1
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Heo Y, Kim J, Hong SH, Kim WJ. Single cell transcriptomics in blood of patients with chronic obstructive pulmonary disease. BMC Pulm Med 2025; 25:19. [PMID: 39810158 PMCID: PMC11734329 DOI: 10.1186/s12890-024-03475-y] [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: 12/20/2023] [Accepted: 12/31/2024] [Indexed: 01/16/2025] Open
Abstract
BACKGROUND Chronic obstructive pulmonary disease (COPD) is a leading cause of morbidity and mortality worldwide. Single-cell RNA sequencing (scRNA-seq) provides gene expression profiles at the single-cell level. Hence, we evaluated gene expression in the peripheral blood of patients with COPD. METHODS Peripheral blood samples from seven healthy controls and eight patients with COPD were obtained in this study. The 10X Genomics Chromium Instrument and cDNA synthesis kit were utilized to generate a barcoded cDNA library for single cell RNA-sequencing. We compared the scRNA-seq data between the COPD and control groups using computational analysis. Functional analyses were performed using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses. RESULTS scRNA-seq was used to analyze the transcriptome of peripheral blood mononuclear cells from seven normal controls and eight patients with COPD. We found an increased number of monocyte/macrophages in the COPD group compared to the normal control group. Among the differentially expressed genes (DEGs) in monocyte/macrophages, we identified 15 upregulated genes (EGR1, NR4A1, CCL3, CXCL8, PTGS2, CD83, BCL2A1, SGK1, IL1B, BTG2, NFKBIZ, DUSP2, MAFB, PLAUR and CCL3L1) and 7 downregulated genes (FOLR3, RPS4Y1, HLA-DRB5, NAMPT, CD52, TMEM176A and TMEM176B) in the COPD group compared to the normal control group. CONCLUSIONS Using scRNA-seq, we found differences in cell type distribution, especially in monocyte/ macrophages. Several upregulated and downregulated genes were found in the monocyte/macrophages of the COPD group.
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Affiliation(s)
- Yeonjeong Heo
- Department of Internal Medicine, Kangwon National University Hospital, Chuncheon, Korea
| | - Jeeyoung Kim
- Department of Internal Medicine, Kangwon National University Hospital, Chuncheon, Korea
| | - Seok-Ho Hong
- Department of Internal Medicine, School of Medicine, Kangwon National University, Chuncheon, Korea
| | - Woo Jin Kim
- Department of Internal Medicine, Kangwon National University Hospital, Chuncheon, Korea.
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2
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Qiao J, Xu M, Xu F, Che Z, Han P, Dai X, Miao N, Zhu M. Identification of SNPs and Candidate Genes Associated with Monocyte/Lymphocyte Ratio and Neutrophil/Lymphocyte Ratio in Duroc × Erhualian F 2 Population. Int J Mol Sci 2024; 25:9745. [PMID: 39273692 PMCID: PMC11396299 DOI: 10.3390/ijms25179745] [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: 07/22/2024] [Revised: 09/06/2024] [Accepted: 09/08/2024] [Indexed: 09/15/2024] Open
Abstract
Understanding the pig immune function is crucial for disease-resistant breeding and potentially for human health research due to shared immune system features. Immune cell ratios, like monocyte/lymphocyte ratio (MLR) and neutrophil/lymphocyte ratio (NLR), offer a more comprehensive view of immune status compared to individual cell counts. However, research on pig immune cell ratios remains limited. This study investigated MLR and NLR in a Duroc × Erhualian F2 resource population. Heritability analysis revealed high values (0.649 and 0.688 for MLR and NLR, respectively), suggesting a strong genetic component. Furthermore, we employed an ensemble-like GWAS (E-GWAS) strategy and functional annotation analysis to identify 11 MLR-associated and 6 NLR-associated candidate genes. These genes were significantly enriched in immune-related biological processes. These findings provide novel genetic markers and candidate genes associated with porcine immunity, thereby providing valuable insights for addressing biosecurity and animal welfare concerns in the pig industry.
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Affiliation(s)
- Jiakun Qiao
- Key Lab of Agricultural Animal Genetics, Breeding, and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan 430070, China
| | - Minghang Xu
- Key Lab of Agricultural Animal Genetics, Breeding, and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan 430070, China
| | - Fangjun Xu
- Key Lab of Agricultural Animal Genetics, Breeding, and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan 430070, China
| | - Zhaoxuan Che
- Key Lab of Agricultural Animal Genetics, Breeding, and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan 430070, China
| | - Pingping Han
- Key Lab of Agricultural Animal Genetics, Breeding, and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan 430070, China
| | - Xiangyu Dai
- Key Lab of Agricultural Animal Genetics, Breeding, and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan 430070, China
| | - Na Miao
- Key Lab of Agricultural Animal Genetics, Breeding, and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan 430070, China
| | - Mengjin Zhu
- Key Lab of Agricultural Animal Genetics, Breeding, and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan 430070, China
- The Cooperative Innovation Center for Sustainable Pig Production, Huazhong Agricultural University, Wuhan 430070, China
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3
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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: 2] [Impact Index Per Article: 0.5] [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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4
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Robertson CC, Inshaw JRJ, Onengut-Gumuscu S, Chen WM, Santa Cruz DF, Yang H, Cutler AJ, Crouch DJM, Farber E, Bridges SL, Edberg JC, Kimberly RP, Buckner JH, Deloukas P, Divers J, Dabelea D, Lawrence JM, Marcovina S, Shah AS, Greenbaum CJ, Atkinson MA, Gregersen PK, Oksenberg JR, Pociot F, Rewers MJ, Steck AK, Dunger DB, Wicker LS, Concannon P, Todd JA, Rich SS. Fine-mapping, trans-ancestral and genomic analyses identify causal variants, cells, genes and drug targets for type 1 diabetes. Nat Genet 2021; 53:962-971. [PMID: 34127860 PMCID: PMC8273124 DOI: 10.1038/s41588-021-00880-5] [Citation(s) in RCA: 128] [Impact Index Per Article: 32.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2020] [Accepted: 05/05/2021] [Indexed: 12/13/2022]
Abstract
We report the largest and most diverse genetic study of type 1 diabetes (T1D) to date (61,427 participants), yielding 78 genome-wide-significant (P < 5 × 10-8) regions, including 36 that are new. We define credible sets of T1D-associated variants and show that they are enriched in immune-cell accessible chromatin, particularly CD4+ effector T cells. Using chromatin-accessibility profiling of CD4+ T cells from 115 individuals, we map chromatin-accessibility quantitative trait loci and identify five regions where T1D risk variants co-localize with chromatin-accessibility quantitative trait loci. We highlight rs72928038 in BACH2 as a candidate causal T1D variant leading to decreased enhancer accessibility and BACH2 expression in T cells. Finally, we prioritize potential drug targets by integrating genetic evidence, functional genomic maps and immune protein-protein interactions, identifying 12 genes implicated in T1D that have been targeted in clinical trials for autoimmune diseases. These findings provide an expanded genomic landscape for T1D.
