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Atla G, Bonàs-Guarch S, Cuenca-Ardura M, Beucher A, Crouch DJM, Garcia-Hurtado J, Moran I, Irimia M, Prasad RB, Gloyn AL, Marselli L, Suleiman M, Berney T, de Koning EJP, Kerr-Conte J, Pattou F, Todd JA, Piemonti L, Ferrer J. Genetic regulation of RNA splicing in human pancreatic islets. Genome Biol 2022; 23:196. [PMID: 36109769 PMCID: PMC9479353 DOI: 10.1186/s13059-022-02757-0] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2021] [Accepted: 08/23/2022] [Indexed: 12/30/2022] Open
Abstract
BACKGROUND Non-coding genetic variants that influence gene transcription in pancreatic islets play a major role in the susceptibility to type 2 diabetes (T2D), and likely also contribute to type 1 diabetes (T1D) risk. For many loci, however, the mechanisms through which non-coding variants influence diabetes susceptibility are unknown. RESULTS We examine splicing QTLs (sQTLs) in pancreatic islets from 399 human donors and observe that common genetic variation has a widespread influence on the splicing of genes with established roles in islet biology and diabetes. In parallel, we profile expression QTLs (eQTLs) and use transcriptome-wide association as well as genetic co-localization studies to assign islet sQTLs or eQTLs to T2D and T1D susceptibility signals, many of which lack candidate effector genes. This analysis reveals biologically plausible mechanisms, including the association of T2D with an sQTL that creates a nonsense isoform in ERO1B, a regulator of ER-stress and proinsulin biosynthesis. The expanded list of T2D risk effector genes reveals overrepresented pathways, including regulators of G-protein-mediated cAMP production. The analysis of sQTLs also reveals candidate effector genes for T1D susceptibility such as DCLRE1B, a senescence regulator, and lncRNA MEG3. CONCLUSIONS These data expose widespread effects of common genetic variants on RNA splicing in pancreatic islets. The results support a role for splicing variation in diabetes susceptibility, and offer a new set of genetic targets with potential therapeutic benefit.
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Affiliation(s)
- Goutham Atla
- Centre for Genomic Regulation, The Barcelona Institute of Science and Technology, Barcelona, Spain
- Centro de Investigación Biomédica en red Diabetes y enfermedades metabólicas asociadas (CIBERDEM), Barcelona, Spain
- Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
| | - Silvia Bonàs-Guarch
- Centre for Genomic Regulation, The Barcelona Institute of Science and Technology, Barcelona, Spain.
- Centro de Investigación Biomédica en red Diabetes y enfermedades metabólicas asociadas (CIBERDEM), Barcelona, Spain.
- Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK.
| | - Mirabai Cuenca-Ardura
- Centre for Genomic Regulation, The Barcelona Institute of Science and Technology, Barcelona, Spain
- Centro de Investigación Biomédica en red Diabetes y enfermedades metabólicas asociadas (CIBERDEM), Barcelona, Spain
| | - Anthony Beucher
- Centre for Genomic Regulation, The Barcelona Institute of Science and Technology, Barcelona, Spain
- Centro de Investigación Biomédica en red Diabetes y enfermedades metabólicas asociadas (CIBERDEM), Barcelona, Spain
- Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
| | - Daniel J M Crouch
- JDRF/Wellcome Diabetes and Inflammation Laboratory, Wellcome Centre for Human Genetics, Nuffield Department of Medicine, NIHR Oxford Biomedical Research Centre, University of Oxford, Oxford, UK
| | - Javier Garcia-Hurtado
- Centre for Genomic Regulation, The Barcelona Institute of Science and Technology, Barcelona, Spain
- Centro de Investigación Biomédica en red Diabetes y enfermedades metabólicas asociadas (CIBERDEM), Barcelona, Spain
| | - Ignasi Moran
- Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
- Present Address: Life Sciences Department, Barcelona Supercomputing Center (BSC), 08034, Barcelona, Spain
| | - Manuel Irimia
