lncRNAs与肺腺癌因果关联的两样本孟德尔随机化研究

孙继宏; 丛静; 王萍玉

doi:10.16462/j.cnki.zhjbkz.2023.11.017

lncRNAs与肺腺癌因果关联的两样本孟德尔随机化研究

doi: 10.16462/j.cnki.zhjbkz.2023.11.017

1.
滨州医学院公共卫生与管理学院流行病学教研室，烟台 264003
2.
滨州医学院公共卫生与管理学院流行病学教研室，烟台市疾病预防控制中心公共卫生科，烟台 264003

基金项目:

国家自然科学基金 81772281

山东省自然科学基金 ZR2020KH015

详细信息

通讯作者:
王萍玉，E-mail：wpingyugirl@163.com

中图分类号: R734.2
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- 被引次数: 0
出版历程
- 收稿日期: 2022-01-20
- 修回日期: 2022-06-09
- 网络出版日期: 2023-11-20
- 刊出日期: 2023-11-10

A two-sample Mendelian randomized study of causality between lncRNAs and lung adenocarcinoma

1.
Department of Epidemiology, School of Public Health and Management, Binzhou Medical University, Yantai 264003, China
2.
Department of Epidemiology, School of Public Health and Management, Binzhou Medical University, Public Health Division, Yantai Center for Disease Control and Prevention, Yantai 264003, China

Funds:

National Natural Science Foundation of China 81772281

Natural Science Foundation of Shandong Province ZR2020KH015

More Information

Corresponding author: WANG Pingyu, E-mail: wpingyugirl@163.com

摘要

摘要: 目的利用两样本孟德尔随机化方法探究长链非编码RNAs(long-chain non-coding RNAs, lncRNAs)与肺腺癌发病风险之间的因果关联。方法采用肺腺癌全基因组关联分析数据和eQTL Gene联盟的cis-eQTL数据集，将与肺腺癌密切相关的单核苷酸多态性(single nucleotide polymorphisms, SNPs)作为工具变量，运用逆方差加权法、MR-Egger回归模型、加权中位数分析法、简单模式法和加权模式法5种两样本孟德尔随机化(Mendelian randomization, MR)模型来评估lncRNAs与肺腺癌之间的因果效应，并进行异质性检验、基因多效性检验和敏感性分析来评估结果的可靠性和稳定性。结果 PVT1、LINC00824、Z94721.1与肺腺癌的关联效应值差异有统计学意义(均P＜0.05)，PVT1(与肺腺癌的效应值OR=0.79，95% CI：0.71~0.89)、LINC00824(与肺腺癌的效应值OR=0.59，95% CI：0.42~0.83)降低了原发性支气管肺癌(肺癌)的发病风险；而Z94721.1(与肺腺癌的效应值OR=1.09，95% CI：1.03~1.16)增加肺癌的发病风险，并且均通过了异质性检验、基因多效性检验和敏感性分析。结论 PVT1、LINC00824、Z94721.1 3个lncRNAs与肺腺癌之间存在稳定的因果关联，为肺腺癌发病机制的研究提供了重要理论依据。
- 孟德尔随机化 /
- 长链非编码RNAs /
- 肺腺癌 /
- 因果推断
Abstract: Objective A two-sample Mendelian randomization method was used to investigate the causal relationship between long-chain non-coding RNAs(lncRNAs) and the risk of lung adenocarcinoma. Methods The genome-wide association study data of lung adenocarcinoma and the cis-eQTL data set of eQTL Gene Alliance were used. The single nucleotide polymorphisms (SNPs) closely related to lung adenocarcinoma was used as a tool variable. Five two-sample Mendelian randomization models, including the inverse variance weighting method, MR-Egger regression model, weighted median analysis method, simple mode method and weighted mode method, were applied to evaluate the causal effect between lncRNAs and the risk of lung adenocarcinoma. Moreover, the heterogeneity test, gene pleiotropy test and sensitivity analysis were carried out to evaluate the reliability and stability of the results. Results PVT1, LINC00824, Z94721.1 exhibited significant association with lung adenocarcinoma (all P < 0.05). The OR was 0.79 (95% CI: 0.71-0.89) for PVT1 and 0.59 (95% CI: 0.42-0.83) for LINC00824, indicating that both PVT1 and LINC00824 reduced the risk of lung cancer. The OR was 1.09 (95% CI: 1.03-1.16) for Z94721.1, showing that Z94721.1 increased the risk of lung cancer. All passed the heterogeneity test, gene pleiotropy test and sensitivity analysis. Conclusions The three lncRNAs, PVT1, LINC00824 and Z94721.1, have stable causal association with lung adenocarcinoma, providing an important theoretical basis for the study of the pathogenesis of lung adenocarcinoma.
- Mendelian randomization /
- Long non-coding RNAs /
- Lung adenocarcinoma /
- Causal relationship

