Targets of ATBC-associated ovarian damage and infertility

Our research began by pinpointing ATBC-associated targets in the ChEMBL, Super-PRED, and STITCH databases, respectively. We then refined our search to 2076 ovarian damage-related and 3236 infertility-related targets using GeneCards, and identified an additional 125 ovarian damage-related and 4 infertility-related targets from the OMIM database. Following data consolidation and deduplication, we focused on 319 targets linked to ATBC, 2110 targets related to ovarian damage, and 3236 targets associated with infertility. The intersection of these target sets revealed 137 common targets for ATBC and ovarian damage, and 143 for infertility, suggesting their potential influence on ATBC-induced conditions (Fig. 1A-B). Additionally, the intersection among ATBC, ovarian damage, and infertility revealed 104 shared targets (Figure S1).

Fig. 1

Venn diagram of the targets of ATBC and ovarian damage and infertility. A Ovarian damage; B Infertility

Protein–protein interaction (PPI) networks between ATBC and common targets of ovarian damage and infertility

We employed the STRING database to map the PPI networks related to ovarian damage and infertility. The ovarian damage network included 137 nodes interconnected by 1530 edges, averaging a node connectivity of 22.3. The infertility network featured 143 nodes with 1345 edges, averaging a node connectivity of 18.8. Cytoscape software was then used to scrutinize the topological attributes of the nodes, with a particular emphasis on degree and betweenness centrality (Fig. 2A-D).

Fig. 2

PPI networks involving ATBC and its common and core targets in ovarian damage and infertility. A PPI network for ATBC-associated ovarian damage, derived from STRING database data, with 137 nodes, 1530 edges, and an average node connectivity of 22.3. B PPI network for ATBC-associated infertility, featuring 143 nodes, 1345 edges, and an average node connectivity of 18.8. C, D PPI network diagrams for ATBC-related ovarian damage and infertility, respectively, highlighting nodes with a degree greater than 10, as generated by Cytoscape software. E, F Pivotal nodes within the ATBC-associated ovarian damage and infertility networks, respectively, with color intensity reflecting the ascending degree values of the nodes, as determined by the cytoHubba plugin

Network analysis pinpointed 19 core targets for ATBC-induced ovarian damage (Fig. 2E), with TNF, SRC, and BCL2 being the most connected targets. For ATBC-induced infertility, 30 core targets were identified (Fig. 2F), headed by TNF, SRC, and CASP3. These genes encode proteins that are integral to a spectrum of cellular processes, such as inflammatory response, regulation of cell proliferation and cycle, apoptosis mediation, and signal transduction pathways.

GO Analysis and Pathway Enrichment Analysis of ATBC-associated targets in ovarian damage and infertility

We then performed a Gene Ontology (GO) analysis on 137 ATBC-related targets for ovarian damage, concentrating on human biological features. This analysis yielded 1514 notable GO entries, covering 1282 biological processes, 92 cellular components, and 140 molecular functions. A parallel analysis for infertility's 143 targets identified 1384 significant entries, encompassing 1193 biological processes, 73 cellular components, and 118 molecular functions. We prioritized these findings by False Discovery Rate (FDR), highlighting the top 10 terms with the lowest FDR values across categories for visual representation in Figs. 3 and 4.

Fig. 3

GO Enrichment analysis for targets associated with ATBC-induced ovarian damage. A A bubble chart depicting the top 10 enriched biological processes; B A chord diagram linking these processes (BPs) to their respective genes. C and D Top 10 enriched cellular components and their interconnections with associated genes. E and F Top 10 enriched molecular functions and genes related to these functions (MFs). In this figure, the Gene Ontology (GO) terms are represented by bubbles, where size corresponds to the gene count within a pathway, and color depth indicates the level of enrichment significance, with darker red representing greater significance

Fig. 4

GO Enrichment analysis for targets associated with ATBC-induced ovarian infertility. A A bubble chart depicting the top 10 enriched biological processes; B A chord diagram linking these processes (BPs) to their respective genes. C and D Top 10 enriched cellular components and their interconnections with associated genes. E and G Top 10 enriched molecular functions and genes related to these functions (MFs). In this figure, the Gene Ontology (GO) terms are represented by bubbles, where size corresponds to the gene count within a pathway, and color depth indicates the level of enrichment significance, with darker red representing greater significance

