Unraveling the Systems Biology of Curcumin: A Mini-review of its Anti-diabetic Potential through Network Pharmacology

Abstract

Diabetes mellitus (DM) is a complex metabolic disease marked by persistent hyperglycemia and a range of related complications, stemming from intricate molecular mechanisms such as oxidative stress, chronic inflammation, and disrupted insulin signaling pathways. Current treatments typically target a single molecule, which limits their effectiveness against the complex, interconnected pathways of DM. Curcumin, a naturally occurring polyphenolic compound extracted from Curcuma longa, has emerged as a promising candidate due to its wide-ranging biological activities and ability to influence multiple molecular pathways involved in DM progression. This mini-review employs a systems biology and network pharmacology approach to explore the diverse molecular targets and key signaling cascades modulated by curcumin, including the AGE-RAGE, PI3K-Akt, TNF, and JAK-STAT pathways. By integrating computational predictions with findings from laboratory and clinical studies, we provide insights into curcumin’s ability to reduce oxidative stress, suppress inflammation, and enhance insulin sensitivity through its multi-targeted actions. Additionally, we discuss the therapeutic relevance of these mechanisms in improving blood glucose regulation and minimizing DM complications, as evidenced by outcomes from clinical investigations. The review also addresses curcumin’s low bioavailability and highlights the emerging role of nano-formulation techniques in enhancing its pharmacokinetic properties. Finally, we identify key gaps in the current research landscape and emphasize the need for comprehensive clinical trials that reflect curcumin’s complex pharmacological profile. Overall, this systems-based evaluation supports curcumin’s potential as a valuable multi-target therapeutic agent that could complement current DM treatments and contribute to better patient care.

Introduction

Diabetes mellitus (DM) is a long-term metabolic disorder marked by consistently elevated blood glucose levels, primarily due to insufficient insulin production, impaired insulin function, or a combination of both factors. The prevalence of DM has surged globally, with current statistics showing that around 589 million adults aged between 20 and 79 years are affected, equating to roughly 1 in every 9 adults worldwide. This figure is expected to escalate to approximately 853 million by the year 2050, highlighting the critical need for effective strategies in prevention and disease management [1]. DM significantly contributes to global morbidity and mortality, with an estimated 3.4 million DM-related fatalities reported in 2024. Additionally, the financial strain of managing the disease is immense, with healthcare costs surpassing USD 1 trillion annually [2]. Alarmingly, over 80% of individuals with DM live in low- and middle-income countries, where limited access to adequate healthcare services and treatments remains a substantial obstacle [1, 3].

Although pharmacological treatments for DM have significantly advanced, several challenges persist in current management strategies. Many antidiabetic medications, including both insulin and oral glucose-lowering agents, often become less effective over time due to the gradual deterioration of pancreatic β-cell function [4, 5]. Additionally, these treatments are frequently associated with undesirable side effects such as hypoglycemia, weight gain, and gastrointestinal issues, which can adversely affect patient compliance and overall quality of life [5, 6]. The complexity of treatment protocols, the need for regular blood glucose monitoring, and the issue of clinical inertia—where timely adjustments or intensifications in therapy are delayed—further complicate effective DM management. Despite following recommended therapeutic guidelines, many individuals with DM continue to face a high risk of developing serious complications, including cardiovascular diseases, kidney damage, nerve disorders, and other long-term health issues [4, 5]. These limitations emphasize the urgent demand for innovative and multi-faceted treatment strategies capable of targeting the diverse and complex pathways involved in DM progression.

Curcumin, the main bioactive compound in turmeric (Curcuma longa), has been traditionally used in Ayurveda and Chinese medicine to treat inflammatory conditions, digestive issues, skin diseases, and wounds due to its strong antioxidant and anti-inflammatory properties [7, 8]. In recent decades, curcumin has gained significant scientific attention for its therapeutic potential in chronic diseases, particularly DM. Studies have shown that curcumin modulates key molecular pathways in DM, including oxidative stress, chronic inflammation, insulin resistance, and pancreatic β-cell dysfunction [7, 9-11]. In animal models of DM, especially those induced by streptozotocin (STZ), curcumin administration (30–300 mg/kg) significantly lowered fasting blood glucose and HbA1c levels, improved insulin sensitivity, and prevented body weight loss. Similarly, in type 2 diabetic mellitus (T2DM) mice, dietary curcumin enhanced glucose tolerance and confirmed its antihyperglycemic effects [10]. Clinical evidence further supports these findings, with meta-analyses and systematic reviews of randomized controlled trials showing that curcumin supplementation significantly reduces fasting blood glucose and HbA1c in patients with T2DM, suggesting its value as an adjunct therapy [12, 13]. Its antidiabetic effects are primarily attributed to its ability to reduce oxidative stress and inflammation—key contributors to DM progression [7, 14]. Furthermore, curcumin enhances insulin sensitivity by modulating pathways involved in glucose metabolism, as reflected in improved HOMA-IR and insulin responsiveness in clinical trials [10, 15]. Although curcumin’s low oral bioavailability poses a challenge, novel delivery systems such as nano-curcumin have shown improved metabolic outcomes, including better insulin regulation and a reduction in DM-related complications like foot ulcers [7].

Due to the intricate and multifaceted nature of DM, there is an urgent demand for a holistic, systems-based approach that brings together insights from bioinformatics, network pharmacology, and clinical data. Network pharmacology, in particular, has proven to be a powerful strategy in DM research, capable of mapping drug-target-disease relationships across multiple biological layers. This approach addresses DM pathology through multi-component and multi-target mechanisms—an advantage over traditional monotherapies. For instance, natural compounds such as polyphenols, flavonoids, and alkaloids have been shown to synergistically inhibit enzymes like α-amylase and α-glucosidase, improve β-cell function, and modulate critical pathways such as AMPK and PI3K/Akt involved in insulin signaling [16]. By leveraging databases and molecular docking techniques, overlapping gene targets relevant to both T2DM and candidate therapeutics can be identified and validated [17, 18]. Studies using this strategy have revealed, for example, that Jiangtangwan (JTW) alleviates insulin resistance via the SRC/PI3K/Akt pathway [19]. Furthermore, combining network pharmacology with metabolomics allows the development of personalized therapies addressing hypoglycemia, hypertension, and dyslipidemia concurrently, showcasing its potential in precision medicine [20]. Conventional reviews tend to concentrate on discrete molecular pathways or clinical findings, often missing the broader therapeutic scope of compounds like curcumin.

In contrast, this review applies a systems biology lens to investigate how curcumin interacts within the complex molecular landscape of T2DM, encompassing genes, proteins, and metabolic circuits. Utilizing tools from network pharmacology along with bioinformatics platforms, target prediction methods, and protein–protein interaction (PPI) networks, we identify novel targets, critical regulatory genes, and key signaling pathways influenced by curcumin [7, 10]. This comprehensive strategy enhances the understanding of curcumin’s diverse biological activities and supports its development as a potential multi-target agent for managing T2DM. Differing from previous studies that often highlight individual mechanisms or general pharmacodynamics, our review presents a systems-level integration that aligns molecular mechanisms with clinical relevance, uncovers previously unexamined therapeutic opportunities, and addresses existing gaps in the literature. By drawing on data from molecular research, animal studies, and clinical trials, this work offers a cohesive overview of curcumin’s role in DM treatment and informs future directions in drug discovery and translational research [11]. Fig. 1 further illustrates this context by depicting the global impact of DM, the shortcomings of current treatment modalities, and the emerging potential of curcumin within a systems pharmacology framework.

Fig. 1.

Global burden of DM, current treatment challenges, and the systems biology-based therapeutic potential of curcumin in DM management

Review Methodology

This mini review was conducted using a systems biology and network pharmacology framework to comprehensively explore the multi-target therapeutic potential of curcumin in the context of DM (Fig. 2). The approach involved a structured process that integrated computational, preclinical, and clinical evidence to identify and analyze the molecular mechanisms through which curcumin may exert anti-diabetic effects.

Fig. 2.

