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Capalbo A, de Wert G, Mertes H, Klausner L, Coonen E, Spinella F, Van de Velde H, Viville S, Sermon K, Vermeulen N, Lencz T, Carmi S. Screening embryos for polygenic disease risk: a review of epidemiological, clinical, and ethical considerations. Hum Reprod Update 2024; 30:529-557. [PMID: 38805697 PMCID: PMC11369226 DOI: 10.1093/humupd/dmae012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2024] [Revised: 03/25/2024] [Indexed: 05/30/2024] Open
Abstract
BACKGROUND The genetic composition of embryos generated by in vitro fertilization (IVF) can be examined with preimplantation genetic testing (PGT). Until recently, PGT was limited to detecting single-gene, high-risk pathogenic variants, large structural variants, and aneuploidy. Recent advances have made genome-wide genotyping of IVF embryos feasible and affordable, raising the possibility of screening embryos for their risk of polygenic diseases such as breast cancer, hypertension, diabetes, or schizophrenia. Despite a heated debate around this new technology, called polygenic embryo screening (PES; also PGT-P), it is already available to IVF patients in some countries. Several articles have studied epidemiological, clinical, and ethical perspectives on PES; however, a comprehensive, principled review of this emerging field is missing. OBJECTIVE AND RATIONALE This review has four main goals. First, given the interdisciplinary nature of PES studies, we aim to provide a self-contained educational background about PES to reproductive specialists interested in the subject. Second, we provide a comprehensive and critical review of arguments for and against the introduction of PES, crystallizing and prioritizing the key issues. We also cover the attitudes of IVF patients, clinicians, and the public towards PES. Third, we distinguish between possible future groups of PES patients, highlighting the benefits and harms pertaining to each group. Finally, our review, which is supported by ESHRE, is intended to aid healthcare professionals and policymakers in decision-making regarding whether to introduce PES in the clinic, and if so, how, and to whom. SEARCH METHODS We searched for PubMed-indexed articles published between 1/1/2003 and 1/3/2024 using the terms 'polygenic embryo screening', 'polygenic preimplantation', and 'PGT-P'. We limited the review to primary research papers in English whose main focus was PES for medical conditions. We also included papers that did not appear in the search but were deemed relevant. OUTCOMES The main theoretical benefit of PES is a reduction in lifetime polygenic disease risk for children born after screening. The magnitude of the risk reduction has been predicted based on statistical modelling, simulations, and sibling pair analyses. Results based on all methods suggest that under the best-case scenario, large relative risk reductions are possible for one or more diseases. However, as these models abstract several practical limitations, the realized benefits may be smaller, particularly due to a limited number of embryos and unclear future accuracy of the risk estimates. PES may negatively impact patients and their future children, as well as society. The main personal harms are an unindicated IVF treatment, a possible reduction in IVF success rates, and patient confusion, incomplete counselling, and choice overload. The main possible societal harms include discarded embryos, an increasing demand for 'designer babies', overemphasis of the genetic determinants of disease, unequal access, and lower utility in people of non-European ancestries. Benefits and harms will vary across the main potential patient groups, comprising patients already requiring IVF, fertile people with a history of a severe polygenic disease, and fertile healthy people. In the United States, the attitudes of IVF patients and the public towards PES seem positive, while healthcare professionals are cautious, sceptical about clinical utility, and concerned about patient counselling. WIDER IMPLICATIONS The theoretical potential of PES to reduce risk across multiple polygenic diseases requires further research into its benefits and harms. Given the large number of practical limitations and possible harms, particularly unnecessary IVF treatments and discarded viable embryos, PES should be offered only within a research context before further clarity is achieved regarding its balance of benefits and harms. The gap in attitudes between healthcare professionals and the public needs to be narrowed by expanding public and patient education and providing resources for informative and unbiased genetic counselling.
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Affiliation(s)
- Antonio Capalbo
- Juno Genetics, Department of Reproductive Genetics, Rome, Italy
- Center for Advanced Studies and Technology (CAST), Department of Medical Genetics, “G. d’Annunzio” University of Chieti-Pescara, Chieti, Italy
| | - Guido de Wert
- Department of Health, Ethics & Society, CAPHRI-School for Public Health and Primary Care and GROW School for Oncology and Reproduction, Maastricht University, Maastricht, The Netherlands
| | - Heidi Mertes
- Department of Philosophy and Moral Sciences, Ghent University, Ghent, Belgium
- Department of Public Health and Primary Care, Ghent University, Ghent, Belgium
| | - Liraz Klausner
- Braun School of Public Health and Community Medicine, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Edith Coonen
- Departments of Clinical Genetics and Reproductive Medicine, Maastricht University Medical Centre, Maastricht, The Netherlands
- School for Oncology and Developmental Biology, GROW, Maastricht University, Maastricht, The Netherlands
| | - Francesca Spinella
- Eurofins GENOMA Group Srl, Molecular Genetics Laboratories, Department of Scientific Communication, Rome, Italy
| | - Hilde Van de Velde
- Research Group Genetics Reproduction and Development (GRAD), Vrije Universiteit Brussel, Brussel, Belgium
- Brussels IVF, UZ Brussel, Brussel, Belgium
| | - Stephane Viville
- Laboratoire de Génétique Médicale LGM, Institut de Génétique Médicale d’Alsace IGMA, INSERM UMR 1112, Université de Strasbourg, France
- Laboratoire de Diagnostic Génétique, Unité de Génétique de l’infertilité (UF3472), Hôpitaux Universitaires de Strasbourg, Strasbourg, France
| | - Karen Sermon
- Research Group Genetics Reproduction and Development (GRAD), Vrije Universiteit Brussel, Brussel, Belgium
| | | | - Todd Lencz
- Institute of Behavioral Science, Feinstein Institutes for Medical Research, Manhasset, NY, USA
- Departments of Psychiatry and Molecular Medicine, Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY 11549, USA
| | - Shai Carmi
- Braun School of Public Health and Community Medicine, The Hebrew University of Jerusalem, Jerusalem, Israel
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2
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Wright CF, Sharp LN, Jackson L, Murray A, Ware JS, MacArthur DG, Rehm HL, Patel KA, Weedon MN. Guidance for estimating penetrance of monogenic disease-causing variants in population cohorts. Nat Genet 2024; 56:1772-1779. [PMID: 39075210 DOI: 10.1038/s41588-024-01842-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2023] [Accepted: 06/24/2024] [Indexed: 07/31/2024]
Abstract
Penetrance is the probability that an individual with a pathogenic genetic variant develops a specific disease. Knowing the penetrance of variants for monogenic disorders is important for counseling of individuals. Until recently, estimates of penetrance have largely relied on affected individuals and their at-risk family members being clinically referred for genetic testing, a 'phenotype-first' approach. This approach substantially overestimates the penetrance of variants because of ascertainment bias. The recent availability of whole-genome sequencing data in individuals from very-large-scale population-based cohorts now allows 'genotype-first' estimates of penetrance for many conditions. Although this type of population-based study can underestimate penetrance owing to recruitment biases, it provides more accurate estimates of penetrance for secondary or incidental findings. Here, we provide guidance for the conduct of penetrance studies to ensure that robust genotypes and phenotypes are used to accurately estimate penetrance of variants and groups of similarly annotated variants from population-based studies.
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Affiliation(s)
- Caroline F Wright
- Department of Clinical and Biomedical Sciences, Medical School, University of Exeter, Exeter, UK.
| | - Luke N Sharp
- Department of Clinical and Biomedical Sciences, Medical School, University of Exeter, Exeter, UK
| | - Leigh Jackson
- Department of Clinical and Biomedical Sciences, Medical School, University of Exeter, Exeter, UK
| | - Anna Murray
- Department of Clinical and Biomedical Sciences, Medical School, University of Exeter, Exeter, UK
| | - James S Ware
- National Heart and Lung Institute and MRC Laboratory of Medical Sciences, Imperial College London, London, UK
- Hammersmith Hospital, Imperial College Healthcare NHS Trust, London, UK
- Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Daniel G MacArthur
- 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
| | - Heidi L Rehm
- Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Kashyap A Patel
- Department of Clinical and Biomedical Sciences, Medical School, University of Exeter, Exeter, UK
| | - Michael N Weedon
- Department of Clinical and Biomedical Sciences, Medical School, University of Exeter, Exeter, UK.