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Affiliation(s)
- Catherine C Robertson
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
- Department of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, VA, USA
| | - Jamie R J Inshaw
- JDRF/Wellcome Diabetes and Inflammation Laboratory, Wellcome Centre for Human Genetics, Nuffield Department of Medicine, NIHR Oxford Biomedical Research Centre, University of Oxford, Oxford, UK
| | - Suna Onengut-Gumuscu
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
- Department of Public Health Sciences, University of Virginia, Charlottesville, VA, USA
| | - Wei-Min Chen
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
- Department of Public Health Sciences, University of Virginia, Charlottesville, VA, USA
| | - David Flores Santa Cruz
- JDRF/Wellcome Diabetes and Inflammation Laboratory, Wellcome Centre for Human Genetics, Nuffield Department of Medicine, NIHR Oxford Biomedical Research Centre, University of Oxford, Oxford, UK
| | - Hanzhi Yang
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | - Antony J Cutler
- JDRF/Wellcome Diabetes and Inflammation Laboratory, Wellcome Centre for Human Genetics, Nuffield Department of Medicine, NIHR Oxford Biomedical Research Centre, University of Oxford, Oxford, UK
| | - Daniel J M Crouch
- JDRF/Wellcome Diabetes and Inflammation Laboratory, Wellcome Centre for Human Genetics, Nuffield Department of Medicine, NIHR Oxford Biomedical Research Centre, University of Oxford, Oxford, UK
| | - Emily Farber
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | - S Louis Bridges
- Division of Rheumatology, Department of Medicine, Hospital for Special Surgery, New York, NY, USA
- Division of Rheumatology, Department of Medicine, Weill Cornell Medical College, New York, NY, USA
| | - Jeffrey C Edberg
- Division of Clinical Immunology and Rheumatology, Department of Medicine, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Robert P Kimberly
- Division of Clinical Immunology and Rheumatology, Department of Medicine, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Jane H Buckner
- Center for Translational Immunology, Benaroya Research Institute, Seattle, WA, USA
| | - Panos Deloukas
- Clinical Pharmacology, William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
- Princess Al-Jawhara Al-Brahim Centre of Excellence in Research of Hereditary Disorders (PACER-HD), King Abdulaziz University, Jeddah, Saudi Arabia
| | - Jasmin Divers
- Division of Health Services Research, Department of Foundations of Medicine, New York University Long Island School of Medicine, Mineola, NY, USA
| | - Dana Dabelea
- Colorado School of Public Health and Lifecourse Epidemiology of Adiposity and Diabetes (LEAD) Center, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Jean M Lawrence
- Department of Research and Evaluation, Kaiser Permanente Southern California, Pasadena, CA, USA
| | - Santica Marcovina
- Northwest Lipid Metabolism and Diabetes Research Laboratories, University of Washington, Seattle, WA, USA
- Medpace Reference Laboratories, Cincinnati, OH, USA
| | - Amy S Shah
- Cincinnati Children's Hospital Medical Center and the University of Cincinnati, Cincinnati, OH, USA
| | - Carla J Greenbaum
- Center for Interventional Immunology, Benaroya Research Institute, Seattle, WA, USA
- Diabetes Program, Benaroya Research Institute, Seattle, WA, USA
| | - Mark A Atkinson
- Department of Pathology, Immunology, and Laboratory Medicine, University of Florida, Gainesville, FL, USA
| | - Peter K Gregersen
- Robert S. Boas Center for Genomics and Human Genetics, Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY, USA
| | - Jorge R Oksenberg
- Department of Neurology and Weill Institute for Neurosciences, University of California at San Francisco, San Francisco, CA, USA
| | - Flemming Pociot
- Department of Pediatrics, Herlev University Hospital, Copenhagen, Denmark
- Institute of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Type 1 Diabetes Biology, Department of Clinical Research, Steno Diabetes Center Copenhagen, Gentofte, Denmark
| | - Marian J Rewers
- Barbara Davis Center for Diabetes, School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Andrea K Steck
- Barbara Davis Center for Diabetes, School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - David B Dunger
- Department of Paediatrics, University of Cambridge, Cambridge, UK
- Wellcome Trust Medical Research Council Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - Linda S Wicker
- JDRF/Wellcome Diabetes and Inflammation Laboratory, Wellcome Centre for Human Genetics, Nuffield Department of Medicine, NIHR Oxford Biomedical Research Centre, University of Oxford, Oxford, UK
| | - Patrick Concannon
- Department of Pathology, Immunology, and Laboratory Medicine, University of Florida, Gainesville, FL, USA
- Genetics Institute, University of Florida, Gainesville, FL, USA
| | - John A Todd
- JDRF/Wellcome Diabetes and Inflammation Laboratory, Wellcome Centre for Human Genetics, Nuffield Department of Medicine, NIHR Oxford Biomedical Research Centre, University of Oxford, Oxford, UK.
| | - Stephen S Rich
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
- Department of Public Health Sciences, University of Virginia, Charlottesville, VA, USA
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5
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Ma J, Lam IKY, Lau CS, Chan VSF. Elevated Interleukin-18 Receptor Accessory Protein Mediates Enhancement in Reactive Oxygen Species Production in Neutrophils of Systemic Lupus Erythematosus Patients. Cells 2021; 10:cells10050964. [PMID: 33919154 PMCID: PMC8143138 DOI: 10.3390/cells10050964] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2021] [Revised: 04/16/2021] [Accepted: 04/19/2021] [Indexed: 12/19/2022] Open
Abstract
Interleukin-18 receptor accessory protein (IL18RAP) is an indispensable subunit for the IL-18 receptor (IL-18R) complex's ability to mediate high-affinity IL-18 binding and signalling transduction. Interest in IL-18 in systemic lupus erythematosus (SLE) has been mostly focused on its role as a type 1 T helper cell-driving cytokine. The functional significance of IL18RAP in mediating the IL-18-driven response in myeloid cells in SLE remains largely unexplored. This study aimed to investigate the expression and function significance of IL18RAP in neutrophils of SLE patients. By qRT-PCR and Western blot analyses, elevated expressions of IL18RAP mRNA and protein were observed in neutrophils from SLE patients-particularly those with a history of nephritis. IL18RAP expression correlated negatively with complement 3 level and positively with disease activity, with higher expression in patients exhibiting renal and immunological manifestations. The increased IL18RAP expression in SLE neutrophils could be attributed to elevated type I interferon level in sera. Functionally, neutrophils from SLE patients showed higher IL-18-mediated enhancement in reactive oxygen species (ROS) generation, which showed positive correlation with IL18RAP expression and could be neutralized by anti-IL18RAP blocking antibodies. Taken together, our findings suggest that IL-18 could contribute to SLE pathogenesis through mediation of neutrophil dysfunction via the upregulation of IL18RAP expression.
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6
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Sun P, Zhou W, Fu Y, Cheung CYY, Dong Y, Yang ML, Zhang H, Jia J, Huo Y, Willer CJ, Chen YE, Tang CS, Tse HF, Lam KSL, Gao W, Xu M, Yu H, Sham PC, Zhang Y, Ganesh SK. An Asian-specific MPL genetic variant alters JAK-STAT signaling and influences platelet count in the population. Hum Mol Genet 2021; 30:836-842. [PMID: 33693786 DOI: 10.1093/hmg/ddab062] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2020] [Revised: 02/20/2021] [Accepted: 02/23/2021] [Indexed: 12/27/2022] Open
Abstract
Genomic discovery efforts for hematological traits have been successfully conducted through genome-wide association study on samples of predominantly European ancestry. We sought to conduct unbiased genetic discovery for coding variants that influence hematological traits in a Han Chinese population. A total of 5257 Han Chinese subjects from Beijing, China were included in the discovery cohort and analyzed by an Illumina ExomeChip array. Replication analyses were conducted in 3827 independent Chinese subjects. We analyzed 12 hematological traits and identified 22 exome-wide significant single-nucleotide polymorphisms (SNP)-trait associations with 15 independent SNPs. Our study provides replication for two associations previously reported but not replicated. Further, one association was identified and replicated in the current study, of a coding variant in the myeloproliferative leukemia (MPL) gene, c.793C > T, p.Leu265Phe (L265F) with increased platelet count (β = 20.6 109 cells/l, Pmeta-analysis = 2.6 × 10-13). This variant is observed at ~2% population frequency in East Asians, whereas it has not been reported in gnomAD European or African populations. Functional analysis demonstrated that expression of MPL L265F in Ba/F3 cells resulted in enhanced phosphorylation of Stat3 and ERK1/2 as compared with the reference MPL allele, supporting altered activation of the JAK-STAT signal transduction pathway as the mechanism underlying the novel association between MPL L265F and platelet count.
