1
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Sartoris S, Del Pozzo G. Exploring the HLA complex in autoimmunity: From the risk haplotypes to the modulation of expression. Clin Immunol 2024; 265:110266. [PMID: 38851519 DOI: 10.1016/j.clim.2024.110266] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2024] [Revised: 05/29/2024] [Accepted: 05/30/2024] [Indexed: 06/10/2024]
Abstract
The genes mapping at the HLA region show high density, strong linkage disequilibrium and high polymorphism, which affect the association of HLA class I and class II genes with autoimmunity. We focused on the HLA haplotypes, genomic structures consisting of an array of specific alleles showing some degrees of genetic association with different autoimmune disorders. GWASs in many pathologies have identified variants in either the coding loci or the flanking regulatory regions, both in linkage disequilibrium in haplotypes, that are frequently associated with increased risk and may influence gene expression. We discuss the relevance of the HLA gene expression because the level of surface heterodimers determines the number of complexes presenting self-antigen and, thus, the strength of pathogenic autoreactive T cells immune response.
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Affiliation(s)
- Silvia Sartoris
- Dept. of Medicine, Section of Immunology University of Verona School of Medicine, Verona, Italy
| | - Giovanna Del Pozzo
- Institute of Genetics and Biophysics "Adriano Buzzati Traverso" National Research Council (CNR), Naples, Italy.
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2
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Yogeshwar SM, Muñiz-Castrillo S, Sabater L, Peris-Sempere V, Mallajosyula V, Luo G, Yan H, Yu E, Zhang J, Lin L, Fagundes Bueno F, Ji X, Picard G, Rogemond V, Pinto AL, Heidbreder A, Höftberger R, Graus F, Dalmau J, Santamaria J, Iranzo A, Schreiner B, Giannoccaro MP, Liguori R, Shimohata T, Kimura A, Ono Y, Binks S, Mariotto S, Dinoto A, Bonello M, Hartmann CJ, Tambasco N, Nigro P, Prüss H, McKeon A, Davis MM, Irani SR, Honnorat J, Gaig C, Finke C, Mignot E. HLA-DQB1*05 subtypes and not DRB1*10:01 mediates risk in anti-IgLON5 disease. Brain 2024; 147:2579-2592. [PMID: 38425314 PMCID: PMC11224611 DOI: 10.1093/brain/awae048] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2023] [Revised: 10/09/2023] [Accepted: 01/21/2024] [Indexed: 03/02/2024] Open
Abstract
Anti-IgLON5 disease is a rare and likely underdiagnosed subtype of autoimmune encephalitis. The disease displays a heterogeneous phenotype that includes sleep, movement and bulbar-associated dysfunction. The presence of IgLON5-antibodies in CSF/serum, together with a strong association with HLA-DRB1*10:01∼DQB1*05:01, supports an autoimmune basis. In this study, a multicentric human leukocyte antigen (HLA) study of 87 anti-IgLON5 patients revealed a stronger association with HLA-DQ than HLA-DR. Specifically, we identified a predisposing rank-wise association with HLA-DQA1*01:05∼DQB1*05:01, HLA-DQA1*01:01∼DQB1*05:01 and HLA-DQA1*01:04∼DQB1*05:03 in 85% of patients. HLA sequences and binding cores for these three DQ heterodimers were similar, unlike those of linked DRB1 alleles, supporting a causal link to HLA-DQ. This association was further reflected in an increasingly later age of onset across each genotype group, with a delay of up to 11 years, while HLA-DQ-dosage dependent effects were also suggested by reduced risk in the presence of non-predisposing DQ1 alleles. The functional relevance of the observed HLA-DQ molecules was studied with competition binding assays. These proof-of-concept experiments revealed preferential binding of IgLON5 in a post-translationally modified, but not native, state to all three risk-associated HLA-DQ receptors. Further, a deamidated peptide from the Ig2-domain of IgLON5 activated T cells in two patients, compared with one control carrying HLA-DQA1*01:05∼DQB1*05:01. Taken together, these data support a HLA-DQ-mediated T-cell response to IgLON5 as a potentially key step in the initiation of autoimmunity in this disease.
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Affiliation(s)
- Selina M Yogeshwar
- Stanford Center for Sleep Sciences and Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA
- Department of Neurology and Experimental Neurology, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität Berlin, 10117, Berlin, Germany
- Einstein Center for Neurosciences Berlin, Charité—Universitätsmedizin Berlin, 10117 Berlin, Germany
| | - Sergio Muñiz-Castrillo
- Stanford Center for Sleep Sciences and Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Lidia Sabater
- Neuroimmunology Program, Fundació de Recerca Clínic Barcelona-Institut d’Investigacions Biomèdiques August Pi i Sunyer, Caixa Research Institute, Universitat de Barcelona, 08036, Barcelona, Spain
| | - Vicente Peris-Sempere
- Stanford Center for Sleep Sciences and Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Vamsee Mallajosyula
- Institute for Immunity, Transplantation, and Infection, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Guo Luo
- Stanford Center for Sleep Sciences and Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Han Yan
- Stanford Center for Sleep Sciences and Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Eric Yu
- Stanford Center for Sleep Sciences and Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Jing Zhang
- Stanford Center for Sleep Sciences and Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Ling Lin
- Stanford Center for Sleep Sciences and Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Flavia Fagundes Bueno
- Stanford Center for Sleep Sciences and Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Xuhuai Ji
- Human Immune Monitoring Center, Institute for Immunity, Transplantation, and Infection, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Géraldine Picard
- French Reference Center on Paraneoplastic Neurological Syndrome and Autoimmune Encephalitis, Hospices Civils de Lyon, 69677, Lyon, France
- Institut MeLiS INSERM U1314/CNRS UMR 5284, Université Claude Bernard Lyon 1, 69372 Lyon, France
| | - Véronique Rogemond
- French Reference Center on Paraneoplastic Neurological Syndrome and Autoimmune Encephalitis, Hospices Civils de Lyon, 69677, Lyon, France
- Institut MeLiS INSERM U1314/CNRS UMR 5284, Université Claude Bernard Lyon 1, 69372 Lyon, France
| | - Anne Laurie Pinto
- French Reference Center on Paraneoplastic Neurological Syndrome and Autoimmune Encephalitis, Hospices Civils de Lyon, 69677, Lyon, France
- Institut MeLiS INSERM U1314/CNRS UMR 5284, Université Claude Bernard Lyon 1, 69372 Lyon, France
| | - Anna Heidbreder
- Kepler University Hospital, Department of Neurology, Johannes Kepler University, 4020 Linz, Austria
| | - Romana Höftberger
- Division of Neuropathology and Neurochemistry, Department of Neurology, Medical University of Vienna, 1090 Vienna, Austria
| | - Francesc Graus
- Neurology Service, Hospital Clínic of Barcelona, Biomedical Research Institute (IDIBAPS), 08036 Barcelona, Spain
| | - Josep Dalmau
- Neurology Service, Hospital Clínic of Barcelona, Biomedical Research Institute (IDIBAPS), 08036 Barcelona, Spain
- Catalan Institution for Research and Advanced Studies (ICREA), 08010 Barcelona, Spain
- Department of Neurology, University of Pennsylvania, Philadelphia, PA 19104, USA
- Spanish National Network for Research on Rare Diseases (CIBERER), 28029 Madrid, Spain
| | - Joan Santamaria
- Neurology Service, Hospital Clínic of Barcelona, Biomedical Research Institute (IDIBAPS), 08036 Barcelona, Spain
| | - Alex Iranzo
- Neurology Service, Hospital Clínic of Barcelona, Biomedical Research Institute (IDIBAPS), 08036 Barcelona, Spain
| | - Bettina Schreiner
- Department of Neurology, University Hospital Zurich, 8091 Zurich, Switzerland
- Institute of Experimental Immunology, University of Zurich, 8057 Zurich, Switzerland
| | - Maria Pia Giannoccaro
- IRCCS Istituto delle Scienze Neurologiche di Bologna, UOC Clinica Neurologica, 40139 Bologna, Italy
- Dipartimento di Scienze Biomediche e Neuromotorie, Università di Bologna, 40100 Bologna, Italy
| | - Rocco Liguori
- IRCCS Istituto delle Scienze Neurologiche di Bologna, UOC Clinica Neurologica, 40139 Bologna, Italy
- Dipartimento di Scienze Biomediche e Neuromotorie, Università di Bologna, 40100 Bologna, Italy
| | - Takayoshi Shimohata
- Department of Neurology, Gifu University Graduate School of Medicine, 501-1194 Gifu, Japan
| | - Akio Kimura
- Department of Neurology, Gifu University Graduate School of Medicine, 501-1194 Gifu, Japan
| | - Yoya Ono
- Department of Neurology, Gifu University Graduate School of Medicine, 501-1194 Gifu, Japan
| | - Sophie Binks
- Oxford Autoimmune Neurology Group, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford OX3 9DU, UK
- Department of Neurology, Oxford University Hospitals NHS Foundation Trust, John Radcliffe Hospital, Oxford OX3 9DU, UK
| | - Sara Mariotto
- Neurology Unit, Department of Neurosciences, Biomedicine, and Movement Sciences, University of Verona, 37124 Verona, Italy
| | - Alessandro Dinoto
- Neurology Unit, Department of Neurosciences, Biomedicine, and Movement Sciences, University of Verona, 37124 Verona, Italy
| | - Michael Bonello
- Department of Neurology, The Walton Centre NHS Foundation Trust, L9 7LJ, Liverpool, UK
| | - Christian J Hartmann
- Department of Neurology, Medical Faculty and University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, 40225 Düsseldorf, Germany
- Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty and University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, 40225 Düsseldorf, Germany
| | - Nicola Tambasco
- Movement Disorders Center, Neurology Department, Perugia General Hospital and University of Perugia, 06156 Perugia, Italy
| | - Pasquale Nigro
- Movement Disorders Center, Neurology Department, Perugia General Hospital and University of Perugia, 06156 Perugia, Italy
| | - Harald Prüss
- Department of Neurology and Experimental Neurology, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität Berlin, 10117, Berlin, Germany
- German Center for Neurodegenerative Diseases (DZNE) Berlin, 10117 Berlin, Germany
| | - Andrew McKeon
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN 55905, USA
- Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA
| | - Mark M Davis
- Institute for Immunity, Transplantation, and Infection, Stanford University School of Medicine, Stanford, CA 94305, USA
- Department of Microbiology and Immunology, Stanford University School of Medicine, Stanford, CA 94305, USA
- Howard Hughes Medical Institute, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Sarosh R Irani
- Department of Neurology, Oxford University Hospitals NHS Foundation Trust, John Radcliffe Hospital, Oxford OX3 9DU, UK
| | - Jérôme Honnorat
- French Reference Center on Paraneoplastic Neurological Syndrome and Autoimmune Encephalitis, Hospices Civils de Lyon, 69677, Lyon, France
- Institut MeLiS INSERM U1314/CNRS UMR 5284, Université Claude Bernard Lyon 1, 69372 Lyon, France
| | - Carles Gaig
- Neurology Service, Hospital Clínic of Barcelona, Biomedical Research Institute (IDIBAPS), 08036 Barcelona, Spain
| | - Carsten Finke
- Department of Neurology and Experimental Neurology, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität Berlin, 10117, Berlin, Germany
- Berlin Center for Advanced Neuroimaging, Charité—Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, 10117 Berlin, Germany
| | - Emmanuel Mignot
- Stanford Center for Sleep Sciences and Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA
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3
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Pahkuri S, Katayama S, Valta M, Nygård L, Knip M, Kere J, Ilonen J, Lempainen J. The effect of type 1 diabetes protection and susceptibility associated HLA class II genotypes on DNA methylation in immune cells. HLA 2024; 103:e15548. [PMID: 38887913 DOI: 10.1111/tan.15548] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2024] [Revised: 04/24/2024] [Accepted: 05/17/2024] [Indexed: 06/20/2024]
Abstract
The HLA region, especially HLA class I and II genes, which encode molecules for antigen presentation to T cells, plays a major role in the predisposition to autoimmune disorders. To clarify the mechanisms behind this association, we examined genome-wide DNA methylation by microarrays to cover over 850,000 CpG sites in the CD4+ T cells and CD19+ B cells of healthy subjects homozygous either for DRB1*15-DQA1*01-DQB1*06:02 (DR2-DQ6, n = 14), associated with a strongly decreased T1D risk, DRB1*03-DQA1*05-DQB1*02 (DR3-DQ2, n = 19), or DRB1*04:01-DQA1*03-DQB1*03:02 (DR4-DQ8, n = 17), associated with a moderately increased T1D risk. In total, we discovered 14 differentially methylated CpG probes, of which 10 were located in the HLA region and six in the HLA-DRB1 locus. The main differences were between the protective genotype DR2-DQ6 and the risk genotypes DR3-DQ2 and DR4-DQ8, where the DR2-DQ6 group was hypomethylated compared to the other groups in all but four of the differentially methylated probes. The differences between the risk genotypes DR3-DQ2 and DR4-DQ8 were small. Our results indicate that HLA variants have few systemic effects on methylation and that their effect on autoimmunity is conveyed directly by HLA molecules, possibly by differences in expression levels or function.
