Affiliated Hospital of Weifang Medical University, School of Clinical Medicine, Weifang Medical University, Weifang, China.
Key Laboratory of Birth Regulation and Control Technology of National Health Commission of China, Shandong Provincial Maternal and Child Health Care Hospital affiliated to Qingdao University, Jinan, China.
Medicine (Baltimore). 2023 Jul 21;102(29):e34420. doi: 10.1097/MD.0000000000034420.
The incidence of autism spectrum disorder (ASD) is increasing year by year in children. The aim of the study was to find possible biomarkers for ASD diagnosis as well as examine MicroRNA (miRNA) signatures and crucial pathways. We conducted a two-stage study to explore potential target genes and functional miRNAs. Peripheral blood samples of children with ASD were enrolled and performed RNA sequencing analysis. The overlapped candidate genes were further screened in combination with differentially expressed genes (DEGs) of GSE77103 datasets. STRING established a protein-protein interaction network comprising DEGs. The hub genes were filtered out using the CytoHubba. Then, we set up a miRNA-mRNA regulatory network. Correlational analyses between hub genes and immune cells associated with ASD were carried out using the CIBERSORT software to assess the diversity of immune cell types in ASD. RNA-sequencing analysis was used to confirm the differential expression of 3 hub genes. Briefly, after blood samples were sequenced interrogating 867 differential genes in our internal screening dataset. After screening GEO databases, 551 DEGs obtained from GSE77103. Fourteen common genes were overlapped through DEGs of GEO datasets and internal screening dataset. Among protein-protein interaction network, 10 hub genes with high degree algorithm were screened out and 3 hub genes of them - ADIPOR1, LGALS3, and GZMB - that were thought to be most associated with the emergence of ASD. Then, we developed a network of miRNA-mRNA regulatory interactions by screening miRNAs (such as hsa-miR-20b-5p, hsa-miR-17-5p, and hsa-miR-216b-5p) that were closely associated to 3 hub genes. Additionally, we discovered 18 different immune cell types associated with ASD using the CIBERSORT algorithm, and we discovered that mononuclear macrophages differed considerably between the 2 groups. Overall, 3 hub genes (ADIPOR1, LGALS3, and GZMB) and 15 candidates miRNAs-target 3 genes regulatory pathways representing potentially novel biomarkers of ASD diseases were revealed. These findings could enhance our knowledge of ASD and offer possible therapeutic targets of ASD patients in the future.
自闭症谱系障碍 (ASD) 在儿童中的发病率逐年上升。本研究旨在寻找 ASD 诊断的可能生物标志物，并研究 MicroRNA (miRNA) 特征和关键途径。我们进行了两阶段研究来探索潜在的靶基因和功能性 miRNA。我们招募了 ASD 儿童的外周血样本并进行了 RNA 测序分析。然后结合 GSE77103 数据集的差异表达基因 (DEGs) 进一步筛选重叠候选基因。STRING 构建了包含 DEGs 的蛋白质-蛋白质相互作用网络。使用 CytoHubba 筛选出枢纽基因。然后，我们建立了 miRNA-mRNA 调控网络。使用 CIBERSORT 软件对与 ASD 相关的枢纽基因和免疫细胞进行相关分析，以评估 ASD 中免疫细胞类型的多样性。使用 RNA-seq 分析确认 3 个枢纽基因的差异表达。简要地说，在我们的内部筛选数据集的血液样本测序后，共检测到 867 个差异基因。通过筛选 GEO 数据库，从 GSE77103 中获得 551 个 DEGs。通过 GEO 数据集和内部筛选数据集的 DEGs 重叠获得 14 个共同基因。在蛋白质-蛋白质相互作用网络中，筛选出 10 个具有高程度算法的枢纽基因，其中 3 个基因 - ADIPOR1、LGALS3 和 GZMB - 被认为与 ASD 的出现最相关。然后，我们通过筛选与 3 个枢纽基因密切相关的 miRNA（如 hsa-miR-20b-5p、hsa-miR-17-5p 和 hsa-miR-216b-5p）构建了 miRNA-mRNA 调控网络。此外，我们使用 CIBERSORT 算法发现了 18 种与 ASD 相关的不同免疫细胞类型，并且发现两组之间单核巨噬细胞有很大差异。总体而言，发现了 3 个枢纽基因 (ADIPOR1、LGALS3 和 GZMB) 和 15 个候选 miRNA-靶向 3 个基因的调控途径，这些可能是 ASD 疾病的潜在新型生物标志物。这些发现可以提高我们对 ASD 的认识，并为未来 ASD 患者提供可能的治疗靶点。
