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Marchal A, Cirulli ET, Neveux I, Bellos E, Thwaites RS, Schiabor Barrett KM, Zhang Y, Nemes-Bokun I, Kalinova M, Catchpole A, Tangye SG, Spaan AN, Lack JB, Ghosn J, Burdet C, Gorochov G, Tubach F, Hausfater P, Dalgard CL, Zhang SY, Zhang Q, Chiu C, Fellay J, Grzymski JJ, Sancho-Shimizu V, Abel L, Casanova JL, Cobat A, Bolze A. Lack of association between classical HLA genes and asymptomatic SARS-CoV-2 infection. HGG ADVANCES 2024; 5:100300. [PMID: 38678364 PMCID: PMC11215417 DOI: 10.1016/j.xhgg.2024.100300] [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: 12/04/2023] [Revised: 04/22/2024] [Accepted: 04/23/2024] [Indexed: 04/29/2024] Open
Abstract
Human genetic studies of critical COVID-19 pneumonia have revealed the essential role of type I interferon-dependent innate immunity to SARS-CoV-2 infection. Conversely, an association between the HLA-B∗15:01 allele and asymptomatic SARS-CoV-2 infection in unvaccinated individuals was recently reported, suggesting a contribution of pre-existing T cell-dependent adaptive immunity. We report a lack of association of classical HLA alleles, including HLA-B∗15:01, with pre-omicron asymptomatic SARS-CoV-2 infection in unvaccinated participants in a prospective population-based study in the United States (191 asymptomatic vs. 945 symptomatic COVID-19 cases). Moreover, we found no such association in the international COVID Human Genetic Effort cohort (206 asymptomatic vs. 574 mild or moderate COVID-19 cases and 1,625 severe or critical COVID-19 cases). Finally, in the Human Challenge Characterisation study, the three HLA-B∗15:01 individuals infected with SARS-CoV-2 developed symptoms. As with other acute primary infections studied, no classical HLA alleles favoring an asymptomatic course of SARS-CoV-2 infection were identified.
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Affiliation(s)
- Astrid Marchal
- Laboratory of Human Genetics of Infectious Diseases, Necker Branch, INSERM U1163, Paris, France; University Paris Cité, Imagine Institute, Paris, France
| | | | - Iva Neveux
- Department of Internal Medicine, University of Nevada School of Medicine, Reno, NV, USA
| | - Evangelos Bellos
- Department of Infectious Disease, Imperial College London, London, UK
| | - Ryan S Thwaites
- National Heart and Lung Institute, Imperial College London, London, UK
| | | | - Yu Zhang
- Laboratory of Clinical Immunology and Microbiology, Division of Intramural Research, NIAID, Bethesda, MD, USA
| | - Ivana Nemes-Bokun
- Department of Infectious Disease, Imperial College London, London, UK
| | | | | | - Stuart G Tangye
- Garvan Institute of Medical Research, Darlinghurst, NSW, Australia; School of Clinical Medicine, Faculty of Medicine and Health, UNSW Sydney, New South Wales, Australia
| | - András N Spaan
- St. Giles Laboratory of Human Genetics of Infectious Diseases, Rockefeller Branch, The Rockefeller University, New York, NY, USA; Department of Medical Microbiology, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
| | - Justin B Lack
- NIAID Collaborative Bioinformatics Resource, Frederick National Laboratory for Cancer Research, Leidos Biomedical Research Inc, Frederick, MD, USA
| | - Jade Ghosn
- Infection, Antimicrobials, Modelling, Evolution (IAME), INSERM, UMR1137, University Paris Cité, Paris, France; AP-HP, Bichat-Claude Bernard Hospital, Infectious and Tropical Diseases Department, Paris, France
| | - Charles Burdet
- Infection, Antimicrobials, Modelling, Evolution (IAME), INSERM, UMR1137, University Paris Cité, Paris, France; AP-HP, Hôpital Bichat, Centre d'Investigation Clinique, INSERM CIC 1425, Paris, France; Département Epidémiologie, Biostatistiques et Recherche Clinique, Hôpital Bichat, Assistance Publique-Hôpitaux de Paris, 75018 Paris, France
| | - Guy Gorochov
- Sorbonne Université, INSERM Centre d'Immunologie et des Maladies Infectieuses, CIMI-Paris, Département d'immunologie Hôpital Pitié-Salpêtrière, Assistance Publique-Hôpitaux de Paris, Paris, France
| | - Florence Tubach
- Sorbonne Université, INSERM, Institut Pierre Louis d'Epidémiologie et de Santé Publique, AP-HP, Hôpital Pitié-Salpêtrière, Département de Santé Publique, Unitéde Recherche Clinique PSL-CFX, CIC-1901, Paris, France
| | - Pierre Hausfater
- Emergency Department, Hôpital Pitié-Salpêtrière, APHP-Sorbonne Université, Paris, France; GRC-14 BIOSFAST Sorbonne Université, UMR INSERM 1135, CIMI, Sorbonne Université, Paris, France
| | - Clifton L Dalgard
- Department of Anatomy, Physiology & Genetics, Uniformed Services University of the Health Sciences, Bethesda, MD, USA
| | - Shen-Ying Zhang
- Laboratory of Human Genetics of Infectious Diseases, Necker Branch, INSERM U1163, Paris, France; University Paris Cité, Imagine Institute, Paris, France; St. Giles Laboratory of Human Genetics of Infectious Diseases, Rockefeller Branch, The Rockefeller University, New York, NY, USA
| | - Qian Zhang
- Laboratory of Human Genetics of Infectious Diseases, Necker Branch, INSERM U1163, Paris, France; University Paris Cité, Imagine Institute, Paris, France; St. Giles Laboratory of Human Genetics of Infectious Diseases, Rockefeller Branch, The Rockefeller University, New York, NY, USA
| | - Christopher Chiu
- Department of Infectious Disease, Imperial College London, London, UK
| | - Jacques Fellay
- School of Life Sciences, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland; Swiss Institute of Bioinformatics, Lausanne, Switzerland; Precision Medicine Unit, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Joseph J Grzymski
- Department of Internal Medicine, University of Nevada School of Medicine, Reno, NV, USA; Renown Health, Reno, NV, USA
| | - Vanessa Sancho-Shimizu
- Department of Infectious Disease, Imperial College London, London, UK; Centre for Paediatrics and Child Health, Faculty of Medicine, Imperial College London, London, UK
| | - Laurent Abel
- Laboratory of Human Genetics of Infectious Diseases, Necker Branch, INSERM U1163, Paris, France; University Paris Cité, Imagine Institute, Paris, France; St. Giles Laboratory of Human Genetics of Infectious Diseases, Rockefeller Branch, The Rockefeller University, New York, NY, USA
| | - Jean-Laurent Casanova
- Laboratory of Human Genetics of Infectious Diseases, Necker Branch, INSERM U1163, Paris, France; University Paris Cité, Imagine Institute, Paris, France; St. Giles Laboratory of Human Genetics of Infectious Diseases, Rockefeller Branch, The Rockefeller University, New York, NY, USA; Department of Pediatrics, Necker Hospital for Sick Children, Paris, France; Howard Hughes Medical Institute, New York, NY, USA
| | - Aurélie Cobat
- Laboratory of Human Genetics of Infectious Diseases, Necker Branch, INSERM U1163, Paris, France; University Paris Cité, Imagine Institute, Paris, France; St. Giles Laboratory of Human Genetics of Infectious Diseases, Rockefeller Branch, The Rockefeller University, New York, NY, USA.
