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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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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 2024:10.1038/s41588-024-01842-3. [PMID: 39075210 DOI: 10.1038/s41588-024-01842-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [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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Heyne HO, Pajuste FD, Wanner J, Daniel Onwuchekwa JI, Mägi R, Palotie A, Kälviainen R, Daly MJ. Polygenic risk scores as a marker for epilepsy risk across lifetime and after unspecified seizure events. Nat Commun 2024; 15:6277. [PMID: 39054313 PMCID: PMC11272783 DOI: 10.1038/s41467-024-50295-z] [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: 09/14/2023] [Accepted: 07/04/2024] [Indexed: 07/27/2024] Open
Abstract
A diagnosis of epilepsy has significant consequences for an individual but is often challenging in clinical practice. Novel biomarkers are thus greatly needed. Here, we investigated how common genetic factors (epilepsy polygenic risk scores, [PRSs]) influence epilepsy risk in detailed longitudinal electronic health records (EHRs) of > 700k Finns and Estonians. We found that a high genetic generalized epilepsy PRS (PRSGGE) increased risk for genetic generalized epilepsy (GGE) (hazard ratio [HR] 1.73 per PRSGGE standard deviation [SD]) across lifetime and within 10 years after an unspecified seizure event. The effect of PRSGGE was significantly larger on idiopathic generalized epilepsies, in females and for earlier epilepsy onset. Analogously, we found significant but more modest focal epilepsy PRS burden associated with non-acquired focal epilepsy (NAFE). Here, we outline the potential of epilepsy specific PRSs to serve as biomarkers after a first seizure event.
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Affiliation(s)
- Henrike O Heyne
- Hasso Plattner Institute for Digital Engineering, University of Potsdam, Potsdam, Germany.
- Hasso Plattner Institute, Mount Sinai School of Medicine, New York, NY, US.
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland.
- Program for Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
| | - Fanny-Dhelia Pajuste
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
- Institute of Molecular and Cell Biology, University of Tartu, Tartu, Estonia
| | - Julian Wanner
- Hasso Plattner Institute for Digital Engineering, University of Potsdam, Potsdam, Germany
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
| | - Jennifer I Daniel Onwuchekwa
- Hasso Plattner Institute for Digital Engineering, University of Potsdam, Potsdam, Germany
- Faculty of Life Sciences, University of Siegen, Siegen, Germany
| | - Reedik Mägi
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
- Institute of Molecular and Cell Biology, University of Tartu, Tartu, Estonia
| | - Aarno Palotie
- Institute for Molecular Medicine Finland (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
| | - Reetta Kälviainen
- Kuopio Epilepsy Center, Neurocenter, Kuopio University Hospital, Member of ERN EpiCARE, Kuopio, Finland
- Institute of Clinical Medicine, School of Medicine, Faculty of Health Sciences, University of Eastern Finland, Kuopio, Finland
| | - Mark J Daly
- Institute for Molecular Medicine Finland (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
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Lassen FH, Venkatesh SS, Baya N, Hill B, Zhou W, Bloemendal A, Neale BM, Kessler BM, Whiffin N, Lindgren CM, Palmer DS. Exome-wide evidence of compound heterozygous effects across common phenotypes in the UK Biobank. CELL GENOMICS 2024; 4:100602. [PMID: 38944039 PMCID: PMC11293579 DOI: 10.1016/j.xgen.2024.100602] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Revised: 03/11/2024] [Accepted: 06/07/2024] [Indexed: 07/01/2024]
Abstract
The phenotypic impact of compound heterozygous (CH) variation has not been investigated at the population scale. We phased rare variants (MAF ∼0.001%) in the UK Biobank (UKBB) exome-sequencing data to characterize recessive effects in 175,587 individuals across 311 common diseases. A total of 6.5% of individuals carry putatively damaging CH variants, 90% of which are only identifiable upon phasing rare variants (MAF < 0.38%). We identify six recessive gene-trait associations (p < 1.68 × 10-7) after accounting for relatedness, polygenicity, nearby common variants, and rare variant burden. Of these, just one is discovered when considering homozygosity alone. Using longitudinal health records, we additionally identify and replicate a novel association between bi-allelic variation in ATP2C2 and an earlier age at onset of chronic obstructive pulmonary disease (COPD) (p < 3.58 × 10-8). Genetic phase contributes to disease risk for gene-trait pairs: ATP2C2-COPD (p = 0.000238), FLG-asthma (p = 0.00205), and USH2A-visual impairment (p = 0.0084). We demonstrate the power of phasing large-scale genetic cohorts to discover phenome-wide consequences of compound heterozygosity.
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Affiliation(s)
- Frederik H Lassen
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK; Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK.
| | - Samvida S Venkatesh
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK; Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK
| | - Nikolas Baya
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK; Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK
| | - Barney Hill
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK
| | - Wei Zhou
- Program in 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; Analytical and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Alex Bloemendal
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Novo Nordisk Center for Genomic Mechanisms of Disease, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Data Sciences Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Benjamin M Neale
- Program in 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; Analytical and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Benedikt M Kessler
- Target Discovery Institute, Centre for Medicines Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Nicola Whiffin
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK; Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Cecilia M Lindgren
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK; Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK; Nuffield Department of Population Health, Medical Sciences Division, University of Oxford, Oxford, UK.
| | - Duncan S Palmer
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Nuffield Department of Population Health, Medical Sciences Division, University of Oxford, Oxford, UK.
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5
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Puertas-Neyra K, Coco-Martin RM, Hernandez-Rodriguez LA, Gobelli D, Garcia-Ferrer Y, Palma-Vecino R, Tellería JJ, Simarro M, de la Fuente MA, Fernandez-Bueno I. Clinical exome analysis and targeted gene repair of the c.1354dupT variant in iPSC lines from patients with PROM1-related retinopathies exhibiting diverse phenotypes. Stem Cell Res Ther 2024; 15:192. [PMID: 38956727 PMCID: PMC11218195 DOI: 10.1186/s13287-024-03804-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2024] [Accepted: 06/16/2024] [Indexed: 07/04/2024] Open
Abstract
BACKGROUND Inherited retinal dystrophies (IRD) are one of the main causes of incurable blindness worldwide. IRD are caused by mutations in genes that encode essential proteins for the retina, leading to photoreceptor degeneration and loss of visual function. IRD generates an enormous global financial burden due to the lack of understanding of a significant part of its pathophysiology, molecular diagnosis, and the near absence of non-palliative treatment options. Patient-derived induced pluripotent stem cells (iPSC) for IRD seem to be an excellent option for addressing these questions, serving as exceptional tools for in-depth studies of IRD pathophysiology and testing new therapeutic approaches. METHODS From a cohort of 8 patients with PROM1-related IRD, we identified 3 patients carrying the same variant (c.1354dupT) but expressing three different IRD phenotypes: Cone and rod dystrophy (CORD), Retinitis pigmentosa (RP), and Stargardt disease type 4 (STGD4). These three target patients, along with one healthy relative from each, underwent comprehensive ophthalmic examinations and their genetic panel study was expanded through clinical exome sequencing (CES). Subsequently, non-integrative patient-derived iPSC were generated and fully characterized. Correction of the c.1354dupT mutation was performed using CRISPR/Cas9, and the genetic restoration of the PROM1 gene was confirmed through flow cytometry and western blotting in the patient-derived iPSC lines. RESULTS CES revealed that 2 target patients with the c.1354dupT mutation presented monoallelic variants in genes associated with the complement system or photoreceptor differentiation and peroxisome biogenesis disorders, respectively. The pluripotency and functionality of the patient-derived iPSC lines were confirmed, and the correction of the target mutation fully restored the capability of encoding Prominin-1 (CD133) in the genetically repaired patient-derived iPSC lines. CONCLUSIONS The c.1354dupT mutation in the PROM1 gene is associated to three distinct AR phenotypes of IRD. This pleotropic effect might be related to the influence of monoallelic variants in other genes associated with retinal dystrophies. However, further evidence needs to be provided. Future experiments should include gene-edited patient-derived iPSC due to its potential as disease modelling tools to elucidate this matter in question.
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Affiliation(s)
- Kevin Puertas-Neyra
- Instituto Universitario de Oftalmobiología Aplicada (IOBA), Universidad de Valladolid, Valladolid, Spain
| | - Rosa M Coco-Martin
- Instituto Universitario de Oftalmobiología Aplicada (IOBA), Universidad de Valladolid, Valladolid, Spain.
- Redes de Investigación Cooperativa Orientadas a Resultados en Salud (RICORS-REI), Inflamación E Inmunopatologia de Organos y Sistemas, Instituto de Salud Carlos III, Valladolid, Spain.
- Centro en Red de Medicina Regenerativa, y Terapia Celular de Castilla y León, Valladolid, Spain.
| | | | - Dino Gobelli
- Unidad de Excelencia Instituto de Biomedicina y Genética Molecular (IBGM), Universidad de Valladolid y Consejo Superior de Investigaciones Científicas (CSIC), Valladolid, Spain
- Departamento de Biología Celular, Genética, Histología y Farmacología, Facultad de Medicina, Universidad de Valladolid, Valladolid, Spain
| | - Yenisey Garcia-Ferrer
- Instituto Universitario de Oftalmobiología Aplicada (IOBA), Universidad de Valladolid, Valladolid, Spain
| | - Raicel Palma-Vecino
- Instituto Universitario de Oftalmobiología Aplicada (IOBA), Universidad de Valladolid, Valladolid, Spain
| | - Juan José Tellería
- Unidad de Excelencia Instituto de Biomedicina y Genética Molecular (IBGM), Universidad de Valladolid y Consejo Superior de Investigaciones Científicas (CSIC), Valladolid, Spain
| | - Maria Simarro
- Unidad de Excelencia Instituto de Biomedicina y Genética Molecular (IBGM), Universidad de Valladolid y Consejo Superior de Investigaciones Científicas (CSIC), Valladolid, Spain
- Departamento de Biología Celular, Genética, Histología y Farmacología, Facultad de Medicina, Universidad de Valladolid, Valladolid, Spain
| | - Miguel A de la Fuente
- Unidad de Excelencia Instituto de Biomedicina y Genética Molecular (IBGM), Universidad de Valladolid y Consejo Superior de Investigaciones Científicas (CSIC), Valladolid, Spain
- Departamento de Biología Celular, Genética, Histología y Farmacología, Facultad de Medicina, Universidad de Valladolid, Valladolid, Spain
| | - Ivan Fernandez-Bueno
- Instituto Universitario de Oftalmobiología Aplicada (IOBA), Universidad de Valladolid, Valladolid, Spain
- Redes de Investigación Cooperativa Orientadas a Resultados en Salud (RICORS-REI), Inflamación E Inmunopatologia de Organos y Sistemas, Instituto de Salud Carlos III, Valladolid, Spain
- Centro en Red de Medicina Regenerativa, y Terapia Celular de Castilla y León, Valladolid, Spain
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Patel MM, Adrada BE. Hereditary Breast Cancer: BRCA Mutations and Beyond. Radiol Clin North Am 2024; 62:627-642. [PMID: 38777539 DOI: 10.1016/j.rcl.2023.12.014] [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] [Indexed: 05/25/2024]
Abstract
Hereditary breast cancers are manifested by pathogenic and likely pathogenic genetic mutations. Penetrance expresses the breast cancer risk associated with these genetic mutations. Although BRCA1/2 are the most widely known genetic mutations associated with breast cancer, numerous additional genes demonstrate high and moderate penetrance for breast cancer. This review describes current genetic testing, details the specific high and moderate penetrance genes for breast cancer and reviews the current approach to screening for breast cancer in patients with these genetic mutations.
