Insulin resistance (IR), long overlooked as an independent risk factor, currently affects approximately 51% of the global population, with its prevalence continuing to rise in both developed and developing countries (Fazio et al., 2024). IR plays a central role in the development of non-communicable diseases such as type 2 diabetes and cardiovascular disorders (Goh et al., 2022). Epidemiological investigations of IR are essential for assessing disease burden and guiding evidence-based public health interventions and clinical decision-making. However, systematic screening and preventive strategies for IR remain lacking in the general population (Chiefari et al., 2021). As a result, IR has been referred to as a “silent epidemic” and has emerged as one of the most critical public health issues of the 21st century (Hernández-Valdez et al., 2023).

The etiology of IR is multifactorial, with obesity recognized as a major modifiable risk factor. Additionally, IR may result from medication use (e.g., glucocorticoids, antiretroviral drugs, and oral contraceptives), disorders of lipid metabolism, genetic defects in insulin signaling (type A IR), or autoimmune responses involving insulin receptor-blocking antibodies (type B IR) (Chockalingam et al., 2021).

IR is a key pathogenic component in a variety of metabolic diseases, including type 2 diabetes, and is defined as a reduced responsiveness of insulin-targeted tissues to physiological insulin levels (Armutcu and McCloskey, 2024). It is characterized by impaired glucose uptake and metabolism in skeletal muscle and adipose tissue, inadequate suppression of hepatic gluconeogenesis, and uncontrolled lipolysis in adipose tissues (Rivas and Nugent, 2021). Consequently, IR contributes to the development of type 2 diabetes (Elkanawati et al., 2024), metabolic syndrome (Tahapary et al., 2022), and ischemic stroke, and is closely associated with poor prognosis (Fan et al., 2024). Numerous studies have also linked IR to alterations in cardiovascular structure and function, such as myocardial hypertrophy and ventricular remodeling, which are key features in the pathogenesis of diabetic heart disease (DHD) (Li et al., 2020). These findings underscore the urgent need to investigate the pathophysiological mechanisms underlying IR and to develop effective therapeutic strategies.

The gut microbiota (GM), often considered an overlooked organ system, has garnered increasing attention in recent years (Ago et al., 2018). The human gastrointestinal tract harbors trillions of microorganisms, including bacteria, fungi, and viruses, with bacteria constituting the majority (Ahlawat et al., 2021). The gut microbiota is diverse yet relatively stable, with a shared core microbiome dominated by two major phyla: Bacteroidetes and Firmicutes (Zhou et al., 2020). The microbial community comprises over 114 bacterial species and weighs approximately 1–2 kg, earning it the designation of the “second genome” of the human body (Fassarella et al., 2021). The gut microbiota plays a vital role in maintaining human health through its involvement in nutrient absorption, energy metabolism, immune regulation, and maintenance of the intestinal barrier (Liu et al., 2023; Qiu et al., 2022). Beneficial gut bacteria can also exert immunosuppressive effects by modulating host immune responses (Fan and Pedersen, 2021).

Dysbiosis of the gut microbiota has been implicated in the pathogenesis of various diseases beyond the gastrointestinal tract, including metabolic disorders, cardiovascular diseases, and neurological conditions (Yang et al., 2023). For instance, gut microbiota composition is closely linked to hypertension (Wang et al., 2022), with pathogenesis involving complex interactions along the metabolite-immune axis and the microbiota-gut-brain axis. Increasing evidence suggests that this axis also contributes to the regulation of sleep behavior and may play a pivotal role in sleep disorders (Isticato, 2023).

Moreover, specific microbial taxa, such as Bifidobacterium and Akkermansia, have been positively correlated with improved insulin sensitivity. Akkermansia strengthens the intestinal mucus layer and upregulates mucin gene expression, thereby reducing the translocation of lipopolysaccharide (LPS) into the circulation—a process known to exacerbate IR and diabetes-related complications (Li et al., 2023). In obese individuals, alterations in gut microbial composition are closely linked to IR, with Bifidobacterium abundance often inversely associated with IR severity (Aljuraiban et al., 2023). Additionally, the gut microbiota can influence host metabolism by modulating bile acid metabolism, increasing levels of lithocholic acid (LCA), and producing succinate, further contributing to the amelioration of IR. These findings suggest that gut microbes, through diverse mechanisms, profoundly influence host metabolic homeostasis and play an essential role in improving IR.