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3
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Platt CJ, Bierzynska A, Ding W, Saleem SA, Koziell A, Saleem MA. Rare heterozygous variants in paediatric steroid resistant nephrotic syndrome - a population-based analysis of their significance. Sci Rep 2024; 14:18568. [PMID: 39127776 DOI: 10.1038/s41598-024-68837-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2022] [Accepted: 07/29/2024] [Indexed: 08/12/2024] Open
Abstract
Genetic testing in nephrotic syndrome may identify heterozygous predicted-pathogenic variants (HPPVs) in autosomal recessive (AR) genes that are known to cause disease in the homozygous or compound heterozygous state. In such cases, it can be difficult to define the variant's true significance and questions remain about whether a second pathogenic variant has been missed during analysis or whether the variant is an incidental finding. There are now known to be over 70 genes associated with nephrotic syndrome, the majority inherited as an AR trait. Knowledge of whether such HPPVs occur with equal frequency in patients compared to the general population would assist interpretation of their significance. Exome sequencing was performed on 187 Steroid-Resistant Nephrotic Syndrome (SRNS) paediatric patients recruited to a UK rare disease registry plus originating from clinics at Evelina, London. 59 AR podocytopathy linked genes were analysed in each patient and a list of HPPVs created. We compared the frequency of detected HPPVs with a 'control' population from the gnomAD database containing exome data from approximately 50,000 individuals. A bespoke filtering process was used for both patients and controls to predict 'likely pathogenicity' of variants. In total 130 Caucasian SRNS patients were screened across 59 AR genes and 201 rare heterozygous variants were identified. 17/201 (8.5%) were assigned as 'likely pathogenic' (HPPV) using our bespoke filtering method. Comparing each gene in turn, for SRNS patients with a confirmed genetic diagnosis, in 57 of the 59 genes we found no statistically significant difference in the frequency of these HPPVs between patients and controls (In genes ARHGDIA and TP53RK, we identified a significantly higher number of HPPVs in the control population compared with the patients when filtering was performed with 'high stringency' settings only). In the SRNS patients without a genetics diagnosis confirmed, there was no statistically significant difference identified in any gene between patient and control. In children with SRNS, we propose that identification of HPPV in AR podocytopathy linked genes is not necessarily representative of pathogenicity, given that the frequency is similar to that seen in controls for the majority. Whilst this may not exclude the presence of genetic kidney disease, this type of heterozygous variant is unlikely to be causal and each result must be interpreted in its clinical context.
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Affiliation(s)
- C J Platt
- Bristol Royal Hospital for Children, Bristol, BS2 8NJ, UK.
| | - A Bierzynska
- Bristol Renal, University of Bristol, Bristol, UK
| | - W Ding
- Bristol Renal, University of Bristol, Bristol, UK
| | | | - A Koziell
- King's College and Evelina, London, UK
| | - M A Saleem
- Bristol Renal, University of Bristol, Bristol, UK
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4
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Borroto MC, Michaud C, Hudon C, Agrawal PB, Agre K, Applegate CD, Beggs AH, Bjornsson HT, Callewaert B, Chen MJ, Curry C, Devinsky O, Dudding-Byth T, Fagan K, Finnila CR, Gavrilova R, Genetti CA, Hiatt SM, Hildebrandt F, Wojcik MH, Kleefstra T, Kolvenbach CM, Korf BR, Kruszka P, Li H, Litwin J, Marcadier J, Platzer K, Blackburn PR, Reijnders MRF, Reutter H, Schanze I, Shieh JT, Stevens CA, Valivullah Z, van den Boogaard MJ, Klee EW, Campeau PM. A Genotype/Phenotype Study of KDM5B-Associated Disorders Suggests a Pathogenic Effect of Dominantly Inherited Missense Variants. Genes (Basel) 2024; 15:1033. [PMID: 39202393 PMCID: PMC11353349 DOI: 10.3390/genes15081033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2024] [Revised: 07/24/2024] [Accepted: 07/29/2024] [Indexed: 09/03/2024] Open
Abstract
Bi-allelic disruptive variants (nonsense, frameshift, and splicing variants) in KDM5B have been identified as causative for autosomal recessive intellectual developmental disorder type 65. In contrast, dominant variants, usually disruptive as well, have been more difficult to implicate in a specific phenotype, since some of them have been found in unaffected controls or relatives. Here, we describe individuals with likely pathogenic variants in KDM5B, including eight individuals with dominant missense variants. This study is a retrospective case series of 21 individuals with variants in KDM5B. We performed deep phenotyping and collected the clinical information and molecular data of these individuals' family members. We compared the phenotypes according to variant type and to those previously described in the literature. The most common features were developmental delay, impaired intellectual development, behavioral problems, autistic behaviors, sleep disorders, facial dysmorphism, and overgrowth. DD, ASD behaviors, and sleep disorders were more common in individuals with dominant disruptive KDM5B variants, while individuals with dominant missense variants presented more frequently with renal and skin anomalies. This study extends our understanding of the KDM5B-related neurodevelopmental disorder and suggests the pathogenicity of certain dominant KDM5B missense variants.
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Affiliation(s)
- Maria Carla Borroto
- Centre de Recherche Azrieli du CHU Sainte-Justine, University of Montreal, Montreal, QC H3T 1C5, Canada (C.H.)
| | - Coralie Michaud
- Centre de Recherche Azrieli du CHU Sainte-Justine, University of Montreal, Montreal, QC H3T 1C5, Canada (C.H.)
| | - Chloé Hudon
- Centre de Recherche Azrieli du CHU Sainte-Justine, University of Montreal, Montreal, QC H3T 1C5, Canada (C.H.)
| | - Pankaj B. Agrawal
- The Manton Center for Orphan Disease Research, Divisions of Newborn Medicine and of Genetics and Genomics, Boston Children’s Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Katherine Agre
- Department of Clinical Genomics, Mayo Clinic, Rochester, MN 55902, USA
| | - Carolyn D. Applegate
- Department of Genetic Medicine, McKusick-Nathans Institute, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA; (C.D.A.)
| | - Alan H. Beggs
- The Manton Center for Orphan Disease Research, Division of Genetics and Genomics, Boston Children’s Hospital, Harvard Medical School, Boston, MA 02115, USA; (A.H.B.)
| | - Hans T. Bjornsson
- Department of Genetic Medicine, McKusick-Nathans Institute, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA; (C.D.A.)
- Louma G. Laboratory of Epigenetic Research, Faculty of Medicine, University of Iceland, 101 Reykjavik, Iceland
- Department of Genetics and Molecular Medicine, Landspitali University Hospital, 101 Reykjavik, Iceland
| | - Bert Callewaert
- Center for Medical Genetics, Ghent University Hospital, 9000 Ghent, Belgium
| | - Mei-Jan Chen
- Department of Genetics, University of Alabama at Birmingham, Birmingham, AL 35294, USA
| | - Cynthia Curry
- Genetic Medicine, University of California San Francisco/Fresno, Fresno, CA 93701, USA
| | - Orrin Devinsky
- Departments of Neurology, Neuroscience, Neurosurgery and Psychiatry, NYU School of Medicine, New York, NY 10016, USA
| | | | - Kelly Fagan
- UCSF Benioff Children’s Hospital, San Francisco, CA 93940, USA
| | - Candice R. Finnila
- HudsonAlpha Institute for Biotechnology, 601 Genome Way, Huntsville, AL 35806, USA
| | - Ralitza Gavrilova
- Department of Clinical Genomics, Mayo Clinic, Rochester, MN 55902, USA
- Department of Neurology, Mayo Clinic, Rochester, MN 55902, USA
| | - Casie A. Genetti
- The Manton Center for Orphan Disease Research, Division of Genetics and Genomics, Boston Children’s Hospital, Harvard Medical School, Boston, MA 02115, USA; (A.H.B.)
