Function of multiple sclerosis-protective HLA class I alleles revealed by genome-wide protein-quantitative trait loci mapping of interferon signalling
Autoři:
Christian Lundtoft aff001; Pascal Pucholt aff001; Juliana Imgenberg-Kreuz aff001; Jonas Carlsson-Almlöf aff002; Maija-Leena Eloranta aff001; Ann-Christine Syvänen aff002; Gunnel Nordmark aff001; Johanna K. Sandling aff001; Ingrid Kockum aff003; Tomas Olsson aff003; Lars Rönnblom aff001; Niklas Hagberg aff001
Působiště autorů:
Rheumatology and Science for Life Laboratories, Department of Medical Sciences, Uppsala University, Uppsala, Sweden
aff001; Molecular Medicine and Science for Life Laboratory, Department of Medical Sciences, Uppsala University, Uppsala, Sweden
aff002; Centre for Molecular Medicine, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
aff003
Vyšlo v časopise:
Function of multiple sclerosis-protective HLA class I alleles revealed by genome-wide protein-quantitative trait loci mapping of interferon signalling. PLoS Genet 16(10): e1009199. doi:10.1371/journal.pgen.1009199
Kategorie:
Research Article
doi:
https://doi.org/10.1371/journal.pgen.1009199
Souhrn
Interferons (IFNs) are cytokines that are central to the host defence against viruses and other microorganisms. If not properly regulated, IFNs may contribute to the pathogenesis of inflammatory autoimmune, or infectious diseases. To identify genetic polymorphisms regulating the IFN system we performed an unbiased genome-wide protein-quantitative trait loci (pQTL) mapping of cell-type specific type I and type II IFN receptor levels and their responses in immune cells from 303 healthy individuals. Seven genome-wide significant (p < 5.0E-8) pQTLs were identified. Two independent SNPs that tagged the multiple sclerosis (MS)-protective HLA class I alleles A*02/A*68 and B*44, respectively, were associated with increased levels of IFNAR2 in B and T cells, with the most prominent effect in IgD–CD27+ memory B cells. The increased IFNAR2 levels in B cells were replicated in cells from an independent set of healthy individuals and in MS patients. Despite increased IFNAR2 levels, B and T cells carrying the MS-protective alleles displayed a reduced response to type I IFN stimulation. Expression and methylation-QTL analysis demonstrated increased mRNA expression of the pseudogene HLA-J in B cells carrying the MS-protective class I alleles, possibly driven via methylation-dependent transcriptional regulation. Together these data suggest that the MS-protective effects of HLA class I alleles are unrelated to their antigen-presenting function, and propose a previously unappreciated function of type I IFN signalling in B and T cells in MS immune-pathogenesis.
Klíčová slova:
B cells – Flow cytometry – Gene expression – Immune cells – Interferons – NK cells – Single nucleotide polymorphisms – T cells
Zdroje
1. Trinchieri G. Type I interferon: friend or foe? J Exp Med. 2010;207(10):2053–63. doi: 10.1084/jem.20101664 20837696
2. Ivashkiv LB. IFNgamma: signalling, epigenetics and roles in immunity, metabolism, disease and cancer immunotherapy. Nat Rev Immunol. 2018;18(9):545–58. doi: 10.1038/s41577-018-0029-z 29921905
3. Crow MK, Rönnblom L. Type I interferons in host defence and inflammatory diseases. Lupus Sci Med. 2019;6(1):e000336. doi: 10.1136/lupus-2019-000336 31205729