In recent years, therapeutic strategies targeting gut microbiota modulation have demonstrated promising efficacy and relatively few side effects, positioning the microbiota as a potential intervention point for IR management. However, the roles and mechanisms of gut microbiota-derived metabolites in the context of IR remain insufficiently explored. Network pharmacology, which integrates drug-target-disease interactions within biological networks, offers a valuable framework for unraveling the molecular mechanisms of complex diseases. This approach facilitates the rapid identification of key bioactive components and therapeutic targets. In the present study, we applied network pharmacology to systematically investigate the metabolic transformation of gut microbiota-derived compounds and to elucidate the molecular mechanisms by which they influence the development of IR. The overall research workflow is illustrated in Figure 1.

Insulin resistance (IR) is a common and complex metabolic disorder that has emerged as a major global health concern. It is characterized by diminished cellular sensitivity to insulin, leading to impaired glucose uptake and utilization, and consequently elevated blood glucose levels. Globally, the prevalence of IR continues to rise steadily; approximately 1 in 11 adults has diabetes, with type 2 diabetes mellitus (T2DM) accounting for 90% of the cases (Zheng et al., 2018). Alarmingly, IR is no longer confined to adults—it is increasingly observed in children and adolescents, compounding the long-term health burden (Jia et al., 2024). More importantly, IR not only contributes directly to the onset and progression of T2DM but also serves as a shared pathological basis for several metabolic disorders, including cardiovascular diseases, nonalcoholic fatty liver disease (NAFLD), and polycystic ovary syndrome (PCOS) (Lee et al., 2022). These complications markedly impair quality of life and impose significant economic burdens on healthcare systems. Therefore, the identification of effective therapeutic strategies to mitigate the impact of IR is of paramount importance.

Emerging evidence suggests that modulation of gut microbiota composition and abundance holds promise as a therapeutic approach for IR. This bidirectional regulation encompasses both the influence of host behaviors on the gut microbiota and the impact of microbial modulation on host metabolic parameters. For instance, a high-fiber diet can enhance the abundance of short-chain fatty acid (SCFA)-producing bacteroidales while reducing proinflammatory bacteria, thereby decreasing intestinal monosaccharide (e.g., fructose, galactose) accumulation and improving insulin sensitivity (Sonnenburg and Sonnenburg, 2014). Physical exercise promotes microbial diversity and has been shown to alleviate IR (Allen et al., 2018). Additionally, adequate sleep and stress management modulate gut microbiota-derived metabolites along the gut-brain axis, thereby enhancing insulin responsiveness (Zhao et al., 2022).

Conversely, targeted microbiota interventions can also improve metabolic outcomes. Supplementation with Alistipes indistinctus significantly reduces hepatic triglyceride accumulation and fasting glucose levels in IR mouse models (Semo et al., 2024). Akkermansia muciniphila, a mucin-degrading bacterium, enhances gut barrier integrity, reduces endotoxin translocation, and stimulates GLP-1 secretion, collectively contributing to improved insulin signaling (Depommier et al., 2019).

Network pharmacology, rooted in systems biology and multi-omics integration, facilitates the construction of drug-target-disease networks to elucidate the molecular mechanisms of therapeutic agents. Its ability to systematically predict drug targets and efficacy, identify novel target-pathway associations, and support precision medicine makes it an invaluable tool in drug discovery and disease modeling (Nogales et al., 2022). To uncover key targets and metabolites in IR treatment, we constructed a comprehensive “disease-gene-gut microbiota-metabolite” interaction network using data from public databases.

Protein–protein interaction (PPI) analysis identified IL6, JUN, and PPARG as hub genes in IR, each functioning through distinct yet interconnected mechanisms: IL6 mediates inflammation, JUN is involved in oxidative stress signaling, and PPARG regulates lipid metabolism. IL6, a prototypical proinflammatory cytokine, activates the JAK/STAT3 pathway, inducing SOCS3 expression in adipose and hepatic tissues. SOCS3 inhibits tyrosine phosphorylation of insulin receptor substrate-1 (IRS-1), thereby disrupting PI3K/Akt signaling and reducing insulin sensitivity (Senn et al., 2002). JUN (c-Jun), a component of the AP-1 transcription factor complex, is activated via the JNK pathway under oxidative stress or high-fat dietary conditions. It promotes inflammatory gene expression and lipogenesis while impairing GLUT4 translocation, thus exacerbating insulin resistance in adipose tissue and the liver (Hirosumi et al., 2002). PPARG plays a pivotal role in lipid metabolism by promoting adipocyte differentiation, enhancing adiponectin secretion, and reducing lipotoxicity in peripheral tissues. Moreover, PPARG suppresses NF-κB-mediated inflammation and improves glucose uptake in muscle and liver while indirectly modulating gut microbiota-derived metabolites to enhance insulin signaling (Ahmadian et al., 2013; Rangwala and Lazar, 2004). Collectively, these factors form an inflammation-metabolism-stress regulatory network, offering multiple points for therapeutic intervention in IR.