| | - Susan M. Hiatt
- HudsonAlpha Institute for Biotechnology, 601 Genome Way, Huntsville, AL 35806, USA
| | - Friedhelm Hildebrandt
- Department of Pediatrics, Boston Children’s Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Monica H. Wojcik
- The Manton Center for Orphan Disease Research, Divisions of Newborn Medicine and of Genetics and Genomics, Boston Children’s Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Tjitske Kleefstra
- Department of Human Genetics, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands
| | - Caroline M. Kolvenbach
- Department of Pediatrics, Boston Children’s Hospital, Harvard Medical School, Boston, MA 02115, USA
- Institute of Anatomy and Cell Biology, Medical Faculty, University of Bonn, 53127 Bonn, Germany
| | - Bruce R. Korf
- Department of Genetics, University of Alabama at Birmingham, Birmingham, AL 35294, USA
| | | | - Hong Li
- Department of Human Genetics, School of Medicine, Emory University, Atlanta, GA 30322, USA
| | - Jessica Litwin
- Department of Neurology, University of California, San Francisco Benioff Children’s Hospital, San Francisco, CA 94158, USA
| | - Julien Marcadier
- Division of Medical Genetics, Alberta Children’s Hospital, Calgary, AB T3B 6A8, Canada
| | - Konrad Platzer
- Institute of Human Genetics, University of Leipzig Medical Center, 04103 Leipzig, Germany
| | | | - Margot R. F. Reijnders
- Department of Human Genetics, Radboud Institute for Molecular Life Sciences, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands
| | - Heiko Reutter
- Institute of Human Genetics, University Hospital of Bonn, 53127 Bonn, Germany
| | - Ina Schanze
- Institute of Human Genetics, 39120 Magdeburg, Germany
| | - Joseph T. Shieh
- Division of Medical Genetics, Department of Pediatrics, University of California, San Francisco Benioff Childen’s Hospital, San Francisco, CA 94143, USA
| | - Cathy A. Stevens
- Department of Pediatrics, University of Tennessee College of Medicine, Chattanooga, TN 38103, USA
| | - Zaheer Valivullah
- Center for Mendelian Genomics, Broad Institute Harvard, Cambridge, MA 02142, USA
| | | | - Eric W. Klee
- Department of Clinical Genomics, Mayo Clinic, Rochester, MN 55902, USA
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN 55902, USA
| | - Philippe M. Campeau
- Centre de Recherche Azrieli du CHU Sainte-Justine, University of Montreal, Montreal, QC H3T 1C5, Canada (C.H.)
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5
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Ma K, Huang S, Ng KK, Lake NJ, Joseph S, Xu J, Lek A, Ge L, Woodman KG, Koczwara KE, Cohen J, Ho V, O'Connor CL, Brindley MA, Campbell KP, Lek M. Deep Mutational Scanning in Disease-related Genes with Saturation Mutagenesis-Reinforced Functional Assays (SMuRF). BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.07.12.548370. [PMID: 37873263 PMCID: PMC10592615 DOI: 10.1101/2023.07.12.548370] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/25/2023]
Abstract
Interpretation of disease-causing genetic variants remains a challenge in human genetics. Current costs and complexity of deep mutational scanning methods hamper crowd-sourcing approaches toward genome-wide resolution of variants in disease-related genes. Our framework, Saturation Mutagenesis-Reinforced Functional assays (SMuRF), addresses these issues by offering simple and cost-effective saturation mutagenesis, as well as streamlining functional assays to enhance the interpretation of unresolved variants. Applying SMuRF to neuromuscular disease genes FKRP and LARGE1, we generated functional scores for all possible coding single nucleotide variants, which aid in resolving clinically reported variants of uncertain significance. SMuRF also demonstrates utility in predicting disease severity, resolving critical structural regions, and providing training datasets for the development of computational predictors. Our approach opens new directions for enabling variant-to-function insights for disease genes in a manner that is broadly useful for crowd-sourcing implementation across standard research laboratories.
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Affiliation(s)
- Kaiyue Ma
- Department of Genetics, Yale School of Medicine, New Haven, CT, USA
| | - Shushu Huang
- Department of Genetics, Yale School of Medicine, New Haven, CT, USA
- Equal second authors
| | - Kenneth K Ng
- Department of Genetics, Yale School of Medicine, New Haven, CT, USA
- Equal second authors
| | - Nicole J Lake
- Department of Genetics, Yale School of Medicine, New Haven, CT, USA
| | - Soumya Joseph
- Howard Hughes Medical Institute, Senator Paul D. Wellstone Muscular Dystrophy Specialized Research Center, Department of Molecular Physiology and Biophysics and Department of Neurology, Roy J. and Lucille A. Carver College of Medicine, The University of Iowa, Iowa City, IA, USA
| | - Jenny Xu
- Yale University, New Haven, CT, USA
| | - Angela Lek
- Department of Genetics, Yale School of Medicine, New Haven, CT, USA
- Muscular Dystrophy Association, Chicago, IL, USA
| | - Lin Ge
- Department of Genetics, Yale School of Medicine, New Haven, CT, USA
- Department of Neurology, National Center for Children's Health, Beijing Children's Hospital, Capital Medical University, Beijing, China
| | - Keryn G Woodman
- Department of Genetics, Yale School of Medicine, New Haven, CT, USA
| | | | - Justin Cohen
- Department of Genetics, Yale School of Medicine, New Haven, CT, USA
| | - Vincent Ho
- Department of Genetics, Yale School of Medicine, New Haven, CT, USA
| | | | - Melinda A Brindley
- Department of Infectious Diseases, Department of Population Health, University of Georgia, Athens, GA, USA
- Senior Authors
| | - Kevin P Campbell
- Howard Hughes Medical Institute, Senator Paul D. Wellstone Muscular Dystrophy Specialized Research Center, Department of Molecular Physiology and Biophysics and Department of Neurology, Roy J. and Lucille A. Carver College of Medicine, The University of Iowa, Iowa City, IA, USA
- Senior Authors
| | - Monkol Lek
- Department of Genetics, Yale School of Medicine, New Haven, CT, USA
- Senior Authors
- Lead Contact
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6
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Stefanucci L, Collins J, Sims MC, Barrio-Hernandez I, Sun L, Burren OS, Perfetto L, Bender I, Callahan TJ, Fleming K, Guerrero JA, Hermjakob H, Martin MJ, Stephenson J, Paneerselvam K, Petrovski S, Porras P, Robinson PN, Wang Q, Watkins X, Frontini M, Laskowski RA, Beltrao P, Di Angelantonio E, Gomez K, Laffan M, Ouwehand WH, Mumford AD, Freson K, Carss K, Downes K, Gleadall N, Megy K, Bruford E, Vuckovic D. The effects of pathogenic and likely pathogenic variants for inherited hemostasis disorders in 140 214 UK Biobank participants. Blood 2023; 142:2055-2068. [PMID: 37647632 PMCID: PMC10733830 DOI: 10.1182/blood.2023020118] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2023] [Revised: 08/04/2023] [Accepted: 08/04/2023] [Indexed: 09/01/2023] Open
Abstract
Rare genetic diseases affect millions, and identifying causal DNA variants is essential for patient care. Therefore, it is imperative to estimate the effect of each independent variant and improve their pathogenicity classification. Our study of 140 214 unrelated UK Biobank (UKB) participants found that each of them carries a median of 7 variants previously reported as pathogenic or likely pathogenic. We focused on 967 diagnostic-grade gene (DGG) variants for rare bleeding, thrombotic, and platelet disorders (BTPDs) observed in 12 367 UKB participants. By association analysis, for a subset of these variants, we estimated effect sizes for platelet count and volume, and odds ratios for bleeding and thrombosis. Variants causal of some autosomal recessive platelet disorders revealed phenotypic consequences in carriers. Loss-of-function variants in MPL, which cause chronic amegakaryocytic thrombocytopenia if biallelic, were unexpectedly associated with increased platelet counts in carriers. We also demonstrated that common variants identified by genome-wide association studies (GWAS) for platelet count or thrombosis risk may influence the penetrance of rare variants in BTPD DGGs on their associated hemostasis disorders. Network-propagation analysis applied to an interactome of 18 410 nodes and 571 917 edges showed that GWAS variants with large effect sizes are enriched in DGGs and their first-order interactors. Finally, we illustrate the modifying effect of polygenic scores for platelet count and thrombosis risk on disease severity in participants carrying rare variants in TUBB1 or PROC and PROS1, respectively. Our findings demonstrate the power of association analyses using large population datasets in improving pathogenicity classifications of rare variants.