Review methodology: a systems biology and network pharmacology-based framework to investigate the multi-target anti-diabetic potential of curcumin

Literature Search and Selection Criteria

This review was conducted using systems biology and network pharmacology framework to explore the multi-target therapeutic role of curcumin in DM. A comprehensive literature search was performed across PubMed, Scopus, and Google Scholar using combinations of keywords such as curcumin, diabetes mellitus, network pharmacology, systems biology, oxidative stress, inflammation, insulin resistance, insulin signaling, and nano-formulation. The search was restricted to studies published between 2000 and 2025 in English. Eligible articles included original in vitro, in vivo, and clinical research directly evaluating curcumin in DM-related pathways, as well as computational and network pharmacology studies that identified or predicted curcumin’s molecular targets in the context of DM. Systematic reviews and meta-analyses were also considered when they contributed mechanistic or translational insights. Articles were excluded if they were non-English, not related to DM, lacked experimental or computational evidence, or were duplicates. To minimize selection bias, two independent reviewers screened studies by title, abstract, and full text, and any discrepancies were resolved by discussion.

Bias Assessment and Evidence Hierarchy

To ensure reliability and transparency, all included studies were qualitatively assessed for methodological rigor. Preclinical studies were examined for design quality, including appropriate controls, replicates, and reproducibility. Clinical studies were evaluated based on trial design, including randomization, blinding, sample size adequacy, intervention duration, and the relevance of outcomes such as HbA1c, fasting glucose, insulin sensitivity, oxidative stress, and inflammatory markers. Computational studies were only considered if they used validated, publicly accessible databases and algorithms. A hierarchical framework was applied to weigh the strength of evidence, ranking meta-analyses and randomized controlled trials at the highest level, followed by observational cohort studies, in vivo animal models, in vitro studies, and computational predictions at the lowest level. This systematic assessment ensured that stronger forms of evidence were prioritized in drawing mechanistic and therapeutic conclusions.

Target Identification and Network Construction

To specifically evaluate curcumin’s molecular interactions in DM, bioinformatics resources were applied in a structured workflow. Potential curcumin targets were predicted using SwissTargetPrediction, SuperPred, BindingDB, and STITCH, which provided both experimentally validated and computationally inferred interactions. DM-associated genes and proteins were retrieved from GeneCards, DisGeNET, and OMIM by querying “diabetes mellitus” and refining the results to genes with high relevance scores or documented experimental validation. The overlapping targets between curcumin and DM-associated datasets were identified and used to build a curcumin–DM interaction network. Protein–protein interaction (PPI) networks were then generated using the STRING database with a high confidence score threshold (≥ 0.7). These networks were analyzed in Cytoscape, and hub genes were identified through CytoHubba using topological parameters such as degree, betweenness, and closeness centrality. This approach highlighted critical molecular nodes through which curcumin may exert its therapeutic actions in DM.

Pathway and Functional Enrichment Analysis

The intersecting targets of curcumin and DM were further subjected to functional enrichment analysis. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed using DAVID, Enrichr, and ShinyGO. Statistically significant pathways were identified based on a cutoff of p < 0.05 with false discovery rate adjustment. Pathways particularly relevant to DM pathophysiology were prioritized, including AGE–RAGE signaling, which is linked to oxidative stress and β-cell apoptosis; PI3K–Akt signaling, which is central to insulin sensitivity and glucose uptake; TNF and JAK–STAT signaling, which mediate inflammation and insulin resistance; and AMPK signaling, which regulates glucose and lipid metabolism. By mapping the predicted targets onto these DM-specific pathways, the network pharmacology approach provided a mechanistic framework for understanding curcumin’s potential multi-target anti-diabetic effects.

Integration with Experimental and Clinical Data

Computational findings were validated against preclinical and clinical evidence to enhance credibility and translational value. In vitro studies on pancreatic β-cells and in vivo models of streptozotocin-induced DM were used to confirm curcumin’s antioxidant, anti-inflammatory, and insulin-sensitizing effects, consistent with computational predictions. Key hub genes such as TNF, IL6, and AKT1 identified in network analysis were cross-referenced with biomarkers measured in clinical trials, where curcumin supplementation was associated with improvements in glycemic control, insulin sensitivity, and reductions in inflammatory cytokines. Discrepancies between predictions and experimental findings were documented, especially those arising from variability in dosing strategies, short intervention durations, or curcumin’s known pharmacokinetic limitations. Emerging nano-formulation strategies were also considered, as they provide enhanced systemic absorption and may improve alignment between computational predictions and observed clinical outcomes.

Identification of Research Gaps

Finally, the review methodology was structured to identify key gaps in the existing literature. These included the limited number of long-term, large-scale randomized controlled trials, heterogeneity in curcumin formulations and dosing regimens, and the lack of validation of network-predicted targets in human populations. Moreover, while computational analyses provide valuable insights into curcumin’s potential multi-target actions, experimental confirmation in clinically relevant models remains insufficient. Addressing these gaps will require integrative approaches combining standardized computational pipelines, reproducible preclinical studies, and rigorously designed clinical trials to strengthen the evidence base for curcumin as a therapeutic strategy in DM.

Network Pharmacology of Diabetes

The development and progression of DM are driven by a highly complex interplay of genes, proteins, and signaling networks that collectively influence glucose homeostasis, insulin sensitivity, and inflammatory processes. Network pharmacology has emerged as a valuable tool for unraveling these intricate molecular relationships, facilitating the discovery of crucial therapeutic targets and regulatory pathways. Several keys signaling pathways have been identified as central contributors to DM pathophysiology, including the Advanced Glycation End Products-Receptor for Advanced Glycation End Products (AGE-RAGE) pathway, the phosphoinositide 3-kinase/protein kinase B (PI3K-Akt) pathway, the tumor necrosis factor (TNF) signaling pathway, and the Janus kinase-signal transducer and activator of transcription (JAK-STAT) pathway. The AGE-RAGE signaling axis plays a pivotal role in sustaining chronic inflammation and oxidative stress, processes that aggravate insulin resistance and accelerate DM-related complications by activating nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) and stimulating the production of pro-inflammatory cytokines [19, 21]. The PI3K-Akt pathway is fundamental to insulin signaling, promoting glucose transport and glycogen formation; disruptions in this pathway are strongly associated with insulin resistance in T2DM [19]. Additionally, Tumor Necrosis Factor alpha (TNF-α), a major pro-inflammatory cytokine, interferes with insulin receptor activity and intensifies inflammatory cascades, further impairing insulin sensitivity [21]. The JAK-STAT signaling pathway, known for regulating immune responses, has also been implicated in pancreatic β-cell dysfunction and autoimmune-mediated destruction, particularly in type 1 diabetes mellitus (T1DM) [19, 22].

Extensive network pharmacology studies, utilizing comprehensive datasets from resources such as MalaCards, DisGeNET, GeneCards, and STRING, have uncovered thousands of genes associated with DM and their intricate molecular interactions, enabling the development of detailed protein-protein interaction (PPI) networks. For example, one investigation identified more than 9,600 genes linked to T2DM and discovered 521 overlapping candidate targets shared with a traditional Chinese medicine formula, with key regulatory nodes such as SRC, PI3K, and AKT emerging as central components within the network [19]. Similarly, network-based analyses of natural bioactive compounds like resveratrol and fenugreek have highlighted critical hub genes, including Phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit alpha (PIK3CA), Signal Transducer and Activator of Transcription 3 (STAT3), and TNF, which play pivotal roles in both the progression and potential treatment of DM [22, 23]. Furthermore, functional enrichment analyses and KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway mapping consistently reveal that insulin signaling, inflammatory responses, and metabolic pathways are among the most significantly enriched processes within DM-related networks [19, 21]. Visualization platforms such as Cytoscape have proven instrumental in graphically representing these complex molecular interconnections, demonstrating a densely linked network where multiple biological pathways intersect. This network-based understanding reinforces the notion that DM is a multifaceted, systemic disorder, underscoring the potential benefits of multi-target therapeutic strategies that can simultaneously modulate several critical genes and pathways to achieve more effective disease management [19, 21, 22]. Fig. 3 demonstrates the critical role of network pharmacology in integrating multi-omics data to uncover hub genes and essential molecular interactions involved in disease mechanisms. By combining genomics, transcriptomics, proteomics, and metabolomics datasets, network pharmacology provides a systems-level understanding of complex biological processes. This approach facilitates the identification of key regulatory nodes and potential therapeutic targets that may otherwise remain undetected through conventional single-target analyses. This figure effectively illustrates how this integrative method can reveal the intricate molecular networks influenced by curcumin, offering valuable insights into its multi-target therapeutic potential in DM management.