We delved into the functional roles of these targets in biological systems and their underlying mechanisms in disease pathogenesis through a comprehensive KEGG pathway analysis. The analysis revealed 179 significantly enriched pathways linked to ovarian damage and 164 pathways associated with infertility. Utilizing an inverse ranking based on False Discovery Rate (FDR) values, we generated a significance statistical bubble chart depicted in Fig. 5, visually representing the top 10 KEGG signaling pathways for both conditions (Table 1, 2). A chord diagram complements this by detailing the genes participating in these pathways. These integrated bioinformatics analyses have provided deeper insights into the targets'roles across biological processes, cellular components, and molecular functions, as well as their engagement in crucial signaling pathways.

Fig. 5

KEGG enrichment analysis of ATBC-related targets for ovarian damage and infertility. A Bubble chart of the top 10 enriched KEGG pathways related to ATBC and ovarian damage. Each bubble represents a specific pathway, with the area indicating the number of enriched genes within that pathway. The color intensity of the bubbles signifies the significance of the enrichment, with deeper red shades indicating higher significance. B Distribution of 19 targets (NFKB1, IL2, FLT3, KRAS, PDGFRA, MAP2 K2, HSP90 AA1, PTK2, MCL1, TLR4, BCL2L1, BCL2, FGFR1, CHRM2, PRKCA, RXRA, IKBKB, NR4 A1, IGF1R) related to ATBC and ovarian damage in the PI3 K/AKT signaling pathway. C Bubble chart of the top 10 enriched pathways related to ATBC and infertility. D: Distribution of 16 targets (NFKB1, CTSD, PARP2, KRAS, MAP2 K2, CASP6, ATM, CASP3, CTSB, CASP8, MAP3 K5, MCL1, BCL2L1, BCL2, TNF, IKBKB) related to ATBC and infertility in the apoptosis signaling pathway

Table 1 KEGG enrichment results of the targets between ATBC and ovarian damageTable 2 KEGG enrichment results of the targets between ATBC and infertility

The findings from GO and KEGG analyses highlight the extensive distribution and expression of these genes within diverse cellular structures. They are implicated in critical physiological functions, including responses to chemical stimuli, modulation of various cell death pathways, and signal transduction. Notably, the KEGG pathway enrichment identified several pathways associated with signaling mechanisms crucial to processes like apoptosis, the PI3 K-Akt signaling pathway, the NF-kappa B pathway, and pathways in cancer. The prominence of these pathways aligns with documented cases of ovarian damage and infertility, offering valuable insights into the genes'roles in pathological mechanisms.

Drug-pathway-target-disease analysis of core targets for ATBC-related ovarian damage and infertility

To investigate the underlying signaling pathways through which ATBC influences key genes associated with infertility and ovarian damage, KEGG pathway analysis for the core target genes was conducted. Results revealed the top 10 significantly enriched pathways based on P-value for both ATBC-induced ovarian damage and infertility (Fig. 6A, B), with 8 overlapping pathways. Within these pathways, 18 common core genes were identified (MMP2, NFKB1, IL2, KRAS, PPARG, CASP3, HSP90 AA1, STAT1, PTGS2, BCL2L1, NFE2L2, BCL2, ESR1, MAPK14, SRC, TLR4, TNF, ATM), indicating that ATBC's impact on ovarian function could be a primary factor contributing to infertility.

