91种炎症蛋白水平与急性髓系白血病发病风险相关的孟德尔随机化研究

摘要/Abstract

摘要：

目的：分析循环炎症蛋白与急性髓系白血病（acute myeloid leukemia，AML）发生风险间的相关性。方法：从FinnGen联盟获取AML数据，以91种循环炎症蛋白的全基因组关联研究（Genome-Wide Association Studies，GWAS）数据作为暴露因素，使用孟德尔随机化（Mendelian randomization，MR）分析评估91种循环炎症蛋白对AML发生风险的影响。采用逆方差加权法（Inverse Variance Weighted，IVW）作为主要分析方法，用MR-Egger和加权中位数（Weighted Median，WM）方法进一步强化结果。此外，用敏感性分析评估结果的稳定性和可靠性。结果：91种循环炎症蛋白中有8种与AML的发生有因果关联（P<0.05）。其中，神经鞘胚素（artemin，ARTN）(OR=0.458 3，95%CI为0.219 0~0.959 1)、白细胞介素（interleukin, IL）-2受体β(OR=0.2347，95%CI为0.094 1~0.585 3)、沉默蛋白2（sirtuin-2，SIRT2）(OR=0.310 4，95%CI为0.138 0~0.698 2)、信号转导接头分子结合蛋白（signal-transducing adaptor mo-lecule binding protein，STAMPB） (OR=0.289 0，95%CI为0.104 9~0.796 1)水平升高与AML发生风险降低相关；而CD6(OR=3.269 3，95%CI为1.285 3~8.315 9)、趋化因子配体5（C-X-C motif chemokine ligand 5，CXCL5）(OR=1.694 6，95%CI为1.013 4~2.833 6)、IL-15受体α (OR=1.572 9，95%CI为1.050 0~2.344 8)、基质金属蛋白酶（matrix metalloproteinase，MMP）-10(OR=1.882 0，95%CI为1.061 4~3.337 1)水平升高与AML发生风险升高相关。使用Cochran’s Q检验（P>0.05）和MR-Egger回归检验（P>0.05）进行敏感性分析，结果显示炎症蛋白的单核苷酸多态性（singlenucleotide polymorphisms，SNP)之间没有异质性和多效性。结论：基于MR研究提示，循环炎症蛋白ARTN、IL-2RB、SIRT2和STAMPB水平与AML发生风险呈负相关，CD6、CXCL5、IL-15RA和MMP-10水平与AML发生风险呈正相关，为今后AML的病理机制研究提供一定的参考信息。

关键词:急性髓系白血病,孟德尔随机化分析,全基因组关联研究,细胞免疫治疗

Abstract:

ObjectiveThe study aims to analyze the correlation between circulating inflammatory proteins and the risk of acute myeloid leukemia (AML).MethodsAML data were obtained from the FinnGen alliance as the outcome. The Genome-wide Association Studies (GWAS) data of 91 circulating inflammatory proteins were used as exposure factors. Mendelian randomization (MR) analysis was conducted to evaluate the effects of 91 circulating inflammatory proteins on the risk of AML. Inverse Variance Weighted (IVW) was used as the main analysis method, and the MR-Egger and Weighted Median (WM) methods were used to further strengthen the results. In addition, sensitivity analysis was used to evaluate the stability and reliability of the results.ResultsAmong the 91 circulating inflammatory proteins, 8 were causally associated with the occurrence of AML (P<0.05). Specifically, higher levels of artemin (ARTN) (OR=0.458 3, 95% CI: 0.219 0-0.959 1), interleukin (IL)-2 receptor β (OR=0.2347, 95% CI: 0.094 1-0.585 3), sirtuin-2 (SIRT2) (OR=0.310 4, 95%CI: 0.138 0-0.698 2), and signal-transducing adaptor molecule binding protein (STAMPB) (OR=0.289 0, 95% CI: 0.104 9-0.796 1) were associated with a reduced risk of AML. In contrast, higher levels of CD6 (OR=3.269 3, 95% CI: 1.285 3-8.315 9), C-X-C motif chemokine ligand 5 (CXCL5) (OR=1.694 6, 95% CI: 1.013 4-2.833 6), IL-15 receptor α (OR=1.572 9, 95% CI: 1.050 0-2.344 8), and matrix metalloproteinase (MMP)-10 (OR=1.882 0, 95% CI: 1.061 4-3.337 1) were associated with an increased risk of AML. Sensitivity analysis using Cochran’s Q test (P>0.05) and MR-Egger regression test (P>0.05) showed no heterogeneity or pleiotropy in the single nucleotide polymorphisms (SNPs) of inflammatory proteins.ConclusionsThe Mendelian randomization study suggests that circulating inflammatory proteins ARTN, IL-2β, SIRT2, STAMPB, CD6, CXCL-5, IL-15α, and MMP-10 are causally associated with the risk of AML, which provides valuable insights for future research on the pathological mechanism of AML.

