Key Features
Enhance your research with our curated data sets and powerful platform features. Pluto Bio makes it simple to find and use the data you need.
Learn MoreAging of uterine endometrium is a critical factor that affects reproductive success, but the mechanistic details are unclear. In this study, we conducted a qualitative examination of age-related changes in endometrial tissues and identified candidate genes as markers for uterine aging. Gene expression in uteri obtained from wild type (WT) C57BL/6 mice at 5, 8 and 60-75 (aged) weeks of age and from 5-week-old klotho mice, a model mouse of progeria, were analyzed in duplicate by RNA-sequencing and compared. Genes expressing the pro-inflammatory cytokines Il17rb and chemokines Ccl21a, Cxcl12 and Cxcl14 were among the differentially expressed genes extracted from comparisons between 5w-WT and aged-WT mice as well as 8w-WT and aged-WT mice. RNA-sequencing gene expression data were validated by real-time PCR. Protein expression levels of the extracted genes and Il8, a downstream protein of Il17rb signal, in normal human endometrium tissue samples in their 20s and 40s (10 cases each) were analyzed by quantitative immunohistochemistry using DAB staining. In these samples belonging to secretory phase, the DAB staining intensity of IL17RB, CCL21, CXCL12 and CXCL14 for patients in their 40s were significantly higher than those for patients in their 20s, as detected by Mann Whitney U test. The potential of these candidate genes as markers for endometrial aging should be confirmed by larger studies. If significant differences in protein expression from these genes are confirmed between fertile and infertile women, these genes could be used as markers to predict infertility due to endometrial aging. SOURCE: Teruhiko Kawamura (teruhiko@gynob.med.kyushu-u.ac.jp) - Kyushu University
View on GEOView in PlutoEnhance your research with our curated data sets and powerful platform features. Pluto Bio makes it simple to find and use the data you need.
Learn MoreUse Pluto's intuitive interface to analyze and visualize data for this experiment. Pluto's platform is equipped with an API & SDKs, making it easy to integrate into your internal bioinformatics processes.
Read about post-pipeline analysisView quality control data and experiment metadata for this experiment.
Request imports from GEO or TCGA directly within Pluto Bio.
Chat with our Scientific Insights team