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Logunova N, Kapina M, Dyatlov A, Kondratieva T, Rubakova E, Majorov K, Kondratieva E, Linge I, Apt A. Polygenic TB control and the sequence of innate/adaptive immune responses to infection: MHC-II alleles determine the size of the S100A8/9-producing neutrophil population. Immunology 2024. [PMID: 39003642 DOI: 10.1111/imm.13836] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2024] [Accepted: 07/01/2024] [Indexed: 07/15/2024] Open
Abstract
Among several quantitative trait loci involved in tuberculosis (TB) control in mice, one was mapped within the chromosome 17 segment occupied by the H2 complex and another within the chromosome 3 segment comprising the S100A8/9 genes, which encode neutrophil inflammatory factor S100A8/9. Previously, we developed a panel of H2-congenic mouse strains differing by small segments of the major histocompatibility complex Class II (MHC-II) region from TB-susceptible H2j mice transferred onto the genetic background of the TB-resistant C57BL/6 (H2b) strain. Susceptible B6.I-9.3 mice differ from B6 progenitors by the alleles of their only classical MHC-II H2-Aβ gene. The goals of the present study were to: (i) comprehensively characterise the differences in TB-related phenotypes between mice of the two strains and (ii) decipher interactions between the H2-Aβ and S100A8/9 genes. Here, we describe the dynamics of TB-related phenotypes differentiating B6.I-9.3 and B6 mice (colony forming units counts, histopathology, lung immune cell infiltration and cytokine profiles). We show that disproportionally diminished CD4+ T-cell population, an enlarged S100A8/9-positive neutrophil population and higher S100A8/9 serum levels in B6.I-9.3 mice collectively form the 'susceptible' phenotype before infection. An increase in IL-17 and a decrease in intrferon-gamma production by CD4+ T-cells in these mice provide a mechanistic explanation of this phenotype. Using F2 segregation analysis, we show that the number of S100A8/9-producing neutrophils in lungs and spleens and the proportion of Th17 CD4+ T-cells in lungs are significantly lower in the presence of the MHC-II dominant 'resistant' b allele compared to the recessive 'susceptible' j/j genotype. This provides direct genetic evidence that MHC-II-regulated CD4+ T-cell landscapes determine neutrophil abundance before infection, an important pathogenic factor in TB immunity.
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Affiliation(s)
- Nadezhda Logunova
- Laboratory for Immunogenetics, Central Tuberculosis Research Institute, Moscow, Russia
| | - Marina Kapina
- Laboratory for Immunogenetics, Central Tuberculosis Research Institute, Moscow, Russia
| | - Alexander Dyatlov
- Laboratory for Immunogenetics, Central Tuberculosis Research Institute, Moscow, Russia
| | - Tatiana Kondratieva
- Laboratory for Immunogenetics, Central Tuberculosis Research Institute, Moscow, Russia
| | - Elvira Rubakova
- Laboratory for Immunogenetics, Central Tuberculosis Research Institute, Moscow, Russia
| | - Konstantin Majorov
- Laboratory for Immunogenetics, Central Tuberculosis Research Institute, Moscow, Russia
| | - Elena Kondratieva
- Laboratory for Immunogenetics, Central Tuberculosis Research Institute, Moscow, Russia
| | - Irina Linge
- Laboratory for Immunogenetics, Central Tuberculosis Research Institute, Moscow, Russia
| | - Alexander Apt
- Laboratory for Immunogenetics, Central Tuberculosis Research Institute, Moscow, Russia
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Santiago-Lamelas L, Castro-Santos P, Carracedo Á, Olloquequi J, Díaz-Peña R. Unveiling the Significance of HLA and KIR Diversity in Underrepresented Populations. Biomedicines 2024; 12:1333. [PMID: 38927540 PMCID: PMC11202227 DOI: 10.3390/biomedicines12061333] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2024] [Revised: 06/11/2024] [Accepted: 06/12/2024] [Indexed: 06/28/2024] Open
Abstract
Human leukocyte antigen (HLA) molecules and their relationships with natural killer (NK) cells, specifically through their interaction with killer-cell immunoglobulin-like receptors (KIRs), exhibit robust associations with the outcomes of diverse diseases. Moreover, genetic variations in HLA and KIR immune system genes offer limitless depths of complexity. In recent years, a surge of high-powered genome-wide association studies (GWASs) utilizing single nucleotide polymorphism (SNP) arrays has occurred, significantly advancing our understanding of disease pathogenesis. Additionally, advances in HLA reference panels have enabled higher resolution and more reliable imputation, allowing for finer-grained evaluation of the association between sequence variations and disease risk. However, it is essential to note that the majority of these GWASs have focused primarily on populations of Caucasian and Asian origins, neglecting underrepresented populations in Latin America and Africa. This omission not only leads to disparities in health care access but also restricts our knowledge of novel genetic variants involved in disease pathogenesis within these overlooked populations. Since the KIR and HLA haplotypes prevalent in each population are clearly modelled by the specific environment, the aim of this review is to encourage studies investigating HLA/KIR involvement in infection and autoimmune diseases, reproduction, and transplantation in underrepresented populations.
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Affiliation(s)
- Lucía Santiago-Lamelas
- Fundación Pública Galega de Medicina Xenómica, SERGAS, Grupo de Medicina Xenomica-USC, Instituto de Investigación Sanitaria de Santiago (IDIS), 15706 Santiago de Compostela, Spain; (L.S.-L.); (P.C.-S.); (Á.C.)
| | - Patricia Castro-Santos
- Fundación Pública Galega de Medicina Xenómica, SERGAS, Grupo de Medicina Xenomica-USC, Instituto de Investigación Sanitaria de Santiago (IDIS), 15706 Santiago de Compostela, Spain; (L.S.-L.); (P.C.-S.); (Á.C.)
- Facultad de Ciencias de la Salud, Universidad Autónoma de Chile, Talca 3460000, Chile
| | - Ángel Carracedo
- Fundación Pública Galega de Medicina Xenómica, SERGAS, Grupo de Medicina Xenomica-USC, Instituto de Investigación Sanitaria de Santiago (IDIS), 15706 Santiago de Compostela, Spain; (L.S.-L.); (P.C.-S.); (Á.C.)
- Grupo de Medicina Xenómica, CIMUS, Universidade de Santiago de Compostela, 15782 Santiago de Compostela, Spain
- Centre for Biomedical Network Research on Rare Diseases (CIBERER), Instituto de Salud Carlos III, 28029 Madrid, Spain
| | - Jordi Olloquequi
- Facultad de Ciencias de la Salud, Universidad Autónoma de Chile, Talca 3460000, Chile
- Departament de Bioquímica i Fisiologia, Facultat de Farmàcia i Ciències de l’Alimentació, Universitat de Barcelona, 08028 Barcelona, Spain
| | - Roberto Díaz-Peña
- Fundación Pública Galega de Medicina Xenómica, SERGAS, Grupo de Medicina Xenomica-USC, Instituto de Investigación Sanitaria de Santiago (IDIS), 15706 Santiago de Compostela, Spain; (L.S.-L.); (P.C.-S.); (Á.C.)