Key words:Acute myeloid leukemia,Mendelian randomization analysis,Genome-wide association study,Cellular immunotherapy

中图分类号:

安慧慧, 吴涛, 刘文慧, 田思锐. 91种炎症蛋白水平与急性髓系白血病发病风险相关的孟德尔随机化研究[J]. 诊断学理论与实践, 2024, 23(05): 509-516.

AN Huihui, WU Tao, LIU Wenhui, TIAN Sirui. A Mendelian randomized study on the correlation between 91 inflammatory protein levels and the risk of acute myeloid leukemia[J]. Journal of Diagnostics Concepts & Practice, 2024, 23(05): 509-516.

图/表4

图1

表1

循环炎症蛋白和急性髓系白血病发生风险的孟德尔随机化分析结果

Exposure	Outcomes	SNPs	IVW			MR-Egger			Weighted median
Exposure	Outcomes	SNPs	SE	OR (95%CI)	P	SE	OR (95%CI)	P	SE	OR (95%CI)	P
ARTN	AML	14	0.3768	0.4583（0.2190-0.9591）	0.0384	0.8732	0.3252（0.0587-1.8007）	0.2226	0.5050	0.3688（0.1371-0.9922）	0.0482
CD6	AML	6	0.4763	3.2693(1.2853-8.3159)	0.0129	1.7673	2.4846(0.0778-79.3565)	0.6337	0.5444	3.1903(1.0975-9.2740)	0.0331
CXCL5	AML	11	0.2623	1.6946(1.0134-2.8336)	0.0443	0.3990	1.5728(0.7196-3.4377)	0.2857	0.2694	1.7337(1.0224-2.9397)	0.0411
IL-15RA	AML	9	0.2037	1.5729(1.0550-2.3448)	0.0262	0.3623	0.8618(0.4237-1.7531)	0.6937	0.2276	1.4059(0.9000-2.1962)	0.1344
IL-2RB	AML	11	0.4662	0.2347(0.0941-0.5853)	0.0019	0.9384	0.5465(0.0869-3.4385)	0.5357	0.6405	0.3298(0.0940-1.1573)	0.0833
MMP-10	AML	11	0.2922	1.8820(1.0614-3.3371)	0.0305	0.4725	1.6175(0.6407-4.0836)	0.3354	0.3657	1.7830(0.8707-3.6512)	0.1138
SIRT2	AML	11	0.4136	0.3104(0.1380-0.6982)	0.0047	0.8396	0.1697(0.0327-0.8798)	0.0638	0.5670	0.2611(0.0859-0.7935)	0.0179
STAMPB	AML	10	0.5171	0.2890(0.1049-0.7961)	0.0164	1.5349	0.2560(0.0126-5.1855)	0.4006	0.7170	0.2570(0.0630-1.0477)	0.0581

