Next Article in Journal
Correction: Salloum-Asfar et al. MicroRNA Profiling Identifies Age-Associated MicroRNAs and Potential Biomarkers for Early Diagnosis of Autism. Int. J. Mol. Sci. 2025, 26, 2044
Previous Article in Journal
Correction: Skenderidou et al. Functional Food Ingredients Enhancing Immune Health: A Systematic Review. Int. J. Mol. Sci. 2025, 26, 8408
Previous Article in Special Issue
Beyond Protein Building Blocks: A Review of Biological Roles and Therapeutic Potential of Free Amino Acids
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Review

Natural Products as Potential Therapeutic Candidates for Diabetic Kidney Disease: Molecular Mechanisms, Translational Challenges, and Future Prospects

1
Department of Nephrology, Zhongnan Hospital of Wuhan University, Wuhan 430071, China
2
Department of General Practice, Zhongnan Hospital of Wuhan University, Wuhan 430071, China
*
Authors to whom correspondence should be addressed.
Int. J. Mol. Sci. 2025, 26(23), 11637; https://doi.org/10.3390/ijms262311637
Submission received: 19 October 2025 / Revised: 18 November 2025 / Accepted: 19 November 2025 / Published: 1 December 2025
(This article belongs to the Collection Latest Review Papers in Bioactives and Nutraceuticals)

Abstract

Diabetic Kidney Disease (DKD) is one of the primary causes of chronic kidney disease. However, existing clinical interventions remain insufficiently effective in halting its progression, highlighting the need to explore novel therapeutic approaches. In recent years, natural products such as Abelmoschus manihot have shown growing potential in lowering urinary protein. Building on this background, this paper systematically summarizes preclinical evidence that certain natural substances ameliorate DKD by targeting key pathogenic mechanisms, including inflammation and oxidative stress. It also contrasts the pros and cons of natural medicines with existing therapies, while further investigating advanced pharmaceutical technologies for the translation of natural medicines into clinical applications. However, the clinical translation of natural medicines currently confronts multiple challenges, including small sample sizes, insufficient follow-up periods, individual heterogeneity, and insufficient accumulation of safety data. Therefore, future efforts should prioritize the in-depth exploitation of medicinal plant resources and their clinical translation, with a focus on enhancing high-quality translational clinical studies. This strategy seeks to provide novel insights and practical solutions for treating DKD.

1. Introduction

As reported by the International Diabetes Federation, 537 million adults aged 20–79 were living with diabetes in 2021, and this figure is expected to rise to 783 million by 2045 [1]. Type 2 diabetes constitutes over 90% of all diabetic cases [2]. Approximately 50% of patients with type 2 diabetes mellitus (T2DM) worldwide are complicated with chronic kidney disease (CKD), indicating that the global burden of diabetic kidney disease (DKD) is of great severity [3]. Furthermore, the presence and severity of DKD exert a significant impact on the prognosis of patients with T2DM. As the disease advances, patients frequently require renal replacement therapy to maintain their lives. This trend not only constitutes a major threat to patients’ quality of life but also imposes a heavy burden on the global healthcare systems.
At present, the management of DKD is centered on metabolic control, hemodynamic regulation, and renal protection to slow the progression of renal injury [4]. Nevertheless, even with optimal treatment regimens in clinical trial settings and the advent of novel therapies such as SGLT2 inhibitors (SGLT2i), the residual risk of progressing to ESKD remains substantial [5,6]. Additionally, some newer drugs—including SGLT2i and glucagon-like peptide-1 (GLP-1) receptor agonists—are costly and inaccessible for many patients. Mineralocorticoid receptor antagonists (MRAs) like spironolactone confer mortality benefits but are associated with a risk of hyperkalemia and hormonal adverse effects, which restricts their clinical utility [7,8]. While SGLT2i reduces the risk of renal composite endpoints, it neither fully arrests disease progression nor avoids increasing the risk of fungal infections, hypovolemia, and diabetic ketoacidosis. Moreover, adequate clinical evidence supporting the long-term safety and tolerability of SGLT2i remains lacking [9,10].
Considering the current limitations in efficacy and risks of adverse effects associated with clinical therapies for DKD, identifying safe, effective, and novel therapeutic strategies remains a primary focus of current research. In recent years, natural products have emerged as an innovative approach for preventing and treating DKD, given their merits of multi-targeted synergistic modulation, low toxicity, and minimal adverse effects. Studies have shown that natural bioactive compounds and traditional Chinese medicinal formulas, including Astragaloside IV [11,12,13,14,15] and Danggui Buxue Decoction [16,17], possess distinct value in treating DKD by modulating metabolism, suppressing podocyte injury and apoptosis, and attenuating renal interstitial fibrosis. Nevertheless, current research on natural product interventions for DKD is fragmented, with a focus on individual compounds or mechanisms, and lacks systematic reviews of recent progress as well as an integrated mechanistic insight. Based on this, this paper systematically summarizes recent research progress on natural products for DKD treatment, focusing on the analysis of their therapeutic targets and molecular mechanisms. For the first time, it integrates a cross-analysis of multiple mechanisms within the unified framework of the “anti-ferroptosis–antioxidation–immunity” cascade, emphasizing the three key dimensions: “mechanism–evidence–translation”. This approach fills a gap in critical assessment and translational pathways among similar reviews, seeking to offer theoretical support for optimizing DKD therapeutic strategies and guiding the development of novel natural product-derived therapeutics.