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Affiliation(s)
- Sirpa Pahkuri
- Immunogenetics Laboratory, Institute of Biomedicine, University of Turku, Turku, Finland
| | - Shintaro Katayama
- Folkhälsan Research Center, Helsinki, Finland
- Stem Cells and Metabolism Research Program, University of Helsinki, Helsinki, Finland
- Department of Biosciences and Nutrition, Karolinska Institutet, Huddinge, Sweden
| | - Milla Valta
- Immunogenetics Laboratory, Institute of Biomedicine, University of Turku, Turku, Finland
| | - Lucas Nygård
- Immunogenetics Laboratory, Institute of Biomedicine, University of Turku, Turku, Finland
- Department of Clinical Microbiology, Institute of Clinical Medicine, University of Eastern Finland, Kuopio, Finland
| | - Mikael Knip
- Faculty of Medicine, Research Program for Clinical and Molecular Metabolism, University of Helsinki, Helsinki, Finland
- Tampere Center for Child Health Research, Tampere University Hospital, Tampere, Finland
| | - Juha Kere
- Folkhälsan Research Center, Helsinki, Finland
- Stem Cells and Metabolism Research Program, University of Helsinki, Helsinki, Finland
- Department of Biosciences and Nutrition, Karolinska Institutet, Huddinge, Sweden
| | - Jorma Ilonen
- Immunogenetics Laboratory, Institute of Biomedicine, University of Turku, Turku, Finland
| | - Johanna Lempainen
- Immunogenetics Laboratory, Institute of Biomedicine, University of Turku, Turku, Finland
- Department of Pediatrics, University of Turku and Turku University Hospital, Turku, Finland
- Clinical Microbiology, Turku University Hospital, Turku, Finland
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4
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Mizutani A, Suzuki S, Shigenari A, Sato T, Tanaka M, Kulski JK, Shiina T. Nucleotide alterations in the HLA-C class I gene can cause aberrant splicing and marked changes in RNA levels in a polymorphic context-dependent manner. Front Immunol 2024; 14:1332636. [PMID: 38327766 PMCID: PMC10847315 DOI: 10.3389/fimmu.2023.1332636] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2023] [Accepted: 12/29/2023] [Indexed: 02/09/2024] Open
Abstract
Polymorphisms of HLA genes, which play a crucial role in presenting peptides with diverse sequences in their peptide-binding pockets, are also thought to affect HLA gene expression, as many studies have reported associations between HLA gene polymorphisms and their expression levels. In this study, we devised an ectopic expression assay for the HLA class I genes in the context of the entire gene, and used the assay to show that the HLA-C*03:03:01 and C*04:01:01 polymorphic differences observed in association studies indeed cause different levels of RNA expression. Subsequently, we investigated the C*03:23N null allele, which was previously noted for its reduced expression, attributed to an alternate exon 3 3' splice site generated by G/A polymorphism at position 781 within the exon 3. We conducted a thorough analysis of the splicing patterns of C*03:23N, and revealed multiple aberrant splicing, including the exon 3 alternative splicing, which overshadowed its canonical counterpart. After confirming a significant reduction in RNA levels caused by the G781A alteration in our ectopic assay, we probed the function of the G-rich sequence preceding the canonical exon 3 3' splice site. Substituting the G-rich sequence with a typical pyrimidine-rich 3' splice site sequence on C*03:23N resulted in a marked elevation in RNA levels, likely due to the enhanced preference for the canonical exon 3 3' splice site over the alternate site. However, the same substitution led to a reduction in RNA levels for C*03:03:01. These findings suggested the dual roles of the G-rich sequence in RNA expression, and furthermore, underscore the importance of studying polymorphism effects within the framework of the entire gene, extending beyond conventional mini-gene reporter assays.
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Affiliation(s)
- Akiko Mizutani
- Department of Molecular Life Science, Tokai University School of Medicine, Isehara, Kanagawa, Japan
- Faculty of Health and Medical Science, Teikyo Heisei University, Tokyo, Japan
| | - Shingo Suzuki
- Department of Molecular Life Science, Tokai University School of Medicine, Isehara, Kanagawa, Japan
| | - Atsuko Shigenari
- Department of Molecular Life Science, Tokai University School of Medicine, Isehara, Kanagawa, Japan
| | - Tadayuki Sato
- Department of Molecular Life Science, Tokai University School of Medicine, Isehara, Kanagawa, Japan
| | - Masafumi Tanaka
- Department of Molecular Life Science, Tokai University School of Medicine, Isehara, Kanagawa, Japan
| | - Jerzy K Kulski
- Department of Molecular Life Science, Tokai University School of Medicine, Isehara, Kanagawa, Japan
- School of Biomedical Sciences, The University of Western Australia, Nedlands, WA, Australia
| | - Takashi Shiina
- Department of Molecular Life Science, Tokai University School of Medicine, Isehara, Kanagawa, Japan
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5
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Shiina T, Kulski JK. HLA Genetics for the Human Diseases. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2024; 1444:237-258. [PMID: 38467984 DOI: 10.1007/978-981-99-9781-7_16] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/13/2024]
Abstract
Highly polymorphic human leukocyte antigen (HLA) molecules (alleles) expressed by different classical HLA class I and class II genes have crucial roles in the regulation of innate and adaptive immune responses, transplant rejection and in the pathogenesis of numerous infectious and autoimmune diseases. To date, over 35,000 HLA alleles have been published from the IPD-IMGT/HLA database, and specific HLA alleles and HLA haplotypes have been reported to be associated with more than 100 different diseases and phenotypes. Next generation sequencing (NGS) technology developed in recent years has provided breakthroughs in various HLA genomic/gene studies and transplant medicine. In this chapter, we review the current information on the HLA genomic structure and polymorphisms, as well as the genetic context in which numerous disease associations have been identified in this region.
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Affiliation(s)
| | - Jerzy K Kulski
- Tokai University School of Medicine, Isehara, Japan
- School of Biomedical Sciences, The University of Western Australia, Nedlands, Western Australia, Australia
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6
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Rocha Y, Jaramillo A, Neumann J, Hacke K, Palou E, Torres J. Crossmatch assays in transplantation: Physical or virtual?: A review. Medicine (Baltimore) 2023; 102:e36527. [PMID: 38115324 PMCID: PMC10727546 DOI: 10.1097/md.0000000000036527] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/25/2023] [Revised: 11/16/2023] [Accepted: 11/17/2023] [Indexed: 12/21/2023] Open
Abstract
The value of the crossmatch test in assessing pretransplant immunological risk is vital for clinical decisions, ranging from the indication of the transplant to the guidance of induction protocols and treatment with immunosuppressants. The crossmatch tests in transplantation can be physical or virtual, each with its advantages and limitations. Currently, the virtual crossmatch stands out for its sensitivity and specificity compared to the physical tests. Additionally, the virtual crossmatch can be performed in less time, allowing for a reduction in cold ischemia time. It shows a good correlation with the results of physical tests and does not negatively impact graft survival. Proper communication between clinicians and the transplant immunology laboratory will lead to a deeper understanding of each patient's immunological profile, better donor-recipient selection, and improved graft survival.
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Affiliation(s)
| | - Andrés Jaramillo
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Phoenix, AZ
| | - Jorge Neumann
- Transplant Immunology Laboratory, Santa Casa Hospital, Porto Alegre, Brazil
| | - Katrin Hacke
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Phoenix, AZ
| | - Eduard Palou
- Department of Immunology, Centre de Diagnòstic Biomèdic, Hospital Clínic de Barcelona, Barcelona, Spain
| | - Juan Torres
- Department of Immunology, Centre de Diagnòstic Biomèdic, Hospital Clínic de Barcelona, Barcelona, Spain
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7
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Kang JB, Shen AZ, Gurajala S, Nathan A, Rumker L, Aguiar VRC, Valencia C, Lagattuta KA, Zhang F, Jonsson AH, Yazar S, Alquicira-Hernandez J, Khalili H, Ananthakrishnan AN, Jagadeesh K, Dey K, Daly MJ, Xavier RJ, Donlin LT, Anolik JH, Powell JE, Rao DA, Brenner MB, Gutierrez-Arcelus M, Luo Y, Sakaue S, Raychaudhuri S. Mapping the dynamic genetic regulatory architecture of HLA genes at single-cell resolution. Nat Genet 2023; 55:2255-2268. [PMID: 38036787 PMCID: PMC10787945 DOI: 10.1038/s41588-023-01586-6] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2023] [Accepted: 10/19/2023] [Indexed: 12/02/2023]
Abstract
The human leukocyte antigen (HLA) locus plays a critical role in complex traits spanning autoimmune and infectious diseases, transplantation and cancer. While coding variation in HLA genes has been extensively documented, regulatory genetic variation modulating HLA expression levels has not been comprehensively investigated. Here we mapped expression quantitative trait loci (eQTLs) for classical HLA genes across 1,073 individuals and 1,131,414 single cells from three tissues. To mitigate technical confounding, we developed scHLApers, a pipeline to accurately quantify single-cell HLA expression using personalized reference genomes. We identified cell-type-specific cis-eQTLs for every classical HLA gene. Modeling eQTLs at single-cell resolution revealed that many eQTL effects are dynamic across cell states even within a cell type. HLA-DQ genes exhibit particularly cell-state-dependent effects within myeloid, B and T cells. For example, a T cell HLA-DQA1 eQTL ( rs3104371 ) is strongest in cytotoxic cells. Dynamic HLA regulation may underlie important interindividual variability in immune responses.
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Affiliation(s)
- Joyce B Kang
- Center for Data Sciences, Brigham and Women's Hospital, Boston, MA, USA
- Division of Genetics, 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
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Amber Z Shen
- Center for Data Sciences, Brigham and Women's Hospital, Boston, MA, USA
- Division of Genetics, 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
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Saisriram Gurajala
- Center for Data Sciences, Brigham and Women's Hospital, Boston, MA, USA
- Division of Genetics, 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
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, 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 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
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Laurie Rumker
- Center for Data Sciences, Brigham and Women's Hospital, Boston, MA, USA
- Division of Genetics, 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
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Vitor R C Aguiar
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Immunology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Cristian Valencia
- Center for Data Sciences, Brigham and Women's Hospital, Boston, MA, USA
- Division of Genetics, 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
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Kaitlyn A Lagattuta
- Center for Data Sciences, Brigham and Women's Hospital, Boston, MA, USA
- Division of Genetics, 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
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Fan Zhang
- Center for Data Sciences, Brigham and Women's Hospital, Boston, MA, USA
- Division of Genetics, 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
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Division of Rheumatology and the Center for Health Artificial Intelligence, University of Colorado School of Medicine, Aurora, CO, USA
| | - Anna Helena Jonsson
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Seyhan Yazar
- Garvan Institute of Medical Research, Sydney, New South Wales, Australia
| | | | - Hamed Khalili
- Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Ashwin N Ananthakrishnan
- Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | | | - Kushal Dey
- Harvard T. H. Chan School of Public Health, Boston, MA, USA
- Computational and Systems Biology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Physiology, Biophysics and Systems Biology Program, Weill Cornell Medicine, New York, NY, USA
| | - Mark J Daly
- Psychiatric and Neurodevelopmental Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- The Stanley Center for Psychiatric Research, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Ramnik J Xavier
- Klarman Cell Observatory, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Center for Computational and Integrative Biology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Department of Molecular Biology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Laura T Donlin
- Hospital for Special Surgery, New York, NY, USA
- Weill Cornell Medicine, New York, NY, USA
| | - Jennifer H Anolik
- Department of Medicine, University of Rochester Medical Center, Rochester, NY, USA
| | - Joseph E Powell
- Garvan Institute of Medical Research, Sydney, New South Wales, Australia
| | - Deepak A Rao
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Michael B Brenner
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Maria Gutierrez-Arcelus
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Immunology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Yang Luo
- Center for Data Sciences, Brigham and Women's Hospital, Boston, MA, USA
- Division of Genetics, 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
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Kennedy Institute of Rheumatology, University of Oxford, Oxford, UK
| | - Saori Sakaue
- Center for Data Sciences, Brigham and Women's Hospital, Boston, MA, USA
- Division of Genetics, 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
- 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, Boston, MA, USA.
- Division of Genetics, 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.
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
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8
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Nersesian S, Carter EB, Lee SN, Westhaver LP, Boudreau JE. Killer instincts: natural killer cells as multifactorial cancer immunotherapy. Front Immunol 2023; 14:1269614. [PMID: 38090565 PMCID: PMC10715270 DOI: 10.3389/fimmu.2023.1269614] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2023] [Accepted: 10/30/2023] [Indexed: 12/18/2023] Open
Abstract
Natural killer (NK) cells integrate heterogeneous signals for activation and inhibition using germline-encoded receptors. These receptors are stochastically co-expressed, and their concurrent engagement and signaling can adjust the sensitivity of individual cells to putative targets. Against cancers, which mutate and evolve under therapeutic and immunologic pressure, the diversity for recognition provided by NK cells may be key to comprehensive cancer control. NK cells are already being trialled as adoptive cell therapy and targets for immunotherapeutic agents. However, strategies to leverage their naturally occurring diversity and agility have not yet been developed. In this review, we discuss the receptors and signaling pathways through which signals for activation or inhibition are generated in NK cells, focusing on their roles in cancer and potential as targets for immunotherapies. Finally, we consider the impacts of receptor co-expression and the potential to engage multiple pathways of NK cell reactivity to maximize the scope and strength of antitumor activities.