- Centre for Genomic Regulation, The Barcelona Institute of Science and Technology, Barcelona, Spain
| | - Rashmi B Prasad
- Lund University Diabetes Centre, Clinical Research Center, Malmö, Sweden
- Department of Clinical Sciences in Malmö, Lund University, Malmö, Sweden
| | - Anna L Gloyn
- Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
- Department of Pediatrics, Division of Endocrinology, Stanford School of Medicine, Stanford, CA, USA
| | - Lorella Marselli
- Department of Clinical and Experimental Medicine, AOUP Cisanello University Hospital, University of Pisa, Pisa, Italy
| | - Mara Suleiman
- Department of Clinical and Experimental Medicine, AOUP Cisanello University Hospital, University of Pisa, Pisa, Italy
| | - Thierry Berney
- Cell Isolation and Transplantation Center, University of Geneva, Geneva, Switzerland
| | - Eelco J P de Koning
- Department of Medicine, Leiden University Medical Center, Leiden, the Netherlands
- Hubrecht Institute/KNAW, Utrecht, the Netherlands
| | - Julie Kerr-Conte
- University of Lille, Institut National de la Santé et de la Recherche Médicale (INSERM), Centre Hospitalier Universitaire de Lille (CHU Lille), Institute Pasteur Lille, U1190 -European Genomic Institute for Diabetes (EGID), F59000, Lille, France
| | - Francois Pattou
- University of Lille, Institut National de la Santé et de la Recherche Médicale (INSERM), Centre Hospitalier Universitaire de Lille (CHU Lille), Institute Pasteur Lille, U1190 -European Genomic Institute for Diabetes (EGID), F59000, Lille, France
| | - John A Todd
- JDRF/Wellcome Diabetes and Inflammation Laboratory, Wellcome Centre for Human Genetics, Nuffield Department of Medicine, NIHR Oxford Biomedical Research Centre, University of Oxford, Oxford, UK
| | - Lorenzo Piemonti
- Diabetes Research Institute, IRCCS Ospedale San Raffaele and Università Vita-Salute San Raffaele, Milan, Italy
| | - Jorge Ferrer
- Centre for Genomic Regulation, The Barcelona Institute of Science and Technology, Barcelona, Spain.
- Centro de Investigación Biomédica en red Diabetes y enfermedades metabólicas asociadas (CIBERDEM), Barcelona, Spain.
- Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK.
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Robertson CC, Inshaw JRJ, Onengut-Gumuscu S, Chen WM, Santa Cruz DF, Yang H, Cutler AJ, Crouch DJM, Farber E, Bridges SL, Edberg JC, Kimberly RP, Buckner JH, Deloukas P, Divers J, Dabelea D, Lawrence JM, Marcovina S, Shah AS, Greenbaum CJ, Atkinson MA, Gregersen PK, Oksenberg JR, Pociot F, Rewers MJ, Steck AK, Dunger DB, Wicker LS, Concannon P, Todd JA, Rich SS. Fine-mapping, trans-ancestral and genomic analyses identify causal variants, cells, genes and drug targets for type 1 diabetes. Nat Genet 2021; 53:962-971. [PMID: 34127860 PMCID: PMC8273124 DOI: 10.1038/s41588-021-00880-5] [Citation(s) in RCA: 98] [Impact Index Per Article: 32.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2020] [Accepted: 05/05/2021] [Indexed: 12/13/2022]
Abstract
We report the largest and most diverse genetic study of type 1 diabetes (T1D) to date (61,427 participants), yielding 78 genome-wide-significant (P < 5 × 10-8) regions, including 36 that are new. We define credible sets of T1D-associated variants and show that they are enriched in immune-cell accessible chromatin, particularly CD4+ effector T cells. Using chromatin-accessibility profiling of CD4+ T cells from 115 individuals, we map chromatin-accessibility quantitative trait loci and identify five regions where T1D risk variants co-localize with chromatin-accessibility quantitative trait loci. We highlight rs72928038 in BACH2 as a candidate causal T1D variant leading to decreased enhancer accessibility and BACH2 expression in T cells. Finally, we prioritize potential drug targets by integrating genetic evidence, functional genomic maps and immune protein-protein interactions, identifying 12 genes implicated in T1D that have been targeted in clinical trials for autoimmune diseases. These findings provide an expanded genomic landscape for T1D.