2. Pathogenesis in Diabetic Kidney Disease

DKD is a prevalent microvascular complication of diabetes, characterized by a multidimensional and complex regulatory network underlying its pathological process (Figure 1). Metabolic disturbances initially induce hemodynamic dysregulation, and the two jointly activate inflammatory responses that subsequently aggravate extracellular matrix remodeling. Genetic predisposition amplifies these pathological processes. These mechanisms form a vicious cycle of mutual promotion, ultimately accelerating the progression of DKD.
The pathogenesis of DKD involves five key pathological factors: metabolic disorders, hemodynamic abnormalities, inflammatory responses, extracellular matrix remodeling, and genetic predisposition. These factors interact mutually, and their synergistic effects drive the initiation and progression of DKD. ( Notes: ↓, decrease; ↑, increase.)

2.1. Metabolic Disorder Regulatory Network

Metabolic disturbances serve as the core initiating factors of DKD pathogenesis, and their regulatory networks encompass abnormalities in multiple pathways. Sustained hyperglycemia activates the polyol pathway, enhancing aldose reductase activity and resulting in intracellular sorbitol buildup, which induces osmotic stress-induced damage [18,19]. Concurrently, it promotes non-enzymatic glycation of proteins, generating advanced glycation end products (AGEs) [20], thus establishing the basis for subsequent pathological damage. Diabetes-associated lipid metabolic disturbances often result in renal lipid accumulation, which exerts toxicity on podocytes, promotes their proliferation, and upregulates extracellular matrix (ECM) synthesis [21,22,23,24,25]. Furthermore, two key factors collectively amplify metabolic stress: first, impaired intestinal insulin secretion in T2DM—manifested as blunted glucose-dependent insulinotropic polypeptide (GIP) responsiveness and reduced GLP-1 levels [26]—and, second, bidirectional crosstalk between “microbiota–metabolism–renal injury” induced by gut microbiota dysbiosis in DKD [27,28,29]. This sustained metabolic stress directly disrupts renal hemodynamic balance [30,31].

2.2. Hemodynamic Abnormalities

In the early phase of diabetes, renal arteriolar dilation occurs, accompanied by increased renal blood flow and elevated glomerular filtration rate (GFR). Persistent hyperfiltration directly impairs glomerular endothelial cells and podocytes, disrupting the glomerular filtration barrier and triggering proteinuria [32,33]. Meanwhile, the renal local renin–angiotensin–aldosterone system (RAAS) is activated, leading to enhanced angiotensin II generation [34], which exacerbates glomerular hyperfiltration, stimulates podocyte proliferation, and upregulates extracellular matrix (ECM) synthesis [35,36,37,38]. Cellular damage induced by metabolic abnormalities and hemodynamic disturbances synergistically activate inflammation and oxidative stress [39].

2.3. Inflammation–Oxidative Stress–Ferroptosis–Immunity: Pathological Amplification Core

Metabolic and hemodynamic insults conjointly trigger the inflammation–oxidative stress axis, perturbing renal local immune homeostasis. This serves as a key amplifying driver of DKD’s pathophysiological progression. In the course of DKD progression, key inflammatory mediators—such as interleukin-1 (IL-1), interleukin-6 (IL-6), and tumor necrosis factor-α (TNF-α)—are significantly upregulated [40,41]. These mediators not only recruit immune cells to infiltrate into the kidney but also induce inflammatory responses in renal mesangial cells and podocytes [42]. The infiltrating immune cells further release pro-inflammatory cytokines, forming a positive feedback loop that triggers the initial “inflammation-immune activation” cascade.
With disease progression, hyperglycemia and hyperlipidemia induce overproduction of reactive oxygen species (ROS) in the kidneys. The resulting oxidative stress not only directly damages biomolecules such as proteins and nucleic acids but also activates inflammatory signaling pathways. Persistent inflammation suppresses the activity of antioxidant enzymes, such as glutathione peroxidase, leading to oxidative imbalance. Simultaneously, inflammation exerts a feedback effect to enhance ROS generation, forming a vicious “oxidative stress-inflammation” cycle [43] that further exacerbates renal injury.
Ultimately, ferroptosis dysregulation initiates a closed-loop mechanism: as an emerging pathological driver in DKD, ferroptosis represents a key intersection between ROS and lipid peroxidation [44]. When anti-ferroptotic pathways (such as the GPX4 pathway) are unable to scavenge lipid peroxides, ferroptosis is activated—simultaneously aggravating oxidative stress via impairment of renal antioxidant capacity and reactivating infiltrating immune cells through the release of damage-associated molecules, thereby potentiating inflammation [45]. This ultimately forms a cascade reaction of “immune activation → amplified inflammation → antioxidant imbalance → ferroptosis dysregulation → reinforced immune-inflammatory response,” which persistently amplifies DKD-related renal damage.

2.4. ECM Remodeling: Terminal Damage of Fibrosis

The persistent amplifying effects of inflammation, immunity, and oxidative stress ultimately lead to irreversible structural damage characterized by ECM remodeling—namely, renal fibrosis [46]. Transforming growth factor-β (TGF-β) is a key mediator in DKD-related fibrotic progression, stimulating mesangial cells and renal tubular epithelial cells to synthesize ECM components and inhibiting ECM degradation enzyme activity, leading to excessive ECM accumulation and thus promoting glomerular sclerosis and tubulointerstitial fibrosis [47]. Notably, hyperglycemia-induced ROS and pro-inflammatory cytokines significantly upregulate TGF-β expression. This process directly bridges upstream metabolic abnormalities and inflammatory stress with downstream ECM remodeling, converting early reversible damage into irreversible fibrotic lesions.

