双向两样本孟德尔随机化探究慢性肾脏病及肾功能相关指标与失眠的因果关联

张婷婷; 李惠; 张星平

doi:10.16766/j.cnki.issn.1674-4152.004086

双向两样本孟德尔随机化探究慢性肾脏病及肾功能相关指标与失眠的因果关联

doi: 10.16766/j.cnki.issn.1674-4152.004086

1.
新疆医科大学第四附属医院, 新疆维吾尔自治区中医医院内分泌科, 新疆乌鲁木齐 830099
2.
新疆医科大学第四附属医院, 新疆维吾尔自治区中医医院中医内科

基金项目:

国家自然科学基金项目 82160873

国家自然科学基金项目 81960837

国家自然科学基金项目 81560762

国家自然科学基金项目 81260526

全国名老中医药专家传承工作室国中医药人教函〔2022〕75号

国家中管局高水平中医药重点学科建设项目国中医药人教函〔2023〕85号

详细信息

通讯作者:
张星平，E-mail: xjzyzxp@163.com

中图分类号: R692
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出版历程
- 收稿日期: 2024-11-06
- 网络出版日期: 2025-10-25

Bidirectional two-sample mendelian randomization investigation of the causal association between chronic kidney disease and renal function related indicators with insomnia

1.
The Fourth Affiliated Hospital of Xinjiang Medical University, Department of Endocrinology, Xinjiang Uygur Autonomous Region Hospital of Traditional Chinese Medicine, Urumqi, Xinjiang 830099, China

摘要

摘要: 目的慢性肾脏病(CKD)及肾功能相关指标异常与失眠在临床上常同时发病，本研究旨在通过双向两样本孟德尔随机化(MR)方法探讨其潜在因果关联。方法从已公开发表、欧洲人群的全基因组关联研究数据集中筛选出与暴露因素强相关且满足连锁不平衡条件的单核苷酸多态性(SNPs)作为工具变量，并从相应结局中提取SNPs行MR分析。以逆方差加权法(IVW)作为主要因果推断结果，以MR-Egger回归、加权中值、加权众数、简单众数法作为IVW的补充与验证。结果 IVW法提示CKD及血清肌酐、血尿酸、胱抑素C与失眠之间不存在显著因果关联，其OR(95% CI)分别为0.997(0.993~1.002)、0.924(0.844~1.011)、1.008(0.997~1.019)、1.001(0.993~1.009)，均P＞0.05；失眠对CKD及血清肌酐、血尿酸、胱抑素C亦不存在显著因果关联，OR(95% CI)分别为1.403(0.625~3.151)、1.002(0.983~1.021)、1.010(0.871~1.170)、0.954(0.679~1.342)，均P＞0.05；MR-Egger回归法、加权中值方法、加权众数法、简单众数法均进一步验证CKD及血清肌酐、血清尿酸、胱抑素C与失眠之间不存在双向因果关联。此外，水平多效性检验、异质性检验、留一法分析结果总体效应不受单个工具变量的影响，进一步佐证MR分析结果稳健可靠。结论 CKD及肾功能相关指标与失眠不存在明显双向因果关联。
- 慢性肾脏病 /
- 肾功能 /
- 失眠 /
- 孟德尔随机化
Abstract: Objective Chronic kidney disease (CKD) and renal function-related index abnormalities and insomnia often occur simultaneously in clinical practice. This study aimed to explore the potential causal association through Bidirectional two-sample Mendelian randomization (MR) analysis. Methods Single nucleotide polymorphisms (SNPs) that were strongly correlated with exposure factors and satisfied the linkage disequilibrium were screened from the published genome-wide association study (GWAS) dataset of European population as instrumental variables, and the SNPs were extracted from the corresponding outcomes for MR analysis. The inverse-variance weighted (IVW) method was used as the main causal inference result, and MR-Egger regression, weighted median, weighted mode, and simple mode methods were used as supplements and validation of IVW to explore the two-way causal association between chronic kidney disease and its related indicators and insomnia. Results There was no significant causal association between CKD, serum creatinine, serum uric acid, cystatin C and insomnia by IVW method. The OR (95% CI) were 0.997 (0.993-1.002), 0.924 (0.844-1.011), 1.008 (0.997-1.019), 1.001 (0.993-1.009), respectively (P>0.05). There was no significant causal association between insomnia and CKD and serum creatinine, serum uric acid, and cystatin C. The OR (95% CI) were 1.403 (0.625~3.151), 1.002 (0.983-1.021), 1.010 (0.871-1.170), and 0.954 (0.679-1.342), respectively (P>0.05). MR-Egger regression method, weighted median method, weighted mode method, and simple mode method further verified that there was no bidirectional causal relationship between CKD and its related indicators (serum creatinine, serum uric acid, cystatin C) and insomnia (P>0.05). In addition, the overall effect of level pleiotropy test, heterogeneity test, and leave one method analysis results were not affected by a single instrumental variable, further confirming the robustness and reliability of MR analysis results. Conclusion There is no obvious bidirectional causal association between CKD and renal function related indicators and insomnia.
- Chronic kidney disease /
- Renal function /
- Insomnia /
- Mendelian randomization analysis

