Abstract

   Latent Endometrial Tuberculosis (LETB) is a significant yet
   under-recognized cause of female infertility, particularly in
   TB-prevalent regions. Current diagnostic methods for LETB lack
   specificity, complicating early detection. Through RNA-Seq
   transcriptome profiling, we aimed to uncover distinct immune response
   landscapes and identify novel inflammation-related diagnostic markers
   for LETB. Our study included clinical diagnostics, histological
   examinations, and transcriptomic analyses comparing differentially
   expressed genes (DEGs) among control, LETB, and active TB groups. We
   identified seven candidate genes (IFI30, HCK, SPI1, IL1B, ITGB2, and
   FCGR2A) uniquely associated with LETB. Bioinformatic analyses revealed
   these genes’ significant roles in immune regulation, including
   leukocyte activation, cytokine signaling, and myeloid
   leukocyte-mediated immunity. Gene Set Enrichment Analysis (GSEA)
   confirmed their involvement in key immune pathways such as
   cytokine-cytokine receptor interaction and leukocyte transendothelial
   migration. Validation through qPCR and immunohistochemistry confirmed
   the differential expression of these biomarkers in LETB tissues. These
   findings provide new insights into LETB pathogenesis, suggesting
   potential biomarkers for enhanced early diagnosis and treatment,
   ultimately aiming to improve reproductive health outcomes for affected
   women.

   Keywords: Latent endometrial tuberculosis, Inflammatory biomarkers,
   RNA-Seq, Immune Response, Diagnosis, Female infertility, Transcriptomic
   analysis

   Subject terms: Computational biology and bioinformatics, Biomarkers,
   Medical research, Reproductive disorders

Introduction

   Latent tuberculosis (TB) remains a pressing global health concern, with
   approximately 1.7 billion individuals worldwide harboring latent
   infection and at risk of progressing to active TB^[32]1. Among these,
   latent genital tuberculosis (LGTB) poses a significant threat to female
   reproductive health, frequently resulting in infertility. Studies
   estimate that LGTB accounts for 5–10% of infertility cases in regions
   with high TB prevalence^[33]2. A critical manifestation of LGTB is
   latent endometrial tuberculosis (LETB), which significantly compromises
   reproductive health by inflicting structural and functional damage to
   the endometrial tissue, a key component for successful implantation and
   pregnancy^[34]3. The tuberculosis bacilli impair the endometrial
   environment, undermining its ability to support normal reproductive
   processes. This underscores the necessity for early detection and
   intervention to mitigate the impact of LETB on fertility^[35]4.

   The early diagnosis of LETB is crucial for the success of assisted
   reproductive technologies (ART) and the prevention of adverse outcomes,
   such as pregnancy loss. At reproductive medicine centers, couples with
   a history of TB-related infertility often turn to ART to achieve
   conception. However, before initiating treatment, it is critical to
   ascertain whether Mycobacterium tuberculosis has invaded the
   reproductive system, particularly the endometrium. LETB can persist in
   the body asymptomatically, posing a diagnostic challenge due to its
   latent nature. If undetected, LETB may transition to active TB during
   ART procedures, such as embryo transfer, leading to severe
   complications, including pregnancy loss. Early and accurate diagnosis
   is therefore essential not only to prevent such complications but also
   to ensure optimal reproductive outcomes in affected women.

   Despite its clinical significance, diagnosing LETB remains challenging
   due to the lack of specific and sensitive diagnostic tools.
   Conventional methods, including microbiological cultures and
   histopathological examinations, often fail to reliably detect latent
   infections due to their limited sensitivity and specificity^[36]5.
   These diagnostic shortcomings highlight an urgent need for novel
   approaches capable of identifying LETB at an early stage. Recent
   advances in molecular techniques, such as RNA sequencing (RNA-Seq),
   offer promising opportunities to uncover distinct molecular and
   immunological markers associated with LETB. These approaches hold the
   potential to revolutionize LETB diagnostics by providing a more
   sensitive and comprehensive understanding of its underlying
   biology^[37]6.

   The immune system plays a pivotal role in the pathogenesis of TB,
   including its latent forms such as LETB. Host immune responses to
   Mycobacterium tuberculosis are central to the disease’s progression,
   with inflammation serving as a hallmark feature of TB infection.
   Cytokine profiles, such as elevated levels of IFN-γ and TNF-α, have
   been shown to correlate with latent TB infections, reflecting the
   immune system’s attempts to control bacterial persistence^[38]7.
   Investigating the immune landscape of LETB may provide critical
   insights into its pathogenesis and identify inflammation-related
   markers that are essential for diagnosis^[39]8. The interaction between
   TB bacilli and the host immune system often generates unique
   immunological signatures, which can be exploited to develop specific
   diagnostic tools^[40]9.