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图 1 两样本孟德尔随机化研究中工具变量核心假设示意图

Figure 1. Schematic diagram of the core hypothesis of instrumental variables in two-sample mendelian randomization study

下载: 全尺寸图片幻灯片

图 2 3个lncRNA的5种MR模型散点图

MR：孟德尔随机化；IVW：逆方差加权法；MR Egger：MR-Egger回归；SM：简单模式法；WME: 加权中位数法；WM：加权模式法；LUAD：肺腺癌；SNPs：单核苷酸多态性。

Figure 2. Scatter plots of 5 mendelian randomization models

MR: Mendelian randomization; IVW: inverse variance weighted; MR Egger: mendelian randomization Egger regression; SM: simple mode; WME: weighted median estimator; WM: weighted mode; LUAD: lung adenocarcinoma SNPs: single nucleotide polymorphisms.

下载: 全尺寸图片幻灯片

表 1 lncRNAs的MR分析效应值结果

Table 1. Mendelian randomization estimates of lncRNAs

lncRNAs	Ensembl ID	MR法MR method	SNPs	β	s_x	OR值value (95% CI)	P值value
PVT1	ENSG00000249859	IVW	26	-0.23	0.06	0.79(0.71~0.89)	4.22×10^-5
LINC00824	ENSG00000254275	IVW	3	-0.53	0.18	0.59(0.42~0.83)	2.89×10^-3
Z94721.1	ENSG00000227598	IVW	14	0.09	0.03	1.09(1.03~1.16)	4.08×10^-3
LINC01891	ENSG00000231682	IVW	22	0.03	0.03	1.03(0.98~1.10)	2.56×10^-1
LINC00511	ENSG00000227036	IVW	14	-0.02	0.04	0.98(0.91~1.06)	5.82×10^-1
AC092142.1	ENSG00000261235	Wald Ratio	1	-0.34	0.44	0.71(0.30~1.67)	4.37×10^-1
注：lncRNAs：长链非编码RNAs; MR: 孟德尔随机化; IVW，逆方差加权法；SNPs，单核苷酸多态性。 Notes: lncRNAs：long non-coding RNAs; MR: Mendelian randomization; IVW, inverse variance weighted; SNPs, single nucleotide polymorphisms.

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表 2 lncRNAs的MR分析效应值结果

Table 2. Mendelian randomization estimates of lncRNAs

lncRNAs	Ensemble ID	MR法MR method	β	s_x	OR值value (95% CI)	P值value	P_{异质性检验} P_{heterogeneity}	P_{多效性检验} P_pleiotropy
PVT1	ENSG00000249859	MR Egger	-0.34	0.10	0.71(0.58~0.87)	3.24×10^-3	0.467	0.245
		WME	-0.24	0.08	0.79(0.68~0.92)	2.26×10^-3
		IVW	-0.23	0.06	0.79(0.71~0.89)	4.22×10^-5	0.444	－
		简单模式法Simple mode	-0.25	0.14	0.78(0.60~1.02)	7.84×10^-2
		加权模式法Weighted mode	-0.23	0.08	0.79(0.68~0.92)	6.58×10^-3
LINC00824	ENSG00000254275	MR Egger	-0.35	0.65	0.70(0.20~2.51)	6.85×10^-1	0.392	0.821
		WME	-0.47	0.20	0.62(0.42~0.93)	2.07×10^-2
		IVW	-0.53	0.18	0.59(0.42~0.83)	2.89×10^-3	0.665	－
		简单模式法Simple mode	-0.42	0.25	0.65(0.40~1.07)	2.32×10^-1
		加权模式法Weighted mode	-0.44	0.25	0.64(0.40~1.04)	2.17×10^-1
Z94721.1	ENSG00000227598	MR Egger	0.02	0.06	1.02(0.91~1.14)	7.53×10^-1	0.868	0.175
		WME	0.08	0.04	1.08(1.00~1.18)	5.05×10^-2
		IVW	0.09	0.03	1.09(1.03~1.16)	4.08×10^-3	0.779	－
		简单模式法Simple mode	0.07	0.07	1.07(0.93~1.23)	3.70×10^-1
		加权模式法Weighted mode	0.07	0.05	1.07(0.97~1.17)	1.82×10^-1
注：1. lncRNAs：长链非编码RNAs; MR: 孟德尔随机化; MR Egger，MR-Egger回归；WME，加权中位数法；IVW，逆方差加权法。 2. “－”表示无数值。 Notes: 1. lncRNAs：long non-coding RNAs; MR: Mendelian randomization; MR Egger, Mendelian randomization Egger regression; WME, weighted median estimator; IVW, inverse variance weighted. 2. "－" represents an infinite number of value.

