Department of Endocrinology, Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan, 250012, Shandong, China.
Department of Endocrinology, Qingdao Municipal Hospital, Qingdao University, Qingdao, 266071, Shandong, China.
Mol Cell Biochem. 2022 Jul;477(7):1931-1946. doi: 10.1007/s11010-022-04420-5. Epub 2022 Mar 31.
The objective of this study was to identify different transcriptome expression profiles involved in the pathogenesis of diabetic nephropathy (DN) and to illustrate the diagnostic and therapeutic potential of mRNAs, long noncoding RNAs (lncRNAs), and circular RNAs (circRNAs) in DN progression. The participants were divided into four groups: normoalbuminuria (group DM), microalbuminuria (group A2), macroalbuminuria (group A3) and healthy controls (group N). There were three individuals in each group for sequencing. Transcriptome sequencing analysis was performed on the peripheral blood of all the participants to identify the differential expression of mRNAs, lncRNAs, and circRNAs between intervention groups and controls. The functional enrichment analysis, the short time-series expression miner (STEM) program, and the miRNA-circRNA-mRNA network were further conducted. To verify the reproducibility of transcriptome sequencing, 10 and 30 blood samples were collected from the control and diseased groups, respectively. Four candidate biomarkers were selected from differentially expressed circRNAs (circ_0005379, circ_0002024, and circ_0000567, and circ_0001017) and their concentrations in the blood were measured using quantitative PCR (qPCR). In the comparison of A2 with N, 549 mRNAs, 1259 lncRNAs, and 12 circRNAs were screened. In the comparison of A3 with N, 1217 mRNAs, 1613 lncRNAs, and 24 circRNAs were screened. Moreover, in the comparison of diabetes mellitus (DM) with N, 948 mRNAs, 1495 lncRNAs, and 25 circRNAs were screened. Functional enrichment analysis showed that differentially expressed mRNAs were related to insulin secretion, insulin resistance, and inflammation, while differentially expressed lncRNAs were mainly associated with crossover junction endodeoxyribonuclease activity. In STEM analysis, a total of 481 mRNAs and 152 differential expression circRNAs showed a significant tendency. The key relationships in the miRNA-circRNA-mRNA network were identified, such as hsa-miR-103a-3p-circ_0005379-PTEN, hsa-miR-497-5p-circ_0002024-IGF1R and hsa-miR-1269a-circ_0000567-SOX6. In addition, qPCR showed consistent results with RNA sequencing. We found that differentially expressed mRNAs, lncRNAs, and circRNAs participated in DN development. Circ_0005379, circ_0002024, and circ_0000567 could be adopted as potential biomarkers for DN.
本研究旨在鉴定参与糖尿病肾病（DN）发病机制的不同转录组表达谱，并阐明 mRNAs、长链非编码 RNA（lncRNAs）和环状 RNA（circRNAs）在 DN 进展中的诊断和治疗潜力。参与者被分为四组：正常白蛋白尿（组 DM）、微量白蛋白尿（组 A2）、大量白蛋白尿（组 A3）和健康对照组（组 N）。每组有 3 个人进行测序。对所有参与者的外周血进行转录组测序分析，以鉴定干预组与对照组之间 mRNAs、lncRNAs 和 circRNAs 的差异表达。进一步进行功能富集分析、短期时间序列表达 miner（STEM）程序和 miRNA-circRNA-mRNA 网络分析。为了验证转录组测序的重现性，分别从对照组和病变组采集了 10 个和 30 个血液样本。从差异表达的 circRNAs（circ_0005379、circ_0002024 和 circ_0000567 以及 circ_0001017）中选择了四个候选生物标志物，并使用定量 PCR（qPCR）测量了它们在血液中的浓度。在 A2 与 N 的比较中，筛选到 549 个 mRNAs、1259 个 lncRNAs 和 12 个 circRNAs。在 A3 与 N 的比较中，筛选到 1217 个 mRNAs、1613 个 lncRNAs 和 24 个 circRNAs。此外，在糖尿病（DM）与 N 的比较中，筛选到 948 个 mRNAs、1495 个 lncRNAs 和 25 个 circRNAs。功能富集分析表明，差异表达的 mRNAs 与胰岛素分泌、胰岛素抵抗和炎症有关，而差异表达的 lncRNAs 主要与交叉连接末端核酸酶活性有关。在 STEM 分析中，总共筛选到 481 个 mRNAs 和 152 个差异表达的 circRNAs 呈现出显著的趋势。确定了 miRNA-circRNA-mRNA 网络中的关键关系，例如 hsa-miR-103a-3p-circ_0005379-PTEN、hsa-miR-497-5p-circ_0002024-IGF1R 和 hsa-miR-1269a-circ_0000567-SOX6。此外，qPCR 结果与 RNA 测序结果一致。我们发现，差异表达的 mRNAs、lncRNAs 和 circRNAs 参与了 DN 的发展。circ_0005379、circ_0002024 和 circ_0000567 可以作为 DN 的潜在生物标志物。