2.5. Genetic Susceptibility

Genetic susceptibility serves as the core determinant dictating individual differences in DKD, shaping DKD susceptibility and progression by modulating an individual’s responsiveness to metabolic, hemodynamic, and inflammatory insults. For instance, a missense mutation (p.K77M) in the thiamine diphosphate (TCN2) gene markedly enhances an individual’s susceptibility to DKD [48]; risk alleles at susceptibility loci within genes including angiotensin-converting enzyme (ACE), interleukin, and TNF-α also augment the risk of DKD development [49,50]. Consequently, patients with diabetes exhibit distinct probabilities of DKD onset and rates of progression when exposed to similar pathological insults [51].
Thoroughly analyzing the interconnections and regularities among the key links of the DKD pathological network—triggering, amplification, damage, and regulation—is crucial for formulating effective DKD prevention and treatment strategies.

3. Therapeutic Drugs and Their Mechanistic Pathways

In recent years, natural medicines have attracted considerable attention in DKD treatment research. Drawing on the aforementioned discussion of DKD pathogenesis, this section focuses on key natural product categories: flavonoids, polysaccharides, terpenoids, phenolics, traditional Chinese medicine and extracts, derivatives and complexes, and alkaloids. We systematically summarize the experimental evidence supporting their therapeutic potential in DKD and associate these natural products with seven key regulatory mechanisms: the AGEs-RAGE pathway, lipid metabolism regulation, gut microbiota modulation, podocyte function preservation, inflammatory response suppression, oxidative stress mitigation, and fibrosis inhibition. This builds an “interdisciplinary intervention network” integrating “pathway-Metabolism-Cell-Organ” cross-synergistic model (Figure 2), which is intended to offer more targeted and actionable theoretical support for subsequent clinical translation of DKD therapeutics.
The core principles of natural medicines for intervening in DKD are embodied in three aspects: first, targeting critical nodes in the DKD pathological cascade (e.g., AGEs-RAGE binding, NLRP3 activation, TGF-β1/Smad signaling) to precisely interrupt pathological progression; second, cross-mechanism synergistic modulation (e.g., the “antioxidant–anti-ferroptosis–anti-inflammatory” axis) caters to the complex pathological features of DKD; third, encompassing cross-linkages among pathological stages (e.g., the crosstalk between the AGEs-RAGE pathway and oxidative stress, and the interplay between gut microbiota and podocyte injury) to construct a holistic renal protective network.
This figure illustrates that two initiating factors of renal injury—metabolic disturbances and hemodynamic dysregulation—synergistically activate the inflammation–oxidative stress amplification pathway. Upon activation, this pathway undergoes sustained signal amplification, and the amplified pathological signals are further propagated to downstream effector pathways, ultimately inducing pathological remodeling of the extracellular matrix (ECM) and triggering irreversible renal structural and functional impairment to the kidneys. In contrast, natural medicines can precisely target key links in the aforementioned pathological cascade (e.g., critical molecules in the inflammation–oxidative stress amplification pathway, or regulatory hubs between upstream initiating factors and downstream ECM remodeling), thereby effectively abrogating the progressive development of renal pathological injury. (Notes: AGEs, advanced glycation end products; RAGE, receptor for advanced glycation end products; NLRP3, NOD-like receptor family pyrin domain containing 3; NF-κB, nuclear transcription factor κB; TGF-β, transforming growth factor-β; Nrf2, nuclear factor erythroid 2-related factor 2.)