Fig. 3.

The role of network pharmacology in integrating multi-omics data to identify hub genes and molecular interactions

Molecular Targets of Curcumin in DM

Curcumin’s therapeutic versatility stems from its ability to modulate a broad range of molecular targets, thereby exerting diverse pharmacological effects. Network pharmacology and bioinformatics studies have identified numerous curcumin-associated proteins across various disease conditions. For example, a network-based analysis in colorectal cancer revealed 30 potential targets, with AKT1, Epidermal Growth Factor Receptor (EGFR), and STAT3 identified as key hubs within pathways such as PI3K-Akt signaling and apoptosis regulation [24, 25]. Similarly, another study identified nine overlapping targets between curcumin and differentially expressed colorectal cancer genes—including DNA methyltransferase 1 (DNMT1), Proliferating Cell Nuclear Antigen (PCNA), Cyclin D1 (CCND1), and Matrix Metalloproteinase 3 (MMP3) which are involved in p53, NF-κB, and TNF signaling pathways [26]. Although centered on cancer, these findings have broader implications, as several of these targets, particularly AKT1 and STAT3, are known to regulate insulin signaling, inflammation, and oxidative stress—key processes in the pathophysiology of DM.

To explore curcumin’s relevance to DM specifically, researchers have leveraged bioinformatics tools such as SwissTargetPrediction, SuperPred, PharmMapper, and DrugBank to predict its protein targets. These predicted targets are systematically compared with DM-related genes sourced from databases like GeneCards and DisGeNET, allowing identification of shared nodes that may mediate curcumin’s antidiabetic effects [27]. Among the frequently overlapping targets are AKT1, TNF, and STAT3—proteins critically involved in insulin resistance, β-cell dysfunction, and chronic inflammation. This convergence highlights the mechanistic overlap between curcumin’s molecular interactions in different diseases and underscores its potential to modulate complex biological networks implicated in DM.

Additionally, the curcumin resource database has documented more than 190 molecular targets, reinforcing its capacity for widespread biological activity and multi-target engagement [28]. A visual summary—such as a Venn diagram or a tabulated comparison (Table 1)—clearly illustrates the intersection between curcumin’s predicted targets and DM-associated genes. These shared targets are involved in essential pathways governing glucose metabolism, oxidative stress, apoptosis, and inflammatory signaling. Such integrative analyses not only validate well-established mechanisms but also reveal novel targets for further experimental validation, deepening our understanding of curcumin’s systems-level pharmacological potential in the management of DM.

Table 1.

Shared Molecular Targets between Curcumin and DM-related Genes

Target Gene/Protein	Functional Role in Diabetes	References
AKT1	Central to insulin signaling and glucose uptake	[24, 27]
STAT3	Mediates inflammatory responses and β-cell function	[24, 27]
TNF	Pro-inflammatory cytokine promoting insulin resistance	[26, 27]
EGFR	Regulates cell proliferation and survival pathways	[24, 27]
CCND1	Cell cycle regulation, linked to β-cell proliferation	[26]
MMP3	Extracellular matrix remodeling, involved in diabetic complications	[26]

Functional Enrichment and Core Targets of Curcumin in DM

Key Pathways Modulated by Curcumin in DM

Curcumin demonstrates significant regulatory influence over multiple DM-associated signaling pathways, primarily by modulating inflammation, oxidative stress, and insulin signaling. Pathway enrichment analyses consistently identify its involvement in key molecular pathways such as AGE-RAGE, PI3K-Akt, TNF, and JAK-STAT, which play central roles in the pathogenesis of DM. These pathways are critically associated with insulin resistance, β-cell dysfunction, and chronic tissue damage.

For instance, curcumin has been shown to restore oxidative balance by activating the Nrf2-mediated antioxidant response, thereby protecting tissues such as the retina from oxidative stress-induced damage, including complications like diabetic retinopathy [29]. Additionally, functional annotation analyses reveal that curcumin significantly overlaps with genes involved in cytokine signaling and inflammation, consistent with its reported capacity to suppress pro-inflammatory mediators such as TNF-α and IL-6 (Interleukin-6) [30, 31]. These anti-inflammatory effects not only alleviate tissue injury but also enhance insulin sensitivity, supporting curcumin’s therapeutic potential in combating DM-related metabolic dysregulation.

Among the most enriched pathways are PI3K-Akt and AGE-RAGE, which are integral to maintaining glucose homeostasis, mediating insulin receptor signaling, and promoting cell survival under diabetic stress [32]. Curcumin also regulates crucial transcription factors such as PPARG (peroxisome proliferator-activated receptor gamma), a key regulator of glucose and lipid metabolism, further reinforcing its role as a multi-target agent against DM and related metabolic disorders [33].

AGE-RAGE pathway

The advanced glycation end-products (AGEs) and their receptor (RAGE) pathway are central to the pathophysiology of DM and its complications, establishing this axis as an attractive therapeutic target [34, 35]. Under chronic hyperglycemia, AGEs accumulate and engage RAGE, initiating cascades of oxidative stress and inflammatory signaling that promote vascular dysfunction, tissue injury, and fibrosis [36, 37]. Activation of this pathway triggers excessive reactive oxygen species (ROS) production, NF-κB–mediated inflammation, endothelial impairment, and extracellular matrix crosslinking, ultimately driving clinical outcomes such as albuminuria, retinopathy progression, neuropathy, arterial stiffness, and atherosclerosis. Experimental and genetic evidence further supports the causal involvement of AGE–RAGE signaling, as blocking this axis reduces vascular inflammation and atherosclerotic burden in preclinical models [38].

Despite strong biological plausibility, translation into therapies directly targeting AGE–RAGE signaling has produced inconsistent results. Aminoguanidine (pimagedine), an AGE formation inhibitor, initially showed promise by reducing proteinuria, but large trials such as ACTION were terminated due to inefficacy and safety issues, while smaller T1DM studies failed to confirm nephroprotection [39-41]. Alagebrium (ALT-711), an AGE crosslink breaker, improved arterial compliance in small, randomized studies and attenuated vascular stiffness in preclinical models, yet definitive outcome-driven trials in DM remain absent [42, 43]. Similarly, benfotiamine, which augments the thiamine pathway to divert glycolytic intermediates and reduce AGE precursors, has not consistently improved neuropathy or renal biomarkers in randomized trials, limiting its clinical utility [44, 45]. Beyond pharmacologic interventions, soluble RAGE (sRAGE) has been investigated as a biomarker due to its decoy receptor activity; however, associations with DM, cardiovascular disease, and mortality remain inconsistent across populations, restricting its application as a surrogate marker [46-48].

Compared with these mixed results, contemporary glucose-lowering agents demonstrate robust clinical efficacy through complementary mechanisms. Sodium–glucose cotransporter-2 inhibitors (SGLT2i) consistently reduce major adverse cardiovascular events, hospitalization for heart failure, and kidney disease progression, as demonstrated in EMPA-REG OUTCOME and CREDENCE [49, 50]. Likewise, glucagon-like peptide-1 receptor agonists (GLP-1 RAs), including liraglutide, improve glycemic control while lowering cardiovascular events in high-risk type 2 diabetes mellitus (T2DM) patients, as evidenced in the LEADER trial, with additional anti-inflammatory and endothelial benefits independent of direct RAGE modulation [51]. Thus, while the AGE–RAGE axis remains biologically compelling and early studies suggest benefits in intermediate vascular outcomes, safety concerns and lack of consistent event-level efficacy have precluded clinical adoption. Until well-powered outcome trials validate RAGE-targeted therapies, optimization of SGLT2i and GLP-1 RAs remains the most reliable approach to reducing vascular and renal complications linked to AGE–RAGE activation [49].