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Affiliation(s)
- Pengfei Sun
- Department of Cardiology, Peking University First Hospital, Beijing 100034, China
| | - Wei Zhou
- Division of Cardiovascular Medicine, Department of Internal Medicine, University of Michigan Medical School, Ann Arbor, MI 48109, USA.,Department of Human Genetics, University of Michigan Medical School, Ann Arbor, MI 48109, USA.,Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA
| | - Yi Fu
- Department of Physiology and Pathophysiology, School of Basic Medical Sciences, Peking University, Beijing 100191, China.,Key Laboratory of Molecular Cardiovascular Science, Ministry of Education, Beijing 100191, China
| | - Chloe Y Y Cheung
- Department of Medicine, Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong 999077, China
| | - Yujun Dong
- Department of Hematology, Peking University First Hospital, Beijing 100034, China
| | - Min-Lee Yang
- Division of Cardiovascular Medicine, Department of Internal Medicine, University of Michigan Medical School, Ann Arbor, MI 48109, USA.,Department of Human Genetics, University of Michigan Medical School, Ann Arbor, MI 48109, USA
| | - He Zhang
- Division of Cardiovascular Medicine, Department of Internal Medicine, University of Michigan Medical School, Ann Arbor, MI 48109, USA.,Department of Human Genetics, University of Michigan Medical School, Ann Arbor, MI 48109, USA.,Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA
| | - Jia Jia
- Department of Cardiology, Peking University First Hospital, Beijing 100034, China
| | - Yong Huo
- Department of Cardiology, Peking University First Hospital, Beijing 100034, China
| | - Cristen J Willer
- Division of Cardiovascular Medicine, Department of Internal Medicine, University of Michigan Medical School, Ann Arbor, MI 48109, USA.,Department of Human Genetics, University of Michigan Medical School, Ann Arbor, MI 48109, USA.,Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA
| | - Y Eugene Chen
- Division of Cardiovascular Medicine, Department of Internal Medicine, University of Michigan Medical School, Ann Arbor, MI 48109, USA
| | - Clara S Tang
- Department of Surgery, Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong 999077, China
| | - Hung-Fat Tse
- Department of Physiology and Pathophysiology, School of Basic Medical Sciences, Peking University, Beijing 100191, China
| | - Karen S L Lam
- Department of Physiology and Pathophysiology, School of Basic Medical Sciences, Peking University, Beijing 100191, China
| | - Wei Gao
- Department of Cardiology, Peking University Third Hospital, Beijing 100083, China
| | - Ming Xu
- Department of Cardiology, Peking University Third Hospital, Beijing 100083, China
| | - Haiyi Yu
- Department of Cardiology, Peking University Third Hospital, Beijing 100083, China
| | - Pak Chung Sham
- Department of Psychiatry and Centre for PanorOmic Sciences, Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong 999077, China
| | - Yan Zhang
- Department of Cardiology, Peking University First Hospital, Beijing 100034, China.,Institute of Cardiovascular Disease?Peking University First Hospital, Beijing, 100034, China
| | - Santhi K Ganesh
- Division of Cardiovascular Medicine, Department of Internal Medicine, University of Michigan Medical School, Ann Arbor, MI 48109, USA.,Department of Human Genetics, University of Michigan Medical School, Ann Arbor, MI 48109, USA
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7
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Andiappan AK, Puan KJ, Lee B, Yeow PT, Yusof N, Merid SK, Kumar D, Lum J, Foo S, Koh G, Poidinger M, Zolezzi F, Wang DY, Melén E, Rotzschke O. Inverse association of FCER1A allergy variant in monocytes and plasmacytoid dendritic cells. J Allergy Clin Immunol 2020; 147:1510-1513.e8. [PMID: 33160967 DOI: 10.1016/j.jaci.2020.10.036] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2020] [Revised: 10/22/2020] [Accepted: 10/29/2020] [Indexed: 10/23/2022]
Affiliation(s)
- Anand Kumar Andiappan
- Singapore Immunology Network, Agency for Science, Technology and Research, Singapore
| | - Kia Joo Puan
- Singapore Immunology Network, Agency for Science, Technology and Research, Singapore
| | - Bernett Lee
- Singapore Immunology Network, Agency for Science, Technology and Research, Singapore
| | - Poh Tuang Yeow
- Singapore Immunology Network, Agency for Science, Technology and Research, Singapore; Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore
| | - Nurhashikin Yusof
- Singapore Immunology Network, Agency for Science, Technology and Research, Singapore
| | - Simon Kebede Merid
- Department of Clinical Science and Education Södersjukhuset, Karolinska Institutet, Stockholm, Sweden
| | - Dilip Kumar
- Singapore Immunology Network, Agency for Science, Technology and Research, Singapore
| | - Josephine Lum
- Singapore Immunology Network, Agency for Science, Technology and Research, Singapore
| | - Shihui Foo
- Singapore Immunology Network, Agency for Science, Technology and Research, Singapore
| | - Geraldine Koh
- Singapore Immunology Network, Agency for Science, Technology and Research, Singapore
| | - Michael Poidinger
- Singapore Immunology Network, Agency for Science, Technology and Research, Singapore; Murdoch Children's Research Institute, Victoria, Australia
| | - Francesca Zolezzi
- Singapore Immunology Network, Agency for Science, Technology and Research, Singapore
| | | | | | - De Yun Wang
- Department of Otalaryngology, National University of Singapore, Singapore
| | - Erik Melén
- Department of Clinical Science and Education Södersjukhuset, Karolinska Institutet, Stockholm, Sweden; Department of Paediatrics, Sachs' Children's Hospital, Stockholm, Sweden; Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Olaf Rotzschke
- Singapore Immunology Network, Agency for Science, Technology and Research, Singapore.
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8
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Cismaru AL, Rudin D, Ibañez L, Liakoni E, Bonadies N, Kreutz R, Carvajal A, Lucena MI, Martin J, Sancho Ponce E, Molokhia M, Eriksson N, Krähenbühl S, Largiadèr CR, Haschke M, Hallberg P, Wadelius M, Amstutz U. Genome-Wide Association Study of Metamizole-Induced Agranulocytosis in European Populations. Genes (Basel) 2020; 11:genes11111275. [PMID: 33138277 PMCID: PMC7716224 DOI: 10.3390/genes11111275] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2020] [Revised: 10/23/2020] [Accepted: 10/27/2020] [Indexed: 12/17/2022] Open
Abstract
Agranulocytosis is a rare yet severe idiosyncratic adverse drug reaction to metamizole, an analgesic widely used in countries such as Switzerland and Germany. Notably, an underlying mechanism has not yet been fully elucidated and no predictive factors are known to identify at-risk patients. With the aim to identify genetic susceptibility variants to metamizole-induced agranulocytosis (MIA) and neutropenia (MIN), we conducted a retrospective multi-center collaboration including cases and controls from three European populations. Association analyses were performed using genome-wide genotyping data from a Swiss cohort (45 cases, 191 controls) followed by replication in two independent European cohorts (41 cases, 273 controls) and a joint discovery meta-analysis. No genome-wide significant associations (p < 1 × 10−7) were observed in the Swiss cohort or in the joint meta-analysis, and no candidate genes suggesting an immune-mediated mechanism were identified. In the joint meta-analysis of MIA cases across all cohorts, two candidate loci on chromosome 9 were identified, rs55898176 (OR = 4.01, 95%CI: 2.41–6.68, p = 1.01 × 10−7) and rs4427239 (OR = 5.47, 95%CI: 2.81–10.65, p = 5.75 × 10−7), of which the latter is located in the SVEP1 gene previously implicated in hematopoiesis. This first genome-wide association study for MIA identified suggestive associations with biological plausibility that may be used as a stepping-stone for post-GWAS analyses to gain further insight into the mechanism underlying MIA.
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Affiliation(s)
- Anca Liliana Cismaru
- Department of Clinical Chemistry, Inselspital Bern University Hospital, University of Bern, 3010 Bern, Switzerland; (A.L.C.); (C.R.L.)
- Graduate School for Cellular and Biomedical Sciences, University of Bern, 3012 Bern, Switzerland
| | - Deborah Rudin
- Department of Clinical Pharmacology & Toxicology, University Hospital Basel, University of Basel, 4031 Basel, Switzerland; (D.R.); (S.K.)
- Department of Biomedicine, University of Basel, 4051 Basel, Switzerland
| | - Luisa Ibañez
- Clinical Pharmacology Service, Hospital Universitari Vall d’Hebron, Department of Pharmacology, Therapeutics and Toxicology, Autonomous University of Barcelona, Fundació Institut Català de Farmacología, 08035 Barcelona, Spain;
| | - Evangelia Liakoni
- Department of Clinical Pharmacology & Toxicology, Inselspital Bern University Hospital, University of Bern, 3010 Bern, Switzerland; (E.L.); (M.H.)
- Institute of Pharmacology, University of Bern, 3012 Bern, Switzerland
| | - Nicolas Bonadies
- Department of Hematology and Central Hematology Laboratory, Inselspital Bern University Hospital, University of Bern, 3010 Bern, Switzerland;
| | - Reinhold Kreutz
- Charité–Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Institut für Klinische Pharmakologie und Toxikologie, 10117 Berlin, Germany;
| | - Alfonso Carvajal
- Centro de Estudios sobre la Seguridad de los Medicamentos, Universidad de Valladolid, 47005 Valladolid, Spain;
| | - Maria Isabel Lucena
- Servicio Farmacologia Clinica, Instituto de Investigación Biomedica de Málaga, Hospital Universitario Virgen de la Victoria, Universidad de Málaga, 29010 Málaga, Spain;
| | - Javier Martin
- Instituto de Parasitología y Biomedicina Lopez-Neyra, Consejo Superior de Investigaciones Cientiíficas, 18016 Granada, Spain;
| | - Esther Sancho Ponce
- Servei d’Hematologia i Banc de Sang, Hospital General de Catalunya, 08190 Sant Cugat del Vallès, Spain;
| | - Mariam Molokhia
- Department of Population Health Sciences, King’s College London, London WC2R 2LS, UK;
| | - Niclas Eriksson
- Uppsala Clinical Research Center and Department of Medical Sciences, Uppsala University, 751 85 Uppsala, Sweden;
| | | | - Stephan Krähenbühl
- Department of Clinical Pharmacology & Toxicology, University Hospital Basel, University of Basel, 4031 Basel, Switzerland; (D.R.); (S.K.)
| | - Carlo R. Largiadèr
- Department of Clinical Chemistry, Inselspital Bern University Hospital, University of Bern, 3010 Bern, Switzerland; (A.L.C.); (C.R.L.)
| | - Manuel Haschke
- Department of Clinical Pharmacology & Toxicology, Inselspital Bern University Hospital, University of Bern, 3010 Bern, Switzerland; (E.L.); (M.H.)
- Institute of Pharmacology, University of Bern, 3012 Bern, Switzerland
| | - Pär Hallberg
- Department of Medical Sciences, Clinical Pharmacology and Science for Life Laboratory, Uppsala University, 751 85 Uppsala, Sweden; (P.H.); (M.W.)
| | - Mia Wadelius
- Department of Medical Sciences, Clinical Pharmacology and Science for Life Laboratory, Uppsala University, 751 85 Uppsala, Sweden; (P.H.); (M.W.)
| | - Ursula Amstutz
- Department of Clinical Chemistry, Inselspital Bern University Hospital, University of Bern, 3010 Bern, Switzerland; (A.L.C.); (C.R.L.)