表1

图2

表2

循环炎症蛋白和急性髓系白血病发生风险的敏感性分析结果

exposure	Outcomes	SNPs	Cochran’s Q test		MR-Egger intercept		MR-Presso
exposure	Outcomes	SNPs	IVW	MR Egger	Egger intercept	P	Global Test RSSobs	P
ARTN	AML	14	10.7366	10.5471	0.0349	0.6711	12.2728	0.6667
CD6	AML	6	1.4264	1.4004	0.0242	0.8797	0.9447	0.9447
CXCL5	AML	11	12.5723	12.4797	0.0170	0.8019	13.4745	0.4093
IL-15RA	AML	9	7.0478	3.0151	0.1516	0.0846	16.1052	0.4327
IL-2RB	AML	11	7.7765	6.6991	-0.1012	0.3264	9.3245	0.6887
MMP-10	AML	11	10.1907	9.9951	0.0315	0.6845	11.2204	0.5253
SIRT2	AML	11	10.4870	9.7401	0.0838	0.4276	12.7845	0.4190
STAMPB	AML	10	8.5948	8.5872	0.0148	0.9350	10.8371	0.4917

表2

参考文献48

[1]	章新, 郑莹. 2005—2020年中国国家及分省疾病监测点的肿瘤死亡疾病负担数据解读[J].诊断学理论与实践,2024,23(4):371-377.
	ZHANG X, ZHENG Y. Interpretation of cancer death burden data from disease surveillance sites in China from 2005 to 2020[J].J Diagn Concepts Pract,2024,23(4):371-377.
[2]	DE KOUCHKOVSKY I, ABDUL-HAY M. Acute myeloid leukemia: a comprehensive review and 2016 update[J].Blood Cancer J,2016,6(7):e441.
[3]	DÖHNER H, ESTEY E H, AMADORI S, et al. Diagnosis and management of acute myeloid leukemia in adults: recommendations from an international expert panel, on behalf of the European LeukemiaNet[J].Blood,2010,115(3):453-474. doi:10.1182/blood-2009-07-235358pmid:19880497
[4]	WHITELEY A E, PRICE T T, CANTELLI G, et al. Leukaemia: a model metastatic disease[J].Nat Rev Cancer,2021,21(7):461-475. doi:10.1038/s41568-021-00355-zpmid:33953370
[5]	DINARELLO C A. Anti-inflammatory agents: present and future[J].Cell,2010,140(6):935-950. doi:10.1016/j.cell.2010.02.043pmid:20303881
[6]	ZHAO J H, 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-wpmid:37563310
[7]	ELLEGAST J M, ALEXE G, HAMZE A, et al. Unleas-hing cell-intrinsic inflammation as a strategy to kill aml blasts[J].Cancer Discov,2022,12(7):1760-1781.
[8]	BOWDEN J, HOLMES M V. Meta-analysis and Mendelian randomization: a review[J].Res Synth Methods,2019,10(4):486-496. doi:10.1002/jrsm.1346pmid:30861319
[9]	ZHU M, MA Z, ZHANG X, et al. C-reactive protein and cancer risk: a pan-cancer study of prospective cohort and Mendelian randomization analysis[J].BMC Med,2022,20(1):301. doi:10.1186/s12916-022-02506-xpmid:36117174
[10]	WANG Q, SHI Q, WANG Z, et al. Integrating plasma proteomes with genome-wide association data for causal protein identification in multiple myeloma[J].BMC Med,2023,21(1):377. doi:10.1186/s12916-023-03086-0pmid:37775746
[11]	CHEN J, XU F, RUAN X, et al. Therapeutic targets for inflammatory bowel disease: proteome-wide Mendelian randomization and colocalization analyses[J].EBioMedicine,2023,89:104494.
[12]	KURKI M I, KARJALAINEN J, PALTA P, et al. FinnGen provides genetic insights from a well-phenotyped isolated population[J].Nature,2023,613(7944):508-518.
[13]	SEKULA P, DEL GRECO M F, 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. pmid:27486138
[14]	DAVIES N M, HOLMES M V, DAVEY SMITH G. Rea-ding Mendelian randomisation studies: a guide, glossary, and checklist for clinicians[J].BMJ,2018,362:k601.
[15]	STALEY J R, BLACKSHAW J, KAMAT M A, et al. PhenoScanner: a database of human genotype-phenotype associations[J].Bioinformatics,2016,32(20):3207-3209. pmid:27318201