Curcumin has emerged as a promising modulator of the AGE–RAGE signaling axis. Research shows that it suppresses RAGE expression and alleviates AGE-driven cellular injury by enhancing PPARG activity and reducing oxidative stress [52, 53]. These actions help preserve the integrity of hepatic stellate cells and other metabolically active tissues that are particularly vulnerable to AGE-mediated damage. Beyond these effects, curcumin interferes with AGE-induced activation of inflammatory pathways such as JAK2/STAT3 and PI3K/AKT, while simultaneously strengthening antioxidant defenses through Nrf2 activation [52]. Collectively, these mechanisms contribute to reduced inflammation, oxidative injury, and fibrosis, positioning the AGE–RAGE pathway (Fig. 4) as an attractive therapeutic target and highlighting curcumin’s potential in developing novel interventions for DM and its complications [37, 52, 53].

Fig. 4.

AGE-RAGE pathway in DM treatment using curcumin

Comparative studies indicate that other polyphenols, including resveratrol and quercetin, also act on the AGE–RAGE axis by lowering oxidative stress, suppressing RAGE expression, and activating Nrf2-mediated protective pathways [54, 55]. While these compounds overlap mechanistically with curcumin, differences in pharmacokinetic profiles and affinities for RAGE-associated targets may account for variations in therapeutic outcomes. By contrast, standard antidiabetic drugs such as metformin primarily work through AMPK activation and improved insulin sensitivity rather than direct modulation of AGE–RAGE signaling [56]. Network pharmacology analyses further show that curcumin engages a broader multitarget interaction landscape compared with metformin, while maintaining notable similarities with other polyphenols [54-56]. This broader interaction network underscores curcumin’s distinctive multitarget therapeutic profile and supports its potential role in combinatorial strategies against AGE–RAGE–mediated diabetic complications.

PI3K-Akt pathway

The PI3K–Akt signaling pathway represents a fundamental mediator of insulin action, regulating glucose uptake, glycogen synthesis, and cellular metabolism. Its activation begins when insulin binds to its receptor, triggering phosphorylation of insulin receptor substrate-1 (IRS-1), which in turn activates phosphoinositide 3-kinase (PI3K). PI3K generates phosphatidylinositol (3,4,5)-trisphosphate (PIP3), facilitating Akt recruitment and activation. Activated Akt enhances translocation of GLUT4 to the cell surface, thereby increasing glucose uptake, while simultaneously suppressing hepatic glucose output, maintaining systemic glucose homeostasis [57, 58]. When this pathway is disrupted, insulin resistance and impaired glucose regulation ensue, making PI3K–Akt dysfunction a defining feature of T2DM and a critical therapeutic target [58, 59]. Beyond metabolic regulation, PI3K–Akt also modulates endothelial nitric oxide synthase (eNOS) activity, linking its impairment to vascular dysfunction. Clinical evidence highlights its indispensability: pharmacological inhibition of PI3K or Akt in oncology consistently produces hyperglycemia, as seen with alpelisib and related agents, which induce glucose dysregulation in over half of treated patients [60-63].

Several established antidiabetic agents exert their therapeutic benefits through modulation of this pathway. Exogenous insulin directly restores proximal insulin receptor–IRS–PI3K–Akt signaling, enabling reliable reductions in HbA1c, though long-term therapy carries risks of hypoglycemia and weight gain [64]. Metformin, traditionally associated with AMP-activated protein kinase (AMPK) activation, has also been shown to enhance IRS2–PI3K–Akt signaling in hepatic and muscle tissues, reinforcing its role in improving insulin sensitivity [65]. Thiazolidinediones (TZDs) act, similarly, increasing PI3K activity and Akt phosphorylation in adipose and skeletal muscle, effects that translate into clinical glycemic improvements despite adverse outcomes such as edema and weight gain [66]. Incretin-based therapies, particularly glucagon-like peptide-1 receptor agonists (GLP-1RAs), stimulate PI3K–Akt in pancreatic β-cells, promoting insulin secretion, β-cell survival, and vascular protection. These mechanisms underpin their ability to reduce HbA1c, support weight loss, and improve cardiovascular outcomes, as confirmed in large trials with liraglutide and semaglutide [67, 68].

Other drug classes provide complementary benefits. Sodium–glucose cotransporter-2 inhibitors (SGLT2i) primarily lower glucose through insulin-independent urinary excretion, with minimal direct effects on PI3K–Akt signaling. Nonetheless, emerging evidence suggests possible interactions with IGF-1R/PI3K signaling in renal tissues. Their substantial cardiovascular and renal outcome benefits, demonstrated in EMPA-REG OUTCOME, emphasize that effective DM management requires both restoration of PI3K–Akt activity and integration of alternative, insulin-independent strategies [49]. Collectively, these findings underscore that pharmacological modulation of PI3K–Akt signaling directly improves glycemic control, endothelial function, and vascular health. At the same time, the complementary efficacy of SGLT2i highlights the therapeutic value of a dual approach—reinforcing PI3K–Akt signaling while targeting independent pathways—to provide comprehensive metabolic and cardiovascular protection in patients with T2DM.

Curcumin exhibits promising modulatory effects on the PI3K–Akt pathway by enhancing insulin sensitivity and improving glucose utilization. Experimental studies demonstrate that curcumin activates the PI3K–Akt cascade in insulin-responsive tissues, thereby facilitating glucose uptake and restoring signaling balance disrupted in DM [19, 69]. These benefits are reinforced by its antioxidant and anti-inflammatory actions, which mitigate oxidative stress and chronic inflammation—both major contributors to insulin resistance. Importantly, curcumin promotes Akt phosphorylation, a pivotal step in maintaining pancreatic β-cell survival and function, thus supporting endogenous insulin secretion and improved glycemic control [70]. By targeting both peripheral insulin resistance and β-cell dysfunction, curcumin addresses two core defects in T2DM, highlighting its potential as a natural multitarget agent for improving metabolic health (Fig. 5).

Fig. 5.

PI3K-Akt pathway in DM treatment using curcumin

Comparative analyses reveal that curcumin’s effects on PI3K–Akt signaling share similarities with other dietary polyphenols while differing mechanistically from standard antidiabetic therapies. Resveratrol, for example, enhances Akt phosphorylation and GLUT4 translocation, improving insulin sensitivity in muscle and adipose tissue [71]. Quercetin also activates the PI3K–Akt pathway while suppressing oxidative stress and inflammation, thereby supporting β-cell viability and glucose tolerance [72]. In contrast, metformin—the most commonly prescribed drug—primarily acts through AMP-activated protein kinase (AMPK) activation, with only indirect influence on PI3K–Akt signaling [56]. Network pharmacology studies further indicate that curcumin’s multitarget profile overlaps more extensively with polyphenols such as resveratrol and quercetin than with metformin, reflecting its pleiotropic regulation of oxidative, inflammatory, and metabolic pathways [56, 71, 72]. This broad mechanistic footprint underscores curcumin’s distinctive therapeutic potential and suggests opportunities for synergistic strategies when combined with other natural compounds or conventional drugs in restoring PI3K–Akt balance in T2DM.

TNF pathway

The tumor necrosis factor (TNF) signaling pathway plays a critical role in the pathogenesis of T2DM by sustaining chronic inflammation and impairing insulin signaling. TNF-α, a pro-inflammatory cytokine secreted primarily by adipose tissue and immune cells, disrupts insulin action by promoting serine phosphorylation of insulin receptor substrate-1 (IRS-1), thereby inhibiting downstream PI3K–Akt signaling and reducing glucose uptake [73]. Elevated TNF-α levels also intensify oxidative stress and amplify inflammatory cascades, accelerating cellular injury and metabolic dysfunction characteristic of T2DM [73, 74]. Mechanistic studies in cell and animal models confirm that TNF-α induces IRS-1 serine phosphorylation, linking inflammatory stress with impaired glucose transport and endothelial dysfunction [75-78]. These findings establish biological plausibility for the TNF pathway as a therapeutic target in improving insulin sensitivity and mitigating complications associated with DM [79].

