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Abstract：
Renin-angiotensin system inhibitors (RASi) are the first choice and basic therapy for the treatment of IgA nephropathy (IgAN) with proteinuria. However, approximately 40% of patients have no response to RASi treatment. The aim of this study was to screen potential biomarkers for predicting the treatment response of RASi in patients with IgAN.
We included IgAN patients who were treatment-naive. They received supportive treatment, including a maximum tolerant dose of RASi for 3 months. According to the degree of decrease in proteinuria after 3 months of follow-up, these patients were divided into a sensitive group and a resistant group. The plasma of the two groups of patients was collected, and the exosomes were extracted for high-throughput sequencing. The screening of hub genes was performed using a weighted gene co-expression network (WGCNA) and filtering differentially expressed genes (DEGs). We randomly selected 20 patients in the sensitive group and 20 patients in the resistant group for hub gene validation by real-time quantitative polymerase chain reaction (qRT-PCR). A receiver operating characteristic (ROC) curve was used to evaluate hub genes that predicted the efficacy of the RASi response among the 40 validation patients.
After screening 370 IgAN patients according to the inclusion and exclusion criteria and the RASi treatment response evaluation, there were 38 patients in the sensitive group and 32 patients in the resistant group. IRAK1, ABCD1 and PLXNB3 were identified as hub genes by analyzing the high-throughput sequencing of the plasma exosomes of the two groups through WGCNA and DEGs screening. The sequencing data were consistent with the validation data showing that these three hub genes were upregulated in the resistant group compared with the sensitive group. The ROC curve indicated that IRAK1 was a good biomarker to predict the therapeutic response of RASi in patients with IgAN.
Plasma exosomal IRAK1 can be a potential biomarker for predicting the treatment response of RASi in patients with IgAN.
We included IgAN patients who were treatment-naive. They received supportive treatment, including a maximum tolerant dose of RASi for 3 months. According to the degree of decrease in proteinuria after 3 months of follow-up, these patients were divided into a sensitive group and a resistant group. The plasma of the two groups of patients was collected, and the exosomes were extracted for high-throughput sequencing. The screening of hub genes was performed using a weighted gene co-expression network (WGCNA) and filtering differentially expressed genes (DEGs). We randomly selected 20 patients in the sensitive group and 20 patients in the resistant group for hub gene validation by real-time quantitative polymerase chain reaction (qRT-PCR). A receiver operating characteristic (ROC) curve was used to evaluate hub genes that predicted the efficacy of the RASi response among the 40 validation patients.
After screening 370 IgAN patients according to the inclusion and exclusion criteria and the RASi treatment response evaluation, there were 38 patients in the sensitive group and 32 patients in the resistant group. IRAK1, ABCD1 and PLXNB3 were identified as hub genes by analyzing the high-throughput sequencing of the plasma exosomes of the two groups through WGCNA and DEGs screening. The sequencing data were consistent with the validation data showing that these three hub genes were upregulated in the resistant group compared with the sensitive group. The ROC curve indicated that IRAK1 was a good biomarker to predict the therapeutic response of RASi in patients with IgAN.
Plasma exosomal IRAK1 can be a potential biomarker for predicting the treatment response of RASi in patients with IgAN.
摘要：
肾素-血管紧张素系统抑制剂(RASi)是治疗蛋白尿IgA肾病(IgAN)的首选药物和基础治疗方法。然而,约40%的患者对RASi治疗无反应.这项研究的目的是筛选潜在的生物标志物，以预测IgAN患者RASi的治疗反应。
我们纳入了未接受治疗的IgAN患者。他们接受了支持性治疗,包括3个月的最大耐受剂量的RASi。根据随访3个月后蛋白尿的减少程度,这些患者被分为敏感组和耐药组。收集两组患者的血浆，并提取外泌体进行高通量测序。使用加权基因共表达网络(WGCNA)和过滤差异表达基因(DEGs)进行hub基因的筛选。我们随机选择敏感组的20例患者和耐药组的20例患者通过实时定量聚合酶链反应（qRT-PCR）进行hub基因验证。使用接受者操作特征(ROC)曲线来评估预测40名验证患者中的RASi应答的功效的中枢基因。
根据纳入和排除标准和RASi治疗反应评估筛选370例IgAN患者后，敏感组38例，耐药组32例。IRAK1、ABCD1和PLXNB3通过WGCNA和DEGs筛选对两组的血浆外泌体进行高通量测序,鉴定为hub基因。测序数据与验证数据一致,表明与敏感组相比,这三个hub基因在抗性组中上调。ROC曲线表明IRAK1是预测IgAN患者RASi治疗反应的良好生物标志物。
血浆外泌体IRAK1可能是预测IgAN患者RASi治疗反应的潜在生物标志物。
我们纳入了未接受治疗的IgAN患者。他们接受了支持性治疗,包括3个月的最大耐受剂量的RASi。根据随访3个月后蛋白尿的减少程度,这些患者被分为敏感组和耐药组。收集两组患者的血浆，并提取外泌体进行高通量测序。使用加权基因共表达网络(WGCNA)和过滤差异表达基因(DEGs)进行hub基因的筛选。我们随机选择敏感组的20例患者和耐药组的20例患者通过实时定量聚合酶链反应（qRT-PCR）进行hub基因验证。使用接受者操作特征(ROC)曲线来评估预测40名验证患者中的RASi应答的功效的中枢基因。
根据纳入和排除标准和RASi治疗反应评估筛选370例IgAN患者后，敏感组38例，耐药组32例。IRAK1、ABCD1和PLXNB3通过WGCNA和DEGs筛选对两组的血浆外泌体进行高通量测序,鉴定为hub基因。测序数据与验证数据一致,表明与敏感组相比,这三个hub基因在抗性组中上调。ROC曲线表明IRAK1是预测IgAN患者RASi治疗反应的良好生物标志物。
血浆外泌体IRAK1可能是预测IgAN患者RASi治疗反应的潜在生物标志物。
