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中华肝脏外科手术学电子杂志

中华肝脏外科手术学电子杂志 ›› 2025, Vol. 14 ›› Issue (06) : 948 -955. doi: 10.3877/cma.j.issn.2095-3232.2025.06.020

临床研究

炎性细胞因子与胰腺导管腺癌的因果关系：一项孟德尔随机化研究
孟泓宇, 戴锦辉, 胡嘉金, 李光辉†()   
  1. 526000　广东省　肇庆市，中山大学附属第三医院肇庆医院肝胆外科
  • 收稿日期:2025-06-11 出版日期:2025-12-10
  • 通信作者: 李光辉
  • 基金资助:
    国家自然科学基金(82270688)

Causal relationship between inflammatory cytokines and pancreatic ductal adenocarcinoma: a Mendelian randomization study

Hongyu Meng, Jinhui Dai, Jiajin Hu, Guanghui Li†()   

  1. Department of Hepatobiliary Surgery, the Third Affiliated Hospital of Sun Yat-sen University Zhaoqing Hospital, Zhaoqing 526000, China
  • Received:2025-06-11 Published:2025-12-10
  • Corresponding author: Guanghui Li
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引用本文：

孟泓宇, 戴锦辉, 胡嘉金, 李光辉. 炎性细胞因子与胰腺导管腺癌的因果关系：一项孟德尔随机化研究[J/OL]. 中华肝脏外科手术学电子杂志, 2025, 14(06): 948-955.

Hongyu Meng, Jinhui Dai, Jiajin Hu, Guanghui Li. Causal relationship between inflammatory cytokines and pancreatic ductal adenocarcinoma: a Mendelian randomization study[J/OL]. Chinese Journal of Hepatic Surgery(Electronic Edition), 2025, 14(06): 948-955.

目的

通过两样本孟德尔随机化（MR）方法探讨炎性细胞因子与胰腺导管腺癌（PDAC）之间的因果关系。

方法

基于全基因组关联研究（GWAS）汇总的91个炎症相关蛋白遗传变异数据和芬兰FinnGen数据库的PDAC结果数据作为分析对象。以逆方差加权（IVW）分析结果作为主要结局指标，MR-Egger、加权中位数、简单模式和加权模式方法作为补充分析。采用一系列的敏感性分析，包括异质性检验、多效性检测和留一法分析等，以评估结果的可靠性。

结果

本研究共筛选出与PDAC有关的46个单核苷酸多态性（SNP），所有SNP均表现出稳健的关联强度（F>10）。MR分析发现，IL-22受体亚单位α1（IL22RA1）、IL-15受体亚单位α（IL15RA）、IL-1α、半胱氨酸-天冬氨酸特异性蛋白酶8（caspase-8）可能与PDAC有因果关系，其中IL22RA1（OR=1.79，95%CI：1.01~3.19）与PDAC风险呈正相关；而IL15RA（OR=0.82，95% CI：0.69~0.98）、IL-1α（OR=0.59，95% CI：0.42~0.83）、caspase-8（OR=0.70，95% CI：0.50~0.96）对PDAC的发生具有负因果作用（P<0.05）。且MR-Egger、加权中位数法、简单模式和加权模式的分析结果与IVW分析结果方向基本一致。MR-Egger和Cochran's Q检验未发现存在水平多效性和异质性；留一法分析未发现对效应估计值影响较大的SNP，表明该因果关系具有一定的稳定性。

结论

MR分析发现IL22RA1与PDAC的发生呈正相关，而IL15RA、IL-1α、caspase-8与PDAC的发生呈负相关。PDAC相关炎性细胞因子分析为临床实践中PDAC新的治疗策略提供依据。

关键词: 炎性细胞因子, 胰腺导管腺癌, 孟德尔随机化, 全基因组关联研究
Objective

To investigate the causal relationship between inflammatory cytokines and pancreatic ductal adenocarcinoma (PDAC) by two-sample Mendelian randomization (MR) method.

