1
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Lin Q, Kuypers M, Baglaenko Y, Cao E, Hezaveh K, Despot T, de Amat Herbozo C, Cruz Tleugabulova M, Umaña JM, McGaha TL, Philpott DJ, Mallevaey T. The intestinal microbiota modulates the transcriptional landscape of iNKT cells at steady-state and following antigen exposure. Mucosal Immunol 2024; 17:226-237. [PMID: 38331095 DOI: 10.1016/j.mucimm.2024.02.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2023] [Revised: 01/30/2024] [Accepted: 02/01/2024] [Indexed: 02/10/2024]
Abstract
Invariant Natural Killer T (iNKT) cells are unconventional T cells that respond to microbe-derived glycolipid antigens. iNKT cells exert fast innate effector functions that regulate immune responses in a variety of contexts, including during infection, cancer, or inflammation. The roles these unconventional T cells play in intestinal inflammation remain poorly defined and vary based on the disease model and species. Our previous work suggested that the gut microbiota influenced iNKT cell functions during dextran sulfate sodium-induced colitis in mice. This study, shows that iNKT cell homeostasis and response following activation are altered in germ-free mice. Using prenatal fecal transplant in specific pathogen-free mice, we show that the transcriptional signatures of iNKT cells at steady state and following αGC-mediated activation in vivo are modulated by the microbiota. Our data suggest that iNKT cells sense the microbiota at homeostasis independently of their T cell receptors. Finally, iNKT cell transcriptional signatures are different in male and female mice. Collectively, our findings suggest that sex and the intestinal microbiota are important factors that regulate iNKT cell homeostasis and responses. A deeper understanding of microbiota-iNKT cell interactions and the impact of sex could improve the development of iNKT cell-based immunotherapies.
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Affiliation(s)
- Qiaochu Lin
- Department of Immunology, University of Toronto, Toronto, Ontario, Canada
| | - Meggie Kuypers
- Department of Immunology, University of Toronto, Toronto, Ontario, Canada
| | - Yuriy Baglaenko
- Center for Autoimmune Genomics and Etiology, Division of Genetics, Cincinnati Children's Hospital, Cincinnati, OH, USA
| | - Eric Cao
- Department of Immunology, University of Toronto, Toronto, Ontario, Canada
| | - Kebria Hezaveh
- Department of Immunology, University of Toronto, Toronto, Ontario, Canada; Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada
| | - Tijana Despot
- Department of Immunology, University of Toronto, Toronto, Ontario, Canada
| | | | | | | | - Tracy L McGaha
- Department of Immunology, University of Toronto, Toronto, Ontario, Canada; Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada
| | - Dana J Philpott
- Department of Immunology, University of Toronto, Toronto, Ontario, Canada
| | - Thierry Mallevaey
- Department of Immunology, University of Toronto, Toronto, Ontario, Canada.
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2
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Kim T, Martínez-Bonet M, Wang Q, Hackert N, Sparks JA, Baglaenko Y, Koh B, Darbousset R, Laza-Briviesca R, Chen X, Aguiar VRC, Chiu DJ, Westra HJ, Gutierrez-Arcelus M, Weirauch MT, Raychaudhuri S, Rao DA, Nigrovic PA. Non-coding autoimmune risk variant defines role for ICOS in T peripheral helper cell development. Nat Commun 2024; 15:2150. [PMID: 38459032 PMCID: PMC10923805 DOI: 10.1038/s41467-024-46457-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2023] [Accepted: 02/26/2024] [Indexed: 03/10/2024] Open
Abstract
Fine-mapping and functional studies implicate rs117701653, a non-coding single nucleotide polymorphism in the CD28/CTLA4/ICOS locus, as a risk variant for rheumatoid arthritis and type 1 diabetes. Here, using DNA pulldown, mass spectrometry, genome editing and eQTL analysis, we establish that the disease-associated risk allele is functional, reducing affinity for the inhibitory chromosomal regulator SMCHD1 to enhance expression of inducible T-cell costimulator (ICOS) in memory CD4+ T cells from healthy donors. Higher ICOS expression is paralleled by an increase in circulating T peripheral helper (Tph) cells and, in rheumatoid arthritis patients, of blood and joint fluid Tph cells as well as circulating plasmablasts. Correspondingly, ICOS ligation and carriage of the rs117701653 risk allele accelerate T cell differentiation into CXCR5-PD-1high Tph cells producing IL-21 and CXCL13. Thus, mechanistic dissection of a functional non-coding variant in human autoimmunity discloses a previously undefined pathway through which ICOS regulates Tph development and abundance.
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Affiliation(s)
- Taehyeung Kim
- Division of Immunology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Marta Martínez-Bonet
- Division of Rheumatology, Inflammation, and Immunity, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Laboratory of Immune-regulation, Instituto de Investigación Sanitaria Gregorio Marañón, Madrid, Spain
| | - Qiang Wang
- Division of Immunology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Nicolaj Hackert
- Division of Immunology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Rheumatology, Department of Medicine V, Heidelberg University Hospital, Heidelberg, Germany
- Institute for Immunology, Heidelberg University Hospital, Heidelberg, Germany
| | - Jeffrey A Sparks
- Division of Rheumatology, Inflammation, and Immunity, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Yuriy Baglaenko
- Division of Rheumatology, Inflammation, and Immunity, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Byunghee Koh
- Division of Rheumatology, Inflammation, and Immunity, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Roxane Darbousset
- Division of Immunology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Raquel Laza-Briviesca
- Division of Immunology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Xiaoting Chen
- Center for Autoimmune Genomics and Etiology, Cincinnati Children's Medical Center, Cincinnati, OH, USA
| | - Vitor R C Aguiar
- Division of Immunology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Darren J Chiu
- Division of Rheumatology, Inflammation, and Immunity, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Harm-Jan Westra
- Division of Rheumatology, Inflammation, and Immunity, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Genetics, University Medical Center Groningen, University of Groningen, Hanzeplein 1, Groningen, The Netherlands
| | - Maria Gutierrez-Arcelus
- Division of Immunology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Matthew T Weirauch
- Center for Autoimmune Genomics and Etiology, Cincinnati Children's Medical Center, Cincinnati, OH, USA
- Divisions of Human Genetics, Biomedical Informatics, and Developmental Biology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - Soumya Raychaudhuri
- Division of Rheumatology, Inflammation, and Immunity, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Deepak A Rao
- Division of Rheumatology, Inflammation, and Immunity, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Peter A Nigrovic
- Division of Immunology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA.
- Division of Rheumatology, Inflammation, and Immunity, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
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3
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Wang XF, Vigouroux R, Syonov M, Baglaenko Y, Nikolakopoulou AM, Ringuette D, Rus H, DiStefano PV, Dufour S, Shabanzadeh AP, Lee S, Mueller BK, Charish J, Harada H, Fish JE, Wither J, Wälchli T, Cloutier JF, Zlokovic BV, Carlen PL, Monnier PP. The liver and muscle secreted HFE2-protein maintains central nervous system blood vessel integrity. Nat Commun 2024; 15:1037. [PMID: 38310100 PMCID: PMC10838306 DOI: 10.1038/s41467-024-45303-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2022] [Accepted: 01/19/2024] [Indexed: 02/05/2024] Open
Abstract
Liver failure causes breakdown of the Blood CNS Barrier (BCB) leading to damages of the Central-Nervous-System (CNS), however the mechanisms whereby the liver influences BCB-integrity remain elusive. One possibility is that the liver secretes an as-yet to be identified molecule(s) that circulate in the serum to directly promote BCB-integrity. To study BCB-integrity, we developed light-sheet imaging for three-dimensional analysis. We show that liver- or muscle-specific knockout of Hfe2/Rgmc induces BCB-breakdown, leading to accumulation of toxic-blood-derived fibrinogen in the brain, lower cortical neuron numbers, and behavioral deficits in mice. Soluble HFE2 competes with its homologue RGMa for binding to Neogenin, thereby blocking RGMa-induced downregulation of PDGF-B and Claudin-5 in endothelial cells, triggering BCB-disruption. HFE2 administration in female mice with experimental autoimmune encephalomyelitis, a model for multiple sclerosis, prevented paralysis and immune cell infiltration by inhibiting RGMa-mediated BCB alteration. This study has implications for the pathogenesis and potential treatment of diseases associated with BCB-dysfunction.
