Association of TNF-α gene T-1031C polymorphism with endometriosis: A meta-analysis

Mining phase separation-related diagnostic biomarkers for endometriosis through WGCNA and multiple machine learning techniques: a retrospective and nomogram study

OBJECTIVE

The objective of this study was to investigate the role of phase separation-related genes in the development of endometriosis (EMs) and to identify potential characteristic genes associated with the condition.

METHODS

We used GEO database data, including 74 non-endometriosis and 74 varying-degree EMs patients. Our approach involved identifying significant gene modules, exploring gene intersections, identifying core genes, and screening for potential EMs biomarkers using weighted gene co-expression network analysis (WGCNA) and various machine learning approaches. We also performed gene set enrichment analysis (GSEA) to understand relevant pathways. This comprehensive approach helps investigate EMs genetics and potential biomarkers.

RESULTS

Nine genes were identified at the intersection, suggesting their involvement in EMs. GSEA linked DEGs to pathways like complement and coagulation cascades, DNA replication, chemokines, apical plasma membrane processes, and diseases such as Hepatitis B, Human T-cell leukemia virus 1 infection, and COVID-19. Five feature genes (FOS, CFD, CCNA1, CA4, CST1) were selected by machine learning for an effective EMs diagnostic nomogram. GSEA indicated their roles in mismatch repair, cell cycle regulation, complement and coagulation cascades, and IL-17 inflammation. Notable differences in immune cell proportions (CD4 T cells, CD8 T cells, DCs, macrophages) were observed between normal and disease groups, suggesting immune involvement.

CONCLUSIONS

This study suggests the potential involvement of phase separation-related genes in the pathogenesis of endometriosis (EMs) and identifies promising biomarkers for diagnosis. These findings have implications for further research and the development of new therapeutic strategies for EMs.

Endometriosis and COVID-19: A Systematic Review and Meta-Analysis

Endometriosis is defined as ectopic endometrial tissues dispersed outside the endometrium. This can cause disruption in hormonal and immunological processes, which may increase susceptibility to SARS-CoV-2 infection. Worsening of endometriosis symptoms may occur as a result of this infection. The aim of our review was to estimate the pooled prevalence of SARS-CoV-2 infection and the health impacts of the COVID-19 pandemic in endometriosis patients. We conducted a systematic review and meta-analysis. MEDLINE, Science Direct, Scopus, and Google Scholar databases were searched, using the keywords: (endometriosis) AND (COVID-19 OR SARS-CoV-2). Forest plots and pooled estimates were created using the Open Meta Analyst software. After screening 474 articles, 19 studies met the eligibility criteria for the systematic review, and 15 studies were included in the meta-analyses. A total of 17,799 patients were analyzed. The pooled prevalence of SARS-CoV-2 infection in endometriosis patients was 7.5%. Pooled estimates for the health impacts were 47.2% for decreased access to medical care, 49.3% increase in dysmenorrhea, 75% increase in anxiety, 59.4% increase in depression, and 68.9% increase in fatigue. Endometriosis patients were undeniably impacted by the COVID-19 pandemic, which caused the worsening of symptoms such as dysmenorrhea, pelvic pain, anxiety, depression, and fatigue.

Association of Interleukin-6-174G/C Polymorphism With Ischemic Stroke: An Updated Meta-Analysis

Background: Although numerous epidemiological studies have investigated the association between -174G/C(rs1800795) polymorphism in the interleukin-6 (IL-6) gene-stimulatory region and the risk of ischemic stroke (IS), they failed to reach a unified conclusion. The true relationship between -174G/C(rs1800795) polymorphism and IS remains controversial and unclear. Therefore, in this meta-analysis, we aimed to analyze more precisely the association between -174G/C(rs1800795) single-nucleotide polymorphism (SNP) of IL-6 gene and IS in a larger pooled population. Methods: A comprehensive literature search was performed in PubMed, Web of Science, and the Cochrane Central Register of Controlled Trials until June 30, 2021. A fixed or random-effects model was utilized based on heterogeneity between studies. The odds ratios (ORs) and 95% confidence intervals (Cis) were calculated in the models of allele comparison (G vs. C), homozygote comparison (GG vs. CC) and (GC vs. CC), dominant (GG vs. GC + CC), hyper dominant (GG + CC vs. GC), and recessive (GG + GC vs. CC) to determine the strength of associations. Results: This meta-analysis included 13 case-control studies in 35 articles with 5,548 individuals. Overall, no significant associations between IL-6 -174G/C(rs1800795) and IS were identified (G vs. C:OR [95% CI] = 0.99 [0.81, 1.21], P = 0.91; GG + CC vs. GC:0.97 [0.85, 1.11], P = 0.66; GG vs. GC + CC: 1.01 [0.81, 1.25], P = 0.94; GC vs. CC: OR [95% CI] = 1.01 [0.68, 1.5], P = 0.96; GG vs. CC:0.93 [0.57, 1.51], P = 0.76; GG + GC vs. CC:0.97 [0.64, 1.47], P = 0.89). In the subgroup analyses by ethnicity or HWE P-value, there was a statistically significant association between IL-6 -174G/C(rs1800795) polymorphisms and IS in the alleles model; (G vs. C: LogOR [95% CI] = 0.14 [-0.16,.45], P = 0.00), homozygote model (GG vs. CC: LogOR [95% CI] = 0.18 [-0.58,.95], P = 0.00) and (GC vs. CC: LogOR [95% CI] = 0.2 [-0.46,.85], P = 0.00), dominant model (GG vs. GC + CC: OR [95% CI] = 0.02 [-0.72, 0.77], P = 0.00), and recessive model (GG + GC vs. CC: OR [95% CI]= -0.17 [-0.86,.52], P = 0.00) of the European population and in the dominant model (GG vs. GC + CC: OR [95% CI] = -0.13 [-0.51, 0.24]) of the Asian population. No statistical significance was identified in both six models of HWE p ≥ 0.2 group (both P ≥ 0.05). Conclusion: This meta-analysis revealed no correlation between IL-6 -174G/C(rs1800795) polymorphism and IS, whereas the subgroup analysis indicated that the relationship between IL-6 -174G/C(rs1800795) polymorphism and IS susceptibility varied significantly according to ethnicity and geography.