- Facultad de Ciencias de la Salud, Universidad Autónoma de Chile, Talca 3460000, Chile
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Li X, Ma Y, Li G, Jin G, Xu L, Li Y, Wei P, Zhang L. Leprosy: treatment, prevention, immune response and gene function. Front Immunol 2024; 15:1298749. [PMID: 38440733 PMCID: PMC10909994 DOI: 10.3389/fimmu.2024.1298749] [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: 09/22/2023] [Accepted: 02/05/2024] [Indexed: 03/06/2024] Open
Abstract
Since the leprosy cases have fallen dramatically, the incidence of leprosy has remained stable over the past years, indicating that multidrug therapy seems unable to eradicate leprosy. More seriously, the emergence of rifampicin-resistant strains also affects the effectiveness of treatment. Immunoprophylaxis was mainly carried out through vaccination with the BCG but also included vaccines such as LepVax and MiP. Meanwhile, it is well known that the infection and pathogenesis largely depend on the host's genetic background and immunity, with the onset of the disease being genetically regulated. The immune process heavily influences the clinical course of the disease. However, the impact of immune processes and genetic regulation of leprosy on pathogenesis and immunological levels is largely unknown. Therefore, we summarize the latest research progress in leprosy treatment, prevention, immunity and gene function. The comprehensive research in these areas will help elucidate the pathogenesis of leprosy and provide a basis for developing leprosy elimination strategies.
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Affiliation(s)
- Xiang Li
- Department of Epidemiology and Health Statistics, School of Public Health, Southeast University, Nanjing, China
| | - Yun Ma
- Chronic Infectious Disease Control Section, Nantong Center for Disease Control and Prevention, Nantong, China
| | - Guoli Li
- Department of Chronic Infectious Disease Control and Prevention, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, China
| | - Guangjie Jin
- Department of Chronic Infectious Disease Control and Prevention, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, China
| | - Li Xu
- Department of Epidemiology and Health Statistics, School of Public Health, Southeast University, Nanjing, China
| | - Yunhui Li
- Department of Epidemiology and Health Statistics, School of Public Health, Southeast University, Nanjing, China
| | - Pingmin Wei
- Department of Epidemiology and Health Statistics, School of Public Health, Southeast University, Nanjing, China
| | - Lianhua Zhang
- Department of Epidemiology and Health Statistics, School of Public Health, Southeast University, Nanjing, China
- Department of Chronic Infectious Disease Control and Prevention, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, China
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Marchal A, Cirulli ET, Neveux I, Bellos E, Thwaites RS, Schiabor Barrett KM, Zhang Y, Nemes-Bokun I, Kalinova M, Catchpole A, Tangye SG, Spaan AN, Lack JB, Ghosn J, Burdet C, Gorochov G, Tubach F, Hausfater P, Dalgard CL, Zhang SY, Zhang Q, Chiu C, Fellay J, Grzymski JJ, Sancho-Shimizu V, Abel L, Casanova JL, Cobat A, Bolze A. Lack of association between HLA and asymptomatic SARS-CoV-2 infection. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.12.06.23299623. [PMID: 38168184 PMCID: PMC10760282 DOI: 10.1101/2023.12.06.23299623] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/05/2024]
Abstract
Human genetic studies of critical COVID-19 pneumonia have revealed the essential role of type I interferon-dependent innate immunity to SARS-CoV-2 infection. Conversely, an association between the HLA-B*15:01 allele and asymptomatic SARS-CoV-2 infection in unvaccinated individuals was recently reported, suggesting a contribution of pre-existing T cell-dependent adaptive immunity. We report a lack of association of classical HLA alleles, including HLA-B*15:01, with pre-omicron asymptomatic SARS-CoV-2 infection in unvaccinated participants in a prospective population-based study in the US (191 asymptomatic vs. 945 symptomatic COVID-19 cases). Moreover, we found no such association in the international COVID Human Genetic Effort cohort (206 asymptomatic vs. 574 mild or moderate COVID-19 cases and 1,625 severe or critical COVID-19 cases). Finally, in the Human Challenge Characterisation study, the three HLA-B*15:01 individuals infected with SARS-CoV-2 developed symptoms. As with other acute primary infections, no classical HLA alleles favoring an asymptomatic course of SARS-CoV-2 infection were identified. These findings suggest that memory T-cell immunity to seasonal coronaviruses does not strongly influence the outcome of SARS-CoV-2 infection in unvaccinated individuals.
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Affiliation(s)
- Astrid Marchal
- Laboratory of Human Genetics of Infectious Diseases, Necker Branch, INSERM U1163, Paris, France, EU
- University Paris Cité, Imagine Institute, Paris, France, EU
| | | | - Iva Neveux
- Department of Internal Medicine, University of Nevada School of Medicine, Reno, NV, USA
| | - Evangelos Bellos
- Department of Infectious Diseases, Imperial College London, London, United Kingdom
| | - Ryan S. Thwaites
- National Heart and Lung Institute, Imperial College London, London, United Kingdom
| | | | - Yu Zhang
- Laboratory of Clinical Immunology and Microbiology, Division of Intramural Research, NIAID, Bethesda, MD, USA
| | - Ivana Nemes-Bokun
- Department of Infectious Diseases, Imperial College London, London, United Kingdom
| | | | | | - Stuart G. Tangye
- Garvan Institute of Medical Research, Darlinghurst, NSW, Australia
- St Vincent’s Clinical School, Faculty of Medicine, UNSW Sydney, NSW, Australia
| | - András N. Spaan
- St. Giles Laboratory of Human Genetics of Infectious Diseases, Rockefeller Branch, The Rockefeller University, New York, NY, USA
- Department of Medical Microbiology, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands, EU
| | - Justin B. Lack
- NIAID Collaborative Bioinformatics Resource, Frederick National Laboratory for Cancer Research, Leidos Biomedical Research Inc., Frederick, MD, USA
| | - Jade Ghosn
- Infection, Antimicrobials, Modelling, Evolution (IAME), INSERM, UMR1137, University of Paris, Paris, France, EU
- AP-HP, Bichat Claude Bernard Hospital, Infectious and Tropical Diseases Department, Paris, France, EU
| | - Charles Burdet
- Infection, Antimicrobials, Modelling, Evolution (IAME), INSERM, UMR1137, University of Paris, Paris, France, EU
- Epidémiologie clinique du Centre d’Investigation Clinique (CIC-EP), INSERM CIC 1425, Hôpital Bichat, 75018 Paris, France, EU
- Département Epidémiologie, Biostatistiques et Recherche Clinique, Hôpital Bichat, Assistance Publique-Hôpitaux de Paris, 75018 Paris, France, EU
| | - Guy Gorochov
- Sorbonne Université, INSERM Centre d’Immunologie et des Maladies Infectieuses, CIMI-Paris, Département d’immunologie Hôpital Pitié-Salpêtrière, Assistance Publique-Hôpitaux de Paris, Paris, France, EU
| | - Florence Tubach
- Sorbonne Université, INSERM, Institut Pierre Louis d’Epidémiologie et de Santé Publique, AP-HP, Hôpital Pitié Salpêtrière, Département de Santé Publique, Unité de Recherche Clinique PSL-CFX, CIC-1901, Paris, France, EU
| | - Pierre Hausfater
- Emergency Department, Hôpital Pitié-Salpêtrière, APHP-Sorbonne Université, Paris, France, EU
- GRC-14 BIOFAST Sorbonne Université, UMR INSERM 1135, CIMI, Sorbonne Université, Paris, France, EU
| | | | | | | | | | | | | | | | | | | | - Clifton L. Dalgard
- Department of Anatomy, Physiology & Genetics, Uniformed Services University of the Health Sciences, Bethesda, MD, USA
| | - Shen-Ying Zhang
- Laboratory of Human Genetics of Infectious Diseases, Necker Branch, INSERM U1163, Paris, France, EU
- University Paris Cité, Imagine Institute, Paris, France, EU
- St. Giles Laboratory of Human Genetics of Infectious Diseases, Rockefeller Branch, The Rockefeller University, New York, NY, USA
| | - Qian Zhang
- Laboratory of Human Genetics of Infectious Diseases, Necker Branch, INSERM U1163, Paris, France, EU
- University Paris Cité, Imagine Institute, Paris, France, EU
