基于孟德尔随机化探索臀围与2型糖尿病的因果关系

李文超; 李洪凯; 刘新辉; 司书成; 于媛媛; 李云霞; 袁同慧; 侯蕾; 刘璐; 周宇畅; 薛付忠; 刘言训

doi:10.16462/j.cnki.zhjbkz.2020.01.003

基于孟德尔随机化探索臀围与2型糖尿病的因果关系

doi: 10.16462/j.cnki.zhjbkz.2020.01.003

250012 济南, 山东大学公共卫生学院生物统计系/山东大学健康医疗大数据研究院

基金项目: 国家自然科学基金(81773547)

详细信息

通讯作者:
刘言训, E-mail:liu-yx@sdu.edu.cn

中图分类号: R587.1
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出版历程
- 收稿日期: 2019-07-22
- 修回日期: 2019-10-25
- 刊出日期: 2020-01-10

Exploring the causal relationship between hip circumference and type 2 diabetes based on mendelian randomization

Department of Biostatistics, School of Public Health, Shandong University and Healthcare Big Data Institute of Shandong University, Jinan 250012, China

Funds: National Natural Science Foundation of China(81773547)

More Information

Corresponding author: LIU Yan-xun, E-mail:liu-yx@sdu.edu.cn

摘要

摘要: 目的采用孟德尔随机化分析方法, 探讨臀围与2型糖尿病的因果关联。方法将分别来自人体测量特征遗传研究(genetic investigation of anthropometric traits, GIANT)和糖尿病遗传学验证和荟萃分析(diabetes genetics replication and Meta-analysis, DIAGRAM)数据库的臀围和2型糖尿病遗传位点数据, 据单核苷酸多态性(single nucleotide polymorphism, SNP)编号匹配合并, 以与臀围密切相关的SNP为工具变量, 运用逆方差加权法、MR-Egger回归模型和加权中位数法分析臀围对2型糖尿病的因果效应。结果不分性别队列、女性队列和男性队列中分别匹配到52、9和15个SNP。异质性检验结果提示SNP间同质。三个队列的OR值及其95%的置信区间分别为1.065(1.030~1.100)、1.103(1.057~1.150)和1.583(1.273~1.968), 均有统计学意义(均有P < 0.05)。敏感性分析结果显示三个队列逐一移除SNP, 其因果效应不受影响, 结果稳健。结论人体臀围与2型糖尿病之间均存在因果关联, 臀围可能为2型糖尿病的危险因素。
- 孟德尔随机化 /
- 臀围 /
- 2型糖尿病 /
- 因果推断
Abstract: Objective To investigate the causal association between hip circumference(HC) and type 2 diabetes mellitus(T2 DM) based on Mendelian randomization. Methods The genetic variants data of the HC and T2 DM from the Genetic Investigation of Anthropometric Traits(GIANT) and DIAbetes Genetics Replication And Meta-analysis(DIAGRAM) database were matched according to the single nucleotide polymorphism(SNP) rsID. Genetic loci strongly related to the HC were used as instrumental variables; and the inverse-variance weighting, MR-Egger regression model and weighting median method were carried out to analyze the causal effect of HC on T2 DM. Results Fifty-two, nine and fifteen SNPs were matched in the total cohort, female cohort and male cohort, respectively. Heterogeneity test suggested the SNPs were homogeneous. We found HC to be positively associated with T2 DM risk(OR=1.065, 95% CI: 1.030-1.100, OR=1.103, 95% CI: 1.057-1.150 and OR=1.583, 95% CI: 1.273-1.968, respectively) in above three cohorts, respectively. Sensitivity analysis showed the results were robust. Conclusions There is a relationship between HC and T2 DM of people, and HC may be the risk factor of T2 DM.
- Mendelian randomization /
- Hip circumference /
- Type 2 diabetes mellitus /
- Causal inference

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图 1 工具变量的有向无环示意图

Figure 1. Directed acyclic graph of instrumental variable

下载: 全尺寸图片幻灯片

图 2 在各队列中HC与T2DM间OR(95% CI)值的森林图

Figure 2. Forest plots of the value of OR(95% CI) of HC and T2DM in different cohort