   This study leverages RNA-Seq transcriptome profiling to identify
   distinct immune response landscapes and inflammation-related diagnostic
   markers in LETB. By analyzing gene expression patterns in endometrial
   tissues affected by latent TB, this research aims to uncover specific
   biomarkers that can enable early and precise diagnosis. The study
   adopts a systematic approach, including careful sample selection, RNA
   sequencing, and bioinformatics analysis, to identify potential
   diagnostic targets. Ultimately, the goal is to improve diagnostic
   accuracy for LETB, thereby facilitating earlier detection and more
   effective treatment strategies. Findings from this study will
   contribute significantly to understanding LETB pathogenesis and may
   pave the way for novel therapeutic interventions, enhancing
   reproductive health outcomes in affected women.

Materials and methods

Ethics statement

   This study was approved by the ethical committee of the Affiliated
   Hospital of Inner Mongolia Medical University. Written informed consent
   was obtained from all study participants. All experimental procedures
   described in this study were carried out in accordance with the
   protocols approved by the ethical committee of the Affiliated Hospital
   of Inner Mongolia Medical University. All experimental designs, data
   collection, and analysis processes were performed in accordance with
   the standards of science and ethics.

Research sample

Retrospective analysis sample

   Medical records of 425 infertile patients who underwent the first cycle
   of IVF fresh embryo transfer at the Reproductive Medicine Center of
   Inner Mongolia Medical University Affiliated Hospital from April 2017
   to April 2019 were collected. Inclusion criteria were as follows: (1)
   age between 22 and 40 years old; (2) no clinical manifestations of
   active tuberculosis; (3) exclusion of active tuberculosis by imaging
   and endometrial histopathology biopsy examination; (4) transfer of
   high-quality embryos of grade I-II. Exclusion criteria were: (1)
   patients with endometrial lesions such as endometrial polyps, complex
   endometrial hyperplasia, atypical endometrial hyperplasia, endometrial
   cancer, etc.; (2) pelvic endometriosis, uterine adenomyosis; (3)
   ovarian insufficiency, AMH < 1.1ng/ml; number of eggs obtained from
   bilateral ovaries ≤ 3; (4) patients solely undergoing assisted
   reproduction due to male factors. Specific grouping is shown in
   Table [41]1.

Table 1.

   Retrospective analysis sample grouping.
   CG (TB-IGRA-, n = 278) LETB (TB-IGRA+, n = 147)
   NIG IG                 NIG IG
   161 117                84  63
   [42]Open in a new tab

   Note: Control Group (CG); Latent Endometrial Tuberculosis group (LETB);
   Inflammatory group (IG, CD38-& CD138-); Non-Inflammatory (NIG, CD38+&
   CD138+) group; The current diagnostic criteria consider a positive
   Tuberculosis Interferon-Gamma Release Assay (TB-IGRA), indicative of
   LETB suspicion, and positivity for both CD38 and CD138, suggesting
   inflammation.

Transcriptome analysis sample

   From April 2017 to April 2019, women aged 20 to 40 who underwent IVF
   treatment at the Reproductive Medicine Center of Inner Mongolia Medical
   University Affiliated Hospital due to tubal factors were selected.
   Prior to entering the IVF cycle, routine TB-IGRA testing was conducted.
   After obtaining informed consent for endometrial biopsy to exclude
   endometrial inflammatory lesions, endometrial biopsies were taken in
   the mid-luteal phase for pathological testing including CD38 and CD138.
   Additionally, a small amount of endometrial tissue was preserved in EP
   tubes and frozen at −80 °C. Specific grouping is shown in Table [43]2.

Table 2.

   Transcriptome analysis sample grouping.
   CG (TB-IGRA-, n = 6)  LETB (TB-IGRA+, n = 6)  TB (TB-IGRA+, n = 3)
   NIG IG                NIG IG
   3           3          3           3                   3
   [44]Open in a new tab

   Note: Control Group (CG); Latent Endometrial Tuberculosis group (LETB);
   Inflammatory group (IG); Non-Inflammatory (NIG) group; Tuberculosis
   group (TB); The current diagnostic criteria consider a positive
   Tuberculosis Interferon-Gamma Release Assay (TB-IGRA), indicative of
   LETB suspicion, and positivity for both CD38 and CD138, suggesting
   inflammation.

Validation analysis sample

   From April 2017 to April 2019, women aged 20 to 40 who underwent IVF
   treatment at the Reproductive Medicine Center of Inner Mongolia Medical
   University Affiliated Hospital due to tubal factors were selected.
   Prior to entering the IVF cycle, routine TB-IGRA testing was conducted.
   After obtaining informed consent for endometrial biopsy to exclude
   endometrial inflammatory lesions, endometrial biopsies were taken in
   the mid-luteal phase for pathological testing including CD38 and CD138.
   Additionally, a small amount of endometrial tissue was preserved in EP
   tubes and frozen at −80 °C. Specific grouping is shown in Table [45]3.

Table 3.

   Validation analysis sample grouping.
   CG (TB-IGRA-, n = 4)  LETB (TB-IGRA+, n = 4)  TB (TB-IGRA+, n = 4)
   NIG IG                NIG IG
   2           2          2           2                   2
   [46]Open in a new tab

   Note: Control Group (CG); Latent Endometrial Tuberculosis group (LETB);
   Inflammatory group (IG); Non-Inflammatory (NIG) group; Tuberculosis
   group (TB); The current diagnostic criteria consider a positive
   Tuberculosis Interferon-Gamma Release Assay (TB-IGRA), indicative of
   LETB suspicion, and positivity for both CD38 and CD138, suggesting
   inflammation.

