坚果摄入量与慢性阻塞性肺疾病的两样本孟德尔随机化研究

张苏; 黄正; 李娜; 许静; 陶怡婷

doi:10.12259/j.issn.2095-610X.S20241112

坚果摄入量与慢性阻塞性肺疾病的两样本孟德尔随机化研究

doi: 10.12259/j.issn.2095-610X.S20241112

张苏¹,
黄正¹,
李娜¹,
许静¹,
陶怡婷^2, ,

1.
天长市人民医院呼吸科，安徽天长　230021
2.
昆明医科大学第一附属医院肾脏科，云南昆明　650032

基金项目: 中央级公益性科研院所基本科研业务费专项基金资助项目（CAFYBB20ZI001-04）

详细信息

作者简介:
张苏（1988～），男，安徽天长人，医学学士，主治医师，主要从事呼吸系统疾病研究工作

通讯作者:
陶怡婷，E-mail：441788274@qq.com

中图分类号: R153.3
计量
- 文章访问数: 209
- HTML全文浏览量: 108
- PDF下载量: 10
- 被引次数: 0
出版历程
- 收稿日期: 2024-05-28
- 网络出版日期: 2024-10-26
- 刊出日期: 2024-11-25

A Two Sample Mendelian Randomization Study on Nut Intake and Chronic Obstructive Pulmonary Disease

Su ZHANG¹,
Zheng HUANG¹,
Na LI¹,
Jing XU¹,
Yiting TAO^{2
, ,}

1.
Dep. of Respiratory ，Tianchang People's Hospital，Tianchang Anhui 230021
2.
Dept. of Nephrology，The 1st Affiliated Hospital of Kunming Medical University，Kunming Yunnan 650032，China

摘要

摘要: 目的以两样本孟德尔随机化方法探讨坚果摄入量和慢性阻塞性肺疾病之间的因果关系。方法从汇总的欧洲大样本openGWAS数据库提取与坚果摄入量紧密关联的SNP位点作为工具变量，分别运用MR-Egger回归、加权中位数及逆方差加权、Simple mode、Weighted mode 5种方法进行孟德尔随机化分析，以OR值及95%CI评价坚果摄入量与慢性阻塞性肺疾病是否存在因果关系。采用mr_pleiotropy_test法检验水平多效性，leave-one-out法进行敏感性分析。结果从ukb-b-16576数据集共提取49个SNPS作为工具变量，MR-Egger回归、加权中位数、逆方差加权法、Simple mode、Weighted mode计算得OR值和95%可信区间分别为[0.91，95%CI （0.82～1.01），P = 0.084]，[0.92，95%CI （0.89～0.95），P = 0.001]，[0.94，95%CI （0.92～0.96），P = 0.001]，[0.91，95%CI （0.85～0.95），P = 0.001]，[0.91，95%CI （0.86～0.96），P = 0.001]，所有b值结果方向均小于0，由于存在异质性（Q=67.36，P=0.012），故关注随机效应IVW模型。mr_pleiotropy_test检验显示MR-Egger截距为3.50E-04，截距接近于0，P = 0.591，所选的工具变量不存在水平多效性。leave-one-out敏感性分析未发现对结果有显著影响的SNP位点，提示结果稳定可靠。结论两样本孟德尔随机化分析表明坚果摄入量与慢性阻塞性肺疾病的发病风险呈负向因果关系，但需要更大样本量和不同种族背景的人的数据来进一步验证。
- 坚果 /
- 慢性阻塞性肺疾病 /
- 孟德尔随机化 /
- 因果推断
Abstract: Objective To explore the causal relationship between nut intake and chronic obstructive pulmonary disease by two-sample Mendelian randomization method. Methods SNP loci closely related to nut intake was extracted from the summarized large sample open GWAS database as instrumental variables, and Mendelian randomization analysis was performed using MR-Egger regression, weighted median, inverse variance weighting, Simple mode and Weighted mode respectively. OR value and 95%CI were used to evaluate whether there was a causal relationship between nut intake and chronic obstructive pulmonary disease. The mr_pleiotropy_test method was used to test the level of pleiotropy, and the leave-one-out method was used for sensitivity analysis. Results A total of 49 SNPS were extracted from the ukb-b-16576 data set as instrumental variables. The OR values and 95% confidence intervals were calculated by MR-Egger regression, weighted median, inverse variance weighting method, Simple mode, and Weighted mode, respectively [0.91, 95%CI （0.82～1.01）, P = 0.084], [0.92, 95%CI （0.89～0.95）, P = 0.001], [0.94, 95%CI （0.92～0.96）, P = 0.001], [0.91, 95%CI （0.85～0.95）, P = 0.001], [0.91, 95%CI （0.86～0.96）, P = 0.001]. All b values were less than 0. Due to the heterogeneity （Q = 67.36, P = 0.012 ）, the random effect IVW model was concerned. The mr_pleiotropy_test showed that the MR-Egger intercept was 3.50E-04, the intercept was close to 0, P = 0.591, and the selected instrumental variables did not have horizontal pleiotropy. Leave-one-out sensitivity analysis did not find SNP loci that had a significant effect on the results, suggesting that the results were stable and reliable. Conclusion The two-sample Mendelian randomization analysis shows a negative causal relationship between nut intake and the risk of chronic obstructive pulmonary disease, but larger sample size and data of people with different ethnic backgrounds are needed for further verification.
- Nuts /
- Chronic obstructive pulmonary disease /
- Mendel randomization /
- Causal inference