Methods

The genetic variation data of 91 inflammation-related proteins collected from genome-wide association studies (GWAS) and PDAC outcome data from FinnGen database were used for data analysis. The result of inverse variance weighted (IVW) analysis was utilized as the main outcome index. MR-Egger, weighted median, simple mode and weighted mode methods were used as supplementary analyses. A series of sensitivity analyses, including heterogeneity test, pleiotropic test and leave-one-out analysis, were used to evaluate the reliability of the results.

Results

A total of 46 single nucleotide polymorphism (SNP) related to PDAC were screened in this study, and all SNP showed robust correlations (F>10). MR analysis showed that interleukin-22 receptor subunit α1 (IL22RA1), interleukin-15 receptor subunit α (IL15RA), IL-1α and cysteine aspartatespecific proteinase 8 (caspase-8) might have causal relationship with PDAC, among which IL22RA1 (OR=1.79, 95%CI: 1.01-3.19) was positively correlated with the risk of PDAC. However, IL15RA (OR=0.82, 95%CI: 0.69-0.98), IL-1α (OR=0.59, 95%CI: 0.42-0.83) and caspase-8 (OR=0.70, 95%CI: 0.50-0.96) had negative causal relationships with the incidence of PDAC (all P<0.05). In addition, the results of MR-Egger, weighted median, simple mode and weighted mode methods were basically consistent with those of IVW analysis. MR-Egger and Cochran's Q tests found no horizontal pleiotropy or heterogeneity. Leave-one-out analysis detected no SNP which had significant impact on the estimated effect, indicating that the causal relationship was stable to certain extent.

Conclusions

MR analysis shows that IL22RA1 is positively correlated with the risk of PDAC, whereas IL15RA, IL-1α and caspase-8 are negatively correlated with the incidence of PDAC. Analysis of PDAC-related inflammatory cytokines offers evidence for novel treatment strategy for PDAC in clinical practice.

