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Cutler AJ, Oliveira J, Ferreira RC, Challis B, Walker NM, Caddy S, Lu J, Stevens HE, Smyth DJ, Pekalski ML, Kennet J, Hunter KMD, Goodfellow I, Wicker LS, Todd JA, Waldron-Lynch F. Capturing the systemic immune signature of a norovirus infection: an n-of-1 case study within a clinical trial. Wellcome Open Res 2017; 2:28. [PMID: 28815218 PMCID: PMC5531165 DOI: 10.12688/wellcomeopenres.11300.3] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [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] [Accepted: 10/06/2017] [Indexed: 01/02/2023] Open
Abstract
Background: The infection of a participant with norovirus during the adaptive study of interleukin-2 dose on regulatory T cells in type 1 diabetes (DILT1D) allowed a detailed insight into the cellular and cytokine immune responses to this prevalent gastrointestinal pathogen. Methods:
Serial blood, serum and peripheral blood mononuclear cell (PBMC) samples were collected pre-, and post-development of the infection. To differentiate between the immune response to norovirus and to control for the administration of a single dose of aldesleukin (recombinant interleukin-2, rIL-2) alone, samples from five non-infected participants administered similar doses were analysed in parallel. Results: Norovirus infection was self-limited and resolved within 24 hours, with the subsequent development of anti-norovirus antibodies. Serum pro- and anti-inflammatory cytokine levels, including IL-10, peaked during the symptomatic period of infection, coincident with increased frequencies of monocytes and neutrophils. At the same time, the frequency of regulatory CD4
+ T cell (Treg), effector T cell (Teff) CD4
+ and CD8
+ subsets were dynamically reduced, rebounding to baseline levels or above at the next sampling point 24 hours later. NK cells and NKT cells transiently increased CD69 expression and classical monocytes expressed increased levels of CD40, HLA-DR and SIGLEC-1, biomarkers of an interferon response. We also observed activation and mobilisation of Teffs, where increased frequencies of CD69
+ and Ki-67
+ effector memory Teffs were followed by the emergence of memory CD8
+ Teff expressing the mucosal tissue homing markers CD103 and β7 integrin. Treg responses were coincident with the innate cell, Teff and cytokine response. Key Treg molecules FOXP3, CTLA-4, and CD25 were upregulated following infection, alongside an increase in frequency of Tregs with the capacity to home to tissues. Conclusions:
The results illustrate the innate, adaptive and counter-regulatory immune responses to norovirus infection. Low-dose IL-2 administration induces many of the Treg responses observed during infection.
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Affiliation(s)
- Antony J Cutler
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Wellcome Trust Center for Human Genetics, Nuffield Department of Medicine, National Institute for Health Research Oxford Biomedical Research Centre, University of Oxford, Oxford, OX3 7BN, UK.,JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, National Institute for Health Research Cambridge Biomedical Research Centre, Cambridge Institute for Medical Research, University of Cambridge, Cambridge Biomedical Campus,Cambridge, CB2 0XY, UK
| | - Joao Oliveira
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, National Institute for Health Research Cambridge Biomedical Research Centre, Cambridge Institute for Medical Research, University of Cambridge, Cambridge Biomedical Campus,Cambridge, CB2 0XY, UK
| | - Ricardo C Ferreira
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Wellcome Trust Center for Human Genetics, Nuffield Department of Medicine, National Institute for Health Research Oxford Biomedical Research Centre, University of Oxford, Oxford, OX3 7BN, UK.,JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, National Institute for Health Research Cambridge Biomedical Research Centre, Cambridge Institute for Medical Research, University of Cambridge, Cambridge Biomedical Campus,Cambridge, CB2 0XY, UK
| | - Ben Challis
- Wellcome Trust/MRC Institute of Metabolic Science, Department of Medicine, National Institute for Health Research Cambridge Biomedical Research Centre, University of Cambridge, Cambridge, CB2 0QQ, UK
| | - Neil M Walker
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, National Institute for Health Research Cambridge Biomedical Research Centre, Cambridge Institute for Medical Research, University of Cambridge, Cambridge Biomedical Campus,Cambridge, CB2 0XY, UK
| | - Sarah Caddy
- Division of Virology, Department of Pathology, University of Cambridge, Addenbrooke's Hospital, Cambridge, CB2 0QQ, UK
| | - Jia Lu
- Division of Virology, Department of Pathology, University of Cambridge, Addenbrooke's Hospital, Cambridge, CB2 0QQ, UK
| | - Helen E Stevens
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, National Institute for Health Research Cambridge Biomedical Research Centre, Cambridge Institute for Medical Research, University of Cambridge, Cambridge Biomedical Campus,Cambridge, CB2 0XY, UK
| | - Deborah J Smyth
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, National Institute for Health Research Cambridge Biomedical Research Centre, Cambridge Institute for Medical Research, University of Cambridge, Cambridge Biomedical Campus,Cambridge, CB2 0XY, UK
| | - Marcin L Pekalski
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Wellcome Trust Center for Human Genetics, Nuffield Department of Medicine, National Institute for Health Research Oxford Biomedical Research Centre, University of Oxford, Oxford, OX3 7BN, UK.,JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, National Institute for Health Research Cambridge Biomedical Research Centre, Cambridge Institute for Medical Research, University of Cambridge, Cambridge Biomedical Campus,Cambridge, CB2 0XY, UK
| | - Jane Kennet
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, National Institute for Health Research Cambridge Biomedical Research Centre, Cambridge Institute for Medical Research, University of Cambridge, Cambridge Biomedical Campus,Cambridge, CB2 0XY, UK
| | - Kara M D Hunter
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, National Institute for Health Research Cambridge Biomedical Research Centre, Cambridge Institute for Medical Research, University of Cambridge, Cambridge Biomedical Campus,Cambridge, CB2 0XY, UK
| | - Ian Goodfellow
- Division of Virology, Department of Pathology, University of Cambridge, Addenbrooke's Hospital, Cambridge, CB2 0QQ, UK
| | - Linda S Wicker
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Wellcome Trust Center for Human Genetics, Nuffield Department of Medicine, National Institute for Health Research Oxford Biomedical Research Centre, University of Oxford, Oxford, OX3 7BN, UK.,JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, National Institute for Health Research Cambridge Biomedical Research Centre, Cambridge Institute for Medical Research, University of Cambridge, Cambridge Biomedical Campus,Cambridge, CB2 0XY, UK
| | - John A Todd
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Wellcome Trust Center for Human Genetics, Nuffield Department of Medicine, National Institute for Health Research Oxford Biomedical Research Centre, University of Oxford, Oxford, OX3 7BN, UK.,JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, National Institute for Health Research Cambridge Biomedical Research Centre, Cambridge Institute for Medical Research, University of Cambridge, Cambridge Biomedical Campus,Cambridge, CB2 0XY, UK
| | - Frank Waldron-Lynch
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, National Institute for Health Research Cambridge Biomedical Research Centre, Cambridge Institute for Medical Research, University of Cambridge, Cambridge Biomedical Campus,Cambridge, CB2 0XY, UK.,Experimental Medicine and Immunotherapeutics, Department of Medicine, National Institute for Health Research Cambridge Biomedical Research Centre, University of Cambridge, Addenbrooke's Hospital, Cambridge, CB2 0QQ, UK.,National Institute for Health Research Cambridge Clinical Trials Unit, Cambridge University Hospitals NHS foundation Trust, Cambridge Biomedical Campus, University of Cambridge, Cambridge, CB2 0QQ, UK
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2
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Cutler AJ, Oliveira J, Ferreira RC, Challis B, Walker NM, Caddy S, Lu J, Stevens HE, Smyth DJ, Pekalski ML, Kennet J, Hunter KMD, Goodfellow I, Wicker LS, Todd JA, Waldron-Lynch F. Capturing the systemic immune signature of a norovirus infection: an n-of-1 case study within a clinical trial. Wellcome Open Res 2017. [PMID: 28815218 DOI: 10.12688/wellcomeopenres.11300.1] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022] Open
Abstract
BACKGROUND The infection of a participant with norovirus during the adaptive study of interleukin-2 dose on regulatory T cells in type 1 diabetes (DILT1D) allowed a detailed insight into the cellular and cytokine immune responses to this prevalent gastrointestinal pathogen. METHODS Serial blood, serum and peripheral blood mononuclear cell (PBMC) samples were collected pre-, and post-development of the infection. To differentiate between the immune response to norovirus and to control for the administration of a single dose of aldesleukin (recombinant interleukin-2, rIL-2) alone, samples from five non-infected participants administered similar doses were analysed in parallel. RESULTS Norovirus infection was self-limited and resolved within 24 hours, with the subsequent development of anti-norovirus antibodies. Serum pro- and anti-inflammatory cytokine levels, including IL-10, peaked during the symptomatic period of infection, coincident with increased frequencies of monocytes and neutrophils. At the same time, the frequency of regulatory CD4 + T cell (Treg), effector T cell (Teff) CD4 + and CD8 + subsets were dynamically reduced, rebounding to baseline levels or above at the next sampling point 24 hours later. NK cells and NKT cells transiently increased CD69 expression and classical monocytes expressed increased levels of CD40, HLA-DR and SIGLEC-1, biomarkers of an interferon response. We also observed activation and mobilisation of Teffs, where increased frequencies of CD69 + and Ki-67 + effector memory Teffs were followed by the emergence of memory CD8 + Teff expressing the mucosal tissue homing markers CD103 and β7 integrin. Treg responses were coincident with the innate cell, Teff and cytokine response. Key Treg molecules FOXP3, CTLA-4, and CD25 were upregulated following infection, alongside an increase in frequency of Tregs with the capacity to home to tissues. CONCLUSIONS The results illustrate the innate, adaptive and counter-regulatory immune responses to norovirus infection. Low-dose IL-2 administration induces many of the Treg responses observed during infection.
