Epigenetic role of the nuclear factor NF-Y on ID gene family in endometrial tissues of women with endometriosis: a case control study

Enhancing Genetic Association Power in Endometriosis through Unsupervised Clustering of Clinical Subtypes Identified from Electronic Health Records

Background

Endometriosis affects 10% of reproductive-age women, and yet, it goes undiagnosed for 3.6 years on average after symptoms onset. Despite large GWAS meta-analyses (N > 750,000), only a few dozen causal loci have been identified. We hypothesized that the challenges in identifying causal genes for endometriosis stem from heterogeneity across clinical and biological factors underlying endometriosis diagnosis.

Methods

We extracted known endometriosis risk factors, symptoms, and concomitant conditions from the Penn Medicine Biobank (PMBB) and performed unsupervised spectral clustering on 4,078 women with endometriosis. The 5 clusters were characterized by utilizing additional electronic health record (EHR) variables, such as endometriosis-related comorbidities and confirmed surgical phenotypes. From four EHR-linked genetic datasets, PMBB, eMERGE, AOU, and UKBB, we extracted lead variants and tag variants 39 known endometriosis loci for association testing. We meta-analyzed ancestry-stratified case/control tests for each locus and cluster in addition to a positive control (Total N endometriosis cases = 10,108).

Results

We have designated the five subtype clusters as pain comorbidities, uterine disorders, pregnancy complications, cardiometabolic comorbidities, and EHR-asymptomatic based on enriched features from each group. One locus, RNLS , surpassed the genome-wide significant threshold in the positive control. Thirteen more loci reached a Bonferroni threshold of 1.3 x 10 -3 (0.05 / 39) in the positive control. The cluster-stratified tests yielded more significant associations than the positive control for anywhere from 5 to 15 loci depending on the cluster. Bonferroni significant loci were identified for four out of five clusters, including WNT4 and GREB1 for the uterine disorders cluster, RNLS for the cardiometabolic cluster, FSHB for the pregnancy complications cluster, and SYNE1 and CDKN2B-AS1 for the EHR-asymptomatic cluster. This study enhances our understanding of the clinical presentation patterns of endometriosis subtypes, showcasing the innovative approach employed to investigate this complex disease.

What Do the Transcriptome and Proteome of Menstrual Blood-Derived Mesenchymal Stem Cells Tell Us about Endometriosis?

Given the importance of menstrual blood in the pathogenesis of endometriosis and the multifunctional roles of menstrual mesenchymal stem cells (MenSCs) in regenerative medicine, this issue has gained prominence in the scientific community. Moreover, recent reviews highlight how robust the integrated assessment of omics data are for endometriosis. To our knowledge, no study has applied the multi-omics approaches to endometriosis MenSCs. This is a case-control study at a university-affiliated hospital. MenSCs transcriptome and proteome data were obtained by RNA-seq and UHPLC-MS/MS detection. Among the differentially expressed proteins and genes, we emphasize ATF3, ID1, ID3, FOSB, SNAI1, NR4A1, EGR1, LAMC3, and ZFP36 genes and MT2A, TYMP, COL1A1, COL6A2, and NID2 proteins that were already reported in the endometriosis. Our functional enrichment analysis reveals integrated modulating signaling pathways such as epithelial–mesenchymal transition (↑) and PI3K signaling via AKT to mTORC1 (↓ in proteome), mTORC1 signaling, TGF beta signaling, TNFA signaling via NFkB, IL6 STAT3 signaling, and response to hypoxia via HIF1A targets (↑ in transcriptome). Our findings highlight primary changes in the endometriosis MenSCs, suggesting that the chronic inflammatory endometrial microenvironment can modulate these cells, providing opportunities for endometriosis etiopathogenesis. Moreover, they identify challenges for future research leveraging knowledge for regenerative and precision medicine in endometriosis.

Exploring diagnostic m6A regulators in endometriosis

Endometriosis is an estrogen-dependent inflammatory disorder, usually causing infertility, pelvic pain, and ovarian masses. This study intended to investigate the implication of N6-methyladenosine (m6A) regulators in endometriosis. We acquired 34 normal, 127 eutopic, and 46 ectopic, samples of endometrium from the Gene Expression Omnibus (GSE7305, GSE7307, GSE51981) database and the Array-express (E-MTAB-694) database. These samples were then used to profile the expression of 20 m6A regulators in endometriosis. The results indicated that most dysregulated (19/20) m6A regulators were significantly downregulated in eutopic vs. normal endometrium and also significantly downregulated in ectopic vs. eutopic endometrium. Several dysregulated m6A regulators were common to both contrast matrices: METTL3, YTHDF2, YTHDF3, HNRNPA2B1, HNRNPC, and FTO. Both HNRNPA2B1 and HNRNPC were associated with the severity of endometriosis in eutopic samples, and also exhibited diagnostic potential for endometriosis. HNRNPA2B1 and HNRNPC may influence immune pathways and the infiltration of immune cells in endometriosis. Abnormalities in the gene transcription factors network associated with endometriosis might affect the expression of HNRNPA2B1 and HNRNPC. In conclusion, we observed significant dysregulation of m6A regulators in endometriosis, and found that HNRNPA2B1 and HNRNPC might correlate with the immune response and serve as useful diagnostic biomarkers for endometriosis.

Systematic review of genome-wide association studies on susceptibility to endometriosis

Endometriosis is a complex and heterogeneous disease in which extrinsic and intrinsic factors, such as genetics, provide to the disease development. Genome-wide association (GWA) studies may be essential to recognize genetic variants associated with the endometriosis risk. However, in the current literature there are some conflicting results between these studies. The aim of the present study was to undertake a systematic review about endometriosis GWA studies, to describe the disease-associated genes and single nucleotide polymorphisms (SNPs) to try to understand the endometriosis etiopathogenesis, besides to discuss possible bias of conflicting results among these studies. This study is a systematic review of GWA studies in endometriosis published until December 31^th, 2019 by PubMed database, considering the following descriptors: endometriosis and ("polymorphism" or "SNP" or "genetic polymorphism" or "variants" or "locus") and ("GWA" or "Genome-wide" or "Genome wide" or "Genetic association study"). The included studies were analyzed with methodological rigor (STROBE and PRISMA) to enable better quality of case-control and meta-analysis studies, respectively. Of the 88 articles found, only 15 were eligible. All articles had appropriate quality evaluated by STROBE and PRISMA checklists (77% and 81%, respectively). Overall, 35,022 endometriosis cases and 181,760 controls were analyzed. The number of participants in each study was quite different (171 to 17,045 for the cases and 308 to 150,021 for the controls), with a predominance of European ethnicity. Most endometriosis cases (86%) were diagnosed by surgery, while selection of the control group was different among studies. About 47% performed only one stage (discovery stage) and 53% performed both the discovery and replication analyses. Eleven genes/SNPs were associated with endometriosis risk in more than one article (chromosome 1, 2, 6, 7, 9 and 12; WNT4, GREB1, FN1, IL1A, ETAA1, RND3, ID4, NFE2L3, CDKN2B-AS1 and VEZT). SNPs were localized in intergenic and intronic regions, their risk allele frequencies varied among the studies and their results were conflicting. In summary, WNT4 rs7521902, GREB1 rs13394619, FN1 rs1250248, IL1A rs6542095 and VEZT rs10859871 variants are highlighted due to high frequency and pathways and function that each gene influences in the development of endometriosis. However, the replication and validation of these variants in different populations are necessary for a better understanding of the endometriosis etiopathogenesis, in order to optimize the diagnosis and improve the efficiency of clinical treatment of the disease.