ABSTRACT
Background: Both the mother and the infant are negatively impacted by macrosomia. Macrosomia is three times as common in hyperglycemic mothers as in normal mothers. This study sought to determine why hyperglycemic mothers experienced higher macrosomia. Methods: Hematoxylin and Eosin staining was used to detect the placental structure of normal mother(NN), mothers who gave birth to macrosomia(NM), and mothers who gave birth to macrosomia and had hyperglycemia (DM). The gene expressions of different groups were detected by RNA-seq. The differentially expressed genes (DEGs) were screened with DESeq2 R software and verified by qRT-PCR. The STRING database was used to build protein-protein interaction networks of DEGs. The Cytoscape was used to screen the Hub genes of the different group. Results: The NN group's placental weight differed significantly from that of the other groups. The structure of NN group's placenta is different from that of the other group, too. 614 and 3207 DEGs of NM and DM, respectively, were examined in comparison to the NN group. Additionally, 394 DEGs of DM were examined in comparison to NM. qRT-PCR verified the results of RNA-seq. Nucleolar stress appears to be an important factor in macrosomia, according on the results of KEGG and GO analyses. The results revealed 74 overlapped DEGs that acted as links between hyperglycemia and macrosomia, and 10 of these, known as Hub genes, were key players in this process. Additionally, this analysis believes that due of their close connections, non-overlapping Hubs shouldn't be discounted. Conclusion: In diabetic mother, ten Hub genes (RPL36, RPS29, RPL8 and so on) are key factors in the increased macrosomia in hyperglycemia. Hyperglycemia and macrosomia are linked by 74 overlapping DEGs. Additionally, this approach contends that non-overlapping Hubs shouldn't be ignored because of their tight relationships.
Subject(s)
Diabetes, Gestational , Fetal Macrosomia , RNA-Seq , Humans , Pregnancy , Female , Fetal Macrosomia/genetics , Diabetes, Gestational/genetics , Diabetes, Gestational/metabolism , Adult , Placenta/metabolism , Placenta/pathology , Protein Interaction Maps , Hyperglycemia/genetics , Hyperglycemia/metabolism , Gene Expression Profiling , Infant, NewbornABSTRACT
Diabetic retinopathy (DR) is a main factor affecting vision of patients, and its pathogenesis is not completely clear. The purpose of our study was to investigate correlations between MST2 and DR progression, and to study the possible mechanism of MST2 and its down pathway in high glucose (HG)-mediated RGC-5 apoptosis. The diabetic rat model was established by intraperitoneal injection of streptozotocin (STZ) 60 mg/kg. HE and TUNEL staining were used to evaluate the pathological changes and apoptosis of retinal cells in rats. Western blot, qRT-PCR and immunohistochemistry showed that levels of MST2 were increased in diabetic group (DM) than control. In addition, the differential expression of MST2 is related to HG-induced apoptosis of RGC-5 cells. CCK-8 and Hoechst 33,342 apoptosis experiments showed that MST2 was required in HG-induced apoptosis of RGC-5 cells. Further research revealed that MST2 regulated the protein expression of YAP1 at the level of phosphorylation in HG-induced apoptosis. Simultaneously, we found that Xmu-mp-1 acts as a MST2 inhibitor to alleviate HG-induced apoptosis. In summary, our study indicates that the MST2/YAP1 signaling pathway plays an important role in DR pathogenesis and RGC-5 apoptosis. This discovery provides new opportunities for future drug development targeting this pathway to prevent DR.
Subject(s)
Diabetes Mellitus, Experimental , Diabetic Retinopathy , Humans , Rats , Animals , Diabetic Retinopathy/metabolism , Diabetic Retinopathy/pathology , Diabetes Mellitus, Experimental/complications , Signal Transduction , Apoptosis , In Situ Nick-End LabelingABSTRACT
The normal aging process is accompanied by cognitive decline, and previous studies have indicated the crucial role of the hypothalamus in regulating both aging and cognition. However, the precise molecular mechanism underlying this relationship remains unclear. Therefore, this present study aimed to identify potential predictors of cognitive decline associated with aging specifically within the hypothalamus. To achieve this, we employed Morris water maze (MWM) testing to assess learning and memory differences between young and aged mice. Additionally, transcriptome sequencing was conducted on the hypothalamus of young and aged mice to identify potential genes. Subsequently, GO and KEGG analyses were performed to investigate the functions of differentially expressed genes (DEGs) and their associated biological pathways. Finally, the results obtained from sequencing analysis were further validated using qRT-PCR. Notably, MWM testing revealed a significant decrease in spatial learning and memory ability among aged mice. According to KEGG analysis, the DEGs primarily encompassed various biochemical signaling pathways related to immune system (e.g., C3; C4b; Ccl2; Ccl7; Cebpb; Clec7a; Col3a1; Cxcl10; Cxcl2; Fosb; Fosl1; Gbp5; H2-Ab1; Hspa1a; Hspa1b; Icam1; Il1b; Itga5; Itgax; Lilrb4a; Plaur; Ptprc; Serpine1; Tnfrsf10b; Tnfsf10), neurodegenerative disease (e.g., Atp2a1; Creb5; Fzd10; Hspa1a; Hspa1b; Il1b; Kcnj10; Nxf3; Slc6a3; Tubb6; Uba1y; Wnt9b), nervous system function (e.g., Chrna4; Chrna6; Creb5; Slc6a3),and aging (e.g., Creb5; Hspa1a; Hspa1b) among others. These identified genes may serve as potential predictors for cognitive function in elderly individuals and will provide a crucial foundation for further exploration into the underlying molecular mechanisms.
Subject(s)
Cognitive Dysfunction , Neurodegenerative Diseases , Humans , Mice , Animals , Aged , Gene Expression Profiling , Aging/genetics , Cognitive Dysfunction/genetics , Hypothalamus , TranscriptomeABSTRACT
DNA methylation plays an important role in the occurrence and development of age-related cataracts (ARC). This study aims to reveal potential epigenetic biomarkers of ARC by detecting modifications to the DNA methylation patterns of genes shown to be related to ARC by transcriptomics. The MethylationEPIC BeadChip (850 K) was used to analyze the DNA methylation levels in ARC patients and unaffected controls, and the Pearson correlation test was used to perform genome-wide integration analysis of DNA methylation and transcriptome data. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases were used to perform functional analysis of the whole genome, promoter regions (TSS1500/TSS200), and the associated differentially methylated genes (DMG). Pyrosequencing was used to verify the methylation levels of the selected genes. The results showed that, compared with the control group, a total of 52,705 differentially methylated sites were detected in the ARC group, of which 13,858 were hypermethylated and 38,847 were hypomethylated. GO and KEGG analyses identified functions related to the cell membrane, the calcium signaling pathway, and their possible molecular mechanisms. Then, 57 DMGs with negative promoter methylation correlations were screened by association analysis. Pyrosequencing verified that the ARC group had higher methylation levels of C3 and CCKAR and lower methylation levels of NLRP3, LEFTY1, and GPR35 compared with the control group. In summary, our study reveals the whole-genome DNA methylation patterns and gene expression profiles in ARC, and the molecular markers of methylation identified herein may aid in the prevention, diagnosis, treatment, and prognosis of ARC.