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Affiliation(s)
- Miral M Patel
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, 1515 Holcombe, CPB5.3208, Houston, TX 77030, USA.
| | - Beatriz Elena Adrada
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, 1515 Holcombe, CPB5.3208, Houston, TX 77030, USA
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Shiels A. Through the Cat-Map Gateway: A Brief History of Cataract Genetics. Genes (Basel) 2024; 15:785. [PMID: 38927721 PMCID: PMC11202810 DOI: 10.3390/genes15060785] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2024] [Revised: 06/06/2024] [Accepted: 06/13/2024] [Indexed: 06/28/2024] Open
Abstract
Clouding of the transparent eye lens, or cataract(s), is a leading cause of visual impairment that requires surgical replacement with a synthetic intraocular lens to effectively restore clear vision. Most frequently, cataract is acquired with aging as a multifactorial or complex trait. Cataract may also be inherited as a classic Mendelian trait-often with an early or pediatric onset-with or without other ocular and/or systemic features. Since the early 1990s, over 85 genes and loci have been genetically associated with inherited and/or age-related forms of cataract. While many of these underlying genes-including those for lens crystallins, connexins, and transcription factors-recapitulate signature features of lens development and differentiation, an increasing cohort of unpredicted genes, including those involved in cell-signaling, membrane remodeling, and autophagy, has emerged-providing new insights regarding lens homeostasis and aging. This review provides a brief history of gene discovery for inherited and age-related forms of cataract compiled in the Cat-Map database and highlights potential gene-based therapeutic approaches to delay, reverse, or even prevent cataract formation that may help to reduce the increasing demand for cataract surgery.
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Affiliation(s)
- Alan Shiels
- Department of Ophthalmology and Visual Sciences, Washington University School of Medicine, St. Louis, MO 63110, USA
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8
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Almansoori S, Alsters SI, Yiorkas AM, Nor Hashim NA, Walters RG, Chahal HS, Purkayastha S, Lessan N, Blakemore AIF. Oligogenic inheritance in severe adult obesity. Int J Obes (Lond) 2024; 48:815-820. [PMID: 38297031 PMCID: PMC11129943 DOI: 10.1038/s41366-024-01476-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/07/2022] [Revised: 11/13/2023] [Accepted: 01/17/2024] [Indexed: 02/02/2024]
Abstract
BACKGROUND/OBJECTIVE The genetic architecture of extreme non-syndromic obesity in adults remains to be elucidated. A range of genes are known to cause monogenic obesity, but even when pathogenic mutations are present, there may be variable penetrance. METHODS Whole-exome sequencing (WES) was carried out on a 15-year-old male proband of Pakistani ancestry who had severe obesity. This was followed by family segregation analysis, using Sanger sequencing. We also undertook re-analysis of WES data from 91 unrelated adults with severe obesity (86% white European ancestry) from the Personalised Medicine for Morbid Obesity (PMMO) cohort, recruited from the UK National Health Service. RESULTS We identified an oligogenic mode of inheritance of obesity in the proband's family-this provided the impetus to reanalyze existing sequence data in a separate dataset. Analysis of PMMO participant data revealed two further patients who carried more than one rare, predicted-deleterious mutation in a known monogenic obesity gene. In all three cases, the genes involved had known autosomal dominant inheritance, with incomplete penetrance. CONCLUSION Oligogenic inheritance may explain some of the variable penetrance in Mendelian forms of obesity. We caution clinicians and researchers to avoid confining sequence analysis to individual genes and, in particular, not to stop looking when the first potentially-causative mutation is found.
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Affiliation(s)
- Sumaya Almansoori
- Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK.
- Department of Life Sciences, College of Health, Medicine and Life Sciences, Brunel University London, London, UK.
- College of Medicine, Mohammed Bin Rashid University of Medicine and Health Sciences, Dubai Healthcare City, Dubai, United Arab Emirates.
- Genome Center, Department of Forensic Science and Criminology, Dubai Police GHQ, Dubai, United Arab Emirates.
| | - Suzanne I Alsters
- South West Thames Regional Genetics Service, St George's University Hospitals NHS Foundation Trust, London, UK
| | - Andrianos M Yiorkas
- Department of Life Sciences, College of Health, Medicine and Life Sciences, Brunel University London, London, UK
| | - Nikman Adli Nor Hashim
- Institute of Biological Sciences, Faculty of Science, Universiti Malaya, Kuala Lumpur, 50603, Malaysia
- Centre for Drug Research in Systems Biology, Structural Bioinformatics and Human Digital Imaging (CRYSTAL), Universiti Malaya, Kuala Lumpur, 50603, Malaysia
| | - Robin G Walters
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
- MRC Population Health Research Unit, University of Oxford, Oxford, UK
| | - Harvinder S Chahal
- Imperial Weight Centre, Imperial College Healthcare NHS Trust, St Mary's Hospital, Praed Street, London, W2 1NY, UK
- Section of Investigative Medicine, Division of Diabetes, Endocrinology and Metabolism, Imperial College London, Hammersmith Campus, Hammersmith Hospital, 6th Floor Commonwealth Building, Du Cane Road, London, W12 0NN, UK
| | | | - Nader Lessan
- Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
- Imperial College London Diabetes Centre Abu Dhabi, Abu Dhabi, United Arab Emirates
| | - Alexandra I F Blakemore
- Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
- Department of Life Sciences, College of Health, Medicine and Life Sciences, Brunel University London, London, UK
- College of Medicine, Nursing, and Health Science, University of Galway, Galway, Republic of Ireland
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9
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Ohta R, Tanigawa Y, Suzuki Y, Kellis M, Morishita S. A polygenic score method boosted by non-additive models. Nat Commun 2024; 15:4433. [PMID: 38811555 DOI: 10.1038/s41467-024-48654-x] [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: 06/27/2023] [Accepted: 05/08/2024] [Indexed: 05/31/2024] Open
Abstract
Dominance heritability in complex traits has received increasing recognition. However, most polygenic score (PGS) approaches do not incorporate non-additive effects. Here, we present GenoBoost, a flexible PGS modeling framework capable of considering both additive and non-additive effects, specifically focusing on genetic dominance. Building on statistical boosting theory, we derive provably optimal GenoBoost scores and provide its efficient implementation for analyzing large-scale cohorts. We benchmark it against seven commonly used PGS methods and demonstrate its competitive predictive performance. GenoBoost is ranked the best for four traits and second-best for three traits among twelve tested disease outcomes in UK Biobank. We reveal that GenoBoost improves prediction for autoimmune diseases by incorporating non-additive effects localized in the MHC locus and, more broadly, works best in less polygenic traits. We further demonstrate that GenoBoost can infer the mode of genetic inheritance without requiring prior knowledge. For example, GenoBoost finds non-zero genetic dominance effects for 602 of 900 selected genetic variants, resulting in 2.5% improvements in predicting psoriasis cases. Lastly, we show that GenoBoost can prioritize genetic loci with genetic dominance not previously reported in the GWAS catalog. Our results highlight the increased accuracy and biological insights from incorporating non-additive effects in PGS models.
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Affiliation(s)
- Rikifumi Ohta
- Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Kashiwa, Chiba, Japan.
| | - Yosuke Tanigawa
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, USA.
- Broad Institute of MIT and Harvard, Cambridge, MA, USA.
| | - Yuta Suzuki
- Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Kashiwa, Chiba, Japan
| | - Manolis Kellis
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, USA.
- Broad Institute of MIT and Harvard, Cambridge, MA, USA.
| | - Shinichi Morishita
- Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Kashiwa, Chiba, Japan.
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10
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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:dmae012. [PMID: 38805697 DOI: 10.1093/humupd/dmae012] [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: 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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11
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Kingdom R, Beaumont RN, Wood AR, Weedon MN, Wright CF. Genetic modifiers of rare variants in monogenic developmental disorder loci. Nat Genet 2024; 56:861-868. [PMID: 38637616 PMCID: PMC11096126 DOI: 10.1038/s41588-024-01710-0] [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: 12/07/2022] [Accepted: 03/06/2024] [Indexed: 04/20/2024]
Abstract
Rare damaging variants in a large number of genes are known to cause monogenic developmental disorders (DDs) and have also been shown to cause milder subclinical phenotypes in population cohorts. Here, we show that carrying multiple (2-5) rare damaging variants across 599 dominant DD genes has an additive adverse effect on numerous cognitive and socioeconomic traits in UK Biobank, which can be partially counterbalanced by a higher educational attainment polygenic score (EA-PGS). Phenotypic deviators from expected EA-PGS could be partly explained by the enrichment or depletion of rare DD variants. Among carriers of rare DD variants, those with a DD-related clinical diagnosis had a substantially lower EA-PGS and more severe phenotype than those without a clinical diagnosis. Our results suggest that the overall burden of both rare and common variants can modify the expressivity of a phenotype, which may then influence whether an individual reaches the threshold for clinical disease.
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Affiliation(s)
- Rebecca Kingdom
- Department of Clinical and Biomedical Sciences, University of Exeter Medical School, Royal Devon & Exeter Hospital, Exeter, UK
| | - Robin N Beaumont
- Department of Clinical and Biomedical Sciences, University of Exeter Medical School, Royal Devon & Exeter Hospital, Exeter, UK
| | - Andrew R Wood
- Department of Clinical and Biomedical Sciences, University of Exeter Medical School, Royal Devon & Exeter Hospital, Exeter, UK
| | - Michael N Weedon
- Department of Clinical and Biomedical Sciences, University of Exeter Medical School, Royal Devon & Exeter Hospital, Exeter, UK
| | - Caroline F Wright
- Department of Clinical and Biomedical Sciences, University of Exeter Medical School, Royal Devon & Exeter Hospital, Exeter, UK.