Clinical and epidemiological evidence further supports a contributory role for TNF signaling in adverse metabolic outcomes, though results vary. Cross-sectional and cohort studies consistently report higher circulating TNF-α in individuals with T2DM and associations with impaired glucose tolerance, vascular dysfunction, and incident neuropathy [80-82]. However, some prospective analyses suggest TNF-α alone is not an independent predictor of DM risk after accounting for confounders such as obesity and comorbidities, indicating that TNF-driven inflammation is one of several overlapping contributors. Interventional studies have produced mixed outcomes: small trials of etanercept in insulin-resistant or T2DM populations demonstrated modest improvements in insulin responsiveness but without consistent HbA1c reductions, and most were of short duration. Observational cohorts in inflammatory arthritis populations show lower DM incidence with anti-TNF therapy compared with conventional treatment, suggesting relevance of the pathway, but causality for metabolic benefit remains unproven [83, 84].

When compared with established therapies, TNF-targeted approaches currently fall short in terms of clinical efficacy and outcome evidence. Sodium–glucose cotransporter-2 inhibitors (SGLT2i) robustly reduce major adverse cardiovascular events, heart-failure hospitalization, and progression of kidney disease in high-risk T2DM patients, as demonstrated in EMPA-REG OUTCOME, CANVAS, and CREDENCE trials [49]. Similarly, glucagon-like peptide-1 receptor agonists (GLP-1 RAs) not only improve glycemic control and weight loss but also reduce cardiovascular events in large trials such as LEADER, with additional anti-inflammatory and endothelial effects that may indirectly intersect with TNF signaling. Collectively, TNF pathway activation provides a mechanistic bridge between inflammation, insulin resistance, and vascular complications, and preliminary interventional data suggest potential benefits. However, without large-scale, event-driven randomized trials demonstrating durable glycemic control and reductions in vascular endpoints, TNF-targeted therapy cannot yet be recommended over guideline-directed agents. At present, SGLT2i and GLP-1 RAs remain the most reliable therapeutic options for translating immunometabolic modulation into clinically meaningful cardiovascular and renal protection, while research into selective TNF-axis interventions continues [49].

Curcumin exerts potent anti-inflammatory effects, partly through the modulation of TNF-α signaling. Experimental studies demonstrate that curcumin downregulates TNF-α expression and inhibits the activation of NF-κB, a central regulator of pro-inflammatory gene transcription downstream of TNF-α [85]. By suppressing this pathway, curcumin reduces inflammatory stress in adipose and peripheral tissues, which in turn enhances insulin responsiveness [86]. In addition, curcumin interferes with TNF-α–induced signaling events that drive IRS serine phosphorylation, thereby preserving insulin receptor function and promoting glucose homeostasis [73, 85]. Through these combined mechanisms—attenuating cytokine production, blocking NF-κB activation, and protecting insulin signaling—curcumin demonstrates therapeutic promise as a natural intervention against inflammation-mediated insulin resistance. These effects (illustrated in Fig. 6) underscore their relevance as an adjunct candidate for anti-diabetic therapies targeting immune-metabolic regulation.

Fig. 6.

TNF pathway in DM treatment using curcumin

From a systems pharmacology perspective, curcumin’s modulation of TNF-α signaling mirrors the actions of other polyphenols while differing mechanistically from conventional antidiabetic drugs. For example, resveratrol reduces TNF-α expression and NF-κB activation in adipose and vascular tissues, thereby improving insulin sensitivity and limiting systemic inflammation [87]. Similarly, quercetin inhibits TNF-α–mediated inflammatory cascades, protecting pancreatic β-cells and mitigating cytokine-driven insulin resistance [88]. By contrast, thiazolidinediones such as pioglitazone suppress TNF-α activity indirectly via PPARγ activation rather than through direct interference with NF-κB signaling [89]. Comparative network pharmacology analyses reveal that curcumin’s multitarget interaction profile overlaps more closely with resveratrol and quercetin, as all three compounds concurrently modulate inflammation, oxidative stress, and insulin signaling [87-89]. This broad targetome highlights curcumin’s potential advantage in correcting immune-metabolic dysregulation, while also suggesting additive or synergistic therapeutic opportunities when combined with polyphenols or synthetic agents.

JAK-STAT pathway

The Janus kinase–signal transducer and activator of transcription (JAK–STAT) pathway plays a central role in regulating immune responses, inflammation, and metabolic signaling, making it highly relevant to the pathophysiology of DM. Upon cytokine stimulation, JAK kinases phosphorylate STAT transcription factors, which then translocate to the nucleus to regulate genes involved in inflammation, apoptosis, and cell survival. In DM—particularly in complications such as diabetic retinopathy and nephropathy—dysregulated JAK–STAT activation contributes to vascular injury and tissue damage through the upregulation of pro-inflammatory mediators like VEGF, thereby accelerating disease progression [90, 91]. Chronic activation of this pathway, driven by cytokines such as interferons, interleukins (e.g., IL-6), and leptin, promotes insulin resistance in liver, muscle, and adipose tissue, while simultaneously driving β-cell stress through enhanced inflammatory gene programs and MHC/HLA class I expression. Consequently, the JAK–STAT axis has been positioned as an immunometabolic nexus linking chronic inflammation to impaired insulin receptor signaling, altered adipocyte biology, and β-cell vulnerability, thus making it a promising therapeutic target for modulating immune-mediated metabolic dysfunction [92-95].

Preclinical and translational evidence supports the therapeutic potential of pharmacologic JAK inhibition in improving metabolic outcomes, though results remain context dependent. In diet-induced obesity and insulin resistance models, JAK inhibitors enhanced insulin sensitivity, reduced adipose tissue inflammation, and corrected hepatic and skeletal muscle insulin signaling defects. Human data, though limited, show parallel trends: in rheumatoid arthritis cohorts treated with JAK inhibitors such as tofacitinib and baricitinib, reductions in systemic inflammatory markers and modest improvements in glycated hemoglobin and insulin resistance indices have been reported. Most notably, a randomized, placebo-controlled phase 2 trial study demonstrated that daily baricitinib preserved β-cell function over 48 weeks in patients with recent-onset T1DM, providing direct proof-of-concept that JAK blockade can modify clinically relevant pancreatic outcomes [96-98]. These findings suggest that JAK–STAT modulation not only improves peripheral insulin sensitivity but may also confer protective effects on β-cell survival, highlighting its dual potential as an immunometabolic intervention.

Despite these promising signals, the safety profile of JAK inhibitors introduces caution in their application to DM management. These agents frequently increase circulating lipid concentrations, including total and LDL cholesterol, and large-scale safety trials have associated them with elevated risks of major adverse cardiovascular events and malignancies compared with TNF inhibitors, with the ORAL Surveillance program for tofacitinib offering the clearest example [99, 100]. Thus, any improvements in insulin sensitivity or β-cell preservation must be balanced against these long-term risks, particularly in populations already predisposed to cardiovascular disease. When compared with established therapies for T2DM, such as SGLT2 inhibitors and GLP-1 receptor agonists, which consistently reduce cardiovascular and renal outcomes in large randomized trials (e.g., EMPA-REG OUTCOME, LEADER), JAK inhibition remains an emerging, complementary strategy rather than a competing standard therapy [49, 94]. While modulation of the JAK–STAT pathway represents a compelling mechanistic target for immunometabolic intervention, its clinical translation in DM care requires more robust, DM-specific outcome trials to establish efficacy and safety beyond surrogate metabolic endpoints.

Curcumin has been shown to modulate the JAK-STAT signaling cascade, exerting both anti-inflammatory and cytoprotective effects. Evidence indicates that curcumin inhibits the phosphorylation of JAKs and STATs, thereby downregulating the transcription of inflammatory genes and preventing cytokine-induced β-cell apoptosis [93, 101]. This suppression of JAK-STAT activity not only lowers systemic inflammation but also preserves pancreatic β-cell function and insulin secretion, both of which are critical for maintaining glucose homeostasis. Moreover, curcumin’s modulation of this pathway parallels the mechanism of pharmaceutical JAK inhibitors, suggesting its potential as a natural complementary or alternative therapeutic option in DM management. By attenuating chronic inflammatory signaling and oxidative stress, curcumin contributes to stabilizing immune responses and reducing the risk of secondary diabetic complications. These findings highlight the therapeutic value of targeting the JAK-STAT axis and position curcumin (Fig. 7) as a promising natural agent for multi-target strategies in DM treatment [92, 102].

