmia 12 (MCOPS12), a developmental disorder characterized by eye malformations and variable involvement of other organs. A subset of patients were described with poorly delineated movement disorders. Additionally, RARB bi-allelic loss-of-function variants, inherited from asymptomatic heterozygous carrier parents, have been found in a recessive family with four MCOPS12-affected members. PATIENT/METHODS We used trio whole-exome sequencing to explore the molecular basis of disease in an individual with congenital eye abnormality and movement disorder. All patients with reported RARB variants were reviewed. RESULTS We report on identification of a heterozygous de novo RARB nonsense variant in a girl with microphthalmia and progressive generalized dystonia. Public database entries indicate that the de novo variant is recurrently present in clinically affected subjects but a literature report has not yet been available. CONCLUSIONS We provide the first detailed evidence for a role of dominant RARB truncating alterations in congenital eye-brain disease, expanding the spectrum of MCOPS12-associated mutations. Considered together with the published family with bi-allelic variants, the data suggest manifestation and non-manifestation of disease in relation to almost identical RARB loss-of-function variations, an apparent paradox that is seen in a growing number of human genetic conditions associated with both recessive and dominant inheritance patterns.
Collapse
Affiliation(s)
- Gesa Trieschmann
- Specialist Centre for Paediatric Neurology, Neurorehabilitation and Epileptology, Schoen Clinic Vogtareuth, Vogtareuth, Germany
| | | | - Steffen Berweck
- Specialist Centre for Paediatric Neurology, Neurorehabilitation and Epileptology, Schoen Clinic Vogtareuth, Vogtareuth, Germany; LMU Hospital, Department of Pediatrics-Dr. von Hauner Childrens's Hospital, Division of Pediatric Neurology and Developmental Medicine, Ludwig-Maximilians University, Munich, Germany
| | - Michael Zech
- Institute of Neurogenomics, Helmholtz Zentrum München, Munich, Germany; Institute of Human Genetics, School of Medicine, Technical University of Munich, Munich, Germany.
| |
Collapse
|
18
|
Medvedev A, Lebedev M, Ponomarev A, Kosaretskiy M, Osipenko D, Tischenko A, Kosaretskiy E, Wang H, Kolobkov D, Chamberlain-Evans V, Vakhitov R, Nikonorov P. GRAPE: genomic relatedness detection pipeline. F1000Res 2023; 11:589. [PMID: 37224332 PMCID: PMC10182380 DOI: 10.12688/f1000research.111658.2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 03/22/2023] [Indexed: 05/26/2023] Open
Abstract
Classifying the degree of relatedness between pairs of individuals has both scientific and commercial applications. As an example, genome-wide association studies (GWAS) may suffer from high rates of false positive results due to unrecognized population structure. This problem becomes especially relevant with recent increases in large-cohort studies. Accurate relationship classification is also required for genetic linkage analysis to identify disease-associated loci. Additionally, DNA relatives matching service is one of the leading drivers for the direct-to-consumer genetic testing market. Despite the availability of scientific and research information on the methods for determining kinship and the accessibility of relevant tools, the assembly of the pipeline, which stably operates on a real-world genotypic data, requires significant research and development resources. Currently, there is no open source end-to-end solution for relatedness detection in genomic data, that is fast, reliable and accurate for both close and distant degrees of kinship, combines all the necessary processing steps to work on a real data, and is ready for production integration. To address this, we developed GRAPE: Genomic RelAtedness detection PipelinE. It combines data preprocessing, identity-by-descent (IBD) segments detection, and accurate relationship estimation. The project uses software development best practices, as well as Global Alliance for Genomics and Health (GA4GH) standards and tools. Pipeline efficiency is demonstrated on both simulated and real-world datasets. GRAPE is available from: https://github.com/genxnetwork/grape.
Collapse
Affiliation(s)
- Alexander Medvedev
- Skolkovo Institute of Science and Technology, Moscow, Russian Federation
- GENXT, Hinxton, UK
| | | | | | | | | | | | | | - Hui Wang
- GENXT, Hinxton, UK
- Huazhong Agricultural University, Wuhan, China
| | | | | | | | | |
Collapse
|
19
|
Zhao Y, van de Leemput J, Han Z. The opportunities and challenges of using Drosophila to model human cardiac diseases. Front Physiol 2023; 14:1182610. [PMID: 37123266 PMCID: PMC10130661 DOI: 10.3389/fphys.2023.1182610] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2023] [Accepted: 04/05/2023] [Indexed: 05/02/2023] Open
Abstract
The Drosophila heart tube seems simple, yet it has notable anatomic complexity and contains highly specialized structures. In fact, the development of the fly heart tube much resembles that of the earliest stages of mammalian heart development, and the molecular-genetic mechanisms driving these processes are highly conserved between flies and humans. Combined with the fly's unmatched genetic tools and a wide variety of techniques to assay both structure and function in the living fly heart, these attributes have made Drosophila a valuable model system for studying human heart development and disease. This perspective focuses on the functional and physiological similarities between fly and human hearts. Further, it discusses current limitations in using the fly, as well as promising prospects to expand the capabilities of Drosophila as a research model for studying human cardiac diseases.
Collapse
Affiliation(s)
- Yunpo Zhao
- Center for Precision Disease Modeling, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, United States
- Division of Endocrinology, Diabetes and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, United States
| | - Joyce van de Leemput
- Center for Precision Disease Modeling, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, United States
- Division of Endocrinology, Diabetes and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, United States
| | - Zhe Han
- Center for Precision Disease Modeling, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, United States
- Division of Endocrinology, Diabetes and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, United States
| |
Collapse
|
20
|
Serrano JG, O'Leary M, VanNoy G, Holm IA, Fraiman YS, Rehm HL, O'Donnell-Luria A, Wojcik MH. Advancing Understanding of Inequities in Rare Disease Genomics. medRxiv 2023:2023.03.28.23286936. [PMID: 37034593 PMCID: PMC10081425 DOI: 10.1101/2023.03.28.23286936] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/19/2023]
Abstract
Purpose Advances in genomic research have led to the diagnosis of rare, early-onset diseases for thousands of individuals. Unfortunately, the benefits of advanced genetic diagnostic technology are not distributed equitably among the population, as has been seen in many other healthcare contexts. Even quantifying and describing inequities in genetic diagnostic yield is challenging due to variation in referrals to clinical genetics practices and other barriers to clinical genetic testing. Methods The Rare Genomes Project (RGP) at the Broad Institute of MIT and Harvard offers research genome sequencing to individuals with rare disease who remain genetically undiagnosed through direct interaction with the individual or family. This presents an opportunity for diagnosis beyond the clinical context, thus eliminating many barriers to access. Findings An initial goal of RGP was to equalize access to genomic sequencing by decoupling testing access from proximity to a major medical center and physician referral. However, our study participants are overwhelmingly non-disadvantaged, as evidenced by their access to specialist care and genetic testing prior to RGP enrollment, and are also predominantly white. Implications We therefore describe our novel initiative to diversify RGP enrollment in order to advance equity in rare disease genetic diagnosis and research. In addition to the moral imperative of medical equity, this is also critical in order to fully understand the genomic underpinnings of rare disease. We utilize a mixed methods approach to understand the priorities and values of underrepresented communities, existing disparities, and the obstacles to addressing them: all of which is necessary to promote equity in future genomic medicine initiatives.
Collapse
|
21
|
Lyulcheva-Bennett E, Genomics England Research Consortium, Bennett D. A retrospective analysis of phosphatase catalytic subunit gene variants in patients with rare disorders identifies novel candidate neurodevelopmental disease genes. Front Cell Dev Biol 2023; 11:1107930. [PMID: 37056996 PMCID: PMC10086149 DOI: 10.3389/fcell.2023.1107930] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2022] [Accepted: 03/03/2023] [Indexed: 03/30/2023] Open
Abstract
Rare genetic disorders represent some of the most severe and life-limiting conditions that constitute a considerable burden on global healthcare systems and societies. Most individuals affected by rare disorders remain undiagnosed, highlighting the unmet need for improved disease gene discovery and novel variant interpretation. Aberrant (de) phosphorylation can have profound pathological consequences underpinning many disease processes. Numerous phosphatases and associated proteins have been identified as disease genes, with many more likely to have gone undiscovered thus far. To begin to address these issues, we have performed a systematic survey of de novo variants amongst 189 genes encoding phosphatase catalytic subunits found in rare disease patients recruited to the 100,000 Genomes Project (100 kGP), the largest national sequencing project of its kind in the United Kingdom. We found that 49% of phosphatases were found to carry de novo mutation(s) in this cohort. Only 25% of these phosphatases have been previously linked to genetic disorders. A gene-to-patient approach matching variants to phenotypic data identified 9 novel candidate rare-disease genes: PTPRD, PTPRG, PTPRT, PTPRU, PTPRZ1, MTMR3, GAK, TPTE2, PTPN18. As the number of patients undergoing whole genome sequencing increases and information sharing improves, we anticipate that reiterative analysis of genomic and phenotypic data will continue to identify candidate phosphatase disease genes for functional validation. This is the first step towards delineating the aetiology of rare genetic disorders associated with altered phosphatase function, leading to new biological insights and improved clinical outcomes for the affected individuals and their families.
Collapse
Affiliation(s)
| | | | - Daimark Bennett
- Division of Developmental Biology and Medicine, School of Medical Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, United Kingdom
| |
Collapse
|
22
|
Seaby EG, Thomas NS, Webb A, Brittain H, Taylor Tavares AL, Baralle D, Rehm HL, O'Donnell-Luria A, Ennis S. Targeting de novo loss-of-function variants in constrained disease genes improves diagnostic rates in the 100,000 Genomes Project. Hum Genet 2023; 142:351-362. [PMID: 36477409 PMCID: PMC9950176 DOI: 10.1007/s00439-022-02509-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2022] [Accepted: 11/28/2022] [Indexed: 12/12/2022]
Abstract
BACKGROUND Genome sequencing was first offered clinically in the UK through the 100,000 Genomes Project (100KGP). Analysis was restricted to predefined gene panels associated with the patient's phenotype. However, panels rely on clearly characterised phenotypes and risk missing diagnoses outside of the panel(s) applied. We propose a complementary method to rapidly identify pathogenic variants, including those missed by 100KGP methods. METHODS The Loss-of-function Observed/Expected Upper-bound Fraction (LOEUF) score quantifies gene constraint, with low scores correlated with haploinsufficiency. We applied DeNovoLOEUF, a filtering strategy to sequencing data from 13,949 rare disease trios in the 100KGP, by filtering for rare, de novo, loss-of-function variants in disease genes with a LOEUF score < 0.2. We compared our findings with the corresponding patient's diagnostic reports. RESULTS 324/332 (98%) of the variants identified using DeNovoLOEUF were diagnostic or partially diagnostic (whereby the variant was responsible for some of the phenotype). We identified 39 diagnoses that were "missed" by 100KGP standard analyses, which are now being returned to patients. CONCLUSION We have demonstrated a highly specific and rapid method with a 98% positive predictive value that has good concordance with standard analysis, low false-positive rate, and can identify additional diagnoses. Globally, as more patients are being offered genome sequencing, we anticipate that DeNovoLOEUF will rapidly identify new diagnoses and facilitate iterative analyses when new disease genes are discovered.
Collapse
Affiliation(s)
- Eleanor G Seaby
- Genomic Informatics Group, Human Development and Health, Faculty of Medicine, University Hospital Southampton, MP 808, Duthie Building, Southampton, SO16 6YD, Hampshire, UK.
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA.
- Division of Genetics and Genomics, Boston Children's Hospital, Boston, MA, 02115, USA.
- Paediatric Infectious Diseases, Imperial College London, London, W2 1NY, UK.
| | - N Simon Thomas
- Genomic Informatics Group, Human Development and Health, Faculty of Medicine, University Hospital Southampton, MP 808, Duthie Building, Southampton, SO16 6YD, Hampshire, UK
- Wessex Regional Genomics Laboratory, Salisbury NHS Foundation Trust, Salisbury, SP2 8BJ, UK
| | - Amy Webb
- Wessex Regional Genomics Laboratory, Salisbury NHS Foundation Trust, Salisbury, SP2 8BJ, UK
| | - Helen Brittain
- Genomics England, Charterhouse Square, London, EC1M 6BQ, UK
| | - Ana Lisa Taylor Tavares
- Genomics England, Charterhouse Square, London, EC1M 6BQ, UK
- East Anglian Medical Genetics Service, Cambridge University Hospital, Hills Road, Cambridge, CB2 0QQ, UK
| | - Diana Baralle
- Genomic Informatics Group, Human Development and Health, Faculty of Medicine, University Hospital Southampton, MP 808, Duthie Building, Southampton, SO16 6YD, Hampshire, UK
| | - Heidi L Rehm
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, 02114, USA
| | - Anne O'Donnell-Luria
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA
- Division of Genetics and Genomics, Boston Children's Hospital, Boston, MA, 02115, USA
| | - Sarah Ennis
- Genomic Informatics Group, Human Development and Health, Faculty of Medicine, University Hospital Southampton, MP 808, Duthie Building, Southampton, SO16 6YD, Hampshire, UK
| |
Collapse
|
23
|
Abstract
Genomic studies of human disorders are often performed by distinct research communities (i.e., focused on rare diseases, common diseases, or cancer). Despite underlying differences in the mechanistic origin of different disease categories, these studies share the goal of identifying causal genomic events that are critical for the clinical manifestation of the disease phenotype. Moreover, these studies face common challenges, including understanding the complex genetic architecture of the disease, deciphering the impact of variants on multiple scales, and interpreting noncoding mutations. Here, we highlight these challenges in depth and argue that properly addressing them will require a more unified vocabulary and approach across disease communities. Toward this goal, we present a unified perspective on relating variant impact to various genomic disorders.
Collapse
Affiliation(s)
- Sushant Kumar
- Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada; Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada.
| | - Mark Gerstein
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA; Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA; Department of Computer Science, Yale University, New Haven, CT 06520, USA; Department of Statistics & Data Science, Yale University, New Haven, CT 06520, USA.
| |
Collapse
|
24
|
Spedicati B, Santin A, Nardone GG, Rubinato E, Lenarduzzi S, Graziano C, Garavelli L, Miccoli S, Bigoni S, Morgan A, Girotto G. The Enigmatic Genetic Landscape of Hereditary Hearing Loss: A Multistep Diagnostic Strategy in the Italian Population. Biomedicines 2023; 11:703. [PMID: 36979683 PMCID: PMC10045163 DOI: 10.3390/biomedicines11030703] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2023] [Revised: 02/21/2023] [Accepted: 02/22/2023] [Indexed: 03/03/2023] Open
Abstract
Hearing loss is the most frequent sensorineural disorder, affecting approximately 1:1000 newborns. Hereditary forms (HHL) represent 50–60% of cases, highlighting the relevance of genetic testing in deaf patients. HHL is classified as non-syndromic (NSHL—70% of cases) or syndromic (SHL—30% of cases). In this study, a multistep and integrative approach aimed at identifying the molecular cause of HHL in 102 patients, whose GJB2 analysis already showed a negative result, is described. In NSHL patients, multiplex ligation probe amplification and long-range PCR analyses of the STRC gene solved 13 cases, while whole exome sequencing (WES) identified the genetic diagnosis in 26 additional ones, with a total detection rate of 47.6%. Concerning SHL, WES detected the molecular cause in 55% of cases. Peculiar findings are represented by the identification of four subjects displaying a dual molecular diagnosis and eight affected by non-syndromic mimics, five of them presenting Usher syndrome type 2. Overall, this study provides a detailed characterisation of the genetic causes of HHL in the Italian population. Furthermore, we highlighted the frequency of Usher syndrome type 2 carriers in the Italian population to pave the way for a more effective implementation of diagnostic and follow-up strategies for this disease.
