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. 2024 Dec 3;13(6):tfae199. doi: 10.1093/toxres/tfae199

The impact of Benzophenone-3 on osteoarthritis pathogenesis: a network toxicology approach

Yongji Li 1, Geqiang Wang 2, Peiran Liu 3, Lin Zhang 4, Hai Hu 5, Xiangjun Yang 6, Hongpeng Liu 7,✉
PMCID: PMC11645663  PMID: 39677492

Abstract

Background

Arthritis is a degenerative joint disease influenced by various environmental factors, including exposure to Benzophenone-3 (BP3), a common UV filter. This study aims to elucidate the toxicological impact of BP3 on arthritis pathogenesis using network toxicology approaches.

Method

We integrated data from the Comparative Toxicogenomics Database (CTD) and Gene Expression Omnibus (GEO) to identify differentially expressed BP3-related toxicological targets in osteoarthritis (OA). Enrichment analyses were conducted to determine the implicated biological processes, cellular components, and molecular functions. Further, the involvement of the PI3K-Akt signaling pathway was investigated, along with correlations with immune cell infiltration and immune-related pathways. Molecular docking analysis was performed to examine BP3 interactions with key PI3K-Akt pathway proteins.

Results

A total of 74 differentially expressed BP3-related targets were identified. Enrichment analysis revealed significant pathways, including PI3K-Akt, MAPK, and HIF-1 signaling. The PI3K-Akt pathway showed notable dysregulation in OA, with reduced activity and differential expression of key genes such as ANGPT1, ITGA4, and PIK3R1. Correlation analysis indicated significant associations between PI3K-Akt pathway activity and various immune cell types and immune pathways. Molecular docking highlighted strong interactions between BP3 and proteins like AREG, suggesting potential disruptions in signaling processes.

Conclusions

BP3 exposure significantly alters the expression of toxicological targets and disrupts the PI3KAkt signaling pathway, contributing to OA pathogenesis. These findings provide insights into the molecular mechanisms of BP3-induced OA and identify potential therapeutic targets for mitigating its effects.

Keywords: Benzophenone-3, Osteoarthritis, Network toxicology, PI3K-Akt Signaling pathway, Immune cell infiltration, Molecular docking

Introduction

Osteoarthritis (OA) is a chronic, degenerative joint disorder characterized by the progressive breakdown of joint cartilage and underlying bone, leading to pain, stiffness, and loss of joint function.1,2 It is a major cause of disability worldwide, affecting over 300 million people. The etiology of OA is multifactorial, involving genetic predispositions, mechanical stress, aging, and environmental factors.3,4 Recent research has highlighted the significant role of environmental pollutants in the exacerbation of OA,5,6 with particular attention to compounds like Benzophenone-3 (BP3), a widely used UV filter in sunscreens and personal care products.7 BP3, also known as oxybenzone, is prevalent in various environmental matrices due to its extensive use and subsequent release into the environment. It has been detected in water bodies, soil, and even human tissues, raising concerns about its potential toxicological impacts.8 Although BP3 is primarily known for its protective role against UV radiation, emerging evidence suggests it may have adverse effects on human health, including endocrine disruption, reproductive toxicity, and now, possibly, the exacerbation of degenerative joint diseases like OA.9–12

Environmental pollutants have long been implicated in the development and progression of OA. For instance, recent research indicates that arsenic-induced reactive oxygen species disrupt the equilibrium between catabolic and anabolic processes in chondrocytes, ultimately leading to the degradation of cartilage.13 Air pollution exposure may play a role in the onset and progression of OA, primarily through mechanisms such as mitochondrial dysfunction, epigenetic changes, oxidative stress, and inflammation.14 Triclocarban induces osteoarthritis in zebrafish anal fins by causing DNMT1-mediated hypermethylation of the type II collagen gene.15 Specifically, BP3 has been associated with various adverse health effects due to its endocrine-disrupting properties.16 Furthermore, a recent investigation revealed that urinary levels of BP3 exhibited a positive correlation with the incidence of OA within the United States population.17 Nevertheless, its involvement in the pathogenesis of OA remains inadequately investigated, and there is a significant lack of studies that integrate network toxicology with molecular docking methodologies to elucidate the systemic effects of BP3 on OA.