ELISA for tuberculosis diagnosis

   In this study, we employed the TB-IGRA kit for adjunctive tuberculosis
   diagnosis using an ex vivo ELISA method. After collecting 4 mL of
   heparinized whole blood from each participant, aliquots were
   distributed into negative control, positive control, and patient
   culture mediums. Incubation at 37 °C for 22 ± 2 h followed, with
   subsequent plasma extraction by centrifugation at 4000 rpm for 10 min.
   Plasma samples were then analyzed for IFN-γ levels per the kit’s
   instructions, adhering strictly to specified storage and operational
   conditions. This rigorous approach yielded critical data for
   tuberculosis diagnosis.

HE staining and immunohistochemistry

   Tissue specimens were fixed in 10% neutral buffered formalin, routinely
   dehydrated, cleared, embedded in paraffin, and sectioned at a thickness
   of 3 μm. Hematoxylin and eosin (HE) staining was performed for
   histopathological evaluation. Immunohistochemistry was conducted using
   the EnVision two-step method. Primary antibodies against CD38, CD138,
   SPL1, and IL1B were purchased from Abcam.

Doppler ultrasound examination

   The Mindray color Doppler ultrasound diagnostic instruments are
   utilized, with probe frequencies ranging from 3.5 to 9.0 MHz. Through
   abdominal or vaginal examination, the uterus and bilateral adnexa are
   explored. Following the routine examination procedure,
   multi-directional, multi-sectional, and multi-angular scanning is
   performed. The location and size of lesions are recorded, and
   evaluation includes internal and posterior echogenicity, morphology,
   boundaries, and relationships with surrounding structures. Lesions are
   subjected to color Doppler detection, and images are stored.

RNA extraction

   Total RNA was extracted from the tissue using TRIzol^® Reagent
   following the manufacturer’s instructions. Subsequently, RNA quality
   was assessed using the 5300 Bioanalyzer (Agilent) and quantified using
   the ND-2000 (NanoDrop Technologies). Only high-quality RNA samples
   (OD260/280 = 1.8 ~ 2.2, OD260/230 ≥ 2.0, RIN ≥ 6.5, 28 S:18 S ≥ 1.0,
   > 1 µg) were utilized for constructing the sequencing library.

Library preparation and sequencing

   RNA purification, reverse transcription, library construction, and
   sequencing were conducted at Shanghai Majorbio Bio-pharm Biotechnology
   Co., Ltd. (Shanghai, China) following the manufacturer’s instructions
   (Illumina, San Diego, CA). The uterine endometrial tissue RNA-seq
   transcriptome library was prepared using Illumina^®Stranded mRNA Prep,
   Ligation from Illumina (San Diego, CA) with 1µg of total RNA.
   Initially, messenger RNA was isolated via the polyA selection method
   using oligo(dT) beads and subsequently fragmented using a fragmentation
   buffer. Next, double-stranded cDNA was synthesized employing the
   SuperScript double-stranded cDNA synthesis kit (Invitrogen, CA) with
   random hexamer primers (Illumina). The synthesized cDNA underwent
   end-repair, phosphorylation, and ‘A’ base addition according to
   Illumina’s library construction protocol. Libraries were size-selected
   for cDNA target fragments of 300 bp on 2% Low Range Ultra Agarose,
   followed by PCR amplification using Phusion DNA polymerase (NEB) for 15
   PCR cycles. After quantification using Qubit 4.0, the paired-end
   RNA-seq sequencing library was sequenced using the NovaSeq 6000
   sequencer (2 × 150 bp read length). The raw paired end reads were
   trimmed and quality controlled by fastp^[47]10with default parameters.
   Then clean reads were separately aligned to reference genome with
   orientation mode using HISAT^[48]11software. The mapped reads of each
   sample were assembled by StringTie^[49]12 in a reference-based approach
   (Table [50]4).

Table 4.