Collapse
|
25
|
Abstract
Exome sequencing (ES) and genome sequencing (GS) have radically transformed the diagnostic approach to undiagnosed rare/ultrarare Mendelian diseases. Next-generation sequencing (NGS), the technology integral for ES, GS, and most large (100+) gene panels, has enabled previously unimaginable diagnoses, changes in medical management, new treatments, and accurate reproductive risk assessments for patients, as well as new disease gene discoveries. Yet, challenges remain, as most individuals remain undiagnosed with current NGS. Improved NGS technology has resulted in long-read sequencing, which may resolve diagnoses in some patients who do not obtain a diagnosis with current short-read ES and GS, but its effectiveness is unclear, and it is expensive. Other challenges that persist include the resolution of variants of uncertain significance, the urgent need for patients with ultrarare disorders to have access to therapeutics, the need for equity in patient access to NGS-based testing, and the study of ethical concerns. However, the outlook for undiagnosed disease resolution is bright, due to continual advancements in the field.
Collapse
Affiliation(s)
- Jennifer A Sullivan
- Division of Medical Genetics, Department of Pediatrics, Duke University School of Medicine, Durham, North Carolina, USA;
| | - Kelly Schoch
- Division of Medical Genetics, Department of Pediatrics, Duke University School of Medicine, Durham, North Carolina, USA;
| | - Rebecca C Spillmann
- Division of Medical Genetics, Department of Pediatrics, Duke University School of Medicine, Durham, North Carolina, USA;
| | - Vandana Shashi
- Division of Medical Genetics, Department of Pediatrics, Duke University School of Medicine, Durham, North Carolina, USA;
| |
Collapse
|
26
|
Paul MS, Duncan AR, Genetti CA, Pan H, Jackson A, Grant PE, Shi J, Pinelli M, Brunetti-Pierri N, Garza-Flores A, Shahani D, Saneto RP, Zampino G, Leoni C, Agolini E, Novelli A, Blümlein U, Haack TB, Heinritz W, Matzker E, Alhaddad B, Abou Jamra R, Bartolomaeus T, AlHamdan S, Carapito R, Isidor B, Bahram S, Ritter A, Izumi K, Shakked BP, Barel O, Ben Zeev B, Begtrup A, Carere DA, Mullegama SV, Palculict TB, Calame DG, Schwan K, Aycinena ARP, Traberg R, Douzgou S, Pirt H, Ismayilova N, Banka S, Chao HT, Agrawal PB. Rare EIF4A2 variants are associated with a neurodevelopmental disorder characterized by intellectual disability, hypotonia, and epilepsy. Am J Hum Genet 2023; 110:120-145. [PMID: 36528028 PMCID: PMC9892767 DOI: 10.1016/j.ajhg.2022.11.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2022] [Accepted: 11/15/2022] [Indexed: 12/23/2022] Open
Abstract
Eukaryotic initiation factor-4A2 (EIF4A2) is an ATP-dependent RNA helicase and a member of the DEAD-box protein family that recognizes the 5' cap structure of mRNAs, allows mRNA to bind to the ribosome, and plays an important role in microRNA-regulated gene repression. Here, we report on 15 individuals from 14 families presenting with global developmental delay, intellectual disability, hypotonia, epilepsy, and structural brain anomalies, all of whom have extremely rare de novo mono-allelic or inherited bi-allelic variants in EIF4A2. Neurodegeneration was predominantly reported in individuals with bi-allelic variants. Molecular modeling predicts these variants would perturb structural interactions in key protein domains. To determine the pathogenicity of the EIF4A2 variants in vivo, we examined the mono-allelic variants in Drosophila melanogaster (fruit fly) and identified variant-specific behavioral and developmental defects. The fruit fly homolog of EIF4A2 is eIF4A, a negative regulator of decapentaplegic (dpp) signaling that regulates embryo patterning, eye and wing morphogenesis, and stem cell identity determination. Our loss-of-function (LOF) rescue assay demonstrated a pupal lethality phenotype induced by loss of eIF4A, which was fully rescued with human EIF4A2 wild-type (WT) cDNA expression. In comparison, the EIF4A2 variant cDNAs failed or incompletely rescued the lethality. Overall, our findings reveal that EIF4A2 variants cause a genetic neurodevelopmental syndrome with both LOF and gain of function as underlying mechanisms.
Collapse
Affiliation(s)
- Maimuna S Paul
- Department of Pediatrics, Division of Neurology and Developmental Neuroscience, Baylor College of Medicine, Houston, TX, USA; Jan and Dan Duncan Neurological Research Institute, Texas Children's Hospital, Houston, TX, USA
| | - Anna R Duncan
- Division of Newborn Medicine, Boston Children's Hospital and Harvard Medical School, Boston, MA, USA; Division of Neonatology and Newborn Medicine, Massachusetts General Hospital for Children, Boston, MA, USA
| | - Casie A Genetti
- Division of Newborn Medicine, Boston Children's Hospital and Harvard Medical School, Boston, MA, USA; Division of Genetics and Genomics, Boston Children's Hospital and Harvard Medical School, Boston, MA, USA; The Manton Center for Orphan Disease Research, Boston Children's Hospital and Harvard Medical School, Boston, MA, USA
| | - Hongling Pan
- Jan and Dan Duncan Neurological Research Institute, Texas Children's Hospital, Houston, TX, USA; Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
| | - Adam Jackson
- Division of Evolution, Infection and Genomics, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester M13 9WL, UK; Manchester Centre for Genomic Medicine, St Mary's Hospital, Manchester University NHS Foundation Trust, Health Innovation Manchester, Manchester, UK
| | - Patricia E Grant
- Division of Newborn Medicine, Boston Children's Hospital and Harvard Medical School, Boston, MA, USA; Department of Radiology, Boston Children's Hospital, Boston, MA, USA
| | - Jiahai Shi
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Michele Pinelli
- Telethon Institute of Genetics and Medicine, Pozzuoli, Italy; Department of Translational Medicine, University of Naples "Federico II", Naples, Italy
| | - Nicola Brunetti-Pierri
- Telethon Institute of Genetics and Medicine, Pozzuoli, Italy; Department of Translational Medicine, University of Naples "Federico II", Naples, Italy
| | | | - Dave Shahani
- Department of Neurology and Epileptology, Cook Children's Hospital, Fort Worth, TX 76104, USA
| | - Russell P Saneto
- Neuroscience Institute, Center for Integrative Brain Research, Departments of Pediatric Neurology and Neurology Seattle Children's Hospital, University of Washington, Seattle, WA, USA
| | - Giuseppe Zampino
- Center for Rare Diseases and Birth Defects, Department of Woman and Child Health and Public Health, Fondazione Policlinico Universitario A. Gemelli, Rome, Italy; Catholic University of the Sacred Heart, Faculty of Medicine and Surgery, Rome, Italy
| | - Chiara Leoni
- Center for Rare Diseases and Birth Defects, Department of Woman and Child Health and Public Health, Fondazione Policlinico Universitario A. Gemelli, Rome, Italy
| | - Emanuele Agolini
- Laboratory of Medical Genetics, Translational Cytogenomics Research Unit, Bambino Gesù Children's Hospital, IRCCS, Rome, Italy
| | - Antonio Novelli
- Laboratory of Medical Genetics, Translational Cytogenomics Research Unit, Bambino Gesù Children's Hospital, IRCCS, Rome, Italy
| | - Ulrike Blümlein
- Department of Pediatrics, Carl-Thiem-Klinikum Cottbus, Cottbus, Germany
| | - Tobias B Haack
- Institute of Human Genetics, Technical University of Munich, 81675 Munich, Germany; Institute of Medical Genetics and Applied Genomics, University of Tuebingen, 72076 Tuebingen, Germany
| | | | - Eva Matzker
- Department of Pediatrics, Carl-Thiem-Klinikum Cottbus, Cottbus, Germany
| | - Bader Alhaddad
- Institute of Human Genetics, Technical University of Munich, 81675 Munich, Germany
| | - Rami Abou Jamra
- Institute of Human Genetics, University of Leipzig Medical Center, 04103 Leipzig, Germany
| | - Tobias Bartolomaeus
- Institute of Human Genetics, University of Leipzig Medical Center, 04103 Leipzig, Germany
| | | | - Raphael Carapito
- Laboratoire 'ImmunoRhumatologie Moléculaire, Plateforme GENOMAX, INSERM UMR_S 1109, Faculté de Médecine, Fédération Hospitalo-Universitaire OMICARE, Fédération de Médecine Translationnelle de Strasbourg (FMTS), ITI TRANSPLANTEX NG, Université de Strasbourg, 67085 Strasbourg, France; Service d'Immunologie Biologique, Plateau Technique de Biologie, Pôle de Biologie, Nouvel Hôpital Civil, Hôpitaux Universitaires de Strasbourg, 1 Place de l'Hôpital, 67091, Strasbourg, France
| | - Bertrand Isidor
- Service de Génétique Médicale, Hôpital Hôtel-Dieu, Centre Hospitalier Universitaire de Nantes, Nantes, France
| | - Seiamak Bahram
- Laboratoire 'ImmunoRhumatologie Moléculaire, Plateforme GENOMAX, INSERM UMR_S 1109, Faculté de Médecine, Fédération Hospitalo-Universitaire OMICARE, Fédération de Médecine Translationnelle de Strasbourg (FMTS), ITI TRANSPLANTEX NG, Université de Strasbourg, 67085 Strasbourg, France; Service d'Immunologie Biologique, Plateau Technique de Biologie, Pôle de Biologie, Nouvel Hôpital Civil, Hôpitaux Universitaires de Strasbourg, 1 Place de l'Hôpital, 67091, Strasbourg, France
| | - Alyssa Ritter
- Division of Human Genetics, Department of Pediatrics, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Kosuke Izumi
- Division of Human Genetics, Department of Pediatrics, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Ben Pode Shakked
- Pediatric Neurology Department, The Edmond and Lilly Safra Children's Hospital, Sheba Medical Center, Tel Hashomer, Israel; Sackler Faculty of Medicine, Tel-Aviv University, Tel-Aviv, Israel
| | - Ortal Barel
- Pediatric Neurology Department, The Edmond and Lilly Safra Children's Hospital, Sheba Medical Center, Tel Hashomer, Israel
| | - Bruria Ben Zeev
- Pediatric Neurology Department, The Edmond and Lilly Safra Children's Hospital, Sheba Medical Center, Tel Hashomer, Israel; Sackler Faculty of Medicine, Tel-Aviv University, Tel-Aviv, Israel
| | - Amber Begtrup
- Clinical Genomics Program, GeneDx, Gaithersburg, MD 20877, USA
| | | | | | | | - Daniel G Calame
- Section of Pediatric Neurology and Developmental Neurosciences, Department of Pediatrics, Baylor College of Medicine, Houston, TX 77030, USA
| | | | | | - Rasa Traberg
- Department of Genetics and Molecular Medicine, Hospital of Lithuanian University of Health Sciences Kauno klinikos, Kaunas, Lithuania
| | - Sofia Douzgou
- Division of Evolution, Infection and Genomics, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester M13 9WL, UK; Department of Medical Genetics, Haukeland University Hospital, Bergen, Norway
| | - Harrison Pirt
- Division of Evolution, Infection and Genomics, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester M13 9WL, UK
| | - Naila Ismayilova
- Department of Paediatric Neurology, Chelsea and Westminster NHS Foundation Trust, London, UK
| | - Siddharth Banka
- Division of Evolution, Infection and Genomics, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester M13 9WL, UK; Manchester Centre for Genomic Medicine, St Mary's Hospital, Manchester University NHS Foundation Trust, Health Innovation Manchester, Manchester, UK
| | - Hsiao-Tuan Chao
- Department of Pediatrics, Division of Neurology and Developmental Neuroscience, Baylor College of Medicine, Houston, TX, USA; Jan and Dan Duncan Neurological Research Institute, Texas Children's Hospital, Houston, TX, USA; Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA; Texas Children's Hospital, Houston, TX, USA; Department of Neuroscience, Baylor College of Medicine, Houston, TX, USA; McNair Medical Institute, The Robert and Janice McNair Foundation, Houston, TX, USA.
| | - Pankaj B Agrawal
- Division of Newborn Medicine, Boston Children's Hospital and Harvard Medical School, Boston, MA, USA; Division of Genetics and Genomics, Boston Children's Hospital and Harvard Medical School, Boston, MA, USA; The Manton Center for Orphan Disease Research, Boston Children's Hospital and Harvard Medical School, Boston, MA, USA.
| |
Collapse
|
27
|
Hijazi H, Reis LM, Pehlivan D, Bernstein JA, Muriello M, Syverson E, Bonner D, Estiar MA, Gan-Or Z, Rouleau GA, Lyulcheva E, Greenhalgh L, Tessarech M, Colin E, Guichet A, Bonneau D, van Jaarsveld R, Lachmeijer A, Ruaud L, Levy J, Tabet AC, Ploski R, Rydzanicz M, Kępczyński Ł, Połatyńska K, Li Y, Fatih JM, Marafi D, Rosenfeld JA, Coban-Akdemir Z, Bi W, Gibbs RA, Hobson GM, Hunter JV, Carvalho CM, Posey JE, Semina EV, Lupski JR. TCEAL1 loss-of-function results in an X-linked dominant neurodevelopmental syndrome and drives the neurological disease trait in Xq22.2 deletions. Am J Hum Genet 2022; 109:2270-2282. [PMID: 36368327 PMCID: PMC9748253 DOI: 10.1016/j.ajhg.2022.10.007] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2022] [Accepted: 10/13/2022] [Indexed: 11/12/2022] Open
Abstract
An Xq22.2 region upstream of PLP1 has been proposed to underly a neurological disease trait when deleted in 46,XX females. Deletion mapping revealed that heterozygous deletions encompassing the smallest region of overlap (SRO) spanning six Xq22.2 genes (BEX3, RAB40A, TCEAL4, TCEAL3, TCEAL1, and MORF4L2) associate with an early-onset neurological disease trait (EONDT) consisting of hypotonia, intellectual disability, neurobehavioral abnormalities, and dysmorphic facial features. None of the genes within the SRO have been associated with monogenic disease in OMIM. Through local and international collaborations facilitated by GeneMatcher and Matchmaker Exchange, we have identified and herein report seven de novo variants involving TCEAL1 in seven unrelated families: three hemizygous truncating alleles; one hemizygous missense allele; one heterozygous TCEAL1 full gene deletion; one heterozygous contiguous deletion of TCEAL1, TCEAL3, and TCEAL4; and one heterozygous frameshift variant allele. Variants were identified through exome or genome sequencing with trio analysis or through chromosomal microarray. Comparison with previously reported Xq22 deletions encompassing TCEAL1 identified a more-defined syndrome consisting of hypotonia, abnormal gait, developmental delay/intellectual disability especially affecting expressive language, autistic-like behavior, and mildly dysmorphic facial features. Additional features include strabismus, refractive errors, variable nystagmus, gastroesophageal reflux, constipation, dysmotility, recurrent infections, seizures, and structural brain anomalies. An additional maternally inherited hemizygous missense allele of uncertain significance was identified in a male with hypertonia and spasticity without syndromic features. These data provide evidence that TCEAL1 loss of function causes a neurological rare disease trait involving significant neurological impairment with features overlapping the EONDT phenotype in females with the Xq22 deletion.
