RESUMEN
Diagnosing Hashimoto thyroiditis (HT) relies on thyroglobulin antibody (TgAb) and thyroid peroxidase antibody (TPOAb) titers. The influence of these antibodies on female infertility remains a subject of debate. This study aims to explore the effect and mechanism of HT on female infertility. First, a single-center cross-sectional study was conducted to investigate whether TgAb and TPOAb are the key factors leading to female infertility. Second, bioinformatic analysis was performed to investigate the potential target molecules and pathways. Third, in vivo experiments were performed to explore the effects of elevated TgAb levels on embryo implantation in a mouse model of autoimmune thyroiditis (AIT). Four hundred and five infertile women and 155 healthy controls were enrolled in the cross-sectional study. Results indicated that the TPOAb titer was associated with female infertility, while the TgAb titer showed no significant association. The increased levels of TgAb and TPOAb are not significantly correlated with anti-Mullerian hormone. Bioinformatic analysis indicated that the common target molecules for HT and female infertility include interleukin (IL)-6, IL-10, matrix metalloproteinase 9, and tumor necrosis factor, suggesting potential regulation through multiple signaling pathways such as HIF-1, VEGF, MAPK, and Th17 cell differentiation. A certain dose of porcine thyroglobulin can successfully establish a mouse model of AIT. In this mouse model, embryo implantation and ovarian reserve remain unaffected by elevated TgAb levels. In conclusion, the serum TPOAb titer was associated with infertility due to female factors but the TgAb titer showed no significant association. A simple increase in serum TgAb titer does not affect embryo implantation and ovarian reserve in the AIT model.
RESUMEN
OBJECTIVE: Screening of feature genes involved in cytokine release syndrome (CRS) from the coronavirus disease 19 (COVID-19). METHODS: The data sets related to COVID-19 were retrieved using Gene Expression Omnibus (GEO) database, the differentially expressed genes (DEGs) related to CRS were analyzed with R software and Venn diagram, and the biological processes and signaling pathways involved in DEGs were analyzed with GO and KEGG enrichment. Core genes were screened using Betweenness and MCC algorithms. GSE164805 and GSE171110 dataset were used to verify the expression level of core genes. Immunoinfiltration analysis was performed by ssGSEA algorithm in the GSVA package. The DrugBank database was used to analyze the feature genes for potential therapeutic drugs. RESULTS: This study obtained 6950 DEGs, of which 971 corresponded with CRS disease genes (common genes). GO and KEGG enrichment showed that multiple biological processes and signaling pathways associated with common genes were closely related to the inflammatory response. Furthermore, the analysis revealed that transcription factors that regulate these common genes are also involved in inflammatory response. Betweenness and MCC algorithms were used for common gene screening, yielding seven key genes. GSE164805 and GSE171110 dataset validation revealed significant differences between the COVID-19 and normal controls in four core genes (feature genes), namely IL6R, TLR4, TLR2, and IFNG. The upregulated IL6R, TLR4, and TLR2 genes were mainly involved in the Toll-like receptor signaling pathway of the inflammatory pathway, while the downregulated IFNG genes primarily participated in the necroptosis and JAK-STAT signaling pathways. Moreover, immune infiltration analysis indicated that higher expression of these genes was associated with immune cell infiltration that mediates inflammatory response. In addition, potential therapeutic drugs for these four feature genes were identified via the DrugBank database. CONCLUSION: IL6R, TLR4, TLR2, and IFNG may be potential pathogenic genes and therapeutic targets for the CRS associated with COVID-19.
