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| miR-146a表达水平与癫痫患者脑电图特征及抗癫痫药物耐药风险的相关性 |
| Correlation between miR-146a expression level and epileptic patients' EEG characteristics and risk of anti-epileptic drug resistance |
| 投稿时间：2025-11-21 |
| DOI：10.3969/j.issn.1000-0399.2026.08.012 |
| 中文关键词: 微小RNA-146a 癫痫 抗癫痫药物 耐药 |
| 英文关键词: MiR-146a Epilepsy Antiepileptic drugs Drug resistance |
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| 摘要点击次数: 117 |
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| 中文摘要: |
| 目的 探讨外周血微小RNA-146a(miR-146a)表达水平与癫痫患者脑电图（EEG）特征及抗癫痫药物耐药风险的相关性，为预测抗癫痫药物耐药性提供依据。方法 回顾性选取滁州市第一人民医院康复医学科2022年4月至2025年4月收治癫痫患者122例作为研究对象，根据抗癫痫药物耐药性分为耐药组（n=38）和非耐药组（n=84），测定两组脑电图特征。收集同期进行健康体检者作为对照组（n=45），测量3组研究对象miR-146a水平，采用相关性分析探讨miR-146a表达水平与癫痫患者脑电图（EEG）特征的关联性。采用多因素logistic回归筛选影响因素，并绘制受试者工作特征（ROC）曲线评价miR-146a表达水平对抗癫痫药物耐药风险的预测价值。结果 3组研究对象miR-146a表达水平对比，耐药组miR-146a表达水平最高，非耐药组次之，对照组最低，差异有统计学意义（F=38.402,P<0.001）；耐药组癫痫样放电频率、放电指数、δ波功率、θ波功率较非耐药组高，α波功率、β波功率较非耐药组低，差异有统计学意义（P<0.05）；相关性分析显示，miR-146a表达水平与癫痫样放电频率、癫痫样放电指数、δ波功率、θ波功率呈正相关，与α波功率、β波功率呈负相关（P<0.05），多因素logistic分析显示，癫痫样放电频率（OR=2.293,95%CI:1.360～3.867）、δ波功率（OR=1.219,95%CI:1.029～1.443）、miR-146a表达水平（OR=2.293,95%CI:1.038～13.278）是抗癫痫药物耐药的危险因素，α波功率（OR=0.778,95%CI:0.624～0.969）、β波功率（OR=0.697,95%CI:0.518～0.938）为其保护因素（P<0.05）。ROC曲线显示，miR-146a表达水平预测癫痫患者抗癫痫药物耐药风险的曲线下面积（AUC）为0.731(95%CI:0.643～0.807),Delong检验显示，miR-146a水平预测耐药风险的效能与α波功率、β波功率、δ波功率及癫痫样放电频率相比，差异均无统计学意义（Z=0.309,P=0.757;Z=0.396,P=0.692;Z=0.142,P=0.887;Z=1.302,P=0.193）。指标联合AUC为0.952(95%CI:0.917～0.988)，高于单一指标（P<0.05）。结论 miR-146a表达水平与癫痫患者脑电图异常特征及抗癫痫药物耐药风险密切相关，其可作为预测耐药风险的潜在生物标志物。 |
| 英文摘要: |
| Objective To investigate the correlation between peripheral blood miR-146a expression levels and EEG characteristics as well as the risk of antiepileptic drug resistance in patients with epilepsy, so as to provide a basis for assessing AED resistance.Methods A retrospective study was conducted on 122 epilepsy patients admitted to the Department of Rehabilitation Medicine at Chuzhou First People's Hospital from April 2022 to April 2025. These patients were classified into a drug-resistant group(n=38) and a non-drug-resistant group(n=84) based on their resistance to antiepileptic drugs, and their EEG characteristics were analyzed. Additionally, 45 healthy individuals undergoing routine physical examinations during the same period were enrolled as a control group. The miR-146a levels were measured in all three groups, and correlation analysis was performed to investigate the association between miR-146a expression levels and EEG features. Multivariate logistic regression was employed to identify influencing factors, and a receiver operating characteristic(ROC) curve was plotted to evaluate the predictive value of miR-146a expression levels for the risk of antiepileptic drug resistance.Results There was a statistical difference in the expression level of miR-146a among the three groups(P<0.001), among which the expression level of miR-146a was the highest in the drug-resistant group, followed by the non-drug-resistant group and the lowest in the control group(P<0.05).The anti-drug epilepsy-like discharge frequency, discharge index, δ-wave power, and θ-wave power in the drug-resistant group were higher than those in the non-drug-resistant group, while α-wave and β-wave power were lower(P<0.05). Correlation analysis revealed that miR-146a expression levels showed positive correlations with epilepsy-like discharge frequency, discharge index, δ-wave power, and θ-wave power, but negative correlations with α-wave and β-wave power(P<0.05). Multivariate logistic analysis revealed that epileptiform discharge frequency(OR=2.293,95%CI:1.360～3.867), δ-wave power(OR=1.219,95%CI:1.029～1.443), and miR-146a expression level(OR=2.293,95%CI:1.038～13.278) were risk factors for resistance to antiepileptic drugs, whereas α-wave power(OR=0.778,95%CI:0.624～0.969) and β-wave power(OR=0.697,95%CI:0.518～0.938) were protective factors against drug resistance(P<0.05). The ROC curve analysis indicated that the AUC for predicting anti-drug medication resistance risk in epilepsy patients using miR-146a expression levels was 0.731(95%CI:0.643～0.807).Delong's test demonstrated that the predictive efficacy of miR-146a levels for drug resistance risk showed no statistically significant differences compared to α-wave power, β-wave power, δ-wave power, or epileptiform discharge frequency(Z=0.309, P=0.757; Z=0.396, P=0.692; Z=0.142, P=0.887; Z=1.302, P=0.193).The combined AUC of the indicators was 0.952(95%CI:0.917～0.988), significantly higher than that of a single indicator(P<0.05).Conclusion The expression level of miR-146a is closely related to the abnormal characteristics of epileptic patients' EEG and the risk of anti-epileptic drug resistance, and it can be used as a potential biomarker to predict the risk of drug resistance. |
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