Obesity, diabetes, and CKD are highly prevalent, often occurring simultaneously, and significantly increase the incidence and mortality of cardiovascular disease. The mechanisms of these four disease states are also closely intertwined, with multidirectional relationships, common risk factors, and shared therapeutic targets. Given the complex interactions between these diseases, the American Heart Association (AHA) recently proposed a new comprehensive health disorder known as the Cardiovascular-Kidney-Metabolic Syndrome (CKM) (Ndumele et al., 2023). This syndrome expands on the traditional concept of cardio-renal syndrome (Cardiorenal Syndrome, CRS), emphasizing the central role of metabolic risk factors in the interplay between heart and kidney damage (Savira et al., 2020; Young and Eknoyan, 2024) In recent years, the incidence of CKM Syndrome has significantly increased, becoming one of the major diseases threatening public health (Young and Eknoyan, 2024). The syndrome is characterized by the coexistence of multiple diseases that interact, exacerbate conditions, and increase treatment complexity (Savira et al., 2020). It has a close association with other diseases such as coronary artery atherosclerosis, chronic kidney disease (CKD), obesity, hypertension, and hyperlipidemia (Cosentino et al., 2023). These diseases have shared pathogenic mechanism, and research on these shared pathways is crucial for understanding the pathogenesis of CKM Syndrome and identifying effective treatment strategies (Cosentino et al., 2023). For the current treatment of CKM, renin-angiotensin system inhibitors and sodium-glucose cotransporter 2 inhibitors can slow kidney disease progression in most CKD patients and reduce heart failure complications. Nonsteroidal mineralocorticoid receptor antagonists like finerenone and glucagon-like peptide-1 receptor agonists like semaglutide also provide cardiorenal benefits, with semaglutide effectively reducing body weight (Zhu et al., 2025). However, there is insufficient evidence supporting efficacy for the CKM syndrome spectrum (such as early metabolic abnormalities) (Cortés-Camacho et al., 2024; Vaduganathan et al., 2024), so it is urgent to develop cheap, accessible and common drugs for CKM.

Due to the complex etiology of Cardiovascular-kidney metabolic syndrome, which involves multiple organs including the heart, kidneys, adipose tissue, and liver, there is currently no animal model that can fully simulate this syndrome. The current model studies of CKM mice exhibit the following major shortcomings. Most models only simulate single metabolic abnormalities (such as hypertension or obesity) (Kennedy et al., 2010; Dragoljevic et al., 2021), making it difficult to fully replicate the multi-system disease characteristics of CKM. For example, models using only HFD (high-fat diet) lack stable renal impairment phenotypes, while chronic kidney disease models often lack indicators of metabolic disorders (Carvalho et al., 2024). Current models fail to adequately simulate cardiorenal interactions, such as the low co-occurrence rate of cardiac diastolic dysfunction and renal fibrosis (Valero-Muñoz et al., 2021), and lack critical pathological features like vascular endothelial dysfunction. Meanwhile, We observed the feasibility advantages of the classic HFPEF model: HFD + L-NAME “two-hit” HFPEF model (Schiattarella et al., 2019), in which L-NAME, a nitric oxide synthase (NOS) inhibitor, reduces NO production by inhibiting endothelial NOS (eNOS), leading to elevated blood pressure and hemodynamic disturbances, and is often combined with a high-fat diet (HFD) to construct HFpEF models. Additionally, its impact on renal function and structure has received significant attention. For example, L-NAME can significantly increase serum creatinine and urea levels by inhibiting NO production, indicating decreased glomerular filtration rate and tubular damage (Ragab et al., 2021). L-NAME causes interstitial fibrosis, glomerulosclerosis, and thickening of the vascular wall, which are structural changes consistent with the pathological features of chronic kidney disease (CKD) (Prince et al., 2020). It has been proven that this model shows significant responses to CKM-targeting drugs such as SGLT2 inhibitors (e.g., empagliflozin) (Levin et al., 2020; Shi et al., 2024; Herrington et al., 2025), Therefore, we utilized HFD + L-NAME model to establish CKM mice model in this study.