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图 1 单个SNP的孟德尔随机化效应森林图

Figure 1. Mendelian randomization effect forest

下载: 全尺寸图片幻灯片

图 2 工具变量的孟德尔随机化效应散点图

Figure 2. Scatter plot of Mendel 's randomization effect

下载: 全尺寸图片幻灯片

图 3 留一法敏感性分析

Figure 3. Sensitivity analysis of leave-one-out method

下载: 全尺寸图片幻灯片

表 1 工具变量SNP信息表

Table 1. Instrumental variable SNP information table

SNPs	CHR	EA	OA	EAF	β	SE	P	F
rs1413952	1	T	C	0.48	9.83E-03	1.67E-03	4.30E-09	34.46
rs75641275	1	C	A	0.14	−1.42E-02	2.39E-03	2.90E-09	35.25
rs261809	1	G	A	0.54	−9.63E-03	1.68E-03	9.80E-09	32.88
rs11586016	1	C	G	0.37	9.88E-03	1.73E-03	1.10E-08	32.59
rs72720396	1	G	A	0.22	1.14E-02	1.99E-03	8.70E-09	33.12
rs11811826	1	A	T	0.22	1.32E-02	2.01E-03	4.40E-11	43.42
rs7599488	2	T	C	0.42	−1.04E-02	1.69E-03	6.70E-10	38.12
rs7582086	2	T	G	0.46	−9.63E-03	1.67E-03	8.80E-09	33.08
rs4149513	2	A	G	0.49	1.17E-02	1.67E-03	2.20E-12	49.25
.............................................
.............................................
rs1622515	11	G	A	0.48	9.92E-03	1.67E-03	2.90E-09	35.23
rs3764002	12	T	C	0.26	1.31E-02	1.90E-03	5.10E-12	47.65
rs61937394	12	G	T	0.19	−1.30E-02	2.20E-03	3.20E-09	35.04
rs12890531	14	G	A	0.21	1.12E-02	2.04E-03	4.50E-08	29.91
rs4140799	14	A	G	0.53	9.46E-03	1.68E-03	1.80E-08	31.74
rs10129747	14	G	A	0.53	9.36E-03	1.68E-03	2.60E-08	30.98
rs34162196	14	T	C	0.1	−2.24E-02	2.77E-03	7.10E-16	65.09
rs270816	15	T	A	0.12	−1.40E-02	2.51E-03	2.80E-08	30.83
rs1797235	15	C	G	0.37	−1.00E-02	1.74E-03	8.90E-09	33.07
rs1582322	16	G	A	0.6	9.94E-03	1.72E-03	6.80E-09	33.58
rs862227	16	G	A	0.45	−9.16E-03	1.67E-03	4.30E-08	30.03

下载: 导出CSV

表 2 5种MR分析方法OR估计值及95%CI

Table 2. OR estimates and 95% CI of five MR analysis methods

方法	β	SE	P	OR（95%CI）	Q	Q_pval
MR Egger	−0.09	0.05	0.084	0.91（0.82，1.01）	66.81	0
加权中位数法	−0.08	0.01	0.001	0.92（0.89，0.95）	67.36	0
逆方差加权	−0.06	0.01	0.001	0.94（0.92，0.95）
简单众数法	−0.1	0.03	0.001	0.90（0.85，0.95）
加权众数法	−0.09	0.03	0.001	0.91（0.86，0.95）

下载: 导出CSV

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