下载: 全尺寸图片幻灯片

表 1 各SNP对HC和T2DM的效应值

Table 1. SNPs and magnitude effect on HC and T2DM

SNP	有效等位基因	其他等位基因	有效等位基因频率	HC			T2DM
SNP	有效等位基因	其他等位基因	有效等位基因频率	β	s_x	P值	β	s_x	P值
rs10132280	C	A	0.666 7	0.022 0	0.003 8	4.8×10^-9	0.029 6	0.019 8	0.120 0
rs10182181	A	G	0.500 0	-0.023 0	0.003 5	6.4×10^-11	0.019 8	0.017 6	0.340 0
rs10929925	C	A	0.650 0	0.019 0	0.003 6	4.5×10^-8	0.048 8	0.019 4	0.016 0
rs10938397	G	A	0.433 3	0.030 0	0.003 7	9.3×10^-17	0.029 6	0.019 8	0.110 0
rs11057405	A	G	0.091 7	-0.040 0	0.006 3	2.1×10^-10	0.095 3	0.046 5	0.055 0
rs11165623	A	G	0.483 3	0.022 0	0.003 5	3.0×10^-10	0.039 2	0.017 3	0.048 0
rs11672660	T	C	0.175 0	-0.028 0	0.004 5	7.1×10^-10	0.019 8	0.027 4	0.390 0
rs12086130	C	T	0.900 0	-0.038 0	0.006 3	2.6×10^-9	0.095 3	0.032 5	0.005 0
rs1294409	T	C	0.616 7	-0.020 0	0.003 7	3.0×10^-8	<0.000 1	0.017 8	0.980 0
rs13098327	A	G	0.183 3	0.027 0	0.004 4	1.2×10^-9	0.019 8	0.020 0	0.400 0
rs1351394	C	T	0.516 7	-0.023 0	0.003 5	6.4×10^-11	0.029 6	0.019 8	0.120 0
rs13695	C	T	0.725 0	-0.024 0	0.004 4	4.3×10^-8	0.010 0	0.025 3	0.800 0
rs143384	G	A	0.400 0	0.026 0	0.003 8	3.9×10^-12	0.019 8	0.022 4	0.230 0
rs1516725	C	T	0.908 3	0.031 0	0.005 4	1.0×10^-8	0.067 7	0.028 6	0.018 0
rs1548457	C	T	0.375 0	0.025 0	0.004 5	1.7×10^-8	0.019 8	0.020 0	0.340 0
rs1561277	A	C	0.225 0	-0.024 0	0.004 1	6.0×10^-9	0.019 8	0.020 0	0.360 0
rs16894959	C	T	0.100 0	0.037 0	0.004 9	9.6×10^-14	0.010 0	0.025 3	0.740 0
rs16905212	C	T	0.325 0	-0.021 0	0.003 8	1.9×10^-8	0.010 0	0.020 2	0.740 0
rs17024393	C	T	0.041 7	0.063 0	0.010 0	2.8×10^-10	0.157 0	0.056 4	0.006 0
rs17066856	T	C	0.866 7	0.036 0	0.006 3	6.3×10^-9	0.067 7	0.033 4	0.041 0
rs1808579	C	T	0.525 0	0.023 0	0.003 5	2.1×10^-10	0.029 6	0.019 8	0.130 0
rs2112347	T	G	0.625 0	0.025 0	0.003 6	9.7×10^-12	0.039 2	0.017 1	0.025 0
rs2206277	T	C	0.091 7	0.039 0	0.004 6	3.1×10^-17	0.039 2	0.024 5	0.097 0
rs2293576	G	A	0.633 3	0.023 0	0.003 8	2.1×10^-9	0.010 0	0.017 6	0.520 0
rs2301573	C	T	0.075 0	0.035 0	0.006 2	2.1×10^-8	<0.000 1	0.030 6	0.970 0
rs2820443	T	C	0.700 0	-0.034 0	0.003 9	4.9×10^-18	0.058 3	0.019 3	0.004 0
rs3087591	G	A	0.375 0	0.021 0	0.003 8	2.5×10^-8	0.010 0	0.020 2	0.490 0
rs355838	T	G	0.366 7	-0.022 0	0.003 6	1.6×10^-9	0.039 2	0.017 3	0.029 0
rs3800229	T	G	0.691 7	0.021 0	0.003 8	3.2×10^-8	0.019 8	0.020 0	0.390 0