Given the widespread use of BP3 and its pervasive presence in the environment, there is an urgent need to comprehensively understand its impact on OA pathogenesis. This study is motivated by the necessity to bridge the knowledge gap regarding the molecular mechanisms through which BP3 influences OA. Understanding these mechanisms is crucial for developing targeted strategies to mitigate the adverse effects of BP3 and improve public health outcomes. The primary objective of this study is to elucidate the toxicological impact of BP3 on OA using a network toxicology approach. To achieve these objectives, we integrated data from the Comparative Toxicogenomics Database (CTD) and Gene Expression Omnibus (GEO). We identified differentially expressed BP3-related targets and conducted enrichment analyses to uncover significant biological pathways. Further, we focused on the PI3K-Akt signaling pathway, analyzing its activity and gene expression profiles in the context of OA. Correlation analyses were performed to explore associations with immune cell infiltration and immune-related pathways. Finally, molecular docking studies were conducted to investigate the interactions between BP3 and key proteins in the PI3K-Akt pathway. This study provides crucial insights into the molecular mechanisms by which BP3 exposure contributes to OA pathogenesis. By identifying specific toxicological targets and disrupted signaling pathways, our findings highlight potential therapeutic targets for mitigating the adverse effects of BP3. Moreover, this research underscores the importance of considering environmental pollutants in the context of chronic diseases, ultimately contributing to better public health policies and preventive strategies.

Methods

Datasets collection and preparation

The OA-related datasets utilized in our investigation were sourced from the NCBI Gene Expression Omnibus (GEO) database (GSE12021, GSE55457, and GSE55235) (Table S1). To ensure consistency across the datasets, we employed the R package “sva” for the integration process, thereby mitigating the variations attributable to batch effects. We conducted an analysis of differential gene expression by applying specific criteria, namely |log fold change (FC)| of at least 0.5 and an adjusted p-value of less than 0.05, to identify the differentially expressed genes (DEGs).

Collection of PB3 toxicological targets sourced from the CTD

The CTD (http://ctdbase.org/) serves as a comprehensive repository that aggregates diverse datasets concerning chemical exposures and their associated biological ramifications. This resource encompasses information on chemical compounds, genomic data, phenotypic variations, pathological conditions, and taxonomic classifications, all derived from peer-reviewed scientific literature.18 In this study, CTD was employed to identify the toxicological targets associated with PB3.

Identification of BP3 toxicity targets associated with differential expression in OA

Using the Venny tool, we identified common targets of DEGs and PB3-related targets. These potential targets could elucidate the toxic role of PB3 in triggering OA. The findings are depicted through volcano and heatmap visualizations generated with the ggplot2 and ComplexHeatmap packages.

Enrichment analysis

To clarify the biological mechanisms and pathways potentially implicated in the development of OA, particularly in the context of exposure to PB3, we conducted analyses of Gene Ontology (GO) functional enrichment alongside Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. The enrichment assessment was performed utilizing the ClusterProfiler package, with a significance threshold established at P < 0.05 to identify pertinent biological pathways. The resultant analytical data were subsequently visualized employing the ggplot2 package. The gene set associated with the PI3K-Akt signaling pathway was derived from the findings of the KEGG analysis. The pathway enrichment scores for the PI3K-Akt signaling pathway in each sample from OA-related datasets were calculated using the GSVA algorithm and depicted through box plots.

Analysis of the immunological microenvironment

To evaluate the levels of 24 subtypes of immune cells and 16 pathways associated with immune responses, single-sample gene set enrichment analysis (ssGSEA) was utilized. Immune cell subtype gene sets were obtained from previous studies,19 while those related to immune response pathways were extracted from the ImmPort database (http://www.immport.org).20 These gene sets were employed to assess the enrichment levels of immune components. Additionally, pearson correlation analysis was performed to investigate the association between the PI3K-Akt signaling pathway and the concentrations of immune cell components, as well as the immune response pathways.

Molecular docking

The compound structure of PB3 was obtained from PubChem (https://pubchem.ncbi.nlm.nih.gov/) in Structure Data File (SDF) format. This compound structure was subsequently processed using AutoDock Tools (version 1.5.6), leading to the conversion of the files into PDBQT format. For the docking experiments, the target protein structures were extracted from the Protein Data Bank (PDB) (https://www.rcsb.org). Their pre-processing was also conducted with AutoDock Tools, which included critical procedures such as the elimination of water molecules that could disrupt binding evaluations, the incorporation of hydrogen atoms to ensure a more accurate representation of the molecular structure, and the assignment of appropriate molecular charges. The docking simulations were performed employing AutoDock Vina, and the resulting data were visualized using PyMOL software, version 1.0.0.