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Affiliation(s)
- Antony J Cutler
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Wellcome Trust Center for Human Genetics, Nuffield Department of Medicine, National Institute for Health Research Oxford Biomedical Research Centre, University of Oxford, Oxford, OX3 7BN, UK.,JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, National Institute for Health Research Cambridge Biomedical Research Centre, Cambridge Institute for Medical Research, University of Cambridge, Cambridge Biomedical Campus,Cambridge, CB2 0XY, UK
| | - Joao Oliveira
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, National Institute for Health Research Cambridge Biomedical Research Centre, Cambridge Institute for Medical Research, University of Cambridge, Cambridge Biomedical Campus,Cambridge, CB2 0XY, UK
| | - Ricardo C Ferreira
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Wellcome Trust Center for Human Genetics, Nuffield Department of Medicine, National Institute for Health Research Oxford Biomedical Research Centre, University of Oxford, Oxford, OX3 7BN, UK.,JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, National Institute for Health Research Cambridge Biomedical Research Centre, Cambridge Institute for Medical Research, University of Cambridge, Cambridge Biomedical Campus,Cambridge, CB2 0XY, UK
| | - Ben Challis
- Wellcome Trust/MRC Institute of Metabolic Science, Department of Medicine, National Institute for Health Research Cambridge Biomedical Research Centre, University of Cambridge, Cambridge, CB2 0QQ, UK
| | - Neil M Walker
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, National Institute for Health Research Cambridge Biomedical Research Centre, Cambridge Institute for Medical Research, University of Cambridge, Cambridge Biomedical Campus,Cambridge, CB2 0XY, UK
| | - Sarah Caddy
- Division of Virology, Department of Pathology, University of Cambridge, Addenbrooke's Hospital, Cambridge, CB2 0QQ, UK
| | - Jia Lu
- Division of Virology, Department of Pathology, University of Cambridge, Addenbrooke's Hospital, Cambridge, CB2 0QQ, UK
| | - Helen E Stevens
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, National Institute for Health Research Cambridge Biomedical Research Centre, Cambridge Institute for Medical Research, University of Cambridge, Cambridge Biomedical Campus,Cambridge, CB2 0XY, UK
| | - Deborah J Smyth
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, National Institute for Health Research Cambridge Biomedical Research Centre, Cambridge Institute for Medical Research, University of Cambridge, Cambridge Biomedical Campus,Cambridge, CB2 0XY, UK
| | - Marcin L Pekalski
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Wellcome Trust Center for Human Genetics, Nuffield Department of Medicine, National Institute for Health Research Oxford Biomedical Research Centre, University of Oxford, Oxford, OX3 7BN, UK.,JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, National Institute for Health Research Cambridge Biomedical Research Centre, Cambridge Institute for Medical Research, University of Cambridge, Cambridge Biomedical Campus,Cambridge, CB2 0XY, UK
| | - Jane Kennet
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, National Institute for Health Research Cambridge Biomedical Research Centre, Cambridge Institute for Medical Research, University of Cambridge, Cambridge Biomedical Campus,Cambridge, CB2 0XY, UK
| | - Kara M D Hunter
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, National Institute for Health Research Cambridge Biomedical Research Centre, Cambridge Institute for Medical Research, University of Cambridge, Cambridge Biomedical Campus,Cambridge, CB2 0XY, UK
| | - Ian Goodfellow
- Division of Virology, Department of Pathology, University of Cambridge, Addenbrooke's Hospital, Cambridge, CB2 0QQ, UK
| | - Linda S Wicker
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Wellcome Trust Center for Human Genetics, Nuffield Department of Medicine, National Institute for Health Research Oxford Biomedical Research Centre, University of Oxford, Oxford, OX3 7BN, UK.,JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, National Institute for Health Research Cambridge Biomedical Research Centre, Cambridge Institute for Medical Research, University of Cambridge, Cambridge Biomedical Campus,Cambridge, CB2 0XY, UK
| | - John A Todd
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Wellcome Trust Center for Human Genetics, Nuffield Department of Medicine, National Institute for Health Research Oxford Biomedical Research Centre, University of Oxford, Oxford, OX3 7BN, UK.,JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, National Institute for Health Research Cambridge Biomedical Research Centre, Cambridge Institute for Medical Research, University of Cambridge, Cambridge Biomedical Campus,Cambridge, CB2 0XY, UK
| | - Frank Waldron-Lynch
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, National Institute for Health Research Cambridge Biomedical Research Centre, Cambridge Institute for Medical Research, University of Cambridge, Cambridge Biomedical Campus,Cambridge, CB2 0XY, UK.,Experimental Medicine and Immunotherapeutics, Department of Medicine, National Institute for Health Research Cambridge Biomedical Research Centre, University of Cambridge, Addenbrooke's Hospital, Cambridge, CB2 0QQ, UK.,National Institute for Health Research Cambridge Clinical Trials Unit, Cambridge University Hospitals NHS foundation Trust, Cambridge Biomedical Campus, University of Cambridge, Cambridge, CB2 0QQ, UK
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3
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Pekalski ML, García AR, Ferreira RC, Rainbow DB, Smyth DJ, Mashar M, Brady J, Savinykh N, Dopico XC, Mahmood S, Duley S, Stevens HE, Walker NM, Cutler AJ, Waldron-Lynch F, Dunger DB, Shannon-Lowe C, Coles AJ, Jones JL, Wallace C, Todd JA, Wicker LS. Neonatal and adult recent thymic emigrants produce IL-8 and express complement receptors CR1 and CR2. JCI Insight 2017; 2:93739. [PMID: 28814669 PMCID: PMC5621870 DOI: 10.1172/jci.insight.93739] [Citation(s) in RCA: 39] [Impact Index Per Article: 5.6] [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: 03/01/2017] [Accepted: 07/18/2017] [Indexed: 12/21/2022] Open
Abstract
The maintenance of peripheral naive T lymphocytes in humans is dependent on their homeostatic division, not continuing emigration from the thymus, which undergoes involution with age. However, postthymic maintenance of naive T cells is still poorly understood. Previously we reported that recent thymic emigrants (RTEs) are contained in CD31+CD25− naive T cells as defined by their levels of signal joint T cell receptor rearrangement excision circles (sjTRECs). Here, by differential gene expression analysis followed by protein expression and functional studies, we define that the naive T cells having divided the least since thymic emigration express complement receptors (CR1 and CR2) known to bind complement C3b- and C3d-decorated microbial products and, following activation, produce IL-8 (CXCL8), a major chemoattractant for neutrophils in bacterial defense. We also observed an IL-8–producing memory T cell subpopulation coexpressing CR1 and CR2 and with a gene expression signature resembling that of RTEs. The functions of CR1 and CR2 on T cells remain to be determined, but we note that CR2 is the receptor for Epstein-Barr virus, which is a cause of T cell lymphomas and a candidate environmental factor in autoimmune disease. Complement receptors (CR1 and CR2) and IL-8 production identify T cells that have recently left the thymus.
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Affiliation(s)
- Marcin L Pekalski
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Wellcome Trust Centre for Human Genetics, Nuffield Department of Medicine, National Institute for Health Research (NIHR) Oxford Biomedical Research Centre, University of Oxford, Oxford, United Kingdom.,JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Wellcome Trust/MRC Building, Cambridge Institute for Medical Research, NIHR Cambridge Biomedical Research Centre, University of Cambridge, Cambridge, United Kingdom
| | - Arcadio Rubio García
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Wellcome Trust Centre for Human Genetics, Nuffield Department of Medicine, National Institute for Health Research (NIHR) Oxford Biomedical Research Centre, University of Oxford, Oxford, United Kingdom.,JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Wellcome Trust/MRC Building, Cambridge Institute for Medical Research, NIHR Cambridge Biomedical Research Centre, University of Cambridge, Cambridge, United Kingdom
| | - Ricardo C Ferreira
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Wellcome Trust Centre for Human Genetics, Nuffield Department of Medicine, National Institute for Health Research (NIHR) Oxford Biomedical Research Centre, University of Oxford, Oxford, United Kingdom.,JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Wellcome Trust/MRC Building, Cambridge Institute for Medical Research, NIHR Cambridge Biomedical Research Centre, University of Cambridge, Cambridge, United Kingdom
| | - Daniel B Rainbow
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Wellcome Trust Centre for Human Genetics, Nuffield Department of Medicine, National Institute for Health Research (NIHR) Oxford Biomedical Research Centre, University of Oxford, Oxford, United Kingdom.,JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Wellcome Trust/MRC Building, Cambridge Institute for Medical Research, NIHR Cambridge Biomedical Research Centre, University of Cambridge, Cambridge, United Kingdom
| | - Deborah J Smyth
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Wellcome Trust/MRC Building, Cambridge Institute for Medical Research, NIHR Cambridge Biomedical Research Centre, University of Cambridge, Cambridge, United Kingdom
| | - Meghavi Mashar
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Wellcome Trust/MRC Building, Cambridge Institute for Medical Research, NIHR Cambridge Biomedical Research Centre, University of Cambridge, Cambridge, United Kingdom
| | - Jane Brady
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Wellcome Trust/MRC Building, Cambridge Institute for Medical Research, NIHR Cambridge Biomedical Research Centre, University of Cambridge, Cambridge, United Kingdom
| | - Natalia Savinykh
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Wellcome Trust/MRC Building, Cambridge Institute for Medical Research, NIHR Cambridge Biomedical Research Centre, University of Cambridge, Cambridge, United Kingdom
| | - Xaquin Castro Dopico
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Wellcome Trust/MRC Building, Cambridge Institute for Medical Research, NIHR Cambridge Biomedical Research Centre, University of Cambridge, Cambridge, United Kingdom
| | - Sumiyya Mahmood
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Wellcome Trust/MRC Building, Cambridge Institute for Medical Research, NIHR Cambridge Biomedical Research Centre, University of Cambridge, Cambridge, United Kingdom
| | - Simon Duley
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Wellcome Trust/MRC Building, Cambridge Institute for Medical Research, NIHR Cambridge Biomedical Research Centre, University of Cambridge, Cambridge, United Kingdom
| | - Helen E Stevens
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Wellcome Trust/MRC Building, Cambridge Institute for Medical Research, NIHR Cambridge Biomedical Research Centre, University of Cambridge, Cambridge, United Kingdom
| | - Neil M Walker
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Wellcome Trust/MRC Building, Cambridge Institute for Medical Research, NIHR Cambridge Biomedical Research Centre, University of Cambridge, Cambridge, United Kingdom
| | - Antony J Cutler
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Wellcome Trust Centre for Human Genetics, Nuffield Department of Medicine, National Institute for Health Research (NIHR) Oxford Biomedical Research Centre, University of Oxford, Oxford, United Kingdom.,JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Wellcome Trust/MRC Building, Cambridge Institute for Medical Research, NIHR Cambridge Biomedical Research Centre, University of Cambridge, Cambridge, United Kingdom
| | - Frank Waldron-Lynch
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Wellcome Trust/MRC Building, Cambridge Institute for Medical Research, NIHR Cambridge Biomedical Research Centre, University of Cambridge, Cambridge, United Kingdom
| | - David B Dunger
- Department of Paediatrics, MRL Wellcome Trust-MRC Institute of Metabolic Science, NIHR Cambridge Comprehensive Biomedical Research Centre, University of Cambridge, Cambridge, United Kingdom
| | - Claire Shannon-Lowe
- Institute for Immunology and Immunotherapy and Centre for Human Virology, The University of Birmingham, Birmingham, United Kingdom
| | - Alasdair J Coles
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, United Kingdom
| | - Joanne L Jones
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, United Kingdom
| | - Chris Wallace
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Wellcome Trust/MRC Building, Cambridge Institute for Medical Research, NIHR Cambridge Biomedical Research Centre, University of Cambridge, Cambridge, United Kingdom.,Department of Medicine, University of Cambridge, Addenbrooke's Hospital, Cambridge, United Kingdom, and MRC Biostatistics Unit, Cambridge Institute of Public Health, Cambridge Biomedical Campus, Cambridge, United Kingdom
| | - John A Todd
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Wellcome Trust Centre for Human Genetics, Nuffield Department of Medicine, National Institute for Health Research (NIHR) Oxford Biomedical Research Centre, University of Oxford, Oxford, United Kingdom.,JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Wellcome Trust/MRC Building, Cambridge Institute for Medical Research, NIHR Cambridge Biomedical Research Centre, University of Cambridge, Cambridge, United Kingdom
| | - Linda S Wicker
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Wellcome Trust Centre for Human Genetics, Nuffield Department of Medicine, National Institute for Health Research (NIHR) Oxford Biomedical Research Centre, University of Oxford, Oxford, United Kingdom.,JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Wellcome Trust/MRC Building, Cambridge Institute for Medical Research, NIHR Cambridge Biomedical Research Centre, University of Cambridge, Cambridge, United Kingdom
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4
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Cutler AJ, Oliveira J, Ferreira RC, Challis B, Walker NM, Caddy S, Lu J, Stevens HE, Smyth DJ, Pekalski ML, Kennet J, Hunter KM, Goodfellow I, Wicker LS, Todd JA, Waldron-Lynch F. Capturing the systemic immune signature of a norovirus infection: an n-of-1 case study within a clinical trial. Wellcome Open Res 2017. [DOI: 10.12688/wellcomeopenres.11300.2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
Background: The infection of a participant with norovirus during the adaptive study of interleukin-2 dose on regulatory T cells in type 1 diabetes (DILT1D) allowed a detailed insight into the cellular and cytokine immune responses to this prevalent gastrointestinal pathogen. Methods: Serial blood, serum and peripheral blood mononuclear cell (PBMC) samples were collected pre-, and post-development of the infection. To differentiate between the immune response to norovirus and to control for the administration of a single dose of aldesleukin (recombinant interleukin-2, rIL-2) alone, samples from five non-infected participants administered similar doses were analysed in parallel. Results: Norovirus infection was self-limited and resolved within 24 hours, with the subsequent development of anti-norovirus antibodies. Serum pro- and anti-inflammatory cytokine levels, including IL-10, peaked during the symptomatic period of infection, coincident with increased frequencies of monocytes and neutrophils. At the same time, the frequency of regulatory CD4+ T cell (Treg), effector T cell (Teff) CD4+ and CD8+ subsets were dynamically reduced, rebounding to baseline levels or above at the next sampling point 24 hours later. NK cells and NKT cells transiently increased CD69 expression and classical monocytes expressed increased levels of CD40, HLA-DR and SIGLEC-1, biomarkers of an interferon response. We also observed activation and mobilisation of Teffs, where increased frequencies of CD69+ and Ki-67+ effector memory Teffs were followed by the emergence of memory CD8+ Teff expressing the mucosal tissue homing markers CD103 and β7 integrin. Treg responses were coincident with the innate cell, Teff and cytokine response. Key Treg molecules FOXP3, CTLA-4, and CD25 were upregulated following infection, alongside an increase in frequency of Tregs with the capacity to home to tissues. Conclusions: The results illustrate the innate, adaptive and counter-regulatory immune responses to norovirus infection. Low-dose IL-2 administration induces many of the Treg responses observed during infection.