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Affiliation(s)
- Sarah Nersesian
- Department of Microbiology and Immunology, Dalhousie University, Halifax, NS, Canada
- Beatrice Hunter Cancer Research Institute, Halifax, NS, Canada
| | - Emily B. Carter
- Department of Microbiology and Immunology, Dalhousie University, Halifax, NS, Canada
- Beatrice Hunter Cancer Research Institute, Halifax, NS, Canada
| | - Stacey N. Lee
- Department of Microbiology and Immunology, Dalhousie University, Halifax, NS, Canada
- Beatrice Hunter Cancer Research Institute, Halifax, NS, Canada
| | | | - Jeanette E. Boudreau
- Department of Microbiology and Immunology, Dalhousie University, Halifax, NS, Canada
- Beatrice Hunter Cancer Research Institute, Halifax, NS, Canada
- Department of Pathology, Dalhousie University, Halifax, NS, Canada
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9
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Lee MV, Saad OM, Wong S, LaMar J, Kamen L, Ordonia B, Melendez R, Hassanzadeh A, Chung S, Kaur S. Development of a semi-automated MHC-associated peptide proteomics (MAPPs) method using streptavidin bead-based immunoaffinity capture and nano LC-MS/MS to support immunogenicity risk assessment in drug development. Front Immunol 2023; 14:1295285. [PMID: 38022649 PMCID: PMC10667718 DOI: 10.3389/fimmu.2023.1295285] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2023] [Accepted: 10/26/2023] [Indexed: 12/01/2023] Open
Abstract
Major histocompatibility complex (MHC)-Associated Peptide Proteomics (MAPPs) is an ex vivo method used to assess the immunogenicity risk of biotherapeutics. MAPPs can identify potential T-cell epitopes within the biotherapeutic molecule. Using adalimumab treated human monocyte derived dendritic cells (DCs) and a pan anti-HLA-DR antibody (Ab), we systematically automated and optimized biotin/streptavidin (SA)-capture antibody coupling, lysate incubation with capture antibody, as well as the washing and elution steps of a MAPPs method using functionalized magnetic beads and a KingFisher Magnetic Particle processor. Automation of these steps, combined with capturing using biotinylated-Ab/SA magnetic beads rather than covalently bound antibody, improved reproducibility as measured by minimal inter-and intra-day variability, as well as minimal analyst-to-analyst variability. The semi-automated MAPPs workflow improved sensitivity, allowing for a lower number of cells per analysis. The method was assessed using five different biotherapeutics with varying immunogenicity rates ranging from 0.1 to 48% ADA incidence in the clinic. Biotherapeutics with ≥10%immunogenicity incidence consistently presented more peptides (1.8-28 fold) and clusters (10-21 fold) compared to those with <10% immunogenicity incidence. Our semi-automated MAPPs method provided two main advantages over a manual workflow- the robustness and reproducibility affords confidence in the epitopes identified from as few as 5 to 10 donors and the method workflow can be readily adapted to incorporate different capture Abs in addition to anti-HLA-DR. The incorporation of semi-automated MAPPs with biotinylated-Ab/SA bead-based capture in immunogenicity screening strategies allows the generation of more consistent and reliable data, helping to improve immunogenicity prediction capabilities in drug development. MHC associated peptide proteomics (MAPPs), Immunogenicity risk assessment, in vitro/ex vivo, biotherapeutics, Major Histocompatibility Complex Class II (MHC II), LC-MS, Immunoaffinity Capture, streptavidin magnetic beads.
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Affiliation(s)
| | - Ola M. Saad
- *Correspondence: M. Violet Lee, ; Ola M. Saad,
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10
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Zou ZL, Zhang Y, Huang YL, Wang JY, Zhou B, Chen HF. Pilot study of genome-wide DNA methylation and gene expression for treatment response to escitalopram in panic disorder. World J Psychiatry 2023; 13:524-532. [PMID: 37701547 PMCID: PMC10494772 DOI: 10.5498/wjp.v13.i8.524] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/17/2023] [Revised: 07/05/2023] [Accepted: 07/27/2023] [Indexed: 08/17/2023] Open
Abstract
BACKGROUND Antidepressants, particularly selective serotonin reuptake inhibitors, are currently considered the first-line treatment for panic disorder (PD). However, little is known about the relationship between the biomarkers that may predict better treatment. AIM To compare genome-wide methylation and gene expression patterns between responsive and non-responsive patients with PD after 4 wk of escitalopram treatment. METHODS Thirty patients with PD were enrolled in this study (responders = 13; non-responders = 17). All patients were assessed using the PD Severity Scale-Chinese version before and after treatment. The Illumina Infinium MethylationEPIC (850k) BeadChip for genome-wide methylation screening and mRNA sequencing was used in all patients with PD. RESULTS A total of 701 differentially methylated positions (DMPs) were found between responders and non-responders (|Δβ| ≥ 0.06, q < 0.05), and the hyper- and hypomethylated CpG sites were 511 (72.9%) and 190 (27.1%), respectively. Relative to non-responders, there were 59 differential transcripts, of which 20 were downregulated and 39 were upregulated (q < 0.05). However, no differentially expressed genes were identified by mRNA sequencing after correcting for multiple testing (|log2(FC)| > 1, q > 0.05). CONCLUSION This preliminary study showed that DMPs might be associated with the treatment response to escitalopram in PD; however, these DMPs need to be verified in large samples.
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Affiliation(s)
- Zhi-Li Zou
- Department of Psychosomatic Medicine, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu 611731, Sichuan Province, China
| | - Yuan Zhang
- Personalized Drug Therapy Key Laboratory of Sichuan Province, Sichuan Academy of Medical Sciences & Sichuan Provincial People's Hospital, Chengdu 610072, Sichuan Province, China
| | - Yu-Lan Huang
- Department of Psychosomatic Medicine, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu 611731, Sichuan Province, China
| | - Jin-Yu Wang
- Department of Psychosomatic Medicine, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu 611731, Sichuan Province, China
| | - Bo Zhou
- Department of Psychosomatic Medicine, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu 611731, Sichuan Province, China
| | - Hua-Fu Chen
- Department of Psychosomatic Medicine, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu 611731, Sichuan Province, China
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11
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Kang JB, Shen AZ, Sakaue S, Luo Y, Gurajala S, Nathan A, Rumker L, Aguiar VRC, Valencia C, Lagattuta K, Zhang F, Jonsson AH, Yazar S, Alquicira-Hernandez J, Khalili H, Ananthakrishnan AN, Jagadeesh K, Dey K, Daly MJ, Xavier RJ, Donlin LT, Anolik JH, Powell JE, Rao DA, Brenner MB, Gutierrez-Arcelus M, Raychaudhuri S. Mapping the dynamic genetic regulatory architecture of HLA genes at single-cell resolution. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.03.14.23287257. [PMID: 36993194 PMCID: PMC10055604 DOI: 10.1101/2023.03.14.23287257] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/19/2023]
Abstract
The human leukocyte antigen (HLA) locus plays a critical role in complex traits spanning autoimmune and infectious diseases, transplantation, and cancer. While coding variation in HLA genes has been extensively documented, regulatory genetic variation modulating HLA expression levels has not been comprehensively investigated. Here, we mapped expression quantitative trait loci (eQTLs) for classical HLA genes across 1,073 individuals and 1,131,414 single cells from three tissues, using personalized reference genomes to mitigate technical confounding. We identified cell-type-specific cis-eQTLs for every classical HLA gene. Modeling eQTLs at single-cell resolution revealed that many eQTL effects are dynamic across cell states even within a cell type. HLA-DQ genes exhibit particularly cell-state-dependent effects within myeloid, B, and T cells. Dynamic HLA regulation may underlie important interindividual variability in immune responses.
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Affiliation(s)
- Joyce B. Kang
- Center for Data Sciences, Brigham and Women’s Hospital, Boston, MA, USA
- Division of Genetics, 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
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | - Amber Z. Shen
- Center for Data Sciences, Brigham and Women’s Hospital, Boston, MA, USA
- Division of Genetics, 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
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | - Saori Sakaue
- Center for Data Sciences, Brigham and Women’s Hospital, Boston, MA, USA
- Division of Genetics, 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
- Division of Rheumatology, Inflammation, and Immunity, 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, Boston, MA, USA
- Division of Genetics, 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
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
- Kennedy Institute of Rheumatology, University of Oxford, Oxford, UK
| | - Saisriram Gurajala
- Center for Data Sciences, Brigham and Women’s Hospital, Boston, MA, USA
- Division of Genetics, 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
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, 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 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
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | - Laurie Rumker
- Center for Data Sciences, Brigham and Women’s Hospital, Boston, MA, USA
- Division of Genetics, 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
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | - Vitor R. C. Aguiar
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Immunology, Boston Children’s Hospital, Harvard Medical School, Boston, MA, USA
| | - Cristian Valencia
- Center for Data Sciences, Brigham and Women’s Hospital, Boston, MA, USA
- Division of Genetics, 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
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | - Kaitlyn Lagattuta
- Center for Data Sciences, Brigham and Women’s Hospital, Boston, MA, USA
- Division of Genetics, 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
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | - Fan Zhang
- Center for Data Sciences, Brigham and Women’s Hospital, Boston, MA, USA
- Division of Genetics, 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
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
- Division of Rheumatology and the Center for Health Artificial Intelligence, University of Colorado School of Medicine, Aurora, CO, USA
| | - Anna Helena Jonsson
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | - Seyhan Yazar
- Garvan Institute of Medical Research, Sydney, NSW, Australia
| | | | - Hamed Khalili
- Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Ashwin N. Ananthakrishnan
- Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | | | - Kushal Dey
- Harvard T. H. Chan School of Public Health, Boston, MA, USA
| | | | - Mark J. Daly
- Psychiatric and Neurodevelopmental Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- The Stanley Center for Psychiatric Research, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Ramnik J. Xavier
- Klarman Cell Observatory, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Center for Computational and Integrative Biology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Department of Molecular Biology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Laura T. Donlin
- Hospital for Special Surgery, New York, NY, USA
- Weill Cornell Medicine, New York, NY, USA
| | - Jennifer H. Anolik
- Department of Medicine, University of Rochester Medical Center, Rochester, NY, USA
| | | | - Deepak A. Rao
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | - Michael B. Brenner
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | - Maria Gutierrez-Arcelus
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Immunology, Boston Children’s Hospital, Harvard Medical School, Boston, MA, 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 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
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
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12
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Nørgaard-Pedersen C, Steffensen R, Kesmodel US, Christiansen OB. Maternal carriage of H-Y restricting HLA class II alleles is a negative prognostic factor for women with recurrent pregnancy loss after birth of a boy. J Reprod Immunol 2023; 156:103817. [PMID: 36753935 DOI: 10.1016/j.jri.2023.103817] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2022] [Revised: 01/18/2023] [Accepted: 01/23/2023] [Indexed: 01/26/2023]
Abstract
Immune system aberrations are suggested to be an important factor in the pathophysiology of unexplained secondary recurrent pregnancy loss (sRPL). The objective was to investigate if the sex ratio of the firstborn child in sRPL patients differs from the background population and whether the sex of the firstborn child has a negative impact on the pregnancy prognosis alone and/or in combination with carriage of male-specific minor histocompatibility (H-Y) restricting HLA class II alleles. From January 2016 to October 2022, 582 patients with unexplained RPL were admitted to the RPL Center of Western Denmark and continuously followed-up. HLA-DRB1 and -DQB1 typing was performed as part of the routine diagnostic work-up. In sRPL patients, a history of a firstborn boy was significantly more frequent than in the Danish background population and was associated with significantly lower odds of a successful reproductive outcome in the first pregnancy after admission compared to a firstborn girl (OR=0.41, 95% CI: 0.20-0.83, p = 0.014). The odds of a successful reproductive outcome were enhanced in patients carrying ≥ 1 H-Y-restricting HLA class II alleles with a first-born girl compared to a firstborn boy (OR=3.33, 95% CI: 1.40-7.88, p = 0.005), while no difference in successful reproductive outcome was seen in sRPL patients not carrying these alleles (OR=1.20, 95% CI: 0.33-4.43, p = 0.781). The sex ratio of children born after RPL was similar to the Danish background population. These findings confirm previous findings and suggests that a harmful immune response triggered by H-Y-antigen exposure during a previous pregnancy in preconditioned women may cause sRPL.
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Affiliation(s)
- C Nørgaard-Pedersen
- Centre for Recurrent Pregnancy loss of Western Denmark, Department of Obstetrics and Gynaecology, Aalborg University Hospital, Reberbansgade 15, 9000 Aalborg, Denmark; Department of Clinical Medicine, Søndre Skovvej 15, 9000 Aalborg, Denmark.
| | - R Steffensen
- Department of Clinical Immunology, Aalborg University Hospital, Urbansgade 32, 9000 Aalborg, Denmark.
| | - U S Kesmodel
- Centre for Recurrent Pregnancy loss of Western Denmark, Department of Obstetrics and Gynaecology, Aalborg University Hospital, Reberbansgade 15, 9000 Aalborg, Denmark; Department of Clinical Medicine, Søndre Skovvej 15, 9000 Aalborg, Denmark.
| | - O B Christiansen
- Centre for Recurrent Pregnancy loss of Western Denmark, Department of Obstetrics and Gynaecology, Aalborg University Hospital, Reberbansgade 15, 9000 Aalborg, Denmark; Department of Clinical Medicine, Søndre Skovvej 15, 9000 Aalborg, Denmark.
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13
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Aguiar VRC, Castelli EC, Single RM, Bashirova A, Ramsuran V, Kulkarni S, Augusto DG, Martin MP, Gutierrez-Arcelus M, Carrington M, Meyer D. Comparison between qPCR and RNA-seq reveals challenges of quantifying HLA expression. Immunogenetics 2023; 75:249-262. [PMID: 36707444 PMCID: PMC9883133 DOI: 10.1007/s00251-023-01296-7] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2022] [Accepted: 01/11/2023] [Indexed: 01/29/2023]
Abstract
Human leukocyte antigen (HLA) class I and II loci are essential elements of innate and acquired immunity. Their functions include antigen presentation to T cells leading to cellular and humoral immune responses, and modulation of NK cells. Their exceptional influence on disease outcome has now been made clear by genome-wide association studies. The exons encoding the peptide-binding groove have been the main focus for determining HLA effects on disease susceptibility/pathogenesis. However, HLA expression levels have also been implicated in disease outcome, adding another dimension to the extreme diversity of HLA that impacts variability in immune responses across individuals. To estimate HLA expression, immunogenetic studies traditionally rely on quantitative PCR (qPCR). Adoption of alternative high-throughput technologies such as RNA-seq has been hampered by technical issues due to the extreme polymorphism at HLA genes. Recently, however, multiple bioinformatic methods have been developed to accurately estimate HLA expression from RNA-seq data. This opens an exciting opportunity to quantify HLA expression in large datasets but also brings questions on whether RNA-seq results are comparable to those by qPCR. In this study, we analyze three classes of expression data for HLA class I genes for a matched set of individuals: (a) RNA-seq, (b) qPCR, and (c) cell surface HLA-C expression. We observed a moderate correlation between expression estimates from qPCR and RNA-seq for HLA-A, -B, and -C (0.2 ≤ rho ≤ 0.53). We discuss technical and biological factors which need to be accounted for when comparing quantifications for different molecular phenotypes or using different techniques.