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Affiliation(s)
- Luca Stefanucci
- Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Cambridge, United Kingdom
- National Health Service Blood and Transplant, Cambridge Biomedical Campus, Cambridge, United Kingdom
- British Heart Foundation, BHF Centre of Research Excellence, University of Cambridge, Cambridge Biomedical Campus, Cambridge, United Kingdom
| | - Janine Collins
- Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Cambridge, United Kingdom
- National Health Service Blood and Transplant, Cambridge Biomedical Campus, Cambridge, United Kingdom
- Department of Haematology, Barts Health NHS Trust, London, United Kingdom
| | - Matthew C. Sims
- Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Cambridge, United Kingdom
- National Health Service Blood and Transplant, Cambridge Biomedical Campus, Cambridge, United Kingdom
- Department of Haematology, Sheffield Teaching Hospitals NHS Foundation Trust, Royal Hallamshire Hospital, Sheffield, United Kingdom
- Department of Oncology and Metabolism, University of Sheffield, Sheffield, United Kingdom
| | - Inigo Barrio-Hernandez
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Cambridge, United Kingdom
| | - Luanluan Sun
- Department of Public Health and Primary Care, BHF Cardiovascular Epidemiology Unit, University of Cambridge, Cambridge, United Kingdom
| | - Oliver S. Burren
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, United Kingdom
| | - Livia Perfetto
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Cambridge, United Kingdom
- Department of Biology and Biotechnology “C.Darwin,” Sapienza University of Rome, Rome, Italy
| | - Isobel Bender
- Department of Biochemistry, University of Oxford, Oxford, United Kingdom
| | - Tiffany J. Callahan
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY
| | - Kathryn Fleming
- School of Cellular and Molecular Medicine, University of Bristol, Bristol, United Kingdom
| | - Jose A. Guerrero
- National Health Service Blood and Transplant, Cambridge Biomedical Campus, Cambridge, United Kingdom
- Department of Haematology, Barts Health NHS Trust, London, United Kingdom
| | - Henning Hermjakob
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Cambridge, United Kingdom
| | - Maria J. Martin
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Cambridge, United Kingdom
| | - James Stephenson
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Cambridge, United Kingdom
| | - NIHR BioResource
- Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Cambridge, United Kingdom
- National Health Service Blood and Transplant, Cambridge Biomedical Campus, Cambridge, United Kingdom
- British Heart Foundation, BHF Centre of Research Excellence, University of Cambridge, Cambridge Biomedical Campus, Cambridge, United Kingdom
- Department of Haematology, Barts Health NHS Trust, London, United Kingdom
- Department of Haematology, Sheffield Teaching Hospitals NHS Foundation Trust, Royal Hallamshire Hospital, Sheffield, United Kingdom
- Department of Oncology and Metabolism, University of Sheffield, Sheffield, United Kingdom
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Cambridge, United Kingdom
- Department of Public Health and Primary Care, BHF Cardiovascular Epidemiology Unit, University of Cambridge, Cambridge, United Kingdom
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, United Kingdom
- Department of Biology and Biotechnology “C.Darwin,” Sapienza University of Rome, Rome, Italy
- Department of Biochemistry, University of Oxford, Oxford, United Kingdom
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY
- School of Cellular and Molecular Medicine, University of Bristol, Bristol, United Kingdom
- Centre for Genomics Research, Discovery Sciences, AstraZeneca, Cambridge, United Kingdom
- Department of Medicine, Austin Health, The University of Melbourne, Melbourne, Australia
- Genomic Medicine, The Jackson Laboratory, Farmington, CT
- Institute for Systems Genomics, University of Connecticut, Farmington, CT
- Department of Clinical and Biomedical Sciences, Faculty of Health and Life Sciences RILD Building, University of Exeter Medical School, Exeter, United Kingdom
- Institute of Molecular Systems Biology, ETH Zürich, Zürich, Switzerland
- Heart and Lung Research Institute, University of Cambridge, Cambridge, United Kingdom
- NIHR Blood and Transplant Research Unit in Donor Health and Behaviour, Cambridge, United Kingdom
- Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, United Kingdom
- Health Data Science Centre, Human Technopole, Milan, Italy
- Haemophilia Centre and Thrombosis Unit, Royal Free London NHS Foundation Trust, London, United Kingdom
- Department of Haematology, Imperial College Healthcare NHS Trust, London, United Kingdom
- Department of Immunology and Inflammation, Centre for Haematology, Imperial College London, London, United Kingdom
- Department of Haematology, University College London Hospitals NHS Trust, London, United Kingdom
- Department of Cardiovascular Sciences, Center for Molecular and Vascular Biology, KULeuven, Leuven, Belgium
- Cambridge Genomics Laboratory, Cambridge University Hospitals National Health Service Foundation Trust, Cambridge Biomedical Campus, Cambridge, United Kingdom
- Department of Epidemiology and Biostatistics, Imperial College London, London, United Kingdom
| | - Kalpana Paneerselvam
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Cambridge, United Kingdom
| | - Slavé Petrovski
- Centre for Genomics Research, Discovery Sciences, AstraZeneca, Cambridge, United Kingdom
- Department of Medicine, Austin Health, The University of Melbourne, Melbourne, Australia
| | - Pablo Porras
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Cambridge, United Kingdom
| | - Peter N. Robinson
- Genomic Medicine, The Jackson Laboratory, Farmington, CT
- Institute for Systems Genomics, University of Connecticut, Farmington, CT
| | - Quanli Wang
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, United Kingdom
| | - Xavier Watkins
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Cambridge, United Kingdom
| | - Mattia Frontini
- Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Cambridge, United Kingdom
- National Health Service Blood and Transplant, Cambridge Biomedical Campus, Cambridge, United Kingdom
- British Heart Foundation, BHF Centre of Research Excellence, University of Cambridge, Cambridge Biomedical Campus, Cambridge, United Kingdom
- Department of Clinical and Biomedical Sciences, Faculty of Health and Life Sciences RILD Building, University of Exeter Medical School, Exeter, United Kingdom
| | - Roman A. Laskowski
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Cambridge, United Kingdom
| | - Pedro Beltrao
- Institute of Molecular Systems Biology, ETH Zürich, Zürich, Switzerland
| | - Emanuele Di Angelantonio
- British Heart Foundation, BHF Centre of Research Excellence, University of Cambridge, Cambridge Biomedical Campus, Cambridge, United Kingdom
- Department of Public Health and Primary Care, BHF Cardiovascular Epidemiology Unit, University of Cambridge, Cambridge, United Kingdom
- Heart and Lung Research Institute, University of Cambridge, Cambridge, United Kingdom
- NIHR Blood and Transplant Research Unit in Donor Health and Behaviour, Cambridge, United Kingdom
- Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, United Kingdom
- Health Data Science Centre, Human Technopole, Milan, Italy
| | - Keith Gomez
- Haemophilia Centre and Thrombosis Unit, Royal Free London NHS Foundation Trust, London, United Kingdom
| | - Mike Laffan
- Department of Haematology, Imperial College Healthcare NHS Trust, London, United Kingdom
- Department of Immunology and Inflammation, Centre for Haematology, Imperial College London, London, United Kingdom
| | - Willem H. Ouwehand
- Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Cambridge, United Kingdom
- National Health Service Blood and Transplant, Cambridge Biomedical Campus, Cambridge, United Kingdom
- Department of Haematology, University College London Hospitals NHS Trust, London, United Kingdom
| | - Andrew D. Mumford
- School of Cellular and Molecular Medicine, University of Bristol, Bristol, United Kingdom
| | - Kathleen Freson
- Department of Cardiovascular Sciences, Center for Molecular and Vascular Biology, KULeuven, Leuven, Belgium
| | - Keren Carss
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, United Kingdom
| | - Kate Downes
- Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Cambridge, United Kingdom
- National Health Service Blood and Transplant, Cambridge Biomedical Campus, Cambridge, United Kingdom
- Cambridge Genomics Laboratory, Cambridge University Hospitals National Health Service Foundation Trust, Cambridge Biomedical Campus, Cambridge, United Kingdom
| | - Nick Gleadall
- Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Cambridge, United Kingdom
- National Health Service Blood and Transplant, Cambridge Biomedical Campus, Cambridge, United Kingdom
| | - Karyn Megy
- Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Cambridge, United Kingdom
| | - Elspeth Bruford
- Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Cambridge, United Kingdom
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Cambridge, United Kingdom
| | - Dragana Vuckovic
- Department of Epidemiology and Biostatistics, Imperial College London, London, United Kingdom
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7
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Dulski J, Soto-Beasley AI, Uitti RJ, Wszolek ZK, Ross OA. PTPA variants are rare in early-onset and familial Parkinson's disease. Brain 2023; 146:e125-e127. [PMID: 37448355 DOI: 10.1093/brain/awad244] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2022] [Revised: 06/23/2023] [Accepted: 07/06/2023] [Indexed: 07/15/2023] Open
Affiliation(s)
- Jarosław Dulski
- Department of Neurology, Mayo Clinic, Jacksonville, FL 32224, USA
