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05.06.2020 | Article

Innate immune stimulation of whole blood reveals IFN-1 hyper-responsiveness in type 1 diabetes

verfasst von: Kameron B. Rodrigues, Matthew J. Dufort, Alba Llibre, Cate Speake, M. Jubayer Rahman, Vincent Bondet, Juan Quiel, Peter S. Linsley, Carla J. Greenbaum, Darragh Duffy, Kristin V. Tarbell

Erschienen in: Diabetologia | Ausgabe 8/2020

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Abstract

Aims/hypothesis

Self-antigen-specific T cell responses drive type 1 diabetes pathogenesis, but alterations in innate immune responses are also critical and not as well understood. Innate immunity in human type 1 diabetes has primarily been assessed via gene-expression analysis of unstimulated peripheral blood mononuclear cells, without the immune activation that could amplify disease-associated signals. Increased responsiveness in each of the two main innate immune pathways, driven by either type 1 IFN (IFN-1) or IL-1, have been detected in type 1 diabetes, but the dominant innate pathway is still unclear. This study aimed to determine the key innate pathway in type 1 diabetes and assess the whole blood immune stimulation assay as a tool to investigate this.

Methods

The TruCulture whole blood ex vivo stimulation assay, paired with gene expression and cytokine measurements, was used to characterise changes in the stimulated innate immune response in type 1 diabetes. We applied specific cytokine-induced signatures to our data, pre-defined from the same assays measured in a separate cohort of healthy individuals. In addition, NOD mice were stimulated with CpG and monocyte gene expression was measured.

Results

Monocytes from NOD mice showed lower baseline vs diabetes-resistant B6.g7 mice, but higher induced IFN-1-associated gene expression. In human participants, ex vivo whole blood stimulation revealed higher induced IFN-1 responses in type 1 diabetes, as compared with healthy control participants. In contrast, neither the IL-1-induced gene signature nor response to the adaptive immune stimulant Staphylococcal enterotoxin B were significantly altered in type 1 diabetes samples vs healthy control participants. Targeted gene-expression analysis showed that this enhanced IFN response was specific to IFN-1, as IFN-γ-driven responses were not significantly different.

Conclusions/interpretation

Our study identifies increased responsiveness to IFN-1 as a feature of both the NOD mouse model of autoimmune diabetes and human established type 1 diabetes. A stimulated IFN-1 gene signature may be a potential biomarker for type 1 diabetes and used to evaluate the effects of therapies targeting this pathway.

Data availability

Mouse gene expression data are found in the gene expression omnibus (GEO) repository, accession GSE146452 (www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE146452). Nanostring count data from the human experiments were deposited in the GEO repository, accession GSE146338 (www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE146338). Data files and R code for all analyses are available at https://github.com/rodriguesk/T1D_truculture_diabetologia.

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Price JD, Tarbell KV (2015) The role of dendritic cell subsets and innate immunity in the pathogenesis of type 1 diabetes and other autoimmune diseases. Front Immunol 6:288. https://doi.org/10.3389/fimmu.2015.00288 CrossRefPubMedPubMedCentral

Liang Y, Sarkar MK, Tsoi LC, Gudjonsson JE (2017) Psoriasis: a mixed autoimmune and autoinflammatory disease. Curr Opin Immunol 49:1–8. https://doi.org/10.1016/j.coi.2017.07.007 CrossRefPubMedPubMedCentral

Arts RJW, Joosten LAB, Netea MG (2018) The potential role of trained immunity in autoimmune and autoinflammatory disorders. Front Immunol 9:298. https://doi.org/10.3389/fimmu.2018.00298 CrossRefPubMedPubMedCentral

Marshak-Rothstein A (2016) Autoimmunity: promoting and stabilizing innate immunity ‘UNWUCHT’. Immunol Rev 269(1):7–10. https://doi.org/10.1111/imr.12387

Hotta-Iwamura C, Tarbell KV (2016) Type 1 diabetes genetic susceptibility and dendritic cell function: potential targets for treatment. J Leukoc Biol 100(1):65–80.