- St. Giles Laboratory of Human Genetics of Infectious Diseases, Rockefeller Branch, The Rockefeller University, New York, NY, USA
| | - Christopher Chiu
- Department of Infectious Diseases, Imperial College London, London, United Kingdom
| | - Jacques Fellay
- School of Life Sciences, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
- Precision Medicine Unit, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Joseph J. Grzymski
- Department of Internal Medicine, University of Nevada School of Medicine, Reno, NV, USA
- Renown Health, Reno, NV, USA
| | - Vanessa Sancho-Shimizu
- Department of Infectious Diseases, Imperial College London, London, United Kingdom
- Centre for Paediatrics and Child Health, Faculty of Medicine, Imperial College London, London, UK
| | - Laurent Abel
- Laboratory of Human Genetics of Infectious Diseases, Necker Branch, INSERM U1163, Paris, France, EU
- University Paris Cité, Imagine Institute, Paris, France, EU
- St. Giles Laboratory of Human Genetics of Infectious Diseases, Rockefeller Branch, The Rockefeller University, New York, NY, USA
| | - Jean-Laurent Casanova
- Laboratory of Human Genetics of Infectious Diseases, Necker Branch, INSERM U1163, Paris, France, EU
- University Paris Cité, Imagine Institute, Paris, France, EU
- St. Giles Laboratory of Human Genetics of Infectious Diseases, Rockefeller Branch, The Rockefeller University, New York, NY, USA
- Howard Hughes Medical Institute, New York, NY, USA
| | - Aurélie Cobat
- Laboratory of Human Genetics of Infectious Diseases, Necker Branch, INSERM U1163, Paris, France, EU
- University Paris Cité, Imagine Institute, Paris, France, EU
- St. Giles Laboratory of Human Genetics of Infectious Diseases, Rockefeller Branch, The Rockefeller University, New York, NY, USA
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Zhou XJ, Su T, Xie J, Xie QH, Wang LZ, Hu Y, Chen G, Jia Y, Huang JW, Li G, Liu Y, Yu XJ, Nath SK, Tsoi LC, Patrick MT, Berthier CC, Liu G, Wang SX, Xu H, Chen N, Hao CM, Zhang H, Yang L. Genome-Wide Association Study in Acute Tubulointerstitial Nephritis. J Am Soc Nephrol 2023; 34:895-908. [PMID: 36749126 PMCID: PMC10125656 DOI: 10.1681/asn.0000000000000091] [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: 07/21/2022] [Accepted: 12/28/2022] [Indexed: 02/08/2023] Open
Abstract
SIGNIFICANCE STATEMENT Polymorphisms of HLA genes may confer susceptibility to acute tubulointerstitial nephritis (ATIN), but small sample sizes and candidate gene design have hindered their investigation. The first genome-wide association study of ATIN identified two significant loci, risk haplotype DRB1*14-DQA1*0101-DQB1*0503 (DR14 serotype) and protective haplotype DRB1*1501-DQA1*0102-DQB1*0602 (DR15 serotype), with amino acid position 60 in the peptide-binding groove P10 of HLA-DR β 1 key. Risk alleles were shared among different causes of ATIN and HLA genotypes associated with kidney injury and immune therapy response. HLA alleles showed the strongest association. The findings suggest that a genetically conferred risk of immune dysregulation is part of the pathogenesis of ATIN. BACKGROUND Acute tubulointerstitial nephritis (ATIN) is a rare immune-related disease, accounting for approximately 10% of patients with unexplained AKI. Previous elucidation of the relationship between genetic factors that contribute to its pathogenesis was hampered because of small sample sizes and candidate gene design. METHODS We undertook the first two-stage genome-wide association study and meta-analysis involving 544 kidney biopsy-defined patients with ATIN and 2346 controls of Chinese ancestry. We conducted statistical fine-mapping analysis, provided functional annotations of significant variants, estimated single nucleotide polymorphism (SNP)-based heritability, and checked genotype and subphenotype correlations. RESULTS Two genome-wide significant loci, rs35087390 of HLA-DQA1 ( P =3.01×10 -39 ) on 6p21.32 and rs2417771 of PLEKHA5 on 12p12.3 ( P =2.14×10 -8 ), emerged from the analysis. HLA imputation using two reference panels suggested that HLA-DRB1*14 mainly drives the HLA risk association . HLA-DRB1 residue 60 belonging to pocket P10 was the key amino acid position. The SNP-based heritability estimates with and without the HLA locus were 20.43% and 10.35%, respectively. Different clinical subphenotypes (drug-related or tubulointerstitial nephritis and uveitis syndrome) seemed to share the same risk alleles. However, the HLA risk genotype was associated with disease severity and response rate to immunosuppressive therapy. CONCLUSIONS We identified two candidate genome regions associated with susceptibility to ATIN. The findings suggest that a genetically conferred risk of immune dysregulation is involved in the pathogenesis of ATIN.
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Affiliation(s)
- Xu-Jie Zhou
- Renal Division, Peking University First Hospital, Peking University Institute of Nephrology, Beijing, China
- Key Laboratory of Renal Disease, Ministry of Health of China, Beijing, China
- Key Laboratory of Chronic Kidney Disease Prevention and Treatment (Peking University), Ministry of Education, Beijing, China
| | - Tao Su
- Renal Division, Peking University First Hospital, Peking University Institute of Nephrology, Beijing, China
- Key Laboratory of Renal Disease, Ministry of Health of China, Beijing, China
- Key Laboratory of Chronic Kidney Disease Prevention and Treatment (Peking University), Ministry of Education, Beijing, China
| | - Jingyuan Xie
- Department of Nephrology, Institute of Nephrology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Qiong-Hong Xie
- Division of Nephrology, Huashan Hospital, Fudan University, Shanghai, China
| | - Li-Zhong Wang
- WeGene, Shenzhen Zaozhidao Technology Co., Ltd., Shenzhen, China
- Human Provincial Key Lab on Bioinformatics, School of Computer Science and Engineering, Central South University, Changsha, China
- Shenzhen WeGene Clinical Laboratory, Shenzhen, China
| | - Yong Hu
- Beijing Institute of Biotechnology, Beijing, China
| | - Gang Chen
- WeGene, Shenzhen Zaozhidao Technology Co., Ltd., Shenzhen, China
- Human Provincial Key Lab on Bioinformatics, School of Computer Science and Engineering, Central South University, Changsha, China
- Shenzhen WeGene Clinical Laboratory, Shenzhen, China
| | - Yan Jia
- Renal Division, Peking University First Hospital, Peking University Institute of Nephrology, Beijing, China
- Key Laboratory of Renal Disease, Ministry of Health of China, Beijing, China
- Key Laboratory of Chronic Kidney Disease Prevention and Treatment (Peking University), Ministry of Education, Beijing, China
| | - Jun-Wen Huang
- Renal Division, Peking University First Hospital, Peking University Institute of Nephrology, Beijing, China
- Key Laboratory of Renal Disease, Ministry of Health of China, Beijing, China
- Key Laboratory of Chronic Kidney Disease Prevention and Treatment (Peking University), Ministry of Education, Beijing, China
| | - Gui Li
- Renal Division, Peking University First Hospital, Peking University Institute of Nephrology, Beijing, China
- Key Laboratory of Renal Disease, Ministry of Health of China, Beijing, China
- Key Laboratory of Chronic Kidney Disease Prevention and Treatment (Peking University), Ministry of Education, Beijing, China
| | - Yang Liu
- Renal Division, Peking University First Hospital, Peking University Institute of Nephrology, Beijing, China
- Key Laboratory of Renal Disease, Ministry of Health of China, Beijing, China
- Key Laboratory of Chronic Kidney Disease Prevention and Treatment (Peking University), Ministry of Education, Beijing, China
| | - Xiao-Juan Yu
- Renal Division, Peking University First Hospital, Peking University Institute of Nephrology, Beijing, China
- Key Laboratory of Renal Disease, Ministry of Health of China, Beijing, China
- Key Laboratory of Chronic Kidney Disease Prevention and Treatment (Peking University), Ministry of Education, Beijing, China
| | - Swapan K. Nath
- Arthritis and Clinical Immunology Program, Oklahoma Medical Research Foundation, Oklahoma City, Oklahoma
| | - Lam C. Tsoi