Key words: Inflammatory cytokines, Pancreatic ductal adenocarcinoma, Mendelian randomization (MR), Genome-wide association study (GWAS)
表1 筛选后46个PDAC相关的SNPs
炎症细胞因子 rsID 效应值 标准误 效应等位基因 其他等位基因 F值
IL22RA1 rs117263973 0.346 7 0.075 2 A G 21.25
rs12240324 0.220 3 0.047 0 A G 21.97
rs13257574 0.271 4 0.058 4 T C 21.59
rs1473089 0.267 9 0.056 1 A C 22.80
rs4811167 0.063 2 0.013 4 T C 22.24
rs56282088 0.281 5 0.057 1 A G 24.30
rs75590335 0.172 2 0.037 0 A G 21.66
rs78594373 -0.127 1 0.027 3 T C 21.67
rs79229049 -0.210 2 0.041 2 A T 26.03
IL15RA rs10125254 0.065 1 0.013 8 A C 22.25
rs117428573 -0.313 2 0.068 4 A C 20.96
rs117484888 0.379 4 0.079 9 A G 22.54
rs12570881 -0.086 7 0.017 4 A T 24.82
rs145793996 -0.227 8 0.049 2 A G 21.43
rs151041734 -0.382 5 0.074 6 T C 26.29
rs192538756 0.115 9 0.024 1 A T 23.12
rs200144408 -0.068 2 0.014 7 T TG 21.52
rs2228059 0.369 2 0.012 7 T G 844.97
rs2836464 0.079 6 0.016 9 A G 22.18
rs4459616 0.140 0 0.029 4 T C 22.67
rs6845172 0.077 8 0.016 2 C G 23.06
rs7898286 -0.196 7 0.013 5 T G 212.26
IL-1α rs10233998 0.131 0 0.028 6 T G 20.98
rs115602471 0.221 5 0.046 9 T C 22.30
rs117537822 0.217 6 0.043 9 T C 24.56
rs11759846 -0.326 3 0.026 6 A G 150.45
rs11878153 0.111 6 0.022 1 A G 25.50
rs12047801 0.078 3 0.017 1 T C 20.96
rs16886503 0.243 8 0.052 4 A T 21.64
rs4767214 0.062 0 0.013 0 T C 22.74
rs523604 0.075 4 0.014 2 A G 28.19
rs61098036 -0.085 6 0.018 7 A G 20.95
rs7138689 0.096 1 0.020 8 T G 21.34
caspase-8 rs1032417 -0.085 8 0.016 5 C G 27.04
rs1034059 0.068 1 0.014 5 A G 22.05
rs111764025 0.109 5 0.023 8 C G 21.16
rs11695193 -0.080 6 0.016 2 A T 24.75
rs11709039 0.078 1 0.016 8 T C 21.61
rs137887001 0.231 8 0.048 6 C G 22.75
rs140844269 -0.361 5 0.077 6 C G 21.70
rs148608719 0.347 4 0.068 3 A G 25.87
rs187405204 0.419 5 0.091 2 T C 21.16
rs34154371 -0.201 6 0.042 2 T C 22.82
rs56328050 -0.198 7 0.017 3 C G 131.90
rs73306603 0.204 4 0.041 2 T C 24.61
rs78449258 -0.200 1 0.042 8 A G 21.85
表2 炎性细胞因子与PDAC的MR分析结果
暴露 SNPs MR方法 P值 OR 95%CI
IL22RA1 9 IVW 0.047 1.79 1.01~3.19
IL15RA 13 IVW 0.029 0.82 0.69~0.98
IL-1α 11 IVW 0.002 0.59 0.42~0.83
caspase-8 13 IVW 0.028 0.70 0.50~0.96
图1 MR分析炎性细胞因子与PDAC风险的散点图 注：IL22RA1为IL-22受体亚单位α1，IL15RA为IL-15受体亚单位α，caspase-8为半胱氨酸-天冬氨酸特异性蛋白酶8，PDAC为胰腺导管腺癌，MR为孟德尔随机化，IVW为逆方差加权，SNP为单核甘酸多态性
表3 炎性细胞因子与PDAC风险MR敏感性分析的异质性和多效性检验结果
暴露 方法 Cochran's Q检验值 异质性检验(P) 多效性检验(P)
IL22RA1 MR-Egger 6.66 0.465 0.065
IVW 11.42 0.179
IL15RA MR-Egger 10.12 0.519 0.679
IVW 10.30 0.589
IL-1α MR-Egger 6.05 0.735 0.251
IVW 7.56 0.672
caspase-8 MR-Egger 10.43 0.493 0.893
IVW 10.44 0.577
图2 炎性细胞因子与PDAC风险MR留一法敏感性分析 注：IL22RA1为IL-22受体亚单位α1，IL15RA为IL-15受体亚单位α，caspase-8为半胱氨酸-天冬氨酸特异性蛋白酶8，PDAC为胰腺导管腺癌，MR为孟德尔随机化
[1]
Siegel RL, Miller KD, Fuchs HE, et al. Cancer statistics, 2021[J]. CA Cancer J Clin, 2021, 71(1): 7-33. DOI: 10.3322/caac.21654.
[2]
Sung H, Ferlay J, Siegel RL, et al. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries[J]. CA Cancer J Clin, 2021, 71(3): 209-249. DOI: 10.3322/caac.21660.
[3]
Raja Arul GL, Toruner MD, Gatenby RA, et al. Ecoevolutionary biology of pancreatic ductal adenocarcinoma[J]. Pancreatology, 2022, 22(6): 730-740. DOI: 10.1016/j.pan.2022.06.005.
[4]
Hu ZI, O'Reilly EM. Therapeutic developments in pancreatic cancer[J]. Nat Rev Gastroenterol Hepatol, 2024, 21(1): 7-24. DOI: 10.1038/s41575-023-00840-w.
[5]
