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Fernandes SJ, Ericsson M, Khademi M, Jagodic M, Olsson T, Gomez-Cabrero D, Kockum I, Tegnér J. Deep characterization of paired chromatin and transcriptomes in four immune cell types from multiple sclerosis patients. Epigenomics 2021; 13:1607-1618. [PMID: 34676774 DOI: 10.2217/epi-2021-0205] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
Abstract
Background: The putative involvement of chromatin states in multiple sclerosis (MS) is thus far unclear. Here we determined the association of chromatin-accessibility with concurrent genetic, epigenetic and transcriptional events. Material & methods: We generated paired assay for transposase-accessible chromatin sequencing and RNA-sequencing profiles from sorted blood immune CD4+ and CD8+ T cells, CD14+ monocytes and CD19+ B cells from healthy controls (HCs) and MS patients. Results: We identified differentially accessible regions between MS patients and HCs, primarily in CD4+ and CD19+. CD4+ regions were enriched for MS-associated single nucleotide polymorphisms and differentially methylated loci. In the vicinity of differentially accessible regions of CD4+ cells, 42 differentially expressed genes were identified. The top two dysregulated genes identified in this multilayer analysis were CCDC114 and SERTAD1. Conclusion: These findings provide new insight into the primary role of CD4+ and CD19+ cells in MS.
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Affiliation(s)
- Sunjay Jude Fernandes
- Unit of Computational Medicine, Department of Medicine, Solna, Center for Molecular Medicine, Karolinska Institutet, Stockholm, 17165, Sweden.,Science for Life Laboratory, Solna, Stockholm, 17165, Sweden.,Department of Clinical Neuroscience, Center for Molecular Medicine, Karolinska Institutet, Karolinska University Hospital, Stockholm, 17165, Sweden
| | - Matilda Ericsson
- Unit of Computational Medicine, Department of Medicine, Solna, Center for Molecular Medicine, Karolinska Institutet, Stockholm, 17165, Sweden.,Science for Life Laboratory, Solna, Stockholm, 17165, Sweden
| | - Mohsen Khademi
- Department of Clinical Neuroscience, Center for Molecular Medicine, Karolinska Institutet, Karolinska University Hospital, Stockholm, 17165, Sweden
| | - Maja Jagodic
- Department of Clinical Neuroscience, Center for Molecular Medicine, Karolinska Institutet, Karolinska University Hospital, Stockholm, 17165, Sweden
| | - Tomas Olsson
- Department of Clinical Neuroscience, Center for Molecular Medicine, Karolinska Institutet, Karolinska University Hospital, Stockholm, 17165, Sweden
| | - David Gomez-Cabrero
- Unit of Computational Medicine, Department of Medicine, Solna, Center for Molecular Medicine, Karolinska Institutet, Stockholm, 17165, Sweden.,Science for Life Laboratory, Solna, Stockholm, 17165, Sweden.,Mucosal & Salivary Biology Division, King's College London Dental Institute, London, SE1 9RT, UK.,Translational Bioinformatics Unit, Navarrabiomed, Complejo Hospitalario de Navarra (CHN), Universidad Pública de Navarra (UPNA), IdiSNA, Pamplona, Spain.,Biological & Environmental Sciences & Engineering Division, Computer, Electrical & Mathematical Sciences & Engineering Division, King Abdullah University of Science & Technology, Thuwal, Kingdom of Saudi Arabia
| | - Ingrid Kockum
- Department of Clinical Neuroscience, Center for Molecular Medicine, Karolinska Institutet, Karolinska University Hospital, Stockholm, 17165, Sweden
| | - Jesper Tegnér
- Unit of Computational Medicine, Department of Medicine, Solna, Center for Molecular Medicine, Karolinska Institutet, Stockholm, 17165, Sweden.,Science for Life Laboratory, Solna, Stockholm, 17165, Sweden.,Biological & Environmental Sciences & Engineering Division, Computer, Electrical & Mathematical Sciences & Engineering Division, King Abdullah University of Science & Technology, Thuwal, Kingdom of Saudi Arabia
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2
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Gresle MM, Jordan MA, Stankovich J, Spelman T, Johnson LJ, Laverick L, Hamlett A, Smith LD, Jokubaitis VG, Baker J, Haartsen J, Taylor B, Charlesworth J, Bahlo M, Speed TP, Brown MA, Field J, Baxter AG, Butzkueven H. Multiple sclerosis risk variants regulate gene expression in innate and adaptive immune cells. Life Sci Alliance 2020; 3:3/7/e202000650. [PMID: 32518073 PMCID: PMC7283543 DOI: 10.26508/lsa.202000650] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2020] [Revised: 05/27/2020] [Accepted: 05/28/2020] [Indexed: 12/20/2022] Open