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, Michigan
- Center for Statistical Genetics, Department of Biostatistics, University of Michigan, Ann Arbor, Michigan
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan
| | - Matthew T. Patrick
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, Michigan
- Center for Statistical Genetics, Department of Biostatistics, University of Michigan, Ann Arbor, Michigan
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan
| | - Celine C. Berthier
- Division of Nephrology, Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan
| | - Gang Liu
- Renal Division, Peking University First Hospital, Peking University Institute of Nephrology, Beijing, China
- Key Laboratory of Renal Disease, Ministry of Health of China, Beijing, China
- Key Laboratory of Chronic Kidney Disease Prevention and Treatment (Peking University), Ministry of Education, Beijing, China
| | - Su-Xia Wang
- Renal Division, Peking University First Hospital, Peking University Institute of Nephrology, Beijing, China
- Key Laboratory of Renal Disease, Ministry of Health of China, Beijing, China
- Key Laboratory of Chronic Kidney Disease Prevention and Treatment (Peking University), Ministry of Education, Beijing, China
| | - Huji Xu
- Department of Rheumatology and Immunology, Shanghai Changzheng Hospital, Second Military Medical University, Shanghai, China
- Peking-Tsinghua Center for Life Sciences, Tsinghua University, Beijing, China
- School of Clinical Medicine, Tsinghua University, Beijing, China
| | - Nan Chen
- Department of Nephrology, Institute of Nephrology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Chuan-Ming Hao
- Division of Nephrology, Huashan Hospital, Fudan University, Shanghai, China
| | - Hong Zhang
- Renal Division, Peking University First Hospital, Peking University Institute of Nephrology, Beijing, China
- Key Laboratory of Renal Disease, Ministry of Health of China, Beijing, China
- Key Laboratory of Chronic Kidney Disease Prevention and Treatment (Peking University), Ministry of Education, Beijing, China
| | - Li Yang
- Renal Division, Peking University First Hospital, Peking University Institute of Nephrology, Beijing, China
- Key Laboratory of Renal Disease, Ministry of Health of China, Beijing, China
- Key Laboratory of Chronic Kidney Disease Prevention and Treatment (Peking University), Ministry of Education, Beijing, China
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7
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Khan M, Khan S, Lohani M, Ahmed MM, Sharma D, Ishrat R, Ahmad S, Sherwani S, Haque S, Bhagwath SS. Assessment of key regulatory genes and identification of possible drug targets for Leprosy (Hansen's disease) using network-based approach. Biotechnol Genet Eng Rev 2023:1-20. [PMID: 36696368 DOI: 10.1080/02648725.2023.2168509] [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: 10/07/2022] [Accepted: 01/10/2023] [Indexed: 01/26/2023]
Abstract
Leprosy is a major health concern and continues to be a source of fear and stigma among people worldwide. Despite remarkable achievements in the treatment, understanding of pathogenesis and transmission, epidemiology of leprosy still remains inadequate. The prolonged incubation period, slow rates of occurrence in those exposed and deceptive clinical presentation pose challenges to develop reliable strategies to stop transmission. Hence, there is a need for improved diagnostics and therapies to prevent mortality caused by leprosy. The objectives of this study are to identify significant genes from protein-protein interactions (PPIs) network of leprosy and to choose the most effective therapeutic targets. Fifty genes related with leprosy were discovered by literature mining. These genes were used to construct a primary network. Leading Eigen Vector method was used to break down the primary network into various sub-networks or communities. It was found that the primary network was divided into many sub-networks at the 6 levels. Seed genes were traced at each level till key regulatory genes were identified. Three seed genes, namely, GNAI3, NOTCH1, and HIF1A, were able to make their way till the final motif stage. These genes along with their interacting partners were considered key regulators of the leprosy network. This study provides leprosy-associated key genes which can lead to improved diagnosis and therapies for leprosy patients.
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Affiliation(s)
- Mahvish Khan
- Department of Biology, College of Science, University of Ha'il, Ha'il, Saudi Arabia
| | - Saif Khan
- Department of Basic Dental and Medical Sciences, College of Dentistry, Ha'il University, Ha'il, Saudi Arabia
| | - Mohtashim Lohani
- Department of Emergency Medical Services, College of Applied Medical Sciences, Jazan University, Jazan, Saudi Arabia
| | - Mohd Murshad Ahmed
- Centre for Interdisciplinary Research in Basic Sciences, Jamia Millia Islamia, New Delhi, India
| | - Diksha Sharma
- Centre for Interdisciplinary Research in Basic Sciences, Jamia Millia Islamia, New Delhi, India
| | - Romana Ishrat
- Centre for Interdisciplinary Research in Basic Sciences, Jamia Millia Islamia, New Delhi, India
| | - Saheem Ahmad
- Department of Clinical Laboratory Sciences, College of Applied Medical Sciences, University of Ha'il, Ha'il, Saudi Arabia
| | - Subuhi Sherwani
- Department of Biology, College of Science, University of Ha'il, Ha'il, Saudi Arabia
| | - Shafiul Haque
- Research and Scientific Studies Unit, College of Nursing & Allied Health Sciences, Jazan University, Jazan, Saudi Arabia
- Gilbert and Rose-Marie Chagoury School of Medicine, Lebanese American University, Beirut, Lebanon
- Centre of Medical and Bio-Allied Health Sciences Research, Ajman University, Ajman, United Arab Emirates
| | - Sundeep S Bhagwath
- Department of Basic Dental and Medical Sciences, College of Dentistry, Ha'il University, Ha'il, Saudi Arabia
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8
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Uncovering novel MHC alleles from RNA-Seq data: expanding the spectrum of MHC class I alleles in sheep. BMC Genom Data 2023; 24:1. [PMID: 36597020 PMCID: PMC9809118 DOI: 10.1186/s12863-022-01102-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2022] [Accepted: 12/20/2022] [Indexed: 01/05/2023] Open
Abstract
BACKGROUND Major histocompatibility complex (MHC) class I glycoproteins present selected peptides or antigens to CD8 + T cells that control the cytotoxic immune response. The MHC class I genes are among the most polymorphic loci in the vertebrate genome, with more than twenty thousand alleles known in humans. In sheep, only a very small number of alleles have been described to date, making the development of genotyping systems or functional studies difficult. A cost-effective way to identify new alleles could be to use already available RNA-Seq data from sheep. Current strategies for aligning RNA-Seq reads against annotated genome sequences or transcriptomes fail to detect the majority of class I alleles. Here, I combine the alignment of RNA-Seq reads against a specific reference database with de novo assembly to identify alleles. The method allows the comprehensive discovery of novel MHC class I alleles from RNA-Seq data (DinoMfRS). RESULTS Using DinoMfRS, virtually all expressed MHC class I alleles could be determined. From 18 animals 75 MHC class I alleles were identified, of which 69 were novel. In addition, it was shown that DinoMfRS can be used to improve the annotation of MHC genes in the sheep genome sequence. CONCLUSIONS DinoMfRS allows for the first time the annotation of unknown, more divergent MHC alleles from RNA-Seq data. Successful application to RNA-Seq data from 16 animals has approximately doubled the number of known alleles in sheep. By using existing data, alleles can now be determined very inexpensively for populations that have not been well studied. In addition, MHC expression studies or evolutionary studies, for example, can be greatly improved in this way, and the method should be applicable to a broader spectrum of other multigene families or highly polymorphic genes.
