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Causal relationships between circulating inflammatory cytokines and diffuse large B cell lymphoma: a bidirectional Mendelian randomization study

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Abstract

Diffuse large B cell lymphoma (DLBCL) is the most common type of non-Hodgkin lymphoma. Studies indicated that inflammatory cytokines involved in the occurrence and progression of DLBCL and it is challenging to discern causality from the effects due to the presence of feedback loops. We conducted a bidirectional Mendelian randomization (MR) study to investigate the potential causal relationship between DLBCL and inflammatory cytokines. The genetic variants associated with inflammatory cytokines were obtained from a genome-wide association study (GWAS) involving 8293 European participants, and the data on 1010 individuals with DLBCL were sourced from the FinnGen consortium. The primary method employed in this study was the inverse-variance weighted (IVW) method, with supplementary analyses conducted using the MR-Egger, weighted median, and MR-PRESSO approaches. Based on the IVW method, genetically predicted that increasing level of Monokine induced by interferon gamma (MIG/CXC chemokine ligand 9, CXCL9) [OR: 1.31; 95% CI: 1.05–1.62; P = 0.01] and interferon gamma-induced protein 10(IP-10/CXC chemokine ligand 10, CXCL10) [OR: 1.30; 95% CI: 1.02–1.66; P = 0.03] showed suggestive associations with DLBCL risk. DLBCL may increase the level of macrophage colony-stimulating factor (M-CSF) [OR: 1.12; 95% CI: 1.01–1.2; P = 0.03], tumor necrosis factor beta (TNF-β) [OR: 1.16; 95% CI: 1.02–1.31; P = 0.02] and TNF-related apoptosis-inducing ligand (TRAIL) [OR: 1.07; 95% CI: 1.01–1.13; P = 0.02]. This study presents evidence supporting a causal relationship between inflammation cytokines and DLBCL. Specifically, MIG/CXCL9 and IP-10/CXCL10 were identified as indicators of upstream causes of DLBCL; while, DLBCL itself was found to elevate the levels of M-CSF, TNF-β, and TRAIL. These findings suggest that targeting specific inflammatory factors through regulation and intervention could serve as a potential approach for the treatment and prevention of DLBCL.

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Data availability

We thank the participants and researchers for providing the publicly available summary data used in this study. The data sources and handling of these data are described in the Materials and Methods and in the Supplementary Tables. Further information is available from the corresponding author upon request.

Abbreviations

DLBCL:

Diffuse large B cell lymphoma

MR:

Mendelian randomization

IVs:

Instrumental variables

GWASs:

Genome-wide association studies

CI:

Confidence interval

IVW:

Inverse-variance weighted

MR-PRESSO:

MR-pleiotropy residual sum and outliers

OR:

Odds ratio

SNPs:

Single nucleotide polymorphisms

CXCL9:

CXC chemokine ligand 9

CXCL10:

CXC chemokine ligand 10

YFS:

Young Finns study

b-NGF:

Beta nerve growth factor

CTACK:

Cutaneous T-cell attracting chemokine

FGFBasic:

Basic fibroblast growth factor

G-CSF:

Granulocyte colony-stimulating factor

GRO-a:

Growth-regulated oncogene-a

HGF:

Hepatocyte growth factor

IFNg:

Interferon gamma

IL:

Interleukin

IP-10:

Interferon gamma-induced protein 10

MCP-1:

Monocyte chemotactic protein-1

MCP-3:

Monocyte-specific chemokine 3

M-CSF:

Macrophage colony-stimulating factor

MIF:

Macrophage-migration inhibitory factor

MIG:

Monokine induced by interferon gamma

MIP-1a:

Macrophage inflammatory protein-1a

MIP-1b:

Macrophage inflammatory protein-1b

PDGFbb:

Platelet-derived growth factor BB

RANTES:

Regulated on activation, normal T-cell expressed and secreted

SCF:

Stem cell factor

SCGFb:

Stem cell growth factor beta

SDF-1a:

Stromal cell-derived factor-1 alpha

TNFα:

Tumor necrosis factor alpha

TNFβ:

Tumor necrosis factor beta

TRAIL:

TNF-related apoptosis-inducing ligand

VEGF:

Vascular endothelial growth factor

References

  1. Li S, Young KH, Medeiros LJ. Diffuse large B-cell lymphoma. Pathology. 2018;50(1):74–87.

    PubMed  Google Scholar 

  2. Sehn LH, Salles G. Orcid Id. Diffuse large B-cell lymphoma. N Engl J Med. 2021;384(9):842–58.

    CAS  PubMed  PubMed Central  Google Scholar 

  3. Martelli M, Ferreri AJ, Agostinelli C, et al. Diffuse large B-cell lymphoma. Crit Rev Oncol Hematol. 2013;87(2):146–71.