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图 1 CKD及其相关指标(Cr、UA、Cys-C)与失眠的正向与反向散点图

注：A~D分别为Cr、UA、Cys-C、CKD作为暴露时的两样本MR散点图；E~H分别为CKD及其相关指标作为结局时的两样本MR散点图。

Figure 1. Positive and reverse scatter plots of CKD and related indicators (Cr, UA, Cys-C) with insomnia

下载: 全尺寸图片幻灯片

图 2 CKD及其相关指标(Cr、UA、Cys-C)与失眠的正向与反向漏斗图

注：A~D分别为Cr、UA、Cys-C、CKD作为暴露时的两样本MR漏斗图；E~H分别为CKD及其相关指标作为结局时的两样本MR漏斗图。

Figure 2. Positive and reverse funnel plots of CKD and related indicators (Cr, UA, Cys-C) with insomnia

下载: 全尺寸图片幻灯片

表 1 CKD及其相关指标(Cr、UA、Cys-C)与失眠的正向与反向MR分析

Table 1. Forward and reverse MR analysis of CKD and its related indicators (Cr, UA, Cys-C) with insomnia

MR	暴露	OR值(95% CI)	P值	结局	OR值(95% CI)	P值
MR-Egger	CKD	1.000(0.991~1.009)	0.990	CKD	0.835(0.075~9.272)	0.884
Weighted median		0.996(0.989~1.002)	0.204		0.810(0.252~2.598)	0.722
IVW		0.997(0.993~1.002)	0.295		1.403(0.625~3.151)	0.412
Simple mode		0.994(0.982~1.006)	0.348		0.663(0.077~5.713)	0.710
Weighted mode		0.995(0.985~1.004)	0.300		0.762(0.166~3.500)	0.729
MR-Egger	Cr	1.084(0.888~1.325)	0.428	Cr	0.991(0.933~1.053)	0.767
Weighted median		0.949(0.853~1.055)	0.332		1.004(0.988~1.020)	0.654
IVW		0.924(0.844~1.011)	0.085		1.002(0.983~1.021)	0.858
Simple mode		0.907(0.687~1.197)	0.491		0.996(0.960~1.033)	0.835
Weighted mode		1.010(0.869~1.174)	0.897		1.002(0.979~1.026)	0.858
MR-Egger	UA	1.006(0.991~1.021)	0.427	UA	0.843(0.510~1.392)	0.509
Weighted median		1.009(0.999~1.020)	0.089		0.969(0.866~1.084)	0.585
IVW		1.008(0.997~1.019)	0.164		1.010(0.871~1.170)	0.897
Simple mode		0.993(0.955~1.034)	0.749		1.407(1.006~1.967)	0.053
Weighted mode		1.007(0.997~1.017)	0.203		0.964(0.799~1.162)	0.699
MR-Egger	Cys-C	0.998(0.987~1.009)	0.675	Cys-C	1.413(0.192~10.388)	0.742
Weighted median		0.998(0.989~1.006)	0.600		0.889(0.710~1.114)	0.306
IVW		1.001(0.993~1.009)	0.755		0.954(0.679~1.342)	0.789
Simple mode		1.005(0.974~1.037)	0.747		0.737(0.437~1.243)	0.279
Weighted mode		0.998(0.990~1.006)	0.664		0.953(0.619~1.466)	0.830

下载: 导出CSV

表 2 CKD及其相关指标(Cr、UA、Cys-C)与失眠的正向与反向敏感性分析

Table 2. Forward and reverse sensitivity analysis of CKD and its related indicators (Cr, UA, Cys-C) with insomnia

暴露	水平多效性		异质性		结局	水平多效性		异质性
暴露	MR-Egger回归截距	P值	Cochran' s Q检验	P值	结局	MR-Egger回归截距	P值	Cochran' s Q检验	P值
CKD	-0.001	0.519	16.924	0.595	CKD	0.006	0.656	46.525	0.162
Cr	-0.001	0.080	742.670	＜0.001	Cr	0	0.710	182.112	＜0.001
UA	＜0.001	0.720	513.333	＜0.001	UA	0.002	0.465	241.867	＜0.001
Cys-C	0	0.340	722.209	＜0.001	Cys-C	-0.004	0.704	84.076	＜0.001

下载: 导出CSV

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