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Affiliation(s)
- Xue Fan Wang
- Krembil Research Institute, University Health Network, Krembil Discovery Tower, 60 Leonard St.,, Toronto, M5T 2O8, ON, Canada
- Institute of Biomedical and Biomaterial Engineering, University of Toronto, 1 King's College circle,, Toronto, M5S 1A8, ON, Canada
| | - Robin Vigouroux
- Krembil Research Institute, University Health Network, Krembil Discovery Tower, 60 Leonard St.,, Toronto, M5T 2O8, ON, Canada
- Department of Physiology, Faculty of Medicine, University of Toronto, 1 King's College circle,, Toronto, M5S 1A8, ON, Canada
| | - Michal Syonov
- Krembil Research Institute, University Health Network, Krembil Discovery Tower, 60 Leonard St.,, Toronto, M5T 2O8, ON, Canada
- Department of Physiology, Faculty of Medicine, University of Toronto, 1 King's College circle,, Toronto, M5S 1A8, ON, Canada
| | - Yuriy Baglaenko
- Krembil Research Institute, University Health Network, Krembil Discovery Tower, 60 Leonard St.,, Toronto, M5T 2O8, ON, Canada
| | - Angeliki M Nikolakopoulou
- Department of Physiology and Neuroscience, The Zilkha Neurogenetic Institute, Keck School of Medicine of the University of Southern California, Los Angeles, CA, USA
| | - Dene Ringuette
- Krembil Research Institute, University Health Network, Krembil Discovery Tower, 60 Leonard St.,, Toronto, M5T 2O8, ON, Canada
- Department of Physiology, Faculty of Medicine, University of Toronto, 1 King's College circle,, Toronto, M5S 1A8, ON, Canada
| | - Horea Rus
- University of Maryland, School of Medicine, Department of Neurology, Baltimore, MD, 21201, USA
| | - Peter V DiStefano
- Toronto General Hospital Research Institute, University Health Network, 101 College St. Rm 3-308, Toronto, M5L 1L7, ON, Canada
| | - Suzie Dufour
- Krembil Research Institute, University Health Network, Krembil Discovery Tower, 60 Leonard St.,, Toronto, M5T 2O8, ON, Canada
| | - Alireza P Shabanzadeh
- Krembil Research Institute, University Health Network, Krembil Discovery Tower, 60 Leonard St.,, Toronto, M5T 2O8, ON, Canada
| | - Seunggi Lee
- Krembil Research Institute, University Health Network, Krembil Discovery Tower, 60 Leonard St.,, Toronto, M5T 2O8, ON, Canada
- Department of Physiology, Faculty of Medicine, University of Toronto, 1 King's College circle,, Toronto, M5S 1A8, ON, Canada
| | | | - Jason Charish
- Krembil Research Institute, University Health Network, Krembil Discovery Tower, 60 Leonard St.,, Toronto, M5T 2O8, ON, Canada
- Department of Physiology, Faculty of Medicine, University of Toronto, 1 King's College circle,, Toronto, M5S 1A8, ON, Canada
| | - Hidekiyo Harada
- Krembil Research Institute, University Health Network, Krembil Discovery Tower, 60 Leonard St.,, Toronto, M5T 2O8, ON, Canada
| | - Jason E Fish
- Toronto General Hospital Research Institute, University Health Network, 101 College St. Rm 3-308, Toronto, M5L 1L7, ON, Canada
| | - Joan Wither
- Krembil Research Institute, University Health Network, Krembil Discovery Tower, 60 Leonard St.,, Toronto, M5T 2O8, ON, Canada
| | - Thomas Wälchli
- Krembil Research Institute, University Health Network, Krembil Discovery Tower, 60 Leonard St.,, Toronto, M5T 2O8, ON, Canada
- Group of CNS Angiogenesis and Neurovascular Link, and Physician-Scientist Program, Institute for Regenerative Medicine, Neuroscience Center Zurich, and Division of Neurosurgery, University and University Hospital Zurich, Zurich, Switzerland
- Division of Neurosurgery, University Hospital Zurich, Zurich, Switzerland
- Division of Neurosurgery, Department of Surgery, Toronto Western Hospital, University Health Network, Toronto, Canada
| | - Jean-François Cloutier
- The Neuro - Montreal Neurological Institute and Hospital, 3801 Rue Université, Montréal, QC, H3A 2B4, Canada
| | - Berislav V Zlokovic
- Department of Physiology and Neuroscience, The Zilkha Neurogenetic Institute, Keck School of Medicine of the University of Southern California, Los Angeles, CA, USA
| | - Peter L Carlen
- Krembil Research Institute, University Health Network, Krembil Discovery Tower, 60 Leonard St.,, Toronto, M5T 2O8, ON, Canada
- Institute of Biomedical and Biomaterial Engineering, University of Toronto, 1 King's College circle,, Toronto, M5S 1A8, ON, Canada
- Department of Physiology and Neuroscience, The Zilkha Neurogenetic Institute, Keck School of Medicine of the University of Southern California, Los Angeles, CA, USA
| | - Philippe P Monnier
- Krembil Research Institute, University Health Network, Krembil Discovery Tower, 60 Leonard St.,, Toronto, M5T 2O8, ON, Canada.
- Institute of Biomedical and Biomaterial Engineering, University of Toronto, 1 King's College circle,, Toronto, M5S 1A8, ON, Canada.
- Department of Ophthalmology and Vision Sciences, Faculty of Medicine, University of Toronto, 340 College St.,, ON, Toronto, M5T 3A9, Canada.
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4
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Xiao Q, Mears J, Nathan A, Ishigaki K, Baglaenko Y, Lim N, Cooney LA, Harris KM, Anderson MS, Fox DA, Smilek DE, Krueger JG, Raychaudhuri S. Immunosuppression causes dynamic changes in expression QTLs in psoriatic skin. Nat Commun 2023; 14:6268. [PMID: 37805522 PMCID: PMC10560299 DOI: 10.1038/s41467-023-41984-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2022] [Accepted: 09/25/2023] [Indexed: 10/09/2023] Open
Abstract
Psoriasis is a chronic, systemic inflammatory condition primarily affecting skin. While the role of the immune compartment (e.g., T cells) is well established, the changes in the skin compartment are more poorly understood. Using longitudinal skin biopsies (n = 375) from the "Psoriasis Treatment with Abatacept and Ustekinumab: A Study of Efficacy"(PAUSE) clinical trial (n = 101), we report 953 expression quantitative trait loci (eQTLs). Of those, 116 eQTLs have effect sizes that were modulated by local skin inflammation (eQTL interactions). By examining these eQTL genes (eGenes), we find that most are expressed in the skin tissue compartment, and a subset overlap with the NRF2 pathway. Indeed, the strongest eQTL interaction signal - rs1491377616-LCE3C - links a psoriasis risk locus with a gene specifically expressed in the epidermis. This eQTL study highlights the potential to use biospecimens from clinical trials to discover in vivo eQTL interactions with therapeutically relevant environmental variables.
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Affiliation(s)
- Qian Xiao
- Center for Data Sciences, Brigham and Women's Hospital, Boston, MA, USA
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Joseph Mears
- Center for Data Sciences, Brigham and Women's Hospital, Boston, MA, USA
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Aparna Nathan
- Center for Data Sciences, Brigham and Women's Hospital, Boston, MA, USA
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Kazuyoshi Ishigaki
- Center for Data Sciences, Brigham and Women's Hospital, Boston, MA, USA
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Laboratory for Human Immunogenetics, RIKEN Center for Integrative Medical Sciences, Yokohama City, Kanagawa, Japan
| | - Yuriy Baglaenko
- Center for Data Sciences, Brigham and Women's Hospital, Boston, MA, USA
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Noha Lim
- Immune Tolerance Network, Diabetes Center, University of California, San Francisco, San Francisco, CA, USA
| | - Laura A Cooney
- Immune Tolerance Network, Diabetes Center, University of California, San Francisco, San Francisco, CA, USA
- Division of Rheumatology, Department of Internal Medicine and Clinical Autoimmunity Center of Excellence, University of Michigan, Ann Arbor, MI, USA
| | - Kristina M Harris
- Immune Tolerance Network, Diabetes Center, University of California, San Francisco, San Francisco, CA, USA
| | - Mark S Anderson
- Immune Tolerance Network, Diabetes Center, University of California, San Francisco, San Francisco, CA, USA
| | - David A Fox
- Division of Rheumatology, Department of Internal Medicine and Clinical Autoimmunity Center of Excellence, University of Michigan, Ann Arbor, MI, USA
| | - Dawn E Smilek
- Immune Tolerance Network, Diabetes Center, University of California, San Francisco, San Francisco, CA, USA
| | - James G Krueger
- Laboratory for Investigative Dermatology, The Rockefeller University, New York, NY, USA
| | - Soumya Raychaudhuri
- Center for Data Sciences, Brigham and Women's Hospital, Boston, MA, USA.
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA.
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.
- Centre for Genetics and Genomics Versus Arthritis, Centre for Musculoskeletal Research, The University of Manchester, Manchester, UK.
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5
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Ferri DM, Nassar C, Manion KP, Kim M, Baglaenko Y, Muñoz-Grajales C, Wither JE. Elevated Levels of Interferon-α Act Directly on B Cells to Breach Multiple Tolerance Mechanisms Promoting Autoantibody Production. Arthritis Rheumatol 2023; 75:1542-1555. [PMID: 36807718 DOI: 10.1002/art.42482] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2021] [Revised: 01/16/2023] [Accepted: 02/14/2023] [Indexed: 02/23/2023]
Abstract
OBJECTIVE Elevated levels of serum interferon-α (IFNα) and the disruption of B cell tolerance are central to systemic lupus erythematosus (SLE) immunopathogenesis; however, the relationship between these 2 processes remains unclear. The purpose of this study was to investigate the impact of elevated IFNα levels on B cell tolerance mechanisms in vivo and determine whether any changes observed were due to the direct effect of IFNα on B cells. METHODS Two classical mouse models of B cell tolerance were used in conjunction with an adenoviral vector encoding IFNα to mimic the sustained elevations of IFNα seen in SLE. The role of B cell IFNα signaling, T cells, and Myd88 signaling was determined using B cell-specific IFNα receptor-knockout, CD4+ T cell-depleted, or Myd88-knockout mice, respectively. Flow cytometry, enzyme-linked immunosorbent assay, real-time quantitative polymerase chain reaction, and cell cultures were used to study the effects of elevated IFNα on the immunologic phenotype. RESULTS Elevation of serum IFNα disrupts multiple B cell tolerance mechanisms and leads to autoantibody production. This disruption was dependent upon B cell expression of IFNα receptor. Many of the IFNα-mediated alterations also required the presence of CD4+ T cells as well as Myd88, suggesting that IFNα acts directly on B cells to modify their response to Myd88 signaling and their ability to interact with T cells. CONCLUSION The results provide evidence that elevated IFNα levels act directly on B cells to facilitate autoantibody production and further highlight the importance of IFN signaling as a potential therapeutic target in SLE.