SCM-198 Prevents Endometriosis by Reversing Low Autophagy of Endometrial Stromal Cell via Balancing ERα and PR Signals

BACKGROUND

Endometriosis (EMS), an endocrine-related inflammatory disease, is characterized by estrogen and progesterone imbalance in ectopic lesions. However, its pathogenic mechanism has not been fully elucidated. While SCM-198 is the synthetic form of leonurine and has multiple pharmacological activities such as antioxidation and anti-inflammation, it remains unknown whether it could inhibit the progress of EMS by regulating estrogen signaling and inflammation.

METHODS

The therapeutic effects of SCM-198 on EMS and its potential mechanism were analyzed by establishing EMS mouse models and performing an RNA sequencing (RNA-seq) assay. ELISA was performed to detect estrogen and tumor necrosis factor (TNF) -α concentrations in normal endometrial stromal cells (nESCs) and ectopic endometrial stromal cells (eESCs) with or without SCM-198 treatment. Western blotting, RNA silencing, and plasmid overexpression were used to analyze the relationship between inflammation, endocrine factors, and autophagy and the regulatory activity of SCM-198 on the inflammation-endocrine-autophagy axis.

RESULTS

Increased estrogen-estrogen receptor (ER) α signaling and decreased progesterone receptor isoform B (PRB) expression synergistically led to a hypo-autophagy state in eESCs, which further inhibited the apoptosis of eESCs. The high expression of TNF-α in eESCs enhanced the antiapoptotic effect mediated by low autophagy through the activation of the aromatase-estrogen-ERα signaling pathway. SCM-198 inhibited the growth of ectopic lesions in EMS mice and promoted the apoptosis of eESCs both in vivo and in vitro. The apoptotic effect of SCM-198 on eESCs was attained by upregulating the autophagy level via the inhibition of the TNF-α-activated aromatase-estrogen-ERα signal and the increase in PRB expression.

CONCLUSION

Inflammation facilitated the progress of EMS by disrupting the estrogen regulatory axis. SCM-198 inhibited EMS progression by regulating the inflammation-endocrine-autophagy axis.

New rat to mouse xenograft transplantation of endometrium as a model of human endometriosis

Background

Endometriosis can lead to infertility. Since there is no definitive treatment for endometriosis, animal modelling seems necessary to examine the possible treatments. Mouse endometrium cannot be separated for endometriosis induction. In addition, transplantation of uterus into the abdominal viscera to induce endometriosis causes organ damage. In this study, we defined a new model of endometriosis leading to separability of endometrium and a safe anatomical region for transplantation.

Methods

Forty female mice were allocated to 5 groups: 1, sham; 2, allograft uterus transplantation of mice to anterior abdominal wall of mice; 3, allograft uterus transplantation of mice to mesentery of mice; 4, xenograft endometrial transplantation of rat to anterior abdominal wall of mice; 5, xenograft endometrial transplantation of rat to mesentery of mice. Adult female rats with a previous pregnancy experience were selected and placed in the vicinity of male rats for 2 weeks to induce estrogen secretion and increase endometrial thickness.

Results

In the 4th group of animals, compared to sham, the peritoneal concentrations of VEGF-A, TNF-α, NO, MDA, and serum levels of CA-125 and IL-37 were increased and total body weight was decreased, while weight and size of endometrial lesions were increased significantly (P < .05). Genes expression of HOXA10 and HOXA11 were decreased significantly (P < .05) in groups 2 and 4 compared to sham.

Conclusions

Xenograft transplantation of endometrium from rat to anterior abdominal wall of mice can potentially mimic human endometriosis morphologically, histologically, and genetically.