Heart failure (HF) is a multifactorial syndrome in which structural or functional defects of the heart impair its pumping capacity and increase intracardiac pressures, triggering progressive hemodynamic alterations and clinical manifestations [1, 2]. With the aging population and the increasing burden of cardiovascular diseases, the global incidence of HF continues to rise, making it a major public health concern. The clinical manifestations of HF are diverse, ranging from asymptomatic left ventricular dysfunction to severe congestive symptoms such as dyspnea, fatigue, and fluid retention [3, 4]. HF not only severely impacts patients’ quality of life but is also associated with high mortality, high readmission rates, and a substantial economic healthcare burden.

HF is associated with extremely high morbidity and mortality. One study reported that the 5-year mortality rate after an HF diagnosis can reach 50%, comparable to many malignant tumors [5]. HF patients are frequently hospitalized, with approximately 50% readmitted within six months after discharge, creating a significant healthcare burden [6]. HF also leads to multi-system complications, including worsening renal function (cardiorenal syndrome), liver abnormalities, and cognitive dysfunction [7]. Notably, even subclinical HF (elevated B-type Natriuretic Peptide [BNP] without symptoms) is associated with an increased risk of death, comparable to that of overt HF [5]. Patients with heart failure frequently experience poor quality of life, and approximately 30–40% present with depressive or anxiety disorders, further compounding the disease burden [8].

Heart failure is identified through an integrated clinical and biochemical assessment, with BNP and its N-terminal fragment (NT-proBNP) serving as reliable biomarkers to differentiate cardiac from non-cardiac causes of dyspnea [9]. Echocardiography is the cornerstone for evaluating cardiac structure and function. Emerging techniques such as three-dimensional echocardiography and strain imaging have improved the detection rate of early cardiac dysfunction [10]. Cardiac magnetic resonance (CMR) offers unique advantages in assessing myocardial fibrosis, inflammation, and specific cardiomyopathies [10, 11]. Additionally, artificial intelligence-assisted electrocardiogram (ECG) analysis is beginning to be used for predicting HF risk and treatment response [12].

The gut microbiota has recently emerged as a key regulator in cardiovascular health and disease. As an interface between host and environment, the gut microbiome participates in metabolic homeostasis, immune regulation, and inflammatory responses [13, 14]. Studies show that the structure and function of the gut microbiota are influenced by multiple factors, including host genetics, diet, environment, and developmental stage, while also exhibiting significant stability and plasticity [15, 16]. Particularly during species adaptation to environmental changes (e.g., invasion pressure, high-altitude environments), the vertical transmission and functional synergy of specific core microbiota become key mechanisms [17].

In recent years, the association between the gut microbiota and cardiovascular diseases, particularly HF has become a research hotspot. HF patients often exhibit gut microbiota dysbiosis, characterized by a reduction in beneficial bacteria and an overgrowth of potentially harmful bacteria [18]. This dysbiosis exacerbates HF progression through multiple mechanisms, including abnormalities in metabolites [e.g., trimethylamine N-oxide (TMAO), short-chain fatty acids (SCFAs)], bacterial translocation due to impaired intestinal barrier integrity, and systemic inflammation and immune activation [19]. Furthermore, the gut microbiota is closely linked to HF risk factors such as hypertension, diabetes, and obesity [20]. Microbiota often exert key effects through metabolites. For instance, choline and carnitine are metabolized by gut microbes into trimethylamine (TMA), which is subsequently oxidized in the liver to TMAO. TMAO can promote atherosclerosis, platelet activation, and myocardial fibrosis, thereby worsening HF [19]. High TMAO levels are significantly associated with poor prognosis in HF patients [21]. SCFAs like butyrate and propionate, produced by microbial fermentation of dietary fiber, possess anti-inflammatory properties and help maintain intestinal barrier function. HF patients show a reduction in SCFA-producing bacteria (e.g., Roseburia, Faecalibacterium), potentially leading to immune dysregulation and myocardial inflammation [19, 22]. The microbiota also regulates bile acid metabolism. Secondary bile acids modulate cardiac energy metabolism and inflammation through the farnesoid X receptor (FXR) and G protein-coupled receptor (TGR5), and their imbalance is associated with HF [23].