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Affiliation(s)
- Catherine C Robertson
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
- Department of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, VA, USA
| | - Jamie R J Inshaw
- JDRF/Wellcome Diabetes and Inflammation Laboratory, Wellcome Centre for Human Genetics, Nuffield Department of Medicine, NIHR Oxford Biomedical Research Centre, University of Oxford, Oxford, UK
| | - Suna Onengut-Gumuscu
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
- Department of Public Health Sciences, University of Virginia, Charlottesville, VA, USA
| | - Wei-Min Chen
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
- Department of Public Health Sciences, University of Virginia, Charlottesville, VA, USA
| | - David Flores Santa Cruz
- JDRF/Wellcome Diabetes and Inflammation Laboratory, Wellcome Centre for Human Genetics, Nuffield Department of Medicine, NIHR Oxford Biomedical Research Centre, University of Oxford, Oxford, UK
| | - Hanzhi Yang
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | - Antony J Cutler
- JDRF/Wellcome Diabetes and Inflammation Laboratory, Wellcome Centre for Human Genetics, Nuffield Department of Medicine, NIHR Oxford Biomedical Research Centre, University of Oxford, Oxford, UK
| | - Daniel J M Crouch
- JDRF/Wellcome Diabetes and Inflammation Laboratory, Wellcome Centre for Human Genetics, Nuffield Department of Medicine, NIHR Oxford Biomedical Research Centre, University of Oxford, Oxford, UK
| | - Emily Farber
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | - S Louis Bridges
- Division of Rheumatology, Department of Medicine, Hospital for Special Surgery, New York, NY, USA
- Division of Rheumatology, Department of Medicine, Weill Cornell Medical College, New York, NY, USA
| | - Jeffrey C Edberg
- Division of Clinical Immunology and Rheumatology, Department of Medicine, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Robert P Kimberly
- Division of Clinical Immunology and Rheumatology, Department of Medicine, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Jane H Buckner
- Center for Translational Immunology, Benaroya Research Institute, Seattle, WA, USA
| | - Panos Deloukas
- Clinical Pharmacology, William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
- Princess Al-Jawhara Al-Brahim Centre of Excellence in Research of Hereditary Disorders (PACER-HD), King Abdulaziz University, Jeddah, Saudi Arabia
| | - Jasmin Divers
- Division of Health Services Research, Department of Foundations of Medicine, New York University Long Island School of Medicine, Mineola, NY, USA
| | - Dana Dabelea
- Colorado School of Public Health and Lifecourse Epidemiology of Adiposity and Diabetes (LEAD) Center, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Jean M Lawrence
- Department of Research and Evaluation, Kaiser Permanente Southern California, Pasadena, CA, USA
| | - Santica Marcovina
- Northwest Lipid Metabolism and Diabetes Research Laboratories, University of Washington, Seattle, WA, USA
- Medpace Reference Laboratories, Cincinnati, OH, USA
| | - Amy S Shah
- Cincinnati Children's Hospital Medical Center and the University of Cincinnati, Cincinnati, OH, USA
| | - Carla J Greenbaum
- Center for Interventional Immunology, Benaroya Research Institute, Seattle, WA, USA
- Diabetes Program, Benaroya Research Institute, Seattle, WA, USA
| | - Mark A Atkinson
- Department of Pathology, Immunology, and Laboratory Medicine, University of Florida, Gainesville, FL, USA
| | - Peter K Gregersen
- Robert S. Boas Center for Genomics and Human Genetics, Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY, USA
| | - Jorge R Oksenberg
- Department of Neurology and Weill Institute for Neurosciences, University of California at San Francisco, San Francisco, CA, USA
| | - Flemming Pociot
- Department of Pediatrics, Herlev University Hospital, Copenhagen, Denmark
- Institute of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Type 1 Diabetes Biology, Department of Clinical Research, Steno Diabetes Center Copenhagen, Gentofte, Denmark
| | - Marian J Rewers
- Barbara Davis Center for Diabetes, School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Andrea K Steck
- Barbara Davis Center for Diabetes, School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - David B Dunger
- Department of Paediatrics, University of Cambridge, Cambridge, UK
- Wellcome Trust Medical Research Council Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - Linda S Wicker
- JDRF/Wellcome Diabetes and Inflammation Laboratory, Wellcome Centre for Human Genetics, Nuffield Department of Medicine, NIHR Oxford Biomedical Research Centre, University of Oxford, Oxford, UK
| | - Patrick Concannon
- Department of Pathology, Immunology, and Laboratory Medicine, University of Florida, Gainesville, FL, USA
- Genetics Institute, University of Florida, Gainesville, FL, USA
| | - John A Todd
- JDRF/Wellcome Diabetes and Inflammation Laboratory, Wellcome Centre for Human Genetics, Nuffield Department of Medicine, NIHR Oxford Biomedical Research Centre, University of Oxford, Oxford, UK.