Shah A, Ganguly K, Rauth S, et al. Unveiling the resistance to therapies in pancreatic ductal adenocarcinoma[J]. Drug Resist Updat, 2024, 77: 101146. DOI: 10.1016/j.drup.2024.101146.
[6]
Zhao H, Wu L, Yan G, et al. Inflammation and tumor progression: signaling pathways and targeted intervention[J]. Signal Transduct Target Ther, 2021, 6(1): 263. DOI: 10.1038/s41392-021-00658-5.
[7]
Denk D, Greten FR. Inflammation: the incubator of the tumor microenvironment[J]. Trends Cancer, 2022, 8(11): 901-914. DOI: 10.1016/j.trecan.2022.07.002.
[8]
Yang L, Qiao S, Zhang G, et al. Inflammatory processes: key mediators of oncogenesis and progression in pancreatic ductal adenocarcinoma (PDAC)[J]. Int J Mol Sci, 2024, 25(20): 10991. DOI: 10.3390/ijms252010991.
[9]
Landskron G, De la Fuente M, Thuwajit P, et al. Chronic inflammation and cytokines in the tumor microenvironment[J]. J Immunol Res, 2014, 2014: 149185. DOI: 10.1155/2014/149185.
[10]
Hu X, Zhao J, Lin Z, et al. Mendelian randomization for causal inference accounting for pleiotropy and sample structure using genome-wide summary statistics[J]. Proc Natl Acad Sci USA, 2022, 119(28): e2106858119. DOI: 10.1073/pnas.2106858119.
[11]
Chen LG, Tubbs JD, Liu Z, et al. Mendelian randomization: causal inference leveraging genetic data[J]. Psychol Med, 2024, 54(8): 1461-1474. DOI: 10.1017/S0033291724000321.
[12]
Tam V, Patel N, Turcotte M, et al. Benefits and limitations of genome-wide association studies[J]. Nat Rev Genet, 2019, 20(8): 467-484. DOI: 10.1038/s41576-019-0127-1.
[13]
Cano-Gamez E, Trynka G. From GWAS to function: using functional genomics to identify the mechanisms underlying complex diseases[J]. Front Genet, 2020, 11: 424. DOI: 10.3389/fgene.2020.00424.
[14]
Zhao JH, Stacey D, Eriksson N, et al. Genetics of circulating inflammatory proteins identifies drivers of immune-mediated disease risk and therapeutic targets[J]. Nat Immunol, 2023, 24(9): 1540-1551. DOI: 10.1038/s41590-023-01588-w.
[15]
Liu B, Lyu L, Zhou W, et al. Associations of the circulating levels of cytokines with risk of amyotrophic lateral sclerosis: a Mendelian randomization study[J]. BMC Med, 2023, 21(1): 39. DOI: 10.1186/s12916-023-02736-7.
[16]
Fang P, Liu X, Qiu Y, et al. Exploring causal correlations between inflammatory cytokines and ankylosing spondylitis: a bidirectional mendelian-randomization study[J]. Front Immunol, 2023, 14: 1285106. DOI: 10.3389/fimmu.2023.1285106.
[17]
Bowden J, Del Greco M F, Minelli C, et al. Assessing the suitability of summary data for two-sample Mendelian randomization analyses using MR-Egger regression: the role of the I2 statistic[J]. Int J Epidemiol, 2016, 45(6): 1961-1974. DOI: 10.1093/ije/dyw220.
[18]
Burgess S, Scott RA, Timpson NJ, et al. Using published data in mendelian randomization: a blueprint for efficient identification of causal risk factors[J]. Eur J Epidemiol, 2015, 30(7): 543-552. DOI: 10.1007/s10654-015-0011-z.
[19]
Bowden J, Davey Smith G, Haycock PC, et al. Consistent estimation in mendelian randomization with some invalid instruments using a weighted Median estimator[J]. Genet Epidemiol, 2016, 40(4): 304-314. DOI: 10.1002/gepi.21965.
[20]
Hartwig FP, Davey Smith G, Bowden J. Robust inference in summary data Mendelian randomization via the zero modal pleiotropy assumption[J]. Int J Epidemiol, 2017, 46(6): 1985-1998. DOI: 10.1093/ije/dyx102.