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5
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Todd JA, Evangelou M, Cutler AJ, Pekalski ML, Walker NM, Stevens HE, Porter L, Smyth DJ, Rainbow DB, Ferreira RC, Esposito L, Hunter KMD, Loudon K, Irons K, Yang JH, Bell CJM, Schuilenburg H, Heywood J, Challis B, Neupane S, Clarke P, Coleman G, Dawson S, Goymer D, Anselmiova K, Kennet J, Brown J, Caddy SL, Lu J, Greatorex J, Goodfellow I, Wallace C, Tree TI, Evans M, Mander AP, Bond S, Wicker LS, Waldron-Lynch F. Regulatory T Cell Responses in Participants with Type 1 Diabetes after a Single Dose of Interleukin-2: A Non-Randomised, Open Label, Adaptive Dose-Finding Trial. PLoS Med 2016; 13:e1002139. [PMID: 27727279 PMCID: PMC5058548 DOI: 10.1371/journal.pmed.1002139] [Citation(s) in RCA: 97] [Impact Index Per Article: 12.1] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/18/2016] [Accepted: 08/25/2016] [Indexed: 12/20/2022] Open
Abstract
BACKGROUND Interleukin-2 (IL-2) has an essential role in the expansion and function of CD4+ regulatory T cells (Tregs). Tregs reduce tissue damage by limiting the immune response following infection and regulate autoreactive CD4+ effector T cells (Teffs) to prevent autoimmune diseases, such as type 1 diabetes (T1D). Genetic susceptibility to T1D causes alterations in the IL-2 pathway, a finding that supports Tregs as a cellular therapeutic target. Aldesleukin (Proleukin; recombinant human IL-2), which is administered at high doses to activate the immune system in cancer immunotherapy, is now being repositioned to treat inflammatory and autoimmune disorders at lower doses by targeting Tregs. METHODS AND FINDINGS To define the aldesleukin dose response for Tregs and to find doses that increase Tregs physiologically for treatment of T1D, a statistical and systematic approach was taken by analysing the pharmacokinetics and pharmacodynamics of single doses of subcutaneous aldesleukin in the Adaptive Study of IL-2 Dose on Regulatory T Cells in Type 1 Diabetes (DILT1D), a single centre, non-randomised, open label, adaptive dose-finding trial with 40 adult participants with recently diagnosed T1D. The primary endpoint was the maximum percentage increase in Tregs (defined as CD3+CD4+CD25highCD127low) from the baseline frequency in each participant measured over the 7 d following treatment. There was an initial learning phase with five pairs of participants, each pair receiving one of five pre-assigned single doses from 0.04 × 106 to 1.5 × 106 IU/m2, in order to model the dose-response curve. Results from each participant were then incorporated into interim statistical modelling to target the two doses most likely to induce 10% and 20% increases in Treg frequencies. Primary analysis of the evaluable population (n = 39) found that the optimal doses of aldesleukin to induce 10% and 20% increases in Tregs were 0.101 × 106 IU/m2 (standard error [SE] = 0.078, 95% CI = -0.052, 0.254) and 0.497 × 106 IU/m2 (SE = 0.092, 95% CI = 0.316, 0.678), respectively. On analysis of secondary outcomes, using a highly sensitive IL-2 assay, the observed plasma concentrations of the drug at 90 min exceeded the hypothetical Treg-specific therapeutic window determined in vitro (0.015-0.24 IU/ml), even at the lowest doses (0.040 × 106 and 0.045 × 106 IU/m2) administered. A rapid decrease in Treg frequency in the circulation was observed at 90 min and at day 1, which was dose dependent (mean decrease 11.6%, SE = 2.3%, range 10.0%-48.2%, n = 37), rebounding at day 2 and increasing to frequencies above baseline over 7 d. Teffs, natural killer cells, and eosinophils also responded, with their frequencies rapidly and dose-dependently decreased in the blood, then returning to, or exceeding, pretreatment levels. Furthermore, there was a dose-dependent down modulation of one of the two signalling subunits of the IL-2 receptor, the β chain (CD122) (mean decrease = 58.0%, SE = 2.8%, range 9.8%-85.5%, n = 33), on Tregs and a reduction in their sensitivity to aldesleukin at 90 min and day 1 and 2 post-treatment. Due to blood volume requirements as well as ethical and practical considerations, the study was limited to adults and to analysis of peripheral blood only. CONCLUSIONS The DILT1D trial results, most notably the early altered trafficking and desensitisation of Tregs induced by a single ultra-low dose of aldesleukin that resolves within 2-3 d, inform the design of the next trial to determine a repeat dosing regimen aimed at establishing a steady-state Treg frequency increase of 20%-50%, with the eventual goal of preventing T1D. TRIAL REGISTRATION ISRCTN Registry ISRCTN27852285; ClinicalTrials.gov NCT01827735.
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Affiliation(s)
- John A. Todd
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, Cambridge Institute for Medical Research, National Institute for Health Research Cambridge Biomedical Research Centre, Cambridge Biomedical Campus, University of Cambridge, Cambridge, United Kingdom
- * E-mail: (FWL); (JAT)
| | - Marina Evangelou
- Department of Mathematics, Imperial College London, London, United Kingdom
| | - Antony J. Cutler
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, Cambridge Institute for Medical Research, National Institute for Health Research Cambridge Biomedical Research Centre, Cambridge Biomedical Campus, University of Cambridge, Cambridge, United Kingdom
| | - Marcin L. Pekalski
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, Cambridge Institute for Medical Research, National Institute for Health Research Cambridge Biomedical Research Centre, Cambridge Biomedical Campus, University of Cambridge, Cambridge, United Kingdom
| | - Neil M. Walker
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, Cambridge Institute for Medical Research, National Institute for Health Research Cambridge Biomedical Research Centre, Cambridge Biomedical Campus, University of Cambridge, Cambridge, United Kingdom
| | - Helen E. Stevens
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, Cambridge Institute for Medical Research, National Institute for Health Research Cambridge Biomedical Research Centre, Cambridge Biomedical Campus, University of Cambridge, Cambridge, United Kingdom
| | - Linsey Porter
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, Cambridge Institute for Medical Research, National Institute for Health Research Cambridge Biomedical Research Centre, Cambridge Biomedical Campus, University of Cambridge, Cambridge, United Kingdom
| | - Deborah J. Smyth
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, Cambridge Institute for Medical Research, National Institute for Health Research Cambridge Biomedical Research Centre, Cambridge Biomedical Campus, University of Cambridge, Cambridge, United Kingdom
| | - Daniel B. Rainbow
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, Cambridge Institute for Medical Research, National Institute for Health Research Cambridge Biomedical Research Centre, Cambridge Biomedical Campus, University of Cambridge, Cambridge, United Kingdom
| | - Ricardo C. Ferreira
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, Cambridge Institute for Medical Research, National Institute for Health Research Cambridge Biomedical Research Centre, Cambridge Biomedical Campus, University of Cambridge, Cambridge, United Kingdom
| | - Laura Esposito
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, Cambridge Institute for Medical Research, National Institute for Health Research Cambridge Biomedical Research Centre, Cambridge Biomedical Campus, University of Cambridge, Cambridge, United Kingdom
| | - Kara M. D. Hunter
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, Cambridge Institute for Medical Research, National Institute for Health Research Cambridge Biomedical Research Centre, Cambridge Biomedical Campus, University of Cambridge, Cambridge, United Kingdom
| | - Kevin Loudon
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, Cambridge Institute for Medical Research, National Institute for Health Research Cambridge Biomedical Research Centre, Cambridge Biomedical Campus, University of Cambridge, Cambridge, United Kingdom
| | - Kathryn Irons
- National Institute for Health Research Cambridge Clinical Trials Unit, Cambridge University Hospitals NHS Foundation Trust, Cambridge Biomedical Campus, Cambridge, United Kingdom
| | - Jennie H. Yang
- Department of Immunobiology, Faculty of Life Sciences & Medicine, King’s College London, National Institute of Health Research Biomedical Research Centre, Guy’s and St Thomas’ National Health Service Foundation Trust and King’s College London, London, United Kingdom
| | - Charles J. M. Bell
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, Cambridge Institute for Medical Research, National Institute for Health Research Cambridge Biomedical Research Centre, Cambridge Biomedical Campus, University of Cambridge, Cambridge, United Kingdom
| | - Helen Schuilenburg
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, Cambridge Institute for Medical Research, National Institute for Health Research Cambridge Biomedical Research Centre, Cambridge Biomedical Campus, University of Cambridge, Cambridge, United Kingdom
| | - James Heywood
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, Cambridge Institute for Medical Research, National Institute for Health Research Cambridge Biomedical Research Centre, Cambridge Biomedical Campus, University of Cambridge, Cambridge, United Kingdom
| | - Ben Challis
- Wellcome Trust/MRC Institute of Metabolic Science, National Institute for Health Research Cambridge Biomedical Research Centre, Cambridge Biomedical Campus, Cambridge, United Kingdom
| | - Sankalpa Neupane
- Wellcome Trust/MRC Institute of Metabolic Science, National Institute for Health Research Cambridge Biomedical Research Centre, Cambridge Biomedical Campus, Cambridge, United Kingdom
| | - Pamela Clarke
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, Cambridge Institute for Medical Research, National Institute for Health Research Cambridge Biomedical Research Centre, Cambridge Biomedical Campus, University of Cambridge, Cambridge, United Kingdom
| | - Gillian Coleman
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, Cambridge Institute for Medical Research, National Institute for Health Research Cambridge Biomedical Research Centre, Cambridge Biomedical Campus, University of Cambridge, Cambridge, United Kingdom
| | - Sarah Dawson
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, Cambridge Institute for Medical Research, National Institute for Health Research Cambridge Biomedical Research Centre, Cambridge Biomedical Campus, University of Cambridge, Cambridge, United Kingdom
| | - Donna Goymer
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, Cambridge Institute for Medical Research, National Institute for Health Research Cambridge Biomedical Research Centre, Cambridge Biomedical Campus, University of Cambridge, Cambridge, United Kingdom
| | - Katerina Anselmiova
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, Cambridge Institute for Medical Research, National Institute for Health Research Cambridge Biomedical Research Centre, Cambridge Biomedical Campus, University of Cambridge, Cambridge, United Kingdom
| | - Jane Kennet
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, Cambridge Institute for Medical Research, National Institute for Health Research Cambridge Biomedical Research Centre, Cambridge Biomedical Campus, University of Cambridge, Cambridge, United Kingdom
| | - Judy Brown
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, Cambridge Institute for Medical Research, National Institute for Health Research Cambridge Biomedical Research Centre, Cambridge Biomedical Campus, University of Cambridge, Cambridge, United Kingdom
| | - Sarah L. Caddy
- Division of Virology, Department of Pathology, Addenbrooke’s Hospital, Cambridge Biomedical Campus, University of Cambridge, Cambridge, United Kingdom
| | - Jia Lu
- Division of Virology, Department of Pathology, Addenbrooke’s Hospital, Cambridge Biomedical Campus, University of Cambridge, Cambridge, United Kingdom
| | - Jane Greatorex
- Public Health England, Clinical Microbiology and Public Health Laboratory, Addenbrooke’s Hospital, Cambridge University Hospitals NHS Foundation Trust, Cambridge Biomedical Campus, Cambridge, United Kingdom
| | - Ian Goodfellow
- Division of Virology, Department of Pathology, Addenbrooke’s Hospital, Cambridge Biomedical Campus, University of Cambridge, Cambridge, United Kingdom
| | - Chris Wallace
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, Cambridge Institute for Medical Research, National Institute for Health Research Cambridge Biomedical Research Centre, Cambridge Biomedical Campus, University of Cambridge, Cambridge, United Kingdom
- MRC Biostatistics Unit Hub for Trials Methodology Research, Cambridge Institute of Public Health, Cambridge Biomedical Campus, Cambridge, United Kingdom
| | - Tim I. Tree
- Department of Immunobiology, Faculty of Life Sciences & Medicine, King’s College London, National Institute of Health Research Biomedical Research Centre, Guy’s and St Thomas’ National Health Service Foundation Trust and King’s College London, London, United Kingdom
| | - Mark Evans
- Wellcome Trust/MRC Institute of Metabolic Science, National Institute for Health Research Cambridge Biomedical Research Centre, Cambridge Biomedical Campus, Cambridge, United Kingdom
| | - Adrian P. Mander
- MRC Biostatistics Unit Hub for Trials Methodology Research, Cambridge Institute of Public Health, Cambridge Biomedical Campus, Cambridge, United Kingdom
| | - Simon Bond
- National Institute for Health Research Cambridge Clinical Trials Unit, Cambridge University Hospitals NHS Foundation Trust, Cambridge Biomedical Campus, Cambridge, United Kingdom
- MRC Biostatistics Unit Hub for Trials Methodology Research, Cambridge Institute of Public Health, Cambridge Biomedical Campus, Cambridge, United Kingdom
| | - Linda S. Wicker
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, Cambridge Institute for Medical Research, National Institute for Health Research Cambridge Biomedical Research Centre, Cambridge Biomedical Campus, University of Cambridge, Cambridge, United Kingdom
| | - Frank Waldron-Lynch
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, Cambridge Institute for Medical Research, National Institute for Health Research Cambridge Biomedical Research Centre, Cambridge Biomedical Campus, University of Cambridge, Cambridge, United Kingdom
- * E-mail: (FWL); (JAT)
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Downes K, Marcovecchio ML, Clarke P, Cooper JD, Ferreira RC, Howson JMM, Jolley J, Nutland S, Stevens HE, Walker NM, Wallace C, Dunger DB, Todd JA. Plasma concentrations of soluble IL-2 receptor α (CD25) are increased in type 1 diabetes and associated with reduced C-peptide levels in young patients. Diabetologia 2014; 57:366-72. [PMID: 24264051 PMCID: PMC3890035 DOI: 10.1007/s00125-013-3113-8] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.2] [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: 08/23/2013] [Accepted: 10/30/2013] [Indexed: 12/15/2022]
Abstract
AIMS/HYPOTHESIS Type 1 diabetes is a common autoimmune disease that has genetic and environmental determinants. Variations within the IL2 and IL2RA (also known as CD25) gene regions are associated with disease risk, and variation in expression or function of these proteins is likely to be causal. We aimed to investigate if circulating concentrations of the soluble form of CD25, sCD25, an established marker of immune activation and inflammation, were increased in individuals with type 1 diabetes and if this was associated with the concentration of C-peptide, a measure of insulin production that reflects the degree of autoimmune destruction of the insulin-producing beta cells. METHODS We used immunoassays to measure sCD25 and C-peptide in peripheral blood plasma from patient and control samples. RESULTS We identified that sCD25 was increased in patients with type 1 diabetes compared with controls and replicated this result in an independent set of 86 adult patient and 80 age-matched control samples (p = 1.17 × 10(-3)). In 230 patients under 20 years of age, with median duration-of-disease of 6.1 years, concentrations of sCD25 were negatively associated with C-peptide concentrations (p = 4.8 × 10(-3)). CONCLUSIONS/INTERPRETATION The 25% increase in sCD25 in patients, alongside the inverse association between sCD25 and C-peptide, probably reflect the adverse effects of an on-going, actively autoimmune and inflammatory immune system on beta cell function in patients.
