P-307 Mapping the uterine pathologies in endometrium: differential genetic interactions set the algorithm for improved diagnosis in women with adenomyosis
Authors: Chakraborty P , Mitra I , Dattachaudhuri R , Sharma S , Kalapahar S , Ghosh S , Chattopadhyay R , Sarkar S , Chaudhury K , Chakravarty B 
Published: June 2022

Abstract

Study question
Do genetic components and functional annotation/s in eutopic endometrium share significant difference to influence diagnosis in adenomyosis?

Summary answer
An integrated clinico-transcriptomic approach chalk the chief individual as well as hub genes in women with adenomyosis to set the algorithm for improved diagnosis.

What is known already
Adenomyosis often document similar presentation/s to other gynecological diseases including endometriosis making the diagnosis difficult. Differentially expressed transcripts and proteins were identified by transcriptomic analysis and genome-wide profiling of eutopic and ectopic endometrial samples in women with endometriosis. Biological networking and functional enrichment analysis enable prioritization of candidate genes for validation purpose in target tissue. Recently, key pathways in proliferative stage of adenomyosis at transcriptome level were documented in eutopic endometrium. However, characterization of functional annotations may assist clinicians to evaluate if they share systematic correlations predictive of ultrasonographic finding/s for help in everyday practice in diagnosing adenomyosis .

Study design, size, duration
Microarray datasets (GSE7307 and GSE78851) were selected from Gene Expression Omnibus database (GEO), which contains endometriosis, adenomyosis and normal endometrial tissues. An in-depth bioinformatic analysis was done to determine differentially expressed genes (DEGs) on GEO2R platform; followed by gene ontology (GO), KEGG pathway enrichment and protein-protein interaction (PPI) analysis by DAVID (http://david.ncifcrf.gov) and Cytoscape (version 3.8.2) respectively. PPI network was predicted further using a search tool, STRING (http://string-db.org; version 11.0) for retrieval of interacting genes.

Participants/materials, setting, methods
Eutopic endometrial samples were obtained during window of implantation from women (n = 10) with endometriosis, adenomyosis and adenomyosis-associated-endometriosis as diagnosed by laparoscopy, and, trans-vaginal ultrasound (TVUS) between March to December 2021 from Institute of Reproductive Medicine, Kolkata. Counterpart/s of male sub-fertility, defined by World-Health-Organization criteria (5th edition) was treated as control (n = 10). In-silico findings were validated by quantitative-real-time PCR (qRT-PCR). TVUS findings and gene expression/s were correlated by Spermann-rank correlation test. P &lt; 0.05 was considered statistically significant.

Main results and the role of chance
A total of 4474 and 1061, significant DEGs (log fold-change&gt;1, p &lt; 0.05) were identified from datasets of endometriosis and adenomyosis respectively. GO function/s included common biological processes and molecular function/s, namely, epithelial-to-mesenchymal transition (EMT), metallopeptidase activity and extracellular matrix remodelling. EMT and Wnt signaling ranked top position/s in KEGG pathway enrichment. Among sixty-four common DEGs, four genes, namely, SERPINA1, MMP11, THBS1, MMP7 have maximal node degree (&gt;2) and MCODE (k = 2) in PPI network and were prioritized as hub genes. STRING analysis computed the network of common hub genes between adenomyosis and endometriosis. qRT-PCR findings confirmed down-regulation (p &lt; 0.02) of SERPINA1, and MMP11 in adenomyosis compared to endometriosis and MMP7, and THBS1 in both endometriosis and adenomyosis (p &lt; 0.03) compared to control. Down-regulation (p &lt; 0.003) of SNORD116, MYH11 and PIGR was simultaneously observed in adenomyosis only as compared to endometriosis. Similar gene expression/s as to adenomyosis was documented in combined cohort because of possible presence of common pathology. Interestingly, posterior-wall thickness (PWT) on TVUS was positively correlated with MMP11 (r = 0.88; p&lt;0.03) and SERPINA1 (r = 0.94; p&lt;0.01) in adenomyosis. MMP-11 also exhibited positive correlation with PWT (r = 0.85; p&lt;0.03) and uterine-size (r = 0.88; p&lt;0.03) in endometriosis and combined cohort respectively while MYH11 negatively correlated (r=-0.97; p&lt;0.02) with uterine-size in adenomyosis associated endometriosis.

Limitations, reasons for caution
The heterogeneous nature of data for bioinformatic analysis is a major limitation. Moreover, only mild adenomyosis was considered in the study; hence, results could differ in women with co-occurrence of other gynecological condition/s and/or in severe cases of adenomyosis. The observed differences need to be replicated in larger study cohort/s.

Wider implications of the findings
We identify a set of novel hub genes and enrichment pathways in receptive phase which provide an in-depth discriminative understanding between pathogenesis of endometriosis and adenomyosis. Our results suggest a dys-regulated micro-environment run an algorithmic cascade for perturbed uterine preparation (in adenomyosis), thus providing platform for newer therapeutic targets.

Trial registration number
Not Applicable