Collapse
Affiliation(s)
- Hadia Hijazi
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
| | - Linda M. Reis
- Department of Pediatrics and Children’s Research Institute, Medical College of Wisconsin and Children’s Wisconsin, Milwaukee, WI, USA
| | - Davut Pehlivan
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA,Section of Pediatric Neurology and Developmental Neuroscience, Department of Pediatrics, Baylor College of Medicine, Houston, TX, USA,Department of Pediatrics, Baylor College of Medicine, Houston, TX, USA,Jan and Dan Duncan Neurological Research Institute at Texas Children’s Hospital, Houston, TX, USA
| | - Jonathan A. Bernstein
- Department of Pediatrics, Division of Medical Genetics, Stanford School of Medicine, Stanford, CA, USA
| | - Michael Muriello
- Department of Pediatrics and Children’s Research Institute, Medical College of Wisconsin and Children’s Wisconsin, Milwaukee, WI, USA
| | - Erin Syverson
- Department of Pediatrics and Children’s Research Institute, Medical College of Wisconsin and Children’s Wisconsin, Milwaukee, WI, USA
| | - Devon Bonner
- Department of Pediatrics, Division of Medical Genetics, Stanford School of Medicine, Stanford, CA, USA
| | - Mehrdad A. Estiar
- Department of Human Genetics, McGill University, Montreal, QC, Canada,The Neuro (Montreal Neurological Institute-Hospital), McGill University, Montreal, QC, Canada
| | - Ziv Gan-Or
- Department of Human Genetics, McGill University, Montreal, QC, Canada,The Neuro (Montreal Neurological Institute-Hospital), McGill University, Montreal, QC, Canada,Department of Neurology & Neurosurgery, McGill University, Montreal, QC, Canada
| | - Guy A. Rouleau
- Department of Human Genetics, McGill University, Montreal, QC, Canada,The Neuro (Montreal Neurological Institute-Hospital), McGill University, Montreal, QC, Canada,Department of Neurology & Neurosurgery, McGill University, Montreal, QC, Canada
| | - Ekaterina Lyulcheva
- Liverpool Centre for Genomic Medicine, Liverpool Women’s Hospital, Liverpool, UK
| | - Lynn Greenhalgh
- Liverpool Centre for Genomic Medicine, Liverpool Women’s Hospital, Liverpool, UK
| | - Marine Tessarech
- Department of Medical Genetics, Angers University Hospital, Angers, France,Mitovasc Unit, UMR CNRS 6015-INSERM 1083, University of Angers, Angers, France
| | - Estelle Colin
- Department of Medical Genetics, Angers University Hospital, Angers, France,Mitovasc Unit, UMR CNRS 6015-INSERM 1083, University of Angers, Angers, France
| | - Agnès Guichet
- Department of Medical Genetics, Angers University Hospital, Angers, France,Mitovasc Unit, UMR CNRS 6015-INSERM 1083, University of Angers, Angers, France
| | - Dominique Bonneau
- Department of Medical Genetics, Angers University Hospital, Angers, France,Mitovasc Unit, UMR CNRS 6015-INSERM 1083, University of Angers, Angers, France
| | - R.H. van Jaarsveld
- Department of Genetics, University Medical Center Utrecht, Utrecht, the Netherlands
| | - A.M.A. Lachmeijer
- Department of Genetics, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Lyse Ruaud
- INSERM UMR1141, Neurodiderot, University of Paris, 75019 Paris, France,APHP.Nord, Robert Debré University Hospital, Department of Genetics, 75019 Paris, France
| | - Jonathan Levy
- APHP.Nord, Robert Debré University Hospital, Department of Genetics, 75019 Paris, France
| | - Anne-Claude Tabet
- APHP.Nord, Robert Debré University Hospital, Department of Genetics, 75019 Paris, France
| | - Rafal Ploski
- Department of Medical Genetics, Medical University of Warsaw, Warsaw, Poland
| | | | - Łukasz Kępczyński
- Department of Genetics, Polish Mother’s Memorial Hospital – Research Institute, Łódź, Poland
| | - Katarzyna Połatyńska
- Department of Developmental Neurology an Epileptology, Polish Mother’s Memorial Hospital – Research Institute, Łódź, Poland
| | - Yidan Li
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
| | - Jawid M. Fatih
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
| | - Dana Marafi
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
| | - Jill A. Rosenfeld
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA,Baylor Genetics, Houston, TX, USA
| | - Zeynep Coban-Akdemir
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
| | - Weimin Bi
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA,Baylor Genetics, Houston, TX, USA
| | - Richard A. Gibbs
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA,Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - Grace M. Hobson
- Department of Research, Nemours Children’s Health, Wilmington, DE, USA
| | - Jill V. Hunter
- E.B. Singleton Department of Pediatric Radiology, Texas Children’s Hospital, Houston, TX, USA
| | - Claudia M.B. Carvalho
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
| | - Jennifer E. Posey
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
| | - Elena V. Semina
- Department of Pediatrics and Children’s Research Institute, Medical College of Wisconsin and Children’s Wisconsin, Milwaukee, WI, USA,Departments of Ophthalmology and Visual Sciences and Cell Biology, Neurobiology and Anatomy, Medical College of Wisconsin, Milwaukee, WI, USA,Corresponding author
| | - James R. Lupski
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA,Department of Pediatrics, Baylor College of Medicine, Houston, TX, USA,Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA,Texas Children’s Hospital, Houston, TX, USA,Corresponding author
| |
Collapse
|
28
|
Schuy J, Grochowski CM, Carvalho CMB, Lindstrand A. Complex genomic rearrangements: an underestimated cause of rare diseases. Trends Genet 2022; 38:1134-1146. [PMID: 35820967 PMCID: PMC9851044 DOI: 10.1016/j.tig.2022.06.003] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2022] [Revised: 05/12/2022] [Accepted: 06/06/2022] [Indexed: 01/24/2023]
Abstract
Complex genomic rearrangements (CGRs) are known contributors to disease but are often missed during routine genetic screening. Identifying CGRs requires (i) identifying copy number variants (CNVs) concurrently with inversions, (ii) phasing multiple breakpoint junctions incis, as well as (iii) detecting and resolving structural variants (SVs) within repeats. We demonstrate how combining cytogenetics and new sequencing methodologies is being successfully applied to gain insights into the genomic architecture of CGRs. In addition, we review CGR patterns and molecular features revealed by studying constitutional genomic disorders. These data offer invaluable lessons to individuals interested in investigating CGRs, evaluating their clinical relevance and frequency, as well as assessing their impact(s) on rare genetic diseases.
Collapse
Affiliation(s)
- Jakob Schuy
- Department of Molecular Medicine and Surgery and Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
| | | | - Claudia M B Carvalho
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA; Pacific Northwest Research Institute, Seattle, WA, USA
| | - Anna Lindstrand
- Department of Molecular Medicine and Surgery and Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden; Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden.
| |
Collapse
|
29
|
Balasooriya GI, Spector DL. Allele-specific differential regulation of monoallelically expressed autosomal genes in the cardiac lineage. Nat Commun 2022; 13:5984. [PMID: 36216821 DOI: 10.1038/s41467-022-33722-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2021] [Accepted: 09/27/2022] [Indexed: 11/29/2022] Open
Abstract
Each mammalian autosomal gene is represented by two alleles in diploid cells. To our knowledge, no insights have been made in regard to allele-specific regulatory mechanisms of autosomes. Here we use allele-specific single cell transcriptomic analysis to elucidate the establishment of monoallelic gene expression in the cardiac lineage. We find that monoallelically expressed autosomal genes in mESCs and mouse blastocyst cells are differentially regulated based on the genetic background of the parental alleles. However, the genetic background of the allele does not affect the establishment of monoallelic genes in differentiated cardiomyocytes. Additionally, we observe epigenetic differences between deterministic and random autosomal monoallelic genes. Moreover, we also find a greater contribution of the maternal versus paternal allele to the development and homeostasis of cardiac tissue and in cardiac health, highlighting the importance of maternal influence in male cardiac tissue homeostasis. Our findings emphasize the significance of allele-specific insights into gene regulation in development, homeostasis and disease. The authors use allele-specific single cell transcriptomic analysis to elucidate the establishment of monoallelic gene expression in the cardiac lineage. The findings emphasize the importance of allele-specific insight into gene regulation in development, homeostasis and disease.
Collapse
|
30
|
Duan R, Hijazi H, Gulec EY, Eker HK, Costa SR, Sahin Y, Ocak Z, Isikay S, Ozalp O, Bozdogan S, Aslan H, Elcioglu N, Bertola DR, Gezdirici A, Du H, Fatih JM, Grochowski CM, Akay G, Jhangiani SN, Karaca E, Gu S, Coban-Akdemir Z, Posey JE, Bayram Y, Sutton VR, Carvalho CM, Pehlivan D, Gibbs RA, Lupski JR. Developmental genomics of limb malformations: Allelic series in association with gene dosage effects contribute to the clinical variability. Human Genetics and Genomics Advances 2022; 3:100132. [PMID: 36035248 PMCID: PMC9403727 DOI: 10.1016/j.xhgg.2022.100132] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2022] [Accepted: 07/19/2022] [Indexed: 11/26/2022] Open
Abstract
Genetic heterogeneity, reduced penetrance, and variable expressivity, the latter including asymmetric body axis plane presentations, have all been described in families with congenital limb malformations (CLMs). Interfamilial and intrafamilial heterogeneity highlight the complexity of the underlying genetic pathogenesis of these developmental anomalies. Family-based genomics by exome sequencing (ES) and rare variant analyses combined with whole-genome array-based comparative genomic hybridization were implemented to investigate 18 families with limb birth defects. Eleven of 18 (61%) families revealed explanatory variants, including 7 single-nucleotide variant alleles and 3 copy number variants (CNVs), at previously reported “disease trait associated loci”: BHLHA9, GLI3, HOXD cluster, HOXD13, NPR2, and WNT10B. Breakpoint junction analyses for all three CNV alleles revealed mutational signatures consistent with microhomology-mediated break-induced replication, a mechanism facilitated by Alu/Alu-mediated rearrangement. Homozygous duplication of BHLHA9 was observed in one Turkish kindred and represents a novel contributory genetic mechanism to Gollop-Wolfgang Complex (MIM: 228250), where triplication of the locus has been reported in one family from Japan (i.e., 4n = 2n + 2n versus 4n = 3n + 1n allelic configurations). Genes acting on limb patterning are sensitive to a gene dosage effect and are often associated with an allelic series. We extend an allele-specific gene dosage model to potentially assist, in an adjuvant way, interpretations of interconnections among an allelic series, clinical severity, and reduced penetrance of the BHLHA9-related CLM spectrum.
Collapse
|
31
|
Yuan B, Schulze KV, Assia Batzir N, Sinson J, Dai H, Zhu W, Bocanegra F, Fong CT, Holder J, Nguyen J, Schaaf CP, Yang Y, Bi W, Eng C, Shaw C, Lupski JR, Liu P. Sequencing individual genomes with recurrent genomic disorder deletions: an approach to characterize genes for autosomal recessive rare disease traits. Genome Med 2022; 14:113. [PMID: 36180924 PMCID: PMC9526336 DOI: 10.1186/s13073-022-01113-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2021] [Accepted: 09/02/2022] [Indexed: 11/25/2022] Open
Abstract
BACKGROUND In medical genetics, discovery and characterization of disease trait contributory genes and alleles depends on genetic reasoning, study design, and patient ascertainment; we suggest a segmental haploid genetics approach to enhance gene discovery and molecular diagnostics. METHODS We constructed a genome-wide map for nonallelic homologous recombination (NAHR)-mediated recurrent genomic deletions and used this map to estimate population frequencies of NAHR deletions based on large-scale population cohorts and region-specific studies. We calculated recessive disease carrier burden using high-quality pathogenic or likely pathogenic variants from ClinVar and gnomAD. We developed a NIRD (NAHR deletion Impact to Recessive Disease) score for recessive disorders by quantifying the contribution of NAHR deletion to the overall allele load that enumerated all pairwise combinations of disease-causing alleles; we used a Punnett square approach based on an assumption of random mating. Literature mining was conducted to identify all reported patients with defects in a gene with a high NIRD score; meta-analysis was performed on these patients to estimate the representation of NAHR deletions in recessive traits from contemporary human genomics studies. Retrospective analyses of extant clinical exome sequencing (cES) were performed for novel rare recessive disease trait gene and allele discovery from individuals with NAHR deletions. RESULTS We present novel genomic insights regarding the genome-wide impact of NAHR recurrent segmental variants on recessive disease burden; we demonstrate the utility of NAHR recurrent deletions to enhance discovery in the challenging context of autosomal recessive (AR) traits and biallelic variation. Computational results demonstrate new mutations mediated by NAHR, involving recurrent deletions at 30 genomic regions, likely drive recessive disease burden for over 74% of loci within these segmental deletions or at least 2% of loci genome-wide. Meta-analyses on 170 literature-reported patients implicate that NAHR deletions are depleted from the ascertained pool of AR trait alleles. Exome reanalysis of personal genomes from subjects harboring recurrent deletions uncovered new disease-contributing variants in genes including COX10, ERCC6, PRRT2, and OTUD7A. CONCLUSIONS Our results demonstrate that genomic sequencing of personal genomes with NAHR deletions could dramatically improve allele and gene discovery and enhance clinical molecular diagnosis. Moreover, results suggest NAHR events could potentially enable human haploid genetic screens as an approach to experimental inquiry into disease biology.
Collapse
Affiliation(s)
- Bo Yuan
- grid.39382.330000 0001 2160 926XDepartment of Molecular and Human Genetics, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030 USA ,grid.39382.330000 0001 2160 926XHuman Genome Sequencing Center, Baylor College of Medicine, Houston, TX USA
| | - Katharina V. Schulze
- grid.39382.330000 0001 2160 926XDepartment of Molecular and Human Genetics, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030 USA ,grid.510928.7Baylor Genetics, Houston, TX USA
| | - Nurit Assia Batzir
- grid.39382.330000 0001 2160 926XDepartment of Molecular and Human Genetics, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030 USA
| | - Jefferson Sinson
- grid.39382.330000 0001 2160 926XDepartment of Molecular and Human Genetics, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030 USA
| | - Hongzheng Dai
- grid.39382.330000 0001 2160 926XDepartment of Molecular and Human Genetics, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030 USA ,grid.510928.7Baylor Genetics, Houston, TX USA
| | - Wenmiao Zhu
- grid.39382.330000 0001 2160 926XDepartment of Molecular and Human Genetics, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030 USA ,grid.510928.7Baylor Genetics, Houston, TX USA
| | | | - Chin-To Fong
- grid.412750.50000 0004 1936 9166Department of Pediatrics, University of Rochester Medical Center, Rochester, NY USA
| | - Jimmy Holder
- grid.39382.330000 0001 2160 926XDepartment of Pediatrics, Baylor College of Medicine, Houston, TX USA
| | - Joanne Nguyen
- grid.267308.80000 0000 9206 2401Department of Pediatrics, University of Texas Health Science Center, Houston, TX USA
| | - Christian P. Schaaf
- grid.39382.330000 0001 2160 926XDepartment of Molecular and Human Genetics, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030 USA ,grid.7700.00000 0001 2190 4373Institute of Human Genetics, Heidelberg University, Heidelberg, Germany
| | - Yaping Yang
- grid.39382.330000 0001 2160 926XDepartment of Molecular and Human Genetics, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030 USA
| | - Weimin Bi
- grid.39382.330000 0001 2160 926XDepartment of Molecular and Human Genetics, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030 USA ,grid.510928.7Baylor Genetics, Houston, TX USA
| | - Christine Eng
- grid.39382.330000 0001 2160 926XDepartment of Molecular and Human Genetics, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030 USA ,grid.510928.7Baylor Genetics, Houston, TX USA
| | - Chad Shaw
- grid.39382.330000 0001 2160 926XDepartment of Molecular and Human Genetics, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030 USA ,grid.21940.3e0000 0004 1936 8278Department of Statistics, Rice University, Houston, TX USA
| | - James R. Lupski
- grid.39382.330000 0001 2160 926XDepartment of Molecular and Human Genetics, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030 USA ,grid.39382.330000 0001 2160 926XHuman Genome Sequencing Center, Baylor College of Medicine, Houston, TX USA ,grid.39382.330000 0001 2160 926XDepartment of Pediatrics, Baylor College of Medicine, Houston, TX USA ,grid.416975.80000 0001 2200 2638Texas Children’s Hospital, Houston, TX USA
| | - Pengfei Liu
- Department of Molecular and Human Genetics, Baylor College of Medicine, One Baylor Plaza, Houston, TX, 77030, USA. .,Baylor Genetics, Houston, TX, USA.
| |
Collapse
|
32
|
Young JL, Halley MC, Anguiano B, Fernandez L, Bernstein JA, Wheeler MT, Tabor HK. Beyond race: Recruitment of diverse participants in clinical genomics research for rare disease. Front Genet 2022; 13:949422. [PMID: 36072659 PMCID: PMC9441547 DOI: 10.3389/fgene.2022.949422] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2022] [Accepted: 07/11/2022] [Indexed: 11/13/2022] Open
Abstract
Purpose: Despite recent attention to increasing diversity in clinical genomics research, researchers still struggle to recruit participants from varied sociodemographic backgrounds. We examined the experiences of parents from diverse backgrounds with enrolling their children in clinical genomics research on rare diseases. We explored the barriers and facilitators parents encountered and possible impacts of sociodemographic factors on their access to research.Methods: We utilized semi-structured interviews with parents of children participating in the Undiagnosed Diseases Network. Interview data were analyzed using comparative content analysis.Results: We interviewed 13 Hispanic, 11 non-Hispanic White, four Asian, and two biracial parents. Participants discussed different pathways to clinical genomics research for rare disease as well as how sociodemographic factors shaped families’ access. Themes focused on variation in: 1) reliance on providers to access research; 2) cultural norms around health communication; 3) the role of social capital in streamlining access; and 4) the importance of language-concordant research engagement.Conclusion: Our findings suggest that variables beyond race/ethnicity may influence access in clinical genomics research. Future efforts to diversify research participation should consider utilizing varied recruitment strategies to reach participants with diverse sociodemographic characteristics.