Dapagliflozin, a sodium-glucose cotransporter 2 (SGLT2) inhibitor, was initially developed for treating type 2 diabetes mellitus (T2DM). However, recent studies have demonstrated its significant clinical benefits in HF treatment, regardless of diabetes status [24, 25]. Dapagliflozin (DAPA) has shown notable cardiovascular protective effects in several large randomized controlled trials. In the DAPA-HF trial, dapagliflozin significantly reduced the risk of the composite endpoint of cardiovascular death or worsening heart failure (hazard ratio [HR] 0.74) in patients with heart failure with reduced ejection fraction (HFrEF) [26, 27]. The DELIVER trial further confirmed that dapagliflozin is also effective in patients with heart failure with mildly reduced or preserved ejection fraction (HFmrEF/HFpEF), reducing the risk of the primary endpoint by 18% (HR 0.82) [28]. Moreover, the efficacy of dapagliflozin was consistent across patients of different ages, ethnicities, and baseline renal function statuses [29]. Notably, the reduction in the risk of hospitalization for heart failure with dapagliflozin was particularly significant, a finding validated in both HFrEF and HFpEF patients [28].

Recent research suggests that the benefits of dapagliflozin may extend beyond its glucose-lowering effects and be closely linked to the modulation of the gut microbiota [30]. The gut microbiota interacts with host organs through metabolites, forming bidirectional communication networks such as the “gut-kidney axis” and “gut-heart axis”, which influence disease progression [31]. However, studies investigating the impact of dapagliflozin on HF through the gut microbiota are still lacking.

In summary, numerous clinical studies have confirmed the significant efficacy of dapagliflozin in improving HF outcomes, but its underlying mechanisms have not been fully elucidated. Traditional views have primarily focused on its diuretic, glucose-lowering, and cardiac load-reducing effects. Systematic research on whether it exerts cardioprotective effects by modulating the gut microbiota and host metabolic networks is still lacking. Given the critical role of the gut-heart axis in the pathogenesis and progression of HF, this study integrates 16S rRNA sequencing and untargeted metabolomics technologies to comprehensively analyze the effects of dapagliflozin on the gut microbiota composition, plasma metabolic profile, and microbiota-metabolite interaction patterns in HF patients. The aim is to reveal the potential molecular mechanisms beyond its glucose-lowering effects and provide new theoretical foundations and intervention strategies for the precise treatment of heart failure.

Based on clinical samples, this study systematically analyzed the effects of dapagliflozin on the gut microbiota composition, plasma metabolic profile, and microbiota-metabolite correlations in patients with HF. The results demonstrated that dapagliflozin not only improved patients’ clinical biochemical parameters but also remodeled the gut microbial ecosystem by promoting the enrichment of specific beneficial bacteria (e.g., Akkermansia, Butyricicoccus), which was accompanied by significant alterations in the plasma metabolite profile. These findings suggest that dapagliflozin may exert cardioprotective effects beyond glucose-lowering in HF management through the “gut-heart axis” mechanism.

Gut microbiota dysbiosis has been recognized as a significant contributing factor in HF, with mechanisms involving inflammatory activation, abnormal energy metabolism, and impaired intestinal barrier function [32]. This study found that after dapagliflozin intervention, the phylum Verrucomicrobiota was significantly enriched, particularly the probiotic Akkermansia. Previous studies have indicated that this bacterium enhances intestinal barrier integrity by degrading the mucus layer and can produce anti-inflammatory mediators, thereby mitigating systemic inflammatory responses [33]. Concurrently, the increase in butyrate-producing bacteria such as Butyricicoccus suggests that dapagliflozin may enhance the production of SCFAs, which helps maintain immune homeostasis and myocardial energy metabolism [33]. In contrast, the bacteria enriched in control group patients (e.g., Phocaeicola, Lachnoclostridium) are often associated with amino acid fermentation and a pro-inflammatory environment, indicating that dapagliflozin induces a beneficial directional modulation at the microbiota level [34].