4. Hagberg N, Rönnblom L. Systemic Lupus Erythematosus—A Disease with A Dysregulated Type I Interferon System. Scand J Immunol. 2015;82(3):199–207. doi: 10.1111/sji.12330 26099519
5. Rusinova I, Forster S, Yu S, Kannan A, Masse M, Cumming H, et al. Interferome v2.0: an updated database of annotated interferon-regulated genes. Nucleic Acids Res. 2013;41(Database issue):D1040–6. doi: 10.1093/nar/gks1215 23203888
6. Buniello A, MacArthur JAL, Cerezo M, Harris LW, Hayhurst J, Malangone C, et al. The NHGRI-EBI GWAS Catalog of published genome-wide association studies, targeted arrays and summary statistics 2019. Nucleic Acids Res. 2019;47(D1):D1005–D12. doi: 10.1093/nar/gky1120 30445434
7. Bronson PG, Chaivorapol C, Ortmann W, Behrens TW, Graham RR. The genetics of type I interferon in systemic lupus erythematosus. Curr Opin Immunol. 2012;24(5):530–7. doi: 10.1016/j.coi.2012.07.008 22889593
8. Fairfax BP, Humburg P, Makino S, Naranbhai V, Wong D, Lau E, et al. Innate immune activity conditions the effect of regulatory variants upon monocyte gene expression. Science. 2014;343(6175):1246949. doi: 10.1126/science.1246949 24604202
9. Lee MN, Ye C, Villani AC, Raj T, Li W, Eisenhaure TM, et al. Common genetic variants modulate pathogen-sensing responses in human dendritic cells. Science. 2014;343(6175):1246980. doi: 10.1126/science.1246980 24604203
10. Dimas AS, Deutsch S, Stranger BE, Montgomery SB, Borel C, Attar-Cohen H, et al. Common regulatory variation impacts gene expression in a cell type-dependent manner. Science. 2009;325(5945):1246–50. doi: 10.1126/science.1174148 19644074
11. Naranbhai V, Fairfax BP, Makino S, Humburg P, Wong D, Ng E, et al. Genomic modulators of gene expression in human neutrophils. Nat Commun. 2015;6:7545. doi: 10.1038/ncomms8545 26151758
12. Kim-Hellmuth S, Bechheim M, Putz B, Mohammadi P, Nedelec Y, Giangreco N, et al. Genetic regulatory effects modified by immune activation contribute to autoimmune disease associations. Nat Commun. 2017;8(1):266. doi: 10.1038/s41467-017-00366-1 28814792
13. Liu Y, Beyer A, Aebersold R. On the Dependency of Cellular Protein Levels on mRNA Abundance. Cell. 2016;165(3):535–50. doi: 10.1016/j.cell.2016.03.014 27104977
14. Orru V, Steri M, Sole G, Sidore C, Virdis F, Dei M, et al. Genetic variants regulating immune cell levels in health and disease. Cell. 2013;155(1):242–56. doi: 10.1016/j.cell.2013.08.041 24074872
15. Roederer M, Quaye L, Mangino M, Beddall MH, Mahnke Y, Chattopadhyay P, et al. The genetic architecture of the human immune system: a bioresource for autoimmunity and disease pathogenesis. Cell. 2015;161(2):387–403. doi: 10.1016/j.cell.2015.02.046 25772697
16. Aguirre-Gamboa R, Joosten I, Urbano PCM, van der Molen RG, van Rijssen E, van Cranenbroek B, et al. Differential Effects of Environmental and Genetic Factors on T and B Cell Immune Traits. Cell Rep. 2016;17(9):2474–87. doi: 10.1016/j.celrep.2016.10.053 27818087
17. Patin E, Hasan M, Bergstedt J, Rouilly V, Libri V, Urrutia A, et al. Natural variation in the parameters of innate immune cells is preferentially driven by genetic factors. Nat Immunol. 2018;19(3):302–14. doi: 10.1038/s41590-018-0049-7 29476184
18. Sun BB, Maranville JC, Peters JE, Stacey D, Staley JR, Blackshaw J, et al. Genomic atlas of the human plasma proteome. Nature. 2018;558(7708):73–9. doi: 10.1038/s41586-018-0175-2 29875488