Mayer-Barber KD, Yan B (2017) Clash of the cytokine titans: counter-regulation of interleukin-1 and type I interferon-mediated inflammatory responses. Cell Mol Immunol 14(1):22–35. https://doi.org/10.1038/cmi.2016.25 CrossRefPubMed

Ludigs K, Parfenov V, Pasquier RAD, Guarda G (2012) Type I IFN-mediated regulation of IL-1 production in inflammatory disorders. Cell Mol Life Sci 69(20):3395–3418. https://doi.org/10.1007/s00018-012-0989-2 CrossRefPubMed

McNab F, Mayer-Barber K, Sher A, Wack A, O’Garra A (2015) Type I interferons in infectious disease. Nat Rev Immunol 15(2):87–103. https://doi.org/10.1038/nri3787 CrossRefPubMedPubMedCentral

Davidson S, Maini MK, Wack A (2015) Disease-promoting effects of type I interferons in viral, bacterial, and coinfections. J Interf Cytokine Res 35(4):252–264. https://doi.org/10.1089/jir.2014.0227 CrossRef

10.

Mostafavi S, Yoshida H, Moodley D et al (2016) Parsing the interferon transcriptional network and its disease associations. Cell 164(3):564–578. https://doi.org/10.1016/j.cell.2015.12.032 CrossRefPubMedPubMedCentral

11.

Mayer-Barber KD, Andrade BB, Oland SD et al (2014) Host-directed therapy of tuberculosis based on interleukin-1 and type I interferon crosstalk. Nature 511(7507):99–103. https://doi.org/10.1038/nature13489 CrossRefPubMedPubMedCentral

12.

Hall JC, Rosen A (2010) Type I interferons: crucial participants in disease amplification in autoimmunity. Nat Rev Rheumatol 6(1):40–49. https://doi.org/10.1038/nrrheum.2009.237 CrossRefPubMedPubMedCentral

13.

Yang C-A, Chiang B-L (2015) Inflammasomes and human autoimmunity: a comprehensive review. J Autoimmun 61:1–8. https://doi.org/10.1016/j.jaut.2015.05.001 CrossRefPubMed

14.

Diana J, Simoni Y, Furio L et al (2013) Crosstalk between neutrophils, B-1a cells and plasmacytoid dendritic cells initiates autoimmune diabetes. Nat Med 19(1):65–73. https://doi.org/10.1038/nm.3042 CrossRefPubMed

15.

Li Q, Xu B, Michie SA, Rubins KH, Schreriber RD, Mcdevitt HO (2008) Interferon-alpha initiates type 1 diabetes in nonobese diabetic mice. Proc Natl Acad Sci U S A 105(34):12439–12444. https://doi.org/10.1073/pnas.0806439105 CrossRefPubMedPubMedCentral

16.

Rahman MJ, Rodrigues KB, Quiel JA et al (2018) Restoration of the type I IFN-IL-1 balance through targeted blockade of PTGER4 inhibits autoimmunity in NOD mice. JCI insight 3(3):e97843. https://doi.org/10.1172/jci.insight.97843 CrossRefPubMedCentral

17.

Rodriguez-Calvo T, Sabouri S, Anquetil F, von Herrath MG (2016) The viral paradigm in type 1 diabetes: who are the main suspects? Autoimmun Rev 15(10):964–969. https://doi.org/10.1016/j.autrev.2016.07.019 CrossRefPubMed

18.

Kallionpaa H, Elo LL, Laajala E et al (2014) Innate immune activity is detected prior to seroconversion in children with HLA-conferred type 1 diabetes susceptibility. Diabetes 63(7):2402–2414. https://doi.org/10.2337/db13-1775 CrossRefPubMed

19.

Ferreira RC, Guo H, Coulson RMR et al (2014) A type I interferon transcriptional signature precedes autoimmunity in children genetically at risk for type 1 diabetes. Diabetes 63(7):2538–2550. https://doi.org/10.2337/db13-1777 CrossRefPubMedPubMedCentral

20.