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9
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Fakhkhari M, Caidi H, Sadki K. HLA alleles associated with COVID-19 susceptibility and severity in different populations: a systematic review. EGYPTIAN JOURNAL OF MEDICAL HUMAN GENETICS 2023; 24:10. [PMID: 36710951 PMCID: PMC9867832 DOI: 10.1186/s43042-023-00390-5] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2022] [Accepted: 01/15/2023] [Indexed: 01/23/2023] Open
Abstract
Background COVID-19 is a respiratory disease caused by a novel coronavirus called as Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). Detected for the first time in December 2019 in Wuhan and it has quickly spread all over the world in a couple of months and becoming a world pandemic. Symptoms of the disease and clinical outcomes are very different in infected people. These differences highlight the paramount need to study and understand the human genetic variation that occurring viral infections. Human leukocyte antigen (HLA) is an important component of the viral antigen presentation pathway, and it plays an essential role in conferring differential viral susceptibility and severity of diseases. HLA alleles have been involved in the immune response to viral diseases such as SARS-CoV-2. Main body of the abstract Herein, we sought to evaluate this hypothesis by summarizing the association between HLA class I and class II alleles with COVID-19 susceptibility and/or severity reported in previous studies among different populations (Chinese, Italian, Iranian, Japanese, Spanish, etc.). The findings of all selected articles showed that several alleles have been found associated with COVID-19 susceptibility and severity. Even results across articles have been inconsistent and, in some cases, conflicting, highlighting that the association between the HLA system and the COVID-19 outcome might be ethnic-dependent, there were some alleles in common between some populations such as HLA-DRB1*15 and HLA-A*30:02. Conclusion These contradictory findings warrant further large, and reproducible studies to decipher any possible genetic predisposition underlying susceptibility to SARS-COV-2 and disease progression and host immune response.
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Affiliation(s)
- Meryem Fakhkhari
- grid.31143.340000 0001 2168 4024Research Laboratory in Oral Biology and Biotechnology, Faculty of Dental Medicine, Mohammed V University in Rabat, Rabat, Morocco
| | - Hayat Caidi
- grid.416738.f0000 0001 2163 0069NARST Surveillance Unit, National Center for Emerging and Zoonotic Infectious Diseases, Centers for Disease Control and Prevention, Atlanta, GA USA
| | - Khalid Sadki
- grid.31143.340000 0001 2168 4024Research Laboratory in Oral Biology and Biotechnology, Faculty of Dental Medicine, Mohammed V University in Rabat, Rabat, Morocco
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10
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Gilchrist JJ, Auckland K, Parks T, Mentzer AJ, Goldblatt L, Naranbhai V, Band G, Rockett KA, Toure OB, Konate S, Sissoko S, Djimdé AA, Thera MA, Doumbo OK, Sow S, Floyd S, Pönnighaus JM, Warndorff DK, Crampin AC, Fine PEM, Fairfax BP, Hill AVS. Genome-wide association study of leprosy in Malawi and Mali. PLoS Pathog 2022; 18:e1010312. [PMID: 36121873 PMCID: PMC9624411 DOI: 10.1371/journal.ppat.1010312] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2022] [Revised: 11/01/2022] [Accepted: 07/12/2022] [Indexed: 11/28/2022] Open
Abstract
Leprosy is a chronic infection of the skin and peripheral nerves caused by Mycobacterium leprae. Despite recent improvements in disease control, leprosy remains an important cause of infectious disability globally. Large-scale genetic association studies in Chinese, Vietnamese and Indian populations have identified over 30 susceptibility loci for leprosy. There is a significant burden of leprosy in Africa, however it is uncertain whether the findings of published genetic association studies are generalizable to African populations. To address this, we conducted a genome-wide association study (GWAS) of leprosy in Malawian (327 cases, 436 controls) and Malian (247 cases, 368 controls) individuals. In that analysis, we replicated four risk loci previously reported in China, Vietnam and India; MHC Class I and II, LACC1 and SLC29A3. We further identified a novel leprosy susceptibility locus at 10q24 (rs2015583; combined p = 8.81 × 10-9; OR = 0.51 [95% CI 0.40 - 0.64]). Using publicly-available data we characterise regulatory activity at this locus, identifying ACTR1A as a candidate mediator of leprosy risk. This locus shows evidence of recent positive selection and demonstrates pleiotropy with established risk loci for inflammatory bowel disease and childhood-onset asthma. A shared genetic architecture for leprosy and inflammatory bowel disease has been previously described. We expand on this, strengthening the hypothesis that selection pressure driven by leprosy has shaped the evolution of autoimmune and atopic disease in modern populations. More broadly, our data highlights the importance of defining the genetic architecture of disease across genetically diverse populations, and that disease insights derived from GWAS in one population may not translate to all affected populations.
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Affiliation(s)
- James J. Gilchrist
- Department of Paediatrics, University of Oxford, Oxford, United Kingdom
- MRC–Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, United Kingdom
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
- * E-mail: (JJG); (AVSH)
| | - Kathryn Auckland
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
| | - Tom Parks
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
- Department of Infectious Diseases, Imperial College London, London, United Kingdom
| | - Alexander J. Mentzer
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
| | | | - Vivek Naranbhai
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
| | - Gavin Band
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
| | - Kirk A. Rockett
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
| | - Ousmane B. Toure
- Malaria Research and Training Centre, University of Science, Techniques and Technologies of Bamako, Bamako, Mali
| | - Salimata Konate
- Malaria Research and Training Centre, University of Science, Techniques and Technologies of Bamako, Bamako, Mali
| | - Sibiri Sissoko
- Malaria Research and Training Centre, University of Science, Techniques and Technologies of Bamako, Bamako, Mali
| | - Abdoulaye A. Djimdé
- Malaria Research and Training Centre, University of Science, Techniques and Technologies of Bamako, Bamako, Mali
| | - Mahamadou A. Thera
- Malaria Research and Training Centre, University of Science, Techniques and Technologies of Bamako, Bamako, Mali
| | - Ogobara K. Doumbo
- Malaria Research and Training Centre, University of Science, Techniques and Technologies of Bamako, Bamako, Mali
| | - Samba Sow
- Center for Vaccine Development, Bamako, Mali
| | - Sian Floyd
- Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, United Kingdom
| | - Jörg M. Pönnighaus
- Malawi Epidemiology and Intervention Research Unit (formerly Karonga Prevention Study), Chilumba, Malawi
| | - David K. Warndorff
- Malawi Epidemiology and Intervention Research Unit (formerly Karonga Prevention Study), Chilumba, Malawi
| | - Amelia C. Crampin
- Malawi Epidemiology and Intervention Research Unit (formerly Karonga Prevention Study), Chilumba, Malawi
| | - Paul E. M. Fine
- Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, United Kingdom
| | - Benjamin P. Fairfax
- MRC–Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, United Kingdom
| | - Adrian V. S. Hill
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
- Jenner Institute, University of Oxford, Oxford, United Kingdom
- * E-mail: (JJG); (AVSH)
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11