Metabolomics results revealed a significant distinction in the plasma metabolic profiles between the dapagliflozin group and the control group, involving multiple pathways such as amino acid, nucleotide, and steroid metabolism. Notably, the anti-inflammatory metabolite salicyluric acid and the energy metabolism-related metabolite O-phospho-L-threonine were significantly elevated in the dapagliflozin group, suggesting that the drug may improve HF status by enhancing anti-inflammatory and energy metabolism pathways. Meanwhile, metabolites enriched in the control group (N-group) patients, such as phospho-L-serine and 5-beta-androstane, are closely associated with disordered amino acid metabolism and imbalanced steroid metabolism, which aligns with the clinical characteristics of energy metabolism dysfunction and hormonal abnormalities in HF patients.

KEGG enrichment analysis further revealed that dapagliflozin intervention primarily affected pathways including amino acid metabolism, one-carbon metabolism, and steroid degradation. These pathways play crucial roles in maintaining myocardial energy supply and regulating cardiac remodeling [35, 36], suggesting that dapagliflozin may improve metabolic homeostasis in HF patients through metabolic reprogramming.

Microbiota-metabolite correlation analysis indicated that Akkermansia was significantly correlated with various key metabolites, suggesting it might be a key node mediating the “gut-heart axis” effects of dapagliflozin. For instance, Akkermansia showed a negative correlation with the anti-inflammatory metabolite salicyluric acid but a positive correlation with Dulcin, a metabolite related to artificial sweeteners. This implies that this bacterium may indirectly influence the metabolic status of HF patients by regulating carbohydrate and energy metabolites. This “microbiota-metabolite-host” interaction model provides a new perspective for explaining the multifaceted protective effects of dapagliflozin.

Our data point to a convergent mechanism whereby dapagliflozin is associated with (i) selective enrichment of barrier-supporting/SCFA-linked taxa (Akkermansia, Butyricicoccus) and (ii) circulating metabolite signatures indicative of improved amino-acid/one-carbon flux and steroid catabolism. Akkermansia can fortify the mucus layer and attenuate endotoxin leakage, thereby dampening systemic inflammation and neurohormonal activation—central drivers of HF progression—while butyrate-associated pathways favor immune homeostasis and mitochondrial efficiency in peripheral tissues. The parallel rise in O-phospho-L-threonine and salicyluric acid may reflect activation of threonine–glycine–serine and folate-dependent one-carbon cycles, which support nucleotide synthesis, redox balance, and cardiomyocyte energy metabolism. In contrast, control-enriched phospho-L-serine and 5-beta-androstane are compatible with amino-acid stress and maladaptive steroid signaling, both linked to adverse remodeling. Notably, L-rhamnose and epiandrosterone increases in the dapagliflozin group further suggest shifts in microbial carbohydrate use and steroid turnover, consistent with the KEGG enrichment in carbon and steroid pathways. Taken together, these microbe–metabolite constellations provide a systems-level rationale for how SGLT2 inhibition could intersect the gut–heart axis by reducing inflammatory tone, stabilizing gut barrier function, and re-aligning myocardial substrate utilization, all of which are pertinent to HF pathogenesis. While these associations cannot establish causality, the directional coherence—beneficial taxa tracking with anti-inflammatory/energy-supportive metabolites and unfavorable taxa aligning with dysmetabolic markers—strengthens the biological plausibility of a gut-mediated component to dapagliflozin’s cardiometabolic profile. Future work integrating fluxomics, targeted SCFA/bile-acid panels, and interventional microbiome designs [e.g., diet, pre/probiotics, or Fecal microbiota transplantation (FMT)] could test these mechanistic links prospectively. Clinically, dapagliflozin has been proven in several large-scale randomized controlled trials to significantly reduce the risk of cardiovascular death and rehospitalization in HF patients [37]. This study further supplements its potential microecological and metabolomic mechanisms, providing clinical evidence for a multidimensional “drug-microbiota-metabolism-host” regulatory framework. However, this study has several limitations. First, the limited sample size and single-center design may affect the generalizability of the results. Second, the cross-sectional design necessitates that causal relationships be further validated through longitudinal follow-up and animal experiments. Additionally, the dynamic changes in microbiota and metabolic pathways under long-term dapagliflozin intervention require more in-depth investigation.