   The mRNA sequencing data statistics.
   Sample Raw reads Raw bases Clean reads Clean bases Error rate (%) Q20
   (%) Q30
   (%) GC
   (%)
   CG NIG 47,350,426 7,149,914,326 46,067,584 6,758,894,916 0.0268 97.20
   92.57 51.94
   54,298,556 8,199,081,956 52,713,700 7,623,789,224 0.0264 97.37 92.95
   51.93
   56,356,580 8,509,843,580 54,883,286 7,950,335,261 0.0266 97.28 92.75
   52.33
   IG 43,141,658 6,514,390,358 41,434,754 6,078,093,406 0.0267 97.24 92.74
   51.37
   53,446,106 8,070,362,006 51,813,696 7,511,173,014 0.0263 97.40 93.03
   52.27
   53,016,154 8,005,439,254 51,276,054 7,392,516,867 0.0264 97.37 92.97
   52.10
   LETB NIG 48,829,076 7,373,190,476 47,420,486 6,915,852,500 0.0263 97.42
   93.05 52.33
   51,965,434 7,846,780,534 49,786,886 7,289,164,008 0.0272 97.01 92.22
   50.79
   46,722,478 7,055,094,178 45,312,204 6,627,150,568 0.0262 97.48 93.15
   52.94
   IG 48,005,458 7,248,824,158 46,989,584 6,893,496,419 0.0269 97.19 92.49
   51.79
   55,793,572 8,424,829,372 53,772,540 7,800,850,282 0.0266 97.27 92.73
   52.11
   49,896,196 7,534,325,596 48,599,792 7,113,620,448 0.0266 97.28 92.73
   51.74
   TB 50,342,790 7,601,761,290 48,473,942 7,093,253,613 0.0265 97.31 92.80
   50.46
   46,850,508 7,074,426,708 45,472,326 6,663,625,083 0.0272 97.07 92.27
   51.94
   55,172,404 8,331,033,004 53,863,158 7,920,817,759 0.0265 97.34 92.85
   51.88
   [51]Open in a new tab

   Note: Control Group (CG); Latent Endometrial Tuberculosis group (LETB);
   Inflammatory group (IG); Non-Inflammatory (NIG) group; Tuberculosis
   group (TB); The current diagnostic criteria consider a positive
   Tuberculosis Interferon-Gamma Release Assay (TB-IGRA), indicative of
   LETB suspicion, and positivity for both CD38 and CD138, suggesting
   inflammation.

Differential expression analysis and functional enrichment

   To identify differentially expressed genes (DEGs) between two distinct
   samples, transcript expression levels were quantified using the
   transcripts per million reads (TPM) method. Gene abundances were
   quantified using RSEM^[52]13Differential expression analysis was
   conducted using either DESeq2 or DEGseq. DEGs meeting the criteria of
   |log2FC| ≥ 1 and FDR ≤ 0.05 (DESeq2)^[53]14or FDR ≤ 0.001
   (DEGseq)^[54]15were considered significantly differentially expressed.
   Additionally, functional enrichment analysis, encompassing Gene
   Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG)
   pathways, was performed to identify DEGs significantly enriched in GO
   terms and metabolic pathways, with a Bonferroni-corrected
   P-value ≤ 0.05 compared to the whole-transcriptome background. GO
   functional enrichment and KEGG pathway analysis were conducted using
   Goatools and KOBAS^[55]16–[56]19, respectively.

Set enrichment analysis (GSEA)

   In this study, we conducted single-gene gene set enrichment analysis
   (GSEA) utilizing R programming language and its packages, specifically
   ‘limma’ for differential gene expression analysis, ‘ggplot2’ and
   ‘pheatmap’ for data visualization, ‘clusterProfiler’ and ‘enrichplot’
   for enrichment analysis against databases such as KEGG, ‘org.Hs.eg.db’
   for gene identifier conversion, and ‘patchwork’ along with ‘gseaplot2’
   for the visualization of the enrichment results. This approach allowed
   us to delve into the enrichment of the gene sets associated with the
   gene of interest within immune-related biological pathways.

Quantitative real-time PCR (qPCR) analysis

   In this study, we employed quantitative real-time polymerase chain
   reaction (qPCR) technology to perform relative quantification analysis
   of gene expression in tissue samples. The experimental workflow
   included RNA extraction (using the OmniPlant RNA Kit from Beijing
   Kangwei Century Biotechnology Co., Ltd.), reverse transcription (with
   the HiScript Q RT SuperMix for qPCR from Nanjing Novozymes
   Biotechnology Co., Ltd.), and relative quantification of target genes
   versus reference genes (β-actin and GAPDH) using the ChamQ SYBR Color
   qPCR Master Mix (also from Nanjing Novozymes Biotechnology Co., Ltd.).
   Amplification and data acquisition were conducted using the
   LineGene9600plus real-time quantitative PCR instrument (Hangzhou Bioer
   Technology Co., Ltd.). Primers were synthesized with PAGE purification
   by Shenggong Bioengineering Co., Ltd., ensuring specificity and
   efficiency (Table [57]5).

Table 5.

   List of qPCR primers required for gene validation.
   Primer     Base Sequence (5’ to 3’)
   ssIFI30-F  TGTGACCCTCTACTATGAAGCA
   ssIFI31-R  GGCACTTGAACTCCCACC
   ssHCK-F    GGAGGCAATACATTCTCAAA
   ssHCK-R    ATACAGGGCAACCACGAT
   ssSP1-F    CACTGGAGGTGTCTGACGG
   ssSP1-R    TGCTTGGACGAGAACTGGAA
   ssIL1B-F   CTCGCCAGTGAAATGAT
   ssIL1B-R   AAGCCCTTGCTGTAGTG
   ssITGB2-F  CCCTCACCCTGTGGCAAGT
   ssITGB2-R  TGCTCCAGCGTGTAGGC
   ssFCGR2A-F CTCCATCCCACAAGCAA
   ssFCGR2A-R CAGTCGCAATGACCACA
   [58]Open in a new tab

Statistical analysis

   Statistical significance was determined by one-way ANOVA using SPSS
   software (SPSS 21.0 for Windows). All productionrelated data are
   reported as the mean ± SE, and differences were considered significant
   at p < 0.05.