19. Yao C, Chen G, Song C, Keefe J, Mendelson M, Huan T, et al. Genome-wide mapping of plasma protein QTLs identifies putatively causal genes and pathways for cardiovascular disease. Nat Commun. 2018;9(1):3268. doi: 10.1038/s41467-018-05512-x 30111768
20. Lagou V, Garcia-Perez JE, Smets I, Van Horebeek L, Vandebergh M, Chen L, et al. Genetic Architecture of Adaptive Immune System Identifies Key Immune Regulators. Cell Rep. 2018;25(3):798–810 e6. doi: 10.1016/j.celrep.2018.09.048 30332657
21. Li Y, Oosting M, Deelen P, Ricano-Ponce I, Smeekens S, Jaeger M, et al. Inter-individual variability and genetic influences on cytokine responses to bacteria and fungi. Nat Med. 2016;22(8):952–60. doi: 10.1038/nm.4139 27376574
22. Li Y, Oosting M, Smeekens SP, Jaeger M, Aguirre-Gamboa R, Le KTT, et al. A Functional Genomics Approach to Understand Variation in Cytokine Production in Humans. Cell. 2016;167(4):1099–110 e14. doi: 10.1016/j.cell.2016.10.017 27814507
23. Bentham J, Morris DL, Graham DSC, Pinder CL, Tombleson P, Behrens TW, et al. Genetic association analyses implicate aberrant regulation of innate and adaptive immunity genes in the pathogenesis of systemic lupus erythematosus. Nat Genet. 2015;47(12):1457–64. doi: 10.1038/ng.3434 26502338
24. McGovern DP, Gardet A, Torkvist L, Goyette P, Essers J, Taylor KD, et al. Genome-wide association identifies multiple ulcerative colitis susceptibility loci. Nat Genet. 2010;42(4):332–7. doi: 10.1038/ng.549 20228799
25. Khor CC, Davila S, Breunis WB, Lee YC, Shimizu C, Wright VJ, et al. Genome-wide association study identifies FCGR2A as a susceptibility locus for Kawasaki disease. Nat Genet. 2011;43(12):1241–6. doi: 10.1038/ng.981 22081228
26. van der Pol W, van de Winkel JG. IgG receptor polymorphisms: risk factors for disease. Immunogenetics. 1998;48(3):222–32. doi: 10.1007/s002510050426 9683667
27. Westra HJ, Peters MJ, Esko T, Yaghootkar H, Schurmann C, Kettunen J, et al. Systematic identification of trans eQTLs as putative drivers of known disease associations. Nature Genetics. 2013;45(10):1238–U195. doi: 10.1038/ng.2756 24013639
28. International Multiple Sclerosis Genetics C, Wellcome Trust Case Control C, Sawcer S, Hellenthal G, Pirinen M, Spencer CC, et al. Genetic risk and a primary role for cell-mediated immune mechanisms in multiple sclerosis. Nature. 2011;476(7359):214–9. doi: 10.1038/nature10251 21833088
29. De Jager PL, Jia X, Wang J, de Bakker PI, Ottoboni L, Aggarwal NT, et al. Meta-analysis of genome scans and replication identify CD6, IRF8 and TNFRSF1A as new multiple sclerosis susceptibility loci. Nat Genet. 2009;41(7):776–82. doi: 10.1038/ng.401 19525953
30. Moutsianas L, Jostins L, Beecham AH, Dilthey AT, Xifara DK, Ban M, et al. Class II HLA interactions modulate genetic risk for multiple sclerosis. Nat Genet. 2015;47(10):1107–13. doi: 10.1038/ng.3395 26343388
31. Lutfalla G, Holland SJ, Cinato E, Monneron D, Reboul J, Rogers NC, et al. Mutant U5A cells are complemented by an interferon-alpha beta receptor subunit generated by alternative processing of a new member of a cytokine receptor gene cluster. EMBO J. 1995;14(20):5100–8. 7588638
32. Fairfax BP, Makino S, Radhakrishnan J, Plant K, Leslie S, Dilthey A, et al. Genetics of gene expression in primary immune cells identifies cell type-specific master regulators and roles of HLA alleles. Nat Genet. 2012;44(5):502–10. doi: 10.1038/ng.2205 22446964
