酚类暴露与基因多态性交互作用对肾功能的影响

张芾炜; 王文卓; 蔡晓敏; 王璐; 何恒; 钟荣; 田剑波; 朱颖; 缪小平

doi:10.16462/j.cnki.zhjbkz.2024.11.001

酚类暴露与基因多态性交互作用对肾功能的影响

doi: 10.16462/j.cnki.zhjbkz.2024.11.001

张芾炜¹,
王文卓¹,
蔡晓敏¹,
王璐¹,
何恒^{1, 2},
钟荣¹,
田剑波³,
朱颖³,
缪小平^1, ,

1.
华中科技大学同济医学院公共卫生学院流行病与卫生统计学系，武汉 430030
2.
福建医科大学公共卫生学院流行病与卫生统计学系，福州 350108
3.
武汉大学公共卫生学院流行病与卫生统计学系，武汉 430071

基金项目:

国家重点研发计划 2022YFA0806601

详细信息

通讯作者:
缪小平，E-mail: miaoxp@hust.edu.cn

中图分类号: R181
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出版历程
- 收稿日期: 2024-01-13
- 修回日期: 2024-05-10
- 网络出版日期: 2024-12-23
- 刊出日期: 2024-11-10

Effect of phenol exposure and single nucleotide polymorphisms interaction on renal function

1.
Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
2.
Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Fuzhou 350108, China
3.
Department of Epidemiology and Health Statistics, School of Public Health, Wuhan University, Wuhan 430071, China

Funds:

National Key Research and Development Program of China 2022YFA0806601

More Information

Corresponding author: MIAO Xiaoping, E-mail: miaoxp@hust.edu.cn

摘要

摘要: 目的探究双酚A(bisphenol A, BPA)、双酚F(bisphenol F, BPF)、三氯生(triclosan, TCS)暴露与基因位点多态性的交互作用对肾功能的影响。方法 2016―2021年在华中科技大学同济医学院附属同济医院的体检人群中，招募了414名成年人作为研究对象，通过问卷形式收集人群信息，采集其尿液样本。检测研究对象尿液样本中3种酚类暴露物(BPA、BPF和TCS)的内暴露水平。测定血清肌酐水平，计算估算的肾小球滤过率(estimated glomerular filtration rate, eGFR)作为肾功能的指标。提取研究对象血液样本中的DNA进行高通量基因分型，并进行基因组填补和质量控制，通过全基因组关联研究分析影响eGFR水平的基因-环境交互作用，最后对显著性和提示性遗传位点进行位置和功能注释，进而探究其相关生物学功能。结果通过高通量基因分型和基因型填补后，共得到414例样本的4 135 024个单核苷酸多态性(single nucleotide polymorphisms, SNPs)位点的基因型数据。在进一步鉴定中发现3个与BPA在影响肾功能水平上存在交互作用的SNPs位点(rs60391380、rs56108314和rs73082740)，其位于4p16.3染色体区段并靠近ADRA2C基因，其中最显著的是rs60391380(β_交互作用=-0.042, 95% CI: -0.057~-0.028, P=1.565×10^-8)，结合表观修饰推测该遗传位点可能与BPA发生交互作用，激活其调控元件的功能，上调ADRA2C基因的表达，进而影响肾功能。本研究还探寻到844个提示性BPA交互作用位点(P < 5×10^-6)。在eGFR全基因组关联分析中发现与BPF存在交互作用的提示性位点52个，未发现显著性位点；对于TCS未发现存在交互作用的显著性和提示性位点。结论在人群中，BPA暴露与遗传变异存在基因-环境交互作用，共同影响肾功能。未发现BPF和TCS暴露存在影响肾功能水平的基因-环境交互作用。
- 酚类暴露 /
- 基因-环境交互作用 /
- 单核苷酸多态性 /
- 慢性肾脏病 /
- 估算的肾小球滤过率
Abstract: Objective To investigate of the interaction between exposure to bisphenol A (BPA), bisphenol F (BPF), triclosan (TCS) and gene locus polymorphism on renal function. Methods A total of 414 adults were recruited as research subjects from the physical examination population of Tongji Hospital affiliated with Tongji Medical College of Huazhong University of Science and Technology between 2016 and 2021. Population information was collected through questionnaires, and urine samples were obtained for analysis. The internal exposure levels of three phenolic compounds, namely BPA, BPF, and TCS, were subsequently measured in the urine samples of the study subjects. Serum creatinine levels were measured to determine renal function, and eGFR was calculated as an indicator. Blood samples were taken from research subjects to extract DNA for high-throughput genotyping, genome filling, and quality control. Genome-wide association studies (GWAS) were then conducted to analyze gene-environment interactions affecting eGFR levels. Finally, the obtained significant and suggestive genetic loci were annotated by location and function to explore their related biological functions. Results Following high-throughput genotyping and genotype filling, 414 samples were obtained with genotype data for 4 135 024 single nucleotide polymorphisms (SNPs) loci. During further identification, three SNPs loci (rs60391380, rs56108314, and rs73082740) were found to have a significant interaction with BPA in relation to renal function. These loci were located in the 4p16.3 chromosome segment, close to the ADRA2C gene. The most significant interaction effect was found for rs60391380, with a beta value of -0.042 (-0.057--0.028) and a P-value of 1.565×10^-8. Based on epigenetic modifications, it was speculated that this genetic locus might interact with BPA, activate its regulatory elements, and upregulate the expression of ADRA2C, thereby affecting renal function. Additionally, 844 BPA interaction sites were explored, with suggestive results (P < 5×10^-6). In the eGFR genome-wide association analysis, 52 loci were found to interact with BPF in a suggestive manner, but no significant loci were identified. For TCS, no significant or suggestive sites of interaction were found. Conclusions The interaction between BPA and SNPs had a joint effect on renal function. However, no statistically significant gene-environment interactions affecting renal function were found for BPF and TCS.
- Phenolic exposures /
- Gene-environment interaction /
- Single nucleotide polymorphism /
- Chronic kidney disease /
- Estimated glomerular filtration rate