Results

Absence of reliable diagnostic markers for latent endometrial tuberculosis
(LETB)

   The endometrium often accompanies inflammation during the immune
   response against latent tuberculosis. Our study aimed to explore
   reliable inflammatory biomarkers for LETB diagnosis. Initially, we
   investigated pregnancy outcomes by comparing the Control Group (CG) and
   LETB, using the following criteria for grouping. Current diagnostic
   standards utilized positive Tuberculosis Interferon-Gamma Release Assay
   (TB-IGRA) results as indicative of LETB, along with positivity for CD38
   and CD138, suggesting inflammation. The results revealed no significant
   differences in pregnancy outcomes between the Inflammatory (IG) and
   Non-Inflammatory (NIG) groups (P > 0.05), indicating the lack of
   specific diagnostic markers for LETB (Fig. [59]1A).

Fig. 1.

   [60]Fig. 1
   [61]Open in a new tab

   Lack of Reliable Diagnostic Markers for Latent Endometrial Tuberculosis
   (LETB). (A) Comparison of Pregnancy Outcomes between Control Group (CG)
   and LETB. The current diagnostic criteria consider a positive
   Tuberculosis Interferon-Gamma Release Assay (TB-IGRA), indicative of
   LETB suspicion, and positivity for both CD38 and CD138, suggesting
   inflammation. The study reveals no significant differences in pregnancy
   outcomes between the Inflammatory (IG) and Non-Inflammatory (NIG)
   groups (P > 0.05). (“/“ symbol indicates unavailable data). (B)
   Comparison of Hematoxylin and Eosin (HE) staining and
   Immunohistochemistry (IHC) results between CG and LETB. CD38 and CD138
   serve as marker genes. Scale bar, 25 mm. (C) Comparison of intrauterine
   ultrasound images between CG and LETB. The morphology of the
   endometrial cavity shows uniformity without thinning of the endometrium
   (typically defined as < 7 mm). No significant differences were observed
   between CG and LETB in terms of endometrial morphology, thickness, and
   uterine cavity volume.

   Subsequently, we compared Hematoxylin and Eosin (HE) staining results
   between the control group and LETB, showing no significant differences.
   Immunohistochemistry (IHC) using CD38 and CD138 as inflammatory markers
   also showed no significant difference in inflammation levels between
   LETB and the control group (Fig. [62]1B). These findings further
   support the conclusion that LETB lacks specific inflammatory markers.
   Additionally, comparison of intrauterine ultrasound images between the
   control group and LETB showed no significant differences in endometrial
   morphology, thickness, or uterine cavity volume. Overall, our
   experimental results indicate the absence of specific inflammatory
   markers associated with LETB (Fig. [63]1C).

Transcriptomic analysis reveals novel inflammatory biomarkers for LETB

   Transcriptomic analysis aimed to uncover novel inflammatory biomarkers
   associated with latent endometrial tuberculosis (LETB). Through a
   systematic screening process, a series of pairwise intersections were
   performed among the control group (CG), LETB, and tuberculosis group
   (TB), followed by a subsequent intersection of the three sets. This
   approach yielded intersection A, representing a common pool of
   differentially expressed genes shared across the groups, thus serving
   as potential diagnostic targets. Further refinement involved excluding
   interference from common inflammatory genes. By intersecting CG-NIG and
   CG-IG, intersection B, comprising common inflammatory genes, was
   identified. Subsequently, genes in intersection B were removed from
   gene set A to derive gene set C, which specifically captured
   LETB-related inflammatory biomarkers. Lastly, intersections between
   LETB-NIG and LETB-IG revealed a specific set of inflammatory genes
   induced by latent tuberculosis, constituting the final candidate gene
   set E (Fig. [64]2A). Upon obtaining gene set E, we conducted an initial
   heatmap analysis to visualize the differential expression patterns of
   these genes across the CG, LETB, and TB groups (Fig. [65]1B). This
   preliminary screening facilitated the identification of seven candidate
   genes (IFI30, HCK, SPI1, IL1B, ITGB2, FCGR2A) based on their distinct
   expression profiles, statistical significance (p-value < 0.05), and
   functional relevance in immune regulation. The heatmap highlighted
   these genes in red, indicating their specific upregulation or
   downregulation in LETB tissues. The differential expression patterns of
   these potential biomarkers were visualized in a heatmap, showcasing
   downregulated genes in orange and upregulated genes in green across CG,
   LETB, and TB groups. Seven candidate genes, identified through rigorous
   screening, were highlighted in red (Fig. [66]2B).

Fig. 2.