Currently, with the rapid development of bioinformatics, network pharmacology based on large databases has become a powerful tool for detailing the mechanisms of complex drug systems from the molecular to the pathway level. Network pharmacology integrates multidisciplinary technologies such as systems biology, polypharmacology, molecular network data, bioinformatics, and computer simulations, making it highly suitable for analyzing targets and corresponding compounds or herbs involved in multiple diseases (Lee et al., 2024; Zhai et al., 2025). Many studies have used network pharmacology methods to reveal the mechanisms by which drugs affect diseases (Yang et al., 2022). This approach has become a promising method for accelerating drug research and development (Li et al., 2023). However, there is currently no systematic network pharmacology study on CKM, and reports identifying drugs through intersecting targets between clinical syndromes are also few. In this study, reverse network pharmacology was applied to analyze CKM-related gene/protein networks for potential therapeutic targets, which were then validated for efficacy and safety in animal experiments. The flowchart of this study is shown in Figure 1.

This study, starting from the pathophysiological mechanisms and disease progression of CKM, identified common targets through disease screening, followed by the selection of core targets and subsequent KEGG and GO enrichment analyses. The potential drugs were inferred from these common targets, and experiments were designed to validate them. In addition, this study systematically explored a novel “two-hit” mice model for CKM and then validated the therapeutic potential of BBR for CKM. The results showed that HFD + L-NAME can establish a stable CKM mice model. BBR significantly improved cardiac function, renal function, and fibrosis through multi-target effects. These findings provided new experimental evidence for the intervention of this complex syndrome.

Cardiovascular-Kidney Metabolic Syndrome (CKM) is a significant global health concern, associated with high morbidity and mortality rates and placing a substantial burden on healthcare systems (Savira et al., 2020; Kim et al., 2025). Over the past 20 years, the disease burden related to metabolic disorders has increased by 49.4%, making it a crucial risk factor for chronic kidney disease (CKD) and cardiovascular disease (CVD) (Xu et al., 2025). The treatment of CKM involves a multi-target, comprehensive management process, with coordinated interventions in cardiovascular, renal, and metabolic aspects. Several medications, such as sodium-glucose cotransporter 2 (SGLT-2) inhibitors and glucagon-like peptide-1 (GLP-1) receptor agonists, have been proven to improve CKM prognosis (Giugliano et al., 2022; Urbanek et al., 2023). However, poor patient adherence to multiple medications is a major barrier to effective treatment (Lim et al., 2023). Consequently, identifying effective therapeutic strategies to mitigate the adverse effects of CKM is of paramount importance. In this study, to explore the key targets and metabolites for CKM treatment, we integrated public databases and constructed a “target-compound-herb” network. This integration proved to be instrumental in pinpointing the crucial targets and metabolites linked to CKM.

The PPI network identified IL-1β, TNF-α, and IFN-γ as hub genes involved in the mechanism of CKM. IL-1β is a key driver of adipose tissue inflammation and systemic low-grade inflammation. In obese individuals, the expression of the IL1B gene in visceral adipose tissue is significantly elevated. It promotes the development of insulin resistance and metabolic syndrome by activating the NLRP3 inflammasome and NF-κB signaling pathways (Menini et al., 2020; Chen et al., 2023). IL1B also directly leads to myocardial fibrosis and tubulointerstitial damage in the kidneys by activating nuclear factor κB (NF-κB) and promoting the TGF-β signaling pathway. In chronic kidney disease (CKD) models, elevated IL1B levels are associated with glomerulosclerosis and proteinuria progression. Moreover, its positive correlation with angiotensin II (Ang II) further exacerbates cardiorenal crosstalk injury (Lei et al., 2019; de Alcantara Santos et al., 2021). Interestingly, although IL1B expression is significantly elevated in the visceral adipose tissue of obese patients, its levels are not directly correlated with diabetes status, suggesting that IL1B may independently initiate metabolic inflammation, separate from diabetes (Rakotoarivelo et al., 2018).