Abstract
At least 200 single-nucleotide polymorphisms (SNPs) are associated with multiple sclerosis (MS) risk. A key function that could mediate SNP-encoded MS risk is their regulatory effects on gene expression. We performed microarrays using RNA extracted from purified immune cell types from 73 untreated MS cases and 97 healthy controls and then performed Cis expression quantitative trait loci mapping studies using additive linear models. We describe MS risk expression quantitative trait loci associations for 129 distinct genes. By extending these models to include an interaction term between genotype and phenotype, we identify MS risk SNPs with opposing effects on gene expression in cases compared with controls, namely, rs2256814 MYT1 in CD4 cells (q = 0.05) and rs12087340 RF00136 in monocyte cells (q = 0.04). The rs703842 SNP was also associated with a differential effect size on the expression of the METTL21B gene in CD8 cells of MS cases relative to controls (q = 0.03). Our study provides a detailed map of MS risk loci that function by regulating gene expression in cell types relevant to MS.
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Affiliation(s)
- Melissa M Gresle
- Department of Medicine, University of Melbourne, Parkville, Australia.,Melbourne Brain Centre, Royal Melbourne Hospital, University of Melbourne, Parkville, Australia.,Department of Neuroscience, Central Clinical School, Monash University, Melbourne, Australia
| | - Margaret A Jordan
- Molecular & Cell Biology, James Cook University, Townsville, Australia
| | - Jim Stankovich
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, Australia
| | - Tim Spelman
- Department of Medicine, University of Melbourne, Parkville, Australia.,Department of Clinical Neuroscience, Karolinska Institute, Stockholm, Sweden
| | - Laura J Johnson
- Florey Institutes of Neuroscience and Mental Health, Parkville, Australia
| | - Louise Laverick
- Department of Medicine, University of Melbourne, Parkville, Australia
| | - Alison Hamlett
- Florey Institutes of Neuroscience and Mental Health, Parkville, Australia
| | - Letitia D Smith
- Molecular & Cell Biology, James Cook University, Townsville, Australia
| | - Vilija G Jokubaitis
- Department of Medicine, University of Melbourne, Parkville, Australia.,Department of Neuroscience, Central Clinical School, Monash University, Melbourne, Australia
| | - Josephine Baker
- Multiple Sclerosis Clinical & Research Unit, Melbourne Health, Royal Melbourne Hospital, Parkville, Australia
| | - Jodi Haartsen
- Eastern Clinical Research Unit, Eastern Health, Box Hill, Australia
| | - Bruce Taylor
- Menzies Institute for Medical Research, University of Tasmania, Hobart, Australia
| | - Jac Charlesworth
- Menzies Institute for Medical Research, University of Tasmania, Hobart, Australia
| | - Melanie Bahlo
- Population Health and Immunity Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, Australia.,Department of Medical Biology, The University of Melbourne, Parkville, Australia
| | - Terence P Speed
- Bioinformatics Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, Australia
| | - Matthew A Brown
- Institute of Health and Biomedical Innovation, Queensland University of Technology, Translational Research Institute, Woolloongabba, Australia.,Guy's and St Thomas' NHS Foundation Trust and King's College London NIHR Biomedical Research Centre, London, England
| | - Judith Field
- Florey Institutes of Neuroscience and Mental Health, Parkville, Australia
| | - Alan G Baxter
- Molecular & Cell Biology, James Cook University, Townsville, Australia
| | - Helmut Butzkueven
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, Australia
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3
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Kreiner E, Waage J, Standl M, Brix S, Pers TH, Couto Alves A, Warrington NM, Tiesler CMT, Fuertes E, Franke L, Hirschhorn JN, James A, Simpson A, Tung JY, Koppelman GH, Postma DS, Pennell CE, Jarvelin MR, Custovic A, Timpson N, Ferreira MA, Strachan DP, Henderson J, Hinds D, Bisgaard H, Bønnelykke K. Shared genetic variants suggest common pathways in allergy and autoimmune diseases. J Allergy Clin Immunol 2017; 140:771-781. [PMID: 28188724 DOI: 10.1016/j.jaci.2016.10.055] [Citation(s) in RCA: 47] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2016] [Revised: 09/12/2016] [Accepted: 10/11/2016] [Indexed: 01/06/2023]
Abstract