- Division of Neurological and Psychiatric Nursing, Faculty of Health Sciences, Medical University of Gdansk, 80-211 Gdansk, Poland
- Neurology Department, St Adalbert Hospital, Copernicus PL Ltd., 80-462 Gdansk, Poland
| | | | - Ryan J Uitti
- Department of Neurology, Mayo Clinic, Jacksonville, FL 32224, USA
| | | | - Owen A Ross
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL 32224, USA
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8
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Levitin MO, Rawlins LE, Sanchez-Andrade G, Arshad OA, Collins SC, Sawiak SJ, Iffland PH, Andersson MHL, Bupp C, Cambridge EL, Coomber EL, Ellis I, Herkert JC, Ironfield H, Jory L, Kretz PF, Kant SG, Neaverson A, Nibbeling E, Rowley C, Relton E, Sanderson M, Scott EM, Stewart H, Shuen AY, Schreiber J, Tuck L, Tonks J, Terkelsen T, van Ravenswaaij-Arts C, Vasudevan P, Wenger O, Wright M, Day A, Hunter A, Patel M, Lelliott CJ, Crino PB, Yalcin B, Crosby AH, Baple EL, Logan DW, Hurles ME, Gerety SS. Models of KPTN-related disorder implicate mTOR signalling in cognitive and overgrowth phenotypes. Brain 2023; 146:4766-4783. [PMID: 37437211 PMCID: PMC10629792 DOI: 10.1093/brain/awad231] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2022] [Revised: 05/31/2023] [Accepted: 06/18/2023] [Indexed: 07/14/2023] Open
Abstract
KPTN-related disorder is an autosomal recessive disorder associated with germline variants in KPTN (previously known as kaptin), a component of the mTOR regulatory complex KICSTOR. To gain further insights into the pathogenesis of KPTN-related disorder, we analysed mouse knockout and human stem cell KPTN loss-of-function models. Kptn -/- mice display many of the key KPTN-related disorder phenotypes, including brain overgrowth, behavioural abnormalities, and cognitive deficits. By assessment of affected individuals, we have identified widespread cognitive deficits (n = 6) and postnatal onset of brain overgrowth (n = 19). By analysing head size data from their parents (n = 24), we have identified a previously unrecognized KPTN dosage-sensitivity, resulting in increased head circumference in heterozygous carriers of pathogenic KPTN variants. Molecular and structural analysis of Kptn-/- mice revealed pathological changes, including differences in brain size, shape and cell numbers primarily due to abnormal postnatal brain development. Both the mouse and differentiated induced pluripotent stem cell models of the disorder display transcriptional and biochemical evidence for altered mTOR pathway signalling, supporting the role of KPTN in regulating mTORC1. By treatment in our KPTN mouse model, we found that the increased mTOR signalling downstream of KPTN is rapamycin sensitive, highlighting possible therapeutic avenues with currently available mTOR inhibitors. These findings place KPTN-related disorder in the broader group of mTORC1-related disorders affecting brain structure, cognitive function and network integrity.
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Affiliation(s)
- Maria O Levitin
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
- Evox Therapeutics Limited, Oxford OX4 4HG, UK
| | - Lettie E Rawlins
- RILD Wellcome Wolfson Medical Research Centre, University of Exeter, Exeter EX2 5DW, UK
- Peninsula Clinical Genetics Service, Royal Devon University Healthcare NHS Foundation Trust, Exeter EX1 2ED, UK
| | | | - Osama A Arshad
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Stephan C Collins
- INSERM Unit 1231, Université de Bourgogne Franche-Comté, Dijon 21078, France
| | - Stephen J Sawiak
- Behavioural and Clinical Neuroscience Institute, University of Cambridge, Cambridge CB2 3EB, UK
- Wolfson Brain Imaging Centre, Department of Clinical Neurosciences, University of Cambridge, Cambridge CB2 0QQ, UK
| | - Phillip H Iffland
- Department of Neurology, University of Maryland School of Medicine, Baltimore, MD 21201, USA
| | - Malin H L Andersson
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Caleb Bupp
- Spectrum Health, Helen DeVos Children’s Hospital, Grand Rapids, MI 49503, USA
| | - Emma L Cambridge
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Eve L Coomber
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Ian Ellis
- Department of Clinical Genetics, Alder Hey Children’s Hospital, Liverpool L14 5AB, UK
| | - Johanna C Herkert
- Department of Genetics, University Medical Centre, University of Groningen, Groningen 9713 GZ, The Netherlands
| | - Holly Ironfield
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Logan Jory
- Haven Clinical Psychology Practice Ltd, Bude, Cornwall EX23 9HP, UK
| | | | - Sarina G Kant
- Department of Clinical Genetics, Erasmus MC, University Medical Center Rotterdam, Rotterdam 3015 GD, The Netherlands
- Department of Clinical Genetics, Leiden University Medical Center, Leiden 2300 RC, The Netherlands
| | - Alexandra Neaverson
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
- Open Targets, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
- Department of Genetics, University of Cambridge, Cambridge CB2 3EH, UK
| | - Esther Nibbeling
- Laboratory for Diagnostic Genome Analysis, Department of Clinical Genetics, Leiden University Medical Center, Leiden 3015 GD, The Netherlands
| | - Christine Rowley
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
- Institute of Metabolic Science, Cambridge University, Cambridge CB2 0QQ, UK
| | - Emily Relton
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
- Faculty of Health and Medical Science, University of Surrey, Guildford GU2 7YH, UK
| | - Mark Sanderson
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Ethan M Scott
- New Leaf Center, Clinic for Special Children, Mount Eaton, OH 44659, USA
| | - Helen Stewart
- Oxford Centre for Genomic Medicine, Oxford University Hospitals NHS Trust, Oxford OX3 7HE, UK
| | - Andrew Y Shuen
- London Health Sciences Centre, London, ON N6A 5W9, Canada
- Division of Medical Genetics, Department of Pediatrics, Schulich School of Medicine and Dentistry, Western University, London, ON N6A 5W9, Canada
| | - John Schreiber
- Department of Neurology, Children’s National Medical Center, Washington DC 20007, USA
| | - Liz Tuck
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - James Tonks
- Haven Clinical Psychology Practice Ltd, Bude, Cornwall EX23 9HP, UK
| | - Thorkild Terkelsen
- Department of Clinical Genetics, Aarhus University Hospital, Aarhus DK-8200, Denmark
| | - Conny van Ravenswaaij-Arts
- Department of Genetics, University Medical Centre, University of Groningen, Groningen 9713 GZ, The Netherlands
| | - Pradeep Vasudevan
- Department of Clinical Genetics, University Hospitals of Leicester, Leicester Royal Infirmary, Leicester LE1 7RH, UK
| | - Olivia Wenger
- New Leaf Center, Clinic for Special Children, Mount Eaton, OH 44659, USA
| | - Michael Wright
- Institute of Human Genetics, International Centre for Life, Newcastle upon Tyne NE1 7RU, UK
| | - Andrew Day
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
- Qkine Ltd., Cambridge CB5 8HW, UK
| | - Adam Hunter
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Minal Patel
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Christopher J Lelliott
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
- Institute of Metabolic Science, Cambridge University, Cambridge CB2 0QQ, UK
| | - Peter B Crino
- Department of Neurology, University of Maryland School of Medicine, Baltimore, MD 21201, USA
| | - Binnaz Yalcin
- INSERM Unit 1231, Université de Bourgogne Franche-Comté, Dijon 21078, France
| | - Andrew H Crosby
- RILD Wellcome Wolfson Medical Research Centre, University of Exeter, Exeter EX2 5DW, UK
| | - Emma L Baple
- RILD Wellcome Wolfson Medical Research Centre, University of Exeter, Exeter EX2 5DW, UK
- Peninsula Clinical Genetics Service, Royal Devon University Healthcare NHS Foundation Trust, Exeter EX1 2ED, UK
| | - Darren W Logan
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
- Waltham Petcare Science Institute, Waltham on the Wolds LE14 4RT, UK
| | - Matthew E Hurles
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
- Open Targets, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Sebastian S Gerety
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
- Open Targets, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
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9
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Lipov A, Jurgens SJ, Mazzarotto F, Allouba M, Pirruccello JP, Aguib Y, Gennarelli M, Yacoub MH, Ellinor PT, Bezzina CR, Walsh R. Exploring the complex spectrum of dominance and recessiveness in genetic cardiomyopathies. NATURE CARDIOVASCULAR RESEARCH 2023; 2:1078-1094. [PMID: 38666070 PMCID: PMC11041721 DOI: 10.1038/s44161-023-00346-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/07/2023] [Accepted: 09/07/2023] [Indexed: 04/28/2024]
Abstract
Discrete categorization of Mendelian disease genes into dominant and recessive models often oversimplifies their underlying genetic architecture. Cardiomyopathies (CMs) are genetic diseases with complex etiologies for which an increasing number of recessive associations have recently been proposed. Here, we comprehensively analyze all published evidence pertaining to biallelic variation associated with CM phenotypes to identify high-confidence recessive genes and explore the spectrum of monoallelic and biallelic variant effects in established recessive and dominant disease genes. We classify 18 genes with robust recessive association with CMs, largely characterized by dilated phenotypes, early disease onset and severe outcomes. Several of these genes have monoallelic association with disease outcomes and cardiac traits in the UK Biobank, including LMOD2 and ALPK3 with dilated and hypertrophic CM, respectively. Our data provide insights into the complex spectrum of dominance and recessiveness in genetic heart disease and demonstrate how such approaches enable the discovery of unexplored genetic associations.