- Correspondence:
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9
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Ulrich A, Otero-Núñez P, Wharton J, Swietlik EM, Gräf S, Morrell NW, Wang D, Lawrie A, Wilkins MR, Prokopenko I, Rhodes CJ. Expression Quantitative Trait Locus Mapping in Pulmonary Arterial Hypertension. Genes (Basel) 2020; 11:E1247. [PMID: 33105808 PMCID: PMC7690609 DOI: 10.3390/genes11111247] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2020] [Revised: 10/14/2020] [Accepted: 10/21/2020] [Indexed: 12/21/2022] Open
Abstract
Expression quantitative trait loci (eQTL) can provide a link between disease susceptibility variants discovered by genetic association studies and biology. To date, eQTL mapping studies have been primarily conducted in healthy individuals from population-based cohorts. Genetic effects have been known to be context-specific and vary with changing environmental stimuli. We conducted a transcriptome- and genome-wide eQTL mapping study in a cohort of patients with idiopathic or heritable pulmonary arterial hypertension (PAH) using RNA sequencing (RNAseq) data from whole blood. We sought confirmation from three published population-based eQTL studies, including the GTEx Project, and followed up potentially novel eQTL not observed in the general population. In total, we identified 2314 eQTL of which 90% were cis-acting and 75% were confirmed by at least one of the published studies. While we observed a higher GWAS trait colocalization rate among confirmed eQTL, colocalisation rate of novel eQTL reported for lung-related phenotypes was twice as high as that of confirmed eQTL. Functional enrichment analysis of genes with novel eQTL in PAH highlighted immune-related processes, a suspected contributor to PAH. These potentially novel eQTL specific to or active in PAH could be useful in understanding genetic risk factors for other diseases that share common mechanisms with PAH.
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Affiliation(s)
- Anna Ulrich
- National Heart and Lung Institute, Hammersmith Campus, Imperial College London, London SW7 2BU, UK; (A.U.); (P.O.-N.); (J.W.); (M.R.W.)
| | - Pablo Otero-Núñez
- National Heart and Lung Institute, Hammersmith Campus, Imperial College London, London SW7 2BU, UK; (A.U.); (P.O.-N.); (J.W.); (M.R.W.)
| | - John Wharton
- National Heart and Lung Institute, Hammersmith Campus, Imperial College London, London SW7 2BU, UK; (A.U.); (P.O.-N.); (J.W.); (M.R.W.)
| | - Emilia M. Swietlik
- Department of Medicine, University of Cambridge, Cambridge CB2 3AX, UK; (E.M.S.); (S.G.); (N.W.M.)
- Pulmonary Vascular Disease Unit, Royal Papworth Hospital NHS Foundation Trust, Cambridge CB2 0AY, UK
| | - Stefan Gräf
- Department of Medicine, University of Cambridge, Cambridge CB2 3AX, UK; (E.M.S.); (S.G.); (N.W.M.)
- NIHR BioResource-Rare Diseases, Cambridge, CB2 0QQ, UK
- Department of Haematology, University of Cambridge, Cambridge CB2 3AX, UK
| | - Nicholas W. Morrell
- Department of Medicine, University of Cambridge, Cambridge CB2 3AX, UK; (E.M.S.); (S.G.); (N.W.M.)
- NIHR BioResource-Rare Diseases, Cambridge, CB2 0QQ, UK
| | - Dennis Wang
- Sheffield Institute for Translational Neuroscience, University of Sheffield, Sheffield S10 2TN, UK;
- Sheffield Bioinformatics Core, University of Sheffield, Sheffield S10 2TN, UK
| | - Allan Lawrie
- Department of Infection, Immunity & Cardiovascular Disease, University of Sheffield, Sheffield S10 2TN, UK;
| | - Martin R. Wilkins
- National Heart and Lung Institute, Hammersmith Campus, Imperial College London, London SW7 2BU, UK; (A.U.); (P.O.-N.); (J.W.); (M.R.W.)
| | - Inga Prokopenko
- Department of Clinical and Experimental Medicine, University of Surrey, Guildford GU2 7XH, UK;
- Department of Metabolism, Digestion and Reproduction, Imperial College London, London SW7 2BU, UK
| | - Christopher J. Rhodes
- National Heart and Lung Institute, Hammersmith Campus, Imperial College London, London SW7 2BU, UK; (A.U.); (P.O.-N.); (J.W.); (M.R.W.)
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10
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Abstract
Structured models of ontogenic, phenotypic and functional diversity have been instrumental for a renewed understanding of the biology of immune cells, such as macrophages and lymphoid cells. However, there are no established models that can be used to define the diversity of neutrophils, the most abundant myeloid cells. This lack of an established model is largely due to the uniquely short lives of neutrophils, a consequence of their inability to divide once terminally differentiated, which has been perceived as a roadblock to functional diversity. This perception is rapidly evolving as multiple phenotypic and functional variants of neutrophils have been found, both in homeostatic and disease conditions. In this Opinion article, we present an overview of neutrophil heterogeneity and discuss possible mechanisms of diversification, including genomic regulation. We suggest that neutrophil heterogeneity is an important feature of immune pathophysiology, such that co-option of the mechanisms of diversification by cancer or other disorders contributes to disease progression.
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11
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Abstract
Leprosy is a chronic infectious disease of the skin and peripheral nerves that presents a strong link with the host genetic background. Different approaches in genetic studies have been applied to leprosy and today leprosy is among the infectious diseases with the greatest number of genetic risk variants identified. Several leprosy genes have been implicated in host immune response to pathogens and point to specific pathways that are relevant for host defense to infection. In addition, host genetic factors are also involved in the heterogeneity of leprosy clinical manifestations and in excessive inflammatory responses that occur in some leprosy patients. Finally, genetic studies in leprosy have provided strong evidence of pleiotropic effects between leprosy and other complex diseases, such as immune-mediated or neurodegenerative diseases. These findings not only impact on the field of leprosy and infectious diseases but also make leprosy a good model for the study of complex immune-mediated diseases. Here, we summarize recent genetic findings in leprosy susceptibility and discuss the overlap of the genetic control in leprosy with Parkinson's disease and inflammatory bowel disease. Moreover, some limitations, challenges, and potential new avenues for future genetics studies of leprosy are also discussed in this review.
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12
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Du Z, Ma L, Qu H, Chen W, Zhang B, Lu X, Zhai W, Sheng X, Sun Y, Li W, Lei M, Qi Q, Yuan N, Shi S, Zeng J, Wang J, Yang Y, Liu Q, Hong Y, Dong L, Zhang Z, Zou D, Wang Y, Song S, Liu F, Fang X, Chen H, Liu X, Xiao J, Zeng C. Whole Genome Analyses of Chinese Population and De Novo Assembly of A Northern Han Genome. GENOMICS PROTEOMICS & BIOINFORMATICS 2019; 17:229-247. [PMID: 31494266 PMCID: PMC6818495 DOI: 10.1016/j.gpb.2019.07.002] [Citation(s) in RCA: 34] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/09/2019] [Revised: 07/07/2019] [Accepted: 08/07/2019] [Indexed: 12/20/2022]
Abstract
To unravel the genetic mechanisms of disease and physiological traits, it requires comprehensive sequencing analysis of large sample size in Chinese populations. Here, we report the primary results of the Chinese Academy of Sciences Precision Medicine Initiative (CASPMI) project launched by the Chinese Academy of Sciences, including the de novo assembly of a northern Han reference genome (NH1.0) and whole genome analyses of 597 healthy people coming from most areas in China. Given the two existing reference genomes for Han Chinese (YH and HX1) were both from the south, we constructed NH1.0, a new reference genome from a northern individual, by combining the sequencing strategies of PacBio, 10× Genomics, and Bionano mapping. Using this integrated approach, we obtained an N50 scaffold size of 46.63 Mb for the NH1.0 genome and performed a comparative genome analysis of NH1.0 with YH and HX1. In order to generate a genomic variation map of Chinese populations, we performed the whole-genome sequencing of 597 participants and identified 24.85 million (M) single nucleotide variants (SNVs), 3.85 M small indels, and 106,382 structural variations. In the association analysis with collected phenotypes, we found that the T allele of rs1549293 in KAT8 significantly correlated with the waist circumference in northern Han males. Moreover, significant genetic diversity in MTHFR, TCN2, FADS1, and FADS2, which associate with circulating folate, vitamin B12, or lipid metabolism, was observed between northerners and southerners. Especially, for the homocysteine-increasing allele of rs1801133 (MTHFR 677T), we hypothesize that there exists a "comfort" zone for a high frequency of 677T between latitudes of 35-45 degree North. Taken together, our results provide a high-quality northern Han reference genome and novel population-specific data sets of genetic variants for use in the personalized and precision medicine.