Results

Characterization and analysis of toxicological targets associated with BP3 in OA

By integrating data from the CTD and GEO, we identified differentially expressed BP3-related Targets. Specifically, Fig. 1A illustrates a Venn diagram summarizing the intersection between BP3-related targets and DEGs in OA. A total of 495 BP3-related targets were extracted from the CTD, while 2,323 DEGs were identified from the OA-related dataset. The intersection of these datasets reveals 74 differentially expressed BP3-related toxicological targets implicated in OA pathogenesis. In Fig. 1B, a volcano plot is illustrated, showcasing the identified toxicological targets. This visualization emphasizes 38 targets that are upregulated (marked in red) and 36 targets that are downregulated (marked in blue). Additionally, Fig. 1C displays a heatmap illustrating the expression levels of the 74 differentially expressed BP3-related targets across healthy controls (HC) and OA samples. Notably, genes such as PTGS2, HIF1A, and ANGPTL4 exhibit marked downregulation in OA samples compared to HC, whereas others such as FRZB, PER3 and TNFSF11 are significantly upregulated. The PPI network of these toxicological targets were shown in Fig. S1. These findings collectively underscore the differential expression and potential regulatory roles of BP3-related targets in OA, thus providing a foundational understanding for further mechanistic and therapeutic investigations.

Fig. 1.

Fig. 1

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Identification and visualization of differentially expressed BP3-related targets in OA. (A) Venn diagram showing the intersection of BP3-related targets (495 genes from the CTD) and DEGs (2323 genes from GEO datasets) related to OA, identifying 74 common differentially expressed BP3-related targets. (B) Volcano plot depicting the distribution of the 74 differentially expressed BP3-related targets. (C) Heatmap displaying the expression levels of the 74 differentially expressed BP3-related targets in HC and OA samples. Hierarchical clustering was applied to both genes (rows) and samples (columns).

Enrichment analysis of differentially expressed BP3-related toxicological targets

To elucidate the pathways through which BP3 exposure might induce OA, we performed enrichment analysis on the 74 differentially expressed BP3-related targets. The enrichment analysis results are illustrated in Fig. 2, which displays the significant GO terms and their respective enrichment scores. BP enriched terms include regulation of lipid metabolic process, regulation of protein localization to cell periphery, regulation of blood pressure, cellular respiration, mammary gland alveolus development, mammary gland lobule development, response to steroid hormone, response to hypoxia, leukocyte cell–cell adhesion, and response to decreased oxygen levels. These terms suggest the involvement of BP3-related targets in critical regulatory pathways and metabolic processes pertinent to OA. CC enriched terms are organelle outer membrane, outer membrane, mitochondrial outer membrane, respiratory chain complex, mitochondrial respirasome, immunological synapse, and oxidoreductase complex. The prominence of these terms indicates that BP3-related targets may localize to membranous structures and complexes that are essential for cellular respiration and immune responses. MF enriched terms include protein tyrosine kinase binding, receptor tyrosine kinase binding, protein tyrosine kinase activity, DNA-binding transcription factor binding, cysteine-type endopeptidase activity in apoptotic signaling pathway, non-membrane spanning protein tyrosine kinase activity, amide binding, and BH domain binding. The enrichment in these molecular functions highlights potential roles of BP3-related targets in signal transduction, gene expression regulation, and apoptosis within OA. Figure 2A presents a bubble plot outlining the KEGG pathway enrichment results. The key enriched pathways were: PI3K-Akt signaling pathway, chemical carcinogenesis-reactive oxygen species, MAPK signaling pathway, HIF-1 signaling pathway, progesterone-mediated oocyte maturation, human T-cell leukemia virus 1 infection, Ras signaling pathway, etc. Figure 3B displays a pathway network map, where nodes represent enriched pathways, and edges indicate shared genes among the pathways. Central interconnected pathway is PI3K-Akt signaling pathway, underscoring a complex network of signal transduction pathways modulated by BP3-related targets. The enrichment analysis reveals that BP3-related targets are implicated in pivotal signaling pathways and disease mechanisms relevant to OA, providing insights into potential therapeutic targets and molecular mechanisms underlying BP3-induced OA.