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12
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Venkatesh SS, Wittemans LBL, Palmer DS, Baya NA, Ferreira T, Hill B, Lassen FH, Parker MJ, Reibe S, Elhakeem A, Banasik K, Bruun MT, Erikstrup C, Jensen BA, Juul A, Mikkelsen C, Nielsen HS, Ostrowski SR, Pedersen OB, Rohde PD, Sorensen E, Ullum H, Westergaard D, Haraldsson A, Holm H, Jonsdottir I, Olafsson I, Steingrimsdottir T, Steinthorsdottir V, Thorleifsson G, Figueredo J, Karjalainen MK, Pasanen A, Jacobs BM, Hubers N, Lippincott M, Fraser A, Lawlor DA, Timpson NJ, Nyegaard M, Stefansson K, Magi R, Laivuori H, van Heel DA, Boomsma DI, Balasubramanian R, Seminara SB, Chan YM, Laisk T, Lindgren CM. Genome-wide analyses identify 21 infertility loci and over 400 reproductive hormone loci across the allele frequency spectrum. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.03.19.24304530. [PMID: 38562841 PMCID: PMC10984039 DOI: 10.1101/2024.03.19.24304530] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Abstract
Genome-wide association studies (GWASs) may help inform treatments for infertility, whose causes remain unknown in many cases. Here we present GWAS meta-analyses across six cohorts for male and female infertility in up to 41,200 cases and 687,005 controls. We identified 21 genetic risk loci for infertility (P≤5E-08), of which 12 have not been reported for any reproductive condition. We found positive genetic correlations between endometriosis and all-cause female infertility (rg=0.585, P=8.98E-14), and between polycystic ovary syndrome and anovulatory infertility (rg=0.403, P=2.16E-03). The evolutionary persistence of female infertility-risk alleles in EBAG9 may be explained by recent directional selection. We additionally identified up to 269 genetic loci associated with follicle-stimulating hormone (FSH), luteinising hormone, oestradiol, and testosterone through sex-specific GWAS meta-analyses (N=6,095-246,862). While hormone-associated variants near FSHB and ARL14EP colocalised with signals for anovulatory infertility, we found no rg between female infertility and reproductive hormones (P>0.05). Exome sequencing analyses in the UK Biobank (N=197,340) revealed that women carrying testosterone-lowering rare variants in GPC2 were at higher risk of infertility (OR=2.63, P=1.25E-03). Taken together, our results suggest that while individual genes associated with hormone regulation may be relevant for fertility, there is limited genetic evidence for correlation between reproductive hormones and infertility at the population level. We provide the first comprehensive view of the genetic architecture of infertility across multiple diagnostic criteria in men and women, and characterise its relationship to other health conditions.
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Affiliation(s)
- Samvida S Venkatesh
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford OX3 7LF, United Kingdom
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford OX3 7BN, United Kingdom
| | - Laura B L Wittemans
- Novo Nordisk Research Centre Oxford, Oxford, United Kingdom
- Nuffield Department of Women's and Reproductive Health, Medical Sciences Division, University of Oxford, United Kingdom
| | - Duncan S Palmer
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford OX3 7LF, United Kingdom
- Nuffield Department of Population Health, Medical Sciences Division, University of Oxford, Oxford, United Kingdom
| | - Nikolas A Baya
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford OX3 7LF, United Kingdom
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford OX3 7BN, United Kingdom
| | - Teresa Ferreira
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford OX3 7LF, United Kingdom
| | - Barney Hill
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford OX3 7LF, United Kingdom
- Nuffield Department of Population Health, Medical Sciences Division, University of Oxford, Oxford, United Kingdom
| | - Frederik Heymann Lassen
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford OX3 7LF, United Kingdom
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford OX3 7BN, United Kingdom
| | - Melody J Parker
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford OX3 7LF, United Kingdom
- Nuffield Department of Clinical Medicine, University of Oxford, John Radcliffe Hospital, Oxford, United Kingdom
| | - Saskia Reibe
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford OX3 7LF, United Kingdom
- Nuffield Department of Population Health, Medical Sciences Division, University of Oxford, Oxford, United Kingdom
| | - Ahmed Elhakeem
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, United Kingdom
- Population Health Science, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Karina Banasik
- Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, Copenhagen, Denmark
- Department of Obstetrics and Gynecology, Copenhagen University Hospital, Hvidovre, Copenhagen, Denmark
| | - Mie T Bruun
- Department of Clinical Immunology, Odense University Hospital, Odense, Denmark
| | - Christian Erikstrup
- Department of Clinical Immunology, Aarhus University Hospital, Aarhus, Denmark
- Department of Clinical Medicine, Health, Aarhus University, Aarhus, Denmark
| | - Bitten A Jensen
- Department of Clinical Immunology, Aalborg University Hospital, Aalborg, Denmark
| | - Anders Juul
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen; Copenhagen, Denmark
- Department of Growth and Reproduction, Copenhagen University Hospital-Rigshospitalet, Copenhagen, Denmark
| | - Christina Mikkelsen
- Department of Clinical Immunology, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Science, Copenhagen University, Copenhagen, Denmark
| | - Henriette S Nielsen
- Department of Obstetrics and Gynecology, The Fertility Clinic, Hvidovre University Hospital, Copenhagen, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Sisse R Ostrowski
- Department of Clinical Immunology, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Ole B Pedersen
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Department of Clinical Immunology, Zealand University Hospital, Kge, Denmark
| | - Palle D Rohde
- Genomic Medicine, Department of Health Science and Technology, Aalborg University, Aalborg, Denmark
| | - Erik Sorensen
- Department of Clinical Immunology, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
| | | | - David Westergaard
- Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, Copenhagen, Denmark
- Department of Obstetrics and Gynecology, Copenhagen University Hospital, Hvidovre, Copenhagen, Denmark
| | - Asgeir Haraldsson
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
- Children's Hospital Iceland, Landspitali University Hospital, Reykjavik, Iceland
| | - Hilma Holm
- deCODE genetics/Amgen, Inc., Reykjavik, Iceland
| | - Ingileif Jonsdottir
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
- deCODE genetics/Amgen, Inc., Reykjavik, Iceland
| | - Isleifur Olafsson
- Department of Clinical Biochemistry, Landspitali University Hospital, Reykjavik, Iceland
| | - Thora Steingrimsdottir
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
- Department of Obstetrics and Gynecology, Landspitali University Hospital, Reykjavik, Iceland
| | | | | | - Jessica Figueredo
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Minna K Karjalainen
- Institute for Molecular Medicine Finland, Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland
- Research Unit of Population Health, Faculty of Medicine, University of Oulu, Finland
- Northern Finland Birth Cohorts, Arctic Biobank, Infrastructure for Population Studies, Faculty of Medicine, University of Oulu, Oulu, Finland
| | - Anu Pasanen
- Research Unit of Clinical Medicine, Medical Research Center Oulu, University of Oulu, and Department of Children and Adolescents, Oulu University Hospital, Oulu, Finland
| | - Benjamin M Jacobs
- Centre for Preventive Neurology, Wolfson Institute of Population Health, Queen Mary University London, London, EC1M 6BQ, United Kingdom
| | - Nikki Hubers
- Department of Biological Psychology, Netherlands Twin Register, Vrije Universiteit, Amsterdam, The Netherlands
- Amsterdam Reproduction and Development Institute, Amsterdam, The Netherlands
| | - Margaret Lippincott
- Harvard Reproductive Sciences Center and Reproductive Endocrine Unit, Massachusetts General Hospital, Boston, Massachusetts, United States of America
- Harvard Medical School, Boston, Massachusetts, United States of America
| | - Abigail Fraser
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, United Kingdom
- Population Health Science, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Deborah A Lawlor
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, United Kingdom
- Population Health Science, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Nicholas J Timpson
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, United Kingdom
- Population Health Science, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Mette Nyegaard
- Genomic Medicine, Department of Health Science and Technology, Aalborg University, Aalborg, Denmark
| | - Kari Stefansson
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
- deCODE genetics/Amgen, Inc., Reykjavik, Iceland
| | - Reedik Magi
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Hannele Laivuori
- Institute for Molecular Medicine Finland, Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland
- Medical and Clinical Genetics, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- Department of Obstetrics and Gynecology, Tampere University Hospital, Finland
- Center for Child, Adolescent, and Maternal Health Research, Faculty of Medicine and Health Technology, Tampere University, Finland
| | - David A van Heel
- Blizard Institute, Queen Mary University London, London, E1 2AT, United Kingdom
| | - Dorret I Boomsma
- Department of Biological Psychology, Netherlands Twin Register, Vrije Universiteit, Amsterdam, The Netherlands
- Amsterdam Reproduction and Development Institute, Amsterdam, The Netherlands
| | - Ravikumar Balasubramanian
- Harvard Reproductive Sciences Center and Reproductive Endocrine Unit, Massachusetts General Hospital, Boston, Massachusetts, United States of America
- Harvard Medical School, Boston, Massachusetts, United States of America
| | - Stephanie B Seminara
- Harvard Reproductive Sciences Center and Reproductive Endocrine Unit, Massachusetts General Hospital, Boston, Massachusetts, United States of America
- Harvard Medical School, Boston, Massachusetts, United States of America
| | - Yee-Ming Chan
- Harvard Medical School, Boston, Massachusetts, United States of America
- Division of Endocrinology, Department of Pediatrics, Boston Children's Hospital, Boston, Massachusetts, United States of America
| | - Triin Laisk
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Cecilia M Lindgren
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford OX3 7LF, United Kingdom
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford OX3 7BN, United Kingdom
- Nuffield Department of Women's and Reproductive Health, Medical Sciences Division, University of Oxford, United Kingdom
- Broad Institute of Harvard and MIT, Cambridge, Massachusetts, United States of America
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13
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Lappalainen T, Li YI, Ramachandran S, Gusev A. Genetic and molecular architecture of complex traits. Cell 2024; 187:1059-1075. [PMID: 38428388 DOI: 10.1016/j.cell.2024.01.023] [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: 10/03/2023] [Revised: 12/20/2023] [Accepted: 01/16/2024] [Indexed: 03/03/2024]
Abstract
Human genetics has emerged as one of the most dynamic areas of biology, with a broadening societal impact. In this review, we discuss recent achievements, ongoing efforts, and future challenges in the field. Advances in technology, statistical methods, and the growing scale of research efforts have all provided many insights into the processes that have given rise to the current patterns of genetic variation. Vast maps of genetic associations with human traits and diseases have allowed characterization of their genetic architecture. Finally, studies of molecular and cellular effects of genetic variants have provided insights into biological processes underlying disease. Many outstanding questions remain, but the field is well poised for groundbreaking discoveries as it increases the use of genetic data to understand both the history of our species and its applications to improve human health.
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Affiliation(s)
- Tuuli Lappalainen
- New York Genome Center, New York, NY, USA; Science for Life Laboratory, Department of Gene Technology, KTH Royal Institute of Technology, Stockholm, Sweden.
| | - Yang I Li
- Section of Genetic Medicine, University of Chicago, Chicago, IL, USA; Department of Human Genetics, University of Chicago, Chicago, IL, USA
| | - Sohini Ramachandran
- Ecology, Evolution and Organismal Biology, Center for Computational Molecular Biology, and the Data Science Institute, Brown University, Providence, RI 029129, USA
| | - Alexander Gusev
- Harvard Medical School and Dana-Farber Cancer Institute, Boston, MA, USA
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14
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Li H, Yu Z, Du F, Song L, Gao Y, Shi F. sscNOVA: a semi-supervised convolutional neural network for predicting functional regulatory variants in autoimmune diseases. Front Immunol 2024; 15:1323072. [PMID: 38380333 PMCID: PMC10876991 DOI: 10.3389/fimmu.2024.1323072] [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: 10/17/2023] [Accepted: 01/15/2024] [Indexed: 02/22/2024] Open
Abstract
Genome-wide association studies (GWAS) have identified thousands of variants in the human genome with autoimmune diseases. However, identifying functional regulatory variants associated with autoimmune diseases remains challenging, largely because of insufficient experimental validation data. We adopt the concept of semi-supervised learning by combining labeled and unlabeled data to develop a deep learning-based algorithm framework, sscNOVA, to predict functional regulatory variants in autoimmune diseases and analyze the functional characteristics of these regulatory variants. Compared to traditional supervised learning methods, our approach leverages more variants' data to explore the relationship between functional regulatory variants and autoimmune diseases. Based on the experimentally curated testing dataset and evaluation metrics, we find that sscNOVA outperforms other state-of-the-art methods. Furthermore, we illustrate that sscNOVA can help to improve the prioritization of functional regulatory variants from lead single-nucleotide polymorphisms and the proxy variants in autoimmune GWAS data.