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Affiliation(s)
- Dario M Ferri
- Schroeder Arthritis Institute, Krembil Research Institute, University Health Network, Toronto, Ontario, Canada
| | - Carol Nassar
- Schroeder Arthritis Institute, Krembil Research Institute, University Health Network, Toronto, Ontario, Canada
| | - Kieran P Manion
- Schroeder Arthritis Institute, Krembil Research Institute, University Health Network, Toronto, Ontario, Canada
| | - Michael Kim
- Schroeder Arthritis Institute, Krembil Research Institute, University Health Network, Toronto, Ontario, Canada
| | - Yuriy Baglaenko
- Schroeder Arthritis Institute, Krembil Research Institute, University Health Network, Toronto, Ontario, Canada
| | - Carolina Muñoz-Grajales
- Schroeder Arthritis Institute, Krembil Research Institute, University Health Network, Toronto, Ontario, Canada
| | - Joan E Wither
- Schroeder Arthritis Institute, Krembil Research Institute, and Division of Rheumatology, Schroeder Arthritis Institute, University Health Network, and Departments of Medicine and Immunology, University of Toronto, Toronto, Ontario, Canada
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6
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Nathan A, Asgari S, Ishigaki K, Valencia C, Amariuta T, Luo Y, Beynor JI, Baglaenko Y, Suliman S, Price AL, Lecca L, Murray MB, Moody DB, Raychaudhuri S. Single-cell eQTL models reveal dynamic T cell state dependence of disease loci. Nature 2022; 606:120-128. [PMID: 35545678 PMCID: PMC9842455 DOI: 10.1038/s41586-022-04713-1] [Citation(s) in RCA: 56] [Impact Index Per Article: 28.0] [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: 08/17/2021] [Accepted: 03/31/2022] [Indexed: 02/02/2023]
Abstract
Non-coding genetic variants may cause disease by modulating gene expression. However, identifying these expression quantitative trait loci (eQTLs) is complicated by differences in gene regulation across fluid functional cell states within cell types. These states-for example, neurotransmitter-driven programs in astrocytes or perivascular fibroblast differentiation-are obscured in eQTL studies that aggregate cells1,2. Here we modelled eQTLs at single-cell resolution in one complex cell type: memory T cells. Using more than 500,000 unstimulated memory T cells from 259 Peruvian individuals, we show that around one-third of 6,511 cis-eQTLs had effects that were mediated by continuous multimodally defined cell states, such as cytotoxicity and regulatory capacity. In some loci, independent eQTL variants had opposing cell-state relationships. Autoimmune variants were enriched in cell-state-dependent eQTLs, including risk variants for rheumatoid arthritis near ORMDL3 and CTLA4; this indicates that cell-state context is crucial to understanding potential eQTL pathogenicity. Moreover, continuous cell states explained more variation in eQTLs than did conventional discrete categories, such as CD4+ versus CD8+, suggesting that modelling eQTLs and cell states at single-cell resolution can expand insight into gene regulation in functionally heterogeneous cell types.
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Affiliation(s)
- Aparna Nathan
- Center for Data Sciences, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Samira Asgari
- Center for Data Sciences, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Kazuyoshi Ishigaki
- Center for Data Sciences, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Cristian Valencia
- Center for Data Sciences, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Tiffany Amariuta
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Yang Luo
- Center for Data Sciences, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Jessica I Beynor
- Center for Data Sciences, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Yuriy Baglaenko
- Center for Data Sciences, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Sara Suliman
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Alkes L Price
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Leonid Lecca
- Department of Global Health and Social Medicine, Harvard Medical School, Boston, MA, USA
- Socios En Salud Sucursal Peru, Lima, Peru
| | - Megan B Murray
- Department of Global Health and Social Medicine, Harvard Medical School, Boston, MA, USA
- Division of Global Health Equity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - D Branch Moody
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Soumya Raychaudhuri
- Center for Data Sciences, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.
- Centre for Genetics and Genomics Versus Arthritis, Manchester Academic Health Science Centre, University of Manchester, Manchester, UK.
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7
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Baglaenko Y, Macfarlane D, Marson A, Nigrovic PA, Raychaudhuri S. Genome editing to define the function of risk loci and variants in rheumatic disease. Nat Rev Rheumatol 2021; 17:462-474. [PMID: 34188205 PMCID: PMC10782829 DOI: 10.1038/s41584-021-00637-8] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [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] [Accepted: 05/20/2021] [Indexed: 02/06/2023]
Abstract
Discoveries in human genetic studies have revolutionized our understanding of complex rheumatic and autoimmune diseases, including the identification of hundreds of genetic loci and single nucleotide polymorphisms that potentially predispose individuals to disease. However, in most cases, the exact disease-causing variants and their mechanisms of action remain unresolved. Functional follow-up of these findings is most challenging for genomic variants that are in non-coding genomic regions, where the large majority of common disease-associated variants are located, and/or that probably affect disease progression via cell type-specific gene regulation. To deliver on the therapeutic promise of human genetic studies, defining the mechanisms of action of these alleles is essential. Genome editing technology, such as CRISPR-Cas, has created a vast toolbox for targeted genetic and epigenetic modifications that presents unprecedented opportunities to decipher disease-causing loci, genes and variants in autoimmunity. In this Review, we discuss the past 5-10 years of progress in resolving the mechanisms underlying rheumatic disease-associated alleles, with an emphasis on how genomic editing techniques can enable targeted dissection and mechanistic studies of causal autoimmune risk variants.
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Affiliation(s)
- Yuriy Baglaenko
- Center for Data Sciences, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, USA
| | - Dana Macfarlane
- Center for Data Sciences, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Alexander Marson
- Gladstone Institutes, San Francisco, CA, USA
- Department of Medicine, University of California, San Francisco, CA, USA
- Department of Microbiology and Immunology, University of California, San Francisco, CA, USA
- Innovative Genomics Institute, University of California, Berkeley, CA, USA
- Rosalind Russell/Ephraim P. Engleman Rheumatology Research Center, University of California, San Francisco, San Francisco, CA, USA
- Parker Institute for Cancer Immunotherapy, San Francisco, CA, USA
- Chan Zuckerberg Biohub, San Francisco, CA, USA
| | - Peter A Nigrovic
- Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Division of Immunology, Boston Children's Hospital, Department of Pediatrics, Harvard Medical School, Boston, MA, USA
| | - Soumya Raychaudhuri
- Center for Data Sciences, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
- Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA.
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, USA.
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.
- Faculty of Medical and Human Sciences, University of Manchester, Manchester, UK.
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8
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Nathan A, Beynor JI, Baglaenko Y, Suliman S, Ishigaki K, Asgari S, Huang CC, Luo Y, Zhang Z, Lopez K, Lindestam Arlehamn CS, Ernst JD, Jimenez J, Calderón RI, Lecca L, Van Rhijn I, Moody DB, Murray MB, Raychaudhuri S. Multimodally profiling memory T cells from a tuberculosis cohort identifies cell state associations with demographics, environment and disease. Nat Immunol 2021; 22:781-793. [PMID: 34031617 PMCID: PMC8162307 DOI: 10.1038/s41590-021-00933-1] [Citation(s) in RCA: 37] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2020] [Accepted: 04/15/2021] [Indexed: 12/27/2022]
Abstract
Multimodal T cell profiling can enable more precise characterization of elusive cell states underlying disease. Here, we integrated single-cell RNA and surface protein data from 500,089 memory T cells to define 31 cell states from 259 individuals in a Peruvian tuberculosis (TB) progression cohort. At immune steady state >4 years after infection and disease resolution, we found that, after accounting for significant effects of age, sex, season and genetic ancestry on T cell composition, a polyfunctional type 17 helper T (TH17) cell-like effector state was reduced in abundance and function in individuals who previously progressed from Mycobacterium tuberculosis (M.tb) infection to active TB disease. These cells are capable of responding to M.tb peptides. Deconvoluting this state-uniquely identifiable with multimodal analysis-from public data demonstrated that its depletion may precede and persist beyond active disease. Our study demonstrates the power of integrative multimodal single-cell profiling to define cell states relevant to disease and other traits.
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Affiliation(s)
- Aparna Nathan
- Center for Data Sciences, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Jessica I Beynor
- Center for Data Sciences, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Yuriy Baglaenko
- Center for Data Sciences, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Sara Suliman
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Kazuyoshi Ishigaki
- Center for Data Sciences, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Samira Asgari
- Center for Data Sciences, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Chuan-Chin Huang
- Department of Global Health and Social Medicine, Harvard Medical School, Boston, MA, USA
- Division of Global Health Equity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Yang Luo
- Center for Data Sciences, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Zibiao Zhang
- Department of Global Health and Social Medicine, Harvard Medical School, Boston, MA, USA
- Division of Global Health Equity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Kattya Lopez
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Socios En Salud Sucursal Peru, Lima, Peru
| | | | - Joel D Ernst
- Division of Experimental Medicine, Department of Medicine, University of California, San Francisco, San Francisco, CA, USA
| | | | - Roger I Calderón
- Socios En Salud Sucursal Peru, Lima, Peru
- Programa Acadêmico de Tuberculose, Faculdade de Medicina, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil
| | - Leonid Lecca
- Department of Global Health and Social Medicine, Harvard Medical School, Boston, MA, USA
- Socios En Salud Sucursal Peru, Lima, Peru
| | - Ildiko Van Rhijn
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Department of Infectious Diseases and Immunology, Faculty of Veterinary Medicine, Utrecht University, Utrecht, the Netherlands
| | - D Branch Moody
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Megan B Murray
- Department of Global Health and Social Medicine, Harvard Medical School, Boston, MA, USA
- Division of Global Health Equity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Soumya Raychaudhuri
- Center for Data Sciences, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.
