m<sup>6</sup>A甲基化调节因子在慢性肾脏病中的预测价值

崔超群; 张帆; 李怡淳; 张铁如; 周涵; 雷立健

doi:10.16462/j.cnki.zhjbkz.2024.11.015

m⁶A甲基化调节因子在慢性肾脏病中的预测价值

doi: 10.16462/j.cnki.zhjbkz.2024.11.015

崔超群¹,
张帆¹,
李怡淳¹,
张铁如¹,
周涵¹,
雷立健^{1, 2, 3, ,}

1.
山西医科大学公共卫生学院流行病学教研室，太原 030001
2.
煤炭环境致病与防治教育部重点实验室，太原 030001
3.
山西医科大学环境污染与重大慢病流行病学研究中心，太原 030001

基金项目:

国家自然科学基金 81872701

详细信息

通讯作者:
雷立健，E-mail: wwdlijian@sxmu.edu.cn

中图分类号: R181
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- 被引次数: 0
出版历程
- 收稿日期: 2024-07-22
- 修回日期: 2024-10-15
- 网络出版日期: 2024-12-23
- 刊出日期: 2024-11-10

The predictive value of m⁶A methylation regulators in chronic kidney disease

CUI Chaoqun¹,
ZHANG Fan¹,
LI Yichun¹,
ZHANG Tieru¹,
ZHOU Han¹,
LEI Lijian^{1, 2, 3
, ,}

1.
Department of Epidemiology, School of Public Health, Shanxi Medical University, Taiyuan 030001, China
2.
MOE Key Laboratory of Coal Environmental Pathogenicity and Prevention, Shanxi Medical University, Taiyuan 030001, China
3.
Research Centre of Environmental Pollution and Major Chronic Diseases Epidemiology, Shanxi Medical University, Taiyuan 030001, China

Funds:

National Natural Science Foundation of China 81872701

More Information

Corresponding author: LEI Lijian, E-mail: wwdlijian@sxmu.edu.cn

摘要

摘要: 目的研究RNA N⁶-甲基腺嘌呤(N⁶-methyladenosine, m⁶A)甲基化调节因子在慢性肾脏病(chronic kidney disease, CKD)中的表达变化，为疾病预防提供新的思路和靶点。方法选取中国华北地区某市社区人群作为研究对象，比较病例组(151人)和对照组(362人)基线特征，并分析RNA m⁶A甲基化调节因子和肾功能指标的相关性，利用LASSO回归筛选相关变量用于构建多因素logistic回归分析模型；通过受试者工作特征曲线、校准曲线和决策曲线对模型进行验证。结果病例组中甲基转移酶样蛋白14(methyltransferase like 14, METTL14)表达水平更高(P＜0.05)，相关性分析结果显示，METTL14(r_s=-0.110, P＜0.05)、去甲基化酶AlkB同源物5(human Alk B homolog 5, ALKBH5)(r_s=-0.218, P＜0.001)均与转化生长因子(transforming growth factor, TGF)-β1呈负相关；脂肪量和肥胖相关蛋白(fat mass and obesity-associated protein, FTO)与尿素(r_s=0.169, P＜0.001)、TGF-β1(r_s=0.088, P＜0.05)均呈正相关。回归分析结果显示，性别、年龄、血肌酐、METTL14、总胆固醇和家庭人均月收入是CKD患病的预测因子(均P＜0.05)。基于此构建风险预测模型，曲线下面积(area under curve, AUC)值为0.796(95% CI: 0.752~0.840)，Bootstrap法验证平均绝对误差值为0.036，通过Hosmer-Lemeshow拟合优度检验，预测模型有较好的校准能力(χ² =12.57, P=0.128)。结论 METTL14在CKD患者中表达水平较高，与CKD发生风险存在相关性。
- 慢性肾脏病 /
- RNA甲基化 /
- 列线图 /
- LASSO回归
Abstract: Objective To investigate in the expression changes of RNA N⁶-methyladenosine (m⁶A) methylation regulators in patients with chronic kidney disease (CKD) and provide novel ideas for disease prevention. Methods A community population in a city in North China was selected to compare the baseline characteristics between the case group (151) and control (362) group. The correlation between the expression of the regulators of RNA m⁶A methylation and renal function-related indexes was analyzed. Screening of relevant variables for the construction of multivariable logistic regression models using LASSO regression, and its validity was assessed using the receiver operating characteristic curve (ROC), calibration curve and decision curve analysis (DCA). Results The expression level of methyltransferase like 14 (METTL14) was higher in the case group (P < 0.05). Correlation analysis revealed that METTL14 (r_s=-0.110, P < 0.05) and human Alk B homolog 5 (ALKBH5) (r_s=-0.218, P < 0.001) were negatively correlated with transforming growth factor (TGF)-β1. Fat mass and obesity-associated protein (FTO) was positively correlated with Urea (r_s=0.169, P < 0.001) and TGF-β1 (r_s=0.088, P < 0.05). The regression analysis results indicated that gender, age, serum creatinine, METTL14, total cholesterol, and per capita monthly household income were predictors for CKD (all P < 0.05). A risk prediction model was constructed based on this, and the area under the curve (AUC) was 0.796 (95% CI: 0.752-0.840). The average absolute error verified by bootstrap method was 0.036. The Hosmer Lemeshow goodness of fit test showed that the prediction model had good calibration ability (χ² =12.57, P=0.128). Conclusions The expression level of METTL14 is higher in patients with CKD. There is a correlation between METTL14 and the development of CKD.
- Chronic kidney disease /
- RNA methylation /
- Nomograms /
- LASSO regression