| | - Stephen S Rich
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
- Department of Public Health Sciences, University of Virginia, Charlottesville, VA, USA
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Inshaw JRJ, Sidore C, Cucca F, Stefana MI, Crouch DJM, McCarthy MI, Mahajan A, Todd JA. Analysis of overlapping genetic association in type 1 and type 2 diabetes. Diabetologia 2021; 64:1342-1347. [PMID: 33830302 PMCID: PMC8099827 DOI: 10.1007/s00125-021-05428-0] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/18/2020] [Accepted: 01/08/2021] [Indexed: 12/20/2022]
Abstract
AIMS/HYPOTHESIS Given the potential shared aetiology between type 1 and type 2 diabetes, we aimed to identify any genetic regions associated with both diseases. For associations where there is a shared signal and the allele that increases risk to one disease also increases risk to the other, inference about shared aetiology could be made, with the potential to develop therapeutic strategies to treat or prevent both diseases simultaneously. Alternatively, if a genetic signal co-localises with divergent effect directions, it could provide valuable biological insight into how the association affects the two diseases differently. METHODS Using publicly available type 2 diabetes summary statistics from a genome-wide association study (GWAS) meta-analysis of European ancestry individuals (74,124 cases and 824,006 controls) and type 1 diabetes GWAS summary statistics from a meta-analysis of studies on individuals from the UK and Sardinia (7467 cases and 10,218 controls), we identified all regions of 0.5 Mb that contained variants associated with both diseases (false discovery rate <0.01). In each region, we performed forward stepwise logistic regression to identify independent association signals, then examined co-localisation of each type 1 diabetes signal with each type 2 diabetes signal using coloc. Any association with a co-localisation posterior probability of ≥0.9 was considered a genuine shared association with both diseases. RESULTS Of the 81 association signals from 42 genetic regions that showed association with both type 1 and type 2 diabetes, four association signals co-localised between both diseases (posterior probability ≥0.9): (1) chromosome 16q23.1, near CTRB1/BCAR1, which has been previously identified; (2) chromosome 11p15.5, near the INS gene; (3) chromosome 4p16.3, near TMEM129 and (4) chromosome 1p31.3, near PGM1. In each of these regions, the effect of genetic variants on type 1 diabetes was in the opposite direction to the effect on type 2 diabetes. Use of additional datasets also supported the previously identified co-localisation on chromosome 9p24.2, near the GLIS3 gene, in this case with a concordant direction of effect. CONCLUSIONS/INTERPRETATION Four of five association signals that co-localise between type 1 diabetes and type 2 diabetes are in opposite directions, suggesting a complex genetic relationship between the two diseases.
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Affiliation(s)
- Jamie R J Inshaw
- JDRF/Wellcome Diabetes and Inflammation Laboratory, Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK.
| | - Carlo Sidore
- Institute for Research in Genetics and Biomedicine (IRGB), Cagliari, Sardinia, Italy
| | - Francesco Cucca
- Institute for Research in Genetics and Biomedicine (IRGB), Cagliari, Sardinia, Italy
| | - M Irina Stefana
- JDRF/Wellcome Diabetes and Inflammation Laboratory, Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Daniel J M Crouch
- JDRF/Wellcome Diabetes and Inflammation Laboratory, Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Mark I McCarthy
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK
- Genentech, South San Francisco, CA, USA
| | - Anubha Mahajan
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK
- Genentech, South San Francisco, CA, USA
| | - John A Todd
- JDRF/Wellcome Diabetes and Inflammation Laboratory, Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK.