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Affiliation(s)
- Haibo Li
- School of Information Engineering, Ningxia University, Yinchuan, China
| | - Zhenhua Yu
- School of Information Engineering, Ningxia University, Yinchuan, China
- Collaborative Innovation Center for Ningxia Big Data and Artificial Intelligence Co-founded by Ningxia Municipality and Ministry of Education, Yinchuan, Ningxia University, Yinchuan, China
| | - Fang Du
- School of Information Engineering, Ningxia University, Yinchuan, China
- Collaborative Innovation Center for Ningxia Big Data and Artificial Intelligence Co-founded by Ningxia Municipality and Ministry of Education, Yinchuan, Ningxia University, Yinchuan, China
| | - Lijuan Song
- School of Information Engineering, Ningxia University, Yinchuan, China
- Collaborative Innovation Center for Ningxia Big Data and Artificial Intelligence Co-founded by Ningxia Municipality and Ministry of Education, Yinchuan, Ningxia University, Yinchuan, China
| | - Yang Gao
- School of Medical Technology, North Minzu University, Yinchuan, China
| | - Fangyuan Shi
- School of Information Engineering, Ningxia University, Yinchuan, China
- Collaborative Innovation Center for Ningxia Big Data and Artificial Intelligence Co-founded by Ningxia Municipality and Ministry of Education, Yinchuan, Ningxia University, Yinchuan, China
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15
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Sarsani V, Brotman SM, Xianyong Y, Fernandes Silva L, Laakso M, Spracklen CN. A cross-ancestry genome-wide meta-analysis, fine-mapping, and gene prioritization approach to characterize the genetic architecture of adiponectin. HGG ADVANCES 2024; 5:100252. [PMID: 37859345 PMCID: PMC10652123 DOI: 10.1016/j.xhgg.2023.100252] [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: 06/29/2023] [Revised: 10/16/2023] [Accepted: 10/16/2023] [Indexed: 10/21/2023] Open
Abstract
Previous genome-wide association studies (GWASs) for adiponectin, a complex trait linked to type 2 diabetes and obesity, identified >20 associated loci. However, most loci were identified in populations of European ancestry, and many of the target genes underlying the associations remain unknown. We conducted a cross-ancestry adiponectin GWAS meta-analysis in ≤46,434 individuals from the Metabolic Syndrome in Men (METSIM) cohort and the ADIPOGen and AGEN consortiums. We combined study-specific association summary statistics using a fixed-effects, inverse variance-weighted approach. We identified 22 loci associated with adiponectin (p < 5×10-8), including 15 known and seven previously unreported loci. Among individuals of European ancestry, Genome-wide Complex Traits Analysis joint conditional analysis (GCTA-COJO) identified 14 additional distinct signals at the ADIPOQ, CDH13, HCAR1, and ZNF664 loci. Leveraging the cross-ancestry data, FINEMAP + SuSiE identified 45 causal variants (PP > 0.9), which also exhibited potential pleiotropy for cardiometabolic traits. To prioritize target genes at associated loci, we propose a combinatorial likelihood scoring formalism (Gene Priority Score [GPScore]) based on measures derived from 11 gene prioritization strategies and the physical distance to the transcription start site. With GPScore, we prioritize the 30 most probable target genes underlying the adiponectin-associated variants in the cross-ancestry analysis, including well-known causal genes (e.g., ADIPOQ, CDH13) and additional genes (e.g., CSF1, RGS17). Functional association networks revealed complex interactions of prioritized genes, their functionally connected genes, and their underlying pathways centered around insulin and adiponectin signaling, indicating an essential role in regulating energy balance in the body, inflammation, coagulation, fibrinolysis, insulin resistance, and diabetes. Overall, our analyses identify and characterize adiponectin association signals and inform experimental interrogation of target genes for adiponectin.
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Affiliation(s)
- Vishal Sarsani
- Department of Mathematics and Statistics, University of Massachusetts Amherst, Amherst, MA, USA
| | - Sarah M Brotman
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Yin Xianyong
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA
| | - Lillian Fernandes Silva
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland, Kuopio, Finland
| | - Markku Laakso
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland, Kuopio, Finland
| | - Cassandra N Spracklen
- Department of Biostatistics and Epidemiology, University of Massachusetts Amherst, Amherst, MA, USA.
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16
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Nurmi AK, Pelttari LM, Kiiski JI, Khan S, Nurmikolu M, Suvanto M, Aho N, Tasmuth T, Kalso E, Schleutker J, Kallioniemi A, Heikkilä P, Aittomäki K, Blomqvist C, Nevanlinna H. NTHL1 is a recessive cancer susceptibility gene. Sci Rep 2023; 13:21127. [PMID: 38036545 PMCID: PMC10689455 DOI: 10.1038/s41598-023-47441-w] [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: 07/06/2023] [Accepted: 11/14/2023] [Indexed: 12/02/2023] Open
Abstract
In search of novel breast cancer (BC) risk variants, we performed a whole-exome sequencing and variant analysis of 69 Finnish BC patients as well as analysed loss-of-function variants identified in DNA repair genes in the Finns from the Genome Aggregation Database. Additionally, we carried out a validation study of SERPINA3 c.918-1G>C, recently suggested for BC predisposition. We estimated the frequencies of 41 rare candidate variants in 38 genes by genotyping them in 2482-4101 BC patients and in 1273-3985 controls. We further evaluated all coding variants in the candidate genes in a dataset of 18,786 BC patients and 182,927 controls from FinnGen. None of the variants associated significantly with cancer risk in the primary BC series; however, in the FinnGen data, NTHL1 c.244C>T p.(Gln82Ter) associated with BC with a high risk for homozygous (OR = 44.7 [95% CI 6.90-290], P = 6.7 × 10-5) and a low risk for heterozygous women (OR = 1.39 [1.18-1.64], P = 7.8 × 10-5). Furthermore, the results suggested a high risk of colorectal, urinary tract, and basal-cell skin cancer for homozygous individuals, supporting NTHL1 as a recessive multi-tumour susceptibility gene. No significant association with BC risk was detected for SERPINA3 or any other evaluated gene.
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Affiliation(s)
- Anna K Nurmi
- Department of Obstetrics and Gynecology, University of Helsinki and Helsinki University Hospital, Biomedicum Helsinki, P.O. Box 700, 00290, Helsinki, Finland
| | - Liisa M Pelttari
- Department of Obstetrics and Gynecology, University of Helsinki and Helsinki University Hospital, Biomedicum Helsinki, P.O. Box 700, 00290, Helsinki, Finland
| | - Johanna I Kiiski
- Department of Obstetrics and Gynecology, University of Helsinki and Helsinki University Hospital, Biomedicum Helsinki, P.O. Box 700, 00290, Helsinki, Finland
| | - Sofia Khan
- Department of Obstetrics and Gynecology, University of Helsinki and Helsinki University Hospital, Biomedicum Helsinki, P.O. Box 700, 00290, Helsinki, Finland
| | - Mika Nurmikolu
- Department of Obstetrics and Gynecology, University of Helsinki and Helsinki University Hospital, Biomedicum Helsinki, P.O. Box 700, 00290, Helsinki, Finland
| | - Maija Suvanto
- Department of Obstetrics and Gynecology, University of Helsinki and Helsinki University Hospital, Biomedicum Helsinki, P.O. Box 700, 00290, Helsinki, Finland
| | - Niina Aho
- Department of Obstetrics and Gynecology, University of Helsinki and Helsinki University Hospital, Biomedicum Helsinki, P.O. Box 700, 00290, Helsinki, Finland
| | - Tiina Tasmuth
- Department of Anaesthesiology, Intensive Care and Pain Medicine, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - Eija Kalso
- Department of Anaesthesiology, Intensive Care and Pain Medicine, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - Johanna Schleutker
- Institute of Biomedicine, University of Turku, and FICAN West Cancer Centre, and Department of Genomics, Laboratory Division, Turku University Hospital, Turku, Finland
| | - Anne Kallioniemi
- Tays Cancer Center, Tampere University Hospital, and BioMediTech Institute and Faculty of Medicine and Health Technology, Tampere University, and Fimlab Laboratories, Tampere, Finland
| | - Päivi Heikkilä
- Department of Pathology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - Kristiina Aittomäki
- Department of Clinical Genetics, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - Carl Blomqvist
- Department of Oncology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - Heli Nevanlinna
- Department of Obstetrics and Gynecology, University of Helsinki and Helsinki University Hospital, Biomedicum Helsinki, P.O. Box 700, 00290, Helsinki, Finland.
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17
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Heyne HO, Pajuste FD, Wanner J, Onwuchekwa JID, Mägi R, Palotie A, Kälviainen R, Daly MJ. Polygenic risk scores as a marker for epilepsy risk across lifetime and after unspecified seizure events. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.11.27.23297542. [PMID: 38076931 PMCID: PMC10705659 DOI: 10.1101/2023.11.27.23297542] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/20/2023]
Abstract
A diagnosis of epilepsy has significant consequences for an individual but is often challenging in clinical practice. Novel biomarkers are thus greatly needed. Here, we investigated how common genetic factors (epilepsy polygenic risk scores, [PRSs]) influence epilepsy risk in detailed longitudinal electronic health records (EHRs) of > 360k Finns spanning up to 50 years of individuals' lifetimes. Individuals with a high genetic generalized epilepsy PRS (PRSGGE) in FinnGen had an increased risk for genetic generalized epilepsy (GGE) (hazard ratio [HR] 1.55 per PRSGGE standard deviation [SD]) across their lifetime and after unspecified seizure events. Effect sizes of epilepsy PRSs were comparable to effect sizes in clinically curated data supporting our EHR-derived epilepsy diagnoses. Within 10 years after an unspecified seizure, the GGE rate was 37% when PRSGGE > 2 SD compared to 5.6% when PRSGGE < -2 SD. The effect of PRSGGE was even larger on GGE subtypes of idiopathic generalized epilepsy (IGE) (HR 2.1 per SD PRSGGE). We further report significantly larger effects of PRSGGE on epilepsy in females and in younger age groups. Analogously, we found significant but more modest focal epilepsy PRS burden associated with non-acquired focal epilepsy (NAFE). We found PRSGGE specifically associated with GGE in comparison with >2000 independent diseases while PRSNAFE was also associated with other diseases than NAFE such as back pain. Here, we show that epilepsy specific PRSs have good discriminative ability after a first seizure event i.e. in circumstances where the prior probability of epilepsy is high outlining a potential to serve as biomarkers for an epilepsy diagnosis.