33. Lappalainen T, Sammeth M, Friedlander MR, t Hoen PA, Monlong J, Rivas MA, et al. Transcriptome and genome sequencing uncovers functional variation in humans. Nature. 2013;501(7468):506–11. doi: 10.1038/nature12531 24037378
34. Chick JM, Munger SC, Simecek P, Huttlin EL, Choi K, Gatti DM, et al. Defining the consequences of genetic variation on a proteome-wide scale. Nature. 2016;534(7608):500–5. doi: 10.1038/nature18270 27309819
35. Imgenberg-Kreuz J, Sandling JK, Almlöf JC, Nordlund J, Signer L, Norheim KB, et al. Genome-wide DNA methylation analysis in multiple tissues in primary Sjogren's syndrome reveals regulatory effects at interferon-induced genes. Ann Rheum Dis. 2016;75(11):2029–36. doi: 10.1136/annrheumdis-2015-208659 26857698
36. Olsson T, Barcellos LF, Alfredsson L. Interactions between genetic, lifestyle and environmental risk factors for multiple sclerosis. Nat Rev Neurol. 2017;13(1):25–36. doi: 10.1038/nrneurol.2016.187 27934854
37. Friese MA, Fugger L. Pathogenic CD8(+) T cells in multiple sclerosis. Ann Neurol. 2009;66(2):132–41. doi: 10.1002/ana.21744 19743458
38. Mustafa M, Vingsbo C, Olsson T, Ljungdahl A, Hojeberg B, Holmdahl R. The major histocompatibility complex influences myelin basic protein 63-88-induced T cell cytokine profile and experimental autoimmune encephalomyelitis. Eur J Immunol. 1993;23(12):3089–95. doi: 10.1002/eji.1830231207 7504988
39. Mustafa M, Vingsbo C, Olsson T, Issazadeh S, Ljungdahl A, Holmdahl R. Protective influences on experimental autoimmune encephalomyelitis by MHC class I and class II alleles. J Immunol. 1994;153(7):3337–44. 7522259
40. Issazadeh S, Kjellen P, Olsson T, Mustafa M, Holmdahl R. Major histocompatibility complex-controlled protective influences on experimental autoimmune encephalomyelitis are peptide specific. Eur J Immunol. 1997;27(6):1584–7. doi: 10.1002/eji.1830270640 9209515
41. Kular L, Liu Y, Ruhrmann S, Zheleznyakova G, Marabita F, Gomez-Cabrero D, et al. DNA methylation as a mediator of HLA-DRB1*15:01 and a protective variant in multiple sclerosis. Nat Commun. 2018;9(1):2397. doi: 10.1038/s41467-018-04732-5 29921915
42. Hauser SL, Bar-Or A, Comi G, Giovannoni G, Hartung HP, Hemmer B, et al. Ocrelizumab versus Interferon Beta-1a in Relapsing Multiple Sclerosis. N Engl J Med. 2017;376(3):221–34. doi: 10.1056/NEJMoa1601277 28002679
43. Palanichamy A, Apeltsin L, Kuo TC, Sirota M, Wang S, Pitts SJ, et al. Immunoglobulin class-switched B cells form an active immune axis between CNS and periphery in multiple sclerosis. Sci Transl Med. 2014;6(248):248ra106. doi: 10.1126/scitranslmed.3008930 25100740
44. Jelcic I, Al Nimer F, Wang J, Lentsch V, Planas R, Jelcic I, et al. Memory B Cells Activate Brain-Homing, Autoreactive CD4(+) T Cells in Multiple Sclerosis. Cell. 2018;175(1):85–100 e23. doi: 10.1016/j.cell.2018.08.011 30173916
45. Rizzo F, Giacomini E, Mechelli R, Buscarinu MC, Salvetti M, Severa M, et al. Interferon-beta therapy specifically reduces pathogenic memory B cells in multiple sclerosis patients by inducing a FAS-mediated apoptosis. Immunol Cell Biol. 2016;94(9):886–94. doi: 10.1038/icb.2016.55 27265253
46. Baker D, Marta M, Pryce G, Giovannoni G, Schmierer K. Memory B Cells are Major Targets for Effective Immunotherapy in Relapsing Multiple Sclerosis. EBioMedicine. 2017;16:41–50. doi: 10.1016/j.ebiom.2017.01.042 28161400