3.1. Metabolic Regulation: AGEs–RAGE–Lipids–Microbiota Cascade Synergistic Network

The AGEs-RAGE pathway serves as a core pathogenic pathway in DKD [52], whose activation directly induces renal oxidative stress [53]. Excessive ROS further promotes the degradation of GPX4—a key ferroptosis protein—disrupting lipid metabolism homeostasis and forming a pathological damage cascade of “oxidative stress–lipid dysregulation–ferroptosis” [54]. Meanwhile, enhanced lipid toxicity enhances intestinal barrier permeability, perturbing gut microbiota homeostasis [55]. Dysbiotic microbiota secretes toxic metabolites—including indole-3-sulfate (IS) and p-cresol sulfate (PCS)—into the “gut–kidney axis,” which further exacerbates renal inflammation and dysregulation of lipid metabolism, thereby perpetuating a vicious cycle [56]. Natural medicines can intervene at multiple nodes in this cascade (Table 1 and Table 2), establishing a synergistic protective network of “pathway blockade-metabolic regulation-microbiota remodeling.” The specific mechanisms are as follows:
  • AGEs-RAGE pathway modulation: Cellular and animal studies have validated the effectiveness of this intervention mechanism cascade. For instance, salidroside reduces AGE accumulation by inhibiting the RAGE/JAK1/STAT3 signaling axis [57]. However, current research exhibits notable limitations: the lack of human clinical trials to validate dose–response relationships leads to a fragmented evidence chain for clinical translation. Moreover, the correlation between pathway inhibition and attenuation of renal injury has only been confirmed in a single DKD model, and the therapeutic efficacy of intervention for DKD linked to distinct etiologies (type 1 vs. type 2 diabetes) is yet to be elucidated.
  • Lipid Metabolism Regulation: The lipid metabolism regulatory effects of natural medicines are well-documented in animal studies. For instance, ginkgolide B stabilizes the expression of GPX4 while simultaneously improving lipid dysregulation and inhibiting ferroptosis [58]. Quercetin had also demonstrated reduced renal lipid deposition in small-sample clinical studies of early-stage DKD [59]. However, a core issue persists: large-scale trials have yet to verify differences in therapeutic efficacy across distinct DKD stages. Furthermore, the synergistic mechanisms of drugs targeting lipid breakdown (e.g., ATGL upregulation) versus those targeting lipid transport (e.g., SCAP/SREBP2 inhibition) have not been explored, leaving clinical combination therapy lacking a theoretical basis.
  • Gut Microbiota Regulation: In animal studies, the correlation between modulation of the gut microbiota and renal protection has been validated. For instance, magnesium lithospermate B modulates gut microbiota composition and inhibits the conversion of p-cresol (PC) to p-cresol sulfonate (PCS), thereby mitigating renal injury [60], while wine-processed Cornus officinalis alleviates gut-derived renal injury by reshaping the gut microbial community [61]. However, existing research has limitations: quantitative evaluation indicators for regulating the “gut–kidney axis” (e.g., the threshold for decreased indole-3-sulfate levels) remain unestablished, and clinical microbiome detection data are insufficient to support these findings. Furthermore, the causal relationship between altered gut microbial structure and decreased renal toxic metabolites has not been validated through assays like fecal microbiota transplantation, rendering it challenging to rule out interfering factors from other metabolic pathways.
Table 1. Drugs involved in the inhibition of non-enzymatic glycosylation reactions.
Table 1. Drugs involved in the inhibition of non-enzymatic glycosylation reactions.
Natural ProductsExperiment TypeDisease ModelMechanismReference
Buckwheat hull Flavonoidsin vivodb/db miceAGEs-RAGE pathway ↓[62]
Licochalcone Ain vivoSTZ-induced miceAGEs-RAGE pathway ↓[63]
Tinospora cordifolia (Willd.) using polylactic acid nanoparticlesin vivoSTZ-induced ratsAGEs-RAGE pathway ↓[64]
Dieckolin vitromGMCsAGEs-RAGE pathway ↓[65]
Dang Gui Bu Xue decoctionin vivo
in vitro
STZ-induced mice
HK-2
AGEs-RAGE pathway ↓[17]
Geniposidein vivo
in vitro
db/db mice
HEK293
AGEs-RAGE pathway ↓[66]
Vanillinin vivoSTZ-induced ratsAGEs-RAGE pathway ↓, NF-κB pathway ↓[67]
Syzygium cumini (L.) Skeels formulationsin vitroHEK293AGEs-RAGE pathway ↓, NF-κB pathway ↓[68]
Loganin and Catalpolin vivo
in vitro
HFD-induced KK-Ay mice
IMPC
AGEs-RAGE pathway ↓, p38 MAPK pathway ↓, NOX 4 pathway ↓[69]
Huang-Lian-Jie-Du Decoctionin vivodb/db miceAGEs/RAGE/Akt/Nrf2 pathway ↓[70]
Salidrosidein vivoSTZ-induced miceRAGE/JAK1/STAT3 pathway ↓[57]
Catalpolin vivo
in vitro
HFD-induced KK-Ay mice
mGECs, RAW264.7 macrophages
RAGE/RhoA/ROCK pathway ↓[71]
Notes: STZ, streptozotocin; AGEs, advanced glycation end products; RAGE, receptor for advanced glycation end products; mGMCs, the mouse glomerular mesangial cells lines; HK-2, human renal tubular epithelial cells; HEK293, the human embryonic kidney cell line; NF-κB, Nuclear Factor kappa B; HFD, high fat diet; IMPC, immortalized mouse podocyte cell line; p38, p38 mitogen-activated protein kinase; MAPK, mitogen-activated protein kinases; NOX 4, nadph oxidase 4; NLRP3, NOD-like receptor family pyrin domain containing 3; AKT, phospho- protein kinase B; Nrf2, nuclear factor erythroid 2-related factor 2; JAK1, janus kinase 1; STAT3, signal transducer and activator of transcription 3; RAW264.7, reticuloendotheliosis virus transformed cell line 264.7; RhoA, ras homolog gene family, member a; ROCK, rho-associated protein kinase; ↓, negative regulation, downregulate, inhibit.
Table 2. Drugs involved in improving lipid metabolism.
Table 2. Drugs involved in improving lipid metabolism.
Natural ProductsExperiment TypeDisease ModelMechanismReference
Tripterygium glycoside tabletin vivoSTZ-induced miceATGL[72]
Ginkgolide Bin vivo
in vitro
db/db mice
MPC5
Ubiquitination degradation of GPX4[58]
Gandi Capsulein vivo
in vitro
db/db mice
MPC5
SIRT1 ↑, AMPK ↑, HNF4A[73]
Quercetinin vivodb/db miceSCAP/SREBP2/LDLr pathway ↓[59]
Chrysinin vivoSTZ-induced miceAMPK ↑, SREBP1c[74]
Yishen Huashi granulein vivo
in vitro
STZ-induced rats
HepG2 and CaCO2 cells
mTOR/AMPK/PI3K/AKT pathway ↓[75]
Notes: STZ, streptozotocin; ATGL, adipose triglyceride lipase; MPC5, the mouse podocyte cell line; GPX4, glutathione peroxidase 4; SIRT1, silent information regulator sirtuin 1; AMPK, amp-activated protein kinase; HNF4A, hepatocyte nuclear factor 4 alpha; SCAP, sterol regulatory element-binding protein cleavage-activating protein; SREBP2, sterol regulatory element-binding protein 2; LDLr, low density lipoprotein receptor; mTOR, mechanistic target of rapamycin; PI3K, phosphoinositide 3-kinase; AKT, protein kinase B; ↓, negative regulation, downregulate, inhibit; ↑, positive regulation, upregulate, promote.