Fig. 6

Drug-pathway-target-disease network of ATBC in ovarian damage (A) and infertility (B). The blue hexagon represents ATBC. The green diamond represents pathways affected by ATBC in both ovarian damage and infertility. The red circles represent targets impacted by ATBC. The orange circles represent the diseases

Verification of core genes differential expression in ovarian damage and infertility

The expression of 12 core genes (10 associated with infertility and 10 with ovarian damage) were validated in the context of infertility and ovarian damage using published datasets from the GEO database. In the GSE120103 dataset, when compared to the endometrium of fertile women, 7 significantly differentially expressed genes were identified in the endometrial tissue of infertile women. These included 3 downregulated genes (ESR1, STAT1, and TNF) and 4 upregulated genes (HSP90 AA1, KRAS, PTGS2, and TLR4) (Fig. 7A). In the subset of women with Stage IV ovarian endometriosis, 8 significantly differentially expressed genes were found in the endometrial tissue of infertile women compared to fertile women. This included 4 downregulated genes (HSP90 AA1, NFKB1, PPARG, and STAT1) and 4 upregulated genes (ESR1, KRAS, PTGS2, and TNF) (Fig. 7B). Within the GSE232306 dataset, when comparing women with diminished ovarian reserve function to those with normal ovarian reserve function, 9 significantly differentially expressed genes were identified, all of which were upregulated (CASP3, ESR1, HSP90 AA1, KRAS, NFKB1, PPARG, PTGS2, SRC, and STAT1) (Fig. 7C).

Fig. 7

Expression of 12 Key Genes in Endometrium and Ovaries of Infertile Women. A Gene expression in endometrium from fertile and infertile women without disease (n = 9 per group). B Gene expression in endometrium from women with Stage IV endometriosis (n = 9 per group). C. Gene expression in ovarian tissue from women with reduced ovarian reserve and normal older controls. * P < 0.05, ** P < 0.01, *** P < 0.001, **** P < 0.0001

Mendelian randomization analysis

To explore the potential impact of core genes on the genetic susceptibility to infertility and ovarian damage, an Inverse Variance Weighted Mendelian Randomization analysis was conducted. The findings revealed that for each one-unit increase in the score of the TLR4 SNPs (rs2039954 and rs5020985) (Fig. 8), the beta value for infertility decreased by 0.2 (OR = 0.76, 95% CI 0.62–0.99; P = 0.049) (Fig. 8). There was no strong evidence to suggest a association between the core genes and ovarian function.

Fig. 8

Mendelian Randomization Analysis of Toll-like Receptor 4 (TLR4) Genetic Variants on Female Infertility. A Scatter plot of the causal effect estimates for TLR4 single nucleotide polymorphisms (SNPs: rs2039954 and rs5020985) on female infertility risk, analyzed using a two-stage Mendelian randomization (MR) framework. Primary estimates were derived via the Inverse Variance Weighted (IVW) method (solid line), with sensitivity analysis performed using MR Egger regression (dashed line) to evaluate directional pleiotropy

Molecular docking analysis

Utilizing molecular docking strategies, we investigated the interactions of ATBC with the top 10 target proteins (8 shared proteins) implicated in both ovarian damage and infertility (TNF, CASP3, HSP90 AA1, ESR1, PPARG, PTGS2, TLR4, STAT1, SRC, BCL2, NFKB1, KRAS) (Table 3). The analysis revealed strong affinities and negative binding energies for all 12 targets, substantiating their crucial involvement in ATBC-induced conditions. Visualization of the lowest binding energies between each target and ATBC is presented (Fig. 9, Table 4). These visual representations enhance our comprehension of the interaction mechanisms between ATBC and the target proteins, offering vital insights for delving into ATBC's reproductive toxicity mechanisms.

Table 3 Core targets informationFig. 9

Molecular Docking Analysis of ATBC with Key Target Proteins Associated with Ovarian Damage and Infertility. A-L Structural visualization of molecular docking interactions between ATBC and 12 target proteins implicated in ovarian damage and infertility. Proteins include: (A) BCL2, (B) CASP3, (C) ESR1, (D) HSP90 AA1, (E) KRAS, (F) NFKB1, (G) PPARG, (H) PTGS2, (I) SRC, (J) STAT1, (K) TLR4, and (L) TNF. Each panel illustrates the lowest-energy binding conformation of ATBC (stick model, carbon atoms in cyan) within the active site of the respective protein (surface or ribbon representation)

Table 4 Molecular docking scores (kcal/mol)