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Affiliation(s)
- Zhenglin Du
- Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China; BIG Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China
| | - Liang Ma
- Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China; CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China
| | - Hongzhu Qu
- Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China; CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China
| | - Wei Chen
- Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China; CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China
| | - Bing Zhang
- Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China
| | - Xi Lu
- Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China
| | - Weibo Zhai
- Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China
| | - Xin Sheng
- Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China; BIG Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China
| | - Yongqiao Sun
- Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China
| | - Wenjie Li
- Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China
| | - Meng Lei
- Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China
| | - Qiuhui Qi
- Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China
| | - Na Yuan
- Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China; BIG Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China
| | - Shuo Shi
- Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China; BIG Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China
| | - Jingyao Zeng
- Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China; BIG Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China
| | - Jinyue Wang
- Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China; BIG Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China
| | - Yadong Yang
- Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China; CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China
| | - Qi Liu
- Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China; CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China
| | - Yaqiang Hong
- Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China; CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China
| | - Lili Dong
- Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China; BIG Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China
| | - Zhewen Zhang
- Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China; BIG Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China
| | - Dong Zou
- Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China; BIG Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China
| | - Yanqing Wang
- Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China; BIG Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China
| | - Shuhui Song
- Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China; BIG Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China
| | - Fan Liu
- Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China; CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Xiangdong Fang
- Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China; CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Hua Chen
- Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China; CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Xin Liu
- Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China; CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Jingfa Xiao
- Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China; BIG Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China.
| | - Changqing Zeng
- Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China; CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China.
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13
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Identification of Potential Transcriptional Biomarkers Differently Expressed in Both S. aureus- and E. coli-Induced Sepsis via Integrated Analysis. BIOMED RESEARCH INTERNATIONAL 2019; 2019:2487921. [PMID: 31093495 PMCID: PMC6481126 DOI: 10.1155/2019/2487921] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/04/2018] [Revised: 02/13/2019] [Accepted: 03/25/2019] [Indexed: 01/13/2023]
Abstract
Sepsis is a critical, complex medical condition, and the major causative pathogens of sepsis are both Staphylococcus aureus (S. aureus) and Escherichia coli (E. coli). Genome-wide studies identify differentially expressed genes for sepsis. However, the results for the identification of DEGs are inconsistent or discrepant among different studies because of heterogeneity of specimen sources, various data processing methods, or different backgrounds of the samples. To identify potential transcriptional biomarkers that are differently expressed in S. aureus- and E. coli-induced sepsis, we have analyzed four microarray datasets from GEO database and integrated results with bioinformatics tools. 42 and 54 DEGs were identified in both S. aureus and E. coli samples from any three different arrays, respectively. Hierarchical clustering revealed dramatic differences between control and sepsis samples. GO functional annotations suggested that DEGs in the S. aureus group were mainly involved in the responses of both defense and immune regulation, but DEGs in the E. coli group were mainly related to the regulation of endopeptidase activity involved in the apoptotic signaling pathway. Although KEGG showed inflammatory bowel disease in the E. coli group, the KEGG pathway analysis showed that these DEGs were mainly involved in the tumor necrosis factor signaling pathway, fructose metabolism, and mannose metabolism in both S. aureus- and E. coli-induced sepsis. Eight common genes were identified between sepsis patients with either S. aureus or E. coli infection and controls in this study. All the candidate genes were further validated to be differentially expressed by an ex-vivo human blood model, and the relative expression of these genes was performed by qPCR. The qPCR results suggest that GK and PFKFB3 might contribute to the progression of S. aureus-induced sepsis, and CEACAM1, TNFAIP6, PSTPIP2, SOCS3, and IL18RAP might be closely linked with E. coli-induced sepsis. These results provide new viewpoints for the pathogenesis of both sepsis and pathogen identification.
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14
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Jonkers IH, Wijmenga C. Context-specific effects of genetic variants associated with autoimmune disease. Hum Mol Genet 2017; 26:R185-R192. [PMID: 28977443 PMCID: PMC5886469 DOI: 10.1093/hmg/ddx254] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2017] [Revised: 06/27/2017] [Accepted: 06/29/2017] [Indexed: 12/22/2022] Open
Abstract
Autoimmune diseases such as rheumatoid arthritis and coeliac disease are typical examples of complex genetic diseases caused by a combination of genetic and non-genetic risk factors. Insight into the genetic risk factors (single nucleotide polymorphisms (SNPs)) has increased since genome-wide association studies (GWAS) became possible in 2007 and, for individual diseases, SNPs can now explain some 15-50% of genetic risk. GWAS have also shown that some 50% of the genetic risk factors for individual autoimmune diseases overlap between different diseases. Thus, shared risk factors may converge to pathways that, when perturbed by genetic variation, predispose to autoimmunity in general. This raises the question of what determines disease specificity, and suggests that identical risk factors may have different effects in various autoimmune diseases. Addressing this question requires translation of genetic risk factors to causal genes and then to molecular and cellular pathways. Since >90% of the genetic risk factors are found in the non-coding part of the genome (i.e. outside the exons of protein-coding genes) and can have an impact on gene regulation, there is an urgent need to better understand the non-coding part of the genome. Here, we will outline the methods being used to unravel the gene regulatory networks perturbed in autoimmune diseases and the importance of doing this in the relevant cell types. We will highlight findings in coeliac disease, which manifests in the small intestine, to demonstrate how cell type and disease context can impact on the consequences of genetic risk factors.
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Affiliation(s)
- Iris H. Jonkers
- Department of Genetics, University Medical Centre Groningen, University of Groningen, 9700 RB Groningen, The Netherlands
| | - Cisca Wijmenga
- Department of Genetics, University Medical Centre Groningen, University of Groningen, 9700 RB Groningen, The Netherlands
- Department of Immunology, K.G. Jebsen Coeliac Disease Research Centre, University of Oslo, 0424 Oslo, Norway
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15
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Sundar IK, Yin Q, Baier BS, Yan L, Mazur W, Li D, Susiarjo M, Rahman I. DNA methylation profiling in peripheral lung tissues of smokers and patients with COPD. Clin Epigenetics 2017; 9:38. [PMID: 28416970 PMCID: PMC5391602 DOI: 10.1186/s13148-017-0335-5] [Citation(s) in RCA: 60] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2016] [Accepted: 03/29/2017] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND Epigenetics changes have been shown to be affected by cigarette smoking. Cigarette smoke (CS)-mediated DNA methylation can potentially affect several cellular and pathophysiological processes, acute exacerbations, and comorbidity in the lungs of patients with chronic obstructive pulmonary disease (COPD). We sought to determine whether genome-wide lung DNA methylation profiles of smokers and patients with COPD were significantly different from non-smokers. We isolated DNA from parenchymal lung tissues of patients including eight lifelong non-smokers, eight current smokers, and eight patients with COPD and analyzed the samples using Illumina's Infinium HumanMethylation450 BeadChip. RESULTS Our data revealed that the differentially methylated genes were related to top canonical pathways (e.g., G beta gamma signaling, mechanisms of cancer, and nNOS signaling in neurons), disease and disorders (organismal injury and abnormalities, cancer, and respiratory disease), and molecular and cellular functions (cell death and survival, cellular assembly and organization, cellular function and maintenance) in patients with COPD. The genome-wide DNA methylation analysis identified suggestive genes, such as NOS1AP, TNFAIP2, BID, GABRB1, ATXN7, and THOC7 with DNA methylation changes in COPD lung tissues that were further validated by pyrosequencing. Pyrosequencing validation confirmed hyper-methylation in smokers and patients with COPD as compared to non-smokers. However, we did not detect significant differences in DNA methylation for TNFAIP2, ATXN7, and THOC7 genes in smokers and COPD groups despite the changes observed in the genome-wide analysis. CONCLUSIONS Our study suggests that DNA methylation in suggestive genes, such as NOS1AP, BID, and GABRB1 may be used as epigenetic signatures in smokers and patients with COPD if the same is validated in a larger cohort. Future studies are required to correlate DNA methylation status with transcriptomics of selective genes identified in this study and elucidate their role and involvement in the progression of COPD and its exacerbations.