[16]	SEKULA P, DEL GRECO M F, 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. pmid:27486138
[17]	BOWDEN J, DEL GRECO M F, MINELLI C, et al. A framework for the investigation of pleiotropy in two-sample summary data Mendelian randomization[J].Stat Med,2017,36(11):1783-1802. doi:10.1002/sim.7221pmid:28114746
[18]	BURGESS S, THOMPSON S G. Interpreting findings from Mendelian randomization using the MR-Egger method[J].Eur J Epidemiol,2017,32(5):377-389. doi:10.1007/s10654-017-0255-xpmid:28527048
[19]	BOWDEN J, DAVEY SMITH G, HAYCOCK P C, 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.21965pmid:27061298
[20]	HEMANI G, BOWDEN J, DAVEY SMITH G. Evaluating the potential role of pleiotropy in Mendelian randomization studies[J].Hum Mol Genet,2018,27(R2):R195-R208.
[21]	VERBANCK M, CHEN CY, NEALE B, et al. Detection of widespread horizontal pleiotropy in causal relationships inferred from Mendelian randomization between complex traits and diseases[J].Nat Genet,2018,50(5):693-698. doi:10.1038/s41588-018-0099-7pmid:29686387
[22]	GIL-LIANES J, LUQUE-LUNA M, ALAMON-REIG F, et al. Sweet syndrome: clinical presentation, malignancy association, autoinflammatory disorders and treatment Response in a Cohort of 93 Patients with Long-term Follow-up[J].Acta Derm Venereol,2023,103:adv18284.
[23]	KRISTINSSON S Y, BJÖRKHOLM M, HULTCRANTZ M, et al. Chronic immune stimulation might act as a trigger for the development of acute myeloid leukemia or mye-lodysplastic syndromes[J].J Clin Oncol,2011,29(21):2897-2903.
[24]	INOUE T, HIRATSUKA M, OSAKI M, et al. The molecular biology of mammalian SIRT proteins: SIRT2 in cell cycle regulation[J].Cell Cycle,2007,6(9):1011-1018. doi:10.4161/cc.6.9.4219pmid:17457050
[25]	NAKAGAWA T, GUARENTE L. Sirtuins at a glance[J].J Cell Sci,2011,124(Pt 6):833-838. doi:10.1242/jcs.081067pmid:21378304
[26]	RUSSO C, MAUGERI A, DE LUCA L, et al. The SIRT2 pathway is involved in the antiproliferative effect of flavanones in human leukemia monocytic THP-1 cells[J].Biomedicines,2022,10(10):2383.
[27]	STRZALKA P, KRAWIEC K, JARYCH D, et al. Assessment of SIRT1-SIRT7 and TP53 genes expression in patients with acute myeloid leukemia[J].Blood,2023,142:6048.
[28]	DENG A, NING Q, ZHOU L, et al. SIRT2 is an unfavo-rable prognostic biomarker in patients with acute myeloid leukemia[J].Sci Rep,2016,6:27694.
[29]	XU H, LI Y, CHEN L, et al. SIRT2 mediates multidrug resistance in acute myelogenous leukemia cells via ERK1/2 signaling pathway[J].Int J Oncol,2016,48(2):613-623. doi:10.3892/ijo.2015.3275pmid:26647771
[30]	LUO Y, ZHAO H, ZHU J, et al. SIRT2 inhibitor SirReal2 enhances anti-tumor effects of PI3K/mTOR inhibitor VS-5584 on acute myeloid leukemia cells[J].Cancer Med,2023,12(18):18901-18917.
[31]	HEZAM K, JIANG J, SUN F, et al. Artemin promotes oncogenicity, metastasis and drug resistance in cancer cells[J].Rev Neurosci,2018,29(1):93-98.
[32]	BANERJEE A, WU Z S, QIAN P, et al. ARTEMIN synergizes with TWIST1 to promote metastasis and poor survival outcome in patients with ER negative mammary carcinoma[J].Breast Cancer Res,2011,13(6):R112.
[33]	JIANG X, CHEN K, FAN K, et al. Prognostic significance of artemin in gastric cancer and its role in tumorigenesis[J].Transl Cancer Res,2020,9(1):12-20. doi:10.21037/tcr.2019.11.13pmid:35117153