KEGG pathway enrichment analysis revealed that the IL-17 signaling pathway, Toll-like receptor (TLR) signaling pathway, and HIF-1 signaling pathway play crucial roles in IR regulation. The IL-17 pathway, activated by Th17 cell-derived IL-17A, stimulates the MAPK/NF-κB cascade, promoting the expression of proinflammatory cytokines (e.g., IL-6, TNF-α) in metabolic tissues. This leads to macrophage polarization toward the M1 phenotype and enhanced serine phosphorylation (but reduced tyrosine phosphorylation) of IRS-1, thereby inhibiting insulin signaling (Bapat et al., 2015; Zúñiga et al., 2010). The TLR pathway recognizes gut-derived endotoxins and free fatty acids, activating NF-κB and JNK via MyD88-dependent mechanisms. This not only triggers inflammatory responses and SOCS3 expression but also disrupts intestinal barrier integrity, exacerbating systemic inflammation and metabolic endotoxemia—conditions that are alleviated by TLR4 inhibition (Cani et al., 2007). HIF-1 signaling, induced by hypoxic adipose environments in obesity, upregulates glycolytic enzymes (e.g., LDHA) and angiogenic factors (e.g., VEGF), contributing to adipocyte hypertrophy and fibrosis. Simultaneously, HIF-1α promotes lipid synthesis by inhibiting mitochondrial oxidative phosphorylation, thereby aggravating lipotoxicity and IR (Halberg et al., 2009). These pathways converge into an interrelated network of inflammation, metabolism, and hypoxia, offering multidimensional therapeutic entry points.

Among the identified substrates, cholesterol, chlorogenic acid, and rutin emerged as key metabolites. Cholesterol modulates IR via liver X receptor (LXR)-mediated reverse cholesterol transport, enhancing ABCA1/ABCG1 expression to prevent macrophage lipid accumulation while suppressing SREBP-1c-driven lipogenesis. In contrast, cholesterol oxidation products exacerbate IR via ER stress and NF-κB activation, indicating that their inhibition may preserve β-cell function and reduce hepatic steatosis. Chlorogenic acid improves IR by activating the AMPK/PGC-1α axis, enhancing mitochondrial metabolism, suppressing gluconeogenic enzymes (PEPCK, G6Pase), and fortifying intestinal mucosal integrity, thereby reducing endotoxin leakage and systemic inflammation (Horton et al., 2002). In an in vitro study conducted by Onyango (2018), hepatocytes and adipocytes cultured in vitro were stimulated with cholesterol, resulting in the activation of downstream NF-κB and JNK pathways of the Toll-like receptor 4 (TLR4) signaling cascade. Concurrently, phosphorylation levels of IRS-1/Akt were reduced, and GLUT4 expression was downregulated, indicating that cholesterol induces insulin resistance through TLR4-mediated activation of multiple stress response pathways. Similarly, research by Radin et al. (2008) demonstrated that knockout of TLR4 or treatment with TLR4 inhibitors (e.g., TAK-242) in adipocytes significantly reduced the expression of cholesterol-induced proinflammatory cytokines and restored insulin signaling activity, suggesting a negative correlation between the TLR4 pathway and the development of insulin resistance.

In an in vivo animal study, Ye et al. (2021) investigated the effects of chlorogenic acid (CGA) on obesity and related metabolic endotoxemia, as well as its association with gut microbiota alterations and insulin regulation. Oral glucose tolerance tests (OGTT) and insulin tolerance tests (ITT) were performed, alongside measurements of inflammatory and gut barrier function markers. The composition of the gut microbiota was analyzed using 16S rRNA high-throughput sequencing. The results showed that CGA suppressed high-fat diet (HFD)-induced weight gain and fat accumulation in mice, independent of food intake, indicating improved glucose homeostasis and reduced insulin resistance. Moreover, CGA decreased plasma lipopolysaccharide (LPS) levels and inhibited the expression of TLR-4, TNF-α, IL-1β, and MCP-1 in the liver and epididymal adipose tissue, thereby alleviating low-grade inflammation and enhancing insulin sensitivity. In addition, CGA increased the abundance of short-chain fatty acid (SCFA)-producing bacteria in the gut, improved gut barrier function, and reduced LPS translocation into the bloodstream. Fecal microbiota transplantation experiments further demonstrated that mice receiving microbiota from the HCGA group exhibited reduced body weight and fat mass, along with improved insulin sensitivity and glucose tolerance.