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4
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Bodmer WF, Crouch DJM. Somatic selection of poorly differentiating variant stem cell clones could be a key to human ageing. J Theor Biol 2020; 489:110153. [PMID: 31935413 DOI: 10.1016/j.jtbi.2020.110153] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2019] [Revised: 12/28/2019] [Accepted: 01/04/2020] [Indexed: 10/25/2022]
Abstract
Any replicating system in which heritable variants with differing replicative potentials can arise is subject to a Darwinian evolutionary process. The continually replicating adult tissue stem cells that control the integrity of many tissues of long-lived, multicellular, complex vertebrate organisms, including humans, constitute such a replicating system. Our suggestion is that somatic selection for mutations (or stable epigenetic changes) that cause an increased rate of adult tissue stem cell proliferation, and their long-term persistence, at the expense of normal differentiation, is a major key to the ageing process. Once an organism has passed the reproductive age, there is no longer any significant counterselection at the organismal level to this inevitable cellular level Darwinian process.
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Affiliation(s)
- Walter F Bodmer
- Department of Oncology, Cancer and Immunogenetics Laboratory, Weatherall Institute of Molecular Medicine, John Radcliffe Hospital, University of Oxford, Oxford, United Kingdom.
| | - Daniel J M Crouch
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Wellcome Centre for Human Genetics, Old Road Campus, University of Oxford, Oxford, United Kingdom.
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5
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Inshaw JRJ, Cutler AJ, Crouch DJM, Wicker LS, Todd JA. Genetic Variants Predisposing Most Strongly to Type 1 Diabetes Diagnosed Under Age 7 Years Lie Near Candidate Genes That Function in the Immune System and in Pancreatic β-Cells. Diabetes Care 2020; 43:169-177. [PMID: 31558544 PMCID: PMC6925581 DOI: 10.2337/dc19-0803] [Citation(s) in RCA: 44] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/23/2019] [Accepted: 08/10/2019] [Indexed: 02/03/2023]
Abstract
OBJECTIVE Immunohistological analyses of pancreata from patients with type 1 diabetes suggest distinct autoimmune islet β-cell pathology between those diagnosed at <7 years (<7 group) and those diagnosed at age ≥13 years (≥13 group), with both B- and T-lymphocyte islet inflammation common in children in the <7 group, whereas B cells are rare in the ≥13 group. Based on these observations, we sought to identify differences in genetic susceptibility between these prespecified age-at-diagnosis groups to inform on the etiology of the most aggressive form of type 1 diabetes that initiates in the first years of life. RESEARCH DESIGN AND METHODS Using multinomial logistic regression models, we tested if known type 1 diabetes loci (17 within the HLA and 55 non-HLA loci) had significantly stronger effect sizes in the <7 group compared with the ≥13 group, using genotype data from 27,071 individuals (18,485 control subjects and 3,121 case subjects diagnosed at <7 years, 3,757 at 7-13 years, and 1,708 at ≥13 years). RESULTS Six HLA haplotypes/classical alleles and six non-HLA regions, one of which functions specifically in β-cells (GLIS3) and the other five likely affecting key T-cell (IL2RA, IL10, IKZF3, and THEMIS), thymus (THEMIS), and B-cell development/functions (IKZF3 and IL10) or in both immune and β-cells (CTSH), showed evidence for stronger effects in the <7 group. CONCLUSIONS A subset of type 1 diabetes-associated variants are more prevalent in children diagnosed under the age of 7 years and are near candidate genes that act in both pancreatic β- and immune cells.
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Affiliation(s)
- Jamie R J Inshaw
- JDRF/Wellcome Diabetes and Inflammation Laboratory, Wellcome Centre for Human Genetics, University of Oxford, Oxford, U.K.
| | - Antony J Cutler
- JDRF/Wellcome Diabetes and Inflammation Laboratory, Wellcome Centre for Human Genetics, University of Oxford, Oxford, U.K
| | - Daniel J M Crouch
- JDRF/Wellcome Diabetes and Inflammation Laboratory, Wellcome Centre for Human Genetics, University of Oxford, Oxford, U.K
| | - Linda S Wicker
- JDRF/Wellcome Diabetes and Inflammation Laboratory, Wellcome Centre for Human Genetics, University of Oxford, Oxford, U.K
| | - John A Todd
- JDRF/Wellcome Diabetes and Inflammation Laboratory, Wellcome Centre for Human Genetics, University of Oxford, Oxford, U.K.