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Affiliation(s)
- Alex Lipov
- Department of Experimental Cardiology, Heart Centre, Amsterdam UMC, Amsterdam, the Netherlands
- Amsterdam Cardiovascular Sciences, Heart Failure & Arrhythmias, Amsterdam, the Netherlands
| | - Sean J. Jurgens
- Department of Experimental Cardiology, Heart Centre, Amsterdam UMC, Amsterdam, the Netherlands
- Amsterdam Cardiovascular Sciences, Heart Failure & Arrhythmias, Amsterdam, the Netherlands
- Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA USA
- Cardiovascular Research Center, Massachusetts General Hospital, Harvard Medical School, Boston, MA USA
| | - Francesco Mazzarotto
- Department of Molecular and Translational Medicine, University of Brescia, Brescia, Italy
- National Heart and Lung Institute, Imperial College London, London, UK
| | - Mona Allouba
- National Heart and Lung Institute, Imperial College London, London, UK
- Aswan Heart Centre, Magdi Yacoub Heart Foundation, Aswan, Egypt
| | - James P. Pirruccello
- Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA USA
- Division of Cardiology, University of California, San Francisco, San Francisco, CA USA
| | - Yasmine Aguib
- National Heart and Lung Institute, Imperial College London, London, UK
- Aswan Heart Centre, Magdi Yacoub Heart Foundation, Aswan, Egypt
| | - Massimo Gennarelli
- Department of Molecular and Translational Medicine, University of Brescia, Brescia, Italy
- Genetics Unit, Istituto di Ricovero e Cura a Carattere Scientifico, Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Magdi H. Yacoub
- National Heart and Lung Institute, Imperial College London, London, UK
- Aswan Heart Centre, Magdi Yacoub Heart Foundation, Aswan, Egypt
- Harefield Heart Science Centre, Uxbridge, UK
| | - Patrick T. Ellinor
- Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA USA
- Cardiovascular Research Center, Massachusetts General Hospital, Harvard Medical School, Boston, MA USA
- Demoulas Center for Cardiac Arrhythmias, Massachusetts General Hospital, Boston, MA USA
| | - Connie R. Bezzina
- Department of Experimental Cardiology, Heart Centre, Amsterdam UMC, Amsterdam, the Netherlands
- Amsterdam Cardiovascular Sciences, Heart Failure & Arrhythmias, Amsterdam, the Netherlands
- European Reference Network for Rare and Low Prevalence Complex Diseases of the Heart, Amsterdam, the Netherlands
| | - Roddy Walsh
- Department of Experimental Cardiology, Heart Centre, Amsterdam UMC, Amsterdam, the Netherlands
- Amsterdam Cardiovascular Sciences, Heart Failure & Arrhythmias, Amsterdam, the Netherlands
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10
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Hill DP, Drabkin HJ, Smith CL, Van Auken KM, D’Eustachio P. Biochemical pathways represented by Gene Ontology-Causal Activity Models identify distinct phenotypes resulting from mutations in pathways. Genetics 2023; 225:iyad152. [PMID: 37579192 PMCID: PMC10550311 DOI: 10.1093/genetics/iyad152] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2023] [Revised: 07/13/2023] [Accepted: 08/02/2023] [Indexed: 08/16/2023] Open
Abstract
Gene inactivation can affect the process(es) in which that gene acts and causally downstream ones, yielding diverse mutant phenotypes. Identifying the genetic pathways resulting in a given phenotype helps us understand how individual genes interact in a functional network. Computable representations of biological pathways include detailed process descriptions in the Reactome Knowledgebase and causal activity flows between molecular functions in Gene Ontology-Causal Activity Models (GO-CAMs). A computational process has been developed to convert Reactome pathways to GO-CAMs. Laboratory mice are widely used models of normal and pathological human processes. We have converted human Reactome GO-CAMs to orthologous mouse GO-CAMs, as a resource to transfer pathway knowledge between humans and model organisms. These mouse GO-CAMs allowed us to define sets of genes that function in a causally connected way. To demonstrate that individual variant genes from connected pathways result in similar but distinguishable phenotypes, we used the genes in our pathway models to cross-query mouse phenotype annotations in the Mouse Genome Database (MGD). Using GO-CAM representations of 2 related but distinct pathways, gluconeogenesis and glycolysis, we show that individual causal paths in gene networks give rise to discrete phenotypic outcomes resulting from perturbations of glycolytic and gluconeogenic genes. The accurate and detailed descriptions of gene interactions recovered in this analysis of well-studied processes suggest that this strategy can be applied to less well-understood processes in less well-studied model systems to predict phenotypic outcomes of novel gene variants and to identify potential gene targets in altered processes.
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Affiliation(s)
- David P Hill
- The Jackson Laboratory, Bar Harbor, ME 04609, USA
| | | | | | - Kimberly M Van Auken
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA 91125, USA
| | - Peter D’Eustachio
- Department of Biochemistry and Molecular Pharmacology, New York University Grossman School of Medicine, New York, NY 10016, USA
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11
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Tsai MJM, Hung MZ, Lin YL, Lee NC, Chien YH, Hwu WL. Curated incidence of lysosomal storage diseases from the Taiwan Biobank. NPJ Genom Med 2023; 8:27. [PMID: 37741878 PMCID: PMC10517920 DOI: 10.1038/s41525-023-00372-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2023] [Accepted: 09/04/2023] [Indexed: 09/25/2023] Open
Abstract
Lysosomal storage diseases (LSDs) are a group of metabolic disorders resulting from a deficiency in one of the lysosomal hydrolases. Most LSDs are inherited in an autosomal or X-linked recessive manner. As LSDs are rare, their true incidence in Taiwan remains unknown. In this study, we used high-coverage whole-genome sequencing data from 1,495 Taiwanese individuals obtained from the Taiwan Biobank. We found 3826 variants in 71 genes responsible for autosomal recessive LSDs. We first excluded benign variants by allele frequency and other criteria. As a result, 270 variants were considered disease-causing. We curated these variants using published guidelines from the American College of Medical Genetics and Genomics (ACMG). Our results revealed a combined incidence rate of 13 per 100,000 (conservative estimation by pathologic and likely pathogenic variants; 95% CI 6.92-22.23) to 94 per 100,000 (extended estimation by the inclusion of variants of unknown significance; 95% CI 75.96-115.03) among 71 autosomal recessive disease-associated genes. The conservative estimations were similar to those in published clinical data. No disease-causing mutations were found for 18 other diseases; thus, these diseases are likely extremely rare in Taiwan. The study results are important for designing screening and treatment methods for LSDs in Taiwan and demonstrate the importance of mutation curation to avoid overestimating disease incidences from genomic data.