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Affiliation(s)
- Henrike O Heyne
- Hasso Plattner Institute for Digital Engineering, University of Potsdam, Germany
- Hasso Plattner Institute, Mount Sinai School of Medicine, NY, US
- 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
| | - Fanny-Dhelia Pajuste
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
- Institute of Molecular and Cell Biology, University of Tartu, Tartu, Estonia
| | - Julian Wanner
- Hasso Plattner Institute for Digital Engineering, University of Potsdam, Germany
- Finnish Institute for Molecular Medicine (FIMM), University of Helsinki, Helsinki, Finland
| | - Jennifer I Daniel Onwuchekwa
- Hasso Plattner Institute for Digital Engineering, University of Potsdam, Germany
- Faculty of Life Sciences, University of Siegen, Germany
| | - Reedik Mägi
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
- Institute of Molecular and Cell Biology, University of Tartu, Tartu, Estonia
| | - Aarno 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
| | - Reetta Kälviainen
- Kuopio Epilepsy Center, Neurocenter, Kuopio University Hospital, Member of ERN EpiCARE, Kuopio, Finland
- Institute of Clinical Medicine, School of Medicine, Faculty of Health Sciences, University of Eastern Finland, Kuopio, Finland
| | - Mark 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
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18
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Halbritter J. Urinary stone disease: closing the heritability gap by challenging conventional Mendelian inheritance. Kidney Int 2023; 104:882-885. [PMID: 37863636 DOI: 10.1016/j.kint.2023.08.021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2023] [Revised: 08/23/2023] [Accepted: 08/24/2023] [Indexed: 10/22/2023]
Abstract
Urinary stone disease is based on gene-environment interaction with an almost 50% heritability. Despite all efforts from exome-sequencing and genome-wide association studies, the genetic factors making up for observed heritability have been incompletely characterized. The study by Sadeghi-Alavijeh et al. leverages the invaluable resources of the 100,000 Genomes Project and the UK Biobank to identify heterozygous rare variants in the phosphate transporter SLC34A3 as a significant factor of urinary stone disease, challenging the traditional concept of Mendelian inheritance.
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Affiliation(s)
- Jan Halbritter
- Department of Nephrology and Medical Intensive Care, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.
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19
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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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20
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Cui L, Yang B, Xiao S, Gao J, Baud A, Graham D, McBride M, Dominiczak A, Schafer S, Aumatell RL, Mont C, Teruel AF, Hübner N, Flint J, Mott R, Huang L. Dominance is common in mammals and is associated with trans-acting gene expression and alternative splicing. Genome Biol 2023; 24:215. [PMID: 37773188 PMCID: PMC10540365 DOI: 10.1186/s13059-023-03060-2] [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: 03/31/2023] [Accepted: 09/18/2023] [Indexed: 10/01/2023] Open
Abstract
BACKGROUND Dominance and other non-additive genetic effects arise from the interaction between alleles, and historically these phenomena play a major role in quantitative genetics. However, most genome-wide association studies (GWAS) assume alleles act additively. RESULTS We systematically investigate both dominance-here representing any non-additive within-locus interaction-and additivity across 574 physiological and gene expression traits in three mammalian stocks: F2 intercross pigs, rat heterogeneous stock, and mice heterogeneous stock. Dominance accounts for about one quarter of heritable variance across all physiological traits in all species. Hematological and immunological traits exhibit the highest dominance variance, possibly reflecting balancing selection in response to pathogens. Although most quantitative trait loci (QTLs) are detectable as additive QTLs, we identify 154, 64, and 62 novel dominance QTLs in pigs, rats, and mice respectively that are undetectable as additive QTLs. Similarly, even though most cis-acting expression QTLs are additive, gene expression exhibits a large fraction of dominance variance, and trans-acting eQTLs are enriched for dominance. Genes causal for dominance physiological QTLs are less likely to be physically linked to their QTLs but instead act via trans-acting dominance eQTLs. In addition, thousands of eQTLs are associated with alternatively spliced isoforms with complex additive and dominant architectures in heterogeneous stock rats, suggesting a possible mechanism for dominance. CONCLUSIONS Although heritability is predominantly additive, many mammalian genetic effects are dominant and likely arise through distinct mechanisms. It is therefore advantageous to consider both additive and dominance effects in GWAS to improve power and uncover causality.
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Affiliation(s)
- Leilei Cui
- National Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, People's Republic of China
- UCL Genetics Institute, University College London, London, WC1E 6BT, UK
- Human Aging Research Institute and School of Life Science, Nanchang University, and Jiangxi Key Laboratory of Human Aging, Jiangxi, China
- School of Life Sciences, Nanchang University, Nanchang, China
| | - Bin Yang
- National Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, People's Republic of China
| | - Shijun Xiao
- National Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, People's Republic of China
| | - Jun Gao
- National Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, People's Republic of China
| | - Amelie Baud
- Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Barcelona, Spain
| | - Delyth Graham
- BHF Glasgow Cardiovascular Research Centre, University of Glasgow, Glasgow, G12 8TA, UK
| | - Martin McBride
- BHF Glasgow Cardiovascular Research Centre, University of Glasgow, Glasgow, G12 8TA, UK
| | - Anna Dominiczak
- BHF Glasgow Cardiovascular Research Centre, University of Glasgow, Glasgow, G12 8TA, UK
| | - Sebastian Schafer
- Cardiovascular and Metabolic Disorders Program, Duke-National University of Singapore Medical School, Singapore, Singapore
| | - Regina Lopez Aumatell
- Department of Medicine and Life Sciences, Universitat Pompeu Fabra, Barcelona, Spain
| | - Carme Mont
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Albert Fernandez Teruel
- Departamento de Psiquiatría y Medicina Legal, Universitat Autonoma de Barcelona, Barcelona, Spain
| | - Norbert Hübner
- Genetics and Genomics of Cardiovascular Diseases Research Group, Max Delbrück Center (MDC) for Molecular Medicine in the Helmholtz Association, Berlin, Germany
- DZHK (German Center for Cardiovascular Research) Partner Site Berlin, Berlin, Germany
- Charité Universitätsmedizin Berlin, Berlin, Germany
| | - Jonathan Flint
- Department of Psychiatry and Behavioral Sciences, Brain Research Institute, University of California, Los Angeles, CA, USA
| | - Richard Mott
- UCL Genetics Institute, University College London, London, WC1E 6BT, UK.
| | - Lusheng Huang
- National Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, People's Republic of China.
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21
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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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22
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Lassen FH, Venkatesh SS, Baya N, Zhou W, Bloemendal A, Neale BM, Kessler BM, Whiffin N, Lindgren CM, Palmer DS. Exome-wide evidence of compound heterozygous effects across common phenotypes in the UK Biobank. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.06.29.23291992. [PMID: 37461573 PMCID: PMC10350147 DOI: 10.1101/2023.06.29.23291992] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 07/27/2023]
Abstract
Exome-sequencing association studies have successfully linked rare protein-coding variation to risk of thousands of diseases. However, the relationship between rare deleterious compound heterozygous (CH) variation and their phenotypic impact has not been fully investigated. Here, we leverage advances in statistical phasing to accurately phase rare variants (MAF ~ 0.001%) in exome sequencing data from 175,587 UK Biobank (UKBB) participants, which we then systematically annotate to identify putatively deleterious CH coding variation. We show that 6.5% of individuals carry such damaging variants in the CH state, with 90% of variants occurring at MAF < 0.34%. Using a logistic mixed model framework, systematically accounting for relatedness, polygenic risk, nearby common variants, and rare variant burden, we investigate recessive effects in common complex diseases. We find six exome-wide significant (P < 1.68 × 10 - 7 ) and 17 nominally significant (P < 5.25 × 10 - 5 ) gene-trait associations. Among these, only four would have been identified without accounting for CH variation in the gene. We further incorporate age-at-diagnosis information from primary care electronic health records, to show that genetic phase influences lifetime risk of disease across 20 gene-trait combinations (FDR < 5%). Using a permutation approach, we find evidence for genetic phase contributing to disease susceptibility for a collection of gene-trait pairs, including FLG-asthma (P = 0.00205 ) and USH2A-visual impairment (P = 0.0084 ). Taken together, we demonstrate the utility of phasing large-scale genetic sequencing cohorts for robust identification of the phenome-wide consequences of compound heterozygosity.
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Affiliation(s)
- Frederik H. Lassen
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, United Kingdom
| | - Samvida S. Venkatesh
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, United Kingdom
| | - Nikolas Baya
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, United Kingdom
| | - Wei Zhou
- Program in 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
- Analytical and Translational Genetics Unit, Department of Medicine Massachusetts General Hospital, Boston, MA, USA
| | - Alex Bloemendal
- Program in Medical and Population Genetics Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Novo Nordisk Center for Genomic Mechanisms of Disease Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Data Sciences Platform Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Benjamin M. Neale
- Program in 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
- Analytical and Translational Genetics Unit, Department of Medicine Massachusetts General Hospital, Boston, MA, USA
| | - Benedikt M. Kessler
- Target Discovery Institute, Centre for Medicines Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
| | - Nicola Whiffin
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, United Kingdom
- Program in Medical and Population Genetics Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Cecilia M. Lindgren
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, United Kingdom
- Nuffield Department of Population Health Health, Medical Sciences Division University of Oxford, Oxford, United Kingdom
| | - Duncan S. Palmer
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, United Kingdom
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23
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Stratakis CA. Genomics and precision medicine and their impact on endocrinology. Endocr Connect 2023; 12:e230106. [PMID: 37014294 PMCID: PMC10305474 DOI: 10.1530/ec-23-0106] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/24/2023] [Accepted: 04/04/2023] [Indexed: 04/05/2023]
Affiliation(s)
- Constantine A Stratakis
- Human Genetics & Precision Medicine, Institute for Molecular Biology & Biotechnology (IMBB), Foundation for Research & Technology Hellas (FORTH), Heraklion, Greece
- ELPEN, Inc. Research Institute, Athens, Greece
- European University of Cyprus School of Medicine, Nicosia, Cyprus
- Medical Genetics, Henry Dunant Hospital, Athens, Greece
- National Institute of Child Health and Human Development (NICHD), National Institutes of Health (NIH), Bethesda, Maryland, USA
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24
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Coleman J, Green AJ, Bradley L. The utility of multiple genomic technologies for interpretation of modern next generation sequencing: A novel case of three FANCA gene variants resulting in autosomal recessive Fanconi anaemia. Blood Cells Mol Dis 2023; 102:102762. [PMID: 37276838 DOI: 10.1016/j.bcmd.2023.102762] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2023] [Revised: 05/24/2023] [Accepted: 05/26/2023] [Indexed: 06/07/2023]
Abstract
Fanconi anaemia (FA) is a rare autosomal recessive condition resulting in changes in the FANC gene family. This report describes a case of Fanconi anaemia in a family with complex biallelic variants. The patient is a 32-year-old female diagnosed with FA on cascade testing during childhood with chromosome breakage studies. On examination she had a fixed deformity of the right thumb and the proximal interphalangeal joint was immobile. Her brother shared this radial abnormality and had FA, requiring a bone marrow transplant. She presented in adulthood seeking further BRCA advice and had next generation sequencing that showed three variants in the FANCA gene. One allele a known pathogenic change, the other had two sequence variants in tandem that have been reported as variants of uncertain significance. There is one other unrelated case of these two variants occurring together in cis, resulting in Fanconi anaemia. This case is an interesting example of three variants in the FANCA gene, one allele with a pathogenic deletion and the other with a single complex allele made up of two missense variants of uncertain significance, likely manifesting with FA. It highlights the utility of different genetic technologies in the interpretation of next generation sequencing.