47. Sorensen TL, Tani M, Jensen J, Pierce V, Lucchinetti C, Folcik VA, et al. Expression of specific chemokines and chemokine receptors in the central nervous system of multiple sclerosis patients. J Clin Invest. 1999;103(6):807–15. doi: 10.1172/JCI5150 10079101
48. Huang J, Khademi M, Fugger L, Lindhe O, Novakova L, Axelsson M, et al. Inflammation-related plasma and CSF biomarkers for multiple sclerosis. Proc Natl Acad Sci U S A. 2020;117(23):12952–60. doi: 10.1073/pnas.1912839117 32457139
49. Claudinon J, Monier MN, Lamaze C. Interfering with interferon receptor sorting and trafficking: impact on signaling. Biochimie. 2007;89(6–7):735–43. doi: 10.1016/j.biochi.2007.03.014 17493737
50. Ivashkiv LB, Donlin LT. Regulation of type I interferon responses. Nat Rev Immunol. 2014;14(1):36–49. doi: 10.1038/nri3581 24362405
51. Couturier N, Bucciarelli F, Nurtdinov RN, Debouverie M, Lebrun-Frenay C, Defer G, et al. Tyrosine kinase 2 variant influences T lymphocyte polarization and multiple sclerosis susceptibility. Brain. 2011;134(Pt 3):693–703. doi: 10.1093/brain/awr010 21354972
52. Dendrou CA, Cortes A, Shipman L, Evans HG, Attfield KE, Jostins L, et al. Resolving TYK2 locus genotype-to-phenotype differences in autoimmunity. Sci Transl Med. 2016;8(363):363ra149. doi: 10.1126/scitranslmed.aag1974 27807284
53. Isaksson M, Ardesjö B, Rönnblom L, Kämpe O, Lassmann H, Eloranta ML, et al. Plasmacytoid DC promote priming of autoimmune Th17 cells and EAE. Eur J Immunol. 2009;39(10):2925–35. doi: 10.1002/eji.200839179 19637225
54. Prinz M, Schmidt H, Mildner A, Knobeloch KP, Hanisch UK, Raasch J, et al. Distinct and nonredundant in vivo functions of IFNAR on myeloid cells limit autoimmunity in the central nervous system. Immunity. 2008;28(5):675–86. doi: 10.1016/j.immuni.2008.03.011 18424188
55. Teige I, Treschow A, Teige A, Mattsson R, Navikas V, Leanderson T, et al. IFN-beta gene deletion leads to augmented and chronic demyelinating experimental autoimmune encephalomyelitis. J Immunol. 2003;170(9):4776–84. doi: 10.4049/jimmunol.170.9.4776 12707359
56. Messer G, Zemmour J, Orr HT, Parham P, Weiss EH, Girdlestone J. HLA-J, a second inactivated class I HLA gene related to HLA-G and HLA-A. Implications for the evolution of the HLA-A-related genes. J Immunol. 1992;148(12):4043–53. 1602142
57. Cheetham SW, Faulkner GJ, Dinger ME. Overcoming challenges and dogmas to understand the functions of pseudogenes. Nat Rev Genet. 2019. doi: 10.1038/s41576-019-0196-1 31848477
58. Rapicavoli NA, Qu K, Zhang JJ, Mikhail M, Laberge RM, Chang HY. A mammalian pseudogene lncRNA at the interface of inflammation and anti-inflammatory therapeutics. Elife. 2013;2. doi: 10.7554/eLife.00762 23898399
59. Chiang JJ, Sparrer KMJ, van Gent M, Lassig C, Huang T, Osterrieder N, et al. Viral unmasking of cellular 5S rRNA pseudogene transcripts induces RIG-I-mediated immunity. Nat Immunol. 2018;19(1):53–62. doi: 10.1038/s41590-017-0005-y 29180807
60. Gu S, Fellerhoff B, Muller N, Laumbacher B, Wank R. Paradoxical downregulation of HLA-A expression by IFNgamma associated with schizophrenia and noncoding genes. Immunobiology. 2013;218(5):738–44. doi: 10.1016/j.imbio.2012.08.275 23083632
61. Friese MA, Jakobsen KB, Friis L, Etzensperger R, Craner MJ, McMahon RM, et al. Opposing effects of HLA class I molecules in tuning autoreactive CD8+ T cells in multiple sclerosis. Nat Med. 2008;14(11):1227–35. doi: 10.1038/nm.1881 18953350