    PubMed  Google Scholar 

  4. Sant M, Allemani C, Tereanu C, et al. Incidence of hematologic malignancies in Europe by morphologic subtype: results of the HAEMACARE project. Blood. 2010;116(19):3724–34.

    CAS  PubMed  Google Scholar 

  5. Cerhan JR, Kricker A, Paltiel O, et al. Medical history, lifestyle, family history, and occupational risk factors for diffuse large B-cell lymphoma: the InterLymph Non-Hodgkin Lymphoma Subtypes Project. J Natl Cancer Inst Monogr. 2014;2014(48):15–25.

    PubMed  PubMed Central  Google Scholar 

  6. Cerhan JR, Berndt SI, Vijai J, et al. Genome-wide association study identifies multiple susceptibility loci for diffuse large B cell lymphoma. Nat Genet. 2014;46(11):1233–8.

    CAS  PubMed  PubMed Central  Google Scholar 

  7. Morton LM, Slager SL, Cerhan JR, et al. Etiologic heterogeneity among non-Hodgkin lymphoma subtypes: the InterLymph Non-Hodgkin Lymphoma Subtypes Project. J Natl Cancer Inst Monogr. 2014;2014(48):130–44.

    PubMed  PubMed Central  Google Scholar 

  8. Acosta-Rodríguez EV, Merino MC, Montes CL, Motrán CC, Gruppi A. Cytokines and chemokines shaping the B-cell compartment. Cytokine Growth Factor Rev. 2007;18(1–2):73–83.

    PubMed  Google Scholar 

  9. Charo IF, Ransohoff RM. The many roles of chemokines and chemokine receptors in inflammation. N Engl J Med. 2006;354(6):610–21.

    CAS  PubMed  Google Scholar 

  10. Schaerli P, Moser B. Chemokines: control of primary and memory T-cell traffic. Immunol Res. 2005;31(1):57–74. https://doi.org/10.1385/IR:31:1:572005:57-74.

    Article  CAS  PubMed  Google Scholar 

  11. Bonati L, Tang L. Cytokine engineering for targeted cancer immunotherapy. Curr Opin Chem Biol. 2021;62:43–52.

    CAS  PubMed  Google Scholar 

  12. Yoshimura A, Ito M, Chikuma S, Akanuma T, Nakatsukasa H. Negative regulation of cytokine signaling in immunity. Cold Spring Harb Perspect Biol. 2018;10(7): a028571.

    PubMed  PubMed Central  Google Scholar 

  13. Atallah-Yunes SA, Robertson MJ. Cytokine based immunotherapy for cancer and lymphoma: biology, challenges and future perspectives. Front Immunol. 2022;20(13): 872010.

    Google Scholar 

  14. Shen N, Yu Y, Zhang R, et al. Expression and prognostic value of PIK3CA, VEGF, IL-8, IL-10, and RIP2 in diffuse large B-cell lymphoma. Int J Clin Pract. 2022;7(2022):2637581.

    Google Scholar 

  15. Nacinović-Duletić A, Stifter S, Dvornik S, Skunca Z, Jonjić N. Correlation of serum IL-6, IL-8 and IL-10 levels with clinicopathological features and prognosis in patients with diffuse large B-cell lymphoma. Int J Lab Hematol. 2008;30(3):230–9.

    PubMed  Google Scholar 

  16. Hashwah H, Bertram K, Stirm K, et al. The IL-6 signaling complex is a critical driver, negative prognostic factor, and therapeutic target in diffuse large B-cell lymphoma. EMBO Mol Med. 2019;11(10): e10576.

    CAS  PubMed  PubMed Central  Google Scholar 

  17. Stirm K, Leary P, Bertram K, et al. Tumor cell-derived IL-10 promotes cell-autonomous growth and immune escape in diffuse large B-cell lymphoma. Oncoimmunology. 2021;10(1):2003533.