BACKGROUND The relationship between allergy and autoimmune disorders is complex and poorly understood. OBJECTIVE We sought to investigate commonalities in genetic loci and pathways between allergy and autoimmune diseases to elucidate shared disease mechanisms. METHODS We meta-analyzed 2 genome-wide association studies on self-reported allergy and sensitization comprising a total of 62,330 subjects. These results were used to calculate enrichment for single nucleotide polymorphisms (SNPs) previously associated with autoimmune diseases. Furthermore, we probed for enrichment within genetic pathways and of transcription factor binding sites and characterized commonalities in variant burden on tissue-specific regulatory sites by calculating the enrichment of allergy SNPs falling in gene regulatory regions in various cells using Encode Roadmap DNase-hypersensitive site data. Finally, we compared the allergy data with those of all known diseases. RESULTS Among 290 loci previously associated with 16 autoimmune diseases, we found a significant enrichment of loci also associated with allergy (P = 1.4e-17) encompassing 29 loci at a false discovery rate of less than 0.05. Such enrichment seemed to be a general characteristic for autoimmune diseases. Among the common loci, 48% had the same direction of effect for allergy and autoimmune diseases. Additionally, we observed an enrichment of allergy SNPs falling within immune pathways and regions of chromatin accessible in immune cells that was also represented in patients with autoimmune diseases but not those with other diseases. CONCLUSION We identified shared susceptibility loci and commonalities in pathways between allergy and autoimmune diseases, suggesting shared disease mechanisms. Further studies of these shared genetic mechanisms might help in understanding the complex relationship between these diseases, including the parallel increase in disease prevalence.
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Affiliation(s)
- Eskil Kreiner
- COPSAC, Copenhagen Prospective Studies on Asthma in Childhood, Herlev and Gentofte Hospital, University of Copenhagen, Copenhagen, Denmark
| | - Johannes Waage
- COPSAC, Copenhagen Prospective Studies on Asthma in Childhood, Herlev and Gentofte Hospital, University of Copenhagen, Copenhagen, Denmark
| | - Marie Standl
- Institute of Epidemiology I, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Susanne Brix
- The Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen, Denmark
| | - Tune H Pers
- The Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen, Denmark; Division of Endocrinology and Center for Basic and Translational Obesity Research, Boston Children's Hospital, Boston, Mass; Medical and Population Genetics Program, Broad Institute of MIT and Harvard, Cambridge, Mass; Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark
| | - Alexessander Couto Alves
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom
| | - Nicole M Warrington
- University of Queensland Diamantina Institute, University of Queensland, Translational Research Institute, Brisbane, Australia; School of Women's and Infants' Health, University of Western Australia, Perth, Australia
| | - Carla M T Tiesler
- Institute of Epidemiology I, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany; Ludwig-Maximilians-Universität of Munich, Dr. von Hauner Children's Hospital, Munich, Germany
| | - Elaine Fuertes
- Institute of Epidemiology I, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Lude Franke
- Department of Genetics, University of Groningen, University Medical Centre Groningen, Groningen, The Netherlands
| | - Joel N Hirschhorn
- Division of Endocrinology and Center for Basic and Translational Obesity Research, Boston Children's Hospital, Boston, Mass; Medical and Population Genetics Program, Broad Institute of MIT and Harvard, Cambridge, Mass; Department of Genetics, Harvard Medical School, Boston, Mass
| | - Alan James
- Busselton Population Medical Research Foundation, Sir Charles Gairdner Hospital, Perth, Australia; School of Medicine and Pharmacology, University of West Australia, Nedlands, Australia; Department of Pulmonary Physiology, West Australian Sleep Disorders Research Institute, Nedlands, Australia
| | - Angela Simpson
- University of Manchester, Manchester Academic Health Science Centre, University Hospital of South Manchester NHS Foundation Trust, Manchester, United Kingdom
| | | | - Gerard H Koppelman
- University of Groningen, University Medical Center Groningen, Department of Pediatric Pulmonology and Pediatric Allergology, Beatrix Children's Hospital, GRIAC Research Institute, Groningen, The Netherlands
| | - Dirkje S Postma