3.2. Regulation of Podocyte Injury: The Balance Between Autophagy and Apoptosis

Podocyte injury is a core pathogenic factor of proteinuria in patients with DKD, with both abnormal autophagy activity (either excessive or insufficient) and activation of apoptosis disrupting the renal filtration barrier [76,77]. Natural medicines can maintain podocyte function through two pathways (Table 3 and Table 4): first, by activating positive regulatory pathways (SIRT1-AMPK) and inhibiting negative regulatory pathways (mTOR, PI3K/Akt) to preserve autophagy homeostasis; second, by blocking upstream apoptotic signals (EGFR, AGEs-RAGE) to reduce podocyte loss, thereby mitigating renal injury.
Current research exhibits distinct targeting specificity in cellular and animal experiments. For instance, catalpol bidirectionally regulates the mTOR/TFEB pathway to preserve autophagy homeostasis [78], while loganin and catalpol synergistically inhibit podocyte apoptosis via multiple signaling pathways [69]. However, limitations are equally notable: evidence is still limited to basic research without large-scale clinical validation. The core contradiction lies in the stage-specific adaptability of autophagy regulation—early-stage DKD requires autophagy activation (e.g., corilagin exerts this effect by activating the SIRT1-AMPK pathway [79]), whereas advanced DKD requires suppression of autophagic overactivation. Existing studies fail to establish clear quantitative thresholds for autophagy activity (e.g., LC3-II/LC3-I ratio thresholds), leading to inconsistent standards for therapeutic regulation. Furthermore, the potential risk of abnormal proliferation induced by long-term inhibition of podocyte apoptosis has not been ruled out via toxicity studies.
Table 3. Drugs involved in the regulation of autophagy mechanisms in podocytes.
Table 3. Drugs involved in the regulation of autophagy mechanisms in podocytes.
Natural ProductsExperiment TypeDisease ModelMechanismReference
Corilaginin vivo
in vitro
STZ-induced mice
MPC5
SIRT1-AMPK pathway ↑[79]
Puerarinin vivo
in vitro
STZ-induced mice
ciMPC
HMOX1/SIRT1 pathway ↑, AMPK pathway ↑; PERK/eIF2α/ATF4 pathway ↑[80,81]
Yishen capsulein vivo
in vitro
STZ-induced rats
MPC5
SIRT1 ↑, NF-κB pathway ↓[82]
Selenized Tripterine Phytosomesin vitroMPC5SIRT1 ↑, NLRP3[83]
Astragalus polysaccharidein vivo
in vitro
STZ-induced rats
BFN60700330
SIRT1/FoxO1 pathway ↑[84]
Emodinin vivoSTZ-induced ratsAMPK ↑, mTOR[85]
Kaempferolin vivodb/db miceAMPK ↑, mTOR[86]
Catalpolin vivo
in vitro
STZ-induced mice
ciMPC
mTOR/TFEB pathway ↑[78]
Vitamin Din vivoSTZ-induced ratsmTOR[87]
Yiqi Huoxue recipein vivoSTZ-induced ratsmTOR ↓, S6K1 ↓, LC3[88]
Geniposidein vivoSTZ-induced miceAMPK/ULK1 pathway ↑[89]
Tangshen Decoctionin vivoSTZ-induced ratsp-AMPK/p-ULK1 pathway ↑[90]
Huang-Gui solid dispersionin vivoSTZ-induced rats
db/db mice
AMPK pathway ↑[91]
Tanshinone IIAin vivo
in vitro
db/db mice
MPC5
PI3K/Akt/mTOR pathway ↓[92]
Paecilomyces cicadae-fermented Radix astragaliin vivo
in vitro
STZ-induced mice
Mouse podocyte cell lines
PI3K/Akt/mTOR pathway ↓[93]
Celastrolin vivoSTZ-induced ratsPI3K/Akt/mTOR pathway ↓[94]
Curcuminin vivo
in vitro
STZ-induced rats
MPC5
PI3K/Akt/mTOR pathway ↓, Beclin1 ↑, UVRAG[95,96]
Isoorientinin vivoSTZ-induced mice
MPC5
PI3K/AKT/TSC2/mTOR pathway ↓[97]
Sarsasapogeninin vivo
in vitro
STZ-induced rats
mouse podocytes
GSK 3β pathway ↓[98]
Notes: STZ, streptozotocin; MPC5, the mouse podocyte cell line; ciMPC, immortalized mouse podocytes treated with high glucose; ciMPC, immortalized mouse podocytes treated with high glucose; SIRT1, silent information regulator sirtuin 1; AMPK, amp-activated protein kinase; HMGB1, high mobility group box 1; PERK, protein kinase R-like endoplasmic reticulum kinase; eIF2α, eukaryotic translation initiation factor 2 alpha; ATF4, activating transcription factor 4; NF-κB, nuclear transcription factor κB; NLRP3, NOD-like receptor family pyrin domain containing 3; FoxO1, forkhead box O1; mTOR, mechanistic target of rapamycin; TFEB, transcription factor EB; S6K1, ribosomal protein S6 kinase beta-1; LC3, microtubule—associated protein 1 light chain 3; ULK1, unc-51 like autophagy activating kinase 1; PI3K, phosphoinositide 3-kinase; AKT, protein kinase B; UVRAG, UV radiation resistance associated; TSC2, tuberous sclerosis complex 2; GSK 3β, glycogen synthase kinase-3 beta; ↓, negative regulation, downregulate, inhibit; ↑, positive regulation, upregulate, promote.
Table 4. Drugs involved in the regulation of apoptosis mechanisms in podocytes.
Table 4. Drugs involved in the regulation of apoptosis mechanisms in podocytes.
Natural ProductsExperiment TypeDisease ModelMechanismReference
Quercetinin vivo
in vitro
db/db mice
ciMPC
EGFR pathway ↓[99]
Zuogui Wanin vivo
in vitro
db/db mice
ciMPC
p38/MAPK pathway ↓[100]
Huidoubain vivo
in vitro
STZ-induced rats
MPC5
NOX 4—ROS pathway ↓[101]
Resveratrolin vivo
in vitro
db/db mice
ciMPC
AMPK pathway ↑[102]
Astragaloside IVin vivo
in vitro
db/db mice
ciMPC
PPARγ/Klotho/FoxO1 pathway ↑; Klotho ↑, NF-κB/NLRP3 axis ↓; IRE-1α/NF-κB/NLRP3 pathway ↓[11,12,13]
Baoshenfang formulain vivo
in vitro
STZ-induced rats
ciMPC
NOX 4/ROS/p38 pathway ↓[103]
Baicalinin vitroMPC5SIRT1/NF-κB pathway ↑[104]
Notes: ciMPC, immortalized mouse podocytes treated with high glucose; MPC5, the mouse podocyte cell line; EGFR, epidermal growth factor receptor; p38, p38 mitogen-activated protein kinase; MAPK, mitogen-activated protein kinases; NOX 4, nadph oxidase 4; ROS, reactive oxygen species; AMPK, amp-activated protein kinase; PPARγ, peroxisome proliferator-activated receptor gamma; FoxO1, forkhead box O1; IRE-1α, inositol requiring enzyme 1 alpha; PAR-1, protease-activated receptor 1; NLRP3, NOD-like receptor family pyrin domain containing; NF-κB, nuclear transcription factor κB; ↓, negative regulation, downregulate, inhibit; ↑, positive regulation, upregulate, promote.