    PubMed  PubMed Central  Google Scholar 

  18. Nakayama S, Yokote T, Hirata Y, et al. TNF-α expression in tumor cells as a novel prognostic marker for diffuse large B-cell lymphoma, not otherwise specified. Am J Surg Pathol. 2014;38(2):228–34.

    PubMed  Google Scholar 

  19. Piechna K, Żołyniak A, Jabłońska E, et al. Activity and rational combinations of a novel, engineered chimeric, TRAIL-based ligand in diffuse large B-cell lymphoma. Front Oncol. 2022;31(12):1048741.

    Google Scholar 

  20. Oehadian A, Koide N, Mu MM, et al. Interferon (IFN)-beta induces apoptotic cell death in DHL-4 diffuse large B cell lymphoma cells through tumor necrosis factor-related apoptosis-inducing ligand (TRAIL). Cancer Lett. 2005;225(1):85–92.

    CAS  PubMed  Google Scholar 

  21. Smith GD, Ebrahim S. “Mendelian randomization”: can genetic epidemiology contribute to understanding environmental determinants of disease? Int J Epidemiol. 2003;32(1):1–22.

    PubMed  Google Scholar 

  22. Lawlor DA, Harbord RM, Sterne JA, Timpson N, Davey SG. Mendelian randomization: using genes as instruments for making causal inferences in epidemiology. Stat Med. 2008;27(8):1133–63.

    PubMed  Google Scholar 

  23. Widding-Havneraas T, Zachrisson HD. A gentle introduction to instrumental variables. J Clin Epidemiol. 2022;149:203–5.

    PubMed  Google Scholar 

  24. Ahola-Olli AV, Würtz P, Havulinna AS, et al. Genome-wide association study identifies 27 loci influencing concentrations of circulating cytokines and growth factors. Am J Hum Genet. 2017;100(1):40–50.

    CAS  PubMed  Google Scholar 

  25. Kalaoja M, Orcid ID, Corbin LJ, et al. The role of inflammatory cytokines as intermediates in the pathway from increased adiposity to disease. Obesity (Silver Spring). 2021;29(2):428–37.

    CAS  PubMed  Google Scholar 

  26. Burgess S, Orcid ID, Davey Smith G, et al. Guidelines for performing Mendelian randomization investigations: update for summer 2023. Wellcome Open Res. 2020;4:186.

    Google Scholar 

  27. Skrivankova VW, Richmond RC, Woolf BAR, et al. Strengthening the reporting of observational studies in epidemiology using Mendelian randomization: the STROBE-MR statement. JAMA. 2021;326(16):1614–21.

    PubMed  Google Scholar 

  28. Palmer TM, Lawlor DA, Harbord RM, et al. Using multiple genetic variants as instrumental variables for modifiable risk factors. Stat Methods Med Res. 2012;21(3):223–42.

    PubMed  PubMed Central  Google Scholar 

  29. Burgess S, Thompson SG. Avoiding bias from weak instruments in Mendelian randomization studies. Int J Epidemiol. 2011;40(3):755–64.

    PubMed  Google Scholar 

  30. Hartwig FP, Davey Smith G, Bowden J. Robust inference in summary data Mendelian randomization via the zero modal pleiotropy assumption. Int J Epidemiol. 2017;46(6):1985–98.

    PubMed  PubMed Central  Google Scholar 

  31. Bowden J, Davey Smith G, Haycock PC, Burgess S. Consistent estimation in Mendelian randomization with some invalid instruments using a weighted median estimator. Genet Epidemiol. 2016;40(4):304–14.

    PubMed  PubMed Central  Google Scholar 

  32. Bowden J, Davey Smith G, Burgess S. Mendelian randomization with invalid instruments: effect estimation and bias detection through Egger regression. Int J Epidemiol. 2015;44(2):512–25.

    PubMed  PubMed Central  Google Scholar 

  33. Verbanck M, Chen CY, Orcid ID, et al. Publisher Correction: Detection of widespread horizontal pleiotropy in causal relationships inferred from Mendelian randomization between complex traits and diseases. Nat Genet. 2018;50(8):1196.

    CAS  PubMed  Google Scholar 

  34. Burgess S, Small DS, Thompson SG. A review of instrumental variable estimators for Mendelian randomization. Stat Methods Med Res. 2017;26(5):2333–55.