Fig. 2.

Fig. 2

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GO terms of differentially expressed BP3-related targets in OA. The xaxis represents the enrichment score, while the y-axis lists the significantly enriched GO terms. The GO terms are categorized into three ontologies: Biological Process (BP), Cellular Component (CC), and Molecular Function (MF).

Fig. 3.

Fig. 3

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KEGG pathway enrichment analysis of differentially expressed BP3-related targets in OA. (A) Bubble plot showing the significantly enriched KEGG pathways related to BP3 exposure in OA. Dot size corresponds to the number of genes involved in each pathway, while the color gradient reflects the significance level (p-value). (B) Network map visualizing the interconnections among enriched KEGG pathways. Nodes represent enriched pathways, and edges indicate shared genes between pathways. Node size indicates the number of associated genes, and the node color gradient represents the p-value for pathway enrichment.

Analysis of PI3K-Akt signaling pathway involvement in OA

To investigate the involvement of the PI3K-Akt signaling pathway in OA following BP3 exposure, we performed differential expression analysis and pathway activity assessment. Figure 4A illustrates a heatmap depicting the expression profiles of genes involved in the PI3K-Akt signaling pathway across HC and OA samples. Key genes such as ANGPT1, ITGA4, PIK3R1, VEGFA, CDK2, and AREG show notable differential expression, suggesting their potential roles in the altered PI3K-Akt signaling in OA. Figure 4B presents a box plot of the PI3K-Akt signaling pathway scores derived using the ssGSEA algorithm. The results demonstrate a significant reduction in the PI3K-Akt pathway activity in OA samples compared to HC samples (***P < 0.001). This decrease in pathway activity indicates potential dysregulation of PI3K-Akt signaling in OA, potentially contributing to disease pathogenesis following BP3 exposure. These findings collectively highlight the significant alterations in the PI3K-Akt signaling pathway in OA, providing insights into the molecular mechanisms through which BP3 exposure might exacerbate OA pathology.

Fig. 4.

Fig. 4

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PI3K-Akt signaling pathway activity in OA resulting from BP3 exposure. (A) Heatmap showing the expression profiles of genes involved in the PI3K-Akt signaling pathway across HC and OA samples. The hierarchical clustering of genes and samples is shown, with color intensities indicating gene expression levels. (B) Box plot illustrating the GSVA scores of the PI3K-Akt signaling pathway in HC and OA groups. ***P < 0.001.

Correlation of PI3K-Akt pathway with immune cell infiltration and immune-related pathways

To explore the relationship between the PI3K-Akt signaling pathway and immune responses in OA following BP3 exposure, we conducted sssGSEA to evaluate the correlations with immune cell infiltration levels and immune-related pathways. Figure 5A depicts the correlation of the PI3K-Akt signaling pathway score with various immune cell infiltration levels. Positive correlations were observed with CD8 T cells (R = 0.678, ***P < 0.001), Tcm (central memory T cells) (R = 0.509, ***P < 0.001), and eosinophils (R = 0.503, ***P < 0.001), among others. Negative correlations were found with macrophages (R = −0.417, **P < 0.01), mast cells (R = −0.397, **P < 0.01), and T cells (R = −0.329, *P < 0.05), indicating a significant inverse relationship between PI3K-Akt pathway activity and these cell types in OA. Figure 5B shows the correlation between the PI3K-Akt signaling pathway score and various immune-related pathways. Significant positive correlations were observed with interleukins (R = 0.595, ***P < 0.001), chemokines (R = 0.438, ***P < 0.001), and cytokine receptors (R = 0.432, ***P < 0.001), among others. A significant negative correlation was identified with TNF family members (R = −0.668, ***P < 0.001), suggesting an inverse association between TNF signaling and PI3K-Akt pathway activity. These findings reveal that the PI3K-Akt signaling pathway is significantly correlated with the infiltration of specific immune cell types and the activity of various immune-related pathways. This suggests that BP3 exposure could potentially modulate immune responses in OA through alterations in the PI3K-Akt signaling pathway.

Fig. 5.

Fig. 5

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Correlation between PI3K-Akt signaling pathway activity and immune cell infiltration and immune-related pathways in OA. (A) Dot plot displaying the correlations between the PI3K-Akt signaling pathway scores and immune cell infiltration levels. (B) Dot plot showing the correlations between the PI3K-Akt signaling pathway scores and immune-related pathways. The x-axis indicates the correlation coefficient, and the y-axis lists the immune cell types or immune pathways. Dot sizes represent the absolute value of the correlation coefficients, and colors indicate the significance levels (P-values).