62. Sundqvist E, Sundström P, Linden M, Hedström AK, Aloisi F, Hillert J, et al. Epstein-Barr virus and multiple sclerosis: interaction with HLA. Genes Immun. 2012;13(1):14–20. doi: 10.1038/gene.2011.42 21776012
63. Polman CH, Reingold SC, Banwell B, Clanet M, Cohen JA, Filippi M, et al. Diagnostic criteria for multiple sclerosis: 2010 revisions to the McDonald criteria. Ann Neurol. 2011;69(2):292–302. doi: 10.1002/ana.22366 21387374
64. Hagberg N, Joelsson M, Leonard D, Reid S, Eloranta ML, Mo J, et al. The STAT4 SLE risk allele rs7574865[T] is associated with increased IL-12-induced IFN-gamma production in T cells from patients with SLE. Ann Rheum Dis. 2018;77(7):1070–7. doi: 10.1136/annrheumdis-2017-212794 29475858
65. Price AL, Patterson NJ, Plenge RM, Weinblatt ME, Shadick NA, Reich D. Principal components analysis corrects for stratification in genome-wide association studies. Nat Genet. 2006;38(8):904–9. doi: 10.1038/ng1847 16862161
66. Price AL, Weale ME, Patterson N, Myers SR, Need AC, Shianna KV, et al. Long-range LD can confound genome scans in admixed populations. Am J Hum Genet. 2008;83(1):132–5; author reply 5–9. doi: 10.1016/j.ajhg.2008.06.005 18606306
67. McCarthy S, Das S, Kretzschmar W, Delaneau O, Wood AR, Teumer A, et al. A reference panel of 64,976 haplotypes for genotype imputation. Nat Genet. 2016;48(10):1279–83. doi: 10.1038/ng.3643 27548312
68. Loh PR, Danecek P, Palamara PF, Fuchsberger C, Y AR, H KF, et al. Reference-based phasing using the Haplotype Reference Consortium panel. Nat Genet. 2016;48(11):1443–8. doi: 10.1038/ng.3679 27694958
69. Zheng X, Shen J, Cox C, Wakefield JC, Ehm MG, Nelson MR, et al. HIBAG—HLA genotype imputation with attribute bagging. Pharmacogenomics J. 2014;14(2):192–200. doi: 10.1038/tpj.2013.18 23712092
70. Stekhoven DJ, Buhlmann P. MissForest—non-parametric missing value imputation for mixed-type data. Bioinformatics. 2012;28(1):112–8. doi: 10.1093/bioinformatics/btr597 22039212
71. Chang CC, Chow CC, Tellier LC, Vattikuti S, Purcell SM, Lee JJ. Second-generation PLINK: rising to the challenge of larger and richer datasets. Gigascience. 2015;4:7. doi: 10.1186/s13742-015-0047-8 25722852
72. Serana F, Sottini A, Ghidini C, Zanotti C, Capra R, Cordioli C, et al. Modulation of IFNAR1 mRNA expression in multiple sclerosis patients. J Neuroimmunol. 2008;197(1):54–62. doi: 10.1016/j.jneuroim.2008.03.019 18482773
73. R Core Team. R: A language and environment for statistical computing: R Foundation for Statistical Computing; 2018 [Available from: https://www.R-project.org/.
Článek vyšel v časopise
PLOS Genetics
2020 Číslo 10
- Proč se v Česku šíří několik „vymýcených“ infekcí najednou? Ptáme se odborníků
- FDA varuje před selfmonitoringem cukru pomocí chytrých hodinek. Jak je to v Česku?
- Prof. Jan Škrha: Metformin je bezpečný, ale je třeba jej bezpečně užívat a léčbu kontrolovat
- Jak souvisí postcovidový syndrom s poškozením mozku?
- Doc. Peter Minárik: Oneskorenie liečby tukovej choroby pečene môže viesť k smrteľným komplikáciám
Nejčtenější v tomto čísle
- Evaluation of both exonic and intronic variants for effects on RNA splicing allows for accurate assessment of the effectiveness of precision therapies
- RNA-directed DNA Methylation
- The DNA methylome of human sperm is distinct from blood with little evidence for tissue-consistent obesity associations
- Correction: Molecular predictors of brain metastasis-related microRNAs in lung adenocarcinoma