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Zhao LP, Skyler J, Papadopoulos GK, Pugliese A, Najera JA, Bondinas GP, Moustakas AK, Wang R, Pyo CW, Nelson WC, Geraghty DE, Lernmark Å. Association of HLA-DQ Heterodimer Residues -18β and β57 With Progression From Islet Autoimmunity to Diabetes in the Diabetes Prevention Trial-Type 1. Diabetes Care 2022; 45:1610-1620. [PMID: 35621697 PMCID: PMC9274226 DOI: 10.2337/dc21-1628] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/13/2021] [Accepted: 03/07/2022] [Indexed: 02/03/2023]
Abstract
OBJECTIVE The purpose was to test the hypothesis that the HLA-DQαβ heterodimer structure is related to the progression of islet autoimmunity from asymptomatic to symptomatic type 1 diabetes (T1D). RESEARCH DESIGN AND METHODS Next-generation targeted sequencing was used to genotype HLA-DQA1-B1 class II genes in 670 subjects in the Diabetes Prevention Trial-Type 1 (DPT-1). Coding sequences were translated into DQ α- and β-chain amino acid residues and used in hierarchically organized haplotype (HOH) association analysis to identify motifs associated with diabetes onset. RESULTS The opposite diabetes risks were confirmed for HLA DQA1*03:01-B1*03:02 (hazard ratio [HR] 1.36; P = 2.01 ∗ 10-3) and DQA1*03:03-B1*03:01 (HR 0.62; P = 0.037). The HOH analysis uncovered residue -18β in the signal peptide and β57 in the β-chain to form six motifs. DQ*VA was associated with faster (HR 1.49; P = 6.36 ∗ 10-4) and DQ*AD with slower (HR 0.64; P = 0.020) progression to diabetes onset. VA/VA, representing DQA1*03:01-B1*03:02 (DQ8/8), had a greater HR of 1.98 (P = 2.80 ∗ 10-3). The DQ*VA motif was associated with both islet cell antibodies (P = 0.023) and insulin autoantibodies (IAAs) (P = 3.34 ∗ 10-3), while the DQ*AD motif was associated with a decreased IAA frequency (P = 0.015). Subjects with DQ*VA and DQ*AD experienced, respectively, increasing and decreasing trends of HbA1c levels throughout the follow-up. CONCLUSIONS HLA-DQ structural motifs appear to modulate progression from islet autoimmunity to diabetes among at-risk relatives with islet autoantibodies. Residue -18β within the signal peptide may be related to levels of protein synthesis and β57 to stability of the peptide-DQab trimolecular complex.
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Affiliation(s)
- Lue Ping Zhao
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA.,School of Public Health, University of Washington, Seattle, WA
| | - Jay Skyler
- Diabetes Research Institute and Division of Endocrinology, Diabetes and Metabolism, University of Miami Miller School of Medicine, Miami, FL
| | - George K Papadopoulos
- Laboratory of Biophysics, Biochemistry, Biomaterials and Bioprocessing, Faculty of Agricultural Technology, Technological Educational Institute of Epirus, Arta, Greece
| | - Alberto Pugliese
- Diabetes Research Institute and Division of Endocrinology, Diabetes and Metabolism, University of Miami Miller School of Medicine, Miami, FL
| | | | - George P Bondinas
- Department of Food Science and Technology, Faculty of Environmental Sciences, Ionian University, Argostoli, Kefalonia, Greece
| | - Antonis K Moustakas
- Department of Food Science and Technology, Faculty of Environmental Sciences, Ionian University, Argostoli, Kefalonia, Greece
| | - Ruihan Wang
- Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, WA
| | - Chul-Woo Pyo
- Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, WA
| | - Wyatt C Nelson
- Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, WA
| | - Daniel E Geraghty
- Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, WA
| | - Åke Lernmark
- Department of Clinical Sciences, Lund University Clinical Research Centre, Skåne University Hospital, Malmö, Sweden
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12
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Human Leukocyte Antigen (HLA) System: Genetics and Association with Bacterial and Viral Infections. J Immunol Res 2022; 2022:9710376. [PMID: 35664353 PMCID: PMC9162874 DOI: 10.1155/2022/9710376] [Citation(s) in RCA: 23] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2022] [Accepted: 05/08/2022] [Indexed: 12/19/2022] Open
Abstract
The human leukocyte antigen (HLA) system is one of the most crucial host factors influencing disease progression in bacterial and viral infections. This review provides the basic concepts of the structure and function of HLA molecules in humans. Here, we highlight the main findings on the associations between HLA class I and class II alleles and susceptibility to important infectious diseases such as tuberculosis, leprosy, melioidosis, Staphylococcus aureus infection, human immunodeficiency virus infection, coronavirus disease 2019, hepatitis B, and hepatitis C in populations worldwide. Finally, we discuss challenges in HLA typing to predict disease outcomes in clinical implementation. Evaluation of the impact of HLA variants on the outcome of bacterial and viral infections would improve the understanding of pathogenesis and identify those at risk from infectious diseases in distinct populations and may improve the individual treatment.
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13
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de Souza BJ, Mendes MA, Sperandio da Silva GM, Sammarco-Rosa P, de Moraes MO, Jardim MR, Sarno EN, Pinheiro RO, Mietto BS. Gene Expression Profile of Mycobacterium leprae Contribution in the Pathology of Leprosy Neuropathy. Front Med (Lausanne) 2022; 9:861586. [PMID: 35492305 PMCID: PMC9051340 DOI: 10.3389/fmed.2022.861586] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2022] [Accepted: 03/14/2022] [Indexed: 11/23/2022] Open
Abstract
Peripheral neuropathy is the main cause of physical disability in leprosy patients. Importantly, the extension and pattern of peripheral damage has been linked to how the host cell will respond against Mycobacterium leprae (M. leprae) infection, in particular, how the pathogen will establish infection in Schwann cells. Interestingly, viable and dead M. leprae have been linked to neuropathology of leprosy by distinct mechanisms. While viable M. leprae promotes transcriptional modifications that allow the bacteria to survive through the use of the host cell's internal machinery and the subvert of host metabolites, components of the dead bacteria are associated with the generation of a harmful nerve microenvironment. Therefore, understanding the pathognomonic characteristics mediated by viable and dead M. leprae are essential for elucidating leprosy disease and its associated reactional episodes. Moreover, the impact of the viable and dead bacteria in Schwann cells is largely unknown and their gene signature profiling has, as yet, been poorly explored. In this study, we analyzed the early differences in the expression profile of genes involved in peripheral neuropathy, dedifferentiation and plasticity, neural regeneration, and inflammation in human Schwann cells challenged with viable and dead M. leprae. We substantiated our findings by analyzing this genetic profiling in human nerve biopsies of leprosy and non-leprosy patients, with accompanied histopathological analysis. We observed that viable and dead bacteria distinctly modulate Schwann cell genes, with emphasis to viable bacilli upregulating transcripts related to glial cell plasticity, dedifferentiation and anti-inflammatory profile, while dead bacteria affected genes involved in neuropathy and pro-inflammatory response. In addition, dead bacteria also upregulated genes associated with nerve support, which expression profile was similar to those obtained from leprosy nerve biopsies. These findings suggest that early exposure to viable and dead bacteria may provoke Schwann cells to behave differentially, with far-reaching implications for the ongoing neuropathy seen in leprosy patients, where a mixture of active and non-active bacteria are found in the nerve microenvironment.