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参考文献(18)

[1]	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.
[2]	Hutchinson BD, Shroff GS, Truong MT, et al. Spectrum of lung adenocarcinoma[J]. Semin Ultrasound CT MR, 2019, 40(3): 255-264. DOI: 10.1053/j.sult.2018.11.009.
[3]	王宇松, 吉晓莹, 穆楠, 等. 非小细胞肺癌分子靶向治疗标志物研究进展[J]. 中国癌症防治杂志, 2020, 12(3): 285-290. DOI: 10.3969/j.issn.1674-5671.2020.03.09. Wang YS, Ji XY, Mu N, et al. Research progress of molecular targeted therapy markers for non-small cell lung cancer[J]. Chin J Oncol Prev Treat, 2020, 12(3): 285-290. DOI: 10.3969/j.issn.1674-5671.2020.03.09.
[4]	Tsai MC, Manor O, Wan Y, et al. Long noncoding RNA as modular scaffold of histone modification complexes[J]. Science, 2010, 329(5992): 689-693. DOI: 10.1126/science.1192002.
[5]	Feng C, Zhao Y, Li Y, et al. LncRNA MALAT1 promotes lung cancer proliferation and gefitinib resistance by acting as a miR-200a sponge[J]. Arch Bronconeumol (Engl Ed), 2019, 55(12): 627-633. DOI: 10.1016/j.arbres.2019.03.026.
[6]	Smith GD, Ebrahim S. Mendelian randomization: prospects, potentials, and limitations[J]. Int J Epidemiol, 2004, 33(1): 30-42. DOI: 10.1093/ije/dyh132.
[7]	王莉娜, Zhang Zuofeng. 孟德尔随机化法在因果推断中的应用[J]. 中华流行病学杂志, 2017, 38(4): 547-552. DOI: 10.3760/cma.j.issn.0254-6450.2017.04.027. Wang LN, Zhang ZF. Mendelian randomization approach, used for causal inferences[J]. Chin J Epidemiol, 2017, 38(4): 547-552. DOI: 10.3760/cma.j.issn.0254-6450.2017.04.027.
[8]	Wang Y, McKay JD, Rafnar T, et al. Corrigendum: Rare variants of large effect in BRCA2 and CHEK2 affect risk of lung cancer[J]. Nat Genet, 2017, 49(4): 651. DOI: 10.1038/ng0417-651a.
[9]	Horsfall LJ, Burgess S, Hall I, et al. Genetically raised serum bilirubin levels and lung cancer: a cohort study and Mendelian randomisation using UK Biobank[J]. Thorax, 2020, 75(11): 955-964. DOI: 10.1136/thoraxjnl-2020-214756.
[10]	Võsa U, Claringbould A, Westra HJ, et al. Large-scale cis- and trans-eQTL analyses identify thousands of genetic loci and polygenic scores that regulate blood gene expression[J]. Nat Genet, 2021, 53(9): 1300-1310. DOI: 10.1038/s41588-021-00913-z.
[11]	Sanderson E, Davey Smith G, Windmeijer F, et al. An examination of multivariable Mendelian randomization in the single-sample and two-sample summary data settings[J]. Int J Epidemiol, 2019, 48(3): 713-727. DOI: 10.1093/ije/dyy262.
[12]	Bowden J, Holmes MV. Meta-analysis and Mendelian randomization: a review[J]. Res Synth Methods. 2019, 10(4): 486-496. DOI: 10.1002/jrsm.1346.
[13]	Hartwig FP, Davey SG, 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.
[14]	Lawlor DA, Harbord RM, Sterne JA, et al. Mendelian randomization: using genes as instruments for making causal inferences in epidemiology[J]. Stat Medi, 2008, 27(8): 1133-1163. DOI: 10.1002/sim.3034.
[15]	Zhou W, Liu G, Hung RJ, et al. Causal relationships between body mass index, smoking and lung cancer: Univariable and multivariable Mendelian randomization[J]. Int J Cancer, 2021, 148(5): 1077-1086. DOI: 10.1002/ijc.33292.
[16]	Wong J, Zhang H, Hsiung CA, et al. Tuberculosis infection and lung adenocarcinoma: Mendelian randomization and pathway analysis of genome-wide association study data from never-smoking Asian women[J]. Genomics, 2020, 112(2): 1223-1232. DOI:10. 1016/j.ygeno. 2019.07.008.
[17]	Zhang Z, Li H, Li J, et al. Polymorphisms in the PVT1 gene and susceptibility to the lung cancer in a Chinese northeast population: a case-control study[J]. J Cancer, 2020, 11(2): 468-478. DOI: 10.7150/jca.34320.
[18]	Zhou X, Zhang Y, Zhang Y, et al. LINC01414/LINC00824 genetic polymorphisms in association with the susceptibility of chronic obstructive pulmonary disease[J]. BMC Pulm Med, 2021, 21(1): 213. DOI: 10.1186/s12890-021-01579-3.