rs3888190	A	C	0.358 3	0.035 0	0.003 6	9.4×10^-22	0.010 0	0.017 8	0.770 0
rs4132228	C	T	0.766 7	-0.021 0	0.003 9	3.1×10^-8	0.067 7	0.019 1	0.001 0
rs4883723	A	G	0.125 0	0.032 0	0.005 1	5.2×10^-10	0.067 7	0.028 6	0.015 0
rs4889606	G	A	0.358 3	-0.021 0	0.003 6	8.8×10^-9	0.010 0	0.015 2	0.590 0
rs543874	G	A	0.266 7	0.045 0	0.004 5	1.8×10^-23	0.039 2	0.022 2	0.093 0
rs6163	C	A	0.608 3	-0.021 0	0.003 7	1.6×10^-8	0.019 8	0.017 6	0.400 0
rs6265	C	T	0.825 0	0.034 0	0.004 5	1.5×10^-14	0.019 8	0.020 0	0.420 0
rs6569648	T	C	0.758 3	-0.029 0	0.004 2	6.5×10^-12	0.067 7	0.019 1	0.001 0
rs663129	A	G	0.283 3	0.050 0	0.004 2	1.4×10^-32	0.067 7	0.021 6	0.002 0
rs6678622	C	T	0.583 3	-0.022 0	0.003 7	1.1×10^-9	<0.000 1	0.020 4	0.990 0
rs6755502	C	T	0.875 0	0.054 0	0.004 7	2.4×10^-30	0.019 8	0.022 4	0.320 0
rs7138803	A	G	0.441 7	0.029 0	0.003 7	1.9×10^-15	0.039 2	0.017 3	0.037 0
rs7144011	T	G	0.275 0	0.030 0	0.004 2	8.6×10^-13	0.067 7	0.019 1	0.001 0
rs7183263	G	T	0.475 0	0.019 0	0.003 6	4.8×10^-8	0.019 8	0.020 0	0.380 0
rs7531118	C	T	0.608 3	0.024 0	0.003 7	4.0×10^-11	0.010 0	0.017 6	0.450 0
rs7632381	T	C	0.516 7	-0.036 0	0.003 5	5.3×10^-24	0.039 2	0.017 1	0.015 0
rs7903146	T	C	0.250 0	-0.026 0	0.003 9	2.1×10^-11	0.336 5	0.020 0	5.5×10^-65
rs798528	C	A	0.300 0	-0.021 0	0.003 8	1.7×10^-8	<0.000 1	0.020 4	0.990 0
rs806794	G	A	0.275 0	-0.032 0	0.004 0	2.8×10^-16	0.010 0	0.020 2	0.740 0
rs879620	C	T	0.408 3	-0.029 0	0.004 7	8.9×10^-10	0.010 0	0.020 2	0.740 0
rs887912	T	C	0.316 7	0.022 0	0.003 9	1.6×10^-8	0.029 6	0.019 8	0.160 0
rs951252	G	A	0.525 0	-0.028 0	0.003 5	4.5×10^-15	0.010 0	0.020 2	0.580 0
rs9939973	A	G	0.475 0	0.070 0	0.003 6	2.3×10^-86	0.095 3	0.016 2	1.2×10^-8

下载: 导出CSV

表 2 leave-one-out法敏感性分析结果

Table 2. Result of "leave one out" method

除去某SNP	OR(95% CI)值	除去某SNP	OR(95% CI)值
rs6755502	1.655 (1.304~2.100)	rs10784502	1.444(1.163~1.791)
rs9846396	1.627(1.314~2.016)	rs3118910	1.190(1.077~1.314)
rs13130484	1.627(1.320~2.005)	rs17109256	1.542(1.233~1.927)
rs951252	1.597(1.284~1.986)	rs4788102	1.629(1.323~2.005)
rs806794	1.581(1.273~1.964)	rs12936587	1.619(1.224~2.141)
rs2744937	1.583(1.275~1.966)	rs6567160	1.470(1.130~1.912)
rs2206277	1.570(1.262~1.954)	rs143384	1.622(1.313~2.003)
rs6569648	1.545(1.232~1.937)

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