   [67]Fig. 2
   [68]Open in a new tab

   Transcriptomic Analysis Attempts to Identify Novel Inflammatory
   Biomarkers for LETB. (A) The Venn diagram illustrates the screening
   process of potential inflammatory biomarkers. Initially, intersections
   were taken between the control group (CG), latent endometrial
   tuberculosis group (LETB), and tuberculosis group (TB) pairwise,
   followed by a subsequent intersection of the three sets to obtain
   intersection A, representing the common differentially expressed gene
   set A, serving as the candidate genes for potential diagnostic targets.
   Subsequently, interference from common inflammatory genes was excluded
   from the candidate gene set A, resulting in gene set C. Specifically,
   intersections were taken between CG-NIG and CG-IG to obtain the
   intersection B of common inflammatory genes, followed by the removal of
   genes contained in B from gene set A to derive gene set C. Finally, a
   specific set of inflammatory genes induced by latent tuberculosis was
   identified from gene set C as the final candidate gene set E. The
   method involved taking intersections between LETB-NIG and LETB-IG to
   obtain intersection D, followed by taking the intersection of gene sets
   C and D to derive gene set E. (B) Heatmap illustrating the differential
   expression of genes in gene set E across the Control Group (CG), Latent
   Endometrial Tuberculosis Group (LETB), and Tuberculosis Group (TB). In
   this analysis, downregulated genes are shown in orange, while
   upregulated genes are depicted in green. Through preliminary screening
   of gene set E, seven candidate inflammatory biomarkers were identified
   and highlighted in red. This visualization highlights the distinct
   expression patterns of these potential diagnostic markers, emphasizing
   their relevance in the immune response associated with LETB.

Unveiling distinct immune response functional enrichment and protein
interaction networks in LETB-associated candidate genes

   Building on the identification of candidate genes in gene set E
   (described in 3.2), we further explored their functional roles in LETB
   pathogenesis through enrichment analysis and protein interaction
   studies.

   Gene Ontology (GO) analysis revealed that the seven candidate genes
   (IFI30, HCK, SPI1, IL1B, ITGB2, FCGR2A) are significantly enriched in
   biological processes associated with immune response regulation. Key
   processes include positive regulation of myeloid leukocyte-mediated
   immunity, leukocyte degranulation, and cell activation. Cellular
   component analysis highlighted their localization to immune-related
   structures, such as tertiary granule membranes, secretory granule
   membranes, and membrane rafts, suggesting roles in intracellular
   signaling and material transport. At the molecular function level,
   these genes were associated with complement binding, protein tyrosine
   kinase activity, and STAT family protein binding, highlighting their
   importance in immune signaling pathways (Fig. [69]3A).

Fig. 3.

   [70]Fig. 3
   [71]Open in a new tab

   Functional Enrichment Analysis of Candidate Genes and Protein-Protein
   Interaction Network Exploration. (A) Gene Ontology (GO) analysis
   highlights the top ten terms in biological processes (BP), cellular
   components (CC), and molecular functions (MF) for a set of candidate
   genes derived from gene set E. Z-scores and log fold changes (logFC)
   quantify expression trends, with ‘upregulated’ indicating increased
   expression and ‘decreasing’/‘increasing’ reflecting changes in
   expression levels. (B) The overall KEGG pathway classifcation of the
   genes from gene set E. Top 10 up-regulated KEGG pathways are
   presented^[72]17–[73]19. (C) For the candidate genes potentially
   indicative of LETB, protein-protein interaction (PPI) analysis was
   conducted using STRING (PPI enrichment p-value < 1.0e-16). Line
   thickness indicates the confidence level of interactions, with only
   high-confidence interactions displayed. The PPI network is enriched for
   immune response pathway genes (false discovery rate = 5.51e-06).

   KEGG pathway enrichment analysis demonstrated that these genes are
   significantly involved in LETB-relevant pathways, particularly
   cytokine-cytokine receptor interaction, leukocyte transendothelial
   migration, and NF-κB signaling. These pathways are critical in driving
   inflammation and immune responses in LETB, providing insights into the
   molecular mechanisms underpinning disease progression (Fig. [74]3B).

   To further investigate the interactions and network relationships among
   these genes, we performed a protein-protein interaction (PPI) analysis.
   The analysis revealed that key proteins encoded by these genes, such as
   HCK, SPI1, IL1B, ITGB2, and FCGR2A, are central nodes in immune
   regulatory networks. Their interactions suggest a coordinated role in
   regulating immune activation and inflammation in LETB. These central
   nodes may represent potential therapeutic or diagnostic targets for
   LETB (Fig. [75]3C).

   Integrating these findings, we propose that the candidate genes
   identified from gene set E not only reflect distinct immune response
   landscapes in LETB but also serve as critical mediators of immune
   regulation and inflammation. Their roles in key immune pathways
   underscore their potential utility as diagnostic biomarkers and
   therapeutic targets for LETB.