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图 1 两组间甲基转移酶和去甲基化酶的相对表达量

a: 指与对照组相比，差异有统计学意义(Z=-2.410，P=0.016)。

Figure 1. Relative expression levels of methylation transferase and demethylase between two groups

a: refers to a statistically significant difference compared to the control group(Z=-2.410, P < 0.05).

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图 2 m⁶A甲基化调节因子与TGF-β1及肾功能指标的相关性矩阵散点图

m⁶A: RNA N⁶-甲基腺嘌呤; ALKBH5: 去甲基化酶AlkB同源物5; FTO: 脂肪量和肥胖相关蛋白; METTL3: 甲基转移酶样蛋白3; METTL14: 甲基转移酶样蛋白14; UNAG，β-N-乙酰氨基葡萄糖苷酶; TGF-β1，转化生长因子-β1; SCr，血肌酐; a：P＜0.05；b：P＜0.01；c：P＜0.001。

Figure 2. Correlation matrix scatter plot of m⁶A methylation regulators with TGF-β1 and renal function indices

m⁶A: N⁶-methyladenosine; ALKBH5: human Alk B homolog 5; FTO: fat mass and obesity-associated protein; METTL3: methyltransferase like 3; METTL14: methyltransferase like 14; UNAG, urinary β-N-acetyl-glucosidase; TGF-β1, transforming growth factor-β1; SCr, serum creatinine; a: P < 0.05;b: P < 0.01;c: P < 0.001。

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图 3 基于LASSO回归的特征变量选择

A：十倍交叉验证图；B：收缩系数图。

Figure 3. Predictors selection based on LASSO regression

A: ten fold cross-validation profile; B: LASSO coefficient profile.

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图 4 慢性肾脏病患病风险预测模型列线图和验证

A：列线图；B：风险预测模型ROC曲线图；C：校准曲线图；D：决策曲线图。

Figure 4. Nomogram of risk prediction model of chronic kidney disease and model validation

A: nomogram; B: ROC curves of risk prediction model; C: calibration curve; D: decision curve analysis.