Fig. 7.

The JAK-STAT pathway in DM treatment using curcumin

From a systems pharmacology perspective, curcumin’s regulation of JAK-STAT signaling resembles the actions of other polyphenols while differing from standard antidiabetic drugs. For instance, resveratrol inhibits STAT3 phosphorylation and reduces pro-inflammatory cytokine production, thereby protecting against insulin resistance and β-cell dysfunction [103]. Similarly, quercetin suppresses IL-6–mediated STAT3 activation, leading to improved glucose tolerance and reduced systemic inflammation [104]. In contrast, conventional antidiabetic agents such as metformin influence this pathway indirectly, primarily through AMPK activation and subsequent modulation of inflammatory mediators rather than direct inhibition of JAK-STAT signaling [105]. Network pharmacology analyses further show that curcumin shares greater overlap with polyphenols like resveratrol and quercetin in targeting inflammatory kinases and transcription factors, while its multitarget effects set it apart from synthetic drugs [103-105]. This broader interaction profile underscores curcumin’s unique pharmacological advantage and suggests synergistic potential when combined with polyphenols or conventional therapies for optimized JAK-STAT axis modulation in DM management.

Key Genes Modulated by Curcumin in DM

At the molecular level, hub gene analysis has identified several critical targets through which curcumin exerts its antidiabetic effects. Network pharmacology studies consistently show that curcumin interacts strongly with central nodes such as AKT1, TNF, STAT3, and IL6—genes that form core components of protein-protein interaction (PPI) networks in DM [30]. These genes regulate insulin signaling, inflammation, oxidative stress, and β-cell survival, aligning with curcumin’s multi-target therapeutic profile. Interestingly, curcumin demonstrates its highest interaction affinity within the top-ranked cluster (MCODE1) of DM-associated PPI networks, suggesting a high likelihood of modulating densely connected, functionally significant gene modules [30].

AKT1 gene

AKT1 encodes a serine/threonine kinase central to the PI3K/AKT/mTOR signaling axis, which regulates glucose uptake, cell proliferation, and survival. Dysfunction in this pathway contributes to insulin resistance and DM complications such as nephropathy and cardiovascular disease [59, 106]. AKT1 influences critical downstream effectors like GSK3 and FOXO, impacting energy metabolism and insulin sensitivity [107]. Genetic variants of AKT1 have been linked to increased susceptibility to T2DM, reinforcing its role as both a therapeutic target and a biomarker [106].

Curcumin enhances AKT1 activity by promoting its phosphorylation, thereby improving insulin-mediated glucose uptake and countering inflammation and oxidative stress—key drivers of insulin resistance [59, 107]. Computational studies suggest that curcumin and its analogs stabilize AKT1’s active conformation through direct molecular interactions [108]. This activation also supports β-cell survival and proliferation, contributing to improved insulin production and glycemic control [109]. These multi-level interactions establish AKT1 as a pivotal mediator of curcumin’s antidiabetic action.

Curcumin’s modulation of AKT1 overlaps with other polyphenols but differs from conventional antidiabetic drugs. Resveratrol enhances AKT1 phosphorylation and promotes GLUT4 translocation, thereby improving glucose uptake and vascular function [71], while quercetin activates PI3K–AKT1 signaling and reduces oxidative stress, protecting β-cells and enhancing insulin sensitivity [110]. In contrast, metformin primarily targets AMPK and exerts only indirect effects on AKT1 activity [56]. Network pharmacology analyses indicate that curcumin, similar to resveratrol and quercetin, influences AKT1 along with upstream regulators and oxidative pathways, highlighting its advantage as a multitarget modulator that may be used synergistically with polyphenols or conventional therapies to optimize glycemic control [56, 71, 110].

TNF gene

The TNF gene, which encodes tumor necrosis factor-alpha (TNF-α), plays a critical role in driving inflammation-induced insulin resistance. TNF-α disrupts insulin signaling by inhibiting adipocyte differentiation and promoting serine phosphorylation of insulin receptor substrates, impairing insulin responsiveness [86]. Curcumin suppresses TNF-α expression and inhibits downstream pathways like NF-κB, JNK, MAPK, and PI3K/Akt, all implicated in DM pathology [111, 112].

In silico docking studies confirm curcumin’s direct binding affinity for TNF-α, suggesting its potential as a natural TNF-α inhibitor [111]. Curcumin derivatives with improved bioavailability have been developed to overcome pharmacokinetic challenges, showing enhanced TNF-α suppression and mitigation of DM-related organ damage [113]. These effects reduce inflammation and oxidative stress, underscoring the TNF gene’s significance in DM therapy. Moreover, TNF-α inhibition is gaining traction in autoimmune DM research, where it may help preserve β-cell function and delay insulin dependency [114].

Curcumin’s modulation of TNF-α shows notable overlap with other polyphenols but diverges from the mechanisms of conventional antidiabetic drugs. Resveratrol suppresses TNF-α production and downstream NF-κB signaling in adipose tissue and vascular endothelium, improving insulin sensitivity and reducing inflammation [87], while quercetin inhibits TNF-α expression and mitigates cytokine-driven oxidative stress, thereby protecting pancreatic β-cells and lowering insulin resistance [115]. In contrast, thiazolidinediones such as pioglitazone reduce TNF-α indirectly through PPARγ activation rather than direct inhibition [89]. Network pharmacology analyses further reveal that curcumin shares significant target overlap with resveratrol and quercetin in modulating inflammatory cytokines like TNF-α but demonstrates a broader multitarget regulatory profile compared to thiazolidinediones [87, 89, 115]. This highlights curcumin’s therapeutic value as a natural TNF-α inhibitor and supports its potential use in synergistic strategies with polyphenols or synthetic agents for DM management.

STAT3 gene

STAT3 is a key transcription factor involved in regulating immune responses, β-cell function, and inflammation in both T1DM and T2DM. Hyperactivation of STAT3 is associated with impaired insulin gene expression and autoimmunity in T1DM, while genetic variants contribute to T2DM susceptibility and metabolic dysregulation [116-119]. STAT3 also maintains pancreatic cell identity, and its inhibition facilitates β-cell regeneration via trans-differentiation of other pancreatic cell types [120, 121].

Curcumin inhibits STAT3 activation in 3T3-L1 cells, thereby reducing adipogenesis—an effect more pronounced in classical 2D culture but still evident in physiologically relevant 3D spheroid systems—highlighting its mechanistic role in obesity-related insulin resistance [122]. Beyond adipocyte models, curcumin has been shown to suppress STAT3 phosphorylation in multiple in vitro and in vivo systems, including human bronchial epithelial and pancreatic cancer cells, where it reduces STAT3-P levels in a dose-dependent manner and downregulates proliferative gene expression [123, 124]. While many of these findings stem from oncologic or non-metabolic studies, the central mechanistic insight—that curcumin attenuates STAT3-driven transcriptional programs—offers a strong rationale, within a network pharmacology framework, for its documented anti-inflammatory and insulin-sensitizing actions in metabolic disease. Supporting this, preclinical and clinical evidence links curcumin supplementation to modest yet significant improvements in fasting glucose, HbA1c, HOMA-IR, β-cell function, and inflammatory biomarkers in patients with T2DM or metabolic syndrome [125]. Although direct clinical confirmation of STAT3 involvement in these outcomes is limited, network-based analyses suggest that STAT3 inhibition represents a critical node in curcumin’s multifaceted anti-diabetic activity. By modulating this pathway, curcumin may provide dual therapeutic benefits—attenuating systemic inflammation while promoting β-cell survival and functional preservation—positioning STAT3 as a promising molecular target for future DM therapeutics.