Validating tuberculosis genomic markers: bridging transcriptomics with
clinical application

   In our study, we conducted a comprehensive analysis using Gene Set
   Enrichment Analysis (GSEA) to investigate the potential roles of six
   key genes (IF130, HCK, SPI1, IL1B, ITGB2, and FCGR2A) identified in
   endometrial tissues with latent tuberculosis infection, within
   immune-related biological pathways. Our analysis revealed significant
   enrichment of these genes in multiple pathways closely associated with
   immune response, including
   “KEGG_CYTOKINE_CYTOKINE_RECEPTOR_INTERACTION,” “KEGG_AXON_GUIDANCE,”
   “KEGG_LEUKOCYTE_TRANSENDOTHELIAL_MIGRATION,” and
   “KEGG_CHEMOKINE_SIGNALING_PATHWAY.”

   These pathways share a common theme in their core roles in
   communication, migration, and signal transduction among immune cells.
   Particularly, the enrichment of IF130, HCK, SPI1, IL1B, ITGB2, and
   FCGR2A in the “KEGG_CYTOKINE_CYTOKINE_RECEPTOR_INTERACTION” pathway
   suggests their potential involvement in regulating the interaction
   between cytokines and their receptors, a crucial step in immune
   response. Furthermore, the enrichment of ITGB2 in the
   “KEGG_LEUKOCYTE_TRANSENDOTHELIAL_MIGRATION” pathway implies its
   importance in the migration of immune cells across the endothelial
   layer, crucial for immune cell trafficking to sites of infection or
   inflammation. The enrichment of FCGR2A in the
   “KEGG_CHEMOKINE_SIGNALING_PATHWAY” pathway may be related to the
   chemotaxis and signaling mechanisms of immune cells (Fig. [76]4).

Fig. 4.

   [77]Fig. 4
   [78]Open in a new tab

   Gene set enrichment analysis of potential LETB biomarkers. Analyses of
   IFI30 (A) HCK (B) SPI1 (C) IL1B (D) ITGB2 (E) FCGR2A (F) were carried
   out. LETB, latent endometrial tuberculosis.

   Based on the analysis, we validated potential LETB biomarkers through
   qPCR, HE staining, and immunohistochemistry. The qPCR results indicated
   that the relative expression of IFI30, HCK, SPI1, IL1B, ITGB2, and
   FCGR2A was significantly higher in the inflammatory group (IG) compared
   to the non-inflammatory group (NIG) (p < 0.05). HE staining revealed
   notable inflammatory cell infiltration and structural alterations in
   the IG, whereas the NIG maintained relatively normal tissue
   architecture. Additionally, based on qPCR data, we selected HCK and
   ITGB2 for immunohistochemical validation, which demonstrated
   significantly enhanced expression in the IG. These findings
   collectively suggest that these biomarkers hold substantial clinical
   diagnostic potential in inflammatory conditions (Fig. [79]5).

Fig. 5.

   [80]Fig. 5
   [81]Open in a new tab

   Validation of Potential LETB Biomarkers through Clinical Samples. (A)
   Validation of potential LETB biomarkers by qPCR; * indicates that the
   relative expression differs (p < 0.05). (B) Comparison of HE staining
   results between the Inflammatory (IG) and Non-Inflammatory (NIG)
   groups. (C) Validation of potential LETB biomarkers by
   Immunohistochemistry.

Discussion

   Our study aimed to identify specific biomarkers for Latent Endometrial
   Tuberculosis (LETB) by employing RNA-Seq transcriptome profiling.
   Initial comparisons revealed that conventional diagnostic methods,
   including TB-IGRA and markers like CD38 and CD138, were insufficient in
   distinguishing LETB from control samples based on pregnancy outcomes,
   histological examinations, and immunohistochemistry (IHC) results.
   Subsequent transcriptomic analyses identified seven candidate genes
   (IFI30, HCK, SPI1, IL1B, ITGB2, and FCGR2A) uniquely associated with
   LETB, which were further validated through quantitative PCR (qPCR) and
   IHC, confirming their differential expression in LETB tissues.

   The immune response in LETB is characterized by unique inflammatory
   markers that differentiate it from other forms of tuberculosis and from
   healthy control endometrial tissues. Our study found that genes such as
   IFI30 and SPI1 play significant roles in myeloid leukocyte-mediated
   immunity and leukocyte degranulation, indicating a robust immune
   response specific to LETB. Gene Ontology (GO) and KEGG pathway analyses
   revealed these genes’ involvement in critical immune pathways, such as
   cytokine-cytokine receptor interaction and leukocyte transendothelial
   migration. These pathways are essential for immune cell communication,
   migration, and activation, which are crucial for mounting an effective
   response against latent infections.

   Drawing inspiration from the studies of Rull et al.^[82]20. and Uuskula
   et al.^[83]21. our research has identified a set of genes associated
   with LETB that could serve as potential biomarkers. These findings
   align with the increased expression of TRAIL and S100A8 in recurrent
   miscarriage (RM) as noted by Rull et al., and they also echo the work
   of Uuskula et al. on placental gene expression dynamics in pregnancy
   complications. Our study contributes to the understanding of LETB and
   its impact on reproductive health, offering new avenues for early
   detection and management strategies that could improve outcomes for
   affected women.