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Affiliation(s)
- Kate Downes
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, NIHR Cambridge Biomedical Research Centre, Cambridge Institute for Medical Research, University of Cambridge, Addenbrooke’s Hospital, Cambridge, CB2 0XY UK
- Present Address: Department of Haematology, NHS Blood and Transplant, University of Cambridge, Long Road, Cambridge, UK
| | - M. Loredana Marcovecchio
- Department of Paediatrics, University of Cambridge, Addenbrooke’s Hospital, Cambridge, UK
- Present Address: Department of Paediatrics, University of Chieti, Chieti, Italy
| | - Pamela Clarke
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, NIHR Cambridge Biomedical Research Centre, Cambridge Institute for Medical Research, University of Cambridge, Addenbrooke’s Hospital, Cambridge, CB2 0XY UK
| | - Jason D. Cooper
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, NIHR Cambridge Biomedical Research Centre, Cambridge Institute for Medical Research, University of Cambridge, Addenbrooke’s Hospital, Cambridge, CB2 0XY UK
- Present Address: Department of Chemical Engineering and Biotechnology, University of Cambridge, Tennis Court Road, Cambridge, UK
| | - Ricardo C. Ferreira
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, NIHR Cambridge Biomedical Research Centre, Cambridge Institute for Medical Research, University of Cambridge, Addenbrooke’s Hospital, Cambridge, CB2 0XY UK
| | - Joanna M. M. Howson
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, NIHR Cambridge Biomedical Research Centre, Cambridge Institute for Medical Research, University of Cambridge, Addenbrooke’s Hospital, Cambridge, CB2 0XY UK
- Present Address: Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Strangeways Research Laboratory, Cambridge, UK
| | - Jennifer Jolley
- Department of Haematology, NHS Blood and Transplant, University of Cambridge, Long Road, Cambridge, UK
| | - Sarah Nutland
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, NIHR Cambridge Biomedical Research Centre, Cambridge Institute for Medical Research, University of Cambridge, Addenbrooke’s Hospital, Cambridge, CB2 0XY UK
| | - Helen E. Stevens
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, NIHR Cambridge Biomedical Research Centre, Cambridge Institute for Medical Research, University of Cambridge, Addenbrooke’s Hospital, Cambridge, CB2 0XY UK
| | - Neil M. Walker
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, NIHR Cambridge Biomedical Research Centre, Cambridge Institute for Medical Research, University of Cambridge, Addenbrooke’s Hospital, Cambridge, CB2 0XY UK
| | - Chris Wallace
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, NIHR Cambridge Biomedical Research Centre, Cambridge Institute for Medical Research, University of Cambridge, Addenbrooke’s Hospital, Cambridge, CB2 0XY UK
| | - David B. Dunger
- Department of Paediatrics, University of Cambridge, Addenbrooke’s Hospital, Cambridge, UK
| | - John A. Todd
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, NIHR Cambridge Biomedical Research Centre, Cambridge Institute for Medical Research, University of Cambridge, Addenbrooke’s Hospital, Cambridge, CB2 0XY UK
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7
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Pekalski ML, Ferreira RC, Coulson RMR, Cutler AJ, Guo H, Smyth DJ, Downes K, Dendrou CA, Castro Dopico X, Esposito L, Coleman G, Stevens HE, Nutland S, Walker NM, Guy C, Dunger DB, Wallace C, Tree TIM, Todd JA, Wicker LS. Postthymic expansion in human CD4 naive T cells defined by expression of functional high-affinity IL-2 receptors. J Immunol 2013; 190:2554-66. [PMID: 23418630 DOI: 10.4049/jimmunol.1202914] [Citation(s) in RCA: 43] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
Abstract
As the thymus involutes with age, the maintenance of peripheral naive T cells in humans becomes strongly dependent on peripheral cell division. However, mechanisms that orchestrate homeostatic division remain unclear. In this study we present evidence that the frequency of naive CD4 T cells that express CD25 (IL-2 receptor α-chain) increases with age on subsets of both CD31(+) and CD31(-) naive CD4 T cells. Analyses of TCR excision circles from sorted subsets indicate that CD25(+) naive CD4 T cells have undergone more rounds of homeostatic proliferation than their CD25(-) counterparts in both the CD31(+) and CD31(-) subsets, indicating that CD25 is a marker of naive CD4 T cells that have preferentially responded to survival signals from self-Ags or cytokines. CD25 expression on CD25(-) naive CD4 T cells can be induced by IL-7 in vitro in the absence of TCR activation. Although CD25(+) naive T cells respond to lower concentrations of IL-2 as compared with their CD25(-) counterparts, IL-2 responsiveness is further increased in CD31(-) naive T cells by their expression of the signaling IL-2 receptor β-chain CD122, forming with common γ-chain functional high-affinity IL-2 receptors. CD25 plays a role during activation: CD25(+) naive T cells stimulated in an APC-dependent manner were shown to produce increased levels of IL-2 as compared with their CD25(-) counterparts. This study establishes CD25(+) naive CD4 T cells, which are further delineated by CD31 expression, as a major functionally distinct immune cell subset in humans that warrants further characterization in health and disease.
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Affiliation(s)
- Marcin L Pekalski
- Juvenile Diabetes Research Foundation/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, Cambridge Institute for Medical Research, University of Cambridge, Cambridge CB2 0XY, United Kingdom
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8
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Saleh NM, Raj SM, Smyth DJ, Wallace C, Howson JMM, Bell L, Walker NM, Stevens HE, Todd JA. Genetic association analyses of atopic illness and proinflammatory cytokine genes with type 1 diabetes. Diabetes Metab Res Rev 2011; 27:838-43. [PMID: 22069270 PMCID: PMC3816329 DOI: 10.1002/dmrr.1259] [Citation(s) in RCA: 40] [Impact Index Per Article: 3.1] [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] [Indexed: 01/08/2023]
Abstract
BACKGROUND The genetic basis of the autoimmune disease type 1 diabetes (T1D) has now been largely determined, so now we can compare these findings with emerging genetic knowledge of disorders and phenotypes that have been negatively or positively associated with T1D historically. Here, we assessed the role in T1D of variants previously reported to be associated with atopic diseases and epithelial barrier function, profilaggrin (FLG), and those that affect the expression levels of the proinflammatory cytokines tumour necrosis factor (TNF)-α, interleukin (IL)-1β, interferon (IFN)γ and IL-18. METHODS We genotyped single nucleotide polymorphisms (SNPs): -105/rs28665122 in SELS or SEPS1 (selenoprotein), three single nucleotide polymorphisms in IL18 (-105/rs360717, +183/rs5744292 and +1467/rs574456) and R501X/rs61816761 in FLG, the major locus associated with atopic dermatitis and predisposing to asthma, in a minimum of 6743 T1D cases and 7864 controls. RESULTS No evidence of T1D association was found for any of the SNPs we genotyped at FLG, SELS or IL18 (p≥0.03), nor with haplotypes of IL18 (p=0.82). Review of previous T1D genome-wide association results revealed that four (human leucocyte antigen (HLA), gasdermin B/ORM1 (Saccharomyces cerevisiae)-like/gasdermin B/, GSDMB/ORMDL3/GSDMA and IL2RB) of ten loci recently reported to be associated with asthma were associated with T1D (p≤0.005). CONCLUSIONS These results show that there are shared genetic associations for atopy-related traits and T1D, and this might help in the future to understand the mechanisms, pathways and environmental factors that underpin the rapid rise in incidence of both disorders in children.