Collapse
Affiliation(s)
- Jennifer L. Young
- Stanford Center for Biomedical Ethics, Stanford University School of Medicine, Stanford, CA, United States
- Center for Genetic Medicine, Northwestern Feinberg School of Medicine, Chicago, IL, United States
- *Correspondence: Jennifer L. Young,
| | - Meghan C. Halley
- Stanford Center for Biomedical Ethics, Stanford University School of Medicine, Stanford, CA, United States
| | - Beatriz Anguiano
- Human Genetics and Genetic Counseling, Stanford University School of Medicine, Stanford, CA, United States
| | - Liliana Fernandez
- Stanford Center for Undiagnosed Diseases, Stanford University, Stanford, CA, United States
| | - Jonathan A. Bernstein
- Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, United States
| | - Matthew T. Wheeler
- Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, CA, United States
| | - Holly K. Tabor
- Stanford Center for Biomedical Ethics, Stanford University School of Medicine, Stanford, CA, United States
- Department of Medicine, Stanford University, Stanford, CA, United States
| | | |
Collapse
|
33
|
Jacobsen JOB, Kelly C, Cipriani V, Research Consortium GE, Mungall CJ, Reese J, Danis D, Robinson PN, Smedley D. Phenotype-driven approaches to enhance variant prioritization and diagnosis of rare disease. Hum Mutat 2022; 43:1071-1081. [PMID: 35391505 PMCID: PMC9288531 DOI: 10.1002/humu.24380] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2021] [Revised: 01/25/2022] [Accepted: 04/03/2022] [Indexed: 11/20/2022]
Abstract
Rare disease diagnostics and disease gene discovery have been revolutionized by whole-exome and genome sequencing but identifying the causative variant(s) from the millions in each individual remains challenging. The use of deep phenotyping of patients and reference genotype-phenotype knowledge, alongside variant data such as allele frequency, segregation, and predicted pathogenicity, has proved an effective strategy to tackle this issue. Here we review the numerous tools that have been developed to automate this approach and demonstrate the power of such an approach on several thousand diagnosed cases from the 100,000 Genomes Project. Finally, we discuss the challenges that need to be overcome if we are going to improve detection rates and help the majority of patients that still remain without a molecular diagnosis after state-of-the-art genomic interpretation.
Collapse
Affiliation(s)
- Julius O. B. Jacobsen
- William Harvey Research Institute, Charterhouse Square, Barts and the London School of Medicine and Dentistry QueenQueen Mary University of LondonLondonUK
| | - Catherine Kelly
- William Harvey Research Institute, Charterhouse Square, Barts and the London School of Medicine and Dentistry QueenQueen Mary University of LondonLondonUK
| | - Valentina Cipriani
- William Harvey Research Institute, Charterhouse Square, Barts and the London School of Medicine and Dentistry QueenQueen Mary University of LondonLondonUK
| | | | - Christopher J. Mungall
- Environmental Genomics and Systems Biology, Lawrence Berkeley National LaboratoryBerkeleyCaliforniaUSA
| | - Justin Reese
- Environmental Genomics and Systems Biology, Lawrence Berkeley National LaboratoryBerkeleyCaliforniaUSA
| | - Daniel Danis
- The Jackson Laboratory for Genomic MedicineFarmingtonConnecticutUSA
| | | | - Damian Smedley
- William Harvey Research Institute, Charterhouse Square, Barts and the London School of Medicine and Dentistry QueenQueen Mary University of LondonLondonUK
| |
Collapse
|
34
|
Seaby EG, Smedley D, Taylor Tavares AL, Brittain H, van Jaarsveld RH, Baralle D, Rehm HL, O'Donnell-Luria A, Ennis S. A gene-to-patient approach uplifts novel disease gene discovery and identifies 18 putative novel disease genes. Genet Med 2022; 24:1697-1707. [PMID: 35532742 DOI: 10.1016/j.gim.2022.04.019] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2022] [Revised: 04/14/2022] [Accepted: 04/14/2022] [Indexed: 12/14/2022] Open
Abstract
PURPOSE Exome and genome sequencing have drastically accelerated novel disease gene discoveries. However, discovery is still hindered by myriad variants of uncertain significance found in genes of undetermined biological function. This necessitates intensive functional experiments on genes of equal predicted causality, leading to a major bottleneck. METHODS We apply the loss-of-function observed/expected upper-bound fraction metric of intolerance to gene inactivation to curate a list of predicted haploinsufficient disease genes. Using data from the 100,000 Genomes Project, we adopt a gene-to-patient approach that matches de novo loss-of-function variants in constrained genes to patients with rare disease. Through large-scale aggregation of data, we reduce excess analytical noise currently hindering novel discoveries. RESULTS Results from 13,949 trios revealed 643 rare, de novo predicted loss-of-function events filtered from 1044 loss-of-function observed/expected upper-bound fraction-constrained genes. A total of 168 variants occurred within 126 genes without a known disease-gene relationship. Of these, 27 genes had >1 kindred affected, and for 18 of these genes, multiple kindreds had overlapping phenotypes. Two years after initial analysis, 11 of 18 (61%) of these genes have been independently published as novel disease gene discoveries. CONCLUSION Using large cohorts and adopting gene-based approaches can rapidly and objectively accelerate dominantly inherited novel gene discovery by targeting the most appropriate genes for functional validation.
Collapse
Affiliation(s)
- Eleanor G Seaby
- Human Development and Health, Faculty of Medicine, University of Southampton, Southampton, United Kingdom; Program in Medical and Population Genetics, Broad institute of MIT and Harvard, Boston, MA; Center for Genomic Medicine, Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA; Division of Genetics and Genomics, Boston Children's Hospital, Boston, MA.
| | - Damian Smedley
- Genomics England, Dawson Hall, Charterhouse Square, London, EC1M 6BQ, United Kingdom
| | | | - Helen Brittain
- Genomics England, Dawson Hall, Charterhouse Square, London, EC1M 6BQ, United Kingdom
| | | | - Diana Baralle
- Human Development and Health, Faculty of Medicine, University of Southampton, Southampton, United Kingdom
| | - Heidi L Rehm
- Program in Medical and Population Genetics, Broad institute of MIT and Harvard, Boston, MA; Center for Genomic Medicine, Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA
| | - Anne O'Donnell-Luria
- Program in Medical and Population Genetics, Broad institute of MIT and Harvard, Boston, MA; Center for Genomic Medicine, Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA; Division of Genetics and Genomics, Boston Children's Hospital, Boston, MA
| | - Sarah Ennis
- Human Development and Health, Faculty of Medicine, University of Southampton, Southampton, United Kingdom
| | | |
Collapse
|
35
|
Stutterd CA, Vanderver A, Lockhart PJ, Helman G, Pope K, Uebergang E, Love C, Delatycki MB, Thorburn D, Mackay MT, Peters H, Kornberg AJ, Patel C, Rodriguez-Casero V, Waak M, Silberstein J, Sinclair A, Nolan M, Field M, Davis MR, Fahey M, Scheffer IE, Freeman JL, Wolf NI, Taft RJ, van der Knaap MS, Simons C, Leventer RJ. Unclassified white matter disorders: A diagnostic journey requiring close collaboration between clinical and laboratory services. Eur J Med Genet 2022; 65:104551. [PMID: 35803560 DOI: 10.1016/j.ejmg.2022.104551] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2022] [Revised: 05/27/2022] [Accepted: 06/18/2022] [Indexed: 11/26/2022]
Abstract
BACKGROUND Next generation sequencing studies have revealed an ever-increasing number of causes for genetic disorders of central nervous system white matter. A substantial number of disorders are identifiable from their specific pattern of biochemical and/or imaging findings for which single gene testing may be indicated. Beyond this group, the causes of genetic white matter disorders are unclear and a broader approach to genomic testing is recommended. AIM This study aimed to identify the genetic causes for a group of individuals with unclassified white matter disorders with suspected genetic aetiology and highlight the investigations required when the initial testing is non-diagnostic. METHODS Twenty-six individuals from 22 families with unclassified white matter disorders underwent deep phenotyping and genome sequencing performed on trio, or larger, family groups. Functional studies and transcriptomics were used to resolve variants of uncertain significance with potential clinical relevance. RESULTS Causative or candidate variants were identified in 15/22 (68.2%) families. Six of the 15 implicated genes had been previously associated with white matter disease (COL4A1, NDUFV1, SLC17A5, TUBB4A, BOLA3, DARS2). Patients with variants in the latter two presented with an atypical phenotype. The other nine genes had not been specifically associated with white matter disease at the time of diagnosis and included genes associated with monogenic syndromes, developmental disorders, and developmental and epileptic encephalopathies (STAG2, LSS, FIG4, GLS, PMPCA, SPTBN1, AGO2, SCN2A, SCN8A). Consequently, only 46% of the diagnoses would have been made via a current leukodystrophy gene panel test. DISCUSSION These results confirm the importance of broad genomic testing for patients with white matter disorders. The high diagnostic yield reflects the integration of deep phenotyping, whole genome sequencing, trio analysis, functional studies, and transcriptomic analyses. CONCLUSIONS Genetic white matter disorders are genetically and phenotypically heterogeneous. Deep phenotyping together with a range of genomic technologies underpin the identification of causes of unclassified white matter disease. A molecular diagnosis is essential for prognostication, appropriate management, and accurate reproductive counseling.
Collapse
Affiliation(s)
- C A Stutterd
- Murdoch Children's Research Institute, Victoria, Australia; Department of Neurology, Royal Children's Hospital, Victoria, Australia; Victorian Clinical Genetics Services, Murdoch Children's Research Institute, Victoria, Australia; Department of Paediatrics, University of Melbourne, Victoria, Australia
| | - A Vanderver
- Division of Neurology, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA; Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - P J Lockhart
- Murdoch Children's Research Institute, Victoria, Australia; Department of Paediatrics, University of Melbourne, Victoria, Australia
| | - G Helman
- Institute for Molecular Bioscience, University of Queensland, St. Lucia, Queensland, Australia
| | - K Pope
- Murdoch Children's Research Institute, Victoria, Australia
| | - E Uebergang
- Murdoch Children's Research Institute, Victoria, Australia
| | - C Love
- Murdoch Children's Research Institute, Victoria, Australia
| | - M B Delatycki
- Murdoch Children's Research Institute, Victoria, Australia; Victorian Clinical Genetics Services, Murdoch Children's Research Institute, Victoria, Australia; Department of Paediatrics, University of Melbourne, Victoria, Australia
| | - D Thorburn
- Murdoch Children's Research Institute, Victoria, Australia; Department of Paediatrics, University of Melbourne, Victoria, Australia
| | - M T Mackay
- Murdoch Children's Research Institute, Victoria, Australia; Department of Neurology, Royal Children's Hospital, Victoria, Australia; Department of Paediatrics, University of Melbourne, Victoria, Australia
| | - H Peters
- Murdoch Children's Research Institute, Victoria, Australia; Department of Paediatrics, University of Melbourne, Victoria, Australia; Department of Metabolic Medicine, Royal Children's Hospital, Victoria, Australia
| | - A J Kornberg
- Murdoch Children's Research Institute, Victoria, Australia; Department of Neurology, Royal Children's Hospital, Victoria, Australia; Department of Paediatrics, University of Melbourne, Victoria, Australia
| | - C Patel
- Genetic Health Queensland, Royal Brisbane and Women's Children's Hospital, South Brisbane Queensland, Australia; Centre for Children's Health Research, The University of Queensland, Queensland, Australia
| | - V Rodriguez-Casero
- Murdoch Children's Research Institute, Victoria, Australia; Department of Neurology, Royal Children's Hospital, Victoria, Australia; Department of Paediatrics, University of Melbourne, Victoria, Australia
| | - M Waak
- Centre for Children's Health Research, The University of Queensland, Queensland, Australia; Department of Neurosciences, Queensland Children's Hospital, Brisbane, Queensland, Australia
| | - J Silberstein
- Princess Margaret Hospital, Perth, Western Australia, Australia
| | - A Sinclair
- Department of Neurosciences, Queensland Children's Hospital, Brisbane, Queensland, Australia
| | - M Nolan
- Department of Paediatric Neurology, Starship Children's Health, Auckland, New Zealand
| | - M Field
- Genetics of Learning Disability (GOLD) Service, Hunter Genetics, Newcastle, New South Wales, Australia
| | - M R Davis
- Department of Diagnostic Genomics, Path West Laboratory Medicine, QEII Medical Centre, Hospital Avenue, Nedlands, WA, Australia
| | - M Fahey
- Department of Paediatrics, Monash University, Victoria, Australia
| | - I E Scheffer
- Murdoch Children's Research Institute, Victoria, Australia; Department of Neurology, Royal Children's Hospital, Victoria, Australia; Department of Paediatrics, University of Melbourne, Victoria, Australia; Department of Medicine, The University of Melbourne, Austin Health, Heidelberg, Victoria, 3084, Australia; The Florey Institute of Neuroscience and Mental Health and Murdoch Children's Research Institute, Parkville, Victoria, 3052, Australia
| | - J L Freeman
- Murdoch Children's Research Institute, Victoria, Australia; Department of Neurology, Royal Children's Hospital, Victoria, Australia; Department of Paediatrics, University of Melbourne, Victoria, Australia
| | - N I Wolf
- Amsterdam Leukodystrophy Center, Department of Child Neurology, Emma Children's Hospital, Amsterdam University Medical Centers, VU University, Amsterdam Neuroscience, Amsterdam, the Netherlands; Department of Functional Genomics, Center for Neurogenomics and Cognitive Research, VU University, Amsterdam, the Netherlands
| | - R J Taft
- Illumina Inc, San Diego, CA, USA
| | - M S van der Knaap
- Amsterdam Leukodystrophy Center, Department of Child Neurology, Emma Children's Hospital, Amsterdam University Medical Centers, VU University, Amsterdam Neuroscience, Amsterdam, the Netherlands; Department of Functional Genomics, Center for Neurogenomics and Cognitive Research, VU University, Amsterdam, the Netherlands
| | - C Simons
- Murdoch Children's Research Institute, Victoria, Australia; Department of Paediatrics, University of Melbourne, Victoria, Australia.
| | - R J Leventer
- Murdoch Children's Research Institute, Victoria, Australia; Department of Neurology, Royal Children's Hospital, Victoria, Australia; Department of Paediatrics, University of Melbourne, Victoria, Australia.
| |
Collapse
|
36
|
Tuteja S, Kadri S, Yap KL. A performance evaluation study: Variant annotation tools - The enigma of clinical next generation sequencing (NGS) based genetic testing. J Pathol Inform 2022; 13:100130. [PMID: 36268089 PMCID: PMC9577137 DOI: 10.1016/j.jpi.2022.100130] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2022] [Revised: 07/25/2022] [Accepted: 07/25/2022] [Indexed: 12/03/2022] Open
Abstract
Dramatically expanding our ability for clinical genetic testing for inherited conditions and complex diseases such as cancer, next generation sequencing (NGS) technologies are allowing for rapid interrogation of thousands of genes and identification of millions of variants. Variant annotation, the process of assigning functional information to DNA variants based on the standardized Human Genome Variation Society (HGVS) nomenclature, is a fundamental challenge in the analysis of NGS data that has led to the development of many bioinformatic algorithms. In this study, we evaluated the performance of 3 variant annotation tools: Alamut® Batch, Ensembl Variant Effect Predictor (VEP), and ANNOVAR, benchmarked by a manually curated ground-truth set of 298 variants from the medical exome database at the Molecular Diagnostics Laboratory at Lurie Children's Hospital. Of the 3 tools, VEP produces the most accurate variant annotations (HGVS nomenclature for 297 of the 298 variants) due to usage of updated gene transcript versions within the algorithm. Alamut® Batch called 296 of the 298 variants correctly; strikingly, ANNOVAR exhibited the greatest number of discrepancies (20 of the 298 variants, 93.3% concordance with ground-truth set). Adoption of validated methods of variant annotation is critical in post-analytical phases of clinical testing.