IL6 gene

The IL6 gene, which encodes interleukin-6 (IL-6), is deeply involved in chronic inflammation and metabolic dysfunction in DM. Elevated IL-6 levels correlate with insulin resistance and act as an independent risk factor for T2DM. IL-6 promotes macrophage infiltration into adipose tissue, exacerbating local inflammation and disrupting insulin signaling [126-128]. Through binding to IL-6R/gp130, it activates the JAK/STAT3 pathway, contributing to β-cell stress and impaired glucose metabolism [126, 129].

Curcumin has been shown to suppress IL-6 expression and inhibit activation of the JAK/STAT3 axis, thereby alleviating inflammation-driven insulin resistance and supporting β-cell protection [128]. While polymorphisms like − 174G/C in IL6 show variable associations across populations, the cytokine’s consistent role in DM pathogenesis validates it as a therapeutic target [130, 131]. Curcumin’s ability to modulate IL6 signaling highlights its potential in IL-6-directed interventions aimed at controlling inflammation and preserving metabolic function.

Curcumin’s regulation of IL-6 shows notable overlap with other polyphenols while differing from the mechanisms of conventional antidiabetic therapies. Resveratrol, for instance, reduces circulating IL-6 levels and inhibits STAT3 phosphorylation, thereby enhancing insulin sensitivity and vascular function [87]. Similarly, quercetin downregulates IL-6 expression in adipose and hepatic tissues, contributing to decreased chronic inflammation and improved glucose tolerance [88]. In contrast, standard antidiabetic drugs such as metformin lower IL-6 levels indirectly by activating AMPK and restoring metabolic balance, rather than directly interfering with IL-6 signaling [105]. Network pharmacology analyses further indicate that curcumin’s targetome overlaps strongly with resveratrol and quercetin in modulating pro-inflammatory cytokines yet extends its influence to broader pathways involving oxidative stress and apoptosis regulation [87, 88, 105]. This multitarget profile underscores curcumin’s therapeutic potential and suggests synergistic benefits when combined with polyphenols or standard agents to mitigate IL-6–driven diabetic complications.

Potential Clinical Applications

Curcumin’s multi-target interactions within DM-associated molecular networks have been shown to produce significant clinical benefits, particularly in enhancing glycemic control and reducing DM-related complications. Systematic reviews and meta-analyses of RCTs (randomized controlled trials) consistently report that curcumin supplementation leads to notable reductions in FBS (fasting blood glucose), HbA1c (glycated hemoglobin), and insulin resistance markers such as HOMA-IR in patients with T2DM. For instance, a comprehensive meta-analysis of 11 randomized controlled trials (RCTs), including 1,131 patients with T2DM, examined the impact of curcumin on HbA1c levels. Nine of these studies demonstrated high methodological quality (Jadad score ≥ 3), indicating adequate randomization, blinding, and reporting. Sample sizes ranged from 32 to 240, with considerable variation in curcumin types (standard, curcuminoids, nano-formulations) and intervention durations (1–9 months). Notably, seven trials showed significant HbA1c reductions, especially with treatments of 12 weeks or more. Nevertheless, limitations such as small cohorts, variable dosing, and regional concentration reduce generalizability, emphasizing the need for larger standardized trials [132]. Likewise, a dose–response meta-analysis involving 59 RCTs on curcumin/turmeric in adults with glycemic disorders found mostly low risk of bias in sequence generation and allocation. However, concerns remained regarding blinding, outcome assessment, and reporting. With small sample sizes (20–235) and predominantly short durations (4–36 weeks) in Iranian populations, findings suggest potential small-study and publication biases [133]. Curcumin’s clinical benefits in DM are underpinned by its anti-inflammatory and antioxidant properties, which help counteract insulin resistance and β-cell dysfunction by reducing chronic inflammation and oxidative stress. A systematic review of 16 clinical trials involving 1,309 participants—mostly randomized, double-blind, placebo-controlled—demonstrated curcumin’s therapeutic promise in T2DM. Sample sizes ranged from 44 to 136, with participants aged 18–85. While most studies showed sound methodology with minimized bias through proper randomization and blinding, some had limitations such as short durations, small cohorts, or incomplete reporting. These factors may limit the generalizability of the results [7].

Despite curcumin’s promising therapeutic potential, its clinical application has been hindered by poor bioavailability, largely due to its low water solubility, rapid metabolism, and swift systemic clearance. To address these limitations, nanotechnology-based curcumin formulations have been developed, significantly improving their absorption, stability, and overall therapeutic efficacy. Clinical studies using nanocurcumin have shown enhanced metabolic outcomes in DM patients, including reductions in fasting plasma glucose, insulin levels, and inflammatory markers, along with improvements in antioxidant status [7]. For example, an umbrella meta-analysis comprising 12 meta-analyses evaluated curcumin’s effects on glycemic and anthropometric outcomes across diverse populations and study designs. Most studies were of high quality based on AMSTAR assessments, though some included trials with high risk of bias. Sample sizes range from 168 to 2,629, with curcumin doses between 0.08 and 1.5 g/day and intervention durations from 6 to 19 weeks. While the overall evidence was rated moderate to high, considerable heterogeneity was observed due to differences in participant characteristics, dosages, and study lengths. Additionally, indirectness and imprecision in HbA1c and insulin outcomes suggest a need for standardized, large-scale trials [134]. These technological advancements suggest that nanocurcumin could effectively bridge the gap between curcumin’s mechanistic potential and its clinical efficacy, positioning it as a promising adjunct therapy in comprehensive DM care. The translation of curcumin’s multi-target molecular interactions into tangible clinical benefits is well-supported by emerging clinical evidence, with nano-formulations playing a critical role in maximizing their bioavailability and therapeutic impact. Further research is needed to optimize these delivery systems and to investigate their long-term effects on DM management.

Clinical trials evaluating curcumin supplementation in T2DM and related metabolic disorders face notable limitations that constrain interpretation. Most studies involved small sample sizes and short intervention periods, reducing statistical power and limiting insights into long-term outcomes. Considerable heterogeneity was reported, largely due to variations in curcumin dosage, formulation, treatment duration, and study populations. A significant proportion of trials were conducted in Asian countries, raising concerns about global generalizability. Additional issues included limited male representation, reliance on single-dose interventions, and insufficient monitoring of adherence. Many studies also failed to assess broader mechanistic biomarkers, such as markers of oxidative stress, inflammation, and gene expression linked to insulin resistance and lipid metabolism, thereby restricting mechanistic understanding. Furthermore, the overall quality of evidence was rated low, and subgroup analyses did not fully address variability. Together, these challenges highlight the urgent need for large-scale, long-duration, and methodologically robust randomized controlled trials with standardized dosing strategies to confirm curcumin’s therapeutic role in DM management [7, 132-134].

Challenges in Translating in Vitro and in Silico Findings To Clinical Relevance

In vitro and in silico studies have significantly advanced our understanding of curcumin’s pharmacological mechanisms, particularly its ability to modulate multiple signaling pathways such as PI3K-Akt, AGE-RAGE, and JAK-STAT. However, translating these findings into clinical settings presents substantial challenges. A major limitation is curcumin’s inherently low oral bioavailability, primarily due to its poor water solubility, rapid metabolism, and swift systemic clearance. As a result, the promising multi-target interactions identified through computational models and laboratory assays often fail to yield consistent therapeutic outcomes in vivo. Differences in absorption, distribution, and pharmacodynamics between preclinical models and human physiology further complicate this translation.

Another significant barrier lies in the variability of experimental conditions and clinical study designs. In vitro research frequently utilizes simplified models such as cell lines or isolated tissues that do not accurately represent the complexity of human metabolic networks. Similarly, in-silico predictions, while informative, are based on static computational models that may not fully capture the dynamic biological context of DM. Clinically, the lack of standardized protocols for curcumin dosage, formulation, and treatment duration, along with variation in patient demographics, makes it difficult to draw definitive conclusions about efficacy. Additionally, the absence of validated biomarkers and the regulatory complexity surrounding multi-target compounds like curcumin hinder clinical translation. Addressing these issues will require a multidisciplinary approach that combines optimized delivery systems (e.g., nano-formulations), robust clinical trials, and validation of computational targets using patient-derived data to fully harness curcumin’s therapeutic potential in DM management.