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Affiliation(s)
- Isaac K Sundar
- Department of Environmental Medicine, University of Rochester Medical Center, Box 850, 601 Elmwood Avenue, Rochester, 14642 NY USA
| | - Qiangzong Yin
- Department of Environmental Medicine, University of Rochester Medical Center, Box 850, 601 Elmwood Avenue, Rochester, 14642 NY USA
| | - Brian S Baier
- Department of Environmental Medicine, University of Rochester Medical Center, Box 850, 601 Elmwood Avenue, Rochester, 14642 NY USA
| | - Li Yan
- Department of Biostatistics and Bioinformatics, Roswell Park Cancer Institute, Buffalo, NY USA
| | - Witold Mazur
- Heart and Lung Center, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - Dongmei Li
- Department of Clinical & Translational Research, University of Rochester Medical Center, Rochester, NY USA
| | - Martha Susiarjo
- Department of Environmental Medicine, University of Rochester Medical Center, Box 850, 601 Elmwood Avenue, Rochester, 14642 NY USA
| | - Irfan Rahman
- Department of Environmental Medicine, University of Rochester Medical Center, Box 850, 601 Elmwood Avenue, Rochester, 14642 NY USA
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16
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Zhernakova DV, Deelen P, Vermaat M, van Iterson M, van Galen M, Arindrarto W, van 't Hof P, Mei H, van Dijk F, Westra HJ, Bonder MJ, van Rooij J, Verkerk M, Jhamai PM, Moed M, Kielbasa SM, Bot J, Nooren I, Pool R, van Dongen J, Hottenga JJ, Stehouwer CDA, van der Kallen CJH, Schalkwijk CG, Zhernakova A, Li Y, Tigchelaar EF, de Klein N, Beekman M, Deelen J, van Heemst D, van den Berg LH, Hofman A, Uitterlinden AG, van Greevenbroek MMJ, Veldink JH, Boomsma DI, van Duijn CM, Wijmenga C, Slagboom PE, Swertz MA, Isaacs A, van Meurs JBJ, Jansen R, Heijmans BT, 't Hoen PAC, Franke L. Identification of context-dependent expression quantitative trait loci in whole blood. Nat Genet 2016; 49:139-145. [PMID: 27918533 DOI: 10.1038/ng.3737] [Citation(s) in RCA: 275] [Impact Index Per Article: 30.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2015] [Accepted: 11/02/2016] [Indexed: 02/07/2023]
Abstract
Genetic risk factors often localize to noncoding regions of the genome with unknown effects on disease etiology. Expression quantitative trait loci (eQTLs) help to explain the regulatory mechanisms underlying these genetic associations. Knowledge of the context that determines the nature and strength of eQTLs may help identify cell types relevant to pathophysiology and the regulatory networks underlying disease. Here we generated peripheral blood RNA-seq data from 2,116 unrelated individuals and systematically identified context-dependent eQTLs using a hypothesis-free strategy that does not require previous knowledge of the identity of the modifiers. Of the 23,060 significant cis-regulated genes (false discovery rate (FDR) ≤ 0.05), 2,743 (12%) showed context-dependent eQTL effects. The majority of these effects were influenced by cell type composition. A set of 145 cis-eQTLs depended on type I interferon signaling. Others were modulated by specific transcription factors binding to the eQTL SNPs.
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Affiliation(s)
- Daria V Zhernakova
- University of Groningen, University Medical Center Groningen, Genomics Coordination Center, Groningen, the Netherlands
| | - Patrick Deelen
- University of Groningen, University Medical Center Groningen, Genomics Coordination Center, Groningen, the Netherlands.,University of Groningen, University Medical Center Groningen, Department of Genetics, Groningen, the Netherlands
| | - Martijn Vermaat
- Department of Human Genetics, Leiden University Medical Center, Leiden, the Netherlands
| | - Maarten van Iterson
- Molecular Epidemiology Section, Department of Medical Statistics and Bioinformatics, Leiden University Medical Center, Leiden, the Netherlands
| | - Michiel van Galen
- Department of Human Genetics, Leiden University Medical Center, Leiden, the Netherlands
| | - Wibowo Arindrarto
- Sequence Analysis Support Core, Leiden University Medical Center, Leiden, the Netherlands
| | - Peter van 't Hof
- Sequence Analysis Support Core, Leiden University Medical Center, Leiden, the Netherlands
| | - Hailiang Mei
- Sequence Analysis Support Core, Leiden University Medical Center, Leiden, the Netherlands
| | - Freerk van Dijk
- University of Groningen, University Medical Center Groningen, Genomics Coordination Center, Groningen, the Netherlands.,University of Groningen, University Medical Center Groningen, Department of Genetics, Groningen, the Netherlands
| | - Harm-Jan Westra
- Divisions of Genetics and Rheumatology, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA.,Partners Center for Personalized Genetic Medicine, Boston, Massachusetts, USA.,Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
| | - Marc Jan Bonder
- University of Groningen, University Medical Center Groningen, Genomics Coordination Center, Groningen, the Netherlands
| | - Jeroen van Rooij
- Department of Internal Medicine, ErasmusMC, Rotterdam, the Netherlands
| | - Marijn Verkerk
- Department of Internal Medicine, ErasmusMC, Rotterdam, the Netherlands
| | - P Mila Jhamai
- Department of Internal Medicine, ErasmusMC, Rotterdam, the Netherlands
| | - Matthijs Moed
- Molecular Epidemiology Section, Department of Medical Statistics and Bioinformatics, Leiden University Medical Center, Leiden, the Netherlands
| | - Szymon M Kielbasa
- Molecular Epidemiology Section, Department of Medical Statistics and Bioinformatics, Leiden University Medical Center, Leiden, the Netherlands
| | - Jan Bot
- SURFsara, Amsterdam, the Netherlands
| | | | - René Pool
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Neuroscience Campus Amsterdam, Amsterdam, the Netherlands
| | - Jenny van Dongen
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Neuroscience Campus Amsterdam, Amsterdam, the Netherlands
| | - Jouke J Hottenga
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Neuroscience Campus Amsterdam, Amsterdam, the Netherlands
| | - Coen D A Stehouwer
- Department of Internal Medicine, Maastricht University Medical Center, Maastricht, the Netherlands.,School for Cardiovascular Diseases (CARIM), Maastricht University Medical Center, Maastricht, the Netherlands
| | - Carla J H van der Kallen
- Department of Internal Medicine, Maastricht University Medical Center, Maastricht, the Netherlands.,School for Cardiovascular Diseases (CARIM), Maastricht University Medical Center, Maastricht, the Netherlands
| | - Casper G Schalkwijk
- Department of Internal Medicine, Maastricht University Medical Center, Maastricht, the Netherlands.,School for Cardiovascular Diseases (CARIM), Maastricht University Medical Center, Maastricht, the Netherlands
| | - Alexandra Zhernakova
- University of Groningen, University Medical Center Groningen, Genomics Coordination Center, Groningen, the Netherlands
| | - Yang Li
- University of Groningen, University Medical Center Groningen, Genomics Coordination Center, Groningen, the Netherlands
| | - Ettje F Tigchelaar
- University of Groningen, University Medical Center Groningen, Genomics Coordination Center, Groningen, the Netherlands
| | - Niek de Klein
- University of Groningen, University Medical Center Groningen, Genomics Coordination Center, Groningen, the Netherlands
| | - Marian Beekman
- Molecular Epidemiology Section, Department of Medical Statistics and Bioinformatics, Leiden University Medical Center, Leiden, the Netherlands
| | - Joris Deelen
- Molecular Epidemiology Section, Department of Medical Statistics and Bioinformatics, Leiden University Medical Center, Leiden, the Netherlands
| | - Diana van Heemst
- Department of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, the Netherlands
| | - Leonard H van den Berg
- Department of Neurology, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Albert Hofman
- Department of Epidemiology, ErasmusMC, Rotterdam, the Netherlands
| | | | - Marleen M J van Greevenbroek
- Department of Internal Medicine, Maastricht University Medical Center, Maastricht, the Netherlands.,School for Cardiovascular Diseases (CARIM), Maastricht University Medical Center, Maastricht, the Netherlands
| | - Jan H Veldink
- Department of Neurology, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Dorret I Boomsma
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Neuroscience Campus Amsterdam, Amsterdam, the Netherlands
| | - Cornelia M van Duijn
- Genetic Epidemiology Unit, Department of Epidemiology, ErasmusMC, Rotterdam, the Netherlands
| | - Cisca Wijmenga
- University of Groningen, University Medical Center Groningen, Genomics Coordination Center, Groningen, the Netherlands
| | - P Eline Slagboom
- Molecular Epidemiology Section, Department of Medical Statistics and Bioinformatics, Leiden University Medical Center, Leiden, the Netherlands
| | - Morris A Swertz
- University of Groningen, University Medical Center Groningen, Genomics Coordination Center, Groningen, the Netherlands.,University of Groningen, University Medical Center Groningen, Department of Genetics, Groningen, the Netherlands
| | - Aaron Isaacs
- School for Cardiovascular Diseases (CARIM), Maastricht University Medical Center, Maastricht, the Netherlands.,Genetic Epidemiology Unit, Department of Epidemiology, ErasmusMC, Rotterdam, the Netherlands.,Maastricht Centre for Systems Biology (MaCSBio), Maastricht University, Maastricht, the Netherlands
| | | | - Rick Jansen
- Department of Psychiatry, VU University Medical Center, Neuroscience Campus Amsterdam, Amsterdam, the Netherlands
| | - Bastiaan T Heijmans
- Molecular Epidemiology Section, Department of Medical Statistics and Bioinformatics, Leiden University Medical Center, Leiden, the Netherlands
| | - Peter A C 't Hoen
- Department of Human Genetics, Leiden University Medical Center, Leiden, the Netherlands
| | - Lude Franke
- University of Groningen, University Medical Center Groningen, Genomics Coordination Center, Groningen, the Netherlands
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17
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Bearoff F, Del Rio R, Case LK, Dragon JA, Nguyen-Vu T, Lin CY, Blankenhorn EP, Teuscher C, Krementsov DN. Natural genetic variation profoundly regulates gene expression in immune cells and dictates susceptibility to CNS autoimmunity. Genes Immun 2016; 17:386-395. [PMID: 27653816 PMCID: PMC5133152 DOI: 10.1038/gene.2016.37] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2016] [Revised: 08/15/2016] [Accepted: 08/18/2016] [Indexed: 02/08/2023]
Abstract
Regulation of gene expression in immune cells is known to be under genetic control, and likely contributes to susceptibility to autoimmune diseases such as multiple sclerosis (MS). How this occurs in concert across multiple immune cell types is poorly understood. Using a mouse model that harnesses the genetic diversity of wild-derived mice, more accurately reflecting genetically diverse human populations, we provide an extensive characterization of the genetic regulation of gene expression in five different naive immune cell types relevant to MS. The immune cell transcriptome is shown to be under profound genetic control, exhibiting diverse patterns: global, cell-specific and sex-specific. Bioinformatic analysis of the genetically controlled transcript networks reveals reduced cell type specificity and inflammatory activity in wild-derived PWD/PhJ mice, compared with the conventional laboratory strain C57BL/6J. Additionally, candidate MS-GWAS (genome-wide association study candidate genes for MS susceptibility) genes were significantly enriched among transcripts overrepresented in C57BL/6J cells compared with PWD. These expression level differences correlate with robust differences in susceptibility to experimental autoimmune encephalomyelitis, the principal model of MS, and skewing of the encephalitogenic T-cell responses. Taken together, our results provide functional insights into the genetic regulation of the immune transcriptome, and shed light on how this in turn contributes to susceptibility to autoimmune disease.