TNF-α is a classic pro-inflammatory cytokine secreted by adipose tissue, immune cells, and others, playing a central role in obesity, insulin resistance, and metabolic disorders (Sethi and Hotamisligil, 2021). TNF-α directly causes insulin resistance in skeletal muscle and adipose tissue by inhibiting the tyrosine phosphorylation of insulin receptor substrate 1 (IRS-1) and activating the IKK and JNK pathways (Bu et al., 2020). Additionally, TNF-α interacts with SGLT2 (sodium-glucose cotransporter 2), promoting vascular inflammation and endothelial dysfunction via the NADPH oxidase-angiotensin II pathway, thereby accelerating atherosclerosis (Mroueh et al., 2024). In cardiovascular diseases (such as myocardial infarction) and acute kidney injury (AKI), TNF-α exacerbates organ damage by promoting cardiomyocyte apoptosis and renal tubular epithelial cell necroptosis. Clinical data show that elevated TNF-α levels are significantly associated with mortality in patients with cardiorenal syndrome (Mavrakanas et al., 2017; Gergely et al., 2025). However, TNF-α inhibition may worsen cardiovascular risk in heart failure patients (Shanmugam et al., 2016; Rolski et al., 2023).

IFN-γ is a pro-inflammatory cytokine whose levels are elevated in patients with obesity and metabolic syndrome (MetS). For the kidneys, IFN-γ, in concert with APOL1 gene expression, can induce pyroptotic angiopathy in renal endothelial cells, accelerating the progression of chronic kidney disease (CKD) (Juliar et al., 2024). For the heart, activation of the IFN-γ signaling pathway in cardiomyocytes is associated with an age-related heart failure phenotype, characterized by metabolic reprogramming (such as inhibition of oxidative phosphorylation) and enhanced inflammatory responses (Ashour et al., 2023). In a nephrotoxic nephritis (NTN) model, anti-IFN-γ antibodies can reduce renal interstitial fibrosis (Kim et al., 2022).

KEGG enrichment analysis revealed that cholesterol metabolism, lipid and atherosclerosis, and the HIF-1 signaling pathway are closely associated with the development of CKM. Dysregulation of cholesterol metabolism plays a crucial role in atherosclerosis, metabolic inflammation, and renal dysfunction (Cortés-Camacho et al., 2024; Wang K et al., 2024). Cholesterol accumulation in renal tubular epithelial cells is closely related to glomerulosclerosis and tubulointerstitial fibrosis (Rampanelli et al., 2018; Yang et al., 2020). Abnormal renal lipid metabolism, such as cholesterol crystal deposition in renal tubules, can activate the renin-angiotensin system (RAS), promoting hypertension and renal fibrosis, thereby forming a vicious cardiorenal cycle (Agrawal et al., 2018; Handelsman et al., 2024). Inhibiting HMG-CoA reductase to lower LDL cholesterol can also reduce renal inflammation and oxidative stress (Park et al., 2017), and reducing remnant cholesterol can significantly improve the prognosis of CKM patients (Ding et al., 2025).

The HIF1α (hypoxia-inducible factor 1α) pathway has a complex pathophysiological link with CKM. HIF1α is a core regulator of cellular responses to hypoxia, but its activation in chronic metabolic diseases (such as diabetes and obesity) may exacerbate oxidative stress and mitochondrial dysfunction (Packer, 2020; Iacobini et al., 2022). In a mouse podocyte ablation model, HIF1α knockout can alleviate glomerulosclerosis and collagen deposition (Baumann et al., 2016). However, in chronic hypoxic or metabolically disordered states, persistent activation of HIF1α leads to fibrosis, inflammation, and organ dysfunction. For example, HIF1α-deficient vascular smooth muscle cells can significantly reduce vascular remodeling and macrophage infiltration (Qi et al., 2019; Xiao et al., 2024). In summary, HIF1α acts as both an adaptive response regulator and a pathogenic driver in CKM, with its effects highly dependent on the disease stage, tissue type, and metabolic environment.