3.3. Inflammation Regulation: Core Interventions by NLRP3 and NF-κB

NLRP3 inflammasomes and NF-κB are core regulatory molecules in the inflammatory response of DKD: its activation releases the pro-inflammatory cytokines IL-1β/IL-18, while the latter promotes the production of pro-inflammatory cytokines such as TNF-α/IL-6. Both can also undergo cross-activation via pathways such as IRE-1α and PAR-1 [105,106]. Natural medicines can target these molecules and their associated pathways to block inflammation-driven renal injury and renal fibrosis progression (Table 5 and Figure 3).
Animal studies have demonstrated the anti-inflammatory and anti-fibrotic effects of natural medicines: for instance, coptisine directly inhibits the activation of the NLRP3 inflammasome [107], while silibinin improves renal function in animal models of DKD by suppressing the NF-κB pathway [108]. However, clinical evidence remains extremely scarce—only one small-sample clinical study has suggested the safety profile of silibinin [109]; two key issues persist: first, drugs targeting NLRP3 are restricted to animal studies; second, drugs targeting NF-κB lack dose–response investigations; and third, clinical application scenarios (early-to-mid vs. late-stage DKD) remain undefined for both classes of drugs. Second, the link between inflammatory pathway inhibition and renal function improvement remains unclear, rendering it difficult to discern whether anti-inflammatory effects directly protect the kidneys or exert indirect effects by suppressing fibrosis.
Table 5. Drugs involved in the inhibition of NLRP3 inflammatory vesicles.
Table 5. Drugs involved in the inhibition of NLRP3 inflammatory vesicles.
Natural ProductsExperiment TypeDisease ModelMechanismReference
Coptisine in vivo
in vitro
STZ-induced rats
HK-2 cells
the NLRP3 inflammasome ↓[107]
Ferulic acidin vivoSTZ-induced micethe NLRP3 inflammasome ↓[110]
Hong Guo Ginseng Guoin vivoSTZ-induced ratsthe NLRP3 inflammasome ↓[111]
Crocinin vivoSTZ-induced ratsthe NLRP3 inflammasome ↓[112]
Berberinein vivo
in vitro
STZ-induced rats
HK-2
the NLRP3 inflammasome ↓[113]
Sarsasapogenin in vivo
in vitro
STZ-induced rats
HMCs
PAR-1 ↓, the NLRP3 inflammasome ↓, NF-κB pathway ↓, AGEs-RAGE pathway ↓[114,115]
Dioscorea zingiberensisin vivoSTZ-induced ratsthe NLRP3 inflammasome ↓, p66Shc[116]
Ethanolic extract from rhizome of Polygoni avicularisin vivo
in vitro
db/db mice
HRMCs
TGF-β1/Smad pathway ↓, the NLRP3 inflammasome ↓[117]
Astragaloside IVin vivo
in vitro
STZ-induced rats
Immortalized rat podocytes
IRE-1α/NF-κB/NLRP3 pathway ↓[11]
Thonningianin Ain vivoSTZ-induced miceNLRP3/ASC/Caspase-1 pathway ↓[118]
Cynapanosides Ain vivo
in vitro
HFD-induced mice
iMPC
NLRP3/NF-κB pathway ↓[119]
6-Gingerolin vivoSTZ-induced ratsmiRNA-146a ↑, miRNA-223 ↑, TLR4/TRAF6/NLRP3 pathway ↓[120]
Notes: STZ, streptozotocin; HK-2, human renal tubular epithelial cells; HMCs, human mesangial cells; HRMCs, Primary human renal mesangial cells; HFD, high fat diet; iMPC, immortalized mouse podocyte cell line; NLRP3, NOD-like receptor family pyrin domain containing 3; PAR-1, protease-activated receptor 1; NF-κB, nuclear transcription factor κB; AGEs, advanced glycation end products; RAGE, receptor for advanced glycation end products; p66Shc, src homology 2 domain containing transforming protein C1isoform p66; TGF-β, transforming growth factor-β; IRE-1α, inositol requiring enzyme 1 alpha; ASC, apoptosis—associated speck—like protein containing a CARD; TLR4, toll-like receptor 4; TLR4, toll-like receptor 4; ↓, negative regulation, downregulate, inhibit; ↑, positive regulation, upregulate, promote.
This figure illustrates the regulatory mechanisms of natural medicines in inhibiting inflammation-driven renal injury in DKD. The NF-κB pathway is a key signaling pathway mediating inflammation-associated renal injury in DKD, and its activation—along with the function of its upstream regulatory and downstream effector pathways)—is closely linked to the progression of renal injury. Natural medicines can exert renal protective effects via two primary mechanisms: first, by directly targeting the NF-κB pathway itself, its upstream regulatory pathways (e.g., TLR4 pathways that initiate NF-κB activation), and downstream effector pathways (e.g., TGF-β1/Smad3 pathways that transduce NF-κB-mediated inflammatory signals); second, by synergistically regulating other signaling pathways interacting with NF-κB (e.g., MAPK pathways, PI3K/AKT pathways, Nrf2/HO-1 pathways). Collectively, these regulatory effects enable natural medicines to effectively block the progression of inflammation-driven renal injury in DKD. (Notes: MAPK, mitogen-activated protein kinases; NF-κB, nuclear transcription factor κB; TGF-β1, transforming growth factor-β 1; Smad3, Sma- and Mad-related protein 3; TLR4, toll-like receptor 4; PI3K, phosphoinositide 3-kinase; AKT, protein kinase B; Nrf2, nuclear factor erythroid 2-related factor 2; HO-1, heme oxygenase-1.)