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图 1 BPA、BPF和TCS暴露和全基因组SNP交互作用与eGFR关联的曼哈顿图

A：BPA交互作用与eGFR关联的曼哈顿图；B：BPF交互作用与eGFR关联的曼哈顿图；C：TCS交互作用与eGFR关联的曼哈顿图; 红色实线代表P值为5×10^-8的统计学显著性阈值，黄色实线代表P值为5×10^-6的提示性阈值；eGFR: 估算的肾小球滤过率；BPA: 双酚A；BPF: 双酚F；TCS: 三氯生。

Figure 1. Manhattan plot of eGFR genome-wide Phenolic-SNP interactions

A: manhattan plot of eGFR genome-wide BPA-SNP interaction; B: manhattan plot of eGFR genome-wide BPF-SNP interaction; C: manhattan plot of eGFR genome-wide TCS-SNP interaction; eGFR: estimated glomerular filtration rate; BPA: bisphenol A; BPF: bisphenol F; TCS: triclosan.

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图 2 BPA暴露与SNP提示性交互作用的显著性位点区域关联图

A：rs60391380位点区域关联图；B：rs56108314位点区域关联图；C：rs73082740位点区域关联图。

Figure 2. Regional association plot of loci for significant BPA-SNP interactions

A: regional plots of rs60391380; B: regional plots of rs56108314: C: regional plots of rs73082740.

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图 3 BPA交互作用显著性和提示性位点基因组位置和表观组学注释

A：显著性和提示性SNPs位点基因组位置注释图；B：显著性SNPs位点表观组学注释图。

Figure 3. Annotation of genomic locations of significant and suggestive loci for BPA interaction

A: genome location annotation of significant and suggestive SNPs loci; B: epigenetic annotation of significant SNPs loci.

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表 1 eGFR及酚类物质暴露水平及分布

Table 1. eGFR and phenolic exposure levels and distribution

人口学特征 Demographic characteristic	eGFR/(mL·min^-1·1.73 m^-2)^①	P值^② value	肌酐校正的BPA Creatinine-corrected BPA/(μg·L^-1)^①	P值^② value	肌酐校正的BPF Creatinine-corrected BPF/(μg·L^-1)^①	P值^② value	肌酐校正的TCS Creatinine-corrected TCS/(μg·L^-1)^①	P值^② value
年龄组/岁 Age group/years		< 0.001		0.214		0.799		0.192
≤60 (n=238)	98.62 (85.43, 105.93)		0.90 (0.39, 2.60)		0.10 (0.03, 0.50)		0.50 (0.14, 1.90)
＞60 (n=176)	88.09 (74.12, 97.35)		0.91 (0.46, 2.50)		0.09 (0.03, 0.40)		0.83 (0.26, 2.60)
性别 Gender		< 0.001		0.135		0.364		0.627
男性 Male(n=278)	96.97 (86.09, 104.97)		0.90 (0.42, 2.40)		0.10 (0.03, 0.40)		0.60 (0.17, 2.00)
女性 Female(n=136)	85.01 (68.49, 98.36)		0.90 (0.41, 2.80)		0.10 (0.03, 0.40)		0.80 (0.2, 2.30)
吸烟状况 Smoking status		0.003		0.685		0.044		0.208
吸烟 Smoking(n=159)	96.93 (86.51, 104.00)		1.10 (0.45, 2.70)		0.20 (0.03, 0.70)		0.60 (0.16, 1.70)
不吸烟 Non-smoking(n=255)	92.18 (76.16, 102.18)		0.88 (0.39, 2.50)		0.08 (0.03, 0.30)		0.70 (0.19, 2.40)
饮酒状况 Drinking status		0.001		0.355		0.878		0.446
饮酒 Drinking(n=148)	97.49 (85.79, 105.74)		0.80 (0.38, 2.20)		0.10 (0.03, 0.40)		0.60 (0.18, 2.50)
不饮酒 Non-drinking(n=266)	92.86 (76.04, 102.08)		1.00 (0.42, 2.70)		0.10 (0.03, 0.40)		0.70 (0.18, 2.10)
BMI/(kg·m^-2)		0.106		0.077		0.188		0.425
< 24(n=197)	92.94 (75.82, 102.46)		0.90 (0.39, 2.80)		0.10 (0.03, 0.50)		0.70 (0.17, 2.00)
≥24(n=217)	94.25 (83.24, 103.74)		0.90 (0.44, 2.10)		0.10 (0.03, 0.40)		0.60 (0.19, 2.50)
注：eGFR，估算的肾小球滤过率；BPA，双酚A；BPF，双酚F；TCS，三氯生。 ①以M(IQR)表示；②采用U检验。 Note: eGFR, estimated glomerular filtration rate; BPA, bisphenol A; BPF, bisphenol F; TCS, triclosan. ① M(IQR); ② U-test was used.