- Centre for Genetics and Genomics Versus Arthritis, Manchester Academic Health Science Centre, University of Manchester, Manchester, UK.
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9
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Gracey E, Hromadová D, Lim M, Qaiyum Z, Zeng M, Yao Y, Srinath A, Baglaenko Y, Yeremenko N, Westlin W, Masse C, Müller M, Strobl B, Miao W, Inman RD. TYK2 inhibition reduces type 3 immunity and modifies disease progression in murine spondyloarthritis. J Clin Invest 2020; 130:1863-1878. [PMID: 32149730 PMCID: PMC7108927 DOI: 10.1172/jci126567] [Citation(s) in RCA: 35] [Impact Index Per Article: 8.8] [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: 12/03/2018] [Accepted: 01/14/2020] [Indexed: 12/17/2022] Open
Abstract
Spondyloarthritis (SpA) represents a family of inflammatory diseases of the spine and peripheral joints. Ankylosing spondylitis (AS) is the prototypic form of SpA in which progressive disease can lead to fusion of the spine. Therapeutically, knowledge of type 3 immunity has translated into the development of IL-23– and IL-17A–blocking antibodies for the treatment of SpA. Despite being able to provide symptomatic control, the current biologics do not prevent the fusion of joints in AS patients. Thus, there is an unmet need for disease-modifying drugs. Genetic studies have linked the Janus kinase TYK2 to AS. TYK2 is a mediator of type 3 immunity through intracellular signaling of IL-23. Here, we describe and characterize a potentially novel small-molecule inhibitor of TYK2 that blocked IL-23 signaling in vitro and inhibited disease progression in animal models of SpA. The effect of the inhibitor appears to be TYK2 specific, using TYK2-inactive mice, which further revealed a duality in the induction of IL-17A and IL-22 by IL-23. Specifically, IL-22 production was TYK2/JAK2/STAT3 dependent, while IL-17A was mostly JAK2 dependent. Finally, we examined the effects of AS-associated TYK2 SNPs on TYK2 expression and function and correlated them with AS disease progression. This work provides evidence that TYK2 inhibitors have great potential as an orally delivered therapeutic for SpA.
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Affiliation(s)
- Eric Gracey
- Department of Immunology, University of Toronto, Toronto, Ontario, Canada.,Genetics and Development, Krembil Research Institute, University Health Network, Toronto, Ontario, Canada.,Spondylitis Program, Toronto Western Hospital, University Health Network, Toronto, Ontario, Canada
| | - Dominika Hromadová
- Institute of Animal Breeding and Genetics, University of Veterinary Medicine, Vienna, Austria
| | - Melissa Lim
- Genetics and Development, Krembil Research Institute, University Health Network, Toronto, Ontario, Canada.,Spondylitis Program, Toronto Western Hospital, University Health Network, Toronto, Ontario, Canada
| | - Zoya Qaiyum
- Genetics and Development, Krembil Research Institute, University Health Network, Toronto, Ontario, Canada.,Spondylitis Program, Toronto Western Hospital, University Health Network, Toronto, Ontario, Canada
| | - Michael Zeng
- Genetics and Development, Krembil Research Institute, University Health Network, Toronto, Ontario, Canada.,Spondylitis Program, Toronto Western Hospital, University Health Network, Toronto, Ontario, Canada
| | - Yuchen Yao
- Department of Immunology, University of Toronto, Toronto, Ontario, Canada.,Genetics and Development, Krembil Research Institute, University Health Network, Toronto, Ontario, Canada.,Spondylitis Program, Toronto Western Hospital, University Health Network, Toronto, Ontario, Canada
| | - Archita Srinath
- Genetics and Development, Krembil Research Institute, University Health Network, Toronto, Ontario, Canada.,Spondylitis Program, Toronto Western Hospital, University Health Network, Toronto, Ontario, Canada
| | - Yuriy Baglaenko
- Divisions of Genetics and Rheumatology, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Natalia Yeremenko
- Division of Clinical Immunology and Rheumatology, Department of Experimental Immunology, Academic Medical Center, Amsterdam, Netherlands
| | | | - Craig Masse
- Nimbus Therapeutics, Cambridge, Massachusetts, USA
| | - Mathias Müller
- Institute of Animal Breeding and Genetics, University of Veterinary Medicine, Vienna, Austria
| | - Birgit Strobl
- Institute of Animal Breeding and Genetics, University of Veterinary Medicine, Vienna, Austria
| | - Wenyan Miao
- Nimbus Therapeutics, Cambridge, Massachusetts, USA
| | - Robert D Inman
- Department of Immunology, University of Toronto, Toronto, Ontario, Canada.,Genetics and Development, Krembil Research Institute, University Health Network, Toronto, Ontario, Canada.,Spondylitis Program, Toronto Western Hospital, University Health Network, Toronto, Ontario, Canada
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10
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Manion KP, Baglaenko Y, Chang NH, Talaei N, Wither JE. Impaired B cell anergy is not sufficient to breach tolerance to nuclear antigen in Vκ8/3H9 lupus-prone mice. PLoS One 2020; 15:e0236664. [PMID: 32722684 PMCID: PMC7386585 DOI: 10.1371/journal.pone.0236664] [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] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2020] [Accepted: 07/10/2020] [Indexed: 11/18/2022] Open
Abstract
Background Systemic lupus erythematosus (SLE) is a severe autoimmune disease in which immune tolerance defects drive production of pathogenic anti-nuclear autoantibodies. Anergic B cells are considered a potential source of these autoantibodies due to their autoreactivity and overrepresentation in SLE patients. Studies of lupus-prone mice have shown that genetic defects mediating autoimmunity can breach B cell anergy, but how this breach occurs with regards to endogenous nuclear antigen remains unclear. We investigated whether B and T cell defects in congenic mice (c1) derived from the lupus-prone New Zealand Black strain can breach tolerance to nuclear self-antigen in the presence of knock-in genes (Vκ8/3H9; dKI) that generate a ssDNA-reactive, anergic B cell population. Methods Flow cytometry was used to assess splenic B and T cells from 8-month-old c1 dKI mice and serum autoantibodies were measured by ELISA. dKI B cells stimulated in vitro with anti-IgM were assessed for proliferation and activation by examining CFSE decay and CD86. Cytokine-producing T cells were identified by flow cytometry following culture of dKI splenocytes with PMA and ionomycin. dKI B cells from 6-8-week-old mice were adoptively transferred into 4-month-old wild type recipients and assessed after 7 days via flow cytometry and immunofluorescence microscopy. Results c1 dKI mice exhibited B cell proliferation indicative of impaired anergy, but had attenuated autoantibodies and germinal centres compared to wild type littermates. This attenuation appeared to stem from a decrease in PD-1hi T helper cells in the dKI strains, as c1 dKI B cells were recruited to germinal centres when adoptively transferred into c1 wild type mice. Conclusion Anergic, DNA-specific autoreactive B cells only seem to drive profound autoimmunity in the presence of concomitant defects in the T cell subsets that support high-affinity plasma cell production.
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Affiliation(s)
- Kieran P. Manion
- Krembil Research Institute, University Health Network, Toronto, Ontario, Canada
| | - Yuriy Baglaenko
- Krembil Research Institute, University Health Network, Toronto, Ontario, Canada
| | - Nan-Hua Chang
- Krembil Research Institute, University Health Network, Toronto, Ontario, Canada
| | - Nafiseh Talaei
- Krembil Research Institute, University Health Network, Toronto, Ontario, Canada
| | - Joan E. Wither
- Krembil Research Institute, University Health Network, Toronto, Ontario, Canada
- Department of Medicine and Immunology, University of Toronto, Toronto, Ontario, Canada
- Division of Rheumatology, University Health Network, Toronto, Ontario, Canada
- * E-mail:
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11
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Gutierrez-Arcelus M, Baglaenko Y, Arora J, Hannes S, Luo Y, Amariuta T, Teslovich N, Rao DA, Ermann J, Jonsson AH, Navarrete C, Rich SS, Taylor KD, Rotter JI, Gregersen PK, Esko T, Brenner MB, Raychaudhuri S. Allele-specific expression changes dynamically during T cell activation in HLA and other autoimmune loci. Nat Genet 2020; 52:247-253. [PMID: 32066938 PMCID: PMC7135372 DOI: 10.1038/s41588-020-0579-4] [Citation(s) in RCA: 60] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2019] [Accepted: 01/13/2020] [Indexed: 11/12/2022]
Abstract
Genetic studies have revealed that autoimmune susceptibility variants are over-represented in memory CD4+ T cell regulatory elements1-3. Understanding how genetic variation affects gene expression in different T cell physiological states is essential for deciphering genetic mechanisms of autoimmunity4,5. Here, we characterized the dynamics of genetic regulatory effects at eight time points during memory CD4+ T cell activation with high-depth RNA-seq in healthy individuals. We discovered widespread, dynamic allele-specific expression across the genome, where the balance of alleles changes over time. These genes were enriched fourfold within autoimmune loci. We found pervasive dynamic regulatory effects within six HLA genes. HLA-DQB1 alleles had one of three distinct transcriptional regulatory programs. Using CRISPR-Cas9 genomic editing we demonstrated that a promoter variant is causal for T cell-specific control of HLA-DQB1 expression. Our study shows that genetic variation in cis-regulatory elements affects gene expression in a manner dependent on lymphocyte activation status, contributing to the interindividual complexity of immune responses.