Zhang’s research team identified cholesterol, chlorogenic acid, and rutin as key metabolites through metabolomic screening and analyzed their co-occurrence with 21 gut microbial taxa using the GutMDisorder database. The results revealed that in HFD-fed mice, rutin increased the abundance of Akkermansia muciniphila, activated the aryl hydrocarbon receptor (AHR) signaling pathway, and promoted the production of the tryptophan-derived metabolite indole-3-acetic acid (IAA). These effects collectively suppressed the hepatic TLR4/NF-κB inflammatory pathway (targeting IL-6) and downregulated lipid synthesis-related genes (Scd-1, Fasn, Acaca). The findings suggest that rutin alleviates IR-related metabolic disturbances through a “microbiota-metabolite-host” axis (Ye et al., 2021).

Furthermore, Eggerthella lenta was identified as a key microbiota in the M-S-M-T network. This species transforms host-derived bile acids into secondary bile acids, which activate intestinal FXR and TGR5 receptors to suppress hepatic gluconeogenesis, promote GLP-1 secretion, and enhance β-cell function. Its metabolites also inhibit the TLR4/NF-κB pathway, reduce adipose macrophage infiltration, and lower proinflammatory cytokine levels, ultimately restoring insulin sensitivity (Paik et al., 2022).

Despite the promising role of the gut microbiota in the treatment of insulin resistance (IR) revealed in this study, several limitations should be acknowledged. First, the gut microbiota data utilized in this work were derived from the gutMGene database, which is primarily based on fecal samples. Although such data provide a valuable reference, they may not fully reflect the actual composition of intestinal microbiota compared to biopsy-derived samples, and are subject to considerable inter-individual variability. As a result, the constructed network may carry certain biases, and the reliability of the microbial data should be further validated using experimental approaches such as fecal microbiota transplantation (FMT), 16S rRNA sequencing, and metagenomic analysis.

Moreover, this study mainly focused on IR itself, whereas the roles of gut microbiota and their metabolites in IR-related complications, such as hypertension and hyperlipidemia, remain underexplored. Future investigations should place greater emphasis on these aspects.

To enhance the robustness of the findings, future studies should integrate network pharmacology with multi-omics approaches—including metagenomics and metabolomics—to establish a more comprehensive regulatory network. Furthermore, systematic validation through animal experiments and clinical trials is essential to clarify the mechanisms by which gut microbiota contribute to the regulation of IR and its associated metabolic disorders.

In this study, we employed network pharmacology approaches to elucidate the regulatory mechanisms by which the gut microbiota contributes to the pathogenesis of insulin resistance (IR). Three hub genes—IL6, JUN, and PPARG—were ultimately identified as potential therapeutic targets for IR. These genes correspond to key pathological aspects of IR: inflammatory regulation (IL6), stress-related signaling (JUN), and lipid metabolic balance (PPARG), providing distinct avenues for targeted intervention.

By constructing the microbiota-substrate-metabolite-target (M-S-M-T) network, we revealed that these three hub genes are closely associated with 10 gut microbiota metabolites, 10 microbial substrates, and 21 Gut microbiota. Among these, cholesterol, chlorogenic acid, and rutin emerged as key compounds that improve IR and its complications through mechanisms including lipid metabolism regulation, mitigation of oxidative stress, and modulation of microbiota-host interactions. For example, inhibiting intestinal cholesterol absorption has been shown to alleviate hepatic steatosis and contribute to the amelioration of IR, highlighting a mechanistic axis of therapeutic relevance.

Additionally, KEGG enrichment analysis identified six major signaling pathways implicated in IR pathophysiology: the IL-17 signaling pathway, Toll-like receptor (TLR) signaling pathway, HIF-1 signaling pathway, NOD-like receptor signaling pathway, TNF signaling pathway, and VEGF signaling pathway. Notably, IL-17, TLR, and HIF-1 signaling pathways play pivotal roles in reshaping the inflammatory microenvironment, responding to metabolic endotoxemia, and mediating hypoxia-induced metabolic imbalance, respectively. These three pathways collectively form an interrelated inflammation–metabolism–hypoxia regulatory network. Targeting key nodes within this network—such as the IL-17 receptor, TLR4, or HIF-1α—may offer multi-dimensional therapeutic strategies for IR and its associated complications.