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Ferreira RC, Castro Dopico X, Oliveira JJ, Rainbow DB, Yang JH, Trzupek D, Todd SA, McNeill M, Steri M, Orrù V, Fiorillo E, Crouch DJM, Pekalski ML, Cucca F, Tree TI, Vyse TJ, Wicker LS, Todd JA. Chronic Immune Activation in Systemic Lupus Erythematosus and the Autoimmune PTPN22 Trp 620 Risk Allele Drive the Expansion of FOXP3 + Regulatory T Cells and PD-1 Expression. Front Immunol 2019; 10:2606. [PMID: 31781109 PMCID: PMC6857542 DOI: 10.3389/fimmu.2019.02606] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2019] [Accepted: 10/21/2019] [Indexed: 02/01/2023] Open
Abstract
In systemic lupus erythematosus (SLE), perturbed immunoregulation underpins a pathogenic imbalance between regulatory and effector CD4+ T-cell activity. However, to date, the characterization of the CD4+ regulatory T cell (Treg) compartment in SLE has yielded conflicting results. Here we show that patients have an increased frequency of CD4+FOXP3+ cells in circulation owing to a specific expansion of thymically-derived FOXP3+HELIOS+ Tregs with a demethylated FOXP3 Treg-specific demethylated region. We found that the Treg expansion was strongly associated with markers of recent immune activation, including PD-1, plasma concentrations of IL-2 and the type I interferon biomarker soluble SIGLEC-1. Since the expression of the negative T-cell signaling molecule PTPN22 is increased and a marker of poor prognosis in SLE, we tested the influence of its missense risk allele Trp620 (rs2476601C>T) on Treg frequency. Trp620 was reproducibly associated with increased frequencies of thymically-derived Tregs in blood, and increased PD-1 expression on both Tregs and effector T cells (Teffs). Our results support the hypothesis that FOXP3+ Tregs are increased in SLE patients as a consequence of a compensatory mechanism in an attempt to regulate pathogenic autoreactive Teff activity. We suggest that restoration of IL-2-mediated homeostatic regulation of FOXP3+ Tregs by IL-2 administration could prevent disease flares rather than treating at the height of a disease flare. Moreover, stimulation of PD-1 with specific agonists, perhaps in combination with low-dose IL-2, could be an effective therapeutic strategy in autoimmune disease and in other immune disorders.
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Affiliation(s)
- Ricardo C Ferreira
- JDRF/Wellcome Diabetes and Inflammation Laboratory, Nuffield Department of Medicine, Wellcome Centre for Human Genetics, NIHR Oxford Biomedical Research Centre, University of Oxford, Oxford, United Kingdom
| | - Xaquin Castro Dopico
- Cambridge Institute for Medical Research, University of Cambridge, Cambridge, United Kingdom
| | - João J Oliveira
- Cambridge Institute for Medical Research, University of Cambridge, Cambridge, United Kingdom
| | - Daniel B Rainbow
- JDRF/Wellcome Diabetes and Inflammation Laboratory, Nuffield Department of Medicine, Wellcome Centre for Human Genetics, NIHR Oxford Biomedical Research Centre, University of Oxford, Oxford, United Kingdom
| | - Jennie H Yang
- Department of Immunobiology, NIHR Biomedical Research Centre, King's College London, London, United Kingdom
| | - Dominik Trzupek
- JDRF/Wellcome Diabetes and Inflammation Laboratory, Nuffield Department of Medicine, Wellcome Centre for Human Genetics, NIHR Oxford Biomedical Research Centre, University of Oxford, Oxford, United Kingdom
| | - Sarah A Todd
- Cambridge Institute for Medical Research, University of Cambridge, Cambridge, United Kingdom
| | - Mhairi McNeill
- Cambridge Institute for Medical Research, University of Cambridge, Cambridge, United Kingdom
| | - Maristella Steri
- Istituto di Ricerca Genetica e Biomedica, Consiglio Nazionale delle Ricerche (CNR), Rome, Italy
| | - Valeria Orrù
- Istituto di Ricerca Genetica e Biomedica, Consiglio Nazionale delle Ricerche (CNR), Rome, Italy
| | - Edoardo Fiorillo
- Istituto di Ricerca Genetica e Biomedica, Consiglio Nazionale delle Ricerche (CNR), Rome, Italy
| | - Daniel J M Crouch
- JDRF/Wellcome Diabetes and Inflammation Laboratory, Nuffield Department of Medicine, Wellcome Centre for Human Genetics, NIHR Oxford Biomedical Research Centre, University of Oxford, Oxford, United Kingdom
| | - Marcin L Pekalski
- JDRF/Wellcome Diabetes and Inflammation Laboratory, Nuffield Department of Medicine, Wellcome Centre for Human Genetics, NIHR Oxford Biomedical Research Centre, University of Oxford, Oxford, United Kingdom
| | - Francesco Cucca