   The six genes identified (IFI30, HCK, SPI1, IL1B, ITGB2, and FCGR2A)
   have been implicated in various immune regulatory mechanisms and
   inflammation associated with tuberculosis. IFI30, known for its role in
   antigen processing and presentation, is critical in the immune system’s
   ability to recognize and respond to Mycobacterium
   tuberculosis^[84]22,[85]23. HCK and SPI1 are involved in the signaling
   pathways that activate macrophages and other immune cells, highlighting
   their importance in controlling TB infection^[86]22,[87]23. IL1B, a key
   pro-inflammatory cytokine, has been shown to be elevated in TB
   infections, contributing to the inflammatory milieu necessary for
   fighting the pathogen^[88]24. ITGB2 and FCGR2A are integral to
   leukocyte adhesion and migration, facilitating the movement of immune
   cells to sites of infection^[89]25–[90]28.

   In addition to their role in TB-related immune responses, these genes
   have been implicated in other health conditions involving inflammation.
   For instance, IFI30 has been linked to autoimmune diseases such as
   rheumatoid arthritis, where its antigen processing activity exacerbates
   immune dysregulation^[91]29. Similarly, HCK and SPI1 are known to
   regulate myeloid cell activation and cytokine signaling in chronic
   inflammatory conditions, including sepsis and inflammatory bowel
   disease^[92]30. IL1B is a well-characterized driver of systemic
   inflammation and has been associated with a wide range of pathological
   conditions, including atherosclerosis and obesity-related
   inflammation^[93]31–[94]33. ITGB2, critical for leukocyte adhesion, has
   been implicated in immune deficiencies and aberrant inflammatory
   responses, while FCGR2A, an important mediator of phagocytosis, plays a
   key role in autoimmune diseases like systemic lupus erythematosus and
   rheumatoid arthritis^[95]29,[96]31. These connections highlight the
   broader biological relevance of the genes identified in our study and
   provide insights into their potential roles in systemic immune
   responses.

   Furthermore, our findings may have implications beyond TB, as
   inflammatory mechanisms similar to those observed in LETB are also seen
   in pregnancy pathologies such as recurrent miscarriage and
   preeclampsia. For example, ITGB2 has been implicated in improper
   trophoblast invasion and placental dysfunction^[97]21,[98]34–[99]36,
   while IL1B is known to play a role in pregnancy-related inflammatory
   disorders, including preterm labor and pregnancy
   loss^[100]20,[101]32,[102]33,[103]36,[104]37. These parallels suggest
   that the immune dysregulation identified in LETB may also have
   relevance to other inflammatory conditions impacting reproductive
   health.

   In this study, we employed RNA-Seq technology to conduct a
   comprehensive analysis of the immune response characteristics
   associated with Latent Endometrial Tuberculosis (LETB), successfully
   identifying inflammation-related genes specific to LETB. Compared to
   the genome-wide expression analysis method utilized^[105]21, RNA-Seq
   offers enhanced resolution, allowing us to more precisely capture gene
   expression variations specific to LETB. Furthermore, while Uuskula et
   al. also applied transcriptome analysis to study the dynamic changes in
   placental gene expression, our research focused on the immune response
   to LETB, further demonstrating the broad applicability of
   high-throughput sequencing technologies across various
   pregnancy-related disease studies^[106]20. Through this comparative
   analysis of methodologies, our findings not only provide novel insights
   into the pathophysiology of LETB but also present potential molecular
   targets for the development of new diagnostic tools and therapeutic
   strategies, ultimately aiming to improve reproductive health outcomes
   for affected women.

   Future research integrating proteomics, metabolomics, and imaging data
   with transcriptomics is likely to enhance the resolution and
   translational relevance of LETB studies. Multi-omics approaches could
   validate and extend the present findings by correlating transcriptomic
   changes with protein activity, metabolic shifts, and tissue-level
   changes observed in radiomics. For example, combining transcriptomic
   biomarkers with metabolic pathway alterations could yield more reliable
   diagnostic and prognostic markers. While this study forms a basis for
   LETB biomarker discovery, incorporating these advanced methodologies
   would provide a more comprehensive understanding of LETB pathogenesis
   and improve the development of precise diagnostic and therapeutic
   strategies.

   Building on our findings, future research should focus on expanding
   sample sizes and integrating proteomic and metabolomic data to provide
   a more comprehensive understanding of LETB’s impact on infertility.
   Longitudinal studies are needed to explore the progression of LETB and
   its direct effects on reproductive outcomes. Additionally, functional
   studies of the identified biomarkers will help elucidate their roles in
   LETB pathogenesis and pave the way for the development of targeted
   diagnostic tools and treatments, ultimately improving fertility
   outcomes for affected women.

Conclusion

   This study identifies and validates novel inflammatory biomarkers for
   LETB, offering new insights into its pathogenesis and potential avenues
   for improved diagnostic and therapeutic strategies. The identified
   biomarkers, including IFI30, HCK, SPI1, IL1B, ITGB2, and FCGR2A, hold
   promise for enhancing the early detection and treatment of LETB,
   thereby improving reproductive health outcomes for affected women.

Acknowledgements