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Affiliation(s)
- Meng-Ju Melody Tsai
- Department of Pediatrics, National Taiwan University Hospital and College of Medicine, National Taiwan University, Taipei, Taiwan
- Department of Pediatrics, National Taiwan University Hospital Yunlin Branch, Yunlin, Taiwan
| | - Miao-Zi Hung
- Department of Medical Genetics, National Taiwan University Hospital, Taipei, Taiwan
| | - Yi-Lin Lin
- Department of Medical Genetics, National Taiwan University Hospital, Taipei, Taiwan
| | - Ni-Chung Lee
- Department of Pediatrics, National Taiwan University Hospital and College of Medicine, National Taiwan University, Taipei, Taiwan
- Department of Medical Genetics, National Taiwan University Hospital, Taipei, Taiwan
| | - Yin-Hsiu Chien
- Department of Pediatrics, National Taiwan University Hospital and College of Medicine, National Taiwan University, Taipei, Taiwan
- Department of Medical Genetics, National Taiwan University Hospital, Taipei, Taiwan
| | - Wuh-Liang Hwu
- Department of Pediatrics, National Taiwan University Hospital and College of Medicine, National Taiwan University, Taipei, Taiwan.
- Department of Medical Genetics, National Taiwan University Hospital, Taipei, Taiwan.
- Center for Precision Medicine, China Medical University Hospital, Taichung, Taiwan.
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12
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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] [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.
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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
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13
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Kalyta K, Stelmaszczyk W, Szczęśniak D, Kotuła L, Dobosz P, Mroczek M. The Spectrum of the Heterozygous Effect in Biallelic Mendelian Diseases-The Symptomatic Heterozygote Issue. Genes (Basel) 2023; 14:1562. [PMID: 37628614 PMCID: PMC10454578 DOI: 10.3390/genes14081562] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2023] [Revised: 07/26/2023] [Accepted: 07/27/2023] [Indexed: 08/27/2023] Open
Abstract
Heterozygous carriers of pathogenic/likely pathogenic variants in autosomal recessive disorders seem to be asymptomatic. However, in recent years, an increasing number of case reports have suggested that mild and unspecific symptoms can occur in some heterozygotes, as symptomatic heterozygotes have been identified across different disease types, including neurological, neuromuscular, hematological, and pulmonary diseases. The symptoms are usually milder in heterozygotes than in biallelic variants and occur "later in life". The status of symptomatic heterozygotes as separate entities is often disputed, and alternative diagnoses are considered. Indeed, often only a thin line exists between dual, dominant, and recessive modes of inheritance and symptomatic heterozygosity. Interestingly, recent population studies have found global disease effects in heterozygous carriers of some genetic variants. What makes the few heterozygotes symptomatic, while the majority show no symptoms? The molecular basis of this phenomenon is still unknown. Possible explanations include undiscovered deep-splicing variants, genetic and environmental modifiers, digenic/oligogenic inheritance, skewed methylation patterns, and mutational burden. Symptomatic heterozygotes are rarely reported in the literature, mainly because most did not undergo the complete diagnostic procedure, so alternative diagnoses could not be conclusively excluded. However, despite the increasing accessibility to high-throughput technologies, there still seems to be a small group of patients with mild symptoms and just one variant of autosomes in biallelic diseases. Here, we present some examples, the current state of knowledge, and possible explanations for this phenomenon, and thus argue against the existing dominant/recessive classification.
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Affiliation(s)
- Kateryna Kalyta
- School of Life Sciences, FHNW—University of Applied Sciences, 4132 Muttenz, Switzerland;
| | - Weronika Stelmaszczyk
- School of Cellular and Molecular Medicine, University of Bristol, Bristol BS8 1TD, UK;
| | - Dominika Szczęśniak
- Institute of Psychiatry and Neurology in Warsaw, Genetics Department, 02-957 Warsaw, Poland;
| | - Lidia Kotuła
- Department of Genetics, Medical University, 20-080 Lublin, Poland;
| | - Paula Dobosz
- Institute of Genetics and Biotechnology, Faculty of Biology, University of Warsaw, Pawinskiego 5A, 02-106 Warsaw, Poland;
| | - Magdalena Mroczek
- University Hospital Basel, University of Basel, 4031 Basel, Switzerland
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14
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Hill DP, Drabkin HJ, Smith CL, Van Auken KM, D’Eustachio P. Biochemical Pathways Represented by Gene Ontology Causal Activity Models Identify Distinct Phenotypes Resulting from Mutations in Pathways. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.05.22.541760. [PMID: 37293039 PMCID: PMC10245817 DOI: 10.1101/2023.05.22.541760] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
Gene inactivation can affect the process(es) in which that gene acts and causally downstream ones, yielding diverse mutant phenotypes. Identifying the genetic pathways resulting in a given phenotype helps us understand how individual genes interact in a functional network. Computable representations of biological pathways include detailed process descriptions in the Reactome Knowledgebase, and causal activity flows between molecular functions in Gene Ontology-Causal Activity Models (GO-CAMs). A computational process has been developed to convert Reactome pathways to GO-CAMs. Laboratory mice are widely used models of normal and pathological human processes. We have converted human Reactome GO-CAMs to orthologous mouse GO-CAMs, as a resource to transfer pathway knowledge between humans and model organisms. These mouse GO-CAMs allowed us to define sets of genes that function in a connected and well-defined way. To test whether individual genes from well-defined pathways result in similar and distinguishable phenotypes, we used the genes in our pathway models to cross-query mouse phenotype annotations in the Mouse Genome Database (MGD). Using GO-CAM representations of two related but distinct pathways, gluconeogenesis and glycolysis, we can identify causal paths in gene networks that give rise to discrete phenotypic outcomes for perturbations of glycolysis and gluconeogenesis. The accurate and detailed descriptions of gene interactions recovered in this analysis of well-studied processes suggest that this strategy can be applied to less well-understood processes in less well-studied model systems to predict phenotypic outcomes of novel gene variants and to identify potential gene targets in altered processes.
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Affiliation(s)
| | | | | | - Kimberly M Van Auken
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena CA 91125 USA
| | - Peter D’Eustachio
- Department of Biochemistry and Molecular Pharmacology, NYU Grossman School of Medicine, New York NY 10016 USA
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15
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Mendelian inheritance revisited: dominance and recessiveness in medical genetics. Nat Rev Genet 2023:10.1038/s41576-023-00574-0. [PMID: 36806206 DOI: 10.1038/s41576-023-00574-0] [Citation(s) in RCA: 18] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/14/2022] [Indexed: 02/22/2023]
Abstract
Understanding the consequences of genotype for phenotype (which ranges from molecule-level effects to whole-organism traits) is at the core of genetic diagnostics in medicine. Many measures of the deleteriousness of individual alleles exist, but these have limitations for predicting the clinical consequences. Various mechanisms can protect the organism from the adverse effects of functional variants, especially when the variant is paired with a wild type allele. Understanding why some alleles are harmful in the heterozygous state - representing dominant inheritance - but others only with the biallelic presence of pathogenic variants - representing recessive inheritance - is particularly important when faced with the deluge of rare genetic alterations identified by high throughput DNA sequencing. Both awareness of the specific quantitative and/or qualitative effects of individual variants and the elucidation of allelic and non-allelic interactions are essential to optimize genetic diagnosis and counselling.