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Affiliation(s)
- Vitor R. C. Aguiar
- Department of Genetics and Evolutionary Biology, Institute of Biosciences, University of São Paulo, São Paulo, SP Brazil ,Division of Immunology, Boston Children’s Hospital, Harvard Medical School, Boston, MA USA ,Broad Institute of MIT and Harvard, Cambridge, MA USA
| | - Erick C. Castelli
- Molecular Genetics and Bioinformatics Laboratory, Experimental Research Unit, School of Medicine, São Paulo State University, Botucatu, SP Brazil
| | - Richard M. Single
- Department of Mathematics and Statistics, University of Vermont, Burlington, VT USA
| | - Arman Bashirova
- Basic Science Program, Frederick National Laboratory for Cancer Research, National Cancer Institute, Frederick, MD USA ,Laboratory of Integrative Cancer Immunology, Center for Cancer Research, National Cancer Institute, Bethesda, MD USA
| | - Veron Ramsuran
- Basic Science Program, Frederick National Laboratory for Cancer Research, National Cancer Institute, Frederick, MD USA ,Laboratory of Integrative Cancer Immunology, Center for Cancer Research, National Cancer Institute, Bethesda, MD USA ,Centre for the AIDS Programme of Research in South Africa (CAPRISA), University of KwaZulu-Natal, Durban, South Africa ,School of Laboratory Medicine and Medical Sciences, University of KwaZulu-Natal, Durban, South Africa
| | - Smita Kulkarni
- Basic Science Program, Frederick National Laboratory for Cancer Research, National Cancer Institute, Frederick, MD USA ,Laboratory of Integrative Cancer Immunology, Center for Cancer Research, National Cancer Institute, Bethesda, MD USA ,Host-Pathogen Interactions Program, Texas Biomedical Research Institute, San Antonio, TX USA
| | - Danillo G. Augusto
- Basic Science Program, Frederick National Laboratory for Cancer Research, National Cancer Institute, Frederick, MD USA ,Laboratory of Integrative Cancer Immunology, Center for Cancer Research, National Cancer Institute, Bethesda, MD USA ,Department of Biological Sciences, The University of North Carolina at Charlotte, Charlotte, NC USA ,Programa de Pós-Graduação em Genética, Universidade Federal do Paraná, Curitiba, PR Brazil
| | - Maureen P. Martin
- Basic Science Program, Frederick National Laboratory for Cancer Research, National Cancer Institute, Frederick, MD USA ,Laboratory of Integrative Cancer Immunology, Center for Cancer Research, National Cancer Institute, Bethesda, MD USA
| | - 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
| | - Mary Carrington
- Basic Science Program, Frederick National Laboratory for Cancer Research, National Cancer Institute, Frederick, MD USA ,Laboratory of Integrative Cancer Immunology, Center for Cancer Research, National Cancer Institute, Bethesda, MD USA ,Ragon Institute of MGH, MIT and Harvard, Cambridge, MA USA
| | - Diogo Meyer
- Department of Genetics and Evolutionary Biology, Institute of Biosciences, University of São Paulo, São Paulo, SP Brazil
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14
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Lukacs M, Nymo IH, Madslien K, Våge J, Veiberg V, Rolandsen CM, Bøe CA, Sundaram AYM, Grimholt U. Functional immune diversity in reindeer reveals a high Arctic population at risk. Front Ecol Evol 2023. [DOI: 10.3389/fevo.2022.1058674] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2023] Open
Abstract
Climate changes the geographic range of both species as well as pathogens, causing a potential increase in the vulnerability of populations or species with limited genetic diversity. With advances in high throughput sequencing (HTS) technologies, we can now define functional expressed genetic diversity of wild species at a larger scale and identify populations at risk. Previous studies have used genomic DNA to define major histocompatibility complex (MHC) class II diversity in reindeer. Varying numbers of expressed genes found in many ungulates strongly argues for using cDNA in MHC typing strategies to ensure that diversity estimates relate to functional genes. We have used available reindeer genomes to identify candidate genes and established an HTS approach to define expressed MHC class I and class II diversity. To capture a broad diversity we included samples from wild reindeer from Southern Norway, semi-domesticated reindeer from Northern Norway and reindeer from the high Artic archipelago Svalbard. Our data show a medium MHC diversity in semi-domesticated and wild Norwegian mainland reindeer, and low MHC diversity reindeer in Svalbard reindeer. The low immune diversity in Svalbard reindeer provides a potential risk if the pathogenic pressure changes in response to altered environmental conditions due to climate change, or increased human-related activity.
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Human leukocyte antigen super-locus: nexus of genomic supergenes, SNPs, indels, transcripts, and haplotypes. Hum Genome Var 2022; 9:49. [PMID: 36543786 PMCID: PMC9772353 DOI: 10.1038/s41439-022-00226-5] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2022] [Revised: 11/08/2022] [Accepted: 11/15/2022] [Indexed: 12/24/2022] Open
Abstract
The human Major Histocompatibility Complex (MHC) or Human Leukocyte Antigen (HLA) super-locus is a highly polymorphic genomic region that encodes more than 140 coding genes including the transplantation and immune regulatory molecules. It receives special attention for genetic investigation because of its important role in the regulation of innate and adaptive immune responses and its strong association with numerous infectious and/or autoimmune diseases. In recent years, MHC genotyping and haplotyping using Sanger sequencing and next-generation sequencing (NGS) methods have produced many hundreds of genomic sequences of the HLA super-locus for comparative studies of the genetic architecture and diversity between the same and different haplotypes. In this special issue on 'The Current Landscape of HLA Genomics and Genetics', we provide a short review of some of the recent analytical developments used to investigate the SNP polymorphisms, structural variants (indels), transcription and haplotypes of the HLA super-locus. This review highlights the importance of using reference cell-lines, population studies, and NGS methods to improve and update our understanding of the mechanisms, architectural structures and combinations of human MHC genomic alleles (SNPs and indels) that better define and characterise haplotypes and their association with various phenotypes and diseases.
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16
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Houtman M, Dzebisashvili A, Dubnovitsky A, Kozhukh G, Rönnblom L, Klareskog L, Malmström V, Padyukov L. Five commercially-available antibodies react differentially with allelic forms of human HLA-DR beta chain. Mol Immunol 2022; 152:106-110. [DOI: 10.1016/j.molimm.2022.10.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2022] [Revised: 10/05/2022] [Accepted: 10/16/2022] [Indexed: 11/06/2022]
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17
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Castelli EC, de Castro MV, Naslavsky MS, Scliar MO, Silva NSB, Pereira RN, Ciriaco VAO, Castro CFB, Mendes-Junior CT, Silveira EDS, de Oliveira IM, Antonio EC, Vieira GF, Meyer D, Nunes K, Matos LRB, Silva MVR, Wang JYT, Esposito J, Cória VR, Magawa JY, Santos KS, Cunha-Neto E, Kalil J, Bortolin RH, Hirata MH, Dell’Aquila LP, Razuk-Filho A, Batista-Júnior PB, Duarte-Neto AN, Dolhnikoff M, Saldiva PHN, Passos-Bueno MR, Zatz M. MUC22, HLA-A, and HLA-DOB variants and COVID-19 in resilient super-agers from Brazil. Front Immunol 2022; 13:975918. [PMID: 36389712 PMCID: PMC9641602 DOI: 10.3389/fimmu.2022.975918] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2022] [Accepted: 09/15/2022] [Indexed: 08/08/2023] Open
Abstract
BACKGROUND Although aging correlates with a worse prognosis for Covid-19, super elderly still unvaccinated individuals presenting mild or no symptoms have been reported worldwide. Most of the reported genetic variants responsible for increased disease susceptibility are associated with immune response, involving type I IFN immunity and modulation; HLA cluster genes; inflammasome activation; genes of interleukins; and chemokines receptors. On the other hand, little is known about the resistance mechanisms against SARS-CoV-2 infection. Here, we addressed polymorphisms in the MHC region associated with Covid-19 outcome in super elderly resilient patients as compared to younger patients with a severe outcome. METHODS SARS-CoV-2 infection was confirmed by RT-PCR test. Aiming to identify candidate genes associated with host resistance, we investigated 87 individuals older than 90 years who recovered from Covid-19 with mild symptoms or who remained asymptomatic following positive test for SARS-CoV-2 as compared to 55 individuals younger than 60 years who had a severe disease or died due to Covid-19, as well as to the general elderly population from the same city. Whole-exome sequencing and an in-depth analysis of the MHC region was performed. All samples were collected in early 2020 and before the local vaccination programs started. RESULTS We found that the resilient super elderly group displayed a higher frequency of some missense variants in the MUC22 gene (a member of the mucins' family) as one of the strongest signals in the MHC region as compared to the severe Covid-19 group and the general elderly control population. For example, the missense variant rs62399430 at MUC22 is two times more frequent among the resilient super elderly (p = 0.00002, OR = 2.24). CONCLUSION Since the pro-inflammatory basal state in the elderly may enhance the susceptibility to severe Covid-19, we hypothesized that MUC22 might play an important protective role against severe Covid-19, by reducing overactive immune responses in the senior population.
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Affiliation(s)
- Erick C. Castelli
- Department of Pathology, School of Medicine, São Paulo State University (UNESP), Botucatu, Brazil
- Molecular Genetics and Bioinformatics Laboratory, Experimental Research Unit (Unipex), School of Medicine, São Paulo State University (UNESP), Botucatu, Brazil
| | - Mateus V. de Castro
- Human Genome and Stem Cell Research Center, University of São Paulo, São Paulo, Brazil
| | - Michel S. Naslavsky
- Human Genome and Stem Cell Research Center, University of São Paulo, São Paulo, Brazil
- Department of Genetics and Evolutionary Biology, Biosciences Institute, University of São Paulo, São Paulo, Brazil
| | - Marilia O. Scliar
- Human Genome and Stem Cell Research Center, University of São Paulo, São Paulo, Brazil
| | - Nayane S. B. Silva
- Molecular Genetics and Bioinformatics Laboratory, Experimental Research Unit (Unipex), School of Medicine, São Paulo State University (UNESP), Botucatu, Brazil
| | - Raphaela N. Pereira
- Molecular Genetics and Bioinformatics Laboratory, Experimental Research Unit (Unipex), School of Medicine, São Paulo State University (UNESP), Botucatu, Brazil
| | - Viviane A. O. Ciriaco
- Molecular Genetics and Bioinformatics Laboratory, Experimental Research Unit (Unipex), School of Medicine, São Paulo State University (UNESP), Botucatu, Brazil
| | - Camila F. B. Castro
- Molecular Genetics and Bioinformatics Laboratory, Experimental Research Unit (Unipex), School of Medicine, São Paulo State University (UNESP), Botucatu, Brazil
- Centro Universitário Sudoeste Paulista, Avaré, Brazil
| | - Celso T. Mendes-Junior
- Departamento de Química, Faculdade de Filosofa, Ciências e Letras de Ribeirão Preto, Universidade de São Paulo, Ribeirão Preto, Brazil
| | - Etiele de S. Silveira
- Programa de Pós-Graduação em Genética e Biologia Molecular, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil
| | - Iuri M. de Oliveira
- Programa de Pós-Graduação em Genética e Biologia Molecular, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil
| | - Eduardo C. Antonio
- Programa de Pós-Graduação em Genética e Biologia Molecular, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil
| | - Gustavo F. Vieira
- Programa de Pós-Graduação em Genética e Biologia Molecular, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil
- Laboratório de Saúde Humana In Silico, Programa de Pós-Graduação em Saúde e Desenvolvimento Humano, Universidade La Salle, Canoas, Brazil
| | - Diogo Meyer
- Department of Genetics and Evolutionary Biology, Biosciences Institute, University of São Paulo, São Paulo, Brazil
| | - Kelly Nunes
- Department of Genetics and Evolutionary Biology, Biosciences Institute, University of São Paulo, São Paulo, Brazil
| | - Larissa R. B. Matos
- Human Genome and Stem Cell Research Center, University of São Paulo, São Paulo, Brazil
| | - Monize V. R. Silva
- Human Genome and Stem Cell Research Center, University of São Paulo, São Paulo, Brazil
| | - Jaqueline Y. T. Wang
- Human Genome and Stem Cell Research Center, University of São Paulo, São Paulo, Brazil
| | - Joyce Esposito
- Human Genome and Stem Cell Research Center, University of São Paulo, São Paulo, Brazil
| | - Vivian R. Cória
- Human Genome and Stem Cell Research Center, University of São Paulo, São Paulo, Brazil
| | - Jhosiene Y. Magawa
- Departamento de Clínica Médica, Disciplina de Alergia e Imunologia Clínica, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
- Laboratório de Imunologia, Instituto do Coração (InCor), LIM19, Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo, (HCFMUSP), São Paulo, Brazil
- Instituto de Investigação em Imunologia, Instituto Nacional de Ciências e Tecnologia-iii (INCT), São Paulo, Brazil
| | - Keity S. Santos
- Departamento de Clínica Médica, Disciplina de Alergia e Imunologia Clínica, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
- Laboratório de Imunologia, Instituto do Coração (InCor), LIM19, Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo, (HCFMUSP), São Paulo, Brazil
- Instituto de Investigação em Imunologia, Instituto Nacional de Ciências e Tecnologia-iii (INCT), São Paulo, Brazil
| | - Edecio Cunha-Neto
- Departamento de Clínica Médica, Disciplina de Alergia e Imunologia Clínica, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
- Laboratório de Imunologia, Instituto do Coração (InCor), LIM19, Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo, (HCFMUSP), São Paulo, Brazil
- Instituto de Investigação em Imunologia, Instituto Nacional de Ciências e Tecnologia-iii (INCT), São Paulo, Brazil
| | - Jorge Kalil
- Departamento de Clínica Médica, Disciplina de Alergia e Imunologia Clínica, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
- Laboratório de Imunologia, Instituto do Coração (InCor), LIM19, Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo, (HCFMUSP), São Paulo, Brazil
- Instituto de Investigação em Imunologia, Instituto Nacional de Ciências e Tecnologia-iii (INCT), São Paulo, Brazil
| | - Raul H. Bortolin
- Department of Clinical and Toxicological Analyses, School of Pharmaceutical Sciences, University of São Paulo, São Paulo, Brazil
| | - Mário Hiroyuki Hirata
- Department of Clinical and Toxicological Analyses, School of Pharmaceutical Sciences, University of São Paulo, São Paulo, Brazil
| | | | | | | | - Amaro N. Duarte-Neto
- Department of Pathology, School of Medicine, University of Sao Paulo, Sao Paulo, Brazil
| | - Marisa Dolhnikoff
- Department of Pathology, School of Medicine, University of Sao Paulo, Sao Paulo, Brazil
| | - Paulo H. N. Saldiva
- Department of Pathology, School of Medicine, University of Sao Paulo, Sao Paulo, Brazil
| | - Maria Rita Passos-Bueno
- Human Genome and Stem Cell Research Center, University of São Paulo, São Paulo, Brazil
- Department of Genetics and Evolutionary Biology, Biosciences Institute, University of São Paulo, São Paulo, Brazil
| | - Mayana Zatz
- Human Genome and Stem Cell Research Center, University of São Paulo, São Paulo, Brazil
- Department of Genetics and Evolutionary Biology, Biosciences Institute, University of São Paulo, São Paulo, Brazil
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18
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Johansson T, Partanen J, Saavalainen P. HLA allele-specific expression: Methods, disease associations, and relevance in hematopoietic stem cell transplantation. Front Immunol 2022; 13:1007425. [PMID: 36248878 PMCID: PMC9554311 DOI: 10.3389/fimmu.2022.1007425] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2022] [Accepted: 09/09/2022] [Indexed: 11/27/2022] Open
Abstract
Varying HLA allele-specific expression levels are associated with human diseases, such as graft versus host disease (GvHD) in hematopoietic stem cell transplantation (HSCT), cytotoxic T cell response and viral load in HIV infection, and the risk of Crohn’s disease. Only recently, RNA-based next generation sequencing (NGS) methodologies with accompanying bioinformatics tools have emerged to quantify HLA allele-specific expression replacing the quantitative PCR (qPCR) -based methods. These novel NGS approaches enable the systematic analysis of the HLA allele-specific expression changes between individuals and between normal and disease phenotypes. Additionally, analyzing HLA allele-specific expression and allele-specific expression loss provide important information for predicting efficacies of novel immune cell therapies. Here, we review available RNA sequencing-based approaches and computational tools for NGS to quantify HLA allele-specific expression. Moreover, we explore recent studies reporting disease associations with differential HLA expression. Finally, we discuss the role of allele-specific expression in HSCT and how considering the expression quantification in recipient-donor matching could improve the outcome of HSCT.