3.4. “Iron Death Resistance–Antioxidation–Immunity” Cascade Regulation

Oxidative stress acts as a pivotal convergence point in this cascade: excessive ROS production impairs cellular antioxidant homeostasis [121], leading to downregulated GPX4 expression, increased lipid peroxidation, and ultimately ferroptosis induction. [122,123]. Natural medicines can establish a dynamic “antioxidation-ferroptosis-immunity” regulatory network through a cascaded intervention model: activating antioxidant pathways (Nrf2)-targeting core ferroptosis molecules (GPX4)-regulating associated inflammatory pathways (Table 6 and Table 7, Figure 4) [124,125], thereby delaying DKD progression. This process involves three distinct stages:
  • Antioxidant initiation pathway: The Nrf2 pathway acts as a key target for antioxidant defense regulation, and its diminished activity in DKD directly contributes to oxidative imbalance [126]. Natural medicines can scavenge ROS by upregulating Nrf2 and its downstream HO-1 expression; for instance, xanthohumol directly activates Nrf2 [127], whereas baicalin not only activates Nrf2 but also inhibits the MAPK signaling pathway [128]. However, a critical issue persists: the tissue specificity of Nrf2 activation unclarified, and the absence of renal-specific targeting drugs could induce side effects arising from systemic over-antioxidation.
  • Core Mechanisms of Ferroptosis: Ferroptosis is a novel iron-dependent, lipid peroxidation-driven regulated cell death pathway. Renal tissue iron overload and decreased GPX4 activity in DKD are core mechanisms underlying ferroptosis [129]. Natural medicines can inhibit this pathway via multiple mechanisms: vitexin directly activates GPX4 [130], while Orthosiphon aristatus (Blume) Miq. indirectly regulates the expression of GPX4/ACSL4 by protecting mitochondrial function [131]. However, a contradiction persists: the molecular crosstalk mechanisms between ferroptosis inhibition and the Nrf2 pathway remain unclear. For instance, whether Nrf2 directly binds to the GPX4 promoter has not been validated using chromatin immunoprecipitation (ChIP) assays, precluding the distinction between direct and indirect regulatory effects.
  • Immune-inflammation crosstalk: Both ferroptosis and oxidative stress activate inflammatory pathways such as the NLRP3 inflammasome and the NF-κB pathway, thereby releasing pro-inflammatory cytokines including IL-1β and TNF-α [132,133]. Natural medicines can counter-regulate immune-inflammatory responses through upstream cascade interventions. For example, leonurine (a compound from Leonurus japonicus) upregulates GPX4 expression via the Nrf2 pathway, thereby inhibiting ferroptosis and reducing the release of pro-inflammatory cytokines [134]. However, clinical translation confronts substantial challenges: the lack of dynamic monitoring data on iron metabolism (serum ferritin), oxidative stress (ROS levels), and immune markers (IL-1β concentration) in DKD patients hampers the establishment of clear biomarker thresholds to guide effective drug intervention.
Table 6. Drugs involved in the activation of Nrf2 and related pathways.
Table 6. Drugs involved in the activation of Nrf2 and related pathways.
Natural ProductsExperiment TypeDisease ModelMechanismReference
Xanthohumolin vivo
in vitro
STZ-induced mice
GECs, HK-2
Nrf2 pathway ↑[127]
Z-ligustilidein vivo
in vitro
STZ-induced mice
Hepa 1c1c7, HBZY- 1, RAW 264.7
Nrf2 pathway ↑[135]
Syringic acidin vivo
in vitro
STZ-induced rats
NRK 52E
Nrf2 pathway ↑[136]
Rumex nervosusin vivoSTZ-induced ratsNrf2 pathway ↑[137]
Eriodictyolin vivoSTZ-induced ratsNrf2 pathway ↑[138]
Quercetinin vivo
in vitro
STZ-induced rats
HK-2
Nrf2 pathway ↑[139]
Baicalinin vivodb/db miceNrf2 pathway ↑, MAPK pathway ↓[128]
Artemisininin vivoSTZ-induced ratsNrf2 pathway ↑, TGF-β1 ↓[140]
Chlorogenic acidin vivo
in vitro
STZ-induced rats
HK-2
Nrf2 pathway ↑, the NLRP3 inflammasome ↓[141]
Isoeucommin Ain vitroHRMCs, RTECsNrf2/HO-1 pathway ↑[142]
Umbelliferonein vivo
in vitro
db/db mice
HK-2
Nrf2/HO-1 pathway ↑[143]