Cardiovascular disorders, kidney disease, and diabetes are major health concerns that sharing common pathological mechanisms (Sebastian et al., 2024). Current research on CKM primarily focuses on clinical studies, examining specific drugs to improve the prognosis of the syndrome. However, fundamental investigations into its underlying mechanisms remain limited. In terms of basic research, CKM currently lacks a well-established model. Traditional HFD or diabetes models can only simulate metabolic-related diseases, with cardiac and renal involvement appearing later (Dragoljevic et al., 2021) The model induced by unilateral nephrectomy plus a high-sugar, high-fat, and high-salt diet for 12 weeks is the closest to the CKM phenotype (Carvalho et al., 2024). It can simulate chronic renal insufficiency combined with metabolic disorders, effectively mimicking the late-stage conditions of CKM. However, there are also drawbacks, such as high modeling costs and the inability to reflect early changes in metabolic syndrome of the heart and kidneys. Therefore, developing more economical and comprehensive CKM models remains an important direction for future research. This study is the first to utilize the classic heart failure with preserved ejection fraction (HFpEF) “two-hit” model to simulate CKM pathogenesis. It successfully reproduced renal function decline, insulin resistance, hypertension, cardiac diastolic dysfunction, and renal and cardiac fibrosis, providing new evidence for the CKM animal model.

In recent years, berberine has demonstrated significant potential in the treatment of cardiovascular diseases, kidney diseases, and metabolic-related disorders. Research in the field of cardiovascular diseases has shown that berberine possesses a range of therapeutic effects, including anti-heart failure, anti-arrhythmia, cholesterol reduction, inhibition of vascular smooth muscle proliferation, anti-platelet aggregation, and anti-inflammatory actions (Wang et al., 2015; Cookson, 2021; Abudureyimu et al., 2023; Hou et al., 2023; Song and Chen, 2021). For instance, in atherosclerosis models, berberine inhibits hepatic lipid synthesis enzymes (such as HMG-CoA reductase), promotes reverse cholesterol transport, and reduces serum total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), and oxidized low-density lipoprotein (ox-LDL). It also decreases aortic plaque formation and improves endothelial function (Tan et al., 2020). In ischemia-reperfusion models, berberine alleviates oxidative stress, autophagy, and inflammatory responses, thereby improving cardiac function after myocardial infarction (MI) and reducing cardiomyocyte apoptosis (Qing et al., 2018; Tian et al., 2023). Moreover, in the “two-hit” HFpEF model, berberine has been shown to mitigate myocardial diastolic dysfunction by modulating Drp1-mediated mitochondrial fission and Ca2+ homeostasis, which corroborates our findings (Abudureyimu et al., 2023).

Berberine has been shown to exert significant protective effects against kidney injury. It reduces serum creatinine and blood urea nitrogen levels, mitigates renal inflammation, and alleviates renal fibrosis (Yu et al., 2019). A meta-analysis revealed that berberine significantly improved renal function indicators (such as BUN and SCR) and inflammatory factors (IL-6 and TNF-α) in animal models of diabetic nephropathy (Hu et al., 2022). Additionally, berberine can lower blood glucose levels and reduce proteinuria (Yang et al., 2024). In chronic kidney disease (CKD) models, berberine modulates the gut microbiota by increasing the abundance of butyrate-producing bacteria and reducing the levels of uremic toxin-producing bacteria. It also inhibits the production of gut-derived uremic toxins, such as p-cresyl sulfate and trimethylamine N-oxide, thereby ameliorating the progression of chronic kidney disease (Pan et al., 2023).

Berberine plays a crucial role in regulating carbohydrate and lipid metabolism. Clinical studies have shown that berberine can reduce blood glucose levels and enhance systemic insulin sensitivity in patients with metabolic syndrome (Yu et al., 2019; Ilyas et al., 2020). In terms of lipid metabolism, berberine compounds (containing berberine, oryzanol, and vitamin B6) significantly lower serum triglycerides (TG) and LDL-C levels in rats with hyperlipidemia induced by a high-fat diet, and inhibit hepatic fat accumulation (Li et al., 2016). The mechanisms underlying these effects are primarily attributed to berberine’s activation of the AMPK pathway, which improves insulin resistance (IR) (Geng et al., 2016), and the AMPK/SIRT1 signaling pathway, which promotes adipose tissue browning and energy expenditure (Xu et al., 2021; Li et al., 2022, p. 3). Moreover, in diet-induced hyperglycemic mouse models, berberine enhances pancreatic β-cell function, significantly increasing insulin secretion and lowering blood glucose levels (Zhao et al., 2021). Notably, in our study, BBR significantly improved glucose tolerance but did not significantly enhance insulin tolerance, suggesting that its mechanism of action may be similar to that of acarbose, focusing more on inhibiting glucose absorption rather than improving insulin sensitivity (Carvalho et al., 2024).