Lundberg M, Krogvold L, Kuric E, Dahl-Jørgensen K, Skog O (2016) Expression of interferon-stimulated genes in insulitic pancreatic islets of patients recently diagnosed with type 1 diabetes. Diabetes 65(10):3104–3110. https://doi.org/10.2337/db16-0616 CrossRefPubMed

21.

Marroqui L, Dos Santos RS, Op de beeck A et al (2017) Interferon-α mediates human beta cell HLA class I overexpression, endoplasmic reticulum stress and apoptosis, three hallmarks of early human type 1 diabetes. Diabetologia 60(4):656–667. https://doi.org/10.1007/s00125-016-4201-3 CrossRefPubMed

22.

Foulis AK, Farquharson MA, Meager A (1987) Immunoreactive α-interferon in insulin-secreting β cells in type 1 diabetes mellitus. Lancet 330(8573):1423–1427. https://doi.org/10.1016/S0140-6736(87)91128-7 CrossRef

23.

Hussain MJ, Peakman M, Gallati H et al (1996) Elevated serum levels of macrophage-derived cytokines precede and accompany the onset of IDDM. Diabetologia 39(1):60–69. https://doi.org/10.1007/BF00400414 CrossRefPubMed

24.

Bradshaw EM, Raddassi K, Elyaman W et al (2009) Monocytes from patients with type 1 diabetes spontaneously secrete proinflammatory cytokines inducing Th17 cells. J Immunol 183(7):4432–4439. https://doi.org/10.4049/jimmunol.0900576 CrossRefPubMed

25.

Cabrera SM, Wang X, Chen Y-G et al (2016) Interleukin-1 antagonism moderates the inflammatory state associated with type 1 diabetes during clinical trials conducted at disease onset. Eur J Immunol 46(4):1030–1046. https://doi.org/10.1002/eji.201546005 CrossRefPubMedPubMedCentral

26.

Chen Y-G, Cabrera SM, Jia S et al (2014) Molecular signatures differentiate immune states in type 1 diabetic families. Diabetes 63(11):3960–3973. https://doi.org/10.2337/db14-0214 CrossRefPubMedPubMedCentral

27.

Larsen CM, Faulenbach M, Vaag A et al (2007) Interleukin-1–receptor antagonist in type 2 diabetes mellitus. N Engl J Med 356(15):1517–1526. https://doi.org/10.1056/NEJMoa065213 CrossRefPubMed

28.

Nikfar S, Saiyarsarai P, Tigabu BM, Abdollahi M (2018) Efficacy and safety of interleukin-1 antagonists in rheumatoid arthritis: a systematic review and meta-analysis. Rheumatol Int 38(8):1363–1383. https://doi.org/10.1007/s00296-018-4041-1 CrossRefPubMed

29.

Moran A, Bundy B, Becker DJ et al (2013) Interleukin-1 antagonism in type 1 diabetes of recent onset: two multicentre, randomised, double-blind, placebo-controlled trials. Lancet 381(9881):1905–1915. https://doi.org/10.1016/S0140-6736(13)60023-9 CrossRefPubMed

30.

Kayserova J, Vcelakova J, Stechova K et al (2014) Decreased dendritic cell numbers but increased TLR9-mediated interferon-alpha production in first degree relatives of type 1 diabetes patients. Clin Immunol 153(1):49–55. https://doi.org/10.1016/j.clim.2014.03.018 CrossRefPubMed

31.

Duffy D, Rouilly V, Libri V et al (2014) Functional analysis via standardized whole-blood stimulation systems defines the boundaries of a healthy immune response to complex stimuli. Immunity 40(3):436–450. https://doi.org/10.1016/j.immuni.2014.03.002 CrossRefPubMed

32.

Urrutia A, Duffy D, Rouilly V et al (2016) Standardized whole-blood transcriptional profiling enables the deconvolution of complex induced immune responses. Cell Rep 16(10):2777–2791. https://doi.org/10.1016/j.celrep.2016.08.011 CrossRefPubMed

33.

Duffy D, Rouilly V, Braudeau C et al (2017) Standardized whole blood stimulation improves immunomonitoring of induced immune responses in multi-center study. Clin Immunol 183:325–335. https://doi.org/10.1016/j.clim.2017.09.019 CrossRefPubMed

34.