Collapse
Affiliation(s)
- Sachleen Tuteja
- Illinois Mathematics and Science Academy, 1500 Sullivan Road, Aurora, IL 60506, USA
| | - Sabah Kadri
- Department of Pathology and Laboratory Medicine, Ann and Robert H. Lurie Children's Hospital of Chicago, 225 E. Chicago Ave, Chicago, IL 60611, USA
- Department of Pathology, Northwestern University Feinberg School of Medicine, 420 E. Superior St, Chicago, IL 606011, USA
| | - Kai Lee Yap
- Department of Pathology and Laboratory Medicine, Ann and Robert H. Lurie Children's Hospital of Chicago, 225 E. Chicago Ave, Chicago, IL 60611, USA
- Department of Pathology, Northwestern University Feinberg School of Medicine, 420 E. Superior St, Chicago, IL 606011, USA
- Corresponding author at: Molecular Diagnostics, Department of Pathology & Laboratory Medicine, Ann & Robert H. Lurie Children's Hospital of Chicago, Northwestern Feinberg School of Medicine, 225 E. Chicago Ave, Box 82, Chicago, IL 60611, USA.
| |
Collapse
|
37
|
Rodrigues EDS, Griffith S, Martin R, Antonescu C, Posey JE, Coban‐Akdemir Z, Jhangiani SN, Doheny KF, Lupski JR, Valle D, Bamshad MJ, Hamosh A, Sheffer A, Chong JX, Einhorn Y, Cupak M, Sobreira N. Variant-level matching for diagnosis and discovery: Challenges and opportunities. Hum Mutat 2022; 43:782-790. [PMID: 35191117 PMCID: PMC9133151 DOI: 10.1002/humu.24359] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2021] [Revised: 02/15/2022] [Accepted: 02/18/2022] [Indexed: 11/30/2022]
Abstract
Here we describe MyGene2, Geno2MP, VariantMatcher, and Franklin; databases that provide variant-level information and phenotypic features to researchers, clinicians, healthcare providers and patients. Following the footsteps of the Matchmaker Exchange project that connects exome, genome, and phenotype databases at the gene level, these databases have as one goal to facilitate connection to one another using Data Connect, a standard for discovery and search of biomedical data from the Global Alliance for Genomics and Health (GA4GH).
Collapse
Affiliation(s)
- Eliete da S. Rodrigues
- McKusick‐Nathans Department of Genetic MedicineJohns Hopkins University School of MedicineBaltimoreMarylandUSA
| | - Sean Griffith
- McKusick‐Nathans Department of Genetic MedicineJohns Hopkins University School of MedicineBaltimoreMarylandUSA
| | - Renan Martin
- McKusick‐Nathans Department of Genetic MedicineJohns Hopkins University School of MedicineBaltimoreMarylandUSA
| | - Corina Antonescu
- McKusick‐Nathans Department of Genetic MedicineJohns Hopkins University School of MedicineBaltimoreMarylandUSA
| | - Jennifer E. Posey
- Department of Molecular and Human GeneticsBaylor College of MedicineHoustonTexasUSA
| | - Zeynep Coban‐Akdemir
- Department of Molecular and Human GeneticsBaylor College of MedicineHoustonTexasUSA
| | - Shalini N. Jhangiani
- Department of Molecular and Human GeneticsBaylor College of MedicineHoustonTexasUSA
- Human Genome Sequencing CenterBaylor College of MedicineHoustonTexasUSA
| | - Kimberly F. Doheny
- McKusick‐Nathans Department of Genetic MedicineJohns Hopkins University School of MedicineBaltimoreMarylandUSA
| | - James R. Lupski
- Department of Molecular and Human GeneticsBaylor College of MedicineHoustonTexasUSA
- Human Genome Sequencing CenterBaylor College of MedicineHoustonTexasUSA
- Department of PediatricsBaylor College of MedicineHoustonTexasUSA
- Texas Children's HospitalHoustonTexasUSA
| | - David Valle
- McKusick‐Nathans Department of Genetic MedicineJohns Hopkins University School of MedicineBaltimoreMarylandUSA
| | - Michael J. Bamshad
- Division of Genetic Medicine, Department of PediatricsUniversity of WashingtonSeattleWashingtonUSA
- Brotman Baty Institute for Precision MedicineSeattleWashingtonUSA
| | - Ada Hamosh
- McKusick‐Nathans Department of Genetic MedicineJohns Hopkins University School of MedicineBaltimoreMarylandUSA
| | | | - Jessica X. Chong
- Division of Genetic Medicine, Department of PediatricsUniversity of WashingtonSeattleWashingtonUSA
- Brotman Baty Institute for Precision MedicineSeattleWashingtonUSA
| | | | | | - Nara Sobreira
- McKusick‐Nathans Department of Genetic MedicineJohns Hopkins University School of MedicineBaltimoreMarylandUSA
| |
Collapse
|
38
|
Arbustini E, Behr ER, Carrier L, van Duijn C, Evans P, Favalli V, van der Harst P, Haugaa KH, Jondeau G, Kääb S, Kaski JP, Kavousi M, Loeys B, Pantazis A, Pinto Y, Schunkert H, Di Toro A, Thum T, Urtis M, Waltenberger J, Elliott P. Interpretation and actionability of genetic variants in cardiomyopathies: a position statement from the European Society of Cardiology Council on cardiovascular genomics. Eur Heart J 2022; 43:1901-1916. [PMID: 35089333 DOI: 10.1093/eurheartj/ehab895] [Citation(s) in RCA: 28] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/22/2021] [Revised: 12/03/2021] [Accepted: 12/20/2021] [Indexed: 11/13/2022] Open
Abstract
This document describes the contribution of clinical criteria to the interpretation of genetic variants using heritable Mendelian cardiomyopathies as an example. The aim is to assist cardiologists in defining the clinical contribution to a genetic diagnosis and the interpretation of molecular genetic reports. The identification of a genetic variant of unknown or uncertain significance is a limitation of genetic testing, but current guidelines for the interpretation of genetic variants include essential contributions from clinical family screening that can establish a de novo assignment of the variant or its segregation with the phenotype in the family. A partnership between clinicians and patients helps to solve major uncertainties and provides reliable and clinically actionable information.
Collapse
Affiliation(s)
- Eloisa Arbustini
- Transplant Research Area and Centre for Inherited Cardiovascular Diseases, Department of Medical Sciences and Infectious Diseases, Fondazione IRCCS Policlinico San Matteo, Pavia, Italy
| | - Elijah R Behr
- Cardiology Research Section and Cardiovascular Clinical Academic Group, Institute of Molecular and Clinical Sciences, St George's, University of London and St George's University Hospitals NHS Foundation Trust, London, UK
| | - Lucie Carrier
- Institute of Experimental Pharmacology and Toxicology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
- DZHK (German Centre for Cardiovascular Research), Partner Site Hamburg/Kiel/Lübeck, Hamburg, Germany
| | - Cornelia van Duijn
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Paul Evans
- Department of Infection, Immunity and Cardiovascular Disease, and INSIGNEO Institute, University of Sheffield, Sheffield S10 2RX, UK
| | | | - Pim van der Harst
- Department of Cardiology, Division of Heart and Lungs, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Kristina Hermann Haugaa
- ProCardio Center for Innovation, Department of Cardiology, Oslo University Hospital, Rikshospitalet, Postboks 4950 Nydalen, Oslo 0424, Norway
- University of Oslo, Boks 1072 Blindern, Oslo 0316, Norway
| | - Guillaume Jondeau
- CNMR Syndrome de Marfan et apparentés, Member of VASCERN, AP-HP Hopital Bichat, Service de Cardiologie, 46 rue Henri Huchard, Paris 75018, France
- INSERM LVTS U1148, Paris 75018, France
- Université de Paris, Paris, France
| | - Stefan Kääb
- Medizinische Klinik und Poliklinik I, LMU University Hospital Munich, Munich, Germany
- German Center for Cardiovascular Research, Munich Heart Alliance, Munich, Germany
| | - Juan Pablo Kaski
- Institute of Cardiovascular Science, University College London, London, UK
- Centre for Inherited Cardiovascular Diseases, Great Ormond Street Hospital, London, UK
| | - Maryam Kavousi
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Bart Loeys
- Cardiogenomics, Center for Medical Genetics, Antwerp University Hospital/University of Antwerp, Antwerp, Belgium
- Department of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Antonis Pantazis
- The Royal Brompton and Harefield Hospitals, Part of Guy's and St Thomas' NHS Foundation Trust, London, UK
| | - Yigal Pinto
- Department of Experimental Cardiology, University of Amsterdam, Amsterdam University Medical Center, Meibergdreef 15, Amsterdam 1105 AZ, The Netherlands
| | - Heribert Schunkert
- Department of Cardiology, Deutsches Herzzentrum München, Technische Universität München, München, Germany
- Deutsches Zentrum für Herz- und Kreislaufforschung (DZHK), Munich Heart Alliance, Munich, Germany
| | - Alessandro Di Toro
- Transplant Research Area and Centre for Inherited Cardiovascular Diseases, Department of Medical Sciences and Infectious Diseases, Fondazione IRCCS Policlinico San Matteo, Pavia, Italy
| | - Thomas Thum
- Institute of Molecular and Translational Therapeutic Strategies (IMTTS), Hannover Medical School, Hannover, Germany
- Fraunhofer Institute of Toxicology and Experimental Medicine (ITEM), Hannover, Germany
| | - Mario Urtis
- Transplant Research Area and Centre for Inherited Cardiovascular Diseases, Department of Medical Sciences and Infectious Diseases, Fondazione IRCCS Policlinico San Matteo, Pavia, Italy
| | - Johannes Waltenberger
- Department of Cardiology and Cardiovascular Medicine, Medical Faculty, University of Münster, Münster, Germany
- Cardiovascular Medicine, Hirslanden Klinik Im Park, Seestrasse 220, Zürich 8027, Switzerland
| | - Perry Elliott
- Barts Heart Centre St Bartholomew's Hospital, London, UK
- Institute for Cardiovascular Science, University College London, London, UK
| |
Collapse
|
39
|
Trinh J, Lüth T, Schaake S, Laabs BH, Schlüter K, Laβ J, Pozojevic J, Tse R, König I, Jamora RD, Rosales RL, Brüggemann N, Saranza G, Diesta CCE, Kaiser FJ, Depienne C, Pearson CE, Westenberger A, Klein C. Mosaic divergent repeat interruptions in XDP influence repeat stability and disease onset. Brain 2022; 146:1075-1082. [PMID: 35481544 PMCID: PMC9976955 DOI: 10.1093/brain/awac160] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2022] [Revised: 03/14/2022] [Accepted: 04/14/2022] [Indexed: 11/14/2022] Open
Abstract
While many genetic causes of movement disorders have been identified, modifiers of disease expression are largely unknown. X-linked dystonia-parkinsonism (XDP) is a neurodegenerative disease caused by a SINE-VNTR-Alu(AGAGGG)n retrotransposon insertion in TAF1, with a polymorphic (AGAGGG)n repeat. Repeat length and variants in MSH3 and PMS2 explain ∼65% of the variance in age at onset (AAO) in XDP. However, additional genetic modifiers are conceivably at play in XDP, such as repeat interruptions. Long-read nanopore sequencing of PCR amplicons from XDP patients (n = 202) was performed to assess potential repeat interruption and instability. Repeat-primed PCR and Cas9-mediated targeted enrichment confirmed the presence of identified divergent repeat motifs. In addition to the canonical pure SINE-VNTR-Alu-5'-(AGAGGG)n, we observed a mosaic of divergent repeat motifs that polarized at the beginning of the tract, where the divergent repeat interruptions varied in motif length by having one, two, or three nucleotides fewer than the hexameric motif, distinct from interruptions in other disease-associated repeats, which match the lengths of the canonical motifs. All divergent configurations occurred mosaically and in two investigated brain regions (basal ganglia, cerebellum) and in blood-derived DNA from the same patient. The most common divergent interruption was AGG [5'-SINE-VNTR-Alu(AGAGGG)2AGG(AGAGGG)n], similar to the pure tract, followed by AGGG [5'-SINE-VNTR-Alu(AGAGGG)2AGGG(AGAGGG)n], at median frequencies of 0.425 (IQR: 0.42-0.43) and 0.128 (IQR: 0.12-0.13), respectively. The mosaic AGG motif was not associated with repeat number (estimate = -3.8342, P = 0.869). The mosaic pure tract frequency was associated with repeat number (estimate = 45.32, P = 0.0441) but not AAO (estimate = -41.486, P = 0.378). Importantly, the mosaic frequency of the AGGG negatively correlated with repeat number after adjusting for age at sampling (estimate = -161.09, P = 3.44 × 10-5). When including the XDP-relevant MSH3/PMS2 modifier single nucleotide polymorphisms into the model, the mosaic AGGG frequency was associated with AAO (estimate = 155.1063, P = 0.047); however, the association dissipated after including the repeat number (estimate = -92.46430, P = 0.079). We reveal novel mosaic divergent repeat interruptions affecting both motif length and sequence (DRILS) of the canonical motif polarized within the SINE-VNTR-Alu(AGAGGG)n repeat. Our study illustrates: (i) the importance of somatic mosaic genotypes; (ii) the biological plausibility of multiple modifiers (both germline and somatic) that can have additive effects on repeat instability; and (iii) that these variations may remain undetected without assessment of single molecules.