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Affiliation(s)
- Tiira Johansson
- Translational Immunology Research Program, Research Programs Unit, University of Helsinki, Helsinki, Finland
- Research and Development, Finnish Red Cross Blood Service, Helsinki, Finland
- *Correspondence: Tiira Johansson,
| | - Jukka Partanen
- Research and Development, Finnish Red Cross Blood Service, Helsinki, Finland
| | - Päivi Saavalainen
- Translational Immunology Research Program, Research Programs Unit, University of Helsinki, Helsinki, Finland
- Genetics Research Program, Folkhälsan Research Center, Helsinki, Finland
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19
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Suslova TA, Vavilov MN, Belyaeva SV, Evdokimov AV, Stashkevich DS, Galkin A, Kofiadi IA. Distribution of HLA-A, -B, -C, -DRB1, -DQB1, -DPB1 allele frequencies in patients with COVID-19 bilateral pneumonia in Russians, living in the Chelyabinsk region (Russia). Hum Immunol 2022; 83:547-550. [PMID: 35525710 PMCID: PMC9046060 DOI: 10.1016/j.humimm.2022.04.009] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2021] [Revised: 04/06/2022] [Accepted: 04/23/2022] [Indexed: 12/14/2022]
Abstract
In this population-based case-control study conducted in the Chelyabinsk region of Russia, we examined the distribution of HLA-A, -B, -C, -DRB1, -DQB1 and -DPB1, in a group of 100 patients with confirmed COVID-19 bilateral pneumonia. Typing was performed by NGS and statistical calculations were carried out with the Arlequin program. HLA-A, -B, -C, -DRB1, -DQB1 and -DPB1 alleles were compared between patients with COVID-19 and 99 healthy controls. We identified that COVID-19 susceptibility is associated with alleles and genotypes rs9277534A (disequilibrium with HLA-DPB1*02:01, -02:02, -04:01, -04:02, -17:01 alleles) with low expression of protein products HLA-DPB1 (pc < 0.028) and homozygosity at HLA-C*04 (p = 0.024, pc = 0.312). Allele HLA-A*01:01 was decreased in a group of patients with severe forms of bilateral pneumonia, and therefore it may be considered as a protective factor for the development of severe symptoms of COVID-19 (p = 0.009, pc = 0.225). Our studies provide further evidence for the functional association between HLA genes and COVID-19.
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Affiliation(s)
| | | | | | | | | | - Alexander Galkin
- Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, 407 East 61st Street, New York, NY 10065, United States
| | - Ilya A Kofiadi
- Pirogov Russian National Reseach Medical University, Moscow, Russia
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20
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Ellinghaus D. How genetic risk contributes to autoimmune liver disease. Semin Immunopathol 2022; 44:397-410. [PMID: 35650446 PMCID: PMC9256578 DOI: 10.1007/s00281-022-00950-8] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2022] [Accepted: 05/06/2022] [Indexed: 12/16/2022]
Abstract
Genome-wide association studies (GWAS) for autoimmune hepatitis (AIH) and GWAS/genome-wide meta-analyses (GWMA) for primary biliary cholangitis (PBC) and primary sclerosing cholangitis (PSC) have been successful over the past decade, identifying about 100 susceptibility loci in the human genome, with strong associations with the HLA locus and many susceptibility variants outside the HLA locus with relatively low risk. However, identifying causative variants and genes and determining their effects on liver cells and their immunological microenvironment is far from trivial. Polygenic risk scores (PRSs) based on current genome-wide data have limited potential to predict individual disease risk. Interestingly, results of mediated expression score regression analysis provide evidence that a substantial portion of gene expression at susceptibility loci is mediated by genetic risk variants, in contrast to many other complex diseases. Genome- and transcriptome-wide comparisons between AIH, PBC, and PSC could help to better delineate the shared inherited component of autoimmune liver diseases (AILDs), and statistical fine-mapping, chromosome X-wide association testing, and genome-wide in silico drug screening approaches recently applied to GWMA data from PBC could potentially be successfully applied to AIH and PSC. Initial successes through single-cell RNA sequencing (scRNA-seq) experiments in PBC and PSC now raise high hopes for understanding the impact of genetic risk variants in the context of liver-resident immune cells and liver cell subpopulations, and for bridging the gap between genetics and disease.
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Affiliation(s)
- David Ellinghaus
- Institute of Clinical Molecular Biology (IKMB), Kiel University and University Medical Center Schleswig-Holstein, Rosalind-Franklin-Str. 12, 24105, Kiel, Germany.
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21
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Regulation of HLA class I expression by non-coding gene variations. PLoS Genet 2022; 18:e1010212. [PMID: 35666741 PMCID: PMC9170083 DOI: 10.1371/journal.pgen.1010212] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2021] [Accepted: 04/20/2022] [Indexed: 11/19/2022] Open
Abstract
The Human Leukocyte Antigen (HLA) is a critical genetic system for different outcomes after solid organ and hematopoietic cell transplantation. Its polymorphism is usually determined by molecular technologies at the DNA level. A potential role of HLA allelic expression remains under investigation in the context of the allogenic immune response between donors and recipients. In this study, we quantified the allelic expression of all three HLA class I loci (HLA-A, B and C) by RNA sequencing and conducted an analysis of expression quantitative traits loci (eQTL) to investigate whether HLA expression regulation could be associated with non-coding gene variations. HLA-B alleles exhibited the highest expression levels followed by HLA-C and HLA-A alleles. The max fold expression variation was observed for HLA-C alleles. The expression of HLA class I loci of distinct individuals demonstrated a coordinated and paired expression of both alleles of the same locus. Expression of conserved HLA-A~B~C haplotypes differed in distinct PBMC's suggesting an individual regulated expression of both HLA class I alleles and haplotypes. Cytokines TNFα /IFNβ, which induced a very similar upregulation of HLA class I RNA and cell surface expression across alleles did not modify the individually coordinated expression at the three HLA class I loci. By identifying cis eQTLs for the HLA class I genes, we show that the non-coding eQTLs explain 29%, 13%, and 31% of the respective HLA-A, B, C expression variance in unstimulated cells, and 9%, 23%, and 50% of the variance in cytokine-stimulated cells. The eQTLs have significantly higher effect sizes in stimulated cells compared to unstimulated cells for HLA-B and HLA-C genes expression. Our data also suggest that the identified eQTLs are independent from the coding variation which defines HLA alleles and thus may be influential on intra-allele expression variability although they might not represent the causal eQTLs.
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22
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Petersdorf EW, Bengtsson M, Horowitz M, McKallor C, Spellman SR, Spierings E, Gooley TA, Stevenson P. HLA-DQ heterodimers in hematopoietic cell transplantation. Blood 2022; 139:3009-3017. [PMID: 35271697 PMCID: PMC9121842 DOI: 10.1182/blood.2022015860] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2022] [Accepted: 02/24/2022] [Indexed: 11/20/2022] Open
Abstract
HLA-DQ heterodimers increase the susceptibility to autoimmune diseases, but their role in hematopoietic cell transplantation is unknown. We tested the hypothesis that outcome after HLA-matched and HLA-DQ-mismatched hematopoietic cell transplantation is influenced by HLA-DQ heterodimers. Heterodimers were defined in 5164 HLA-matched and 520 HLA-DQ-mismatched patients and their transplant donors according to well-established crystallographic criteria. Group 1 (G1) heterodimers are any DQA1*02/03/04/05/06α paired with any DQB1*02/03/04β. Group 2 (G2) heterodimers are DQA1*01α paired with any DQB1*05/06β. Multivariable models identified significantly higher relapse risk in G1G2 and G2G2 compared with G1G1 HLA-matched patients with malignant disease; risk increased with an increasing number of G2 molecules. In HLA-DQ-mismatched transplantation for malignant diseases, matching or mismatching for G2 increased relapse risk. G2 lowered disease-free survival after both HLA-matched and HLA-DQ-mismatched transplantation. A paradigm based on HLA-DQ heterodimers provides a functional definition of the hematopoietic cell transplantation barrier and a means to lower risks for future patients.
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Affiliation(s)
- Effie W Petersdorf
- Division of Clinical Research, Fred Hutchinson Cancer Research Center, Seattle, WA
- Department of Medicine, University of Washington, Seattle, WA
| | - Mats Bengtsson
- Department of Immunology, Genetics, and Pathology, University of Uppsala, Uppsala, Sweden
| | - Mary Horowitz
- Center for International Blood and Marrow Transplant Research, Milwaukee, WI
- Division of Hematology and Oncology, Medical College of Wisconsin, Milwaukee, WI
| | - Caroline McKallor
- Division of Clinical Research, Fred Hutchinson Cancer Research Center, Seattle, WA
| | - Stephen R Spellman
- Center for International Blood and Marrow Transplant Research, Minneapolis, MN
| | - Eric Spierings
- Matchis Foundation, Leiden, The Netherlands; and
- University Medical Center Utrecht, Utrecht, The Netherlands
| | - Ted A Gooley
- Division of Clinical Research, Fred Hutchinson Cancer Research Center, Seattle, WA
| | - Phil Stevenson
- Division of Clinical Research, Fred Hutchinson Cancer Research Center, Seattle, WA
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23
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Fuchs EJ, McCurdy SR, Solomon SR, Wang T, Herr MM, Modi D, Grunwald MR, Nishihori T, Kuxhausen M, Fingerson S, McKallor C, Bashey A, Kasamon YL, Bolon YT, Saad A, McGuirk J, Paczesny S, Gadalla SM, Marsh SGE, Shaw BE, Spellman SR, Lee SJ, Petersdorf EW. HLA informs risk predictions after haploidentical stem cell transplantation with posttransplantation cyclophosphamide. Blood 2022; 139:1452-1468. [PMID: 34724567 PMCID: PMC8914182 DOI: 10.1182/blood.2021013443] [Citation(s) in RCA: 46] [Impact Index Per Article: 23.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2021] [Accepted: 10/18/2021] [Indexed: 11/20/2022] Open
Abstract
Hematopoietic cell transplantation from HLA-haploidentical related donors is increasingly used to treat hematologic cancers; however, characteristics of the optimal haploidentical donor have not been established. We studied the role of donor HLA mismatching in graft-versus-host disease (GVHD), disease recurrence, and survival after haploidentical donor transplantation with posttransplantation cyclophosphamide (PTCy) for 1434 acute leukemia or myelodysplastic syndrome patients reported to the Center for International Blood and Marrow Transplant Research. The impact of mismatching in the graft-versus-host vector for HLA-A, -B, -C, -DRB1, and -DQB1 alleles, the HLA-B leader, and HLA-DPB1 T-cell epitope (TCE) were studied using multivariable regression methods. Outcome was associated with HLA (mis)matches at individual loci rather than the total number of HLA mismatches. HLA-DRB1 mismatches were associated with lower risk of disease recurrence. HLA-DRB1 mismatching with HLA-DQB1 matching correlated with improved disease-free survival. HLA-B leader matching and HLA-DPB1 TCE-nonpermissive mismatching were each associated with improved overall survival. HLA-C matching lowered chronic GVHD risk, and the level of HLA-C expression correlated with transplant-related mortality. Matching status at the HLA-B leader and HLA-DRB1, -DQB1, and -DPB1 predicted disease-free survival, as did patient and donor cytomegalovirus serostatus, patient age, and comorbidity index. A web-based tool was developed to facilitate selection of the best haploidentical-related donor by calculating disease-free survival based on these characteristics. In conclusion, HLA factors influence the success of haploidentical transplantation with PTCy. HLA-DRB1 and -DPB1 mismatching and HLA-C, -B leader, and -DQB1 matching are favorable. Consideration of HLA factors may help to optimize the selection of haploidentical related donors.