As a crucial consideration for clinical use, the toxicity of berberine varies with species and administration route. For example, its intraperitoneal LD50 is 23 mg/kg, while the oral LD50 is 329 mg/kg (Singh and Sharma, 2018). At therapeutic doses, berberine shows low systemic toxicity with no severe organ damage or lethal reactions (Li et al., 2020; Sun et al., 2023). However, high doses or long-term use may cause liver and heart damage in zebrafish (Sun et al., 2023). Common adverse reactions include mild gastrointestinal symptoms like constipation and diarrhea (Imenshahidi and Hosseinzadeh, 2019). In a clinical study, 34.5% of T2DM patients treated with 500 mg of berberine three times daily for 13 weeks reported gastrointestinal issues, possibly due to its effects on gut microbiota (Yin et al., 2008). Berberine may also inhibit cytochrome P450 enzymes or P-glycoprotein, affecting drug metabolism, so caution is needed when co-administering certain drugs to avoid cumulative toxicity (Li et al., 2020).

Although this study has revealed the potential of BBR in the treatment of CKM, several limitations need to be addressed. Network pharmacology interprets diseases and drugs through known and predicted gene targets. However, it cannot provide specific genetic associations or causality with diseases as biological informatics methods like WGCNA or Mendelian randomization can. In this study, reverse network pharmacology enriched potential drugs, including nicotine, which is a factor causing the issue. Additionally, biological systems exhibit high complexity and nonlinearity. Network pharmacology, through network algorithm analysis, may not deeply involve core targets in disease progression; instead, it may only identify downstream common targets. This limitation may restrict the development of network pharmacology. These shortcomings are being addressed through multi-omics integration, such as metabolomics and transcriptomics combined validation (Huang et al., 2024). New methods, such as dynamic network modeling and AI-driven intelligent algorithm optimization (Zhang et al., 2024), have been gradually improved. However, they still lack systematic solutions.

Despite the fact that the HFD + L-NAME model partially mimics the pathological features of CKM, it may not fully capture the complexity and heterogeneity of human CKM. For instance, the model does not account for the interplay between genetic and environmental factors associated with CKM, which may limit the extrapolation of the study results. Meanwhile, although BBR has demonstrated promising therapeutic effects in animal experiments, the validation at the cellular and molecular levels is relatively insufficient. For example, there is a lack of direct evidence from genetic knockout or pharmacological interventions for key signaling pathways regulated by BBR (such as HIF1-α, AMPK and PI3K/AKT). This shortfall restricts the in-depth understanding of its mechanisms of action.

Future research directions include conducting clinical trials of BBR for CKM to evaluate its safety and pharmacokinetic characteristics in CKM patients. Mechanism expansion should involve using single-cell sequencing technology to decipher the regulatory networks of BBR on specific cell types in the heart and kidney, such as fibroblasts and podocytes. Additionally, exploring the synergistic effects of BBR with existing drugs, such as SGLT2 inhibitors, could optimize comprehensive management strategies for CKM.

This study provides comprehensive evidence that the HFD + L-NAME model effectively simulates the complex pathological features of Cardiovascular-Kidney Metabolic Syndrome (CKM), including metabolic disorders, cardiac dysfunction, and renal fibrosis. Through reverse pharmacology and multidimensional experiments, we identified berberine (BBR) as a potential therapeutic agent for CKM. BBR demonstrated significant therapeutic effects by improving metabolic profiles, enhancing cardiac diastolic function, and reducing renal fibrosis in CKM mice. These findings highlight BBR’s multi-target mechanisms, which simultaneously address multiple pathological aspects of CKM.

The results of this study underscore the potential of BBR as a novel therapeutic candidate for CKM, offering a new direction for the treatment of this complex syndrome. Future research should focus on further elucidating the molecular mechanisms underlying BBR’s therapeutic effects, particularly through single-cell sequencing and multi-omics approaches. Additionally, clinical trials are warranted to evaluate BBR’s safety and efficacy in human patients with CKM. These efforts will contribute to the development of more effective and targeted therapies for CKM, ultimately improving patient outcomes.