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Affiliation(s)
- F Bearoff
- Department of Microbiology and Immunology, Drexel University College of Medicine, Philadelphia, PA, USA
| | - R Del Rio
- Department of Medicine, University of Vermont, Burlington, VT, USA
| | - L K Case
- The Jackson Laboratory, Bar Harbor, ME, USA
| | - J A Dragon
- Department of Microbiology and Molecular Genetics, University of Vermont, Burlington, VT, USA
| | - T Nguyen-Vu
- Center for Nuclear Receptors and Cell Signaling, Department of Biology and Biochemistry, University of Houston, Houston, TX, USA
| | - C-Y Lin
- Center for Nuclear Receptors and Cell Signaling, Department of Biology and Biochemistry, University of Houston, Houston, TX, USA
| | - E P Blankenhorn
- Department of Microbiology and Immunology, Drexel University College of Medicine, Philadelphia, PA, USA
| | - C Teuscher
- Department of Medicine, University of Vermont, Burlington, VT, USA
- Department of Pathology, University of Vermont, Burlington, VT, USA
| | - D N Krementsov
- Department of Medicine, University of Vermont, Burlington, VT, USA
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18
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Tan H, Deng B, Yu H, Yang Y, Ding L, Zhang Q, Qin J, Kijlstra A, Chen R, Yang P. Genetic analysis of innate immunity in Behcet's disease identifies an association with IL-37 and IL-18RAP. Sci Rep 2016; 6:35802. [PMID: 27775096 PMCID: PMC5075872 DOI: 10.1038/srep35802] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2016] [Accepted: 10/03/2016] [Indexed: 01/20/2023] Open
Abstract
Interleukin-1 (IL-1) and the IL-1 receptor (IL-1R) family play an important role in the pathogenesis of inflammatory diseases. This study aimed to investigate the association between single nucleotide polymorphisms (SNP) of IL-1 and IL-1R family genes with Vogt-Koyanagi-Harada (VKH) and Behcet’s disease (BD) in Han Chinese. The case-control study was divided into two stages and included 419 VKH cases, 1063 BD cases and 1872 healthy controls. The MassARRAY platform (Sequenom), iPLEX Gold Assay and TaqMan SNP assays were used to score genotypes of 24 SNPs. The expression of IL-37 and IL-18Rap was measured by ELISA and real-time PCR in genotyped healthy individuals. A significantly lower frequency of the AG genotype, and a higher frequency of the GG genotype and G allele of IL-37/rs3811047 were observed in BD as compared to controls. AA genotype and A allele frequency of IL-18RAP/rs2058660 was significantly decreased in BD as compared to controls. Functional studies performed in healthy controls showed that rs3811047 AG genotype carriers had a higher IL-37 gene expression in peripheral blood mononuclear cells (PBMCs) than GG carriers. GG carriers showed a higher cytokine expression as compared to AG carriers. No association was detected between the tested SNPs and VKH.
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Affiliation(s)
- Handan Tan
- The First Affiliated Hospital of Chongqing Medical University, Chongqing Key Laboratory of Ophthalmology and Chongqing Eye Institute, Chongqing, P. R. China
| | - Bolin Deng
- The First Affiliated Hospital of Chongqing Medical University, Chongqing Key Laboratory of Ophthalmology and Chongqing Eye Institute, Chongqing, P. R. China
| | - Hongsong Yu
- The First Affiliated Hospital of Chongqing Medical University, Chongqing Key Laboratory of Ophthalmology and Chongqing Eye Institute, Chongqing, P. R. China
| | - Yi Yang
- The First Affiliated Hospital of Chongqing Medical University, Chongqing Key Laboratory of Ophthalmology and Chongqing Eye Institute, Chongqing, P. R. China
| | - Lin Ding
- The First Affiliated Hospital of Chongqing Medical University, Chongqing Key Laboratory of Ophthalmology and Chongqing Eye Institute, Chongqing, P. R. China
| | - Qi Zhang
- The First Affiliated Hospital of Chongqing Medical University, Chongqing Key Laboratory of Ophthalmology and Chongqing Eye Institute, Chongqing, P. R. China
| | - Jieying Qin
- The First Affiliated Hospital of Chongqing Medical University, Chongqing Key Laboratory of Ophthalmology and Chongqing Eye Institute, Chongqing, P. R. China
| | - Aize Kijlstra
- University Eye Clinic Maastricht, Maastricht, Limburg, the Netherlands
| | - Rui Chen
- Department of Molecular and Human Genetics, Human Genome Sequencing Center, Structural and Computational Biology and Molecular Biophysics Graduate Program, The Verna and Marrs Mclean Department of Biochemistry and Molecular Biology and Program in Developmental Biology, Baylor College of Medicine, Houston, USA
| | - Peizeng Yang
- The First Affiliated Hospital of Chongqing Medical University, Chongqing Key Laboratory of Ophthalmology and Chongqing Eye Institute, Chongqing, P. R. China
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19
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Peloquin JM, Goel G, Kong L, Huang H, Haritunians T, Sartor RB, Daly MJ, Newberry RD, McGovern DP, Yajnik V, Lira SA, Xavier RJ. Characterization of candidate genes in inflammatory bowel disease-associated risk loci. JCI Insight 2016; 1:e87899. [PMID: 27668286 DOI: 10.1172/jci.insight.87899] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022] Open
Abstract
GWAS have linked SNPs to risk of inflammatory bowel disease (IBD), but a systematic characterization of disease-associated genes has been lacking. Prior studies utilized microarrays that did not capture many genes encoded within risk loci or defined expression quantitative trait loci (eQTLs) using peripheral blood, which is not the target tissue in IBD. To address these gaps, we sought to characterize the expression of IBD-associated risk genes in disease-relevant tissues and in the setting of active IBD. Terminal ileal (TI) and colonic mucosal tissues were obtained from patients with Crohn's disease or ulcerative colitis and from healthy controls. We developed a NanoString code set to profile 678 genes within IBD risk loci. A subset of patients and controls were genotyped for IBD-associated risk SNPs. Analyses included differential expression and variance analysis, weighted gene coexpression network analysis, and eQTL analysis. We identified 116 genes that discriminate between healthy TI and colon samples and uncovered patterns in variance of gene expression that highlight heterogeneity of disease. We identified 107 coexpressed gene pairs for which transcriptional regulation is either conserved or reversed in an inflammation-independent or -dependent manner. We demonstrate that on average approximately 60% of disease-associated genes are differentially expressed in inflamed tissue. Last, we identified eQTLs with either genotype-only effects on expression or an interaction effect between genotype and inflammation. Our data reinforce tissue specificity of expression in disease-associated candidate genes, highlight genes and gene pairs that are regulated in disease-relevant tissue and inflammation, and provide a foundation to advance the understanding of IBD pathogenesis.