[21]
Cohen JF, Chalumeau M, Cohen R, et al. Cochran's Q test was useful to assess heterogeneity in likelihood ratios in studies of diagnostic accuracy[J]. J Clin Epidemiol, 2015, 68(3): 299-306. DOI: 10.1016/j.jclinepi.2014.09.005.
[22]
Garrity PA, Chen D, Rothenberg EV, et al. Interleukin-2 transcription is regulated in vivo at the level of coordinated binding of both constitutive and regulated factors[J]. Mol Cell Biol, 1994, 14(3): 2159-2169. DOI: 10.1128/mcb.14.3.2159-2169.1994.
[23]
Sekula P, Fabiola Greco M, Pattaro C, et al. Mendelian randomization as an approach to assess causality using observational data[J]. J Am Soc Nephrol, 2016, 27(11): 3253-3265. DOI: 10.1681/ASN.2016010098.
[24]
Kurz E, Hirsch CA, Dalton T, et al. Exercise-induced engagement of the IL-15/IL-15Rα axis promotes anti-tumor immunity in pancreatic cancer[J]. Cancer Cell, 2022, 40(7): 720-737. e5. DOI: 10.1016/j.ccell.2022.05.006.
[25]
Pimentel JM, Zhou JY, Wu GS. The role of TRAIL in apoptosis and immunosurveillance in cancer[J]. Cancers, 2023, 15(10): 2752. DOI: 10.3390/cancers15102752.
[26]
Di Cristofano F, George A, Tajiknia V, et al. Therapeutic targeting of TRAIL death receptors[J]. Biochem Soc Trans, 2023, 51(1): 57-70. DOI: 10.1042/BST20220098.
[27]
Davidovich P, Higgins CA, Najda Z, et al. cFLIPL acts as a suppressor of TRAIL-and Fas-initiated inflammation by inhibiting assembly of caspase-8/FADD/RIPK1 NF-κB-activating complexes[J]. Cell Rep, 2023, 42(12): 113476. DOI: 10.1016/j.celrep.2023.113476.
[28]
Wang Y, Qian X, Wang Y, et al. Turn TRAIL into better anticancer therapeutic through TRAIL fusion proteins[J]. Cancer Med, 2025, 14(1): e70517. DOI: 10.1002/cam4.70517.
[29]
Moeng S, Son SW, Seo HA, et al. Luteolin-regulated microRNA-301-3p targets caspase-8 and modulates TRAIL sensitivity in PANC-1 cells[J]. Anticancer Res, 2020, 40(2): 723-731. DOI: 10.21873/anticanres.14003.
[30]
Hunzeker ZE, Zhao L, Kim AM, et al. The role of IL-22 in cancer[J]. Med Oncol, 2024, 41(10): 240. DOI: 10.1007/s12032-024-02481-8.
[31]
Huang Y, Yu F, Ding Y, et al. Hepatic IL22RA1 deficiency promotes hepatic steatosis by modulating oxysterol in the liver[J]. Hepatology, 2025, 81(5): 1564-1582. DOI: 10.1097/HEP.0000000000000998.
[32]
Zhang S, Yang G. IL22RA1/JAK/STAT signaling acts as a cancer target through pan-cancer analysis[J]. Front Immunol, 2022, 13: 915246. DOI: 10.3389/fimmu.2022.915246.
[33]
He W, Wu J, Shi J, et al. IL22RA1/STAT3 signaling promotes stemness and tumorigenicity in pancreatic cancer[J]. Cancer Res, 2018, 78(12): 3293-3305. DOI: 10.1158/0008-5472.CAN-17-3131.
[34]
Tjomsland V, Spångeus A, Välilä J, et al. Interleukin 1α sustains the expression of inflammatory factors in human pancreatic cancer microenvironment by targeting cancer-associated fibroblasts[J]. Neoplasia, 2011, 13(8): 664-675. DOI: 10.1593/neo.11332.
[35]
Broderick L, Hoffman HM. IL-1 and autoinflammatory disease: biology, pathogenesis and therapeutic targeting[J]. Nat Rev Rheumatol, 2022, 18(8): 448-463. DOI: 10.1038/s41584-022-00797-1.
[36]
Gelfo V, Romaniello D, Mazzeschi M, et al. Roles of IL-1 in cancer: from tumor progression to resistance to targeted therapies[J]. Int J Mol Sci, 2020, 21(17): 6009. DOI: 10.3390/ijms21176009.
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