Targeting chronic endometritis: study reveals potential diagnostic markers

In a recent study published in Frontiers in Medicine, researchers investigated the gene expression signatures and immune cell involvement in chronic endometritis (CE) for potential diagnostic markers and insights into its pathophysiology.

Study: Gene expression signatures associated with chronic endometritis revealed by RNA sequencing. Image Credit: Peakstock/Shutterstock.comStudy: Gene expression signatures associated with chronic endometritis revealed by RNA sequencing. Image Credit: Peakstock/Shutterstock.com

Background

CE is an inflammatory uterine endometrium condition commonly caused by intrauterine infections. Though asymptomatic, CE is linked to implantation failure and miscarriage, necessitating accurate diagnosis and treatment to improve pregnancy rates in fertility treatments.

CE is histologically characterized by plasma cell infiltration in the endometrial stroma. A reliable clinical test, clusters of differentiation 138 (CD138) immunohistochemistry staining, is used in addition to regular histological examination for diagnosis.

However, the diagnostic criteria for CD138-positive cells lack uniformity, leading to inconsistent results. The role of CD138 as a marker for infection-induced inflammation in the endometrium remains debated.

About the study

In the present study, 190 patients were enrolled, all deemed healthy between July 2020 and April 2021. Patients who had taken antibiotics within the previous three months were excluded from the study to ensure the data's accuracy. The diagnosis of CE was established using CD138 immunohistochemistry staining.

For the ribonucleic acid (RNA) sequencing analysis, the researchers randomly selected a subset of patients from the CE and non-CE groups. They ensured that at least 30 patients were in each group for better statistical analysis.

To obtain transcriptome data from the endometrial tissues, total RNA was extracted using a standardized protocol. The RNA sequencing libraries were prepared, and the samples were sequenced using the HiSeq X platform. The resulting sequence reads were then aligned to a Homosapien transcript fasta set, and gene expression levels were analyzed.

The researchers conducted statistical analyses to compare the clinical information between the CE and non-CE groups, providing valuable insights into the characteristics and differences of patients with CE.

Additionally, quantitative reverse-transcription polymerase chain reaction (PCR) was used to validate the expression of a specific gene, trans-Golgi network vesicle protein 23 (TVP23A), which may have potential implications in CE.

The researchers also performed immune cell analysis on the endometrial tissues. By utilizing the Cell-type Identification by Estimating Relative Subsets of RNA Transcripts (CIBERSORT) algorithm, they estimated the proportions of 22 different types of immune cells in both CE and non-CE endometrial tissues.

Study results

The results showed that, out of 123 patients, 67 were excluded due to recent antibiotic or hormone therapy, leaving 57 patients. CE was diagnosed using CD138 immunohistochemical staining, with 24 patients classified as CE (CD138 count ≥5) and 33 as non-CE (CD138 count <5).

RNA sequencing analysis performed on endometrial tissues from 33 CE and 24 non-CE patients resulted in 20 million read pairs. Differential gene expression analysis identified 20 upregulated genes in the CE group, predominantly related to immunoglobulins, and one consistently elevated gene, TVP23A, in CE samples.

The researchers analyzed samples collected during the proliferative and secretory phases. Thirteen genes were upregulated in the CE group during the proliferative phase, including immunoglobulin genes, coiled-coil domain containing 13 (CCDC13), and marginal zone B1 (MZB1).

In the secretory phase, eight genes were upregulated in the CE group and non-immunoglobulin genes.

The CIBERSORTx analysis showed that plasma cells were more abundant in CE samples, while clusters of differentiation 4 (CD4) memory T cells (resting) were less abundant in CE samples compared to non-CE models.

Discussion

The study identified genes upregulated in CE endometria compared to non-CE endometria, including 12 non-immunoglobulin genes and 13 immunoglobulin genes. Interestingly, the proportion of immunoglobulin-related genes among differentially expressed genes (DEGs) varied between the proliferative and secretory phases, suggesting potential phase-specific gene expression signatures associated with CE.

The findings also reported the identification of the TVP23A gene as a novel CE-specific marker. Unlike other genes identified, TVP23A was consistently upregulated in most CE cases, irrespective of the number of CD138-positive cells. This gene's potential role in CE pathophysiology and its specificity makes it a promising candidate for diagnostic markers.

Moreover, the analysis of immune cell populations in CE endometria revealed an increased abundance of plasma cells and a decreased abundance of CD4 memory T cells compared to non-CE endometria.

The altered immune cell populations may be attributed to chronic inflammation in CE tissues, leading to compromised memory T-cell responses.

Conclusions

To summarize, the study identified 12 non-immunoglobulin genes and 13 immunoglobulin genes with elevated expression in CE, mainly attributed to the presence of plasma cells.

However, the TVP23A gene showed consistent upregulation in most CE cases, making it a potential novel diagnostic marker for CE. RNA sequencing provided valuable insights into CE's molecular physiology and its potential role in reproductive failure.

Journal reference:
Vijay Kumar Malesu

Written by

Vijay Kumar Malesu

Vijay holds a Ph.D. in Biotechnology and possesses a deep passion for microbiology. His academic journey has allowed him to delve deeper into understanding the intricate world of microorganisms. Through his research and studies, he has gained expertise in various aspects of microbiology, which includes microbial genetics, microbial physiology, and microbial ecology. Vijay has six years of scientific research experience at renowned research institutes such as the Indian Council for Agricultural Research and KIIT University. He has worked on diverse projects in microbiology, biopolymers, and drug delivery. His contributions to these areas have provided him with a comprehensive understanding of the subject matter and the ability to tackle complex research challenges.    

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