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Affiliation(s)
| | | | | | | | | | | | | | | | - John A Todd
- *Correspondence to: John A. Todd, Juvenile Diabetes Research Foundation/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, Cambridge Institute for Medical Research, University of Cambridge, Addenbrooke's Hospital, Cambridge CB2 0XY, UK E-mail:
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Davison LJ, Wallace C, Cooper JD, Cope NF, Wilson NK, Smyth DJ, Howson JM, Saleh N, Al-Jeffery A, Angus KL, Stevens HE, Nutland S, Duley S, Coulson RM, Walker NM, Burren OS, Rice CM, Cambien F, Zeller T, Munzel T, Lackner K, Blankenberg S, Fraser P, Gottgens B, Todd JA. Long-range DNA looping and gene expression analyses identify DEXI as an autoimmune disease candidate gene. Hum Mol Genet 2011; 21:322-33. [PMID: 21989056 PMCID: PMC3276289 DOI: 10.1093/hmg/ddr468] [Citation(s) in RCA: 86] [Impact Index Per Article: 6.6] [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] [Indexed: 01/13/2023] Open
Abstract
The chromosome 16p13 region has been associated with several autoimmune diseases, including type 1 diabetes (T1D) and multiple sclerosis (MS). CLEC16A has been reported as the most likely candidate gene in the region, since it contains the most disease-associated single-nucleotide polymorphisms (SNPs), as well as an imunoreceptor tyrosine-based activation motif. However, here we report that intron 19 of CLEC16A, containing the most autoimmune disease-associated SNPs, appears to behave as a regulatory sequence, affecting the expression of a neighbouring gene, DEXI. The CLEC16A alleles that are protective from T1D and MS are associated with increased expression of DEXI, and no other genes in the region, in two independent monocyte gene expression data sets. Critically, using chromosome conformation capture (3C), we identified physical proximity between the DEXI promoter region and intron 19 of CLEC16A, separated by a loop of >150 kb. In reciprocal experiments, a 20 kb fragment of intron 19 of CLEC16A, containing SNPs associated with T1D and MS, as well as with DEXI expression, interacted with the promotor region of DEXI but not with candidate DNA fragments containing other potential causal genes in the region, including CLEC16A. Intron 19 of CLEC16A is highly enriched for transcription-factor-binding events and markers associated with enhancer activity. Taken together, these data indicate that although the causal variants in the 16p13 region lie within CLEC16A, DEXI is an unappreciated autoimmune disease candidate gene, and illustrate the power of the 3C approach in progressing from genome-wide association studies results to candidate causal genes.
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Affiliation(s)
- Lucy J. Davison
- Juvenile Diabetes Research Foundation/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics and
- To whom correspondence should be addressed at: JDRF/WT Diabetes and Inflammation Laboratory, Department of Medical Genetics, Cambridge Institute for Medical Research, Hills Road, Cambridge CB2 0XY, UK. Tel: +44 1223762104; Fax: +44 1223762102;
| | - Chris Wallace
- Juvenile Diabetes Research Foundation/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics and
| | - Jason D. Cooper
- Juvenile Diabetes Research Foundation/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics and
| | - Nathan F. Cope
- Nuclear Dynamics Laboratory, Babraham Institute, Cambridge, UK
| | - Nicola K. Wilson
- Haematopoetic Stem Cell Lab, Cambridge Institute for Medical Research (CIMR), NIHR Biomedical Research Centre, University of Cambridge, Cambridge, UK
| | - Deborah J. Smyth
- Juvenile Diabetes Research Foundation/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics and
| | - Joanna M.M. Howson
- Juvenile Diabetes Research Foundation/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics and
| | - Nada Saleh
- Juvenile Diabetes Research Foundation/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics and
| | - Abdullah Al-Jeffery
- Juvenile Diabetes Research Foundation/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics and
| | - Karen L. Angus
- Juvenile Diabetes Research Foundation/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics and
| | - Helen E. Stevens
- Juvenile Diabetes Research Foundation/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics and
| | - Sarah Nutland
- Juvenile Diabetes Research Foundation/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics and
| | - Simon Duley
- Juvenile Diabetes Research Foundation/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics and
| | - Richard M.R. Coulson
- Juvenile Diabetes Research Foundation/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics and
| | - Neil M. Walker
- Juvenile Diabetes Research Foundation/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics and
| | - Oliver S. Burren
- Juvenile Diabetes Research Foundation/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics and
| | - Catherine M. Rice
- The Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Francois Cambien
- INSERM UMRS 937, Pierre and Marie Curie University and Medical School, Paris, France
| | - Tanja Zeller
- University Heart Center Hamburg, Clinical for General and Interventional Cardiology, 20246 Hamburg, Germany
| | - Thomas Munzel
- Medizinische Klinik und Poliklinik, Johannes-Gutenberg Universität Mainz, Germany and
| | - Karl Lackner
- Department of Clinical Chemistry and Laboratory Medicine, Johannes-Gutenberg Universität Mainz, Germany
| | - Stefan Blankenberg
- University Heart Center Hamburg, Clinical for General and Interventional Cardiology, 20246 Hamburg, Germany
| | | | - Peter Fraser
- Nuclear Dynamics Laboratory, Babraham Institute, Cambridge, UK
| | - Berthold Gottgens
- Haematopoetic Stem Cell Lab, Cambridge Institute for Medical Research (CIMR), NIHR Biomedical Research Centre, University of Cambridge, Cambridge, UK
| | - John A. Todd
- Juvenile Diabetes Research Foundation/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics and
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Yang JHM, Downes K, Howson JMM, Nutland S, Stevens HE, Walker NM, Todd JA. Evidence of association with type 1 diabetes in the SLC11A1 gene region. BMC Med Genet 2011; 12:59. [PMID: 21524304 PMCID: PMC3114708 DOI: 10.1186/1471-2350-12-59] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/16/2010] [Accepted: 04/27/2011] [Indexed: 12/28/2022]
Abstract
BACKGROUND Linkage and congenic strain analyses using the nonobese diabetic (NOD) mouse as a model for human type 1 autoimmune diabetes (T1D) have identified several NOD mouse Idd (insulin dependent diabetes) loci, including Slc11a1 (formerly known as Nramp1). Genetic variants in the orthologous region encompassing SLC11A1 in human chromosome 2q35 have been reported to be associated with various immune-related diseases including T1D. Here, we have conducted association analysis of this candidate gene region, and then investigated potential correlations between the most T1D-associated variant and RNA expression of the SLC11A1 gene and its splice isoform. METHODS Nine SNPs (rs2276631, rs2279015, rs1809231, rs1059823, rs17235409 (D543N), rs17235416 (3'UTR), rs3731865 (INT4), rs7573065 (-237 C → T) and rs4674297) were genotyped using TaqMan genotyping assays and the polymorphic promoter microsatellite (GT)n was genotyped using PCR and fragment length analysis. A maximum of 8,863 T1D British cases and 10,841 British controls, all of white European descent, were used to test association using logistic regression. A maximum of 5,696 T1D families were also tested for association using the transmission/disequilibrium test (TDT). We considered P ≤ 0.005 as evidence of association given that we tested nine variants in total. Upon identification of the most T1D-associated variant, we investigated the correlation between its genotype and SLC11A1 expression overall or with splice isoform ratio using 42 PAXgene whole blood samples from healthy donors by quantitative PCR (qPCR). RESULTS Using the case-control collection, rs3731865 (INT4) was identified to be the variant most associated with T1D (P = 1.55 × 10-6). There was also some evidence of association at rs4674297 (P = 1.57 × 10-4). No evidence of disease association was obtained at any of the loci using the family collections (PTDT ≥ 0.13). We also did not observe a correlation between rs3731865 genotypes and SLC11A1 expression overall or with splice isoform expression. CONCLUSION We conclude that rs3731685 (INT4) in the SLC11A1 gene may be associated with T1D susceptibility in the European ancestry population studied. We did not observe a difference in SLC11A1 expression at the RNA level based on the genotypes of rs3731865 in whole blood samples. However, a potential correlation cannot be ruled out in purified cell subsets especially monocytes or macrophages.
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Affiliation(s)
- Jennie H M Yang
- Juvenile Diabetes Research Foundation/Wellcome Trust Diabetes and Inflammation Laboratory, Cambridge Institute for Medical Research, University of Cambridge, Addenbrooke's Hospital, Hills Road, Cambridge CB2 0XY, UK.
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11
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Wang TJ, Zhang F, Richards JB, Kestenbaum B, van Meurs JB, Berry D, Kiel D, Streeten EA, Ohlsson C, Koller DL, Palotie L, Cooper JD, O'Reilly PF, Houston DK, Glazer NL, Vandenput L, Peacock M, Shi J, Rivadeneira F, McCarthy MI, Anneli P, de Boer IH, Mangino M, Kato B, Smyth DJ, Booth SL, Jacques PF, Burke GL, Goodarzi M, Cheung CL, Wolf M, Rice K, Goltzman D, Hidiroglou N, Ladouceur M, Hui SL, Wareham NJ, Hocking LJ, Hart D, Arden NK, Cooper C, Malik S, Fraser WD, Hartikainen AL, Zhai G, Macdonald H, Forouhi NG, Loos RJ, Reid DM, Hakim A, Dennison E, Liu Y, Power C, Stevens HE, Jaana L, Vasan RS, Soranzo N, Bojunga J, Psaty BM, Lorentzon M, Foroud T, Harris TB, Hofman A, Jansson JO, Cauley JA, Uitterlinden AG, Gibson Q, Järvelin MR, Karasik D, Siscovick DS, Econs MJ, Kritchevsky SB, Florez JC, Todd JA, Dupuis J, Hypponen E, Spector TD. Common genetic determinants of vitamin D insufficiency: a genome-wide association study. Lancet 2010; 376:180-8. [PMID: 20541252 PMCID: PMC3086761 DOI: 10.1016/s0140-6736(10)60588-0] [Citation(s) in RCA: 1163] [Impact Index Per Article: 83.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
BACKGROUND Vitamin D is crucial for maintenance of musculoskeletal health, and might also have a role in extraskeletal tissues. Determinants of circulating 25-hydroxyvitamin D concentrations include sun exposure and diet, but high heritability suggests that genetic factors could also play a part. We aimed to identify common genetic variants affecting vitamin D concentrations and risk of insufficiency. METHODS We undertook a genome-wide association study of 25-hydroxyvitamin D concentrations in 33 996 individuals of European descent from 15 cohorts. Five epidemiological cohorts were designated as discovery cohorts (n=16 125), five as in-silico replication cohorts (n=9367), and five as de-novo replication cohorts (n=8504). 25-hydroxyvitamin D concentrations were measured by radioimmunoassay, chemiluminescent assay, ELISA, or mass spectrometry. Vitamin D insufficiency was defined as concentrations lower than 75 nmol/L or 50 nmol/L. We combined results of genome-wide analyses across cohorts using Z-score-weighted meta-analysis. Genotype scores were constructed for confirmed variants. FINDINGS Variants at three loci reached genome-wide significance in discovery cohorts for association with 25-hydroxyvitamin D concentrations, and were confirmed in replication cohorts: 4p12 (overall p=1.9x10(-109) for rs2282679, in GC); 11q12 (p=2.1x10(-27) for rs12785878, near DHCR7); and 11p15 (p=3.3x10(-20) for rs10741657, near CYP2R1). Variants at an additional locus (20q13, CYP24A1) were genome-wide significant in the pooled sample (p=6.0x10(-10) for rs6013897). Participants with a genotype score (combining the three confirmed variants) in the highest quartile were at increased risk of having 25-hydroxyvitamin D concentrations lower than 75 nmol/L (OR 2.47, 95% CI 2.20-2.78, p=2.3x10(-48)) or lower than 50 nmol/L (1.92, 1.70-2.16, p=1.0x10(-26)) compared with those in the lowest quartile. INTERPRETATION Variants near genes involved in cholesterol synthesis, hydroxylation, and vitamin D transport affect vitamin D status. Genetic variation at these loci identifies individuals who have substantially raised risk of vitamin D insufficiency. FUNDING Full funding sources listed at end of paper (see Acknowledgments).