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Affiliation(s)
| | - Mayara Abud Mendes
- Leprosy Laboratory, Oswaldo Cruz Institute, Fiocruz, Rio de Janeiro, Brazil
| | | | | | | | | | | | | | - Bruno Siqueira Mietto
- Laboratory of Cell Biology, Institute of Biological Sciences, Federal University of Juiz de Fora, Juiz de Fora, Brazil
- *Correspondence: Bruno Siqueira Mietto
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14
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Fava VM, Dallmann-Sauer M, Orlova M, Correa-Macedo W, Van Thuc N, Thai VH, Alcaïs A, Abel L, Cobat A, Schurr E. Deep resequencing identifies candidate functional genes in leprosy GWAS loci. PLoS Negl Trop Dis 2021; 15:e0010029. [PMID: 34879060 PMCID: PMC8687567 DOI: 10.1371/journal.pntd.0010029] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2021] [Revised: 12/20/2021] [Accepted: 11/27/2021] [Indexed: 11/18/2022] Open
Abstract
Leprosy is the second most prevalent mycobacterial disease globally. Despite the existence of an effective therapy, leprosy incidence has consistently remained above 200,000 cases per year since 2010. Numerous host genetic factors have been identified for leprosy that contribute to the persistently high case numbers. In the past decade, genetic epidemiology approaches, including genome-wide association studies (GWAS), identified more than 30 loci contributing to leprosy susceptibility. However, GWAS loci commonly encompass multiple genes, which poses a challenge to define causal candidates for each locus. To address this problem, we hypothesized that genes contributing to leprosy susceptibility differ in their frequencies of rare protein-altering variants between cases and controls. Using deep resequencing we assessed protein-coding variants for 34 genes located in GWAS or linkage loci in 555 Vietnamese leprosy cases and 500 healthy controls. We observed 234 nonsynonymous mutations in the targeted genes. A significant depletion of protein-altering variants was detected for the IL18R1 and BCL10 genes in leprosy cases. The IL18R1 gene is clustered with IL18RAP and IL1RL1 in the leprosy GWAS locus on chromosome 2q12.1. Moreover, in a recent GWAS we identified an HLA-independent signal of association with leprosy on chromosome 6p21. Here, we report amino acid changes in the CDSN and PSORS1C2 genes depleted in leprosy cases, indicating them as candidate genes in the chromosome 6p21 locus. Our results show that deep resequencing can identify leprosy candidate susceptibility genes that had been missed by classic linkage and association approaches.
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Affiliation(s)
- Vinicius M. Fava
- Program in Infectious Diseases and Immunity in Global Health, The Research Institute of the McGill University Health Centre, Montreal, Canada
- McGill International TB Centre, Montreal, Canada
| | - Monica Dallmann-Sauer
- Program in Infectious Diseases and Immunity in Global Health, The Research Institute of the McGill University Health Centre, Montreal, Canada
- McGill International TB Centre, Montreal, Canada
- Department of Human Genetics, Faculty of Medicine and Health Sciences, McGill University, Montreal, Canada
| | - Marianna Orlova
- Program in Infectious Diseases and Immunity in Global Health, The Research Institute of the McGill University Health Centre, Montreal, Canada
- McGill International TB Centre, Montreal, Canada
- Department of Medicine, Faculty of Medicine and Health Sciences, McGill University, Montreal, Canada
| | - Wilian Correa-Macedo
- Program in Infectious Diseases and Immunity in Global Health, The Research Institute of the McGill University Health Centre, Montreal, Canada
- McGill International TB Centre, Montreal, Canada
- Department of Biochemistry, Faculty of Medicine and Health Sciences, McGill University, Montreal, Canada
| | | | - Vu Hong Thai
- Hospital for Dermato-Venerology, Ho Chi Minh City, Vietnam
| | - Alexandre Alcaïs
- Laboratory of Human Genetics of Infectious Diseases, Necker Branch, Institut National de la Santé et de la Recherche Médicale 1163, Paris, France
- Imagine Institute, Paris Descartes-Sorbonne Paris Cité University, Paris, France
| | - Laurent Abel
- Laboratory of Human Genetics of Infectious Diseases, Necker Branch, Institut National de la Santé et de la Recherche Médicale 1163, Paris, France
- Imagine Institute, Paris Descartes-Sorbonne Paris Cité University, Paris, France
- St. Giles Laboratory of Human Genetics of Infectious Diseases, Rockefeller Branch, Rockefeller University, New York, United States of America
| | - Aurélie Cobat
- Laboratory of Human Genetics of Infectious Diseases, Necker Branch, Institut National de la Santé et de la Recherche Médicale 1163, Paris, France
- Imagine Institute, Paris Descartes-Sorbonne Paris Cité University, Paris, France
| | - Erwin Schurr
- Program in Infectious Diseases and Immunity in Global Health, The Research Institute of the McGill University Health Centre, Montreal, Canada
- McGill International TB Centre, Montreal, Canada
- Department of Human Genetics, Faculty of Medicine and Health Sciences, McGill University, Montreal, Canada
- Department of Medicine, Faculty of Medicine and Health Sciences, McGill University, Montreal, Canada
- Department of Biochemistry, Faculty of Medicine and Health Sciences, McGill University, Montreal, Canada
- * E-mail:
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Luo Y, Kiriya M, Tanigawa K, Kawashima A, Nakamura Y, Ishii N, Suzuki K. Host-Related Laboratory Parameters for Leprosy Reactions. Front Med (Lausanne) 2021; 8:694376. [PMID: 34746168 PMCID: PMC8568883 DOI: 10.3389/fmed.2021.694376] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2021] [Accepted: 09/30/2021] [Indexed: 12/27/2022] Open
Abstract
Leprosy reactions are acute inflammatory episodes that complicate the course of a Mycobacterium leprae infection and are the major cause of leprosy-associated pathology. Two types of leprosy reactions with relatively distinct pathogenesis and clinical features can occur: type 1 reaction, also known as reversal reaction, and type 2 reaction, also known as erythema nodosum leprosum. These acute nerve-destructive immune exacerbations often cause irreversible disabilities and deformities, especially when diagnosis is delayed. However, there is no diagnostic test to detect or predict leprosy reactions before the onset of clinical symptoms. Identification of biomarkers for leprosy reactions, which impede the development of symptoms or correlate with early-onset, will allow precise diagnosis and timely interventions to greatly improve the patients' quality of life. Here, we review the progress of research aimed at identifying biomarkers for leprosy reactions, including its correlation with not only immunity but also genetics, transcripts, and metabolites, providing an understanding of the immune dysfunction and inflammation that underly the pathogenesis of leprosy reactions. Nevertheless, no biomarkers that can reliably predict the subsequent occurrence of leprosy reactions from non-reactional patients and distinguish type I reaction from type II have yet been found.
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Affiliation(s)
- Yuqian Luo
- Department of Laboratory Medicine, Nanjing Drum Tower Hospital and Jiangsu Key Laboratory for Molecular Medicine, Nanjing University Medical School, Nanjing, China.,Department of Clinical Laboratory Science, Faculty of Medical Technology, Teikyo University, Tokyo, Japan
| | - Mitsuo Kiriya
- Department of Clinical Laboratory Science, Faculty of Medical Technology, Teikyo University, Tokyo, Japan
| | - Kazunari Tanigawa
- Department of Molecular Pharmaceutics, Faculty of Pharma-Science, Teikyo University, Tokyo, Japan
| | - Akira Kawashima
- Department of Clinical Laboratory Science, Faculty of Medical Technology, Teikyo University, Tokyo, Japan
| | - Yasuhiro Nakamura
- Department of Molecular Pharmaceutics, Faculty of Pharma-Science, Teikyo University, Tokyo, Japan
| | - Norihisa Ishii
- Department of Clinical Laboratory Science, Faculty of Medical Technology, Teikyo University, Tokyo, Japan.,National Sanatorium Tamazenshoen, Tokyo, Japan
| | - Koichi Suzuki
- Department of Clinical Laboratory Science, Faculty of Medical Technology, Teikyo University, Tokyo, Japan
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