Collapse
Affiliation(s)
- Joanne Trinh
- Correspondence to: Joanne Trinh, PhD University of Lübeck, Ratzeburger Allee 160 23538 Lübeck, Germany E-mail:
| | - Theresa Lüth
- Institute of Neurogenetics, University of Lübeck and University Hospital Schleswig-Holstein, Lübeck, Germany
| | - Susen Schaake
- Institute of Neurogenetics, University of Lübeck and University Hospital Schleswig-Holstein, Lübeck, Germany
| | - Björn-Hergen Laabs
- Institute of Medical Biometry and Statistics, University of Lübeck, Lübeck, Germany
| | - Kathleen Schlüter
- Institute of Neurogenetics, University of Lübeck and University Hospital Schleswig-Holstein, Lübeck, Germany
| | - Joshua Laβ
- Institute of Neurogenetics, University of Lübeck and University Hospital Schleswig-Holstein, Lübeck, Germany
| | - Jelena Pozojevic
- Institute of Neurogenetics, University of Lübeck and University Hospital Schleswig-Holstein, Lübeck, Germany
| | - Ronnie Tse
- Institute of Neurogenetics, University of Lübeck and University Hospital Schleswig-Holstein, Lübeck, Germany
| | - Inke König
- Institute of Medical Biometry and Statistics, University of Lübeck, Lübeck, Germany
| | - Roland Dominic Jamora
- Department of Neurosciences, College of Medicine—Philippine General Hospital, University of the Philippines Manila, Manila, Philippines
| | - Raymond L Rosales
- Department of Neurology and Psychiatry, University of Santo Tomas and the CNS-Metropolitan Medical Center, Manila, Philippines
| | - Norbert Brüggemann
- Institute of Neurogenetics, University of Lübeck and University Hospital Schleswig-Holstein, Lübeck, Germany,Department of Neurology, University of Lübeck, Lübeck, Germany
| | - Gerard Saranza
- Section of Neurology, Department of Internal Medicine, Chong Hua Hospital, Cebu, Philippines
| | - Cid Czarina E Diesta
- Department of Neurosciences, Movement Disorders Clinic, Makati Medical Center, Makati City, Philippines
| | - Frank J Kaiser
- Institute for Human Genetics at the University Hospital Essen, Essen, Germany,Center for Rare Diseases (Essenser Zentrum für Seltene Erkrankungen—EZSE) at the University Hospital Essen, Essen, Germany
| | - Christel Depienne
- Institute for Human Genetics at the University Hospital Essen, Essen, Germany
| | - Christopher E Pearson
- Program of Genetics and Genome Biology, The Hospital for Sick Children, The Peter Gilgan Centre for Research and Learning, Toronto, Canada,University of Toronto, Program of Molecular Genetics, Toronto, Canada
| | - Ana Westenberger
- Institute of Neurogenetics, University of Lübeck and University Hospital Schleswig-Holstein, Lübeck, Germany
| | - Christine Klein
- Institute of Neurogenetics, University of Lübeck and University Hospital Schleswig-Holstein, Lübeck, Germany
| |
Collapse
|
40
|
Baxter SM, Posey JE, Lake NJ, Sobreira N, Chong JX, Buyske S, Blue EE, Chadwick LH, Coban-Akdemir ZH, Doheny KF, Davis CP, Lek M, Wellington C, Jhangiani SN, Gerstein M, Gibbs RA, Lifton RP, MacArthur DG, Matise TC, Lupski JR, Valle D, Bamshad MJ, Hamosh A, Mane S, Nickerson DA, Rehm HL, O'Donnell-Luria A. Centers for Mendelian Genomics: A decade of facilitating gene discovery. Genet Med 2022; 24:784-797. [PMID: 35148959 PMCID: PMC9119004 DOI: 10.1016/j.gim.2021.12.005] [Citation(s) in RCA: 32] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2021] [Revised: 12/08/2021] [Accepted: 12/12/2021] [Indexed: 12/27/2022] Open
Abstract
PURPOSE Mendelian disease genomic research has undergone a massive transformation over the past decade. With increasing availability of exome and genome sequencing, the role of Mendelian research has expanded beyond data collection, sequencing, and analysis to worldwide data sharing and collaboration. METHODS Over the past 10 years, the National Institutes of Health-supported Centers for Mendelian Genomics (CMGs) have played a major role in this research and clinical evolution. RESULTS We highlight the cumulative gene discoveries facilitated by the program, biomedical research leveraged by the approach, and the larger impact on the research community. Beyond generating a list of gene-phenotype relationships and participating in widespread data sharing, the CMGs have created resources, tools, and training for the larger community to foster understanding of genes and genome variation. The CMGs have participated in a wide range of data sharing activities, including deposition of all eligible CMG data into the Analysis, Visualization, and Informatics Lab-space (AnVIL), sharing candidate genes through the Matchmaker Exchange and the CMG website, and sharing variants in Genotypes to Mendelian Phenotypes (Geno2MP) and VariantMatcher. CONCLUSION The work is far from complete; strengthening communication between research and clinical realms, continued development and sharing of knowledge and tools, and improving access to richly characterized data sets are all required to diagnose the remaining molecularly undiagnosed patients.
Collapse
Affiliation(s)
- Samantha M Baxter
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA.
| | - Jennifer E Posey
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX
| | - Nicole J Lake
- Department of Genetics, Yale School of Medicine, New Haven, CT; Murdoch Children's Research Institute, Melbourne, Victoria, Australia
| | - Nara Sobreira
- McKusick-Nathans Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD
| | - Jessica X Chong
- Department of Pediatrics, Division of Genetic Medicine, University of Washington and Seattle Children's Hospital, Seattle, WA; Brotman Baty Institute for Precision Medicine, Seattle, WA
| | - Steven Buyske
- Department of Statistics, Rutgers University, Piscataway, NJ; Department of Genetics, Rutgers University, Piscataway, NJ
| | - Elizabeth E Blue
- Brotman Baty Institute for Precision Medicine, Seattle, WA; Division of Medical Genetics, Department of Medicine, University of Washington, Seattle, WA
| | - Lisa H Chadwick
- Division of Genome Sciences, National Human Genome Research Institute, Bethesda, MD
| | - Zeynep H Coban-Akdemir
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX; Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX
| | - Kimberly F Doheny
- McKusick-Nathans Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD
| | - Colleen P Davis
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA
| | - Monkol Lek
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA; Department of Genetics, Yale School of Medicine, New Haven, CT
| | | | | | - Mark Gerstein
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT; Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT
| | - Richard A Gibbs
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX; Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX
| | - Richard P Lifton
- Department of Genetics, Yale School of Medicine, New Haven, CT; Laboratory of Human Genetics and Genomics, The Rockefeller University, New York, NY
| | - Daniel G MacArthur
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA; Centre for Population Genomics, Garvan Institute of Medical Research and UNSW Sydney, Sydney, New South Wales, Australia; Centre for Population Genomics, Murdoch Children's Research Institute, Melbourne, Victoria, Australia
| | - Tara C Matise
- Department of Genetics, Rutgers University, Piscataway, NJ
| | - James R Lupski
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX; Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX; Department of Pediatrics, Baylor College of Medicine, Houston, TX
| | - David Valle
- McKusick-Nathans Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD
| | - Michael J Bamshad
- Department of Pediatrics, Division of Genetic Medicine, University of Washington and Seattle Children's Hospital, Seattle, WA; Brotman Baty Institute for Precision Medicine, Seattle, WA; Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA
| | - Ada Hamosh
- McKusick-Nathans Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD
| | - Shrikant Mane
- Department of Genetics, Yale School of Medicine, New Haven, CT
| | - Deborah A Nickerson
- Brotman Baty Institute for Precision Medicine, Seattle, WA; Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA
| | - Heidi L Rehm
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA; Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA; Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA.
| | - Anne O'Donnell-Luria
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA; Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA; Department of Pediatrics, Division of Genetics and Genomics, Boston Children's Hospital, Boston, MA.
| |
Collapse
|
41
|
Lima AR, Ferreira BM, Zhang C, Jolly A, Du H, White JJ, Dawood M, Lins TC, Chiabai MA, van Beusekom E, Cordoba MS, Caldas Rosa ECC, Kayserili H, Kimonis V, Wu E, Mellado C, Aggarwal V, Richieri-Costa A, Brunoni D, Canó TM, Jorge AAL, Kim CA, Honjo R, Bertola DR, Dandalo-Girardi RM, Bayram Y, Gezdirici A, Yilmaz-Gulec E, Gumus E, Yilmaz GC, Okamoto N, Ohashi H, Coban-Akdemir Z, Mitani T, Jhangiani SN, Muzny DM, Regattieri NAP, Pogue R, Pereira RW, Otto PA, Gibbs RA, Ali BR, van Bokhoven H, Brunner HG, Reid Sutton V, Lupski JR, Vianna-Morgante AM, Carvalho CMB, Mazzeu JF. Phenotypic and mutational spectrum of ROR2-related Robinow syndrome. Hum Mutat 2022; 43:900-918. [PMID: 35344616 DOI: 10.1002/humu.24375] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2021] [Revised: 03/23/2022] [Accepted: 03/24/2022] [Indexed: 02/05/2023]
Abstract
Robinow syndrome is characterized by a triad of craniofacial dysmorphisms, disproportionate-limb short stature and genital hypoplasia. A significant degree of phenotypic variability seems to correlate with different genes/loci. Disturbances of the non-canonical WNT-pathway have been identified as the main cause of the syndrome. Biallelic variants in ROR2 cause an autosomal recessive form of the syndrome with distinctive skeletal findings. Twenty-two patients with a clinical diagnosis of autosomal recessive Robinow syndrome were screened for variants in ROR2 using multiple molecular approaches. We identified 25 putatively pathogenic ROR2 variants, 16 novel, including single nucleotide variants and exonic deletions. Detailed phenotypic analyses revealed that all subjects presented with a prominent forehead, hypertelorism, short nose, abnormality of the nasal tip, brachydactyly, mesomelic limb shortening, short stature and genital hypoplasia in male patients. A total of 19 clinical features were present in more than 75% of the subjects, thus pointing to an overall uniformity of the phenotype. Disease-causing variants in ROR2, contribute to a clinically recognizable AR trait phenotype with multiple skeletal defects. A comprehensive quantitative clinical evaluation this cohort delineated the phenotypic spectrum of ROR2-related Robinow syndrome. The identification of exonic deletion variant alleles further supports the contention of a loss-of-function mechanism in the etiology of the syndrome. This article is protected by copyright. All rights reserved.
Collapse
Affiliation(s)
- Ariadne R Lima
- Programa de Pós-Graduação em Ciências da Saúde, Universidade de Brasília, Brasília, DF, Brasil
| | - Barbara M Ferreira
- Programa de Pós-Graduação em Ciências Médicas, Universidade de Brasília, Brasília, DF, Brasil
| | - Chaofan Zhang
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
| | - Angad Jolly
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA.,Medical Scientist Training Program, Baylor College of Medicine, Houston, TX, USA
| | - Haowei Du
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
| | - Janson J White
- Department of Pediatrics, University of Washington, Seattle, WA, USA
| | - Moez Dawood
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA.,Medical Scientist Training Program, Baylor College of Medicine, Houston, TX, USA.,Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - Tulio C Lins
- Programa de Pós-graduação em Ciências Genômicas e Biotecnologia, Universidade Católica de Brasília, Brasília, DF, Brasil
| | - Marcela A Chiabai
- Programa de Pós-graduação em Ciências Genômicas e Biotecnologia, Universidade Católica de Brasília, Brasília, DF, Brasil
| | | | - Mara S Cordoba
- Faculdade de Medicina, Universidade de Brasília, Brasília, DF, Brasil.,Hospital Universitário de Brasília, Brasília, Brasil
| | - Erica C C Caldas Rosa
- Programa de Pós-Graduação em Ciências da Saúde, Universidade de Brasília, Brasília, DF, Brasil
| | - Hulya Kayserili
- Koç University, School of Medicine (KUSoM), Medical Genetics Department, Istanbul, Turkey
| | - Virginia Kimonis
- Division of Genetics and Genomic Medicine, Dept. of Pediatrics, University of California-Irvine, Irvine, CA, USA
| | - Erica Wu
- Stanford University, Obstetrics and Gynecology, Stanford, CA, USA
| | - Cecilia Mellado
- Unidad de Genética, División de Pediatría, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Vineet Aggarwal
- Department of Orthopedics, Indira Gandhi Medical College, Snowdon, Shimla-1, India
| | | | - Décio Brunoni
- Universidade Presbiteriana Mackenzie - UPM, São Paulo, SP, Brasil
| | - Talyta M Canó
- Programa de Pós-Graduação em Ciências Médicas, Universidade de Brasília, Brasília, DF, Brasil.,Núcleo de Genética - SESDF, Brasília, DF, Brasil
| | - Alexander A L Jorge
- Unidade de Endocrinologia Genética, Laboratório de Endocrinologia Celular e Molecular LIM25, Disciplina de Endocrinologia da Faculdade de Medicina da Universidade de São Paulo, São Paulo, SP, Brasil
| | - Chong A Kim
- Unidade de Genética, Instituto da Criança - Hospital das Clinicas HCFMUSP, Faculdade de Medicina, Universidade de São Paulo, São Paulo, SP, Brasil
| | - Rachel Honjo
- Unidade de Genética, Instituto da Criança - Hospital das Clinicas HCFMUSP, Faculdade de Medicina, Universidade de São Paulo, São Paulo, SP, Brasil
| | - Débora R Bertola
- Unidade de Endocrinologia Genética, Laboratório de Endocrinologia Celular e Molecular LIM25, Disciplina de Endocrinologia da Faculdade de Medicina da Universidade de São Paulo, São Paulo, SP, Brasil.,Departamento de Genética e Biologia Evolutiva, Instituto de Biociências, Universidade de São Paulo, São Paulo, SP, Brasil
| | - Raissa M Dandalo-Girardi
- Programa de Mestrado Profissional em Aconselhamento Genético e Genômica Humana, Instituto de Biociências, Universidade de São Paulo, São Paulo, SP, Brasil
| | - Yavuz Bayram
- Division of Genomic Diagnostics, Department of Pathology and Laboratory Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, USA.,Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Alper Gezdirici
- Department of Medical Genetics, Basaksehir Cam and Sakura City Hospital, Istanbul, Turkey
| | | | - Evren Gumus
- Medical Genetics Department, Medicine Faculty, Mugla Sitki Kocman University, Mugla, Turkey
| | - Gülay C Yilmaz
- Medical Genetics Department, Medicine Faculty, Mugla Sitki Kocman University, Mugla, Turkey
| | - Nobuhiko Okamoto
- Department of Medical Genetics, Osaka Women's and Children's Hospital, Osaka, Japan
| | - Hirofumi Ohashi
- Division of Medical Genetics, Saitama Children's Medical Center, Saitama, 330-8777, Japan
| | - Zeynep Coban-Akdemir
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA.,Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, UT Health, Houston, TX, USA
| | - Tadahiro Mitani
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
| | - Shalini N Jhangiani
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - Donna M Muzny
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | | | - Robert Pogue
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - Rinaldo W Pereira
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - Paulo A Otto
- Departamento de Genética e Biologia Evolutiva, Instituto de Biociências, Universidade de São Paulo, São Paulo, SP, Brasil
| | - Richard A Gibbs
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - Bassam R Ali
- Department of Genetics and Genomics, College of Medicine and Health Sciences, United Arab Emirates University, Al-Ain, United Arab Emirates
| | - Hans van Bokhoven
- Programa de Pós-graduação em Ciências Genômicas e Biotecnologia, Universidade Católica de Brasília, Brasília, DF, Brasil
| | - Han G Brunner
- Programa de Pós-graduação em Ciências Genômicas e Biotecnologia, Universidade Católica de Brasília, Brasília, DF, Brasil
| | - V Reid Sutton
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA.,Texas Children's Hospital, Houston, TX, USA
| | - James R Lupski
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA.,Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA.,Texas Children's Hospital, Houston, TX, USA.,Department of Pediatrics, Baylor College of Medicine, Houston, TX, USA
| | - Angela M Vianna-Morgante
- Departamento de Genética e Biologia Evolutiva, Instituto de Biociências, Universidade de São Paulo, São Paulo, SP, Brasil
| | - Claudia M B Carvalho
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA.,Pacific Northwest Research Institute, Seattle, WA, USA
| | - Juliana F Mazzeu
- Programa de Pós-Graduação em Ciências da Saúde, Universidade de Brasília, Brasília, DF, Brasil.,Programa de Pós-Graduação em Ciências Médicas, Universidade de Brasília, Brasília, DF, Brasil.,Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands.,Robinow Syndrome Foundation, Anoka, MN, USA
| |
Collapse
|
42
|
Herman I, Jolly A, Du H, Dawood M, Abdel-Salam GMH, Marafi D, Mitani T, Calame DG, Coban-Akdemir Z, Fatih JM, Hegazy I, Jhangiani SN, Gibbs RA, Pehlivan D, Posey JE, Lupski JR. Quantitative dissection of multilocus pathogenic variation in an Egyptian infant with severe neurodevelopmental disorder resulting from multiple molecular diagnoses. Am J Med Genet A 2022; 188:735-750. [PMID: 34816580 PMCID: PMC8837671 DOI: 10.1002/ajmg.a.62565] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2021] [Revised: 10/11/2021] [Accepted: 10/18/2021] [Indexed: 12/19/2022]
Abstract
Genomic sequencing and clinical genomics have demonstrated that substantial subsets of atypical and/or severe disease presentations result from multilocus pathogenic variation (MPV) causing blended phenotypes. In an infant with a severe neurodevelopmental disorder, four distinct molecular diagnoses were found by exome sequencing (ES). The blended phenotype that includes brain malformation, dysmorphism, and hypotonia was dissected using the Human Phenotype Ontology (HPO). ES revealed variants in CAPN3 (c.259C > G:p.L87V), MUSK (c.1781C > T:p.A594V), NAV2 (c.1996G > A:p.G666R), and ZC4H2 (c.595A > C:p.N199H). CAPN3, MUSK, and ZC4H2 are established disease genes linked to limb-girdle muscular dystrophy (OMIM# 253600), congenital myasthenia (OMIM# 616325), and Wieacker-Wolff syndrome (WWS; OMIM# 314580), respectively. NAV2 is a retinoic-acid responsive novel disease gene candidate with biological roles in neurite outgrowth and cerebellar dysgenesis in mouse models. Using semantic similarity, we show that no gene identified by ES individually explains the proband phenotype, but rather the totality of the clinically observed disease is explained by the combination of disease-contributing effects of the identified genes. These data reveal that multilocus pathogenic variation can result in a blended phenotype with each gene affecting a different part of the nervous system and nervous system-muscle connection. We provide evidence from this n = 1 study that in patients with MPV and complex blended phenotypes resulting from multiple molecular diagnoses, quantitative HPO analysis can allow for dissection of phenotypic contribution of both established disease genes and novel disease gene candidates not yet proven to cause human disease.