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Affiliation(s)
- J Coleman
- Department of Clinical Genetics, Children's Health Ireland at Crumlin Children's Hospital, Dublin, Ireland.
| | - A J Green
- Department of Clinical Genetics, Children's Health Ireland at Crumlin Children's Hospital, Dublin, Ireland; School of Medicine, University College Dublin, Ireland
| | - L Bradley
- Department of Clinical Genetics, Children's Health Ireland at Crumlin Children's Hospital, Dublin, Ireland
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25
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Naqvi S, Kim S, Hoskens H, Matthews HS, Spritz RA, Klein OD, Hallgrímsson B, Swigut T, Claes P, Pritchard JK, Wysocka J. Precise modulation of transcription factor levels identifies features underlying dosage sensitivity. Nat Genet 2023; 55:841-851. [PMID: 37024583 PMCID: PMC10181932 DOI: 10.1038/s41588-023-01366-2] [Citation(s) in RCA: 15] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2022] [Accepted: 03/07/2023] [Indexed: 04/08/2023]
Abstract
Transcriptional regulation exhibits extensive robustness, but human genetics indicates sensitivity to transcription factor (TF) dosage. Reconciling such observations requires quantitative studies of TF dosage effects at trait-relevant ranges, largely lacking so far. TFs play central roles in both normal-range and disease-associated variation in craniofacial morphology; we therefore developed an approach to precisely modulate TF levels in human facial progenitor cells and applied it to SOX9, a TF associated with craniofacial variation and disease (Pierre Robin sequence (PRS)). Most SOX9-dependent regulatory elements (REs) are buffered against small decreases in SOX9 dosage, but REs directly and primarily regulated by SOX9 show heightened sensitivity to SOX9 dosage; these RE responses partially predict gene expression responses. Sensitive REs and genes preferentially affect functional chondrogenesis and PRS-like craniofacial shape variation. We propose that such REs and genes underlie the sensitivity of specific phenotypes to TF dosage, while buffering of other genes leads to robust, nonlinear dosage-to-phenotype relationships.
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Affiliation(s)
- Sahin Naqvi
- Department of Chemical and Systems Biology, Stanford University School of Medicine, Stanford, CA, USA
- Departments of Genetics and Biology, Stanford University, Stanford, CA, USA
- Department of Developmental Biology, Stanford University School of Medicine, Stanford, CA, USA
| | - Seungsoo Kim
- Department of Chemical and Systems Biology, Stanford University School of Medicine, Stanford, CA, USA
- Department of Developmental Biology, Stanford University School of Medicine, Stanford, CA, USA
- Howard Hughes Medical Institute, Stanford University School of Medicine, Stanford, CA, USA
| | - Hanne Hoskens
- Department of Human Genetics, KU Leuven, Leuven, Belgium
- Medical Imaging Research Center, University Hospitals Leuven, Leuven, Belgium
- Department of Cell Biology & Anatomy, Alberta Children's Hospital Research Institute and McCaig Bone and Joint Institute, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
| | - Harold S Matthews
- Department of Human Genetics, KU Leuven, Leuven, Belgium
- Medical Imaging Research Center, University Hospitals Leuven, Leuven, Belgium
| | - Richard A Spritz
- Human Medical Genetics and Genomics Program and Department of Pediatrics, University of Colorado School of Medicine, Aurora, CO, USA
| | - Ophir D Klein
- Departments of Orofacial Sciences and Pediatrics, Program in Craniofacial Biology, and Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA
- Department of Pediatrics, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Benedikt Hallgrímsson
- Department of Cell Biology & Anatomy, Alberta Children's Hospital Research Institute and McCaig Bone and Joint Institute, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
| | - Tomek Swigut
- Department of Chemical and Systems Biology, Stanford University School of Medicine, Stanford, CA, USA
| | - Peter Claes
- Department of Human Genetics, KU Leuven, Leuven, Belgium
- Medical Imaging Research Center, University Hospitals Leuven, Leuven, Belgium
- Department of Electrical Engineering, ESAT/PSI, KU Leuven, Leuven, Belgium
- Murdoch Children's Research Institute, Melbourne, Victoria, Australia
| | | | - Joanna Wysocka
- Department of Chemical and Systems Biology, Stanford University School of Medicine, Stanford, CA, USA.
- Department of Developmental Biology, Stanford University School of Medicine, Stanford, CA, USA.
- Howard Hughes Medical Institute, Stanford University School of Medicine, Stanford, CA, USA.
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26
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Leone MP, Morlino S, Nardella G, Pracella R, Giachino D, Celli L, Baldo D, Turolla L, Piccione M, Salzano E, Busè M, Lastella P, Zollino M, Cantone R, Grosso E, Zonta A, Pasini B, Piscopo C, De Maggio I, Priolo M, Mammi C, Foiadelli T, Trabatti C, Savasta S, Iolascon A, Ferraris A, Lodato V, Di Giosaffatte N, Majore S, Selicorni A, Petracca A, Fusco C, Celli M, Guarnieri V, Micale L, Castori M. Specifications and validation of the ACMG/AMP criteria for clinical interpretation of sequence variants in collagen genes associated with joint hypermobility. Hum Genet 2023; 142:785-808. [PMID: 37079061 DOI: 10.1007/s00439-023-02547-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2023] [Accepted: 03/17/2023] [Indexed: 04/21/2023]
Abstract
Deleterious variants in collagen genes are the most common cause of hereditary connective tissue disorders (HCTD). Adaptations of the American College of Medical Genetics and Genomics/Association for Molecular Pathology (ACMG/AMP) criteria are still lacking. A multidisciplinary team was set up for developing specifications of the ACMG/AMP criteria for COL1A1, COL1A2, COL2A1, COL3A1, COL5A1, COL5A2, COL11A1, COL11A2 and COL12A1, associated with various forms of HCTD featuring joint hypermobility, which is becoming one of the most common reasons of referral for molecular testing in this field. Such specifications were validated against 209 variants, and resulted effective for classifying as pathogenic and likely pathogenic null alleles without downgrading of the PVS1 level of strength and recurrent Glycine substitutions. Adaptations of selected criteria reduced uncertainties on private Glycine substitutions, intronic variants predicted to affect the splicing, and null alleles with a downgraded PVS1 level of strength. Segregation and multigene panel sequencing data mitigated uncertainties on non-Glycine substitutions by the attribution of one or more benignity criteria. These specifications may improve the clinical utility of molecular testing in HCTD by reducing the number of variants with neutral/conflicting interpretations. Close interactions between laboratory and clinicians are crucial to estimate the a priori utility of molecular test and to improve medical reports.
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Affiliation(s)
- Maria Pia Leone
- Division of Medical Genetics, Poliambulatorio "Giovanni Paolo II", Fondazione IRCCS-Casa Sollievo della Sofferenza, Viale Padre Pio 7, 71013, San Giovanni Rotondo, Italy
| | - Silvia Morlino
- Division of Medical Genetics, Poliambulatorio "Giovanni Paolo II", Fondazione IRCCS-Casa Sollievo della Sofferenza, Viale Padre Pio 7, 71013, San Giovanni Rotondo, Italy
| | - Grazia Nardella
- Division of Medical Genetics, Poliambulatorio "Giovanni Paolo II", Fondazione IRCCS-Casa Sollievo della Sofferenza, Viale Padre Pio 7, 71013, San Giovanni Rotondo, Italy
| | - Riccardo Pracella
- Division of Medical Genetics, Poliambulatorio "Giovanni Paolo II", Fondazione IRCCS-Casa Sollievo della Sofferenza, Viale Padre Pio 7, 71013, San Giovanni Rotondo, Italy
| | - Daniela Giachino
- Medical Genetics Unit, Department of Clinical and Biological Sciences, University of Turin, AOU 'S. Luigi Gonzaga', Orbassano, Turin, Italy
| | - Luca Celli
- Center for Rare Diseases, AOU Policlinico 'Umberto I', Rome, Italy
| | - Demetrio Baldo
- Medical Genetics Unit, AULSS2 Marca Trevigiana, Treviso, Italy
| | - Licia Turolla
- Medical Genetics Unit, AULSS2 Marca Trevigiana, Treviso, Italy
| | - Maria Piccione
- Department of Health Promotion, Mother and Child Care, Internal Medicine and Medical Specialties, University of Palermo, Palermo, Italy
- Division of Medical Genetics, AOOR Villa Sofia-Cervello, Palermo, Italy
| | - Emanuela Salzano
- Division of Medical Genetics, AOOR Villa Sofia-Cervello, Palermo, Italy
| | - Martina Busè
- Division of Medical Genetics, AOOR Villa Sofia-Cervello, Palermo, Italy
| | - Patrizia Lastella
- Centro Sovraziendale Malattie Rare - UOC Medicina Interna Universitaria "C. Frugoni" - AOU Policlinico Consorziale di Bari, Bari, Italy
| | - Marcella Zollino
- Institute of Genomic Medicine, Department of Life Sciences and Public Health, 'Sacro Cuore' Catholic University of Rome, Rome, Italy
- Medical Genetics Unit, Foundation IRCCS AOU Policlinico 'A. Gemelli', Rome, Italy
| | - Rachele Cantone
- Medical Genetics Unit, AOU 'Città della Salute e della Scienza' - 'Molinette' Hospital, Turin, Italy
| | - Enrico Grosso
- Medical Genetics Unit, AOU 'Città della Salute e della Scienza' - 'Molinette' Hospital, Turin, Italy
| | - Andrea Zonta
- Medical Genetics Unit, AOU 'Città della Salute e della Scienza' - 'Molinette' Hospital, Turin, Italy
| | - Barbara Pasini
- Medical Genetics Unit, AOU 'Città della Salute e della Scienza' - 'Molinette' Hospital, Turin, Italy
| | - Carmelo Piscopo
- Medical and Laboratory Genetics Unit, AORN 'Antonio Cardarelli', Naples, Italy
| | - Ilaria De Maggio
- Medical and Laboratory Genetics Unit, AORN 'Antonio Cardarelli', Naples, Italy
| | - Manuela Priolo
- Medical Genetics Unit, Grande Ospedale Metropolitano 'Bianchi Melacrino Morelli', Reggio Calabria, Italy
| | - Corrado Mammi
- Medical Genetics Unit, Grande Ospedale Metropolitano 'Bianchi Melacrino Morelli', Reggio Calabria, Italy
| | - Thomas Foiadelli
- Clinica Pediatrica, Fondazione IRCCS Policlinico San Matteo, Pavia, Italy
| | - Chiara Trabatti
- Division of Pediatrics, Azienda Socio Sanitaria Territoriale (ASST) Crema, Crema, Italy
| | - Salvatore Savasta
- Division of Pediatrics, Azienda Socio Sanitaria Territoriale (ASST) Crema, Crema, Italy
| | - Achille Iolascon
- Department of Molecular Medicine and Medical Biotechnologies, Federico II' University of Naples, Naples, Italy
- CEINGE Biotecnologie Avanzate, Naples, Italy
| | - Alessandro Ferraris
- Clinical Genetics Unit, UOC Laboratory of Medical Genetics, Department of Experimental Medicine at, Sapienza University, AO San Camillo-Forlanini, Rome, Italy
| | - Valentina Lodato
- Clinical Genetics Unit, UOC Laboratory of Medical Genetics, Department of Experimental Medicine at, Sapienza University, AO San Camillo-Forlanini, Rome, Italy
| | - Niccolò Di Giosaffatte
- Clinical Genetics Unit, UOC Laboratory of Medical Genetics, Department of Experimental Medicine at, Sapienza University, AO San Camillo-Forlanini, Rome, Italy
| | - Silvia Majore
- Clinical Genetics Unit, UOC Laboratory of Medical Genetics, Department of Experimental Medicine at, Sapienza University, AO San Camillo-Forlanini, Rome, Italy
| | - Angelo Selicorni
- Department of Pediatrics, Center for Fragile Child, ASST Lariana Sant'Anna Hospital, Como, San Fermo della Battaglia, Italy
| | - Antonio Petracca
- Division of Medical Genetics, Poliambulatorio "Giovanni Paolo II", Fondazione IRCCS-Casa Sollievo della Sofferenza, Viale Padre Pio 7, 71013, San Giovanni Rotondo, Italy
| | - Carmela Fusco
- Division of Medical Genetics, Poliambulatorio "Giovanni Paolo II", Fondazione IRCCS-Casa Sollievo della Sofferenza, Viale Padre Pio 7, 71013, San Giovanni Rotondo, Italy
| | - Mauro Celli
- Center for Rare Diseases, AOU Policlinico 'Umberto I', Rome, Italy
| | - Vito Guarnieri
- Division of Medical Genetics, Poliambulatorio "Giovanni Paolo II", Fondazione IRCCS-Casa Sollievo della Sofferenza, Viale Padre Pio 7, 71013, San Giovanni Rotondo, Italy
| | - Lucia Micale
- Division of Medical Genetics, Poliambulatorio "Giovanni Paolo II", Fondazione IRCCS-Casa Sollievo della Sofferenza, Viale Padre Pio 7, 71013, San Giovanni Rotondo, Italy
| | - Marco Castori
- Division of Medical Genetics, Poliambulatorio "Giovanni Paolo II", Fondazione IRCCS-Casa Sollievo della Sofferenza, Viale Padre Pio 7, 71013, San Giovanni Rotondo, Italy.