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Affiliation(s)
- Maria Gutierrez-Arcelus
- Center for Data Sciences, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Division of Rheumatology, Inflammation and Immunity, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, USA
| | - Yuriy Baglaenko
- Center for Data Sciences, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Division of Rheumatology, Inflammation and Immunity, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, USA
| | - Jatin Arora
- Center for Data Sciences, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Division of Rheumatology, Inflammation and Immunity, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, USA
- Max Planck Institute for Evolutionary Biology, Plön, Germany
| | - Susan Hannes
- Center for Data Sciences, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Division of Rheumatology, Inflammation and Immunity, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, USA
| | - Yang Luo
- Center for Data Sciences, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Division of Rheumatology, Inflammation and Immunity, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, USA
| | - Tiffany Amariuta
- Center for Data Sciences, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Division of Rheumatology, Inflammation and Immunity, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, USA
- Graduate School of Arts and Sciences, Harvard University, Cambridge, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Nikola Teslovich
- Center for Data Sciences, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Division of Rheumatology, Inflammation and Immunity, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Deepak A Rao
- Division of Rheumatology, Inflammation and Immunity, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Joerg Ermann
- Division of Rheumatology, Inflammation and Immunity, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - A Helena Jonsson
- Division of Rheumatology, Inflammation and Immunity, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Cristina Navarrete
- Division of Infection and Immunity, University College London, London, UK
| | - Stephen S Rich
- Center for Public Health Genomics, University of Virginia School of Medicine, Charlottesville, VA, USA
| | - Kent D Taylor
- The Institute for Translational Genomics and Population Sciences, Division of Genomic Outcomes, Department of Pediatrics, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Jerome I Rotter
- The Institute for Translational Genomics and Population Sciences, Division of Genomic Outcomes, Department of Pediatrics, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Peter K Gregersen
- The Robert S. Boas Center for Genomics and Human Genetics, Feinstein Institute for Medical Research, Northwell Health, Manhasset, NY, USA
| | - Tonu Esko
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, USA
- Estonian Genome Center, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Michael B Brenner
- Division of Rheumatology, Inflammation and Immunity, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Soumya Raychaudhuri
- Center for Data Sciences, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
- Division of Rheumatology, Inflammation and Immunity, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, USA.
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.
- Centre for Genetics and Genomics Versus Arthritis, Division of Musculoskeletal and Dermatological Sciences, School of Biological Sciences, University of Manchester, Manchester, UK.
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12
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Korsunsky I, Millard N, Fan J, Slowikowski K, Zhang F, Wei K, Baglaenko Y, Brenner M, Loh PR, Raychaudhuri S. Fast, sensitive and accurate integration of single-cell data with Harmony. Nat Methods 2019; 16:1289-1296. [PMID: 31740819 PMCID: PMC6884693 DOI: 10.1038/s41592-019-0619-0] [Citation(s) in RCA: 2564] [Impact Index Per Article: 512.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2018] [Accepted: 09/06/2019] [Indexed: 12/18/2022]
Abstract
The emerging diversity of single-cell RNA-seq datasets allows for the full transcriptional characterization of cell types across a wide variety of biological and clinical conditions. However, it is challenging to analyze them together, particularly when datasets are assayed with different technologies, because biological and technical differences are interspersed. We present Harmony (https://github.com/immunogenomics/harmony), an algorithm that projects cells into a shared embedding in which cells group by cell type rather than dataset-specific conditions. Harmony simultaneously accounts for multiple experimental and biological factors. In six analyses, we demonstrate the superior performance of Harmony to previously published algorithms while requiring fewer computational resources. Harmony enables the integration of ~106 cells on a personal computer. We apply Harmony to peripheral blood mononuclear cells from datasets with large experimental differences, five studies of pancreatic islet cells, mouse embryogenesis datasets and the integration of scRNA-seq with spatial transcriptomics data.
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Affiliation(s)
- Ilya Korsunsky
- Center for Data Sciences, Brigham and Women's Hospital, Boston, MA, USA
- Divisions of Genetics and Rheumatology, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Nghia Millard
- Center for Data Sciences, Brigham and Women's Hospital, Boston, MA, USA
- Divisions of Genetics and Rheumatology, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Jean Fan
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
| | - Kamil Slowikowski
- Center for Data Sciences, Brigham and Women's Hospital, Boston, MA, USA
- Divisions of Genetics and Rheumatology, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Fan Zhang
- Center for Data Sciences, Brigham and Women's Hospital, Boston, MA, USA
- Divisions of Genetics and Rheumatology, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Kevin Wei
- Divisions of Genetics and Rheumatology, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Yuriy Baglaenko
- Center for Data Sciences, Brigham and Women's Hospital, Boston, MA, USA
- Divisions of Genetics and Rheumatology, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Michael Brenner
- Divisions of Genetics and Rheumatology, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Po-Ru Loh
- Center for Data Sciences, Brigham and Women's Hospital, Boston, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Soumya Raychaudhuri
- Center for Data Sciences, Brigham and Women's Hospital, Boston, MA, USA.
- Divisions of Genetics and Rheumatology, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Versus Arthritis Centre for Genetics and Genomics, Centre for Musculoskeletal Research, Manchester Academic Health Science Centre, The University of Manchester, Manchester, UK.
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13
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Luo Y, Suliman S, Asgari S, Amariuta T, Baglaenko Y, Martínez-Bonet M, Ishigaki K, Gutierrez-Arcelus M, Calderon R, Lecca L, León SR, Jimenez J, Yataco R, Contreras C, Galea JT, Becerra M, Nejentsev S, Nigrovic PA, Moody DB, Murray MB, Raychaudhuri S. Early progression to active tuberculosis is a highly heritable trait driven by 3q23 in Peruvians. Nat Commun 2019; 10:3765. [PMID: 31434886 PMCID: PMC6704092 DOI: 10.1038/s41467-019-11664-1] [Citation(s) in RCA: 31] [Impact Index Per Article: 6.2] [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] [Subscribe] [Scholar Register] [Received: 08/28/2018] [Accepted: 07/24/2019] [Indexed: 12/13/2022] Open
Abstract
Of the 1.8 billion people worldwide infected with Mycobacterium tuberculosis, 5-15% will develop active tuberculosis (TB). Approximately half will progress to active TB within the first 18 months after infection, presumably because they fail to mount an effective initial immune response. Here, in a genome-wide genetic study of early TB progression, we genotype 4002 active TB cases and their household contacts in Peru. We quantify genetic heritability ([Formula: see text]) of early TB progression to be 21.2% (standard error 0.08). This suggests TB progression has a strong genetic basis, and is comparable to traits with well-established genetic bases. We identify a novel association between early TB progression and variants located in a putative enhancer region on chromosome 3q23 (rs73226617, OR = 1.18; P = 3.93 × 10-8). With in silico and in vitro analyses we identify rs73226617 or rs148722713 as the likely functional variant and ATP1B3 as a potential causal target gene with monocyte specific function.
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Affiliation(s)
- Yang Luo
- Division of Rheumatology, Inflammation and Immunity, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Division of Genetics, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Center for Data Sciences, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Sara Suliman
- Division of Rheumatology, Inflammation and Immunity, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Samira Asgari
- Division of Rheumatology, Inflammation and Immunity, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Division of Genetics, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Center for Data Sciences, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Tiffany Amariuta
- Division of Rheumatology, Inflammation and Immunity, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Division of Genetics, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Center for Data Sciences, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Graduate School of Arts and Sciences, Harvard University, Cambridge, MA, 02138, USA
| | - Yuriy Baglaenko
- Division of Rheumatology, Inflammation and Immunity, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Division of Genetics, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Center for Data Sciences, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Marta Martínez-Bonet
- Division of Rheumatology, Inflammation and Immunity, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Kazuyoshi Ishigaki
- Division of Rheumatology, Inflammation and Immunity, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Division of Genetics, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Center for Data Sciences, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Maria Gutierrez-Arcelus
- Division of Rheumatology, Inflammation and Immunity, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Division of Genetics, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Center for Data Sciences, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | | | | | | | | | | | | | - Jerome T Galea
- School of Social Work, University of South Florida, Tampa, FL, USA
| | - Mercedes Becerra
- Department of Global Health and Social Medicine, and Division of Global Health Equity, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Sergey Nejentsev
- Department of Medicine, University of Cambridge, Cambridge, UK
- Department of Molecular Cell Biology and Immunology, Amsterdam University Medical Centers, Amsterdam, Netherlands
| | - Peter A Nigrovic
- Division of Rheumatology, Inflammation and Immunity, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Division of Immunology, Boston Children's Hospital, Boston, MA, USA
| | - D Branch Moody
- Division of Rheumatology, Inflammation and Immunity, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Megan B Murray
- Department of Global Health and Social Medicine, and Division of Global Health Equity, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
| | - Soumya Raychaudhuri
- Division of Rheumatology, Inflammation and Immunity, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
- Division of Genetics, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
- Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.
- Center for Data Sciences, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
- Arthritis Research UK Centre for Genetics and Genomics, Manchester Academic Health Science Centre, University of Manchester, Manchester, UK.
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14
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Nathan A, Baglaenko Y, Fonseka CY, Beynor JI, Raychaudhuri S. Multimodal single-cell approaches shed light on T cell heterogeneity. Curr Opin Immunol 2019; 61:17-25. [PMID: 31430664 DOI: 10.1016/j.coi.2019.07.002] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2019] [Revised: 07/03/2019] [Accepted: 07/14/2019] [Indexed: 01/13/2023]
Abstract
Single-cell methods have revolutionized the study of T cell biology by enabling the identification and characterization of individual cells. This has led to a deeper understanding of T cell heterogeneity by generating functionally relevant measurements - like gene expression, surface markers, chromatin accessibility, T cell receptor sequences - in individual cells. While these methods are independently valuable, they can be augmented when applied jointly, either on separate cells from the same sample or on the same cells. Multimodal approaches are already being deployed to characterize T cells in diverse disease contexts and demonstrate the value of having multiple insights into a cell's function. But, these data sets pose new statistical challenges for integration and joint analysis.