Representative molecular pathway of OA induced by BP3 exposure

To investigate the molecular mechanisms through which BP3 exposure may induce OA, we analyzed the hub PI3K-Akt signaling pathway. Figure 6 provides a detailed map of this pathway, illustrating the expression changes induced by BP3 exposure. Genes such as GF (Growth Factor), SGK (Serum/Glucocorticoid Regulated Kinase), and Bcl-XL (B-cell lymphoma-extra large) are significantly downregulated. These genes are associated with cell growth, survival, and metabolic processes, indicating a potential disruption in these pathways due to BP3 exposure. The pathway map depicts the intricate series of interactions, starting from receptor tyrosine kinases (RTKs) leading to the inactivation of PI3K and subsequent inactivation of AKT. Inactivated AKT influences various downstream effectors involved in: Key anti-apoptotic proteins such as Bcl-2 and Mcl-1, affecting cellular apoptosis mechanisms in chondrocytes and synoviocytes. Molecules such as CDK, essential for cell cycle progression, which could impact cell proliferation in subchondral bone cells. This pathway map emphasizes the critical role of the PI3K-Akt signaling pathway in the molecular mechanisms underlying BP3-induced OA. The differential expression of key genes within this pathway highlights potential therapeutic targets for mitigating BP3-induced OA.

Fig. 6.

Fig. 6

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PI3K-Akt signaling pathway alterations in OA induced by BP3 exposure. The diagram illustrates the PI3KAkt signaling pathway, highlighting gene expression changes induced by BP3 exposure.

Molecular docking of BP3 with PI3K-Akt pathway proteins

To explore the potential interactions between BP3 and key proteins involved in the PI3K-Akt signaling pathway, we performed a molecular docking analysis. Table 1 presents the docking scores, which reflect the binding affinity between BP3 and these proteins. These results indicate that BP3 interacts with multiple key proteins in the PI3K-Akt signaling pathway, with the strongest binding observed for AREG (vina score = −79.8), potentially disrupting normal signaling processes. This disruption in the PI3K-Akt signaling cascade may contribute to the pathogenesis of osteoarthritis upon BP3 exposure. Figure 7A depicts the surface representation of BP3 docked within the binding pocket of AREG. BP3 is shown snugly fitting into a specific binding pocket of AREG. Figure 7B offers a detailed close-up view of the interaction interface between BP3 and AREG. Various interactions contributing to the binding affinity are depicted, including hydrogen bonds, hydrophobic contacts, and electrostatic interactions. These interactions suggest a high binding affinity of BP3 to AREG, correlating with the docking score of −79.8 kcal/mol, which is the strongest observed among evaluated PI3K-Akt signaling pathway proteins. Overall, this detailed docking analysis provides critical insights into the molecular basis of BP3’s interaction with AREG, further supporting the toxicological implications of BP3 exposure in OA development.

Table 1.

Docking scores of PI3K-Akt signaling pathway-related proteins with BP3.

PI3K-Akt pathway-related genes Protein ID Vina score
VEGFA 6D3O −6.7
HSP90AA1 3O0I −8.1
MCL1 4WMR −8.6
BCL2L1 1MAZ −6.5
ITGA4 3V4P −7.9
ANGPT1 4EPU −7.8
SGK1 3HDN −7.5
CDK2 3PXR −8.2
AREG 2RNL −79.8
CHUK 5TQW −7.4
PIK3R1 6D81 −6.4
ANGPT2 4JZC −5.9
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Fig. 7.

Fig. 7

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Optimal docking pose of BP3 with the toxicity target AREG. (A) Surface representation of the AREG protein with BP3 bound within its binding pocket. (B) the interaction interface showing the detailed binding pose of BP3 within AREG.