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27
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28
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Körner A, Stein R, Landgraf K. Beyond genetic screening-functionality-based precision medicine in monogenic obesity. Lancet Diabetes Endocrinol 2023; 11:143-144. [PMID: 36822741 DOI: 10.1016/s2213-8587(23)00031-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/24/2023] [Accepted: 01/24/2023] [Indexed: 02/25/2023]
Affiliation(s)
- Antje Körner
- Helmholtz Institute for Metabolic, Obesity, and Vascular Research, Helmholtz Zentrum München at the University of Leipzig and University Hospital Leipzig, Leipzig, Germany; University of Leipzig, Medical Faculty, Leipzig University Hospital for Children and Adolescents, Center for Pediatric Research, Leipzig, Germany.
| | - Robert Stein
- Helmholtz Institute for Metabolic, Obesity, and Vascular Research, Helmholtz Zentrum München at the University of Leipzig and University Hospital Leipzig, Leipzig, Germany; University of Leipzig, Medical Faculty, Leipzig University Hospital for Children and Adolescents, Center for Pediatric Research, Leipzig, Germany
| | - Kathrin Landgraf
- University of Leipzig, Medical Faculty, Leipzig University Hospital for Children and Adolescents, Center for Pediatric Research, Leipzig, Germany
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29
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Kurki MI, Karjalainen J, Palta P, Sipilä TP, Kristiansson K, Donner KM, Reeve MP, Laivuori H, Aavikko M, Kaunisto MA, Loukola A, Lahtela E, Mattsson H, Laiho P, Della Briotta Parolo P, Lehisto AA, Kanai M, Mars N, Rämö J, Kiiskinen T, Heyne HO, Veerapen K, Rüeger S, Lemmelä S, Zhou W, Ruotsalainen S, Pärn K, Hiekkalinna T, Koskelainen S, Paajanen T, Llorens V, Gracia-Tabuenca J, Siirtola H, Reis K, Elnahas AG, Sun B, Foley CN, Aalto-Setälä K, Alasoo K, Arvas M, Auro K, Biswas S, Bizaki-Vallaskangas A, Carpen O, Chen CY, Dada OA, Ding Z, Ehm MG, Eklund K, Färkkilä M, Finucane H, Ganna A, Ghazal A, Graham RR, Green EM, Hakanen A, Hautalahti M, Hedman ÅK, Hiltunen M, Hinttala R, Hovatta I, Hu X, Huertas-Vazquez A, Huilaja L, Hunkapiller J, Jacob H, Jensen JN, Joensuu H, John S, Julkunen V, Jung M, Junttila J, Kaarniranta K, Kähönen M, Kajanne R, Kallio L, Kälviäinen R, Kaprio J, Kerimov N, Kettunen J, Kilpeläinen E, Kilpi T, Klinger K, Kosma VM, Kuopio T, Kurra V, Laisk T, Laukkanen J, Lawless N, Liu A, Longerich S, Mägi R, Mäkelä J, Mäkitie A, Malarstig A, Mannermaa A, Maranville J, Matakidou A, Meretoja T, Mozaffari SV, Niemi MEK, Niemi M, Niiranen T, O Donnell CJ, Obeidat ME, Okafo G, Ollila HM, Palomäki A, Palotie T, Partanen J, Paul DS, Pelkonen M, Pendergrass RK, Petrovski S, Pitkäranta A, Platt A, Pulford D, Punkka E, Pussinen P, Raghavan N, Rahimov F, Rajpal D, Renaud NA, Riley-Gillis B, Rodosthenous R, Saarentaus E, Salminen A, Salminen E, Salomaa V, Schleutker J, Serpi R, Shen HY, Siegel R, Silander K, Siltanen S, Soini S, Soininen H, Sul JH, Tachmazidou I, Tasanen K, Tienari P, Toppila-Salmi S, Tukiainen T, Tuomi T, Turunen JA, Ulirsch JC, Vaura F, Virolainen P, Waring J, Waterworth D, Yang R, Nelis M, Reigo A, Metspalu A, Milani L, Esko T, Fox C, Havulinna AS, Perola M, Ripatti S, Jalanko A, Laitinen T, Mäkelä TP, Plenge R, McCarthy M, Runz H, Daly MJ, Palotie A. FinnGen provides genetic insights from a well-phenotyped isolated population. Nature 2023; 613:508-518. [PMID: 36653562 PMCID: PMC9849126 DOI: 10.1038/s41586-022-05473-8] [Citation(s) in RCA: 873] [Impact Index Per Article: 873.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2022] [Accepted: 10/21/2022] [Indexed: 01/20/2023]
Abstract
Population isolates such as those in Finland benefit genetic research because deleterious alleles are often concentrated on a small number of low-frequency variants (0.1% ≤ minor allele frequency < 5%). These variants survived the founding bottleneck rather than being distributed over a large number of ultrarare variants. Although this effect is well established in Mendelian genetics, its value in common disease genetics is less explored1,2. FinnGen aims to study the genome and national health register data of 500,000 Finnish individuals. Given the relatively high median age of participants (63 years) and the substantial fraction of hospital-based recruitment, FinnGen is enriched for disease end points. Here we analyse data from 224,737 participants from FinnGen and study 15 diseases that have previously been investigated in large genome-wide association studies (GWASs). We also include meta-analyses of biobank data from Estonia and the United Kingdom. We identified 30 new associations, primarily low-frequency variants, enriched in the Finnish population. A GWAS of 1,932 diseases also identified 2,733 genome-wide significant associations (893 phenome-wide significant (PWS), P < 2.6 × 10-11) at 2,496 (771 PWS) independent loci with 807 (247 PWS) end points. Among these, fine-mapping implicated 148 (73 PWS) coding variants associated with 83 (42 PWS) end points. Moreover, 91 (47 PWS) had an allele frequency of <5% in non-Finnish European individuals, of which 62 (32 PWS) were enriched by more than twofold in Finland. These findings demonstrate the power of bottlenecked populations to find entry points into the biology of common diseases through low-frequency, high impact variants.