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Affiliation(s)
- Thomas J. Wang
- Massachusetts General Hospital, Division of Cardiology, Department of Medicine, Boston MA
- Harvard Medical School, Boston MA
- Framingham Heart Study, Framingham MA
| | - Feng Zhang
- King's College London, Department of Twin Research and Genetic Epidemiology, London England
| | - J. Brent Richards
- McGill University, Jewish General Hospital, Departments of Medicine, Human Genetics, Epidemiology and Biostatistics, Montreal Canada
| | - Bryan Kestenbaum
- University of Washington, Kidney Research Institute, Department of Medicine, Division of Nephrology, Harborview Medical Center, Seattle, WA
| | - Joyce B. van Meurs
- Erasmus Medical Center, Department of Internal Medicine, Rotterdam Netherlands
- Netherlands Genomics Initiative (NGI)-sponsored Netherlands Consortium for Healthy Aging (NCHA), Rotterdam Netherlands
| | - Diane Berry
- UCL Institute of Child Health, MRC Centre of Epidemiology for Child Health and Centre for Paediatric Epidemiology and Biostatistics, London England
| | - Douglas Kiel
- Harvard Medical School, Boston MA
- Framingham Heart Study, Framingham MA
- Hebrew SeniorLife, Institute for Aging Research, Genetic Epidemiology Program, Harvard Medical School, Boston MA
| | | | - Claes Ohlsson
- University of Gothenburg, Sahlgrenska Academy, Institute of Medicine, Department of Internal Medicine, Gothenburg Sweden
| | | | - Leena Palotie
- Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, CB10 1HH, United Kingdom
- University of Helsinki and National Institute for Health and Welfare, Partnership for Molecular Medicine, Institute for Molecular Medicine Finland FIMM, Helsinki Finland
- National Institute for Health and Welfare, Helsinki Finland
| | - Jason D. Cooper
- University of Cambridge, JDRF/WT Diabetes and Inflammation Laboratory, Cambridge United Kingdom
| | - Paul F. O'Reilly
- Imperial College, Faculty of Medicine, Department of Epidemiology and Public Health, London England
| | - Denise K. Houston
- Wake Forest University School of Medicine, Sticht Center on Aging, Winston Salem NC
| | - Nicole L. Glazer
- University of Washington, Cardiovascular Health Research Unit and Department of Medicine, Seattle WA
| | - Liesbeth Vandenput
- University of Gothenburg, Sahlgrenska Academy, Institute of Medicine, Department of Internal Medicine, Gothenburg Sweden
| | - Munro Peacock
- Indiana University, School of Medicine, Indianapolis Indiana
| | - Julia Shi
- University of Maryland School of Medicine, Division of Endocrinology, Baltimore MD
| | - Fernando Rivadeneira
- Erasmus Medical Center, Department of Internal Medicine, Rotterdam Netherlands
- Netherlands Genomics Initiative (NGI)-sponsored Netherlands Consortium for Healthy Aging (NCHA), Rotterdam Netherlands
| | - Mark I. McCarthy
- Oxford Centre for Diabetes, Endocrinology and Metabolism (OCDEM), Oxford United Kingdom
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
- Oxford NIHR Biomedical Research Centre, Churchill Hospital, Oxford, UK
| | - Pouta Anneli
- National Institute of Health and Welfare, Oulu Finland
| | - Ian H. de Boer
- University of Washington, Kidney Research Institute, Department of Medicine, Division of Nephrology, Harborview Medical Center, Seattle, WA
| | - Massimo Mangino
- King's College London, Department of Twin Research and Genetic Epidemiology, London England
| | - Bernet Kato
- King's College London, Department of Twin Research and Genetic Epidemiology, London England
| | - Deborah J. Smyth
- University of Cambridge, JDRF/WT Diabetes and Inflammation Laboratory, Cambridge United Kingdom
| | - Sarah L. Booth
- Tufts University, Jean Mayer USDA Human Nutrition Research Center on Aging, Boston MA
| | - Paul F. Jacques
- Tufts University, Jean Mayer USDA Human Nutrition Research Center on Aging, Boston MA
| | - Greg L. Burke
- Wake Forest University Health Sciences, Division of Public Health Sciences, Winston-Salem, NC
| | - Mark Goodarzi
- Cedars-Sinai Medical Center, Department of Medicine, Los Angeles CA
| | - Ching-Lung Cheung
- Harvard Medical School, Boston MA
- Hebrew SeniorLife, Institute for Aging Research, Genetic Epidemiology Program, Harvard Medical School, Boston MA
- Genome Institute of Singapore, Computational and Mathematical Biology, ASTAR (Agency for Science, Technology and Research), Biopolis, Singapore
| | - Myles Wolf
- University of Miami Miller School of Medicine, Division of Nephrology and Hypertension, Miami FL
| | - Kenneth Rice
- University of Washington, Cardiovascular Health Research Unit and Department of Medicine, Seattle WA
| | - David Goltzman
- McGill University, Department of Medicine, Montreal Canada
- McGill University Health Centre, Montreal, Canada
| | | | - Martin Ladouceur
- McGill University, Jewish General Hospital, Departments of Medicine, Human Genetics, Epidemiology and Biostatistics, Montreal Canada
| | - Siu L. Hui
- Indiana University, School of Medicine, Indianapolis Indiana
| | - Nicholas J. Wareham
- MRC Epidemiology Unit, Institute of Metabolic Science, Addenbrooke's Hospital, Cambridge, United Kingdom
| | - Lynne J. Hocking
- University of Aberdeen, Division of Applied Medicine, Bone and Musculoskeletal Research Programme, Aberdeen United Kingdom
| | - Deborah Hart
- King's College London, Department of Twin Research and Genetic Epidemiology, London England
| | - Nigel K. Arden
- University of Southampton, MRC Epidemiology Resource Centre, Southampton England
- University of Oxford, NIHR Musculoskeletal Biomedical Research Unit, Oxford England
| | - Cyrus Cooper
- University of Southampton, MRC Epidemiology Resource Centre, Southampton England
- University of Oxford, NIHR Musculoskeletal Biomedical Research Unit, Oxford England
| | - Suneil Malik
- Office of Biotechnology, Genomics and Population Health, Public Health Agency of Canada, Toronto, Canada
| | - William D. Fraser
- Unit of Clinical Chemistry, School of Clinical Sciences, University of Liverpool, Liverpool
| | | | - Guangju Zhai
- King's College London, Department of Twin Research and Genetic Epidemiology, London England
| | - Helen Macdonald
- University of Aberdeen, Division of Applied Medicine, Bone and Musculoskeletal Research Programme, Aberdeen United Kingdom
| | - Nita G. Forouhi
- MRC Epidemiology Unit, Institute of Metabolic Science, Addenbrooke's Hospital, Cambridge, United Kingdom
| | - Ruth J.F. Loos
- MRC Epidemiology Unit, Institute of Metabolic Science, Addenbrooke's Hospital, Cambridge, United Kingdom
| | - David M. Reid
- University of Aberdeen, Division of Applied Medicine, Bone and Musculoskeletal Research Programme, Aberdeen United Kingdom
| | - Alan Hakim
- Whipps Cross Rheumatology Department, London England
| | - Elaine Dennison
- University of Southampton, MRC Epidemiology Resource Centre, Southampton England
| | - Yongmei Liu
- Wake Forest University School of Medicine, Sticht Center on Aging, Winston Salem NC
| | - Chris Power
- UCL Institute of Child Health, MRC Centre of Epidemiology for Child Health and Centre for Paediatric Epidemiology and Biostatistics, London England
| | - Helen E. Stevens
- University of Cambridge, JDRF/WT Diabetes and Inflammation Laboratory, Cambridge United Kingdom
| | - Laitinen Jaana
- Finnish Institute of Occupational Health, Oulu Finland
- University of Oulu, Institute of Health Sciences, Oulu Finland
| | - Ramachandran S. Vasan
- Framingham Heart Study, Framingham MA
- Boston University School of Medicine, Division of Preventive Medicine, Boston MA
| | - Nicole Soranzo
- King's College London, Department of Twin Research and Genetic Epidemiology, London England
- Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, CB10 1HH, United Kingdom
| | - Jörg Bojunga
- Klinikum der Johann Wolfgang Goethe University, Frankfurt Germany
| | - Bruce M. Psaty
- University of Washington, Departments of Medicine, Epidemiology and Health Services, Seattle WA
| | - Mattias Lorentzon
- University of Gothenburg, Sahlgrenska Academy, Institute of Medicine, Department of Internal Medicine, Gothenburg Sweden
| | - Tatiana Foroud
- Indiana University, School of Medicine, Indianapolis Indiana
| | - Tamara B. Harris
- National Institutes of Health, National Institute on Aging, Bethesda MD
| | - Albert Hofman
- Netherlands Genomics Initiative (NGI)-sponsored Netherlands Consortium for Healthy Aging (NCHA), Rotterdam Netherlands
- Erasmus Medical Center, Department of Epidemiology, Rotterdam Netherlands
| | - John-Olov Jansson
- University of Gothenburg, Sahlgrenska Academy, Institute of Neuroscience and Physiology, Department of Physiology, Gothenburg Sweden
| | - Jane A. Cauley
- University of Pittsburgh, Department of Epidemiology, Pittsburgh PA
| | - Andre G. Uitterlinden
- Netherlands Genomics Initiative (NGI)-sponsored Netherlands Consortium for Healthy Aging (NCHA), Rotterdam Netherlands
- Erasmus Medical Center, Departments of Internal, Epidemiology and Klinical Genetics, Rotterdam Netherlands
| | - Quince Gibson
- Erasmus Medical Center, Department of Internal Medicine, Rotterdam Netherlands
| | - Marjo-Riitta Järvelin
- Imperial College, Faculty of Medicine, Department of Epidemiology and Public Health, London England
- National Institute of Health and Welfare, Oulu Finland
- University of Oulu, Institute of Health Sciences, Oulu Finland
- University of Oulu, Biocenter Oulu, Oulu Finland
| | - David Karasik
- Harvard Medical School, Boston MA
- Hebrew SeniorLife, Institute for Aging Research, Genetic Epidemiology Program, Harvard Medical School, Boston MA
| | - David S. Siscovick
- University of Washington, Cardiovascular Health Research Unit and Departments of Medicine and Epidemiology, Seattle WA
| | | | | | - Jose C. Florez
- Harvard Medical School, Boston MA
- Massachusetts General Hospital, Diabetes Research Center (Diabetes Unit) and Center for Human Genetic Research, Boston MA
- Broad Institute, Program in Medical and Population Genetics, Cambridge MA
| | - John A. Todd
- University of Cambridge, JDRF/WT Diabetes and Inflammation Laboratory, Cambridge United Kingdom
| | - Josee Dupuis
- Framingham Heart Study, Framingham MA
- Boston University School of Public Health, Department of Biostatistics, Boston MA
| | - Elina Hypponen
- UCL Institute of Child Health, MRC Centre of Epidemiology for Child Health and Centre for Paediatric Epidemiology and Biostatistics, London England
| | - Timothy D. Spector
- King's College London, Department of Twin Research and Genetic Epidemiology, London England
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12
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Craddock N, Hurles ME, Cardin N, Pearson RD, Plagnol V, Robson S, Vukcevic D, Barnes C, Conrad DF, Giannoulatou E, Holmes C, Marchini JL, Stirrups K, Tobin MD, Wain LV, Yau C, Aerts J, Ahmad T, Andrews TD, Arbury H, Attwood A, Auton A, Ball SG, Balmforth AJ, Barrett JC, Barroso I, Barton A, Bennett AJ, Bhaskar S, Blaszczyk K, Bowes J, Brand OJ, Braund PS, Bredin F, Breen G, Brown MJ, Bruce IN, Bull J, Burren OS, Burton J, Byrnes J, Caesar S, Clee CM, Coffey AJ, Connell JMC, Cooper JD, Dominiczak AF, Downes K, Drummond HE, Dudakia D, Dunham A, Ebbs B, Eccles D, Edkins S, Edwards C, Elliot A, Emery P, Evans DM, Evans G, Eyre S, Farmer A, Ferrier IN, Feuk L, Fitzgerald T, Flynn E, Forbes A, Forty L, Franklyn JA, Freathy RM, Gibbs P, Gilbert P, Gokumen O, Gordon-Smith K, Gray E, Green E, Groves CJ, Grozeva D, Gwilliam R, Hall A, Hammond N, Hardy M, Harrison P, Hassanali N, Hebaishi H, Hines S, Hinks A, Hitman GA, Hocking L, Howard E, Howard P, Howson JMM, Hughes D, Hunt S, Isaacs JD, Jain M, Jewell DP, Johnson T, Jolley JD, Jones IR, Jones LA, Kirov G, Langford CF, Lango-Allen H, Lathrop GM, Lee J, Lee KL, Lees C, Lewis K, Lindgren CM, Maisuria-Armer M, Maller J, Mansfield J, Martin P, Massey DCO, McArdle WL, McGuffin P, McLay KE, Mentzer A, Mimmack ML, Morgan AE, Morris AP, Mowat C, Myers S, Newman W, Nimmo ER, O'Donovan MC, Onipinla A, Onyiah I, Ovington NR, Owen MJ, Palin K, Parnell K, Pernet D, Perry JRB, Phillips A, Pinto D, Prescott NJ, Prokopenko I, Quail MA, Rafelt S, Rayner NW, Redon R, Reid DM, Renwick, Ring SM, Robertson N, Russell E, St Clair D, Sambrook JG, Sanderson JD, Schuilenburg H, Scott CE, Scott R, Seal S, Shaw-Hawkins S, Shields BM, Simmonds MJ, Smyth DJ, Somaskantharajah E, Spanova K, Steer S, Stephens J, Stevens HE, Stone MA, Su Z, Symmons DPM, Thompson JR, Thomson W, Travers ME, Turnbull C, Valsesia A, Walker M, Walker NM, Wallace C, Warren-Perry M, Watkins NA, Webster J, Weedon MN, Wilson AG, Woodburn M, Wordsworth BP, Young AH, Zeggini E, Carter NP, Frayling TM, Lee C, McVean G, Munroe PB, Palotie A, Sawcer SJ, Scherer SW, Strachan DP, Tyler-Smith C, Brown MA, Burton PR, Caulfield MJ, Compston A, Farrall M, Gough SCL, Hall AS, Hattersley AT, Hill AVS, Mathew CG, Pembrey M, Satsangi J, Stratton MR, Worthington J, Deloukas P, Duncanson A, Kwiatkowski DP, McCarthy MI, Ouwehand W, Parkes M, Rahman N, Todd JA, Samani NJ, Donnelly P. Genome-wide association study of CNVs in 16,000 cases of eight common diseases and 3,000 shared controls. Nature 2010; 464:713-20. [PMID: 20360734 PMCID: PMC2892339 DOI: 10.1038/nature08979] [Citation(s) in RCA: 594] [Impact Index Per Article: 42.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2009] [Accepted: 03/05/2010] [Indexed: 01/13/2023]
Abstract
Copy number variants (CNVs) account for a major proportion of human genetic polymorphism and have been predicted to play an important role in genetic susceptibility to common disease. To address this we undertook a large direct genome-wide study of association between CNVs and eight common human diseases. Using a purpose-designed array we typed ~19,000 individuals into distinct copy-number classes at 3,432 polymorphic CNVs, including an estimated ~50% of all common CNVs larger than 500bp. We identified several biological artefacts that lead to false-positive associations, including systematic CNV differences between DNAs derived from blood and cell-lines. Association testing and follow-up replication analyses confirmed three loci where CNVs were associated with disease, IRGM for Crohn's disease, HLA for Crohn's disease, rheumatoid arthritis, and type 1 diabetes, and TSPAN8 for type 2 diabetes, though in each case the locus had previously been identified in SNP-based studies, reflecting our observation that the majority of common CNVs which are well-typed on our array are well tagged by SNPs and so have been indirectly explored through SNP studies. We conclude that common CNVs which can be typed on existing platforms are unlikely to contribute greatly to the genetic basis of common human diseases.