Guerrero AD, Dong MB, Zhao Y, Lau-Kilby A, Tarbell KV (2014) Interleukin-2-mediated inhibition of dendritic cell development correlates with decreased CD135 expression and increased monocyte/macrophage precursors. Immunology 143(4):640–650. https://doi.org/10.1111/imm.12345 CrossRefPubMedPubMedCentral

35.

Dong MB, Rahman MJ, Tarbell KV (2016) Flow cytometric gating for spleen monocyte and DC subsets: differences in autoimmune NOD mice and with acute inflammation. J Immunol Methods 432:4–12. https://doi.org/10.1016/j.jim.2015.08.015 CrossRefPubMed

36.

Rodero MP, Decalf J, Bondet V et al (2017) Detection of interferon alpha protein reveals differential levels and cellular sources in disease. J Exp Med 214(5):1547–1555. https://doi.org/10.1084/jem.20161451 CrossRefPubMedPubMedCentral

37.

Llibre A, Bilek N, Bondet V et al (2019) Plasma type I IFN protein concentrations in human tuberculosis. Front Cell Infect Microbiol 9:296. https://doi.org/10.3389/fcimb.2019.00296 CrossRefPubMedPubMedCentral

38.

Vandesompele J, De Preter K, Pattyn F et al (2002) Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes. Genome Biol 3(7):research0034. https://doi.org/10.1186/gb-2002-3-7-research0034

39.

Armbruster DA, Pry T (2008) Limit of blank, limit of detection and limit of quantitation. Clin Biochem Rev 29(Suppl 1):S49–S52PubMedPubMedCentral

40.

Johnson WE, Li C, Rabinovic A (2007) Adjusting batch effects in microarray expression data using empirical Bayes methods. Biostatistics 8(1):118–127. https://doi.org/10.1093/biostatistics/kxj037 CrossRefPubMed

41.

Leek JT, Johnson WE, Parker HS, Jaffe AE, Storey JD (2012) The sva package for removing batch effects and other unwanted variation in high-throughput experiments. Bioinformatics 28(6):882–883. https://doi.org/10.1093/bioinformatics/bts034 CrossRefPubMedPubMedCentral

42.

Ritchie ME, Phipson B, Wu D et al (2015) Limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Res 43(7):e47. https://doi.org/10.1093/nar/gkv007

43.

Gu Z, Eils R, Schlesner M (2016) Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics 32(18):2847–2849. https://doi.org/10.1093/bioinformatics/btw313 CrossRefPubMed

44.

Wu D, Lim E, Vaillant F, Asselin-Labat M-L, Visvader JE, Smyth GK (2010) ROAST: rotation gene set tests for complex microarray experiments. Bioinformatics 26(17):2176–2182. https://doi.org/10.1093/bioinformatics/btq401 CrossRefPubMedPubMedCentral

45.

Liberzon A, Birger C, Thorvaldsdóttir H, Ghandi M, Mesirov JP, Tamayo P (2015) The Molecular Signatures Database (MSigDB) hallmark gene set collection. Cell Syst 1(6):417–425. https://doi.org/10.1016/J.CELS.2015.12.004

46.

R Core Team (2018) R: a language and environment for statistical computing. Available from: https://www.R-project.org/. Accessed: 20 April 2019

47.

Wickham H (2016) ggplot2: elegant graphics for data analysis, 2nd edn. Springer-Verlag, New York, NY. https://doi.org/10.1007/978-3-319-24277-4 CrossRef

48.

Arif S, Tree TI, Astill TP et al (2004) Autoreactive T cell responses show proinflammatory polarization in diabetes but a regulatory phenotype in health. J Clin Invest 113(3):451–463. https://doi.org/10.1172/JCI19585 CrossRefPubMedPubMedCentral

49.

Haskins K, Cooke A (2011) CD4 T cells and their antigens in the pathogenesis of autoimmune diabetes. Curr Opin Immunol 23(6):739–745. https://doi.org/10.1016/J.COI.2011.08.004 CrossRefPubMedPubMedCentral

50.