    PubMed  Google Scholar 

  35. Burgess S, Orcid ID, Thompson SG. Interpreting findings from Mendelian randomization using the MR-Egger method. Eur J Epidemiol. 2017;32(5):377–89.

    PubMed  PubMed Central  Google Scholar 

  36. Verbanck M, Chen CY, Orcid ID, et al. Detection of widespread horizontal pleiotropy in causal relationships inferred from Mendelian randomization between complex traits and diseases. Nat Genet. 2018;50(5):693–8.

    CAS  PubMed  PubMed Central  Google Scholar 

  37. Hemani G, Orcid ID, Zheng J, et al. The MR-Base platform supports systematic causal inference across the human phenome. Elife. 2018;7:e34408.

    PubMed  PubMed Central  Google Scholar 

  38. Bao C, Gu J, Huang X, et al. Cytokine profiles in patients with newly diagnosed diffuse large B-cell lymphoma: IL-6 and IL-10 levels are associated with adverse clinical features and poor outcomes. Cytokine. 2023;169: 156289.

    CAS  PubMed  Google Scholar 

  39. Salven P, Orpana A, Teerenhovi L, Joensuu H. Simultaneous elevation in the serum concentrations of the angiogenic growth factors VEGF and bFGF is an independent predictor of poor prognosis in non-Hodgkin lymphoma: a single-institution study of 200 patients. Blood. 2000;96(12):3712–8.

    CAS  PubMed  Google Scholar 

  40. Ruiduo C, Ying D, Qiwei W. CXCL9 promotes the progression of diffuse large B-cell lymphoma through up-regulating β-catenin. Biomed Pharmacother. 2018;107:689–95.

    PubMed  Google Scholar 

  41. Zhou X, Guo S, Shi Y. Comprehensive analysis of the expression and significance of CXCLs in human diffuse large B-cell lymphoma. Sci Rep. 2022;12(1):2817.

    CAS  PubMed  PubMed Central  Google Scholar 

  42. Luster AD, Leder P. IP-10, a -C-X-C- chemokine, elicits a potent thymus-dependent antitumor response in vivo. J Exp Med. 1993;178(3):1057–65.

    CAS  PubMed  Google Scholar 

  43. Ansell SM, Maurer MJ, Ziesmer SC, et al. Elevated pretreatment serum levels of interferon-inducible protein-10 (CXCL10) predict disease relapse and prognosis in diffuse large B-cell lymphoma patients. Am J Hematol. 2012;87(9):865–959.

    CAS  PubMed  PubMed Central  Google Scholar 

  44. Moriai S, Takahara M, Ogino T, et al. Production of interferon-{gamma}-inducible protein-10 and its role as an autocrine invasion factor in nasal natural killer/T-cell lymphoma cells. Clin Cancer Res. 2009;15(22):6771–9.

    CAS  PubMed  Google Scholar 

  45. Teichmann M, Meyer B, Beck A, Niedobitek G. Expression of the interferon-inducible chemokine IP-10 (CXCL10), a chemokine with proposed anti-neoplastic functions, in Hodgkin lymphoma and nasopharyngeal carcinoma. J Pathol. 2005;206(1):68–75.

    CAS  PubMed  Google Scholar 

  46. Witzig TE, Maurer MJ, Stenson MJ, et al. Elevated serum monoclonal and polyclonal free light chains and interferon inducible protein-10 predicts inferior prognosis in untreated diffuse large B-cell lymphoma. Am J Hematol. 2014;89(4):417–22.

    CAS  PubMed  PubMed Central  Google Scholar 

  47. Noyori O, Komohara Y, Nasser H, et al. Expression of IL-34 correlates with macrophage infiltration and prognosis of diffuse large B-cell lymphoma. Clin Transl Immunology. 2019;8(8): e1074.

    PubMed  PubMed Central  Google Scholar 

  48. Wynn TA, Chawla A, Pollard JW. Macrophage biology in development, homeostasis and disease. Nature. 2013;496(7446):445–55.

    CAS  PubMed  PubMed Central  Google Scholar 

  49. Noy R, Pollard JW. Tumor-associated macrophages: from mechanisms to therapy. Immunity. 2014;41(1):49–61.

    CAS  PubMed  PubMed Central  Google Scholar 

  50. Nakayama-Ichiyama S, Yokote T, Oka S, et al. Macrophage colony-stimulating factor produced by diffuse large B-cell lymphoma. Br J Haematol. 2010;149(3):310.