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表 1 研究对象的基本特征

Table 1. Basic characteristics of study subjects

变量 Variable	对照组 Control group^① (n=362)	病例组 Case group^① (n=151)	χ²/Z值 value	P值 value
性别 Gender			17.409	< 0.001
女性 Female	174(48.1)	103(68.2)
男性 Male	188(51.9)	48(31.8)
年龄/岁 Age/years	66(63, 70)	69(65, 75)	-4.817	< 0.001
婚姻状态 Marital status			10.058	0.002
非在婚(未婚、离异、丧偶等) Non-marital (unmarried, divorced, widowed, etc)	42(11.6)	34(22.5)
在婚 In marriage	320(88.4)	117(77.5)
受教育程度 Educational attainment			-2.164	0.030
小学及以下 Elementary school and below	66(18.2)	34(22.5)
初中 Junior high school	118(32.6)	57(37.7)
专科/高中 Junior college/high School	146(40.3)	54(35.8)
本科及以上 Bachelor′s degree or above	32(8.8)	6(3.9)
家庭人均月收入/元 Household per capita monthly income/yuan			-1.551	0.121
＜3 000	154(42.5)	67(44.4)
3 000~＜5 000	159(43.9)	80(53.0)
5 000~＜7 000	34(9.4)	3(2.0)
≥7 000	15(4.1)	1(0.7)
吸烟 Smoking			1.886	0.170
否 No	288(79.6)	128(84.8)
是 Yes	74(20.4)	23(15.2)
周围人吸烟情况 Smoking by people around you			1.184	0.277
否 No	280(77.3)	110(72.8)
是 Yes	82(22.7)	41(27.2)
饮酒 Drinking			5.221	0.022
否 No	303(83.7)	138(91.4)
是 Yes	59(16.3)	13(8.6)
体育锻炼 Physical activity			-1.405	0.160
每天 Every day	264(72.9)	118(78.1)
每周3~5次 3-5 times a week	20(5.5)	8(5.3)
每周≤2次 ≤2 times a week	25(6.9)	12(7.9)
基本不运动 Basically no exercise	53(14.6)	13(8.6)
睡眠(自评) Sleep(self-rated)			-0.857	0.392
好 Good	227(62.7)	100(66.2)
一般 Not bad	60(16.6)	25(16.6)
不好 Bad	75(20.7)	26(17.2)
BMI/(kg·m^-2)			6.539	0.011
＜28	278(76.8)	131(86.8)
≥28	84(23.2)	20(13.2)
糖尿病 Diabetes			0.698	0.403
否 No	290(80.1)	116(76.8)
是 Yes	72(19.9)	35(23.2)
高血压 Hypertension			0.134	0.715
否 No	171(47.2)	74(49.0)
是 Yes	191(52.8)	77(51.0)
冠心病 Coronary heart disease			7.481	0.006
否 No	321(88.7)	120(79.5)
是 Yes	41(11.3)	31(20.5)
TC/(mmol·L^-1)			-0.670	0.503
＜5.2	204(56.4)	84(55.6)
5.2~＜6.2	111(30.7)	38(25.2)
≥6.2	47(13.0)	29(19.2)
TG/(mmol·L^-1)			-0.492	0.623
＜1.7	209(57.7)	93(61.6)
1.7~＜2.3	82(22.7)	26(17.2)
≥2.3	71(19.6)	32(21.2)
LDL-C/(mmol·L^-1)			-2.477	0.013
＜3.4	291(80.4)	106(70.2)
3.4~＜4.1	45(12.4)	29(19.2)
≥4.1	26(7.2)	16(10.6)
HDL-C/(mmol·L^-1)			2.019	0.155
＜1	21(5.8)	14(9.3)
≥1	341(94.2)	137(90.7)
尿素 Urea/(mmol·L^-1)	4.90(4.20, 5.70)	5.45(4.60, 6.30)	-3.928	< 0.001
SCr/(μmol·L^-1)	64.80(57.20, 75.00)	83.70(67.70, 92.10)	-8.626	< 0.001
UNAG/(U·g^-1Cr)	9.65(4.70, 17.74)	11.44(5.31, 20.50)	-0.939	0.348
TGF-β1/(ng·mL^-1)	27.31(13.35, 50.02)	23.57(10.82, 43.75)	-1.643	0.100
注：TC，总胆固醇；TG，三酰甘油；LDL-C，低密度脂蛋白胆固醇；HDL-C，高密度脂蛋白胆固醇；SCr，血肌酐；UNAG，β-N-乙酰氨基葡萄糖苷酶；TGF-β1，转化生长因子-β1。 ①以人数(占比/%)或M(P₂₅, P₇₅)表示。 Note: TC, total cholesterol; TG, triglyceride; LDL-C, low-density lipoprotein cholesterol; HDL-C, high-density lipoprotein cholesterol; SCr, serum creatinine; UNAG, urinary β-N-acetyl-glucosidase; TGF-β1, transforming growth factor-β1. ① Number of people (proportion/%) or M(P₂₅, P₇₅).

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表 2 慢性肾脏病患病风险的多因素logistic回归分析

Table 2. Multivariate logistic regression model of chronic kidney disease risk

变量 Variable	β值 value	s_x值 value	Wald值 value	P值 value	OR值 value (95% CI)
性别 Gender	-0.689	0.238	8.346	0.004	0.502(0.315~0.801)
年龄/岁 Age/years	0.059	0.015	15.134	< 0.001	1.061(1.030~1.093)
肥胖 Obesity	-0.481	0.298	2.596	0.107	0.618(0.345~1.110)
SCr/(μmol·L^-1)	0.038	0.006	34.334	< 0.001	1.039(1.026~1.052)
lg(METTL14)	0.635	0.266	5.698	0.017	1.886(1.120~3.176)
TGF-β1/(ng·mL^-1)	-0.006	0.005	2.584	0.108	0.994(0.987~1.001)
TC/(mmol·L^-1)
< 5.2
5.2~＜6.2	-0.014	0.260	0.003	0.956	0.986(0.593~1.640)
≥6.2	1.097	0.330	11.071	< 0.001	2.996(1.570~5.718)
家庭人均月收入/元 Household per capita monthly income/yuan
< 3 000
3 000~＜5 000	0.072	0.234	0.095	0.758	1.075(0.679~1.701)
5 000~＜7 000	-2.482	0.897	7.658	0.006	0.084(0.014~0.485)
≥7 000	-1.514	1.092	1.924	0.165	0.220(0.026~1.869)
注：TC，总胆固醇；SCr，血肌酐；METTL14，甲基转移酶样蛋白14；TGF-β1，转化生长因子-β1。 Note: TC, total cholesterol; SCr, serum creatinine; METTL14, methyltransferase like 14; TGF-β1, transforming growth factor-β1.

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