- University of Groningen, University Medical Center Groningen, Department Pulmonary Medicine and Tuberculosis, GRIAC Research Institute, Groningen, The Netherlands
| | - Craig E Pennell
- School of Women's and Infants' Health, University of Western Australia, Perth, Australia
| | - Marjo-Riitta Jarvelin
- Department of Epidemiology and Biostatistics, MRC Health Protection Agency (HPA) Centre for Environment and Health, School of Public Health, Imperial College London, London, United Kingdom; Center for Life Course Epidemiology, Faculty of Medicine, University of Oulu, Oulu, Finland; Biocenter Oulu, University of Oulu, Oulu, Finland; Unit of Primary Care, Oulu University Hospital, Oulu, Finland; Department of Children and Young People and Families, National Institute for Health and Welfare, Oulu, Finland
| | - Adnan Custovic
- University of Manchester, Manchester Academic Health Science Centre, University Hospital of South Manchester NHS Foundation Trust, Manchester, United Kingdom
| | - Nicholas Timpson
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
| | | | - David P Strachan
- Population Health Research Institute, St George's, University of London, London, United Kingdom
| | - John Henderson
- School of Social and Community Medicine, University of Bristol, Bristol, United Kingdom
| | | | - Hans Bisgaard
- COPSAC, Copenhagen Prospective Studies on Asthma in Childhood, Herlev and Gentofte Hospital, University of Copenhagen, Copenhagen, Denmark.
| | - Klaus Bønnelykke
- COPSAC, Copenhagen Prospective Studies on Asthma in Childhood, Herlev and Gentofte Hospital, University of Copenhagen, Copenhagen, Denmark
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Abstract
Schizophrenia is a major psychiatric disorder that lacks a unifying neuropathology, while currently available pharmacological treatments provide only limited benefits to many patients. This review will discuss how the field of neuroepigenetics could contribute to advancements of the existing knowledge on the neurobiology and treatment of psychosis. Genome-scale mapping of DMA methylation, histone modifications and variants, and chromosomal loopings for promoter-enhancer interactions and other epigenetic determinants of genome organization and function are likely to provide important clues about mechanisms contributing to dysregulated expression of synaptic and metabolic genes in schizophrenia brain, including the potential links to the underlying genetic risk architecture and environmental exposures. In addition, studies in animal models are providing a rapidly increasing list of chromatin-regulatory mechanisms with significant effects on cognition and complex behaviors, thereby pointing to the therapeutic potential of epigenetic drug targets in the nervous system.
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Affiliation(s)
- Schahram Akbarian
- Department of Psychiatry, Friedman Brain Institute Icahn School of Medicine at Mount Sinai, New York, USA
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5
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Polymorphisms of the CD24 Gene Are Associated with Risk of Multiple Sclerosis: A Meta-Analysis. Int J Mol Sci 2015; 16:12368-81. [PMID: 26039238 PMCID: PMC4490449 DOI: 10.3390/ijms160612368] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2015] [Revised: 05/22/2015] [Accepted: 05/27/2015] [Indexed: 11/17/2022] Open
Abstract
CD24 is a cell-surface protein mainly expressed in cells of the immune and central nervous system (CNS), cells that play a critical role in the development of multiple sclerosis (MS). In the current study, we investigated four polymorphisms of the CD24 gene regarding their associations with MS. To this end, univariate and multivariate meta-analysis were applied along with modifications to include data from family-trios so as to increase the robustness of the meta-analysis. We found that the polymorphism 226 C>T (Ala57Val) of the CD24 gene is associated with MS according to the recessive mode of inheritance (odds ratio = 1.75; 95% CI: 1.09, 2.81). Moreover, the 1527–1528 TG>del polymorphism is inversely associated with MS according to the dominant mode of inheritance (odds ratio = 0.57; 95% CI 0.39, 0.83). Conversely, the 1056 A>G and 1626 A>G polymorphisms were not found to be associated with MS. We conclude that the CD24 226 C>T polymorphism increases the risk of MS, while the 1527–1528 TG>del polymorphism seems to have a protective role against MS, suggesting that these two polymorphisms can be used as predictive biomarkers for MS development.