Collapse
Affiliation(s)
- Isabella Herman
- Section of Pediatric Neurology and Developmental Neuroscience, Department of Pediatrics, Baylor College of Medicine, Houston, Texas, 77030, USA,Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas, 77030, USA,Texas Children's Hospital, Houston, Texas, 77030, USA
| | - Angad Jolly
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas, 77030, USA,Medical Scientist Training Program, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Haowei Du
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas, 77030, USA
| | - Moez Dawood
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas, 77030, USA,Medical Scientist Training Program, Baylor College of Medicine, Houston, TX, 77030, USA,Human Genome Sequencing Center, Baylor College of Medicine, Houston, Texas, 77030, USA
| | - Ghada M. H. Abdel-Salam
- Clinical Genetics Department, Human Genetics and Genome Research Division, National Research Centre, Cairo, Egypt
| | - Dana Marafi
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas, 77030, USA,Department of Pediatrics, Faculty of Medicine, Kuwait University, P.O. Box 24923, 13110 Safat, Kuwait,Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, Texas, USA
| | - Tadahiro Mitani
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas, 77030, USA
| | - Daniel G. Calame
- Section of Pediatric Neurology and Developmental Neuroscience, Department of Pediatrics, Baylor College of Medicine, Houston, Texas, 77030, USA,Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas, 77030, USA,Texas Children's Hospital, Houston, Texas, 77030, USA
| | - Zeynep Coban-Akdemir
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas, 77030, USA,Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, Texas, USA
| | - Jawid M. Fatih
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas, 77030, USA
| | - Ibrahim Hegazy
- Clinical Genetics Department, Human Genetics and Genome Research Division, National Research Centre, Cairo, Egypt
| | - Shalini N. Jhangiani
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas, 77030, USA,Human Genome Sequencing Center, Baylor College of Medicine, Houston, Texas, 77030, USA
| | - Richard A. Gibbs
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas, 77030, USA,Human Genome Sequencing Center, Baylor College of Medicine, Houston, Texas, 77030, USA
| | - Davut Pehlivan
- Section of Pediatric Neurology and Developmental Neuroscience, Department of Pediatrics, Baylor College of Medicine, Houston, Texas, 77030, USA,Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas, 77030, USA,Texas Children's Hospital, Houston, Texas, 77030, USA
| | - Jennifer E. Posey
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas, 77030, USA
| | - James R. Lupski
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas, 77030, USA,Texas Children's Hospital, Houston, Texas, 77030, USA,Human Genome Sequencing Center, Baylor College of Medicine, Houston, Texas, 77030, USA,Department of Pediatrics, Baylor College of Medicine, Houston, TX, 77030
| |
Collapse
|
43
|
Abstract
The generation of a comprehensive catalog of null alleles covering all protein-coding genes is the goal of the International Mouse Phenotyping Consortium. Over the past 20 years, significant progress has been made towards achieving this goal through the combined efforts of many large-scale programs that built an embryonic stem cell resource to generate knockout mice and more recently employed CRISPR/Cas9-based mutagenesis to delete critical regions predicted to result in frameshift mutations, thus, ablating gene function. The IMPC initiative builds on prior and ongoing work by individual research groups creating gene knockouts in the mouse. Here, we analyze the collective efforts focusing on the combined null allele resource resulting from strains developed by the research community and large-scale production programs. Based upon this pooled analysis, we examine the remaining fraction of protein-coding genes focusing on clearly defined mouse-human orthologs as the highest priority for completing the mutant mouse null resource. In summary, we find that there are less than 3400 mouse-human orthologs remaining in the genome without a targeted null allele that can be further prioritized to achieve our overall goal of the complete functional annotation of the protein-coding portion of a mammalian genome.
Collapse
|
44
|
Álvarez-Mora MI, Sánchez A, Rodríguez-Revenga L, Corominas J, Rabionet R, Puig S, Madrigal I. Diagnostic yield of next-generation sequencing in 87 families with neurodevelopmental disorders. Orphanet J Rare Dis 2022; 17:60. [PMID: 35183220 PMCID: PMC8858550 DOI: 10.1186/s13023-022-02213-z] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2021] [Accepted: 02/06/2022] [Indexed: 01/14/2023] Open
Abstract
Abstract
Background
Neurodevelopmental disorders (NDDs) are a group of heterogeneous conditions, which include mainly intellectual disability, developmental delay (DD) and autism spectrum disorder (ASD), among others. These diseases are highly heterogeneous and both genetic and environmental factors play an important role in many of them. The introduction of next generation sequencing (NGS) has lead to the detection of genetic variants in several genetic diseases. The main aim of this report is to discuss the impact and advantages of the implementation of NGS in the diagnosis of NDDs. Herein, we report diagnostic yields of applying whole exome sequencing in 87 families affected by NDDs and additional data of whole genome sequencing (WGS) from 12 of these families.
Results
The use of NGS technologies allowed identifying the causative gene alteration in approximately 36% (31/87) of the families. Among them, de novo mutation represented the most common cause of genetic alteration found in 48% (15/31) of the patients with diagnostic mutations. The majority of variants were located in known neurodevelopmental disorders genes. Nevertheless, some of the diagnoses were made after the use of GeneMatcher tools which allow the identification of additional patients carrying mutations in THOC2, SETD1B and CHD9 genes. Finally the use of WGS only allowed the identification of disease causing variants in 8% (1/12) of the patients in which previous WES failed to identify a genetic aetiology.
Conclusion
NGS is more powerful in identifying causative pathogenic variant than conventional algorithms based on chromosomal microarray as first-tier test. Our results reinforce the implementation of NGS as a first-test in genetic diagnosis of NDDs.
Collapse
|
45
|
Fujiwara T, Shin JM, Yamaguchi A. Advances in the development of PubCaseFinder, including the new application programming interface and matching algorithm. Hum Mutat 2022; 43:734-742. [PMID: 35143083 PMCID: PMC9305291 DOI: 10.1002/humu.24341] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2021] [Revised: 01/17/2022] [Accepted: 02/07/2022] [Indexed: 11/11/2022]
Abstract
Over 10,000 rare genetic diseases have been identified, and millions of newborns are affected by severe rare genetic diseases each year. A variety of Human Phenotype Ontology (HPO)-based clinical decision support systems (CDSS) and patient repositories have been developed to support clinicians in diagnosing patients with suspected rare genetic diseases. In September 2017, we released PubCaseFinder (https://pubcasefinder.dbcls.jp), a web-based CDSS that provides ranked lists of genetic and rare diseases using HPO-based phenotypic similarities, where top-listed diseases represent the most likely differential diagnosis. We also developed a Matchmaker Exchange (MME) application programming interface (API) to query PubCaseFinder, which has been adopted by several patient repositories. In this paper, we describe notable updates regarding PubCaseFinder, the GeneYenta matching algorithm implemented in PubCaseFinder, and the PubCaseFinder API. The updated GeneYenta matching algorithm improves the performance of the CDSS automated differential diagnosis function. Moreover, the updated PubCaseFinder and new API empower patient repositories participating in MME and medical professionals to actively use HPO-based resources. This article is protected by copyright. All rights reserved.
Collapse
Affiliation(s)
- Toyofumi Fujiwara
- Database Center for Life Science, Joint Support-Center for Data Science Research, Research Organization of Information and Systems, Kashiwa-shi, Chiba-ken, 277-0871, Japan
| | - Jae-Moon Shin
- Database Center for Life Science, Joint Support-Center for Data Science Research, Research Organization of Information and Systems, Kashiwa-shi, Chiba-ken, 277-0871, Japan
| | - Atsuko Yamaguchi
- Graduate School of Integrative Science and Engineering, Tokyo City University, Setagaya-ku, Tokyo, 158-8557, Japan
| |
Collapse
|
46
|
Ghosh AJ, Hobbs BD. Recent advancements in understanding the genetic involvement of alpha-1 antitrypsin deficiency associated lung disease: a look at future precision medicine approaches. Expert Rev Respir Med 2022; 16:173-182. [PMID: 35025710 PMCID: PMC8983484 DOI: 10.1080/17476348.2022.2027755] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Abstract
INTRODUCTION Alpha-1 antitrypsin deficiency occurs in individuals with deleterious genetic mutations on both chromosomes (maternal and paternal) in SERPINA1, the gene encoding the alpha-1 antitrypsin protein. There has been substantial progress in understanding the genetic variation that underlies the heterogeneous penetrance of lung disease in alpha-1 antitrypsin deficiency. AREAS COVERED This review will cover SERPINA1 gene structure and genetic variation, population genetics, genome-wide genetic modifiers of lung disease, alternative mechanisms of disease, and emerging therapeutics - including gene and cell therapy - related to alpha-1 antitrypsin deficiency-associated lung disease. EXPERT OPINION There remains ample opportunity to employ precision medicine in the diagnosis, prognosis, and therapy of alpha-1 antitrypsin deficiency-associated lung disease. In particular, a genome-wide association study and subsequent polygenic risk score is an important first step in identifying genome-wide genetic modifiers contributing to the variability of lung disease in severe alpha-1 antitrypsin deficiency.
Collapse
Affiliation(s)
- Auyon J. Ghosh
- Assistant Professor of Medicine, Division of Pulmonary, Critical Care, and Sleep Medicine, SUNY Upstate Medical University, 750 E. Adams St, Syracuse, NY, 13210
| | - Brian D. Hobbs
- Assistant Professor of Medicine, Channing Division of Network Medicine, Brigham and Women’s Hospital, 181 Longwood Ave, Boston, MA, 02115,Division of Pulmonary and Critical Care Medicine, Brigham and Women’s Hospital,Harvard Medical School
| |
Collapse
|
47
|
Zhang C, Jolly A, Shayota BJ, Mazzeu JF, Du H, Dawood M, Soper PC, Ramalho de Lima A, Ferreira BM, Coban-Akdemir Z, White J, Shears D, Thomson FR, Douglas SL, Wainwright A, Bailey K, Wordsworth P, Oldridge M, Lester T, Calder AD, Dumic K, Banka S, Donnai D, Jhangiani SN, Potocki L, Chung WK, Mora S, Northrup H, Ashfaq M, Rosenfeld JA, Mason K, Pollack LC, McConkie-Rosell A, Kelly W, McDonald M, Hauser NS, Leahy P, Powell CM, Boy R, Honjo RS, Kok F, Martelli LR, Filho VO, Genomics England Research Consortium, Muzny DM, Gibbs RA, Posey JE, Liu P, Lupski JR, Sutton VR, Carvalho CM. Novel pathogenic variants and quantitative phenotypic analyses of Robinow syndrome: WNT signaling perturbation and phenotypic variability. HGG Adv 2022; 3:100074. [PMID: 35047859 PMCID: PMC8756549 DOI: 10.1016/j.xhgg.2021.100074] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2021] [Accepted: 11/24/2021] [Indexed: 11/20/2022] Open
Abstract
Robinow syndrome (RS) is a genetically heterogeneous disorder with six genes that converge on the WNT/planar cell polarity (PCP) signaling pathway implicated (DVL1, DVL3, FZD2, NXN, ROR2, and WNT5A). RS is characterized by skeletal dysplasia and distinctive facial and physical characteristics. To further explore the genetic heterogeneity, paralog contribution, and phenotypic variability of RS, we investigated a cohort of 22 individuals clinically diagnosed with RS from 18 unrelated families. Pathogenic or likely pathogenic variants in genes associated with RS or RS phenocopies were identified in all 22 individuals, including the first variant to be reported in DVL2. We retrospectively collected medical records of 16 individuals from this cohort and extracted clinical descriptions from 52 previously published cases. We performed Human Phenotype Ontology (HPO) based quantitative phenotypic analyses to dissect allele-specific phenotypic differences. Individuals with FZD2 variants clustered into two groups with demonstrable phenotypic differences between those with missense and truncating alleles. Probands with biallelic NXN variants clustered together with the majority of probands carrying DVL1, DVL2, and DVL3 variants, demonstrating no phenotypic distinction between the NXN-autosomal recessive and dominant forms of RS. While phenotypically similar diseases on the RS differential matched through HPO analysis, clustering using phenotype similarity score placed RS-associated phenotypes in a unique cluster containing WNT5A, FZD2, and ROR2 apart from non-RS-associated paralogs. Through human phenotype analyses of this RS cohort and OMIM clinical synopses of Mendelian disease, this study begins to tease apart specific biologic roles for non-canonical WNT-pathway proteins.