- Istituto di Ricerca Genetica e Biomedica, Consiglio Nazionale delle Ricerche (CNR), Rome, Italy.,Dipartimento di Scienze Biomediche, Università degli Studi di Sassari, Sassari, Italy
| | - Tim I Tree
- Department of Immunobiology, NIHR Biomedical Research Centre, King's College London, London, United Kingdom
| | - Tim J Vyse
- Department of Medical & Molecular Genetics, King's College London, Guy's Hospital, London, United Kingdom
| | - Linda S Wicker
- JDRF/Wellcome Diabetes and Inflammation Laboratory, Nuffield Department of Medicine, Wellcome Centre for Human Genetics, NIHR Oxford Biomedical Research Centre, University of Oxford, Oxford, United Kingdom
| | - John A Todd
- JDRF/Wellcome Diabetes and Inflammation Laboratory, Nuffield Department of Medicine, Wellcome Centre for Human Genetics, NIHR Oxford Biomedical Research Centre, University of Oxford, Oxford, United Kingdom
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7
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Crouch DJM, Winney B, Koppen WP, Christmas WJ, Hutnik K, Day T, Meena D, Boumertit A, Hysi P, Nessa A, Spector TD, Kittler J, Bodmer WF. Genetics of the human face: Identification of large-effect single gene variants. Proc Natl Acad Sci U S A 2018; 115:E676-E685. [PMID: 29301965 PMCID: PMC5789906 DOI: 10.1073/pnas.1708207114] [Citation(s) in RCA: 41] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
To discover specific variants with relatively large effects on the human face, we have devised an approach to identifying facial features with high heritability. This is based on using twin data to estimate the additive genetic value of each point on a face, as provided by a 3D camera system. In addition, we have used the ethnic difference between East Asian and European faces as a further source of face genetic variation. We use principal components (PCs) analysis to provide a fine definition of the surface features of human faces around the eyes and of the profile, and chose upper and lower 10% extremes of the most heritable PCs for looking for genetic associations. Using this strategy for the analysis of 3D images of 1,832 unique volunteers from the well-characterized People of the British Isles study and 1,567 unique twin images from the TwinsUK cohort, together with genetic data for 500,000 SNPs, we have identified three specific genetic variants with notable effects on facial profiles and eyes.
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Affiliation(s)
- Daniel J M Crouch
- Cancer and Immunogenetics Laboratory, Weatherall Institute of Molecular Medicine, University of Oxford, Oxford OX3 9DS, United Kingdom
- Department of Oncology, University of Oxford, Oxford OX3 7DQ, United Kingdom
| | - Bruce Winney
- Cancer and Immunogenetics Laboratory, Weatherall Institute of Molecular Medicine, University of Oxford, Oxford OX3 9DS, United Kingdom
- Department of Oncology, University of Oxford, Oxford OX3 7DQ, United Kingdom
| | - Willem P Koppen
- Centre for Vision, Speech and Signal Processing, Department of Electronic Engineering, University of Surrey, Guildford GU2 7XH, United Kingdom
| | - William J Christmas
- Centre for Vision, Speech and Signal Processing, Department of Electronic Engineering, University of Surrey, Guildford GU2 7XH, United Kingdom
| | - Katarzyna Hutnik
- Cancer and Immunogenetics Laboratory, Weatherall Institute of Molecular Medicine, University of Oxford, Oxford OX3 9DS, United Kingdom
- Department of Oncology, University of Oxford, Oxford OX3 7DQ, United Kingdom
| | - Tammy Day
- Cancer and Immunogenetics Laboratory, Weatherall Institute of Molecular Medicine, University of Oxford, Oxford OX3 9DS, United Kingdom
- Department of Oncology, University of Oxford, Oxford OX3 7DQ, United Kingdom
| | - Devendra Meena
- Cancer and Immunogenetics Laboratory, Weatherall Institute of Molecular Medicine, University of Oxford, Oxford OX3 9DS, United Kingdom
- Department of Oncology, University of Oxford, Oxford OX3 7DQ, United Kingdom
| | - Abdelhamid Boumertit
- Cancer and Immunogenetics Laboratory, Weatherall Institute of Molecular Medicine, University of Oxford, Oxford OX3 9DS, United Kingdom
- Department of Oncology, University of Oxford, Oxford OX3 7DQ, United Kingdom
| | - Pirro Hysi
- TwinsUK, St. Thomas' Hospital, King's College London, London SE1 7EH, United Kingdom
| | - Ayrun Nessa
- TwinsUK, St. Thomas' Hospital, King's College London, London SE1 7EH, United Kingdom
| | - Tim D Spector
- TwinsUK, St. Thomas' Hospital, King's College London, London SE1 7EH, United Kingdom