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13
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Nejentsev S, Howson JMM, Walker NM, Szeszko J, Field SF, Stevens HE, Reynolds P, Hardy M, King E, Masters J, Hulme J, Maier LM, Smyth D, Bailey R, Cooper JD, Ribas G, Campbell RD, Clayton DG, Todd JA. Localization of type 1 diabetes susceptibility to the MHC class I genes HLA-B and HLA-A. Nature 2007; 450:887-92. [PMID: 18004301 PMCID: PMC2703779 DOI: 10.1038/nature06406] [Citation(s) in RCA: 407] [Impact Index Per Article: 23.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2007] [Accepted: 10/25/2007] [Indexed: 01/04/2023]
Abstract
The major histocompatibility complex (MHC) on chromosome 6 is associated with susceptibility to more common diseases than any other region of the human genome, including almost all disorders classified as autoimmune. In type 1 diabetes the major genetic susceptibility determinants have been mapped to the MHC class II genes HLA-DQB1 and HLA-DRB1 (refs 1-3), but these genes cannot completely explain the association between type 1 diabetes and the MHC region. Owing to the region's extreme gene density, the multiplicity of disease-associated alleles, strong associations between alleles, limited genotyping capability, and inadequate statistical approaches and sample sizes, which, and how many, loci within the MHC determine susceptibility remains unclear. Here, in several large type 1 diabetes data sets, we analyse a combined total of 1,729 polymorphisms, and apply statistical methods-recursive partitioning and regression-to pinpoint disease susceptibility to the MHC class I genes HLA-B and HLA-A (risk ratios >1.5; P(combined) = 2.01 x 10(-19) and 2.35 x 10(-13), respectively) in addition to the established associations of the MHC class II genes. Other loci with smaller and/or rarer effects might also be involved, but to find these, future searches must take into account both the HLA class II and class I genes and use even larger samples. Taken together with previous studies, we conclude that MHC-class-I-mediated events, principally involving HLA-B*39, contribute to the aetiology of type 1 diabetes.
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Affiliation(s)
- Sergey Nejentsev
- Juvenile Diabetes Research Foundation/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, Cambridge Institute of Medical Research, University of Cambridge, CB2 0XY, UK
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14
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Todd JA, Walker NM, Cooper JD, Smyth DJ, Downes K, Plagnol V, Bailey R, Nejentsev S, Field SF, Payne F, Lowe CE, Szeszko JS, Hafler JP, Zeitels L, Yang JHM, Vella A, Nutland S, Stevens HE, Schuilenburg H, Coleman G, Maisuria M, Meadows W, Smink LJ, Healy B, Burren OS, Lam AAC, Ovington NR, Allen J, Adlem E, Leung HT, Wallace C, Howson JMM, Guja C, Ionescu-Tîrgovişte C, Simmonds MJ, Heward JM, Gough SCL, Dunger DB, Wicker LS, Clayton DG. Robust associations of four new chromosome regions from genome-wide analyses of type 1 diabetes. Nat Genet 2007; 39:857-64. [PMID: 17554260 PMCID: PMC2492393 DOI: 10.1038/ng2068] [Citation(s) in RCA: 1092] [Impact Index Per Article: 64.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2007] [Accepted: 05/14/2007] [Indexed: 12/11/2022]
Abstract
The Wellcome Trust Case Control Consortium (WTCCC) primary genome-wide association (GWA) scan on seven diseases, including the multifactorial autoimmune disease type 1 diabetes (T1D), shows associations at P < 5 x 10(-7) between T1D and six chromosome regions: 12q24, 12q13, 16p13, 18p11, 12p13 and 4q27. Here, we attempted to validate these and six other top findings in 4,000 individuals with T1D, 5,000 controls and 2,997 family trios independent of the WTCCC study. We confirmed unequivocally the associations of 12q24, 12q13, 16p13 and 18p11 (P(follow-up) <or= 1.35 x 10(-9); P(overall) <or= 1.15 x 10(-14)), leaving eight regions with small effects or false-positive associations. We also obtained evidence for chromosome 18q22 (P(overall) = 1.38 x 10(-8)) from a GWA study of nonsynonymous SNPs. Several regions, including 18q22 and 18p11, showed association with autoimmune thyroid disease. This study increases the number of T1D loci with compelling evidence from six to at least ten.
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Affiliation(s)
- John A Todd
- Juvenile Diabetes Research Foundation/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, University of Cambridge, Addenbrooke's Hospital, Cambridge CB2 0XY, UK.
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Payne F, Cooper JD, Walker NM, Lam AC, Smink LJ, Nutland S, Stevens HE, Hutchings J, Todd JA. Interaction analysis of the CBLB and CTLA4 genes in type 1 diabetes. J Leukoc Biol 2007; 81:581-3. [PMID: 17209142 DOI: 10.1189/jlb.0906577] [Citation(s) in RCA: 15] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022] Open
Abstract
Gene-gene interaction analyses have been suggested as a potential strategy to help identify common disease susceptibility genes. Recently, evidence of a statistical interaction between polymorphisms in two negative immunoregulatory genes, CBLB and CTLA4, has been reported in type 1 diabetes (T1D). This study, in 480 Danish families, reported an association between T1D and a synonymous coding SNP in exon 12 of the CBLB gene (rs3772534 G>A; minor allele frequency, MAF=0.24; derived relative risk, RR for G allele=1.78; P=0.046). Furthermore, evidence of a statistical interaction with the known T1D susceptibility-associated CTLA4 polymorphism rs3087243 (laboratory name CT60, G>A) was reported (P<0.0001), such that the CBLB SNP rs3772534 G allele was overtransmitted to offspring with the CTLA4 rs3087243 G/G genotype. We have, therefore, attempted to obtain additional support for this finding in both large family and case-control collections. In a primary analysis, no evidence for an association of the CBLB SNP rs3772534 with disease was found in either sample set (2162 parent-child trios, P=0.33; 3453 cases and 3655 controls, P=0.69). In the case-only statistical interaction analysis between rs3772534 and rs3087243, there was also no support for an effect (1994 T1D affected offspring, and 3215 cases, P=0.92). These data highlight the need for large, well-characterized populations, offering the possibility of obtaining additional support for initial observations owing to the low prior probability of identifying reproducible evidence of gene-gene interactions in the analysis of common disease-associated variants in human populations.
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Affiliation(s)
- Felicity Payne
- Juvenile Diabetes Research Foundation/Wellcome Trust, Diabetes and Inflammation Laboratory, Cambridge Institute for Medical Research, University of Cambridge, Wellcome Trust/MRC Building, Addenbrooke's Hospital, Cambridge, UK
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16
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Szeszko JS, Howson JMM, Cooper JD, Walker NM, Twells RCJ, Stevens HE, Nutland SL, Todd JA. Analysis of polymorphisms of the interleukin-18 gene in type 1 diabetes and Hardy-Weinberg equilibrium testing. Diabetes 2006; 55:559-62. [PMID: 16443795 DOI: 10.2337/diabetes.55.02.06.db05-0826] [Citation(s) in RCA: 29] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/29/2023]
Abstract
Recently, the interleukin-18 cytokine gene (IL18) was reported to be associated with type 1 diabetes. In the present report, we calculated that the reported genotypes of the two 5' region/promoter single nucleotide polymorphisms (SNPs), -607 (C-->A) (rs1946518) and -137 (G-->C) (rs187238), were not in Hardy-Weinberg equilibrium (HWE). We therefore investigated the association of the -607 and -137 SNPs in a U.K. type 1 diabetic Caucasian case-control collection (1,560 case and 1,715 control subjects tested at -607 and 4,323 case and 4,610 control subjects tested at -137) as well as a type 1 diabetic Caucasian collection comprised of families of European ancestry (1,347 families tested at -137 and 1,356 families tested at -607). No evidence for association with type 1 diabetes was found, including for the -607 A/A and C/A genotypes. To evaluate whether common variation elsewhere in the gene was associated with disease susceptibility, we analyzed eight IL18 tag SNPs in a type 1 diabetic case-control collection (1,561 case and 1,721 control subjects). No evidence for association was obtained (P = 0.11). We conclude that common allelic variation in IL18 is unlikely to contribute substantially to type 1 diabetes susceptibility in the populations tested and recommend routine application of tests for HWE in population-based studies for genetic association.
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Affiliation(s)
- Jeffrey S Szeszko
- Juvenile Diabetes Research Foundation/Wellcome Trust Diabetes and Inflammation Laboratory, Cambridge Institute for Medical Research, University of Cambridge, UK
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17
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Clayton DG, Walker NM, Smyth DJ, Pask R, Cooper JD, Maier LM, Smink LJ, Lam AC, Ovington NR, Stevens HE, Nutland S, Howson JMM, Faham M, Moorhead M, Jones HB, Falkowski M, Hardenbol P, Willis TD, Todd JA. Population structure, differential bias and genomic control in a large-scale, case-control association study. Nat Genet 2005; 37:1243-6. [PMID: 16228001 DOI: 10.1038/ng1653] [Citation(s) in RCA: 401] [Impact Index Per Article: 21.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2005] [Accepted: 08/15/2005] [Indexed: 11/09/2022]
Abstract
The main problems in drawing causal inferences from epidemiological case-control studies are confounding by unmeasured extraneous factors, selection bias and differential misclassification of exposure. In genetics the first of these, in the form of population structure, has dominated recent debate. Population structure explained part of the significant +11.2% inflation of test statistics we observed in an analysis of 6,322 nonsynonymous SNPs in 816 cases of type 1 diabetes and 877 population-based controls from Great Britain. The remainder of the inflation resulted from differential bias in genotype scoring between case and control DNA samples, which originated from two laboratories, causing false-positive associations. To avoid excluding SNPs and losing valuable information, we extended the genomic control method by applying a variable downweighting to each SNP.