Collapse
Affiliation(s)
- Chaofan Zhang
- Department of Molecular and Human Genetics, BCM, Houston, TX 77030, USA
| | - Angad Jolly
- Department of Molecular and Human Genetics, BCM, Houston, TX 77030, USA
- Medical Scientist Training Program, BCM, Houston, TX 77030, USA
| | - Brian J. Shayota
- Department of Molecular and Human Genetics, BCM, Houston, TX 77030, USA
- Texas Children's Hospital, Houston, TX 77030, USA
| | - Juliana F. Mazzeu
- University of Brasilia, Brasilia 70050, Brazil
- Robinow Syndrome Foundation, Anoka, MN 55303, USA
| | - Haowei Du
- Department of Molecular and Human Genetics, BCM, Houston, TX 77030, USA
| | - Moez Dawood
- Department of Molecular and Human Genetics, BCM, Houston, TX 77030, USA
- Medical Scientist Training Program, BCM, Houston, TX 77030, USA
- Human Genome Sequencing Center, BCM, Houston, TX 77030, USA
| | | | | | | | - Zeynep Coban-Akdemir
- Department of Molecular and Human Genetics, BCM, Houston, TX 77030, USA
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, UTHealth, Houston, TX 77030, USA
| | - Janson White
- Department of Molecular and Human Genetics, BCM, Houston, TX 77030, USA
| | - Deborah Shears
- Oxford Centre for Genomic Medicine, Oxford University Hospitals NHS Foundation Trust, Oxford OX3 7HE, UK
| | - Fraser Robert Thomson
- Cardiothoracic Surgery, Oxford University Hospitals NHS Foundation Trust, Oxford OX3 7HE, UK
| | | | - Andrew Wainwright
- Oxford Centre for Genomic Medicine, Oxford University Hospitals NHS Foundation Trust, Oxford OX3 7HE, UK
| | - Kathryn Bailey
- Pediatric Rheumatology, Nuffield Orthopedic Centre, Oxford University Hospitals NHS Foundation Trust, Oxford OX3 7HE, UK
| | - Paul Wordsworth
- Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, Botnar Research Centre, Oxford OX3 7LD, UK
| | - Mike Oldridge
- Oxford Regional Genetics Laboratories, Oxford University Hospitals NHS Foundation Trust, Oxford OX3 7LE, UK
| | - Tracy Lester
- Oxford Regional Genetics Laboratories, Oxford University Hospitals NHS Foundation Trust, Oxford OX3 7LE, UK
| | - Alistair D. Calder
- Radiology Department, Great Ormond Street Hospital NHS Foundation Trust, London WC1N 3JH, UK
| | - Katja Dumic
- Department of Pediatric Endocrinology and Diabetes, University Clinical Center Zagreb, Zagreb 10000, Croatia
| | - Siddharth Banka
- Division of Evolution, Infection and Genomics, School of Biological Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester M13 9WL, UK
- Manchester Center for Genomic Medicine, St Mary's Hospital, Manchester University NHS Foundation Trust, Health Innovation Manchester, Manchester M13 9WL, UK
| | - Dian Donnai
- Manchester Center for Genomic Medicine, St Mary's Hospital, Manchester University NHS Foundation Trust, Health Innovation Manchester, Manchester M13 9WL, UK
| | | | - Lorraine Potocki
- Department of Molecular and Human Genetics, BCM, Houston, TX 77030, USA
- Texas Children's Hospital, Houston, TX 77030, USA
| | - Wendy K. Chung
- Department of Pediatrics and Medicine, Columbia University, NY 10032, USA
| | - Sara Mora
- GeneDx Inc., Gaithersburg, MD 20878, USA
| | - Hope Northrup
- Department of Pediatrics, McGovern Medical School at the University of Texas Health Science Center at Houston (UTHealth Houston) and Children’s Memorial Hermann Hospital, Houston, TX 77030, USA
| | - Myla Ashfaq
- Department of Pediatrics, McGovern Medical School at the University of Texas Health Science Center at Houston (UTHealth Houston) and Children’s Memorial Hermann Hospital, Houston, TX 77030, USA
| | - Jill A. Rosenfeld
- Department of Molecular and Human Genetics, BCM, Houston, TX 77030, USA
| | - Kati Mason
- GeneDx Inc., Gaithersburg, MD 20878, USA
- Arnold Palmer Hospital for Children, Orlando, FL 32806, USA
| | | | | | - Wei Kelly
- Division of Medical Genetics, Duke University Medical Center, Durham, NC 27708, USA
| | - Marie McDonald
- Division of Medical Genetics, Duke University Medical Center, Durham, NC 27708, USA
| | - Natalie S. Hauser
- Medical Genetics, Inova Fairfax Hospital, Falls Church, VA 22042, USA
| | - Peter Leahy
- Cook Children's Hospital, Fort Worth, TX 76104, USA
| | - Cynthia M. Powell
- Division of Pediatric Genetics and Metabolism, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, NC 27599, USA
| | - Raquel Boy
- State University of Rio de Janeiro, Rio de Janeiro 21941, Brazil
| | - Rachel Sayuri Honjo
- Unidade de Genética, Instituto da Criança - Hospital das Clinicas HCFMUSP, Faculdade de Medicina, University of Sao Paulo, São Paulo 05508, Brasil
| | - Fernando Kok
- Mendelics Análise Genômica, São Paulo 04013, Brasil
| | - Lucia R. Martelli
- Department of Genetics, Ribeirao Preto Medical School, University of Sao Paulo, São Paulo 05508, Brazil
| | - Vicente Odone Filho
- Instituto de Tratamento do Câncer Infantil, São Paulo University Medical School, Hospital Israelita Albert Einstein, São Paulo 05508, Brasil
| | | | - Donna M. Muzny
- Human Genome Sequencing Center, BCM, Houston, TX 77030, USA
| | - Richard A. Gibbs
- Department of Molecular and Human Genetics, BCM, Houston, TX 77030, USA
- Human Genome Sequencing Center, BCM, Houston, TX 77030, USA
| | - Jennifer E. Posey
- Department of Molecular and Human Genetics, BCM, Houston, TX 77030, USA
| | - Pengfei Liu
- Department of Molecular and Human Genetics, BCM, Houston, TX 77030, USA
- Baylor Genetics, Houston, TX 77021, USA
| | - James R. Lupski
- Department of Molecular and Human Genetics, BCM, Houston, TX 77030, USA
- Texas Children's Hospital, Houston, TX 77030, USA
- Human Genome Sequencing Center, BCM, Houston, TX 77030, USA
- Department of Pediatrics, BCM, Houston, TX 77030, USA
| | - V. Reid Sutton
- Department of Molecular and Human Genetics, BCM, Houston, TX 77030, USA
- Texas Children's Hospital, Houston, TX 77030, USA
| | - Claudia M.B. Carvalho
- Department of Molecular and Human Genetics, BCM, Houston, TX 77030, USA
- Pacific Northwest Research Institute (PNRI), Seattle, WA 98122, USA
| |
Collapse
|
48
|
Hines TJ, Lutz C, Murray SA, Burgess RW. An Integrated Approach to Studying Rare Neuromuscular Diseases Using Animal and Human Cell-Based Models. Front Cell Dev Biol 2022; 9:801819. [PMID: 35047510 PMCID: PMC8762301 DOI: 10.3389/fcell.2021.801819] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2021] [Accepted: 11/30/2021] [Indexed: 11/13/2022] Open
Abstract
As sequencing technology improves, the identification of new disease-associated genes and new alleles of known genes is rapidly increasing our understanding of the genetic underpinnings of rare diseases, including neuromuscular diseases. However, precisely because these disorders are rare and often heterogeneous, they are difficult to study in patient populations. In parallel, our ability to engineer the genomes of model organisms, such as mice or rats, has gotten increasingly efficient through techniques such as CRISPR/Cas9 genome editing, allowing the creation of precision human disease models. Such in vivo model systems provide an efficient means for exploring disease mechanisms and identifying therapeutic strategies. Furthermore, animal models provide a platform for preclinical studies to test the efficacy of those strategies. Determining whether the same mechanisms are involved in the human disease and confirming relevant parameters for treatment ideally involves a human experimental system. One system currently being used is induced pluripotent stem cells (iPSCs), which can then be differentiated into the relevant cell type(s) for in vitro confirmation of disease mechanisms and variables such as target engagement. Here we provide a demonstration of these approaches using the example of tRNA-synthetase-associated inherited peripheral neuropathies, rare forms of Charcot-Marie-Tooth disease (CMT). Mouse models have led to a better understanding of both the genetic and cellular mechanisms underlying the disease. To determine if the mechanisms are similar in human cells, we will use genetically engineered iPSC-based models. This will allow comparisons of different CMT-associated GARS alleles in the same genetic background, reducing the variability found between patient samples and simplifying the availability of cell-based models for a rare disease. The necessity of integrating mouse and human models, strategies for accomplishing this integration, and the challenges of doing it at scale are discussed using recently published work detailing the cellular mechanisms underlying GARS-associated CMT as a framework.
Collapse
|
49
|
Zhou D, Jia S, Yi L, Wu Z, Song Y, Zhang B, Li Y, Yang X, Xu A, Li X, Zhang W, Duan W, Li Z, Qi S, Chen Z, Ouyang Q, Jia J, Huang J, Ou X, You H. OUP accepted manuscript. Metallomics 2022; 14:6561631. [PMID: 35357466 PMCID: PMC9154322 DOI: 10.1093/mtomcs/mfac024] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2021] [Accepted: 03/29/2022] [Indexed: 11/29/2022]
Abstract
The mutations in modifier genes may contribute to some inherited diseases including Wilson disease (WD). This study was designed to identify potential modifier genes that contribute to WD. A total of 10 WD patients with single or no heterozygous ATP7B mutations were recruited for whole-exome sequencing (WES). Five hundred and thirteen candidate genes, of which the genetic variants present in at least two patients, were identified. In order to clarify which proteins might be involved in copper transfer or metabolism processes, the isobaric tags for relative and absolute quantitation (iTRAQ) was performed to identify the differentially expressed proteins between normal and CuSO4-treated cell lines. Thirteen genes/proteins were identified by both WES and iTRAQ, indicating that disease-causing variants of these genes may actually contribute to the aberrant copper ion accumulation. Additionally, the c.86C > T (p.S29L) mutation in the SLC31A2 gene (coding CTR2) has a relative higher frequency in our cohort of WD patients (6/191) than reported (0.0024 in gnomAD database) in our healthy donors (0/109), and CTR2S29L leads to increased intracellular Cu concentration and Cu-induced apoptosis in cultured cell lines. In conclusion, the WES and iTRAQ approaches successfully identified several disease-causing variants in potential modifier genes that may be involved in the WD phenotype.
Collapse
Affiliation(s)
| | | | | | | | - Yi Song
- Experimental Center, Beijing Friendship Hospital, Capital Medical University, Beijing 100050, China
- Clinical Research Center for Rare Liver Diseases, Capital Medical University, Beijing, China
- National Clinical Research Center for Digestive Diseases, On behalf of China Registry of Genetic/Metabolic Liver Diseases (CR-GMLD) Group, Beijing, China
| | - Bei Zhang
- Experimental Center, Beijing Friendship Hospital, Capital Medical University, Beijing 100050, China
- Clinical Research Center for Rare Liver Diseases, Capital Medical University, Beijing, China
- National Clinical Research Center for Digestive Diseases, On behalf of China Registry of Genetic/Metabolic Liver Diseases (CR-GMLD) Group, Beijing, China
| | - Yanmeng Li
- Experimental Center, Beijing Friendship Hospital, Capital Medical University, Beijing 100050, China
- Clinical Research Center for Rare Liver Diseases, Capital Medical University, Beijing, China
- National Clinical Research Center for Digestive Diseases, On behalf of China Registry of Genetic/Metabolic Liver Diseases (CR-GMLD) Group, Beijing, China
| | - Xiaoxi Yang
- Experimental Center, Beijing Friendship Hospital, Capital Medical University, Beijing 100050, China
- Clinical Research Center for Rare Liver Diseases, Capital Medical University, Beijing, China
- National Clinical Research Center for Digestive Diseases, On behalf of China Registry of Genetic/Metabolic Liver Diseases (CR-GMLD) Group, Beijing, China
| | - Anjian Xu
- Experimental Center, Beijing Friendship Hospital, Capital Medical University, Beijing 100050, China
- Clinical Research Center for Rare Liver Diseases, Capital Medical University, Beijing, China
- National Clinical Research Center for Digestive Diseases, On behalf of China Registry of Genetic/Metabolic Liver Diseases (CR-GMLD) Group, Beijing, China
| | - Xiaojin Li
- Experimental Center, Beijing Friendship Hospital, Capital Medical University, Beijing 100050, China
- Clinical Research Center for Rare Liver Diseases, Capital Medical University, Beijing, China
- National Clinical Research Center for Digestive Diseases, On behalf of China Registry of Genetic/Metabolic Liver Diseases (CR-GMLD) Group, Beijing, China
| | - Wei Zhang
- Liver Research Center, Beijing Friendship Hospital, Capital Medical University, Beijing Key Laboratory of Translational Medicine on Liver Cirrhosis, Beijing, China
- Clinical Research Center for Rare Liver Diseases, Capital Medical University, Beijing, China
- National Clinical Research Center for Digestive Diseases, On behalf of China Registry of Genetic/Metabolic Liver Diseases (CR-GMLD) Group, Beijing, China
| | - Weijia Duan
- Liver Research Center, Beijing Friendship Hospital, Capital Medical University, Beijing Key Laboratory of Translational Medicine on Liver Cirrhosis, Beijing, China
- Clinical Research Center for Rare Liver Diseases, Capital Medical University, Beijing, China
- National Clinical Research Center for Digestive Diseases, On behalf of China Registry of Genetic/Metabolic Liver Diseases (CR-GMLD) Group, Beijing, China
| | - Zhenkun Li
- Experimental Center, Beijing Friendship Hospital, Capital Medical University, Beijing 100050, China
- Clinical Research Center for Rare Liver Diseases, Capital Medical University, Beijing, China
- National Clinical Research Center for Digestive Diseases, On behalf of China Registry of Genetic/Metabolic Liver Diseases (CR-GMLD) Group, Beijing, China
| | - Saiping Qi
- Experimental Center, Beijing Friendship Hospital, Capital Medical University, Beijing 100050, China
- Clinical Research Center for Rare Liver Diseases, Capital Medical University, Beijing, China
- National Clinical Research Center for Digestive Diseases, On behalf of China Registry of Genetic/Metabolic Liver Diseases (CR-GMLD) Group, Beijing, China
| | - Zhibin Chen
- Experimental Center, Beijing Friendship Hospital, Capital Medical University, Beijing 100050, China
- Clinical Research Center for Rare Liver Diseases, Capital Medical University, Beijing, China
- National Clinical Research Center for Digestive Diseases, On behalf of China Registry of Genetic/Metabolic Liver Diseases (CR-GMLD) Group, Beijing, China
| | - Qin Ouyang
- Experimental Center, Beijing Friendship Hospital, Capital Medical University, Beijing 100050, China
- Clinical Research Center for Rare Liver Diseases, Capital Medical University, Beijing, China
- National Clinical Research Center for Digestive Diseases, On behalf of China Registry of Genetic/Metabolic Liver Diseases (CR-GMLD) Group, Beijing, China
| | | | | | | | - Hong You
- Correspondence: E-mail: (Hong You)
| |
Collapse
|
50
|
Yang SA, Salazar JL, Li-Kroeger D, Yamamoto S. Functional Studies of Genetic Variants Associated with Human Diseases in Notch Signaling-Related Genes Using Drosophila. Methods Mol Biol 2022; 2472:235-276. [PMID: 35674905 PMCID: PMC9396741 DOI: 10.1007/978-1-0716-2201-8_19] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Rare variants in the many genes related to Notch signaling cause diverse Mendelian diseases that affect myriad organ systems. In addition, genome- and exome-wide association studies have linked common and rare variants in Notch-related genes to common diseases and phenotypic traits. Moreover, somatic mutations in these genes have been observed in many types of cancer, some of which are classified as oncogenic and others as tumor suppressive. While functional characterization of some of these variants has been performed through experimental studies, the number of "variants of unknown significance" identified in patients with diverse conditions keeps increasing as high-throughput sequencing technologies become more commonly used in the clinic. Furthermore, as disease gene discovery efforts identify rare variants in human genes that have yet to be linked to a disease, the demand for functional characterization of variants in these "genes of unknown significance" continues to increase. In this chapter, we describe a workflow to functionally characterize a rare variant in a Notch signaling related gene that was found to be associated with late-onset Alzheimer's disease. This pipeline involves informatic analysis of the variant of interest using diverse human and model organism databases, followed by in vivo experiments in the fruit fly Drosophila melanogaster. The protocol described here can be used to study variants that affect amino acids that are not conserved between human and fly. By "humanizing" the almondex gene in Drosophila with mutant alleles and heterologous genomic rescue constructs, a missense variant in TM2D3 (TM2 Domain Containing 3) was shown to be functionally damaging. This, and similar approaches, greatly facilitate functional interpretations of genetic variants in the human genome and propel personalized medicine.
Collapse
Affiliation(s)
- Sheng-An Yang
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
- Jan and Dan Duncan Neurological Research Institute, Texas Children's Hospital, Houston, TX, USA
| | - Jose L Salazar
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
- Jan and Dan Duncan Neurological Research Institute, Texas Children's Hospital, Houston, TX, USA
| | - David Li-Kroeger
- Jan and Dan Duncan Neurological Research Institute, Texas Children's Hospital, Houston, TX, USA.
- Department of Neurology, Baylor College of Medicine, Houston, TX, USA.
| | - Shinya Yamamoto
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA.
- Jan and Dan Duncan Neurological Research Institute, Texas Children's Hospital, Houston, TX, USA.
- Department of Neuroscience, Baylor College of Medicine, Houston, TX, USA.
- Development, Disease Models and Therapeutics Graduate Program, Baylor College of Medicine, Houston, TX, USA.
| |
Collapse
|