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16
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Heyne HO, Karjalainen J, Karczewski KJ, Lemmelä SM, Zhou W, Havulinna AS, Kurki M, Rehm HL, Palotie A, Daly MJ. Mono- and biallelic variant effects on disease at biobank scale. Nature 2023; 613:519-525. [PMID: 36653560 PMCID: PMC9849130 DOI: 10.1038/s41586-022-05420-7] [Citation(s) in RCA: 29] [Impact Index Per Article: 29.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2021] [Accepted: 10/06/2022] [Indexed: 01/20/2023]
Abstract
Identifying causal factors for Mendelian and common diseases is an ongoing challenge in medical genetics1. Population bottleneck events, such as those that occurred in the history of the Finnish population, enrich some homozygous variants to higher frequencies, which facilitates the identification of variants that cause diseases with recessive inheritance2,3. Here we examine the homozygous and heterozygous effects of 44,370 coding variants on 2,444 disease phenotypes using data from the nationwide electronic health records of 176,899 Finnish individuals. We find associations for homozygous genotypes across a broad spectrum of phenotypes, including known associations with retinal dystrophy and novel associations with adult-onset cataract and female infertility. Of the recessive disease associations that we identify, 13 out of 20 would have been missed by the additive model that is typically used in genome-wide association studies. We use these results to find many known Mendelian variants whose inheritance cannot be adequately described by a conventional definition of dominant or recessive. In particular, we find variants that are known to cause diseases with recessive inheritance with significant heterozygous phenotypic effects. Similarly, we find presumed benign variants with disease effects. Our results show how biobanks, particularly in founder populations, can broaden our understanding of complex dosage effects of Mendelian variants on disease.
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Affiliation(s)
- H O Heyne
- Finnish Institute for Molecular Medicine (FIMM), University of Helsinki, Helsinki, Finland.
- Digital Health Center, Hasso Plattner Institute for Digital Engineering, University of Potsdam, Potsdam, Germany.
- Hasso Plattner Institute for Digital Health at Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Program for Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
| | - J Karjalainen
- Finnish Institute for Molecular Medicine (FIMM), University of Helsinki, Helsinki, Finland
- Program for Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - K J Karczewski
- Finnish Institute for Molecular Medicine (FIMM), University of Helsinki, Helsinki, Finland
- Program for Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - S M Lemmelä
- Finnish Institute for Molecular Medicine (FIMM), University of Helsinki, Helsinki, Finland
- Finnish Institute for Health and Welfare, Helsinki, Finland
| | - W Zhou
- Finnish Institute for Molecular Medicine (FIMM), University of Helsinki, Helsinki, Finland
- Program for Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - A S Havulinna
- Finnish Institute for Molecular Medicine (FIMM), University of Helsinki, Helsinki, Finland
- Finnish Institute for Health and Welfare, Helsinki, Finland
| | - M Kurki
- Finnish Institute for Molecular Medicine (FIMM), University of Helsinki, Helsinki, Finland
- Program for Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - H L Rehm
- Program for Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - A Palotie
- Finnish Institute for Molecular Medicine (FIMM), University of Helsinki, Helsinki, Finland
- Program for Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Psychiatric and Neurodevelopmental Genetics Unit, Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA
| | - M J Daly
- Finnish Institute for Molecular Medicine (FIMM), University of Helsinki, Helsinki, Finland.
- Program for Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA.
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA.
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17
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Bennett RL, French KS, Resta RG, Austin J. Practice resource-focused revision: Standardized pedigree nomenclature update centered on sex and gender inclusivity: A practice resource of the National Society of Genetic Counselors. J Genet Couns 2022; 31:1238-1248. [PMID: 36106433 DOI: 10.1002/jgc4.1621] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2021] [Revised: 07/08/2022] [Accepted: 07/12/2022] [Indexed: 12/14/2022]
Abstract
This focused revision builds on the expert opinions from the original publications of 'Recommendations for human standardized pedigree nomenclature' published in 1995 and updated in 2008. Our review of medical publications since 2008 did not identify any fundamental systematic alternative pedigree nomenclature. These findings attest to the relevance of most of the nomenclature with the critical exception of the nomenclature used to denote sex assigned at birth and gender. While we are not recommending the creation of any new pedigree symbols, a major focus of this publication is clarification of the use of symbols and language in the description of the distinction between sex and gender, with a view to ensuring safe and inclusive practice for people who are gender-diverse or transgender. In addition, we recommend modifications to the way that carrier status is depicted. Our goal is to respect individual differences and identities while maintaining biologically, clinically, and genetically meaningful information.
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Affiliation(s)
- Robin L Bennett
- Division of Medical Genetics, Department of Medicine, University of Washington, Seattle, Washington, USA
| | | | - Robert G Resta
- Retired, formerly affiliated with Swedish Cancer Institute, Swedish Medical Center, Seattle, Washington, USA
| | - Jehannine Austin
- Departments of Psychiatry and Medical Genetics, University of British Columbia, Vancouver, Canada
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18
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Which patients with CKD will benefit from genomic sequencing? Synthesizing progress to illuminate the future. Curr Opin Nephrol Hypertens 2022; 31:541-547. [PMID: 36093902 PMCID: PMC9594128 DOI: 10.1097/mnh.0000000000000836] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Abstract
PURPOSE OF REVIEW This review will summarize and synthesize recent findings in regard to monogenic kidney disorders, including how that evidence is being translated into practice. It will add to existing key knowledge to provide context for clinicians in consolidating existing practice and approaches. RECENT FINDINGS Whilst there are long established factors, which indicate increased likelihood of identifying a monogenic cause for kidney disease, these can now be framed in terms of the identification of new genes, new indications for genomic testing and new evidence for clinical utility of genomic testing in nephrology. Further, inherent in the use of genomics in nephrology are key concepts including robust informed consent, variant interpretation and return of results. Recent findings of variants in genes related to complex or broader kidney phenotypes are emerging in addition to understanding of de novo variants. Phenocopy phenomena are indicating a more pragmatic use of broader gene panels whilst evidence is emerging of a role in unexplained kidney disease. Clinical utility is evolving but is being successfully demonstrated across multiple domains of outcome and practice. SUMMARY We provide an updated framework of evidence to guide application of genomic testing in chronic kidney disease (CKD), building upon existing principles and knowledge to indicate how the practice and implementation of this can be applied today. There are clearly established roles for genomic testing for some patients with CKD, largely those with suspected heritable forms, with these continuing to expand as new evidence emerges.
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19
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Hujoel MLA, Sherman MA, Barton AR, Mukamel RE, Sankaran VG, Terao C, Loh PR. Influences of rare copy-number variation on human complex traits. Cell 2022; 185:4233-4248.e27. [PMID: 36306736 PMCID: PMC9800003 DOI: 10.1016/j.cell.2022.09.028] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2021] [Revised: 07/22/2022] [Accepted: 09/19/2022] [Indexed: 11/06/2022]
Abstract
The human genome contains hundreds of thousands of regions harboring copy-number variants (CNV). However, the phenotypic effects of most such polymorphisms are unknown because only larger CNVs have been ascertainable from SNP-array data generated by large biobanks. We developed a computational approach leveraging haplotype sharing in biobank cohorts to more sensitively detect CNVs. Applied to UK Biobank, this approach accounted for approximately half of all rare gene inactivation events produced by genomic structural variation. This CNV call set enabled a detailed analysis of associations between CNVs and 56 quantitative traits, identifying 269 independent associations (p < 5 × 10-8) likely to be causally driven by CNVs. Putative target genes were identifiable for nearly half of the loci, enabling insights into dosage sensitivity of these genes and uncovering several gene-trait relationships. These results demonstrate the ability of haplotype-informed analysis to provide insights into the genetic basis of human complex traits.
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Affiliation(s)
- Margaux L A Hujoel
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA; Center for Data Sciences, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
| | - Maxwell A Sherman
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA; Center for Data Sciences, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Alison R Barton
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA; Center for Data Sciences, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA; Bioinformatics and Integrative Genomics Program, Harvard Medical School, Boston, MA, USA
| | - Ronen E Mukamel
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA; Center for Data Sciences, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Vijay G Sankaran
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Division of Hematology/Oncology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA; Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA
| | - Chikashi Terao
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan; Clinical Research Center, Shizuoka General Hospital, Shizuoka, Japan; Department of Applied Genetics, School of Pharmaceutical Sciences, University of Shizuoka, Shizuoka, Japan
| | - Po-Ru Loh
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA; Center for Data Sciences, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
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20
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Kuchenbaecker K. Missing heritability found for height. Nature 2022; 610:631-632. [PMID: 36224358 DOI: 10.1038/d41586-022-03029-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
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