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Affiliation(s)
- Mitja I Kurki
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland.,Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA.,Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA, USA.,Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
| | - Juha Karjalainen
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland.,Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA.,Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA, USA.,Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
| | - Priit Palta
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland.,Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Timo P Sipilä
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland
| | | | - Kati M Donner
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland
| | - Mary P Reeve
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland
| | - Hannele Laivuori
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland.,Medical and Clinical Genetics, University of Helsinki and Helsinki University Hospital, Helsinki, Finland.,Department of Obstetrics and Gynecology, Tampere University Hospital, Tampere, Finland.,Faculty of Medicine and Health Technology, Center for Child, Adolescent and Maternal Health, University of Tampere, Tampere, Finland
| | - Mervi Aavikko
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland
| | - Mari A Kaunisto
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland
| | - Anu Loukola
- Helsinki Biobank, University of Helsinki and Hospital District of Helsinki and Uusimaa, Helsinki, Finland
| | - Elisa Lahtela
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland
| | - Hannele Mattsson
- Finnish Institute for Health and Welfare (THL), Helsinki, Finland
| | - Päivi Laiho
- Finnish Institute for Health and Welfare (THL), Helsinki, Finland
| | - Pietro Della Briotta Parolo
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland
| | - Arto A Lehisto
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland
| | - Masahiro Kanai
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland.,Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA.,Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA, USA.,Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA.,Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Nina Mars
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland
| | - Joel Rämö
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland
| | - Tuomo Kiiskinen
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland
| | - Henrike O Heyne
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland.,Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA.,Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA, USA.,Digital Health Center, Hasso Plattner Institute for Digital Engineering, University of Potsdam Potsdam, Potsdam, Germany.,Hasso Plattner Institute for Digital Health at Mount Sinai, Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Kumar Veerapen
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland.,Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA.,Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA, USA.,Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
| | - Sina Rüeger
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland
| | - Susanna Lemmelä
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland.,Finnish Institute for Health and Welfare (THL), Helsinki, Finland
| | - Wei Zhou
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA.,Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA, USA.,Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
| | - Sanni Ruotsalainen
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland
| | - Kalle Pärn
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland
| | - Tero Hiekkalinna
- Finnish Institute for Health and Welfare (THL), Helsinki, Finland
| | - Sami Koskelainen
- Finnish Institute for Health and Welfare (THL), Helsinki, Finland
| | - Teemu Paajanen
- Finnish Institute for Health and Welfare (THL), Helsinki, Finland
| | - Vincent Llorens
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland
| | - Javier Gracia-Tabuenca
- TAUCHI Research Center, Faculty of Information Technology and Communication Sciences, Tampere University, Tampere, Finland
| | - Harri Siirtola
- TAUCHI Research Center, Faculty of Information Technology and Communication Sciences, Tampere University, Tampere, Finland
| | - Kadri Reis
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | | | - Benjamin Sun
- Translational Biology, Research and Development, Biogen, Cambridge, MA, USA.,BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Christopher N Foley
- Optima Partners, Edinburgh, UK.,MRC Biostatistics Unit, School of Clinical Medicine, University of Cambridge, Cambridge, UK
| | | | - Kaur Alasoo
- Institute of Computer Science, University of Tartu, Tartu, Estonia
| | - Mikko Arvas
- Finnish Red Cross Blood Service, Helsinki, Finland
| | | | | | | | - Olli Carpen
- Helsinki Biobank, University of Helsinki and Hospital District of Helsinki and Uusimaa, Helsinki, Finland
| | | | - Oluwaseun A Dada
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland
| | - Zhihao Ding
- Boehringer Ingelheim, Ingelheim am Rhein, Germany
| | | | - Kari Eklund
- Division of Rheumatology, Department of Medicine, Helsinki University Central Hospital, Helsinki, Finland.,Orton Orthopedic Hospital, Helsinki, Finland
| | - Martti Färkkilä
- Abdominal Center, Helsinki University Hospital, Helsinki University, Helsinki, Finland
| | - Hilary Finucane
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA.,Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA, USA.,Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
| | - Andrea Ganna
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland.,Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA.,Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA, USA.,Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
| | - Awaisa Ghazal
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland
| | | | | | - Antti Hakanen
- Auria Biobank, University of Turku and Turku University Hospital, Turku, Finland
| | | | - Åsa K Hedman
- Pfizer, New York, NY, USA.,Department of Medicine, Karolinska Institute, Solna, Sweden
| | - Mikko Hiltunen
- Clinical Biobank Tampere, Tampere University and Tampere University Hospital, Tampere, Finland
| | - Reetta Hinttala
- Medical Research Center Oulu and PEDEGO Research Unit, University of Oulu, Oulu, Finland.,Biocenter Oulu, University of Oulu, Oulu, Finland.,Oulu University Hospital, Oulu, Finland
| | - Iiris Hovatta
- Department of Psychology and Logopedics, Faculty of Medicine, University of Helsinki, Helsinki, Finland.,SleepWell Research Program, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | | | | | - Laura Huilaja
- PEDEGO Research Unit, University of Oulu, Oulu, Finland.,Department of Dermatology and Medical Research Center Oulu, Oulu University Hospital, Oulu, Finland
| | | | | | | | - Heikki Joensuu
- Helsinki University Hospital and University of Helsinki, Helsinki, Finland
| | | | - Valtteri Julkunen
- Neuro Center, Neurology, Kuopio University Hospital, Kuopio, Finland.,Institute of Clinical Medicine-Neurology, University of Eastern Finland, Kuopio, Finland
| | - Marc Jung
- Boehringer Ingelheim, Ingelheim am Rhein, Germany
| | - Juhani Junttila
- Northern Finland Biobank Borealis, University of Oulu, Northern Ostrobothnia Hospital District, Oulu, Finland
| | - Kai Kaarniranta
- Department of Ophthalmology, Kuopio University Hospital, Kuopio, Finland.,Department of Ophthalmology, Institute of Clinical Medicine, University of Eastern Finland, Kuopio, Finland
| | - Mika Kähönen
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland.,Department of Clinical Physiology, Tampere University Hospital, Tampere, Finland
| | - Risto Kajanne
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland
| | - Lila Kallio
- Auria Biobank, University of Turku and Turku University Hospital, Turku, Finland
| | - Reetta Kälviäinen
- Epilepsy Center, Kuopio University Hospital, Kuopio, Finland.,Department of Neurology, University of Eastern Finland, Kuopio, Finland
| | - Jaakko Kaprio
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland.,Department of Public Health, University of Helsinki, Helsinki, Finland
| | | | - Nurlan Kerimov
- Institute of Computer Science, University of Tartu, Tartu, Estonia
| | - Johannes Kettunen
- Finnish Institute for Health and Welfare (THL), Helsinki, Finland.,Biocenter Oulu, University of Oulu, Oulu, Finland.,Computational Medicine, Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland
| | - Elina Kilpeläinen
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland
| | - Terhi Kilpi
- Finnish Institute for Health and Welfare (THL), Helsinki, Finland
| | | | - Veli-Matti Kosma
- Biobank of Eastern Finland, University of Eastern Finland, Kuopio, Finland.,Kuopio University Hospital, Kuopio, Finland
| | - Teijo Kuopio
- Central Finland Biobank, Central Finland Health Care District, Jyväskylä, Finland
| | - Venla Kurra
- Department of Clinical Genetics, Tampere University Hospital, Tampere, Finland.,Department of Clinical Genetics, Faculty of Medicine and Health Technology, Tampere, Finland
| | - Triin Laisk
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Jari Laukkanen
- Central Finland Biobank, Central Finland Health Care District, Jyväskylä, Finland.,Department of Medicine, Institute of Clinical Medicine, University of Eastern Finland, Kuopio, Finland
| | | | - Aoxing Liu
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland
| | | | - Reedik Mägi
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | | | - Antti Mäkitie
- Department of Otorhinolaryngology-Head and Neck Surgery, University of Helsinki, Helsinki, Finland.,Helsinki University Hospital, Helsinki, Finland
| | - Anders Malarstig
- Pfizer, Cambridge, MA, USA.,Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Solna, Sweden
| | - Arto Mannermaa
- Biobank of Eastern Finland, University of Eastern Finland, Kuopio, Finland.,Kuopio University Hospital, Kuopio, Finland
| | | | - Athena Matakidou
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
| | - Tuomo Meretoja
- Helsinki University Hospital and University of Helsinki, Helsinki, Finland
| | | | - Mari E K Niemi
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland
| | - Marianna Niemi
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland.,TAUCHI Research Center & Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Teemu Niiranen
- Finnish Institute for Health and Welfare (THL), Helsinki, Finland.,Turku University Hospital and University of Turku, Turku, Finland
| | | | - Ma En Obeidat
- Novartis Institutes for BioMedical Research, Cambridge, MA, USA
| | - George Okafo
- Boehringer Ingelheim, Ingelheim am Rhein, Germany
| | - Hanna M Ollila
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland.,Anesthesia, Critical Care, and Pain Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Antti Palomäki
- Turku University Hospital and University of Turku, Turku, Finland
| | - Tuula Palotie
- Department of Oral and Maxillofacial Diseases, Helsinki University Hospital, Helsinki, Finland.,Department of Oral and Maxillofacial Diseases, University of Helsinki, Helsinki, Finland
| | - Jukka Partanen
- Finnish Red Cross Blood Service, Helsinki, Finland.,Finnish Hematological Biobank, Helsinki, Finland
| | - Dirk S Paul
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
| | - Margit Pelkonen
- Department of Pulmonary Diseases, Kuopio University Hospital, Kuopio, Finland
| | | | - Slavé Petrovski
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
| | - Anne Pitkäranta
- Department of Otorhinolaryngology, Helsinki University Hospital and University of Helsinki, Helsinki, Finland
| | - Adam Platt
- Translational Science and Experimental Medicine, Research and Early Development, Respiratory and Immunology, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
| | | | - Eero Punkka
- Helsinki Biobank, University of Helsinki and Hospital District of Helsinki and Uusimaa, Helsinki, Finland
| | - Pirkko Pussinen
- Department of Oral and Maxillofacial Diseases, University of Helsinki, Helsinki, Finland
| | | | | | - Deepak Rajpal
- Translational Sciences, Sanofi R&D, Framingham, MA, USA
| | - Nicole A Renaud
- Novartis Institutes for BioMedical Research, Cambridge, MA, USA
| | | | - Rodosthenis Rodosthenous
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland
| | - Elmo Saarentaus
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland
| | - Aino Salminen
- Department of Oral and Maxillofacial Diseases, University of Helsinki, Helsinki, Finland
| | - Eveliina Salminen
- Helsinki University Hospital, Helsinki, Finland.,Department of Clinical Genetics, HUSLAB, HUS Diagnostic Center, University of Helsinki, Helsinki, Finland
| | - Veikko Salomaa
- Finnish Institute for Health and Welfare (THL), Helsinki, Finland
| | - Johanna Schleutker
- Auria Biobank, University of Turku and Turku University Hospital, Turku, Finland
| | - Raisa Serpi
- Northern Finland Biobank Borealis, University of Oulu, Northern Ostrobothnia Hospital District, Oulu, Finland
| | - Huei-Yi Shen
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland
| | - Richard Siegel
- Novartis Institutes for BioMedical Research, Basel, Switzerland
| | - Kaisa Silander
- Finnish Institute for Health and Welfare (THL), Helsinki, Finland
| | - Sanna Siltanen
- Finnish Clinical Biobank Tampere, Tampere University and Tampere University Hospital, Tampere, Finland
| | - Sirpa Soini
- Finnish Institute for Health and Welfare (THL), Helsinki, Finland
| | - Hilkka Soininen
- Department of Neurology, Institute of Clinical Medicine, University of Eastern Finland, Kuopio, Finland
| | | | - Ioanna Tachmazidou
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
| | - Kaisa Tasanen
- PEDEGO Research Unit, University of Oulu, Oulu, Finland.,Department of Dermatology and Medical Research Center Oulu, Oulu University Hospital, Oulu, Finland
| | - Pentti Tienari
- Department of Neurology, Helsinki University Hospital, Helsinki, Finland.,Translational Immunology, Research Programs Unit, University of Helsinki, Helsinki, Finland
| | - Sanna Toppila-Salmi
- Department of Allergy, Helsinki University Hospital and University of Helsinki, Helsinki, Finland
| | - Taru Tukiainen
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland
| | - Tiinamaija Tuomi
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland.,Abdominal Center, Endocrinology, Helsinki University Hospital, Helsinki, Finland.,Folkhalsan Research Center, Helsinki, Finland.,Research Program of Clinical and Molecular Metabolism, University of Helsinki, Helsinki, Finland
| | - Joni A Turunen
- Helsinki University Hospital and University of Helsinki, Helsinki, Finland.,Eye Genetics Group, Folkhälsan Research Center, Helsinki, Finland
| | - Jacob C Ulirsch
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA.,Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Felix Vaura
- Finnish Institute for Health and Welfare (THL), Helsinki, Finland.,University of Turku, Turku, Finland
| | - Petri Virolainen
- Auria Biobank, University of Turku and Turku University Hospital, Turku, Finland
| | | | | | | | - Mari Nelis
- Genomics Core Facility, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Anu Reigo
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Andres Metspalu
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Lili Milani
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Tõnu Esko
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | | | - Aki S Havulinna
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland.,Finnish Institute for Health and Welfare (THL), Helsinki, Finland
| | - Markus Perola
- Finnish Institute for Health and Welfare (THL), Helsinki, Finland
| | - Samuli Ripatti
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland
| | - Anu Jalanko
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland
| | - Tarja Laitinen
- Finnish Clinical Biobank Tampere, Tampere University and Tampere University Hospital, Tampere, Finland
| | - Tomi P Mäkelä
- Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland
| | | | | | | | - Mark J Daly
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland.,Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA.,Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA, USA.,Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
| | - Aarno Palotie
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland. .,Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA. .,Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA, USA. .,Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA.
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