Our findings are consistent with emerging evidence that SGLT2 inhibitors exert broad cardiometabolic effects beyond glucose lowering [38, 39]. For example, Albulushi et al. [40] directly compared Glucagon-Like Peptide-1 (GLP-1) receptor agonists and SGLT2 inhibitors in patients with HFpEF and diabetes, demonstrating that SGLT2 inhibitors confer significant benefits on both metabolic remodeling and myocardial function. This aligns with our observation that dapagliflozin is associated with favorable shifts in gut microbiota and metabolomic profiles, suggesting that part of its cardioprotective action may involve systemic metabolic reprogramming. Incorporating such evidence strengthens the rationale that dapagliflozin could influence HF outcomes through multiple, interlinked pathways.

The concept of “precision therapy” in HF remains largely theoretical, but our findings provide preliminary clues for translation. Identification of specific microbial signatures, such as the enrichment of Akkermansia and Butyricicoccus, raises the possibility of using these taxa as non-invasive biomarkers for monitoring therapeutic response. Similarly, metabolite shifts—including elevations in salicyluric acid and O-phospho-L-threonine—may serve as surrogate indicators of anti-inflammatory or energy metabolic pathways activated by dapagliflozin. In the future, integration of microbiome and metabolomic profiling could contribute to risk stratification, early intervention strategies, and personalization of SGLT2 inhibitor therapy. Although immediate bedside application is limited, these mechanistic insights build a rationale for microbiota-targeted adjuncts (e.g., probiotics, dietary fiber supplementation) that might synergize with pharmacological treatment in HF management.

Clinically, these findings hold meaningful therapeutic implications for the management of HF. By demonstrating that dapagliflozin reshapes both the gut microbiota and the circulating metabolome, this study provides biological evidence that its cardiovascular benefits may partly derive from modulation of the gut–heart axis. Such remodeling could translate into improved myocardial energy efficiency, reduced systemic inflammation, and enhanced neurohormonal stability—pathophysiological targets that are inadequately addressed by conventional therapies.

Importantly, these microbe–metabolite signatures may serve as accessible biomarkers for patient stratification and treatment monitoring. For example, the enrichment of Akkermansia and Butyricicoccus or elevations in metabolites such as salicyluric acid and O-phospho-L-threonine may indicate a favorable biological response to dapagliflozin. Incorporating these indicators with established clinical parameters (e.g., NT-proBNP, renal function, and inflammatory indices) could enable an integrated “gut–metabolic” profiling system to guide therapy decisions.

From a precision-treatment perspective, this work suggests a feasible translational framework: (1) baseline microbiome–metabolome profiling to define each patient’s gut–metabolic phenotype; (2) SGLT2 inhibitor initiation according to guideline-directed medical therapy; (3) adjunctive interventions tailored to the microbial pattern—such as prebiotic or probiotic supplementation for SCFA deficiency or Akkermansia depletion; and (4) longitudinal assessment of microbial and metabolomic dynamics to optimize drug efficacy and minimize adverse events. In the future, combining dapagliflozin with microbiota-targeted approaches may constitute a new direction for individualized, multi-pathway modulation of HF pathophysiology.

While direct causal verification remains to be established, these findings open a clinically relevant avenue toward precision medicine, linking pharmacologic SGLT2 inhibition with microecological homeostasis and systemic metabolic remodeling. Prospective validation in multicenter, multi-omics trials will be essential to translate these mechanistic insights into therapeutic algorithms applicable to daily clinical practice.