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Affiliation(s)
- Joanna M Peloquin
- Gastrointestinal Unit and Center for the Study of Inflammatory Bowel Disease.,Center for Computational and Integrative Biology
| | - Gautam Goel
- Gastrointestinal Unit and Center for the Study of Inflammatory Bowel Disease.,Center for Computational and Integrative Biology
| | - Lingjia Kong
- Gastrointestinal Unit and Center for the Study of Inflammatory Bowel Disease.,Center for Computational and Integrative Biology
| | - Hailiang Huang
- Analytic and Translational Genetics Unit, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA.,Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
| | - Talin Haritunians
- F. Widjaja Foundation Inflammatory Bowel and Immunobiology Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA
| | - R Balfour Sartor
- Department of Medicine, Center for Gastrointestinal Biology and Disease, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Mark J Daly
- Analytic and Translational Genetics Unit, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA.,Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
| | - Rodney D Newberry
- Department of Internal Medicine, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Dermot P McGovern
- F. Widjaja Foundation Inflammatory Bowel and Immunobiology Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA
| | - Vijay Yajnik
- Gastrointestinal Unit and Center for the Study of Inflammatory Bowel Disease
| | - Sergio A Lira
- Immunology Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Ramnik J Xavier
- Gastrointestinal Unit and Center for the Study of Inflammatory Bowel Disease.,Center for Computational and Integrative Biology.,Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
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20
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Fine-mapping analysis revealed complex pleiotropic effect and tissue-specific regulatory mechanism of TNFSF15 in primary biliary cholangitis, Crohn's disease and leprosy. Sci Rep 2016; 6:31429. [PMID: 27507062 PMCID: PMC4979016 DOI: 10.1038/srep31429] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2016] [Accepted: 07/18/2016] [Indexed: 12/17/2022] Open
Abstract
Genetic polymorphism within the 9q32 locus is linked with increased risk of several diseases, including Crohn’s disease (CD), primary biliary cholangitis (PBC) and leprosy. The most likely disease-causing gene within 9q32 is TNFSF15, which encodes the pro-inflammatory cytokine TNF super-family member 15, but it was unknown whether these disparate diseases were associated with the same genetic variance in 9q32, and how variance within this locus might contribute to pathology. Using genetic data from published studies on CD, PBC and leprosy we revealed that bearing a T allele at rs6478108/rs6478109 (r2 = 1) or rs4979462 was significantly associated with increased risk of CD and decreased risk of leprosy, while the T allele at rs4979462 was associated with significantly increased risk of PBC. In vitro analyses showed that the rs6478109 genotype significantly affected TNFSF15 expression in cells from whole blood of controls, while functional annotation using publicly-available data revealed the broad cell type/tissue-specific regulatory potential of variance at rs6478109 or rs4979462. In summary, we provide evidence that variance within TNFSF15 has the potential to affect cytokine expression across a range of tissues and thereby contribute to protection from infectious diseases such as leprosy, while increasing the risk of immune-mediated diseases including CD and PBC.
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21
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Simarmata D, Ng DCE, Kam YW, Lee B, Sum MSH, Her Z, Chow A, Leo YS, Cardosa J, Perera D, Ooi MH, Ng LFP. Early clearance of Chikungunya virus in children is associated with a strong innate immune response. Sci Rep 2016; 6:26097. [PMID: 27180811 PMCID: PMC4867653 DOI: 10.1038/srep26097] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2016] [Accepted: 04/25/2016] [Indexed: 02/07/2023] Open
Abstract
Chikungunya fever (CHIKF) is a global infectious disease which can affect a wide range of age groups. The pathological and immunological response upon Chikungunya virus (CHIKV) infection have been reported over the last few years. However, the clinical profile and immune response upon CHIKV infection in children remain largely unknown. In this study, we analyzed the clinical and immunological response, focusing on the cytokine/chemokine profile in a CHIKV-infected pediatric cohort from Sarawak, Malaysia. Unique immune mediators triggered upon CHIKV infection were identified through meta-analysis of the immune signatures between this pediatric group and cohorts from previous outbreaks. The data generated from this study revealed that a broad spectrum of cytokines/chemokines is up-regulated in a sub-group of virus-infected children stratified according to their viremic status during hospitalization. Furthermore, different immune mediator profiles (the levels of pro-inflammatory cytokines, chemokines and growth and other factors) were observed between children and adults. This study gives an important insight to understand the immune response of CHIKV infection in children and would aid in the development of better prognostics and clinical management for children.
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Affiliation(s)
- Diane Simarmata
- Singapore Immunology Network, Agency for Science, Technology and Research (A*STAR), Singapore 138648, Singapore
| | - David Chun Ern Ng
- Department of Paediatrics, Sarawak General Hospital, Kuching 93587, Sarawak, Malaysia
| | - Yiu-Wing Kam
- Singapore Immunology Network, Agency for Science, Technology and Research (A*STAR), Singapore 138648, Singapore
| | - Bernett Lee
- Singapore Immunology Network, Agency for Science, Technology and Research (A*STAR), Singapore 138648, Singapore
| | - Magdline Sia Henry Sum
- Institute of Health &Community Medicine, Universiti Malaysia Sarawak (UNIMAS), Kota Samarahan 94300, Malaysia
| | - Zhisheng Her
- Singapore Immunology Network, Agency for Science, Technology and Research (A*STAR), Singapore 138648, Singapore
| | - Angela Chow
- Institute of Infectious Disease and Epidemiology (IIDE), Tan Tock Seng Hospital, Singapore 308433, Singapore
| | - Yee-Sin Leo
- Institute of Infectious Disease and Epidemiology (IIDE), Tan Tock Seng Hospital, Singapore 308433, Singapore
| | - Jane Cardosa
- Institute of Health &Community Medicine, Universiti Malaysia Sarawak (UNIMAS), Kota Samarahan 94300, Malaysia
| | - David Perera
- Institute of Health &Community Medicine, Universiti Malaysia Sarawak (UNIMAS), Kota Samarahan 94300, Malaysia
| | - Mong H Ooi
- Department of Paediatrics, Sarawak General Hospital, Kuching 93587, Sarawak, Malaysia.,Institute of Health &Community Medicine, Universiti Malaysia Sarawak (UNIMAS), Kota Samarahan 94300, Malaysia.,Department of Paediatrics, Sibu Hospital, Sibu 96000, Malaysia
| | - Lisa F P Ng
- Singapore Immunology Network, Agency for Science, Technology and Research (A*STAR), Singapore 138648, Singapore
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22
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Zhong L, Li H, Li Z, Shi B, Wang P, Wang C, Fan J, Sun H, Wang P, Qin X, Peng Z. C7 genotype of the donor may predict early bacterial infection after liver transplantation. Sci Rep 2016; 6:24121. [PMID: 27063552 PMCID: PMC4827091 DOI: 10.1038/srep24121] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2015] [Accepted: 03/14/2016] [Indexed: 01/27/2023] Open
Abstract
Post-transplantation infection causes high mortality and remains a significant challenge. High clinical risk factors for bacterial infection in recipients are often found in critically ill patients. However, for some recipients, bacterial infections are inevitable. It is conceivable that this susceptibility may be related to the genetics of the donor and recipient. Using expression quantitative trait loci (eQTL) analysis, we found that the C7 rs6876739 CC genotypes and mannan-binding lectin (MBL2) gene polymorphisms of liver donors were significantly associated with bacterial infection in recipients. In an extended validation group of 113 patients, donor C7 rs6876739 genetic variation was an independent risk factor for bacterial infection. The donor C7 rs6876739 CC genotype was associated with lower levels of recipient C7 protein, soluble membrane attack complex (MAC), and IL-1β expression compared with the donor C7 rs6876739 TT genotype. In vitro, the MAC significantly triggered NLRP3 inflammasome activation and IL-1β release, suggesting that the mechanism by which C7 defends against bacteria may involve MAC formation, leading to NLRP3 inflammasome activation and IL-1β release. Our findings may be helpful in identifying transplantation recipients at risk of bacterial infection prior to surgery and may contribute to novel infection prevention strategies and the improvement of postoperative outcomes.
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Affiliation(s)
- Lin Zhong
- Department of General Surgery, Shanghai Jiao Tong University Affiliated First People's Hospital, 85 Wu Jing Road, 200080, China
| | - Hao Li
- Department of General Surgery, Shanghai Jiao Tong University Affiliated First People's Hospital, 85 Wu Jing Road, 200080, China
| | - Zhiqiang Li
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Shanghai Jiao Tong University, Shanghai, China
| | - Baojie Shi
- Department of General Surgery, Shanghai Jiao Tong University Affiliated First People's Hospital, 85 Wu Jing Road, 200080, China
| | - PuSen Wang
- Department of General Surgery, Shanghai Jiao Tong University Affiliated First People's Hospital, 85 Wu Jing Road, 200080, China
| | - ChunGuang Wang
- Department of General Surgery, Shanghai Jiao Tong University Affiliated First People's Hospital, 85 Wu Jing Road, 200080, China
| | - Junwei Fan
- Department of General Surgery, Shanghai Jiao Tong University Affiliated First People's Hospital, 85 Wu Jing Road, 200080, China
| | - Hongcheng Sun
- Department of General Surgery, Shanghai Jiao Tong University Affiliated First People's Hospital, 85 Wu Jing Road, 200080, China
| | - Peiwen Wang
- Department of Gastroenterology, Shanghai Jiao Tong University Affiliated First People's Hospital, 85 Wu Jing Road, 200080, China
| | - Xuebin Qin
- Department of Neuroscience, Temple University School of Medicine, Philadelphia, PA 19140, USA
| | - Zhihai Peng
- Department of General Surgery, Shanghai Jiao Tong University Affiliated First People's Hospital, 85 Wu Jing Road, 200080, China
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