Discussion

BP3, a UV filter commonly found in personal care products, has garnered increasing attention for its potential impact on human health, including its role in OA pathogenesis. OA is a chronic degenerative joint disease characterized by cartilage degradation and inflammation. Previous studies have suggested that environmental factors, such as chemical exposures, may exacerbate OA symptoms, yet the molecular mechanisms remain unclear.21,22 Our study, utilizing a network toxicology approach, sheds light on the toxicological effects of BP3 in OA, particularly through the disruption of the PI3K-Akt signaling pathway. Our findings indicate that BP3 exposure leads to significant dysregulation of the PI3K-Akt signaling pathway, which plays a critical role in cellular processes such as survival, proliferation, and inflammation.23 The observed dysregulation, characterized by reduced pathway activity and altered expression of key genes such as ANGPT1, ITGA4, and VEGFA, is consistent with the literatures implicating this pathway in cartilage degradation and joint inflammation. Furthermore, recent studies have highlighted the multifactorial nature of arthritis, involving various cell types and factors, suggesting that BP3 may interact with additional cellular mechanisms beyond the PI3K-Akt pathway in OA.24–26

ANGPT1 (angiopoietin-1) and ITGA4 (integrin alpha-4) are integral to cell adhesion and angiogenesis, processes essential for maintaining cartilage integrity and joint function.27,28 TNF alpha enhances the expression of ANGPT1 mRNA and protein in synovial fibroblasts, suggesting that ANGPT1 may play a critical role in regulating angiogenesis associated with inflammatory arthritis.29 In our study, the upregulation of ANGPT1 and ITGA4 suggests impaired angiogenesis and cell-matrix interactions, which can contribute to cartilage breakdown and OA progression. Similarly, VEGFA (vascular endothelial growth factor A) is crucial for vascularization and repair mechanisms.30 VEGF is involved in the pathophysiological processes associated with cartilage senescence and degeneration, as well as in the mechanisms underlying cartilage regeneration.31 In addition, a meta-analysis demonstrates a robust association between elevated levels of VEGF expression and the pathophysiology of OA.32 Its altered expression in response to BP3 may affect the vascular supply to the cartilage and hinder the repair processes, further exacerbating OA.

The disruption of the PI3K-Akt pathway by BP3 may also have broader implications for cellular stress responses and apoptosis. The PI3K-Akt pathway is known to regulate several downstream targets involved in cell survival and inflammation.33,34 Reduced activity of this pathway, as evidenced in our study, may lead to increased cell apoptosis and chronic inflammation, which are hallmarks of OA.35 Our correlation analysis further uncovered significant associations between PI3K-Akt pathway activity and immune cell infiltration in OA tissues. The PI3K-Akt pathway is integral to immune cell regulation, influencing processes such as cell survival, proliferation, and inflammatory responses.36,37 Dysregulation of this pathway, as observed in our study, may lead to abnormal immune responses, contributing to the chronic inflammation characteristic of OA. This is consistent with the previous research demonstrating that PI3K-Akt signaling impacts immune cell function and inflammatory pathways, thereby influencing disease outcomes.38–40 The significant association between PI3K-Akt signaling and immune cell infiltration (macrophages and T cells) underscores BP3’s potential dual role in both cartilage degeneration and immune modulation. BP3 exposure might not only exacerbate cartilage damage directly but also influence immune responses, thereby amplifying inflammation and accelerating OA progression. As studies on OA continue to explore therapeutic strategies, such as pharmacological agents targeting the immune system or regenerative treatments aiming to repair cartilage, it is crucial to consider how environmental factors like BP3 may affect both immune responses and cartilage integrity. This aligns with earlier findings that chronic inflammation, driven by immune cells such as macrophages and T-cells, plays a crucial role in OA pathogenesis.41–43 Furthermore, the interaction between BP3 and the PI3K-Akt pathway, particularly through its impact on immune pathways, suggests a mechanism by which BP3 exposure could enhance OA severity. For instance, alterations in macrophages composition and activity in the joint could lead to increased secretion of pro-inflammatory cytokines, further promoting cartilage degradation and joint inflammation.44,45 These findings highlight the importance of considering environmental factors like BP3 in the broader context of immune regulation and inflammatory diseases.

