Dysregulation in Multiple Transcriptomic Endometrial Pathways Is Associated with Recurrent Implantation Failure and Recurrent Early Pregnancy Loss.
Norhayati Liaqat Ali KhanTamer NafeeTingting ShaoAmber Rose HartSarah ElliottBolarinde OlaPaul Roy HeathAlireza FazeliPublished in: International journal of molecular sciences (2022)
Overlapping disease aetiologies associated with multiple altered biological processes have been identified that change the endometrial function leading to recurrent implantation failure (RIF) and recurrent early pregnancy loss (REPL). We aimed to provide a detailed insight into the nature of the biological malfunction and related pathways of differentially expressed genes in RIF and REPL. Endometrial biopsies were obtained from 9 women experiencing RIF, REPL and control groups. Affymetrix microarray analysis was performed to measure the gene expression level of the endometrial biopsies. Unsupervised clustering of endometrial samples shows scattered distribution of gene expression between the RIF, REPL and control groups. 2556 and 1174 genes (p value < 0.05, Fold change > 1.2) were significantly altered in the endometria of RIF and REPL patients’ group, respectively compared to the control group. Downregulation in Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways of the differentially expressed genes (DEGs) in RIF and REPL including ribosome and oxidative phosphorylation pathways. Gene Ontology (GO) analysis revealed ribosomes and mitochondria inner membrane as the most significantly downregulated cellular component (CC) affected in RIF and REPL. Determination of the dysregulated genes and related biological pathways in RIF and REPL will be key in understanding their molecular pathology and of major importance in addressing diagnosis, prognosis, and treatment issues
Keyphrases
- pulmonary tuberculosis
- gene expression
- genome wide
- genome wide identification
- bioinformatics analysis
- mycobacterium tuberculosis
- endometrial cancer
- dna methylation
- genome wide analysis
- single cell
- end stage renal disease
- machine learning
- cell proliferation
- newly diagnosed
- adipose tissue
- rna seq
- metabolic syndrome
- cell death
- pregnant women
- signaling pathway
- mass spectrometry
- patient reported
- molecularly imprinted