[34]	WANG X H, LIU Y N, TIAN K, et al. Expression and clinical significance of ARTN and MMP-9 in endometrial carcinoma[J].J Biol Regul Homeost Agents,2017,31(4):879-887.
[35]	XU H, YANG X, XUAN X, et al. STAMBP promotes lung adenocarcinoma metastasis by regulating the EGFR/MAPK signaling pathway[J].Neoplasia,2021,23(6):607-623. doi:10.1016/j.neo.2021.05.011pmid:34102455
[36]	YANG Q, YAN D, ZOU C, et al. The deubiquitinating enzyme STAMBP is a newly discovered driver of triple-negative breast cancer progression that maintains RAI14 protein stability[J].Exp Mol Med,2022,54(11):2047-2059. doi:10.1038/s12276-022-00890-1pmid:36434041
[37]	KITTANG A O, SAND K, BRENNER A K, et al. The systemic profile of soluble immune mediators in patients with myelodysplastic syndromes[J].Int J Mol Sci,2016,17(7):1080.
[38]	PARDANANI A, FINKE C, LASHO T L, et al. IPSS-independent prognostic value of plasma CXCL10, IL-7 and IL-6 levels in myelodysplastic syndromes[J].Leukemia,2012,26(4):693-699. doi:10.1038/leu.2011.251pmid:21912394
[39]	BRUSERUD Ø, RYNINGEN A, OLSNES A M, et al. Subclassification of patients with acute myelogenous leukemia based on chemokine responsiveness and constitutive chemokine release by their leukemic cells[J].Haematologica,2007,92(3):332-341. doi:10.3324/haematol.10148pmid:17339182
[40]	CAO H, TADROS V, HIRAMOTO B, et al. Targeting TKI-activated NFKB2-MIF/CXCLs-CXCR2 signaling pathways in FLT3 mutated acute myeloid leukemia reduced blast viability[J].Biomedicines,2022,10(5):1038.
[41]	SUI S, LI Z, TAN J, et al. Low expression of CD5 and CD6 is associated with poor overall survival for patients with T-cell malignancies[J].J Oncol,2022,2022:2787426.
[42]	STRATMANN S, YONES S A, GARBULOWSKI M, et al. Transcriptomic analysis reveals proinflammatory signatures associated with acute myeloid leukemia progression[J].Blood Adv,2022,6(1):152-164.
[43]	RAMBALDI B, KIM H T, ARIHARA Y, et al. Phenotypic and functional characterization of the CD6-ALCAM T-cell co-stimulatory pathway after allogeneic cell transplantation[J].Haematologica,2022,107(11):2617-2629.
[44]	SOIFFER R J, FAIRCLOUGH D, ROBERTSON M, et al. CD6-depleted allogeneic bone marrow transplantation for acute leukemia in first complete remission[J].Blood,1997,89(8):3039-3047. pmid:9108425
[45]	ROWLEY J, MONIE A, HUNG C F, et al. Expression of IL-15RA or an IL-15/IL-15RA fusion on CD8+ T cells modifies adoptively transferred T-cell function in cis[J].Eur J Immunol,2009,39(2):491-506. doi:10.1002/eji.200838594pmid:19180469
[46]	ZHANG Y, ZHUANG Q, WANG F, et al. Co-expression IL-15 receptor alpha with IL-15 reduces toxicity via limi-ting IL-15 systemic exposure during CAR-T immunotherapy[J].J Transl Med,2022,20(1):432.
[47]	REIKVAM H, HATFIELD K J, OYAN A M, et al. Primary human acute myelogenous leukemia cells release matrix metalloproteases and their inhibitors: release profile and pharmacological modulation[J].Eur J Haematol,2010,84(3):239-251. doi:10.1111/j.1600-0609.2009.01382.xpmid:19922462
[48]	HATFIELD K J, REIKVAM H, BRUSERUD Ø. The crosstalk between the matrix metalloprotease system and the chemokine network in acute myeloid leukemia[J].Curr Med Chem,2010,17(36):4448-4461. pmid:21062258