One of the novel contributions of our study is the molecular docking analysis, which demonstrated strong interactions between BP3 and AREG. AREG (amphiregulin) is known for its involvement in cellular growth and repair mechanisms, particularly in the context of inflammation.46,47 BP3’s interaction with AREG could disrupt the downstream signaling of the PI3K-Akt pathway, resulting in an impaired response to inflammatory signals, thus contributing to OA pathogenesis. This interaction extends our understanding of how BP3 might influence cellular signaling in OA, not only through direct disruption of key pathways but also through specific protein interactions that could enhance inflammation and tissue damage. This extends previous research by suggesting that BP3 may exert its effects not only by direct pathway dysregulation but also through specific protein interactions. The novelty of our study lies in its comprehensive integration of toxicogenomics and molecular docking data, revealing the intricate molecular mechanisms by which BP3 contributes to OA pathogenesis. By focusing on the PI3K-Akt pathway and its key targets (AREG, ANGPT1, and ITGA4), we have provided new insights into how environmental toxins influence joint health. Additionally, the correlation between immune cell infiltration and pathway activity adds a new dimension to understanding OA’s immune-related aspects.

Despite the promising bioinformatics findings in this study, there are several limitations that should be acknowledged. First, due to the lack of experimental resources, we were unable to validate our results through laboratory techniques such as Western blotting, which would provide direct evidence of the differential expression and functional implications of the identified targets. Second, the bioinformatics analysis relied on publicly available datasets, which may introduce inherent biases or limitations related to sample quality and heterogeneity. Additionally, while the study focused on identifying key signaling pathways, the precise cellular mechanisms through which BP3 influences osteoarthritis pathology remain to be fully elucidated. Future experimental studies, including in vitro and in vivo models, are needed to confirm these findings and explore the mechanistic roles of BP3 in OA more comprehensively.

Conclusions

In conclusion, this study advances our understanding of BP3’s impact on OA. The disruption of the PI3K-Akt pathway, coupled with immune system involvement, offers potential targets for therapeutic intervention. Further studies are needed to explore the exact molecular mechanisms and validate these findings in vivo, providing a foundation for future therapeutic strategies aimed at mitigating the harmful effects of environmental toxins like BP3.

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Supplementary Material

Supplementary_materials_tfae199
supplementary_materials_tfae199.docx (204.8KB, docx)

Acknowledgments

Not applicable.

Contributor Information

Yongji Li, Department of Orthopaedics and Traumatology I, Heilongjiang University of Chinese Medicine Second Affiliated Hospital Hanan Branch, No. 26, Hanan Second Avenue, Pingfang District, Harbin 150060, China.

Geqiang Wang, Department of Orthopaedics and Traumatology III, The First Affiliated Hospital of Heilongjiang University of Traditional Chinese Medicine, No. 26, Hanan Second Avenue, Pingfang District, Harbin 150040, China.

Peiran Liu, Department of Orthopaedics and Traumatology I, Heilongjiang University of Chinese Medicine Second Affiliated Hospital Hanan Branch, No. 26, Hanan Second Avenue, Pingfang District, Harbin 150060, China.

Lin Zhang, Department of Geriatrics, Heilongjiang University of Chinese Medicine Second Affiliated Hospital Hanan Branch, No. 26, Hanan Second Avenue, Pingfang District, Harbin 150060, China.

Hai Hu, Department of Orthopaedics and Traumatology I, Heilongjiang University of Chinese Medicine Second Affiliated Hospital Hanan Branch, No. 26, Hanan Second Avenue, Pingfang District, Harbin 150060, China.

Xiangjun Yang, Department of Orthopaedics and Traumatology I, Heilongjiang University of Chinese Medicine Second Affiliated Hospital Hanan Branch, No. 26, Hanan Second Avenue, Pingfang District, Harbin 150060, China.

Hongpeng Liu, Department of Orthopaedics and Traumatology I, The Second Affiliated Hospital of Heilongjiang University of Traditional Chinese Medicine, No. 411, Gogol Street, Nangang District, Harbin 150000, China.

Author contributions

Yongji Li wrote the manuscript. Geqiang Wang, Peiran Liu, Lin Zhang, Hai Hu, and Xiangjun Yang analyzed the data and produced the figures. Hongpeng Liu reviewed and edited the manuscript.

Funding

Not applicable.

Conflict of interest statement

All authors declared that there was no conflict of interest.

Data availability

The data utilized in this study were sourced from the GEO database, accessible at https://www.ncbi.nlm.nih.gov/geo/. The corresponding accession numbers are: GSE55457, GSE12021, and GSE55235.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplementary_materials_tfae199
supplementary_materials_tfae199.docx (204.8KB, docx)

Data Availability Statement

The data utilized in this study were sourced from the GEO database, accessible at https://www.ncbi.nlm.nih.gov/geo/. The corresponding accession numbers are: GSE55457, GSE12021, and GSE55235.

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