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6
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Swindell WR, Sarkar MK, Stuart PE, Voorhees JJ, Elder JT, Johnston A, Gudjonsson JE. Psoriasis drug development and GWAS interpretation through in silico analysis of transcription factor binding sites. Clin Transl Med 2015; 4:13. [PMID: 25883770 PMCID: PMC4392043 DOI: 10.1186/s40169-015-0054-5] [Citation(s) in RCA: 40] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2014] [Accepted: 02/26/2015] [Indexed: 12/22/2022] Open
Abstract
Background Psoriasis is a cytokine-mediated skin disease that can be treated effectively with immunosuppressive biologic agents. These medications, however, are not equally effective in all patients and are poorly suited for treating mild psoriasis. To develop more targeted therapies, interfering with transcription factor (TF) activity is a promising strategy. Methods Meta-analysis was used to identify differentially expressed genes (DEGs) in the lesional skin from psoriasis patients (n = 237). We compiled a dictionary of 2935 binding sites representing empirically-determined binding affinities of TFs and unconventional DNA-binding proteins (uDBPs). This dictionary was screened to identify “psoriasis response elements” (PREs) overrepresented in sequences upstream of psoriasis DEGs. Results PREs are recognized by IRF1, ISGF3, NF-kappaB and multiple TFs with helix-turn-helix (homeo) or other all-alpha-helical (high-mobility group) DNA-binding domains. We identified a limited set of DEGs that encode proteins interacting with PRE motifs, including TFs (GATA3, EHF, FOXM1, SOX5) and uDBPs (AVEN, RBM8A, GPAM, WISP2). PREs were prominent within enhancer regions near cytokine-encoding DEGs (IL17A, IL19 and IL1B), suggesting that PREs might be incorporated into complex decoy oligonucleotides (cdODNs). To illustrate this idea, we designed a cdODN to concomitantly target psoriasis-activated TFs (i.e., FOXM1, ISGF3, IRF1 and NF-kappaB). Finally, we screened psoriasis-associated SNPs to identify risk alleles that disrupt or engender PRE motifs. This identified possible sites of allele-specific TF/uDBP binding and showed that PREs are disproportionately disrupted by psoriasis risk alleles. Conclusions We identified new TF/uDBP candidates and developed an approach that (i) connects transcriptome informatics to cdODN drug development and (ii) enhances our ability to interpret GWAS findings. Disruption of PRE motifs by psoriasis risk alleles may contribute to disease susceptibility. Electronic supplementary material The online version of this article (doi:10.1186/s40169-015-0054-5) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- William R Swindell
- Department of Dermatology, University of Michigan School of Medicine, Ann Arbor, MI 48109-2200 USA
| | - Mrinal K Sarkar
- Department of Dermatology, University of Michigan School of Medicine, Ann Arbor, MI 48109-2200 USA
| | - Philip E Stuart
- Department of Dermatology, University of Michigan School of Medicine, Ann Arbor, MI 48109-2200 USA
| | - John J Voorhees
- Department of Dermatology, University of Michigan School of Medicine, Ann Arbor, MI 48109-2200 USA
| | - James T Elder
- Department of Dermatology, University of Michigan School of Medicine, Ann Arbor, MI 48109-2200 USA
| | - Andrew Johnston
- Department of Dermatology, University of Michigan School of Medicine, Ann Arbor, MI 48109-2200 USA
| | - Johann E Gudjonsson
- Department of Dermatology, University of Michigan School of Medicine, Ann Arbor, MI 48109-2200 USA
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