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Affiliation(s)
- Ephraim J Fuchs
- Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins Hospital, Baltimore, MD
| | | | - Scott R Solomon
- Northside Hospital Cancer Institute, Blood and Marrow Transplant Program, Atlanta, GA
| | - Tao Wang
- Department of Medicine, Center for International Blood and Marrow Transplant Research (CIBMTR), Medical College of Wisconsin, Milwaukee, WI
- Division of Biostatistics, Institute for Health and Equity, Medical College of Wisconsin, Milwaukee, WI
| | | | | | - Michael R Grunwald
- Department of Hematologic Oncology and Blood Disorders, Levine Cancer Institute, Atrium Health, Charlotte, NC
| | - Taiga Nishihori
- Department of Blood and Marrow Transplant and Cellular Immunotherapy (BMT CI), Moffitt Cancer Center, Tampa, FL
| | - Michelle Kuxhausen
- CIBMTR, National Marrow Donor Program/Be The Match Foundation, Minneapolis, MN
| | - Stephanie Fingerson
- CIBMTR, National Marrow Donor Program/Be The Match Foundation, Minneapolis, MN
| | - Caroline McKallor
- Division of Clinical Research, Fred Hutchinson Cancer Research Center, Seattle, WA
| | - Asad Bashey
- Northside Hospital Cancer Institute, Blood and Marrow Transplant Program, Atlanta, GA
| | - Yvette L Kasamon
- Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins Hospital, Baltimore, MD
| | - Yung-Tsi Bolon
- CIBMTR, National Marrow Donor Program/Be The Match Foundation, Minneapolis, MN
| | - Ayman Saad
- Division of Hematology, Ohio State University, Columbus, OH
| | - Joseph McGuirk
- Division of Hematologic Malignancies and Cellular Therapeutics, The University of Kansas Cancer Center, Kansas City, KS
| | - Sophie Paczesny
- Department of Microbiology and Immunology, Medical University of South Carolina, Charleston, SC
| | - Shahinaz M Gadalla
- Division of Cancer Epidemiology and Genetics, National Institutes of Health, National Cancer Institute, Clinical Genetics Branch, Rockville, MD
| | - Steven G E Marsh
- Anthony Nolan Research Institute-University College London Cancer Institute, Royal Free Campus, London, United Kingdom; and
| | - Bronwen E Shaw
- Department of Medicine, Center for International Blood and Marrow Transplant Research (CIBMTR), Medical College of Wisconsin, Milwaukee, WI
| | - Stephen R Spellman
- CIBMTR, National Marrow Donor Program/Be The Match Foundation, Minneapolis, MN
| | - Stephanie J Lee
- Division of Clinical Research, Fred Hutchinson Cancer Research Center, Seattle, WA
- Department of Medicine, CIBMTR, Medical College of Wisconsin, Milwaukee, WI
| | - Effie W Petersdorf
- Division of Clinical Research, Fred Hutchinson Cancer Research Center, Seattle, WA
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24
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Spencer Mangum D, Caywood E. A clinician’s guide to HLA matching in allogeneic hematopoietic stem cell transplant. Hum Immunol 2022; 83:687-694. [DOI: 10.1016/j.humimm.2022.03.002] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2021] [Revised: 02/14/2022] [Accepted: 03/02/2022] [Indexed: 12/26/2022]
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25
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Downregulation of HLA class II is associated with relapse after allogeneic stem cell transplantation and alters recognition by antigen-specific T cells. Int J Hematol 2022; 115:371-381. [PMID: 35037229 DOI: 10.1007/s12185-021-03273-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2021] [Revised: 12/06/2021] [Accepted: 12/06/2021] [Indexed: 10/19/2022]
Abstract
Genomic deletion of donor-patient-mismatched HLA alleles in leukemic cells is a major cause of relapse after allogeneic hematopoietic stem cell transplantation (HSCT). Mismatched HLA is frequently lost as an individual allele or a whole region in HLA-class I, however, it is downregulated in HLA-class II. We hypothesized that there might be a difference in T cell recognition capacity against epitopes associated with HLA-class I and HLA-class II and consequently such allogeneic immune pressure induced HLA alterations in leukemic cells. To investigate this, we conducted in vitro experiments with T cell receptor-transduced T (TCR-T) cells. The cytotoxic activity of NY-ESO-1-specific TCR-T cells exhibited similarly against K562 cells with low HLA-A*02:01 expression. However, we demonstrated that the cytokine production against low HLA-DPB1*05:01 expression line decreased gradually from the HLA expression level approximately 2-log lower than normal expressors. Using sort-purified leukemia cells before and after HSCT, we applied the next-generation sequencing, and revealed that there were several marked downregulations of HLA-class II alleles which demonstrated consistently low expression from pre-transplantation. The marked downregulation of HLA-class II may lead to decreased antigen recognition ability of antigen-specific T cells and may be one of immune evasion mechanism associated with HLA-class II downregulation.
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26
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Naito T, Okada Y. HLA imputation and its application to genetic and molecular fine-mapping of the MHC region in autoimmune diseases. Semin Immunopathol 2022; 44:15-28. [PMID: 34786601 PMCID: PMC8837514 DOI: 10.1007/s00281-021-00901-9] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2021] [Accepted: 10/22/2021] [Indexed: 12/19/2022]
Abstract
Variations of human leukocyte antigen (HLA) genes in the major histocompatibility complex region (MHC) significantly affect the risk of various diseases, especially autoimmune diseases. Fine-mapping of causal variants in this region was challenging due to the difficulty in sequencing and its inapplicability to large cohorts. Thus, HLA imputation, a method to infer HLA types from regional single nucleotide polymorphisms, has been developed and has successfully contributed to MHC fine-mapping of various diseases. Different HLA imputation methods have been developed, each with its own advantages, and recent methods have been improved in terms of accuracy and computational performance. Additionally, advances in HLA reference panels by next-generation sequencing technologies have enabled higher resolution and a more reliable imputation, allowing a finer-grained evaluation of the association between sequence variations and disease risk. Risk-associated variants in the MHC region would affect disease susceptibility through complicated mechanisms including alterations in peripheral responses and central thymic selection of T cells. The cooperation of reliable HLA imputation methods, informative fine-mapping, and experimental validation of the functional significance of MHC variations would be essential for further understanding of the role of the MHC in the immunopathology of autoimmune diseases.
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Affiliation(s)
- Tatsuhiko Naito
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, 2-2 Yamadaoka, Osaka, Suita, 565-0871, Japan.
- Department of Neurology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.
| | - Yukinori Okada
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, 2-2 Yamadaoka, Osaka, Suita, 565-0871, Japan
- Laboratory of Statistical Immunology, Immunology Frontier Research Center (WPI-IFReC), Osaka University, Suita, Japan
- Integrated Frontier Research for Medical Science Division, Institute for Open and Transdisciplinary Research Initiatives, Osaka University, Suita, Japan
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27
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Castelli EC, de Castro MV, Naslavsky MS, Scliar MO, Silva NSB, Andrade HS, Souza AS, Pereira RN, Castro CFB, Mendes-Junior CT, Meyer D, Nunes K, Matos LRB, Silva MVR, Wang JYT, Esposito J, Coria VR, Bortolin RH, Hirata MH, Magawa JY, Cunha-Neto E, Coelho V, Santos KS, Marin MLC, Kalil J, Mitne-Neto M, Maciel RMB, Passos-Bueno MR, Zatz M. MHC Variants Associated With Symptomatic Versus Asymptomatic SARS-CoV-2 Infection in Highly Exposed Individuals. Front Immunol 2021; 12:742881. [PMID: 34650566 PMCID: PMC8506217 DOI: 10.3389/fimmu.2021.742881] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2021] [Accepted: 09/06/2021] [Indexed: 12/11/2022] Open
Abstract
Despite the high number of individuals infected by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) who develop coronavirus disease 2019 (COVID-19) symptoms worldwide, many exposed individuals remain asymptomatic and/or uninfected and seronegative. This could be explained by a combination of environmental (exposure), immunological (previous infection), epigenetic, and genetic factors. Aiming to identify genetic factors involved in immune response in symptomatic COVID-19 as compared to asymptomatic exposed individuals, we analyzed 83 Brazilian couples where one individual was infected and symptomatic while the partner remained asymptomatic and serum-negative for at least 6 months despite sharing the same bedroom during the infection. We refer to these as "discordant couples". We performed whole-exome sequencing followed by a state-of-the-art method to call genotypes and haplotypes across the highly polymorphic major histocompatibility complex (MHC) region. The discordant partners had comparable ages and genetic ancestry, but women were overrepresented (65%) in the asymptomatic group. In the antigen-presentation pathway, we observed an association between HLA-DRB1 alleles encoding Lys at residue 71 (mostly DRB1*03:01 and DRB1*04:01) and DOB*01:02 with symptomatic infections and HLA-A alleles encoding 144Q/151R with asymptomatic seronegative women. Among the genes related to immune modulation, we detected variants in MICA and MICB associated with symptomatic infections. These variants are related to higher expression of soluble MICA and low expression of MICB. Thus, quantitative differences in these molecules that modulate natural killer (NK) activity could contribute to susceptibility to COVID-19 by downregulating NK cell cytotoxic activity in infected individuals but not in the asymptomatic partners.
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Affiliation(s)
- Erick C. Castelli
- Department of Pathology, School of Medicine, São Paulo State University (UNESP), Botucatu, Brazil
- Molecular Genetics and Bioinformatics Laboratory–Experimental Research Unit, School of Medicine, São Paulo State University (UNESP), Botucatu, Brazil
| | - Mateus V. de Castro
- Human Genome and Stem Cell Research Center, University of São Paulo, São Paulo, Brazil
| | - Michel S. Naslavsky
- Human Genome and Stem Cell Research Center, University of São Paulo, São Paulo, Brazil
- Department of Genetics and Evolutionary Biology, Biosciences Institute, University of São Paulo, São Paulo, Brazil
| | - Marilia O. Scliar
- Human Genome and Stem Cell Research Center, University of São Paulo, São Paulo, Brazil
| | - Nayane S. B. Silva
- Molecular Genetics and Bioinformatics Laboratory–Experimental Research Unit, School of Medicine, São Paulo State University (UNESP), Botucatu, Brazil
| | - Heloisa S. Andrade
- Molecular Genetics and Bioinformatics Laboratory–Experimental Research Unit, School of Medicine, São Paulo State University (UNESP), Botucatu, Brazil
| | - Andreia S. Souza
- Molecular Genetics and Bioinformatics Laboratory–Experimental Research Unit, School of Medicine, São Paulo State University (UNESP), Botucatu, Brazil
| | - Raphaela N. Pereira
- Molecular Genetics and Bioinformatics Laboratory–Experimental Research Unit, School of Medicine, São Paulo State University (UNESP), Botucatu, Brazil
| | - Camila F. B. Castro
- Molecular Genetics and Bioinformatics Laboratory–Experimental Research Unit, School of Medicine, São Paulo State University (UNESP), Botucatu, Brazil
- Centro Universitário Sudoeste Paulista, Avaré, Brazil
| | - Celso T. Mendes-Junior
- Departamento de Química, Faculdade de Filosofa, Ciências e Letras de Ribeirão Preto, Universidade de São Paulo, Ribeirão Preto, Brazil
| | - Diogo Meyer
- Department of Genetics and Evolutionary Biology, Biosciences Institute, University of São Paulo, São Paulo, Brazil
| | - Kelly Nunes
- Department of Genetics and Evolutionary Biology, Biosciences Institute, University of São Paulo, São Paulo, Brazil
| | - Larissa R. B. Matos
- Human Genome and Stem Cell Research Center, University of São Paulo, São Paulo, Brazil
| | - Monize V. R. Silva
- Human Genome and Stem Cell Research Center, University of São Paulo, São Paulo, Brazil
| | - Jaqueline Y. T. Wang
- Human Genome and Stem Cell Research Center, University of São Paulo, São Paulo, Brazil
| | - Joyce Esposito
- Human Genome and Stem Cell Research Center, University of São Paulo, São Paulo, Brazil
| | - Vivian R. Coria
- Human Genome and Stem Cell Research Center, University of São Paulo, São Paulo, Brazil
| | - Raul H. Bortolin
- Department of Clinical and Toxicological Analyses, School of Pharmaceutical Sciences, University of São Paulo, São Paulo, Brazil
| | - Mario H. Hirata
- Department of Clinical and Toxicological Analyses, School of Pharmaceutical Sciences, University of São Paulo, São Paulo, Brazil
| | - Jhosiene Y. Magawa
- Departamento de Clínica Médica, Disciplina de Alergia e Imunologia Clínica, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
| | - Edecio Cunha-Neto
- Departamento de Clínica Médica, Disciplina de Alergia e Imunologia Clínica, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
- Laboratório de Imunologia, Instituto do Coração (InCor), LIM19, Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo, (HCFMUSP), São Paulo, Brazil
- Instituto de Investigação em Imunologia - Instituto Nacional de Ciências e Tecnologia-iii-INCT, São Paulo, Brazil
| | - Verônica Coelho
- Laboratório de Imunologia, Instituto do Coração (InCor), LIM19, Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo, (HCFMUSP), São Paulo, Brazil
- Instituto de Investigação em Imunologia - Instituto Nacional de Ciências e Tecnologia-iii-INCT, São Paulo, Brazil
| | - Keity S. Santos
- Departamento de Clínica Médica, Disciplina de Alergia e Imunologia Clínica, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
- Laboratório de Imunologia, Instituto do Coração (InCor), LIM19, Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo, (HCFMUSP), São Paulo, Brazil
- Instituto de Investigação em Imunologia - Instituto Nacional de Ciências e Tecnologia-iii-INCT, São Paulo, Brazil
| | - Maria Lucia C. Marin
- Laboratório de Imunologia, Instituto do Coração (InCor), LIM19, Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo, (HCFMUSP), São Paulo, Brazil
- Instituto de Investigação em Imunologia - Instituto Nacional de Ciências e Tecnologia-iii-INCT, São Paulo, Brazil
| | - Jorge Kalil
- Departamento de Clínica Médica, Disciplina de Alergia e Imunologia Clínica, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
- Laboratório de Imunologia, Instituto do Coração (InCor), LIM19, Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo, (HCFMUSP), São Paulo, Brazil
- Instituto de Investigação em Imunologia - Instituto Nacional de Ciências e Tecnologia-iii-INCT, São Paulo, Brazil
| | | | | | - Maria Rita Passos-Bueno
- Human Genome and Stem Cell Research Center, University of São Paulo, São Paulo, Brazil
- Department of Genetics and Evolutionary Biology, Biosciences Institute, University of São Paulo, São Paulo, Brazil
| | - Mayana Zatz
- Human Genome and Stem Cell Research Center, University of São Paulo, São Paulo, Brazil
- Department of Genetics and Evolutionary Biology, Biosciences Institute, University of São Paulo, São Paulo, Brazil
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28
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Suzuki S, Shigenari A, Ito S, Kulski JK, Shiina T. Identification of three novel HLA-DRA alleles by next-generation sequencing. HLA 2021; 98:560-562. [PMID: 34402606 DOI: 10.1111/tan.14412] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2021] [Revised: 08/11/2021] [Accepted: 08/12/2021] [Indexed: 01/09/2023]
Abstract
Three novel HLA-DRA alleles, DRA*01:03, DRA*01:04, and DRA*01:05 alleles with unique amino acid sequences.