| | - Josef Kittler
- Centre for Vision, Speech and Signal Processing, Department of Electronic Engineering, University of Surrey, Guildford GU2 7XH, United Kingdom
| | - Walter F Bodmer
- Cancer and Immunogenetics Laboratory, Weatherall Institute of Molecular Medicine, University of Oxford, Oxford OX3 9DS, United Kingdom;
- Department of Oncology, University of Oxford, Oxford OX3 7DQ, United Kingdom
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Crouch DJM. Statistical aspects of evolution under natural selection, with implications for the advantage of sexual reproduction. J Theor Biol 2017; 431:79-86. [PMID: 28779948 DOI: 10.1016/j.jtbi.2017.07.021] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2016] [Revised: 06/06/2017] [Accepted: 07/21/2017] [Indexed: 12/01/2022]
Abstract
The prevalence of sexual reproduction remains mysterious, as it poses clear evolutionary drawbacks compared to reproducing asexually. Several possible explanations exist, with one of the most likely being that finite population size causes linkage disequilibria to randomly generate and impede the progress of natural selection, and that these are eroded by recombination via sexual reproduction. Previous investigations have either analysed this phenomenon in detail for small numbers of loci, or performed population simulations for many loci. Here we present a quantitative genetic model for fitness, based on the Price Equation, in order to examine the theoretical consequences of randomly generated linkage disequilibria when there are many loci. In addition, most previous work has been concerned with the long-term consequences of deleterious linkage disequilibria for population fitness. The expected change in mean fitness between consecutive generations, a measure of short-term evolutionary success, is shown under random environmental influences to be related to the autocovariance in mean fitness between the generations, capturing the effects of stochastic forces such as genetic drift. Interaction between genetic drift and natural selection, due to randomly generated linkage disequilibria, is demonstrated to be one possible source of mean fitness autocovariance. This suggests a possible role for sexual reproduction in reducing the negative effects of genetic drift, thereby improving the short-term efficacy of natural selection.
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Abstract
The identification of ancestral admixture proportions for human DNA samples has recently had success in forensic cases. Current methods infer admixture proportions for the target sample, but not for their parents, which provides an additional layer of information that may aid certain forensic investigations. We describe new maximum likelihood methods (LEAPFrOG and LEAPFrOG Expectation Maximisation), for inferring both an individual's admixture proportions and the admixture proportions possessed by the unobserved parents, with respect to two or more source populations, using single-nucleotide polymorphism data typed only in the target individual. This is achieved by examining the increase in heterozygosity in the offspring of parents who are from different populations or who represent different mixtures from a number of source populations. We validated the methods via simulation; combining chromosomes from different Hapmap Phase III population samples to emulate first-generation admixture. Performance was strong for individuals with mixed African/European (YRI/CEU) ancestry, but poor for mixed Japanese/Chinese (JPT/CHB) ancestry, reflecting the difficulty in distinguishing closely related source populations. A total of 11 African-American trios were used to compare the parental admixture inferred from their own genotypes against that inferred purely from their offspring genotypes. We examined the performance of 34 ancestry informative markers from a multiplex kit for ancestry inference. Simulations showed that estimates were unreliable when parents had similar admixture, suggesting more markers are needed. Our results demonstrate that ancestral backgrounds of case samples and their parents are obtainable to aid in forensic investigations, provided that high-throughput methods are adopted by the forensic community.
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Affiliation(s)
- Daniel J M Crouch
- Department of Medical and Molecular Genetics, King's College London, London, UK
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