    PubMed  Google Scholar 

  51. Ruddle NH. Lymphotoxin and TNF: how it all began-a tribute to the travelers. Cytokine Growth Factor Rev. 2014;25(2):83–9.

    CAS  PubMed  PubMed Central  Google Scholar 

  52. Gommerman JL, Browning JL, Ware CF. The Lymphotoxin Network: orchestrating a type I interferon response to optimize adaptive immunity. Cytokine Growth Factor Rev. 2014;25(2):139–45.

    CAS  PubMed  PubMed Central  Google Scholar 

  53. Cao C, Liu S, Lou SF, Liu T. The +252A/G polymorphism in the Lymphotoxin-α gene and the risk of non-Hodgkin lymphoma: a meta-analysis. Eur Rev Med Pharmacol Sci. 2014;18(4):544–52.

    CAS  PubMed  Google Scholar 

  54. Qu Y, Orcid ID, Wang X, et al. The effects of TNF-α/TNFR2 in regulatory T cells on the microenvironment and progression of gastric cancer. Int J Cancer. 2022;150(8):1373–91.

    CAS  PubMed  Google Scholar 

  55. Cruceriu D, Baldasici O, Balacescu O, Orcid ID, Berindan-Neagoe I. The dual role of tumor necrosis factor-alpha (TNF-α) in breast cancer: molecular insights and therapeutic approaches. Cell Oncol (Dordr). 2020;43(1):1–18.

    CAS  PubMed  Google Scholar 

  56. Wang X, Yang L, Huang F, et al. Inflammatory cytokines IL-17 and TNF-α up-regulate PD-L1 expression in human prostate and colon cancer cells. Immunol Lett. 2017;184:7–14.

    CAS  PubMed  PubMed Central  Google Scholar 

  57. Ashkenazi A. Directing cancer cells to self-destruct with pro-apoptotic receptor agonists. Nat Rev Drug Discov. 2008;7(12):1001–12.

    CAS  PubMed  Google Scholar 

  58. Amarante-Mendes GP, Griffith TS. Therapeutic applications of TRAIL receptor agonists in cancer and beyond. Pharmacol Ther. 2015;155:117–31.

    CAS  PubMed  PubMed Central  Google Scholar 

  59. Wu W, Yang Y, Deng G, et al. Vernodalol enhances TRAIL-induced apoptosis in diffuse large B-cell lymphoma cells. Mol Carcinog. 2017;56(10):2190–9.

    CAS  PubMed  Google Scholar 

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Acknowledgements

The authors express their gratitude to the participants and investigators of the FinnGen and YFS, FINRISK studies. We also thank Figdraw (https://www.figdraw.com) for the assistance in model drawing.

Funding

This work was supported by the Youth Project Shaoxing People’s Hospital (Grant Number: 2023YB15), Medical and Health Science and Technology Project of Zhejiang Province (Grant Number: 2023RC107), Department of Health of Zhejiang Province (Grant Number: 2021KY1137), Young Innovative Talents Project of Zhejiang Health Science and Technology Plan (Grant Number: 2022RC078).

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All authors contributed to the study conception and design. Jieni Yu, Chao Xu, and Leihua Fu designed the study, Zhijian Zhang and Lina Ding analyzed and interpreted the data, and drafted the manuscript. Li Hong, Feidan Gao and Jing Jin analyzed and interpreted the data, Jiaping Fu finished the figures, Weiying Feng and Pan Hong revised the manuscript. All author read and approved the final manuscript.

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Correspondence to Chao Xu.

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The authors have no relevant financial or non-financial interests to disclose.

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This study has been conducted using published studies and consortia providing publicly available summary statistics. All original studies have been approved by the corresponding ethical review board, and the participants have provided informed consent.

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Jieni Yu and Leihua Fu are contributed equally to this work and share first authorship.

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Yu, J., Fu, L., Zhang, Z. et al. Causal relationships between circulating inflammatory cytokines and diffuse large B cell lymphoma: a bidirectional Mendelian randomization study. Clin Exp Med 23, 4585–4595 (2023). https://doi.org/10.1007/s10238-023-01221-y

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