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Affiliation(s)
- David G Clayton
- Juvenile Diabetes Research Foundation/Wellcome Trust Diabetes and Inflammation Laboratory, University of Cambridge, Cambridge Institute for Medical Research, Wellcome Trust/MRC Building, Cambridge, CB2 2XY, UK
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Mein CA, Barratt BJ, Dunn MG, Siegmund T, Smith AN, Esposito L, Nutland S, Stevens HE, Wilson AJ, Phillips MS, Jarvis N, Law S, de Arruda M, Todd JA. Evaluation of single nucleotide polymorphism typing with invader on PCR amplicons and its automation. Genome Res 2000; 10:330-43. [PMID: 10720574 PMCID: PMC311429 DOI: 10.1101/gr.10.3.330] [Citation(s) in RCA: 157] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/27/2023]
Abstract
Large-scale pharmacogenetics and complex disease association studies will require typing of thousands of single-nucleotide polymorphisms (SNPs) in thousands of individuals. Such projects would benefit from a genotyping system with accuracy >99% and a failure rate <5% on a simple, reliable, and flexible platform. However, such a system is not yet available for routine laboratory use. We have evaluated a modification of the previously reported Invader SNP-typing chemistry for use in a genotyping laboratory and tested its automation. The Invader technology uses a Flap Endonuclease for allele discrimination and a universal fluorescence resonance energy transfer (FRET) reporter system. Three hundred and eighty-four individuals were genotyped across a panel of 36 SNPs and one insertion/deletion polymorphism with Invader assays using PCR product as template, a total of 14,208 genotypes. An average failure rate of 2.3% was recorded, mostly associated with PCR failure, and the typing was 99.2% accurate when compared with genotypes generated with established techniques. An average signal-to-noise ratio (9:1) was obtained. The high degree of discrimination for single base changes, coupled with homogeneous format, has allowed us to deploy liquid handling robots in a 384-well microtitre plate format and an automated end-point capture of fluorescent signal. Simple semiautomated data interpretation allows the generation of approximately 25,000 genotypes per person per week, which is 10-fold greater than gel-based SNP typing and microsatellite typing in our laboratory. Savings on labor costs are considerable. We conclude that Invader chemistry using PCR products as template represents a useful technology for typing large numbers of SNPs rapidly and efficiently.
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Affiliation(s)
- C A Mein
- Wellcome Trust Centre for the Study of Molecular Mechanisms in Disease, University of Cambridge, Addenbrooke's Hospital, Cambridge CB2 2XY UK
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Abstract
Whispered syllables lack many of the frequency and voicing cues of normally voiced speech, but these two acoustically distinct forms of speech are placed into the same linguistic categories. To examine how whispered and voiced speech are encoded in the auditory system, the responses to speech sounds were recorded from 132 single auditory nerve fibers in 20 ketamine anesthetized chinchillas. Stimuli were the naturally produced syllables /da/ and /ta/ presented in whispered and normal voicing. The results for each syllable presented at a fixed intensity were analyzed by pooling the responses from individual auditory nerve fibers across animals to create a global average peri-stimulus time (GAPST) histogram. For each word-initial consonant, the pattern of peaks in the GAPST was the same for both normal and whispered speech. For the vowel the GAPSTs for the whispered speech sounds did not display the synchronization observed in the responses to the voiced syllables. The temporal pattern of the peaks was constant over a 40 dB intensity range, although peak sizes varied. Grouping fibers within different frequency ranges created local averages (LAPST) that revealed the significant contribution of high frequency fibers in the response to the whispered consonants. Responses of individual fibers varied with both the syllable and the voicing. These findings suggest that the encoding of either a whispered or a normal stop consonant results in the same temporal pattern in the ensemble response.
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Affiliation(s)
- H E Stevens
- Department of Psychology, University of Illinois at Urbana-Champaign, Champaign 61820, USA.
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20
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Abstract
Responses of auditory nerve fibers to trains of clicks were recorded in ketamine anesthetized chinchillas. By varying the number of clicks and the interclick interval, this study examined whether "post-onset adaptation," described in psychoacoustic experiments on localization, occurred in auditory nerve fibers. The results showed that the number of action potentials recorded from a nerve fiber in response to a train of clicks was a power function of the number of clicks. For interclick intervals of 2 ms or greater the exponent of the power function was 0.5, and this exponent did not change over a 20-dB range of intensities. The timing of action potentials relative to the click stimuli was measured using synchronization coefficients. The coefficients increased with interclick interval, decreased with increasing intensity, and were greater for fibers with low rates of spontaneous activity than for high spontaneous fibers. Recovery functions showed that for interclick intervals of 2 ms or more, the responses to the second click were at least 70% of the response to the initial click. The recovery depended upon the number of clicks in the train. These findings indicate that auditory nerve fibers respond to high rates of stimulus presentation and do not display the adaptation observed in localization studies.
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Affiliation(s)
- R E Wickesberg
- Department of Psychology, University of Illinois at Urbana-Champaign 61820, USA
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21
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Javer AR, Stevens HE, Stillwell M, Jafar AM. Efficacy of nuclear scintigraphy in the diagnosis and management of sinusitis. J Otolaryngol 1996; 25:375-82. [PMID: 8972429] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Abstract
OBJECTIVE The purpose of this study was to determine whether or not nuclear scintigraphy is useful in the diagnosis and management of chronic sinusitis. The ideal isotope(s) and drawbacks of the different isotopes in different clinical situations are reviewed and discussed. DESIGN A retrospective review of patients undergoing nuclear medicine studies to aid in the diagnosis and management of sinus disease was carried out. METHOD Ideal candidates were chosen from both previously operated and unoperated patients whose computed tomography (CT) scan findings could not differentiate benign mucosal thickening from active inflammation. Nuclear scintigraphy scans using indium (In-111), gallium (Ga-67), and technetium (Tch-99m) were used to differentiate acute infection from chronic inflammation involving bone (osteitis) and/or mucosa. This information was then used to guide the management of their condition. Nuclear scintigraphy results were compared to findings on CT scan and during surgery. RESULTS In-111 was found to be the best isotope for identifying pus or acute disease in the sinuses whereas Ga-67 was very good for identifying both chronic mucosal disease as well as acute disease. Tch-99m was very sensitive for identifying bony remodelling and was therefore not found to be useful if the patient had undergone previous sinus surgery. CONCLUSION Although not to be considered, in our view, a first-line diagnostic test, nuclear scintigraphy, is useful in cases where CT results are nondifferentiating.
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Affiliation(s)
- A R Javer
- Division of Otolaryngology, St. Paul's Hospital, Vancouver, British Columbia
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22
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Samad I, Stevens HE, Maloney A. The efficacy of nasal septal surgery. J Otolaryngol 1992; 21:88-91. [PMID: 1583714] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
Nasal septal deformity is a frequent clinical entity, and septoplasty comprises one of the most common procedures performed by otolaryngologists today. Its efficacy seems intuitive, however the literature reveals relatively few papers confirming its utility. In this study, all patients undergoing septal reconstruction (excluding septorhinoplasty) at three major teaching hospitals in Vancouver during the years 1988 to 1990 were reviewed retrospectively in a two-pronged study. Information was collected concerning symptoms, physical findings and surgical technique. In the second phase, patients were contacted by telephone in a blinded fashion. Data was collected concerning patient satisfaction regarding various parameters including initial and ultimate symptom resolution, acceptance of nasal packing and postoperative complications. The following conclusions may be drawn: 1) Septoplasty was successful in relieving nasal obstruction in 70.5% of patients. 2) Turbinate surgery including outfracturing appears to significantly improve the outcome of surgery. 3) Rhinitis, including allergy, congestion, postnasal drip and rhinorrhea did not significantly affect success in relieving nasal obstruction. 4) Nasal packing did not significantly affect the outcome, but was the most frequently complained of aspect of the surgery. Therefore, we do not feel nasal packing is necessary.
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Affiliation(s)
- I Samad
- Division of Otolaryngology, University of British Columbia, Vancouver, Canada
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Stevens HE. Allergic and inflammatory aspects of chronic rhinosinusitis. J Otolaryngol 1991; 20:395-9. [PMID: 1723108] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Abstract
The pathophysiology of rhinosinusitis is complex and poorly understood. Although it is recognized that obstruction of the sinus ostia which is surgically correctable contributes to recurrent bacterial sinusitis, allergic and nonallergic inflammation may contribute to or mimic infectious rhinosinusitis. Those aspects of rhinosinusitis which are not necessarily surgically correctable require consideration and may affect surgical prognosis. This article focuses on those considerations.
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Affiliation(s)
- H E Stevens
- Division of Otolaryngology, University Hospital-Shaughnessy Site, Vancouver, British Columbia, Canada
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Stevens HE. Vascular complication of neck space infection: case report and literature review. J Otolaryngol 1990; 19:206-10. [PMID: 2355414] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
Antibiotic therapy has changed the face of medicine radically, and physicians no longer have the empirical knowledge of bacterial infections that they once had. Consequently, the diagnosis and management of complicated infections presents a significant challenge to today's otolaryngologists. We present a rare complication, even before the advent of antibiotics, of a head and neck infection: a carotid artery pseudoaneurysm resulting from peritonsillar abscess. The diagnosis and management of this problem is discussed and the pertinent literature reviewed.
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Affiliation(s)
- H E Stevens
- Division of Otolaryngology, University Hospital, Vancouver, British Columbia, Canada
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Stevens HE. Epistaxis. Can Fam Physician 1990; 36:757-760. [PMID: 21234028 PMCID: PMC2280591] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 05/30/2023]
Abstract
Good equipment, readily available, and organized management are essential for successful control of epistaxis without exacerbating the patient's trauma. Epistaxis most commonly results from localized causes but can reflect systemic disease. The author describes practical management of epistaxis, particularly for acute problems in the emergency room.
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Stevens HE, Blair NJ. Intranasal sphenoethmoidectomy: 10-year experience and literature review. J Otolaryngol 1988; 17:254-9. [PMID: 3216450] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
Abstract
We believe that complete intranasal sphenoethmoidectomy is the procedure of choice for massive nasal polyposis and polypoid sinusitis. The anatomy is complex, visualization with conventional matters is limited, and the potential complications can be severe. Nevertheless, with thorough underlying knowledge of the anatomy and proper training consisting of cadaver dissection and supervised surgery, a safe, effective technique can be mastered. Two hundred and thirty sphenoethmoidectomies done in 87 patients over the past 10 years are reviewed. The initial recurrence rate was 25%. There was a 3% incidence of serious complications. These results are comparable to those in the literature. While recognizing the potential complications of this difficult procedure, we believe that it can be performed safely and effectively by properly trained surgeons and that an effort should be made to extend proper instruction to otolaryngology residents.
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Affiliation(s)
- H E Stevens
- University of British Columbia, Department of Otolaryngology, Shaughnessy Hospital
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Stevens HE, Doyle PJ. Bilateral gustatory rhinorrhea following bilateral parotidectomy: a case report. J Otolaryngol 1988; 17:191-3. [PMID: 3398109] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Abstract
To the authors' knowledge, no cases of gustatory rhinorrhea following parotidectomy have been reported. A case is presented of a 28-year-old woman who underwent bilateral parotidectomies within a four-year period for congenital sialectasia and secondary infection. Both operations were complicated by Frey's syndrome and she also developed bilateral gustatory rhinorrhea. The successful management of this problem with bilateral vidian neurectomies and the refractory nature of her Frey's syndrome, finally controlled with tympanic neurectomies, are discussed.
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Affiliation(s)
- H E Stevens
- Department of Otolaryngology, Shaughnessy Hospital, Vancouver, British Columbia, Canada
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Stevens HE. Comparative skin and RAST test results. Laryngoscope 1986; 96:448-9. [PMID: 3959707 DOI: 10.1288/00005537-198604000-00021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
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Decker JR, Kaune WT, Stevens HE. A microprocessor-based environmental monitor for large animal experimental facilities. Biomed Sci Instrum 1978; 14:109-14. [PMID: 687719] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
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