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Affiliation(s)
- Shingo Suzuki
- Department of Molecular Life Science, Division of Basic Medical Science and Molecular Medicine, Tokai University School of Medicine, Isehara, Japan
| | - Atsuko Shigenari
- Department of Molecular Life Science, Division of Basic Medical Science and Molecular Medicine, Tokai University School of Medicine, Isehara, Japan
| | - Sayaka Ito
- Department of Molecular Life Science, Division of Basic Medical Science and Molecular Medicine, Tokai University School of Medicine, Isehara, Japan
| | - Jerzy K Kulski
- Department of Molecular Life Science, Division of Basic Medical Science and Molecular Medicine, Tokai University School of Medicine, Isehara, Japan.,Faculty of Health and Medical Sciences, The University of Western Australia, Crawley, Western Australia, Australia
| | - Takashi Shiina
- Department of Molecular Life Science, Division of Basic Medical Science and Molecular Medicine, Tokai University School of Medicine, Isehara, Japan
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29
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Houtman M, Hesselberg E, Rönnblom L, Klareskog L, Malmström V, Padyukov L. Haplotype-Specific Expression Analysis of MHC Class II Genes in Healthy Individuals and Rheumatoid Arthritis Patients. Front Immunol 2021; 12:707217. [PMID: 34484204 PMCID: PMC8416041 DOI: 10.3389/fimmu.2021.707217] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2021] [Accepted: 08/02/2021] [Indexed: 01/03/2023] Open
Abstract
HLA-DRB1 alleles have been associated with several autoimmune diseases. For anti-citrullinated protein antibody positive rheumatoid arthritis (RA), HLA-DRB1 shared epitope (SE) alleles are the major genetic risk factors. In order to study the genetic regulation of major histocompatibility complex (MHC) Class II gene expression in immune cells, we investigated transcriptomic profiles of a variety of immune cells from healthy individuals carrying different HLA-DRB1 alleles. Sequencing libraries from peripheral blood mononuclear cells, CD4+ T cells, CD8+ T cells, and CD14+ monocytes of 32 genetically pre-selected healthy female individuals were generated, sequenced and reads were aligned to the standard reference. For the MHC region, reads were mapped to available MHC reference haplotypes and AltHapAlignR was used to estimate gene expression. Using this method, HLA-DRB and HLA-DQ were found to be differentially expressed in different immune cells of healthy individuals as well as in whole blood samples of RA patients carrying HLA-DRB1 SE-positive versus SE-negative alleles. In contrast, no genes outside the MHC region were differentially expressed between individuals carrying HLA-DRB1 SE-positive and SE-negative alleles, thus HLA-DRB1 SE alleles have a strong cis effect on gene expression. Altogether, our findings suggest that immune effects associated with different allelic forms of HLA-DR and HLA-DQ may be associated not only with differences in the structure of these proteins, but also with differences in their expression levels.
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Affiliation(s)
- Miranda Houtman
- Division of Rheumatology, Department of Medicine, Karolinska Institutet, Karolinska University Hospital, Stockholm, Sweden
| | - Espen Hesselberg
- Division of Rheumatology, Department of Medicine, Karolinska Institutet, Karolinska University Hospital, Stockholm, Sweden
| | - Lars Rönnblom
- Department of Medical Sciences, Rheumatology, Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Lars Klareskog
- Division of Rheumatology, Department of Medicine, Karolinska Institutet, Karolinska University Hospital, Stockholm, Sweden
| | - Vivianne Malmström
- Division of Rheumatology, Department of Medicine, Karolinska Institutet, Karolinska University Hospital, Stockholm, Sweden
| | - Leonid Padyukov
- Division of Rheumatology, Department of Medicine, Karolinska Institutet, Karolinska University Hospital, Stockholm, Sweden
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30
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Rossi AP, Alloway RR, Hildeman D, Woodle ES. Plasma cell biology: Foundations for targeted therapeutic development in transplantation. Immunol Rev 2021; 303:168-186. [PMID: 34254320 DOI: 10.1111/imr.13011] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2021] [Accepted: 06/22/2021] [Indexed: 12/20/2022]
Abstract
Solid organ transplantation is a life-saving procedure for patients with end-stage organ disease. Over the past 70 years, tremendous progress has been made in solid organ transplantation, particularly in T-cell-targeted immunosuppression and organ allocation systems. However, humoral alloimmune responses remain a major challenge to progress. Patients with preexisting antibodies to human leukocyte antigen (HLA) are at significant disadvantages in regard to receiving a well-matched organ, moreover, those who develop anti-HLA antibodies after transplantation face a significant foreshortening of renal allograft survival. Historical therapies to desensitize patients prior to transplantation or to treat posttransplant AMR have had limited effectiveness, likely because they do not significantly reduce antibody levels, as plasma cells, the source of antibody production, remain largely unaffected. Herein, we will discuss the significance of plasma cells in transplantation, aspects of their biology as potential therapeutic targets, clinical challenges in developing strategies to target plasma cells in transplantation, and lastly, novel approaches that have potential to advance the field.
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Affiliation(s)
- Amy P Rossi
- Division of Immunobiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA.,Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, USA.,Immunology Graduate Program, University of Cincinnati College of Medicine, Cincinnati, OH, USA.,Medical Scientist Training Program, University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - Rita R Alloway
- Division of Nephrology, Department of Internal Medicine, University of Cincinnati, Cincinnati, OH, USA
| | - David Hildeman
- Division of Immunobiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA.,Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, USA.,Immunology Graduate Program, University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - E Steve Woodle
- Division of Transplantation, Department of Surgery, University of Cincinnati College of Medicine, Cincinnati, OH, USA
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31
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Mapping the SARS-CoV-2 spike glycoprotein-derived peptidome presented by HLA class II on dendritic cells. Cell Rep 2021; 35:109179. [PMID: 34004174 PMCID: PMC8116342 DOI: 10.1016/j.celrep.2021.109179] [Citation(s) in RCA: 46] [Impact Index Per Article: 15.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2020] [Revised: 02/16/2021] [Accepted: 05/04/2021] [Indexed: 12/15/2022] Open
Abstract
Understanding and eliciting protective immune responses to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is an urgent priority. To facilitate these objectives, we profile the repertoire of human leukocyte antigen class II (HLA-II)-bound peptides presented by HLA-DR diverse monocyte-derived dendritic cells pulsed with SARS-CoV-2 spike (S) protein. We identify 209 unique HLA-II-bound peptide sequences, many forming nested sets, which map to sites throughout S including glycosylated regions. Comparison of the glycosylation profile of the S protein to that of the HLA-II-bound S peptides reveals substantial trimming of glycan residues on the latter, likely induced during antigen processing. Our data also highlight the receptor-binding motif in S1 as a HLA-DR-binding peptide-rich region and identify S2-derived peptides with potential for targeting by cross-protective vaccine-elicited responses. Results from this study will aid analysis of CD4+ T cell responses in infected individuals and vaccine recipients and have application in next-generation vaccine design.
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32
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Digitale JC, Callaway PC, Martin M, Nelson G, Viard M, Rek J, Arinaitwe E, Dorsey G, Kamya M, Carrington M, Rodriguez-Barraquer I, Feeney ME. HLA Alleles B *53:01 and C *06:02 Are Associated With Higher Risk of P. falciparum Parasitemia in a Cohort in Uganda. Front Immunol 2021; 12:650028. [PMID: 33815410 PMCID: PMC8017319 DOI: 10.3389/fimmu.2021.650028] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2021] [Accepted: 02/22/2021] [Indexed: 12/11/2022] Open
Abstract
Variation within the HLA locus been shown to play an important role in the susceptibility to and outcomes of numerous infections, but its influence on immunity to P. falciparum malaria is unclear. Increasing evidence indicates that acquired immunity to P. falciparum is mediated in part by the cellular immune response, including NK cells, CD4 and CD8 T cells, and semi-invariant γδ T cells. HLA molecules expressed by these lymphocytes influence the epitopes recognized by P. falciparum-specific T cells, and class I HLA molecules also serve as ligands for inhibitory receptors including KIR. Here we assessed the relationship of HLA class I and II alleles to the risk of P. falciparum infection and symptomatic malaria in a cohort of 892 Ugandan children and adults followed prospectively via both active and passive surveillance. We identified two HLA class I alleles, HLA-B*53:01 and HLA-C*06:02, that were associated with a higher prevalence of P. falciparum infection. Notably, no class I or II HLA alleles were found to be associated with protection from P. falciparum parasitemia or symptomatic malaria. These findings suggest that class I HLA plays a role in the ability to restrict parasitemia, supporting an essential role for the cellular immune response in P. falciparum immunity. Our findings underscore the need for better tools to enable mechanistic studies of the T cell response to P. falciparum at the epitope level and suggest that further study of the role of HLA in regulating pre-erythrocytic stages of the P. falciparum life cycle is warranted.
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Affiliation(s)
- Jean C. Digitale
- Department of Medicine, University of California, San Francisco, San Francisco, CA, United States
- Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA, United States
| | - Perri C. Callaway
- Department of Medicine, University of California, San Francisco, San Francisco, CA, United States
- Infectious Disease and Immunity Graduate Group, University of California, Berkeley, Berkeley, CA, United States
| | - Maureen Martin
- Basic Science Program, Frederick National Laboratory for Cancer Research in the Laboratory of Integrative Cancer Immunology, National Cancer Institute, Bethesda, MD, United States
| | - George Nelson
- Advanced Biomedical Computational Science, Frederick National Laboratory for Cancer Research, Frederick, MD, United States
| | - Mathias Viard
- Basic Science Program, Frederick National Laboratory for Cancer Research in the Laboratory of Integrative Cancer Immunology, National Cancer Institute, Bethesda, MD, United States
| | - John Rek
- Infectious Diseases Research Collaboration, Kampala, Uganda
| | - Emmanuel Arinaitwe
- Infectious Diseases Research Collaboration, Kampala, Uganda
- London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Grant Dorsey
- Department of Medicine, University of California, San Francisco, San Francisco, CA, United States
| | - Moses Kamya
- Infectious Diseases Research Collaboration, Kampala, Uganda
- Department of Medicine, Makerere University, Kampala, Uganda
| | - Mary Carrington
- Basic Science Program, Frederick National Laboratory for Cancer Research in the Laboratory of Integrative Cancer Immunology, National Cancer Institute, Bethesda, MD, United States
- Ragon Institute of MGH MIT and Harvard, Cambridge, MA, United States
| | | | - Margaret E. Feeney
- Department of Medicine, University of California, San Francisco, San Francisco, CA, United States
- Department of Pediatrics, University of California, San Francisco, San Francisco, CA, United States
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33
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Hu T, Chitnis N, Monos D, Dinh A. Next-generation sequencing technologies: An overview. Hum Immunol 2021; 82:801-811. [PMID: 33745759 DOI: 10.1016/j.humimm.2021.02.012] [Citation(s) in RCA: 248] [Impact Index Per Article: 82.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2020] [Revised: 02/18/2021] [Accepted: 02/23/2021] [Indexed: 12/14/2022]
Abstract
Since the days of Sanger sequencing, next-generation sequencing technologies have significantly evolved to provide increased data output, efficiencies, and applications. These next generations of technologies can be categorized based on read length. This review provides an overview of these technologies as two paradigms: short-read, or "second-generation," technologies, and long-read, or "third-generation," technologies. Herein, short-read sequencing approaches are represented by the most prevalent technologies, Illumina and Ion Torrent, and long-read sequencing approaches are represented by Pacific Biosciences and Oxford Nanopore technologies. All technologies are reviewed along with reported advantages and disadvantages. Until recently, short-read sequencing was thought to provide high accuracy limited by read-length, while long-read technologies afforded much longer read-lengths at the expense of accuracy. Emerging developments for third-generation technologies hold promise for the next wave of sequencing evolution, with the co-existence of longer read lengths and high accuracy.