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Affiliation(s)
- Aparna Nathan
- Center for Data Sciences, Brigham and Women's Hospital, Boston, MA 02115, USA; Division of Genetics, Department of Medicine, Harvard Medical School, Brigham and Women's Hospital, Boston, MA 02115, USA; Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Harvard Medical School, Brigham and Women's Hospital, Boston, MA 02115, USA; Department of Biomedical Informatics, Harvard Medical School, Boston, MA 02115 USA; Program in Medical and Population Genetics, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142, USA
| | - Yuriy Baglaenko
- Center for Data Sciences, Brigham and Women's Hospital, Boston, MA 02115, USA; Division of Genetics, Department of Medicine, Harvard Medical School, Brigham and Women's Hospital, Boston, MA 02115, USA; Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Harvard Medical School, Brigham and Women's Hospital, Boston, MA 02115, USA; Program in Medical and Population Genetics, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142, USA
| | - Chamith Y Fonseka
- Center for Data Sciences, Brigham and Women's Hospital, Boston, MA 02115, USA; Division of Genetics, Department of Medicine, Harvard Medical School, Brigham and Women's Hospital, Boston, MA 02115, USA; Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Harvard Medical School, Brigham and Women's Hospital, Boston, MA 02115, USA; Department of Biomedical Informatics, Harvard Medical School, Boston, MA 02115 USA; Program in Medical and Population Genetics, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142, USA
| | - Jessica I Beynor
- Center for Data Sciences, Brigham and Women's Hospital, Boston, MA 02115, USA; Division of Genetics, Department of Medicine, Harvard Medical School, Brigham and Women's Hospital, Boston, MA 02115, USA; Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Harvard Medical School, Brigham and Women's Hospital, Boston, MA 02115, USA; Program in Medical and Population Genetics, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142, USA
| | - Soumya Raychaudhuri
- Center for Data Sciences, Brigham and Women's Hospital, Boston, MA 02115, USA; Division of Genetics, Department of Medicine, Harvard Medical School, Brigham and Women's Hospital, Boston, MA 02115, USA; Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Harvard Medical School, Brigham and Women's Hospital, Boston, MA 02115, USA; Department of Biomedical Informatics, Harvard Medical School, Boston, MA 02115 USA; Program in Medical and Population Genetics, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142, USA; Arthritis Research UK Centre for Genetics and Genomics, Centre for Musculoskeletal Research, The University of Manchester, Oxford Road, Manchester, M13 9PT, UK.
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15
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Shinde R, Hezaveh K, Halaby MJ, Kloetgen A, Chakravarthy A, da Silva Medina T, Deol R, Manion KP, Baglaenko Y, Eldh M, Lamorte S, Wallace D, Chodisetti SB, Ravishankar B, Liu H, Chaudhary K, Munn DH, Tsirigos A, Madaio M, Gabrielsson S, Touma Z, Wither J, De Carvalho DD, McGaha TL. Apoptotic cell-induced AhR activity is required for immunological tolerance and suppression of systemic lupus erythematosus in mice and humans. Nat Immunol 2018; 19:571-582. [PMID: 29760532 PMCID: PMC5976527 DOI: 10.1038/s41590-018-0107-1] [Citation(s) in RCA: 110] [Impact Index Per Article: 18.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2017] [Accepted: 03/30/2018] [Indexed: 12/15/2022]
Abstract
The transcription factor AhR modulates immunity at multiple levels. Here we report phagocytes exposed to apoptotic cells exhibited rapid activation of AhR, which drove production of interleukin 10. Activation of AhR was dependent on interactions between apoptotic-cell DNA and the pattern-recognition receptor TLR9 that was required for prevention of immune responses to DNA and histones in vivo. Moreover, disease progression in murine systemic lupus erythematosus (SLE) correlated with strength of the AhR signal, and disease course could be altered by modulation of AhR activity. Deletion of AhR in the myeloid lineage caused systemic autoimmunity in mice and an increased AhR transcriptional signature correlated with disease in patients with SLE. Thus, AhR activity induced by apoptotic cell phagocytes maintains peripheral tolerance.
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Affiliation(s)
- Rahul Shinde
- Tumor Immunotherapy Program, Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada.,Department of Immunology, University of Toronto, Toronto, ON, Canada
| | - Kebria Hezaveh
- Tumor Immunotherapy Program, Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada.,Department of Immunology, University of Toronto, Toronto, ON, Canada
| | - Marie Jo Halaby
- Tumor Immunotherapy Program, Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada.,Department of Immunology, University of Toronto, Toronto, ON, Canada
| | - Andreas Kloetgen
- Department of Pathology, New York University School of Medicine, New York, NY, USA
| | - Ankur Chakravarthy
- Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
| | - Tiago da Silva Medina
- Tumor Immunotherapy Program, Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada
| | - Reema Deol
- Tumor Immunotherapy Program, Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada
| | - Kieran P Manion
- Department of Immunology, University of Toronto, Toronto, ON, Canada.,Krembil Research Institute, University Health Network, Toronto, ON, Canada
| | - Yuriy Baglaenko
- Department of Immunology, University of Toronto, Toronto, ON, Canada.,Krembil Research Institute, University Health Network, Toronto, ON, Canada
| | - Maria Eldh
- Department of Medicine, Unit for Immunology and Allergy, Karolinska Institute, Stockholm, Sweden
| | - Sara Lamorte
- Tumor Immunotherapy Program, Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada.,Department of Immunology, University of Toronto, Toronto, ON, Canada
| | - Drew Wallace
- Tumor Immunotherapy Program, Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada
| | - Sathi Babu Chodisetti
- Department of Immunology, Pennsylvania State University School of Medicine, Hershey, PA, USA
| | | | - Haiyun Liu
- Department of Dermatology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Kapil Chaudhary
- Department of Medicine, Washington University School of Medicine, St. Louis, MO, USA
| | - David H Munn
- Department of Paediatrics, Medical College of Georgia, Augusta, GA, USA
| | - Aristotelis Tsirigos
- Department of Pathology, New York University School of Medicine, New York, NY, USA.,Laura and Isaac Perlmutter Cancer Center, New York University School of Medicine, New York, NY, USA.,Applied Bioinformatics Laboratories, New York University School of Medicine, New York, NY, USA
| | - Michael Madaio
- Department of Medicine, Medical College of Georgia, Augusta, GA, USA
| | - Susanne Gabrielsson
- Department of Medicine, Unit for Immunology and Allergy, Karolinska Institute, Stockholm, Sweden
| | - Zahi Touma
- University of Toronto Lupus Clinic, University of Toronto, Toronto, ON, Canada.,Centre for Prognosis Studies in Rheumatic Diseases, Toronto Western Hospital, University Health Network, Toronto, ON, Canada.,Department of Medicine, University of Toronto, Toronto, ON, Canada
| | - Joan Wither
- Department of Immunology, University of Toronto, Toronto, ON, Canada.,Krembil Research Institute, University Health Network, Toronto, ON, Canada.,Department of Medicine, University of Toronto, Toronto, ON, Canada
| | - Daniel D De Carvalho
- Tumor Immunotherapy Program, Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada.,Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
| | - Tracy L McGaha
- Tumor Immunotherapy Program, Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada. .,Department of Immunology, University of Toronto, Toronto, ON, Canada.
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16
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Wu CAM, Roth TL, Baglaenko Y, Ferri DM, Brauer P, Zuniga-Pflucker JC, Rosbe KW, Wither JE, Marson A, Allen CDC. Genetic engineering in primary human B cells with CRISPR-Cas9 ribonucleoproteins. J Immunol Methods 2018; 457:33-40. [PMID: 29614266 DOI: 10.1016/j.jim.2018.03.009] [Citation(s) in RCA: 32] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2018] [Revised: 03/24/2018] [Accepted: 03/26/2018] [Indexed: 12/27/2022]
Abstract
Genome editing in human cells with targeted nucleases now enables diverse experimental and therapeutic genome engineering applications, but extension to primary human B cells remains limited. Here we report a method for targeted genetic engineering in primary human B cells, utilizing electroporation of CRISPR-Cas9 ribonucleoproteins (RNPs) to introduce gene knockout mutations at protein-coding loci with high efficiencies that in some cases exceeded 80%. Further, we demonstrate knock-in editing of targeted nucleotides with efficiency exceeding 10% through co-delivery of oligonucleotide templates for homology directed repair. We delivered Cas9 RNPs in two distinct in vitro culture systems to achieve editing in both undifferentiated B cells and activated B cells undergoing differentiation, reflecting utility in diverse experimental conditions. In summary, we demonstrate a powerful and scalable research tool for functional genetic studies of human B cell biology that may have further applications in engineered B cell therapeutics.