Addressing Mixed and Inconsistent Evidence

Although numerous studies highlight curcumin’s potential benefits on glycemic control, insulin resistance, and oxidative balance in T2DM, the overall findings remain inconsistent. A meta-analysis of 11 randomized controlled trials (n = 645) reported significant increases in total antioxidant capacity and reductions in malondialdehyde (MDA), yet no meaningful effect on high-sensitive C-reactive protein (hs-CRP), a key inflammatory marker, was observed [135]. Similarly, a clinical trial in non-insulin-dependent DM patients demonstrated improvements in certain inflammatory indicators but did not detect changes in oxidative stress markers, insulin levels, HOMA-IR, or HbA1c, highlighting variability depending on endpoints and study design [7]. High heterogeneity between studies further complicates interpretation, and subgroup analyses by age, dosage, or treatment duration have not fully explained the inconsistent outcomes, particularly for markers such as hs-CRP and MDA [15, 135].

In specific contexts like diabetic kidney disease, pooled data showed no significant effect of curcumin on proteinuria (PRO) with high heterogeneity (I² = 86.9%), although certain subgroups appeared to benefit [136]. Likewise, meta-analyses of glycemic and lipid parameters revealed no significant impact on body mass index (BMI), while modest improvements in HbA1c, HOMA, and LDL cholesterol were observed, suggesting that efficacy may be marker-specific and dependent on dose or duration [137]. Collectively, these findings indicate that curcumin’s anti-diabetic effects are context-dependent, often limited to specific biomarkers or require optimized formulations and prolonged interventions. Given the variability, limited reproducibility, and substantial heterogeneity, its benefits should be interpreted cautiously, and future research must prioritize standardized dosing, larger sample sizes, longer study durations, and consistent outcome measures to clarify curcumin’s therapeutic potential in DM management.

Adverse Effects, Drug Interactions, and Translational Limitations

Despite curcumin’s promising multi-target effects in alleviating DM-related metabolic dysfunction, its clinical translation requires careful consideration of safety, toxicity, and pharmacokinetic limitations. Curcumin is generally safe at dietary levels, and clinical studies report good tolerability even at doses up to 8 g/day [138]. Nonetheless, higher doses or prolonged use may cause gastrointestinal disturbances such as nausea, diarrhea, and abdominal discomfort [139]. Its poor bioavailability, rapid metabolism, and systemic clearance further limit therapeutic efficacy, necessitating adjuvants like piperine or advanced delivery systems such as nanoparticles and liposomes, which may alter both pharmacokinetics and safety profiles [140].

Drug–nutrient and drug–drug interactions are additional considerations. Curcumin can inhibit cytochrome P450 enzymes, P-glycoprotein, and UDP-glucuronosyltransferases, potentially affecting the metabolism of commonly used drugs including anticoagulants, antiplatelets, and hypoglycemic agents [141]. Its mild anticoagulant and hypoglycemic properties may also potentiate bleeding or hypoglycemia when combined with warfarin, aspirin, or sulfonylureas [142, 143]. For network pharmacology and systems biology approaches, incorporating ADMET profiling and drug–interaction predictions alongside efficacy studies are essential to accurately evaluate curcumin’s translational potential and safely integrate it into therapeutic strategies for DM.

Research Gaps, Future Directions and Translational Insights

Although extensive studies have advanced the understanding of curcumin’s multi-target mechanisms and its therapeutic promise in DM management, several important research gaps persist and warrant further exploration. Network pharmacology analyses have revealed a wide range of potential molecular targets and signaling pathways influenced by curcumin, including lesser-known kinases, transcription factors, and epigenetic regulators. These targets may significantly contribute to curcumin’s anti-diabetic effects but currently lack rigorous experimental validation. Additionally, the dynamic relationship between curcumin and the gut microbiota—an emerging regulator of metabolic health and DM progression—remains poorly understood. Investigating this interaction through metagenomic and metabolomic approaches could uncover novel mechanisms by which curcumin modulates glucose metabolism and systemic inflammation. Furthermore, while in-silico and preclinical studies suggest potential synergistic effects between curcumin and conventional anti-diabetic medications or other natural bioactives, comprehensive and comparative clinical trials are still needed to confirm these benefits, optimize dosage regimens, and evaluate long-term safety. Addressing these areas is critical to fully harness curcumin’s therapeutic potential and to develop evidence-based strategies for DM management.

Another critical research gap lies in the design of clinical trials that fully capture curcumin’s multi-target and systems-level effects, rather than narrowly focusing on isolated endpoints like fasting glucose or HbA1c. Many existing clinical studies are constrained by small sample sizes, short intervention periods, and a lack of mechanistic biomarker assessments, limiting the ability to connect molecular insights with meaningful patient outcomes. To overcome these limitations, future trials should adopt systems biology frameworks, integrating multi-omics profiling (transcriptomics, proteomics, metabolomics) and network-based biomarker analyses. Such methodologies would provide a holistic understanding of curcumin’s systemic impact on metabolic regulation, inflammation, and oxidative stress in diabetic patients. Importantly, these approaches could also enable patient stratification to identify subgroups most likely to benefit from curcumin-based interventions, supporting a move toward personalized nutrition and precision medicine.

From a translational standpoint, several practical recommendations should be prioritized. First, standardized formulations of curcumin, particularly nano-formulations and bioavailability-enhanced derivatives, must be systematically evaluated in large-scale, long-duration clinical trials to generate reliable safety and efficacy data. Second, regulatory frameworks should encourage comparative effectiveness research that benchmarks curcumin not only against placebo but also against standard-of-care antidiabetic drugs, highlighting where it may function best as an adjunctive therapy. Third, clear guidance on drug–curcumin interactions are urgently needed, as polypharmacy is common in diabetic populations. Finally, collaborative efforts between academia, industry, and regulatory agencies will be essential for establishing harmonized quality standards, validated biomarkers, and clinical endpoints that can facilitate the translation of curcumin from promising bioactive compound to clinically integrated therapeutic option.

Conclusion

Adopting a systems biology approach reveals that curcumin interacts with an extensive and interconnected network of molecular targets and signaling pathways relevant to DM, including oxidative stress regulators, inflammatory mediators, and critical insulin signaling cascades such as the AGE-RAGE, PI3K-Akt, TNF, and JAK-STAT pathways. This multi-target engagement enables curcumin to address the complex and multifactorial nature of DM more comprehensively than traditional single-target therapies. By concurrently reducing chronic inflammation, mitigating oxidative stress, and enhancing insulin sensitivity, curcumin offers a holistic therapeutic approach that aligns with the systemic pathophysiology of DM. Emerging evidence from both preclinical and clinical studies consistently supports curcumin’s efficacy in improving glycemic control and reducing the risk of DM-related complications, reinforcing its relevance within this network-based therapeutic framework. The clinical potential of curcumin has been further strengthened by advancements in nano-formulation technologies, which significantly enhance its bioavailability, stability, and overall therapeutic performance. Taken together, these insights position-curcumin as a promising multi-target agent that could be effectively integrated into comprehensive DM management strategies, potentially complementing existing pharmacotherapies and addressing current gaps in treatment outcomes. Moving forward, continued multidisciplinary research—combining network pharmacology, molecular investigations, and well-designed clinical trials—will be vital to fully unlock curcumin’s therapeutic potential and optimize its application in the fight against DM and its complications.

Author Contributions

M.R. Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Validation Visualization, Writing – original draft. M.F.F.M.A. Supervision, Project administration, Validation, Writing – review & editing.

Funding

Open access funding provided by The Ministry of Higher Education Malaysia and Universiti Malaysia Pahang Al-Sultan Abdullah. The authors would like to thank to the Universiti Malaysia Pahang Al-Sultan Abdullah for providing financial support under the Internal Research Grant (RDU240331).

Data Availability

No datasets were generated or analysed during the current study.

Declarations

Conflict of Interest

The authors declare no competing interests.