Cabrera SM, Henschel AM, Hessner MJ (2016) Innate inflammation in type 1 diabetes. Transl Res 167(1):214–227. https://doi.org/10.1016/j.trsl.2015.04.011 CrossRefPubMed

51.

Timmerman JJ, Verweij CL, van Gijlswijk-Janssen DJ, van der Woude FJ, van Es LA, Daha MR (1995) Cytokine-regulated production of the major histocompatibility complex class-III-encoded complement proteins factor B and C4 by human glomerular mesangial cells. Hum Immunol 43(1):19–28. https://doi.org/10.1016/0198-8859(94)00122-7 CrossRefPubMed

52.

Walker LSK, von Herrath M (2016) CD4 T cell differentiation in type 1 diabetes. Clin Exp Immunol 183(1):16–29. https://doi.org/10.1111/cei.12672 CrossRefPubMed

53.

Fatima N, Faisal SM, Zubair S et al (2016) Role of pro-inflammatory cytokines and biochemical markers in the pathogenesis of type 1 diabetes: correlation with age and glycemic condition in diabetic human subjects. PLoS One 11(8):e0161548. https://doi.org/10.1371/journal.pone.0161548 CrossRefPubMedPubMedCentral

54.

Akbari M, Hassan-Zadeh V (2018) Hyperglycemia affects the expression of inflammatory genes in peripheral blood mononuclear cells of patients with type 2 diabetes. Immunol Investig 47(7):654–665. https://doi.org/10.1080/08820139.2018.1480031 CrossRef

55.

Rahman MJ, Rahir G, Dong MB et al (2016) Despite increased type 1 IFN, autoimmune nonobese diabetic mice display impaired dendritic cell response to CpG and decreased nuclear localization of IFN-activated STAT1. J Immunol 196(5):2031–2040. https://doi.org/10.4049/jimmunol.1501239 CrossRefPubMed

56.

Levy H, Wang X, Kaldunski M et al (2012) Transcriptional signatures as a disease-specific and predictive inflammatory biomarker for type 1 diabetes. Genes Immun 13(8):593–604. https://doi.org/10.1038/gene.2012.41 CrossRefPubMedPubMedCentral

57.

Park SH, Kang K, Giannopoulou E et al (2017) Type I interferons and the cytokine TNF cooperatively reprogram the macrophage epigenome to promote inflammatory activation. Nat Immunol 18(10):1104–1116. https://doi.org/10.1038/ni.3818 CrossRefPubMedPubMedCentral

58.

Kreuzer D, Nikoopour E, Au BCY et al (2015) Reduced interferon-α production by dendritic cells in type 1 diabetes does not impair immunity to influenza virus. Clin Exp Immunol 179(2):245–255. https://doi.org/10.1111/cei.12462 CrossRefPubMedPubMedCentral

59.

Xia CQ, Peng R, Chernatynskaya AV et al (2014) Increased IFN-α-producing plasmacytoid dendritic cells (pDCs) in human Th1-mediated type 1 diabetes: pDCs augment Th1 responses through IFN-α production. J Immunol 193(3):1024–1034. https://doi.org/10.4049/jimmunol.1303230 CrossRefPubMed

Titel: Innate immune stimulation of whole blood reveals IFN-1 hyper-responsiveness in type 1 diabetes
verfasst von: Kameron B. Rodrigues
Matthew J. Dufort
Alba Llibre
Cate Speake
M. Jubayer Rahman
Vincent Bondet
Juan Quiel
Peter S. Linsley
Carla J. Greenbaum
Darragh Duffy
Kristin V. Tarbell
Publikationsdatum: 05.06.2020
Verlag: Springer Berlin Heidelberg
Erschienen in: Diabetologia / Ausgabe 8/2020
Print ISSN: 0012-186X
Elektronische ISSN: 1432-0428
DOI: https://doi.org/10.1007/s00125-020-05179-4

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Innate immune stimulation of whole blood reveals IFN-1 hyper-responsiveness in type 1 diabetes

Abstract

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