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Affiliation(s)
- Chung-An M Wu
- Cardiovascular Research Institute, Sandler Asthma Basic Research Center, 555 Mission Bay Blvd S, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Theodore L Roth
- Department of Microbiology and Immunology, 513 Parnassus Ave, University of California, San Francisco, CA 94143, USA
| | - Yuriy Baglaenko
- Krembil Research Institute, 60 Leonard Ave, University Health Network, Toronto, Ontario, Canada; Department of Immunology, 60 Leonard Ave, University of Toronto, Toronto, Ontario, Canada
| | - Dario M Ferri
- Krembil Research Institute, 60 Leonard Ave, University Health Network, Toronto, Ontario, Canada; Department of Immunology, 60 Leonard Ave, University of Toronto, Toronto, Ontario, Canada
| | - Patrick Brauer
- Department of Immunology, 60 Leonard Ave, University of Toronto, Toronto, Ontario, Canada; Sunnybrook Research Institute, 2075 Bayview Ave, University of Toronto, Toronto, Ontario, Canada
| | - Juan Carlos Zuniga-Pflucker
- Department of Immunology, 60 Leonard Ave, University of Toronto, Toronto, Ontario, Canada; Sunnybrook Research Institute, 2075 Bayview Ave, University of Toronto, Toronto, Ontario, Canada
| | - Kristina W Rosbe
- Department of Otolaryngology, 550 16th St, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Joan E Wither
- Krembil Research Institute, 60 Leonard Ave, University Health Network, Toronto, Ontario, Canada; Department of Immunology, 60 Leonard Ave, University of Toronto, Toronto, Ontario, Canada; Department of Medicine, 60 Leonard Ave, University of Toronto, Toronto, Ontario, Canada.
| | - Alexander Marson
- Department of Microbiology and Immunology, 513 Parnassus Ave, University of California, San Francisco, CA 94143, USA; Department of Medicine, Diabetes Center, Helen Diller Family Comprehensive Cancer Center, 513 Parnassus Ave, University of California, San Francisco, CA 94143, USA; Innovative Genomics Institute, 2151 Berkeley Way, University of California, Berkeley, Berkeley, CA 94720, USA; Chan Zuckerberg Biohub, 499 Illinois St, San Francisco, CA 94158, USA.
| | - Christopher D C Allen
- Cardiovascular Research Institute, Sandler Asthma Basic Research Center, 555 Mission Bay Blvd S, University of California, San Francisco, San Francisco, CA 94143, USA; Department of Anatomy, 555 Mission Bay Blvd S, University of California, San Francisco, San Francisco, CA 94143, USA.
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17
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Chang NH, Manion KP, Loh C, Pau E, Baglaenko Y, Wither JE. Multiple tolerance defects contribute to the breach of B cell tolerance in New Zealand Black chromosome 1 congenic mice. PLoS One 2017. [PMID: 28628673 PMCID: PMC5476272 DOI: 10.1371/journal.pone.0179506] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [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: 11/18/2022] Open
Abstract
Lupus is characterized by a loss of B cell tolerance leading to autoantibody production. In this study, we explored the mechanisms underlying this loss of tolerance using B6 congenic mice with an interval from New Zealand Black chromosome 1 (denoted c1(96–100)) sufficient for anti-nuclear antibody production. Transgenes for soluble hen egg white lysozyme (sHEL) and anti-HEL immunoglobulin were crossed onto this background and various tolerance mechanisms examined. We found that c1(96–100) mice produced increased levels of IgM and IgG anti-HEL antibodies compared to B6 mice and had higher proportions of germinal center B cells and long-lived plasma cells, suggesting a germinal center-dependent breach of B cell anergy. Consistent with impaired anergy induction, c1(96–100) double transgenic B cells showed enhanced survival and CD86 upregulation. Hematopoietic chimeric sHEL mice with a mixture of B6 and c1(96–100) HEL transgenic B cells recapitulated these results, suggesting the presence of a B cell autonomous defect. Surprisingly, however, there was equivalent recruitment of B6 and c1(96–100) B cells into germinal centers and differentiation to splenic plasmablasts in these mice. In contrast, there were increased proportions of c1(96–100) T follicular helper cells and long-lived plasma cells as compared to their B6 counterparts, suggesting that both B and T cell defects are required to breach germinal center tolerance in this model. This possibility was further supported by experiments showing an enhanced breach of anergy in double transgenic mice with a longer chromosome 1 interval with additional T cell defects.
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Affiliation(s)
- Nan-Hua Chang
- Arthritis Centre of Excellence, Division of Genetics and Development, Krembil Research Institute, Toronto, Ontario, Canada
| | - Kieran P. Manion
- Arthritis Centre of Excellence, Division of Genetics and Development, Krembil Research Institute, Toronto, Ontario, Canada
- Department of Immunology, University of Toronto, Toronto, Ontario, Canada
| | - Christina Loh
- Arthritis Centre of Excellence, Division of Genetics and Development, Krembil Research Institute, Toronto, Ontario, Canada
- Department of Immunology, University of Toronto, Toronto, Ontario, Canada
| | - Evelyn Pau
- Arthritis Centre of Excellence, Division of Genetics and Development, Krembil Research Institute, Toronto, Ontario, Canada
- Department of Immunology, University of Toronto, Toronto, Ontario, Canada
| | - Yuriy Baglaenko
- Arthritis Centre of Excellence, Division of Genetics and Development, Krembil Research Institute, Toronto, Ontario, Canada
- Department of Immunology, University of Toronto, Toronto, Ontario, Canada
| | - Joan E. Wither
- Arthritis Centre of Excellence, Division of Genetics and Development, Krembil Research Institute, Toronto, Ontario, Canada
- Department of Immunology, University of Toronto, Toronto, Ontario, Canada
- Department of Medicine, University of Toronto, Toronto, Ontario, Canada
- Division of Rheumatology, University Health Network, Toronto, Ontario, Canada
- * E-mail:
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18
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Baglaenko Y, Cruz Tleugabulova M, Gracey E, Talaei N, Manion KP, Chang NH, Ferri DM, Mallevaey T, Wither JE. Invariant NKT Cell Activation Is Potentiated by Homotypic trans-Ly108 Interactions. J Immunol 2017; 198:3949-3962. [PMID: 28373584 DOI: 10.4049/jimmunol.1601369] [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] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/25/2016] [Accepted: 03/07/2017] [Indexed: 01/27/2023]
Abstract
Invariant NKT (iNKT) cells are innate lymphocytes that respond to glycolipids presented by the MHC class Ib molecule CD1d and are rapidly activated to produce large quantities of cytokines and chemokines. iNKT cell development uniquely depends on interactions between double-positive thymocytes that provide key homotypic interactions between signaling lymphocyte activation molecule (SLAM) family members. However, the role of SLAM receptors in the differentiation of iNKT cell effector subsets and activation has not been explored. In this article, we show that C57BL/6 mice containing the New Zealand Black Slam locus have profound alterations in Ly108, CD150, and Ly9 expression that is associated with iNKT cell hyporesponsiveness. This loss of function was only apparent when dendritic cells and iNKT cells had a loss of SLAM receptor expression. Using small interfering RNA knockdowns and peptide-blocking strategies, we demonstrated that trans-Ly108 interactions between dendritic cells and iNKT cells are critical for robust activation. LY108 costimulation similarly increased human iNKT cell activation. Thus, in addition to its established role in iNKT cell ontogeny, Ly108 regulates iNKT cell function in mice and humans.
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Affiliation(s)
- Yuriy Baglaenko
- Krembil Research Institute, University Health Network, Toronto, Ontario M5T 2S8, Canada.,Department of Immunology, University of Toronto, Toronto, Ontario M5S 1A8, Canada; and
| | | | - Eric Gracey
- Krembil Research Institute, University Health Network, Toronto, Ontario M5T 2S8, Canada.,Department of Immunology, University of Toronto, Toronto, Ontario M5S 1A8, Canada; and
| | - Nafiseh Talaei
- Krembil Research Institute, University Health Network, Toronto, Ontario M5T 2S8, Canada.,Department of Immunology, University of Toronto, Toronto, Ontario M5S 1A8, Canada; and
| | - Kieran Patricia Manion
- Krembil Research Institute, University Health Network, Toronto, Ontario M5T 2S8, Canada.,Department of Immunology, University of Toronto, Toronto, Ontario M5S 1A8, Canada; and
| | - Nan-Hua Chang
- Krembil Research Institute, University Health Network, Toronto, Ontario M5T 2S8, Canada
| | - Dario Michael Ferri
- Krembil Research Institute, University Health Network, Toronto, Ontario M5T 2S8, Canada.,Department of Immunology, University of Toronto, Toronto, Ontario M5S 1A8, Canada; and
| | - Thierry Mallevaey
- Department of Immunology, University of Toronto, Toronto, Ontario M5S 1A8, Canada; and
| | - Joan E Wither
- Krembil Research Institute, University Health Network, Toronto, Ontario M5T 2S8, Canada; .,Department of Immunology, University of Toronto, Toronto, Ontario M5S 1A8, Canada; and.,Department of Medicine, University of Toronto, Toronto, Ontario M5S 1A8, Canada
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19
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Gracey E, Yao Y, Green B, Qaiyum Z, Baglaenko Y, Lin A, Anton A, Ayearst R, Yip P, Inman RD. Sexual Dimorphism in the Th17 Signature of Ankylosing Spondylitis. Arthritis Rheumatol 2016; 68:679-89. [PMID: 26473967 DOI: 10.1002/art.39464] [Citation(s) in RCA: 117] [Impact Index Per Article: 14.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2015] [Accepted: 10/01/2015] [Indexed: 01/13/2023]
Abstract
OBJECTIVE To identify an immunologic basis for the male sex bias in ankylosing spondylitis (AS). METHODS Cohorts of male and female patients with AS and age- and sex-matched healthy control subjects were selected, and the levels of serum cytokines (interferon-γ [IFNγ], tumor necrosis factor α, interleukin-17A [IL-17A], and IL-6) were examined by enzyme-linked immunosorbent assay, the frequencies of Th1 and Th17 cells were assessed by flow cytometry, and whole blood gene expression was analyzed using both microarray and NanoString approaches. RESULTS The frequency of IL-17A and Th17 cells, both of which are key factors in the inflammatory Th17 axis, was elevated in male patients with AS but not in female patients with AS. In contrast, AS-associated alterations in the Th1 axis, such as the frequency of IFNγ and Th1 cells in serum, were independent of a patient's sex. Results of microarray analysis supported an altered Th17 axis in male patients, with a specific increase in IL17RA. In addition, male and female patients with AS displayed shared gene expression patterns, while male patients with AS had additional alterations in gene expression that were not seen in female patients with AS. The differential sex-related immune profiles were independent of HLA-B27 status, clinical disease activity (as measured by the Bath Ankylosing Spondylitis Disease Activity Index), or treatment (with nonsteroidal antiinflammatory drugs or biologic agents), implicating intrinsic sexual dimorphism in AS. CONCLUSION The results of this study demonstrate distinct sexual dimorphism in the activation status of the immune system in patients with AS, particularly in the Th17 axis. This dimorphism could underlie sex-related differences in the clinical features of AS and could provide a rationale for sex-specific treatment of AS.