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Affiliation(s)
- Taishan Hu
- Department of Pathology and Laboratory Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, United States
| | - Nilesh Chitnis
- Department of Pathology and Laboratory Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, United States; Department of Surgery, Baylor College of Medicine, Houston, TX, United States
| | - Dimitri Monos
- Department of Pathology and Laboratory Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, United States; Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States.
| | - Anh Dinh
- Department of Pathology and Laboratory Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, United States; Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States.
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34
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Johansson T, Yohannes DA, Koskela S, Partanen J, Saavalainen P. HLA RNA Sequencing With Unique Molecular Identifiers Reveals High Allele-Specific Variability in mRNA Expression. Front Immunol 2021; 12:629059. [PMID: 33717155 PMCID: PMC7949471 DOI: 10.3389/fimmu.2021.629059] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2020] [Accepted: 01/18/2021] [Indexed: 11/13/2022] Open
Abstract
The HLA gene complex is the most important single genetic factor in susceptibility to most diseases with autoimmune or autoinflammatory origin and in transplantation matching. Most studies have focused on the vast allelic variation in these genes; only a few studies have explored differences in the expression levels of HLA alleles. In this study, we quantified mRNA expression levels of HLA class I and II genes from peripheral blood samples of 50 healthy individuals. The gene- and allele-specific mRNA expression was assessed using unique molecular identifiers, which enabled PCR bias removal and calculation of the number of original mRNA transcripts. We identified differences in mRNA expression between different HLA genes and alleles. Our results suggest that HLA alleles are differentially expressed and these differences in expression levels are quantifiable using RNA sequencing technology. Our method provides novel insights into HLA research, and it can be applied to quantify expression differences of HLA alleles in various tissues and to evaluate the role of this type of variation in transplantation matching and susceptibility to autoimmune diseases.
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Affiliation(s)
- Tiira Johansson
- Research Programs Unit, Translational Immunology Program, University of Helsinki, Helsinki, Finland
- Research and Development, Finnish Red Cross Blood Service, Helsinki, Finland
| | - Dawit A. Yohannes
- Research Programs Unit, Translational Immunology Program, University of Helsinki, Helsinki, Finland
| | - Satu Koskela
- Research and Development, Finnish Red Cross Blood Service, Helsinki, Finland
| | - Jukka Partanen
- Research and Development, Finnish Red Cross Blood Service, Helsinki, Finland
| | - Päivi Saavalainen
- Research Programs Unit, Translational Immunology Program, University of Helsinki, Helsinki, Finland
- Research and Development, Finnish Red Cross Blood Service, Helsinki, Finland
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Zarinsefat A, Hartoularos G, Rychkov D, Rashmi P, Chandran S, Vincenti F, Yee CJ, Sarwal MM. Single-Cell RNA Sequencing of Tocilizumab-Treated Peripheral Blood Mononuclear Cells as an in vitro Model of Inflammation. Front Genet 2021; 11:610682. [PMID: 33469465 PMCID: PMC7813999 DOI: 10.3389/fgene.2020.610682] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2020] [Accepted: 12/02/2020] [Indexed: 12/27/2022] Open
Abstract
COVID-19 has posed a significant threat to global health. Early data has revealed that IL-6, a key regulatory cytokine, plays an important role in the cytokine storm of COVID-19. Multiple trials are therefore looking at the effects of Tocilizumab, an IL-6 receptor antibody that inhibits IL-6 activity, on treatment of COVID-19, with promising findings. As part of a clinical trial looking at the effects of Tocilizumab treatment on kidney transplant recipients with subclinical rejection, we performed single-cell RNA sequencing of comparing stimulated PBMCs before and after Tocilizumab treatment. We leveraged this data to create an in vitro cytokine storm model, to better understand the effects of Tocilizumab in the presence of inflammation. Tocilizumab-treated cells had reduced expression of inflammatory-mediated genes and biologic pathways, particularly amongst monocytes. These results support the hypothesis that Tocilizumab may hinder the cytokine storm of COVID-19, through a demonstration of biologic impact at the single-cell level.
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Affiliation(s)
- Arya Zarinsefat
- Department of Surgery, University of California, San Francisco, San Francisco, CA, United States
| | - George Hartoularos
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA, United States
| | - Dmitry Rychkov
- Department of Surgery, University of California, San Francisco, San Francisco, CA, United States
| | - Priyanka Rashmi
- Department of Surgery, University of California, San Francisco, San Francisco, CA, United States
| | - Sindhu Chandran
- Department of Medicine, University of California, San Francisco, San Francisco, CA, United States
| | - Flavio Vincenti
- Department of Surgery, University of California, San Francisco, San Francisco, CA, United States
| | - Chun J. Yee
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA, United States
| | - Minnie M. Sarwal
- Department of Surgery, University of California, San Francisco, San Francisco, CA, United States
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Class II HLA mismatch improves outcomes following haploidentical transplantation with posttransplant cyclophosphamide. Blood Adv 2020; 4:5311-5321. [PMID: 33108457 DOI: 10.1182/bloodadvances.2020003110] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2020] [Accepted: 09/21/2020] [Indexed: 11/20/2022] Open
Abstract
HLA disparity is the major predictor of outcome following unrelated donor (UD) transplantation, where a single mismatch (mm) at the HLA-A, HLA-B, HLA-C, or HLA-DRB1 locus leads to increased mortality, and mismatching at multiple loci compounds this effect. In contrast, HLA disparity has not been shown to increase mortality in the context of haploidentical transplant using posttransplant cyclophosphamide (PTCy). To better define the consequences of loci-specific HLA mm, we analyzed 208 consecutive patients undergoing haploidentical transplantation for hematologic malignancy using PTCy at our institution (median age, 52 years [range, 19-75 years]; peripheral blood stem cell, 66%; reduced-intensity conditioning, 59%). Median follow-up was 65.4 months (range, 34.3-157.2 months). In univariate analysis, a single class II HLA mm at HLA-DR, HLA-DQ or a nonpermissive (np) HLA-DP mm had a protective effect on disease-free and overall survival (OS), primarily a result of reduced relapse risk. Furthermore, this survival effect was cumulative, so that patients with 3 class II mm (HLA-DR, HLA-DQ, and np HLA-DP) had the best OS. In multivariate analysis, HLA-DR mm and np HLA-DP mm were both independently associated with improved OS (hazard ratio [HR], 0.43; P =.001; and HR, 0.47; P =.011, respectively). In contrast, single or multiple mm at HLA-A, HLA-B, or HLA-C loci had no effect on acute graft-versus-host disease (GVHD), nonrelapse mortality (NRM), relapse, or survival, although the presence of an HLA-A mm was associated with increased chronic GVHD incidence. The association of class II mm with lower relapse occurred without a corresponding increase in NRM or acute or chronic GVHD. These findings will require validation in larger registry studies.
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Zarinsefat A, Hartoularos G, Chandran S, Yee CJ, Vincenti F, Sarwal MM. Single-cell RNA sequencing of Tocilizumab-treated peripheral blood mononuclear cells as an in vitro model of inflammation. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2020:2020.09.11.281782. [PMID: 32935096 PMCID: PMC7491509 DOI: 10.1101/2020.09.11.281782] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/11/2023]
Abstract
COVID-19 has posed a significant threat to global health. Early data has revealed that IL-6, a key regulatory cytokine, plays an important role in the cytokine storm of COVID-19. Multiple trials are therefore looking at the effects of Tocilizumab, an IL-6 receptor antibody that inhibits IL-6 activity, on treatment of COVID-19, with promising findings. As part of a clinical trial looking at the effects of Tocilizumab treatment on kidney transplant recipients with subclinical rejection, we performed single-cell RNA sequencing of comparing stimulated PBMCs before and after Tocilizumab treatment. We leveraged this data to create an in vitro cytokine storm model, to better understand the effects of Tocilizumab in the presence of inflammation. Tocilizumab-treated cells had reduced expression of inflammatory-mediated genes and biologic pathways, particularly amongst monocytes. These results support the hypothesis that Tocilizumab may hinder the cytokine storm of COVID-19, through a demonstration of biologic impact at the single-cell level.
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Parker R, Partridge T, Wormald C, Kawahara R, Stalls V, Aggelakopoulou M, Parker J, Doherty RP, Morejon YA, Lee E, Saunders K, Haynes BF, Acharya P, Thaysen-Andersen M, Borrow P, Ternette N. Mapping the SARS-CoV-2 spike glycoprotein-derived peptidome presented by HLA class II on dendritic cells. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2020. [PMID: 32839772 PMCID: PMC7444283 DOI: 10.1101/2020.08.19.255901] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/22/2023]
Abstract
Understanding and eliciting protective immune responses to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is an urgent priority. To facilitate these objectives, we have profiled the repertoire of human leukocyte antigen class II (HLA-II)-bound peptides presented by HLA-DR diverse monocyte-derived dendritic cells pulsed with SARS-CoV-2 spike (S) protein. We identify 209 unique HLA-II-bound peptide sequences, many forming nested sets, which map to sites throughout S including glycosylated regions. Comparison of the glycosylation profile of the S protein to that of the HLA-II-bound S peptides revealed substantial trimming of glycan residues on the latter, likely introduced during antigen processing. Our data also highlight the receptor-binding motif in S1 as a HLA-DR-binding peptide-rich region. Results from this study have application in vaccine design, and will aid analysis of CD4+ T cell responses in infected individuals and vaccine recipients.
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Okano M, Miyamae J, Suzuki S, Nishiya K, Katakura F, Kulski JK, Moritomo T, Shiina T. Identification of Novel Alleles and Structural Haplotypes of Major Histocompatibility Complex Class I and DRB Genes in Domestic Cat ( Felis catus) by a Newly Developed NGS-Based Genotyping Method. Front Genet 2020; 11:750. [PMID: 32760428 PMCID: PMC7375346 DOI: 10.3389/fgene.2020.00750] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2020] [Accepted: 06/23/2020] [Indexed: 12/24/2022] Open
Abstract
The major histocompatibility complex (MHC) is a highly polymorphic and duplicated genomic region that encodes transplantation and immune regulatory molecules. Although it is well-known that particular MHC allelic polymorphisms and haplotypes are genetically relate to immune-mediated diseases detailed information of the cat MHC (Feline Leukocyte Antigen; FLA) genetic and haplotypic structure and diversity is limited in comparison to humans and many other species. In this study, to better understand the degree and types of allele and allelic haplotype diversity of FLA-class I (FLA-I) and FLA-DRB loci in domestic cats, we identified six expressible FLA-I loci in peripheral white blood cells by in silico estimation of the coding exons and NGS-based amplicon sequencing using five unrelated cats. We then used a newly developed NGS-based genotyping method to genotype and annotate 32 FLA-I and 16 FLA-DRB sequences in two families of 20 domestic cats. A total of 14 FLA-I and seven FLA-DRB were identified as novel polymorphic sequences. Phylogenetic analyses grouped the sequences into six FLA-I (FLA-E/H/K, FLA-A, FLA-J, FLA-L, FLA-O and a tentatively named FLA-E/H/K_Rec) and four FLA-DRB (FLA-DRB1, FLA-DRB3, FLA-DRB4, and FLA-DRB5) lineages. Pedigree analysis of two cat families revealed eight distinct FLA structural haplotypes (Class I - DRB) with five to eight FLA-I and two to three FLA-DRB transcribed loci per haplotype. It is evident that the eight FLA haplotypes were generated by gene duplications and deletions, and rearrangements by genetic recombination with the accumulation and/or inheritance of novel polymorphisms. These findings are useful for further genetic diversity analysis and disease association studies among cat breeds and in veterinary medicine.
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Affiliation(s)
- Masaharu Okano
- Department of Veterinary Medicine, College of Bioresource Sciences, Nihon University, Fujisawa, Japan
| | - Jiro Miyamae
- Faculty of Veterinary Medicine, Okayama University of Science, Imabari, Japan
| | - Shingo Suzuki
- Division of Basic Medical Science and Molecular Medicine, Department of Molecular Life Science, Tokai University, Isehara, Japan
| | - Kohei Nishiya
- Department of Veterinary Medicine, College of Bioresource Sciences, Nihon University, Fujisawa, Japan
| | - Fumihiko Katakura
- Department of Veterinary Medicine, College of Bioresource Sciences, Nihon University, Fujisawa, Japan
| | - Jerzy K Kulski
- Division of Basic Medical Science and Molecular Medicine, Department of Molecular Life Science, Tokai University, Isehara, Japan.,Faculty of Health and Medical Sciences, UWA Medical School, The University of Western Australia, Perth, WA, Australia
| | - Tadaaki Moritomo
- Department of Veterinary Medicine, College of Bioresource Sciences, Nihon University, Fujisawa, Japan
| | - Takashi Shiina
- Division of Basic Medical Science and Molecular Medicine, Department of Molecular Life Science, Tokai University, Isehara, Japan
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