Although our study provides novel insights into the gut–heart axis under dapagliflozin treatment, several limitations should be acknowledged. First, this was a single-center study conducted in a defined regional population. Differences in diet, lifestyle, and comorbidities across geographic and ethnic groups may influence both gut microbial composition and metabolic profiles, potentially limiting the generalizability of our findings. Second, the sample size was modest, which may reduce statistical power for detecting subtle associations and increase the risk of type II errors. Therefore, while the observed microbial and metabolomic alterations are informative, they should be interpreted with caution. Future multi-center studies with larger, more diverse cohorts are needed to validate whether the patterns identified here are broadly representative of the wider heart failure population. Beyond validation, future work should also address the long-term and mechanistic dimensions of dapagliflozin’s gut–metabolic effects. Longitudinal studies incorporating serial sampling are warranted to determine whether the observed microbiome and metabolomic remodeling is sustained over months or years, and how these temporal changes correlate with cardiac function and clinical outcomes. Integrating time-resolved microbiome–metabolome data with echocardiographic and biochemical indicators could reveal predictive signatures of therapeutic response or resistance.

In parallel, translating these multi-omics insights into practice will require developing feasible, standardized panels of microbial taxa and circulating metabolites for clinical use. These signatures could support personalized risk stratification, guide adjunctive nutritional or microbiota-targeted interventions, and refine precision treatment algorithms for HF. Multi-center interventional trials combining dapagliflozin with microbiota-modulating strategies—such as pre/probiotic supplementation or dietary optimization—represent promising avenues to confirm causality and optimize therapeutic benefit.

Another limitation is that baseline differences in certain laboratory parameters—such as inflammatory markers and lipid profiles—were observed between groups. These disparities may act as potential confounders influencing gut microbiota composition and metabolomic signatures. We did not perform statistical adjustment for these variables due to the modest sample size, and therefore residual confounding cannot be excluded. Future studies with larger cohorts and stratified or multivariable analyses will be required to disentangle drug effects from baseline clinical differences. As a cross-sectional study, our analysis captures associations between dapagliflozin exposure and gut–metabolite profiles at a single time point, without establishing temporal or causal relationships. Future longitudinal and interventional studies are needed to verify these associations.

Future research could focus on the following directions: (1) Integrating metagenomics and metabolomics to delineate a comprehensive “gut-heart axis” network under dapagliflozin intervention; (2) Utilizing FMT and germ-free animal models to validate the role of key microbiota (e.g., Akkermansia) in HF; (3) Exploring combined intervention strategies, such as probiotic or dietary fiber supplementation, to determine if synergistic effects with dapagliflozin exist, thereby providing precise microecological strategies for HF treatment.

Based on integrated 16S rRNA sequencing and untargeted metabolomics, this study demonstrates that dapagliflozin significantly modulates the gut microbiota composition and plasma metabolomic profile in patients with heart failure. Dapagliflozin promoted the enrichment of beneficial genera such as Akkermansia and Butyricicoccus, while reducing potentially harmful taxa. Concurrent shifts in plasma metabolites involved key pathways including amino acid metabolism, one-carbon metabolism, and steroid degradation. Correlation analyses further revealed significant microbiota-metabolite interactions, supporting the possibility that dapagliflozin contributes to cardioprotective benefits partly via gut–heart axis modulation These findings provide novel mechanistic insights into the pleiotropic benefits of dapagliflozin beyond glucose-lowering and support the potential of microbiota-targeted strategies in the precision treatment of heart failure.

The datasets used and analyzed during the current study are available from the corresponding author on reasonable request.

ZF and XDX conceived and designed the research. YZ and YL performed the experiments. QQL, QLZ, WJZ, CM and ZZ analyzed the results and data. YZ and YL wrote, ZF and XDX revised the manuscript. All authors contributed to editorial changes in the manuscript. All authors read and approved the final manuscript. All authors have participated sufficiently in the work and agreed to be accountable for all aspects of the work.

This study was approved by the ethics committee of The People’s Hospital of Chizhou City (approved No. 2023-KY-18). We certify that the study was performed in accordance with the 1964 declaration of HELSINKI and later amendments. Written informed consent to participate in this study was provided by the participants’ legal guardian/next of kin.

This study was supported by 2023 Chizhou City major science and technology special project and Anhui Provincial Key Research and Development Program (Grant No. 2022e07020058).

The authors declare no conflict of interest.

During the preparation of this work the authors used Deepseek-R1 in order to check spell and grammar. After using this tool, the authors reviewed and edited the content as needed and takes full responsibility for the content of the publication.