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Affiliation(s)
- Eric Gracey
- University of Toronto, Toronto Western Hospital, and University Health Network, Toronto, Ontario, Canada
| | - YuChen Yao
- University of Toronto, Toronto Western Hospital, and University Health Network, Toronto, Ontario, Canada
| | - Blerta Green
- Toronto Western Hospital and University Health Network, Toronto, Ontario, Canada
| | - Zoya Qaiyum
- University of Toronto, Toronto Western Hospital, and University Health Network, Toronto, Ontario, Canada
| | - Yuriy Baglaenko
- University of Toronto, Toronto Western Hospital, and University Health Network, Toronto, Ontario, Canada
| | - Aifeng Lin
- Toronto Western Hospital and University Health Network, Toronto, Ontario, Canada
| | - Ammepa Anton
- Toronto Western Hospital and University Health Network, Toronto, Ontario, Canada
| | - Renise Ayearst
- Toronto Western Hospital and University Health Network, Toronto, Ontario, Canada
| | - Paul Yip
- University Health Network, Toronto, Ontario, Canada
| | - Robert D Inman
- University of Toronto, Toronto Western Hospital, and University Health Network, Toronto, Ontario, Canada
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Gracey E, Qaiyum Z, Almaghlouth I, Lawson D, Karki S, Avvaru N, Zhang Z, Yao Y, Ranganathan V, Baglaenko Y, Inman RD. IL-7 primes IL-17 in mucosal-associated invariant T (MAIT) cells, which contribute to the Th17-axis in ankylosing spondylitis. Ann Rheum Dis 2016; 75:2124-2132. [PMID: 27165176 DOI: 10.1136/annrheumdis-2015-208902] [Citation(s) in RCA: 183] [Impact Index Per Article: 22.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2015] [Revised: 04/06/2016] [Accepted: 04/09/2016] [Indexed: 01/08/2023]
Abstract
OBJECTIVE Ankylosing spondylitis (AS) is a chronic inflammatory disease of unknown origin in which interleukin (IL) 17 has been genetically and therapeutically recognised as a key player. Identification of the cellular sources and inducers of IL-17 is crucial in our understanding of the drivers of inflammation in AS. Recently, mucosal-associated invariant T (MAIT) cells have been implicated in autoimmune diseases. Their gut origin, effector phenotype and expression of multiple AS-associated genes, such as IL7R and IL23R, makes them potential contributors to the pathogenesis of AS. METHODS Mononuclear cells from patients with AS, healthy controls (HCs) and patients with rheumatoid arthritis were isolated from blood and synovial fluid (SF). Flow cytometry was used to identify MAIT cells. Phenotype was assessed by intracellular staining for cytokines and granzyme. Function was assessed by antigen-specific stimulation using Salmonella, or antigen non-specific activation via priming with IL-7 or IL-23. RESULTS MAIT cells were reduced in frequency in the blood of patients with AS compared with HCs, yet patients with AS had an elevated frequency IL-17A+ MAIT cells. There was an enrichment of MAIT cells in SF, which had an exaggerated IL-17 phenotype. IL-17 elevation in AS MAIT cells was dependent on priming with IL-7 but not IL-23 or antigen stimulation. The AS-associated IL7R single nucleotide polymorphism (SNP), rs11742270, had no effect on IL-7R expression or function in the experiments performed. CONCLUSIONS This study reveals a potential role for MAIT cells in patients with AS and is the first linking IL-7 to the elevated IL-17 profile in patients through the AS-associated risk gene IL7R.
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Affiliation(s)
- Eric Gracey
- Department of Immunology, University of Toronto, Toronto, Ontario, Canada.,Toronto Western Hospital, University Health Network, Toronto, Ontario, Canada
| | - Zoya Qaiyum
- Department of Immunology, University of Toronto, Toronto, Ontario, Canada.,Toronto Western Hospital, University Health Network, Toronto, Ontario, Canada
| | - Ibrahim Almaghlouth
- Toronto Western Hospital, University Health Network, Toronto, Ontario, Canada
| | - Daeria Lawson
- Toronto Western Hospital, University Health Network, Toronto, Ontario, Canada
| | - Susan Karki
- Toronto Western Hospital, University Health Network, Toronto, Ontario, Canada
| | - Naga Avvaru
- Toronto Western Hospital, University Health Network, Toronto, Ontario, Canada
| | - Zhenbo Zhang
- Toronto Western Hospital, University Health Network, Toronto, Ontario, Canada
| | - Yuchen Yao
- Department of Immunology, University of Toronto, Toronto, Ontario, Canada.,Toronto Western Hospital, University Health Network, Toronto, Ontario, Canada
| | - Vidya Ranganathan
- Toronto Western Hospital, University Health Network, Toronto, Ontario, Canada
| | - Yuriy Baglaenko
- Department of Immunology, University of Toronto, Toronto, Ontario, Canada.,Toronto Western Hospital, University Health Network, Toronto, Ontario, Canada
| | - Robert D Inman
- Department of Immunology, University of Toronto, Toronto, Ontario, Canada.,Toronto Western Hospital, University Health Network, Toronto, Ontario, Canada
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Gracey E, Baglaenko Y, Prayitno N, Van Rooijen N, Akram A, Lin A, Chiu B, Inman RD. Pulmonary Chlamydia muridarum challenge activates lung interstitial macrophages which correlate with IFN-γ production and infection control in mice. Eur J Immunol 2015; 45:3417-30. [PMID: 26344246 DOI: 10.1002/eji.201545874] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2015] [Revised: 07/23/2015] [Accepted: 09/01/2015] [Indexed: 11/09/2022]
Abstract
Protective immunity to the pathogen Chlamydia is dependent on a robust IFN-γ response generated by innate and adaptive lymphocytes. Here we assess the role of the macrophage in orchestrating a protective response in vivo to the murine pathogen, Chlamydia muridarum. During acute pulmonary and peritoneal infection, resident macrophages in both sites are infected with C. muridarum and adopt an inflammatory phenotype. In the lung, this activation is restricted to interstitial macrophages, which harbor higher levels of C. muridarum 16sRNA than alveolar macrophages. We examined innate and adaptive lymphocyte activation in the peritoneal cavity with macrophage depletion and with adoptive transfer of infected macrophages. These experiments demonstrate macrophage activation correlates with a protective IFN-γ response and effective control of C. muridarum. These studies suggest that a quantitative or qualitative alteration in macrophages may play a key role in the development of Chlamydia-associated diseases.
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Affiliation(s)
- Eric Gracey
- Department of Immunology, University of Toronto, Canada.,Division of Genetics and Development, Toronto Western Research Institute, University Health Network, Toronto, Canada
| | - Yuriy Baglaenko
- Department of Immunology, University of Toronto, Canada.,Division of Genetics and Development, Toronto Western Research Institute, University Health Network, Toronto, Canada
| | | | - Nico Van Rooijen
- Vrije Universiteit, Vrije Universiteit Medical Center, Department of Molecular Cell Biology, Amsterdam, The Netherlands
| | - Ali Akram
- Division of Genetics and Development, Toronto Western Research Institute, University Health Network, Toronto, Canada
| | - Aifeng Lin
- Division of Genetics and Development, Toronto Western Research Institute, University Health Network, Toronto, Canada
| | - Basil Chiu
- Division of Genetics and Development, Toronto Western Research Institute, University Health Network, Toronto, Canada
| | - Robert D Inman
- Department of Immunology, University of Toronto, Canada.,Division of Genetics and Development, Toronto Western Research Institute, University Health Network, Toronto, Canada
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Loh C, Pau E, Lajoie G, Li TT, Baglaenko Y, Cheung YH, Chang NH, Wither JE. Epistatic suppression of fatal autoimmunity in New Zealand black bicongenic mice. J Immunol 2011; 186:5845-53. [PMID: 21464090 DOI: 10.4049/jimmunol.1003426] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
Numerous mapping studies have implicated genetic intervals from lupus-prone New Zealand Black (NZB) chromosomes 1 and 4 as contributing to lupus pathogenesis. By introgressing NZB chromosomal intervals onto a non-lupus-prone B6 background, we determined that: NZB chromosome 1 congenic mice (denoted B6.NZBc1) developed fatal autoimmune-mediated kidney disease, and NZB chromosome 4 congenic mice (denoted B6.NZBc4) exhibited a marked expansion of B1a and NKT cells in the surprising absence of autoimmunity. In this study, we sought to examine whether epistatic interactions between these two loci would affect lupus autoimmunity by generating bicongenic mice that carry both NZB chromosomal intervals. Compared with B6.NZBc1 mice, bicongenic mice demonstrated significantly decreased mortality, kidney disease, Th1-biased IgG autoantibody isotypes, and differentiation of IFN-γ-producing T cells. Furthermore, a subset of bicongenic mice exhibited a paucity of CD21(+)CD1d(+) B cells and an altered NKT cell activation profile that correlated with greater disease inhibition. Thus, NZBc4 contains suppressive epistatic modifiers that appear to inhibit the development of fatal NZBc1 autoimmunity by promoting a shift away from a proinflammatory cytokine profile, which in some mice may involve NKT cells.
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Affiliation(s)
- Christina Loh
- Arthritis Center of Excellence, Toronto Western Research Institute, Toronto, Ontario M5T 2S8, Canada
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