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表 2 eGFR相关的BPA暴露与遗传变异交互作用显著性位点

Table 2. eGFR-associated genome-wide BPA interaction analysis of significant SNPs loci

SNPs	染色体 Chromosome	基因 Gene	染色体区段 Loci	功能区域 Function	风险/参照等位基因 alternative allele/reference allele
rs60391380	chr4	ADRA2C	4p16.3	intergenic	G/A
rs56108314	chr4	ADRA2C	4p16.3	intergenic	C/T
rs73082740	chr4	ADRA2C	4p16.3	intergenic	C/G

SNPs	SNP与eGFR关联 SNP association with eGFR^①		BPA与eGFR关联 BPA association with eGFR^①		BPA-SNP交互作用 BPA interaction with SNPs^①
SNPs	β值value (95% CI)	P值value	β值value (95% CI)	P值value	β值value (95% CI)	P_int

rs60391380	-0.030 (-0.047~-0.012)	7.728×10^-4	-0.002 (-0.003~-0.001)	6.230×10^-3	-0.042 (-0.057~-0.028)	1.565×10^-8
rs56108314	0.001 (-0.008~0.019)	0.463	-0.002 (-0.003~-0.001)	2.997×10^-3	-0.042 (-0.056~-0.027)	2.756×10^-8
rs73082740	0.002 (-0.014~0.014)	0.981	-0.002 (-0.003~-0.001)	3.214×10^-3	-0.041 (-0.055~-0.026)	3.864×10^-8
注：SNPs，单核苷酸多态性；eGFR，估算的肾小球滤过率；BPA，双酚A。 ①采用多元线性回归模型计算，并对年龄、性别、BMI、吸烟状况和饮酒状况进行了调整。 Note: SNPs, single nucleotide polymorphisms; eGFR, estimated glomerular filtration rate; BPA, bisphenol A. ① Calculated using multiple linear regression models and adjusted for age, gender, BMI, smoking status, and drinking status.

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表 3 SNPs不同基因型分层人群中BPA与eGFR关联

Table 3. Association between BPA and eGFR in Genotypic Stratified Population

SNPs	基因型 Genotype	人数(占比/%) Number of people (proportion/%)	eGFR水平 eGFR level^①
SNPs	基因型 Genotype	人数(占比/%) Number of people (proportion/%)	β值 value (95% CI)	P值 value
rs60391380	AA	261 (63.04)	-0.015 (-0.032~0.002)	0.091
	AG+GG	153 (36.96)	-0.024 (-0.043~-0.005)	0.013
rs56108314	TT	261 (63.04)	-0.014 (-0.031~0.003)	0.098
	TC+CC	153 (36.96)	-0.024 (-0.043~-0.005)	0.014
rs73082740	GG	262 (63.28)	-0.014 (-0.031~0.004)	0.122
	GC+CC	152 (36.72)	-0.027 (-0.046~-0.009)	0.005
注：SNPs，单核苷酸多态性；eGFR，估算的肾小球滤过率；BPA，双酚A。 ①采用多元线性回归模型计算，并对年龄、性别、BMI、吸烟状况和饮酒状况进行了调整。 Note: SNPs, single nucleotide polymorphisms; eGFR, estimated glomerular filtration rate; BPA, bisphenol A. ① Calculated using multiple linear regression models and adjusted for age, gender, BMI, smoking status, and drinking status.

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