Tetrandrinein vivoSTZ-induced ratsNrf2/HO-1 pathway ↑[144]
Sinapic acidin vivoSTZ-induced ratsNrf2/HO-1 pathway ↑[145]
Moringa oleifera Lam. Seed extractin vivo
in vitro
STZ-induced rats
HRMCs
Nrf2/HO-1 pathway ↑[146]
Asiaticosidein vivo
in vitro
STZ-induced rats
HBZY-1
Nrf2/HO-1 pathway ↑[147]
Kaempferolin vivoSTZ-induced ratsNrf2/HO-1 pathway ↑[148]
Neferinein vivo
in vitro
STZ-induced mice
HMCs
miR-17-5p ↓, Nrf2/HO-1 pathway ↑[149]
Eucommia lignansin vivo
in vitro
STZ-induced rats
HBZY-1
AR ↓, Nrf2/HO-1 pathway ↑, AMPK pathway ↑[150]
Triptolidein vivo
in vitro
db/db mice, STZ-induced mice; SV40-MES-13, MPC5Phosphorylation of GSK3β ↓, Nrf2 ↑, HO-1 ↑; the NLRP3 inflammasome↓[151,152]
Moringa isothiocyanate -1in vivodb/db miceERK/Nrf2/HO-1 pathway ↑, NF-κB pathway↓[153]
Epigallocatechin-3-gallatein vivoSTZ-induced ratsNrf2/ARE pathway ↑[154]
Obacunonein vivo
in vitro
STZ-induced rats
HK-2
Nrf2-KEAP1 pathway ↓[155]
Note: STZ, streptozotocin; GECs, glomerular endothelial cells; HK-2, human renal tubular epithelial cells; Hepa 1c1c7. murine hepatoma cells; RAW 264.7, murine macrophages; NRK-52E, rat renal tubular epithelial cell; HBZY-1, rat mesangial cells; RTECs, a renal tubular epithelial cell line; HRMCs, Primary human renal mesangial cells; HMCs, human mesangial cells; SV40-MES13, mesangial cell line; MPC5, the mouse podocyte cell line; Nrf2, nuclear factor erythroid 2-related factor 2; MAPK, mitogen-activated protein kinases; TGF-β, transforming growth factor-β; HO-1, heme oxygenase-1; ERK, extracellular signal-regulated kinase; miR, miRNA; AR, androgen receptor; AMPK, amp-activated protein kinase; GSK 3β, glycogen synthase kinase-3 beta; NLRP3, NOD-like receptor family pyrin domain containing 3; ERK, extracellular signal-regulated kinase; NF-κB, nuclear transcription factor κB; ARE, antioxidant response element; Smad, small mothers against decapentaplegic; KEAP1, Kelch-like ECH-associated protein 1; ↓, negative regulation, downregulate, inhibit; ↑, positive regulation, upregulate, promote.
Table 7. Drugs involved in the regulation of iron death.
Table 7. Drugs involved in the regulation of iron death.
Natural ProductsExperiment TypeDisease ModelMechanismReference
Vitexinin vivo
in vitro
STZ-induced rats
HK-2
GPX4 ↑[130]
Astragaloside IVin vivodb/db miceGPX4 ↑, xCT ↑, GSH/GSSG ↑, ACSL4 ↓[14]
Orthosiphon aristatus (Blume) Miqin vivodb/db miceNCOA4 ↓, ACSL4 ↓, FTH1 ↑, GPX4 ↑[131]
Jian-Pi-Gu-Shen-Hua-Yu decoctionin vivoSTZ-induced miceGPX4 pathway ↑[156]
leonurinein vivo
in vitro
STZ-induced mice
HUVECs
Nrf2/GPX4 pathway ↑[134]
Rheinin vivo
in vitro
db/db mice
MPC5
Rac1/NOX1/β—catenin axis ↓, SLC7A11/GPX4 axis ↑[157]
San-Huang-Yi-Shen capsulein vivoSTZ-induced miceCystine/GSH/GPX4 axis ↑[158]
Ginkgolide Bin vivo
in vitro
db/db mice
MPC5
Ubiquitination degradation of GPX4 ↓[58]
Germacronein vivodb/db micemtDNA/cGAS/STING pathway ↓[159]
Tanshinone IIAin vivo
in vitro
db/db mice
MPC5
ELAVL1-ACSL4 axis ↓[160]
Schisandrin Ain vivo
in vitro
STZ-induced mice
HRGECs
AdipoR1/AMPK pathway ↑[161]
Notes: STZ, streptozotocin; HK-2, human renal tubular epithelial cells; HUVECs, human umbilical vein endothelial cells; MPC5, the mouse podocyte cell line; HRGECs, Human renal glomerular endothelial cells; GPX4, glutathione peroxidase 4; xCT, solute carrier family 7 member 11; GSH, glutathione reduced; GSSG, glutathione disulfide; ACSL4, acyl-CoA synthetase long-chain family member 4; FTH1, ferritin heavy chain 1; Nrf2, nuclear factor erythroid 2-related factor 2; Rac1, ras-related C3 botulinum toxin substrate 1; NOX1, NADPH oxidase 1; SLC7A11, solute carrier family 7 member 11; mtDNA, mitochondrial DNA; cGAS, cyclic GMP-AMP synthase; STING, stimulator of interferon genes; ELAVL1, elav like rna binding protein 1; AMPK, amp-activated protein kinase; ↓, negative regulation, downregulate, inhibit; ↑, positive regulation, upregulate, promote.
This diagram illustrates how natural products exert their effects by regulating three key pathways: ferroptosis, antioxidant pathways, and immunity. Oxidative stress serves as the core driver of ferroptosis, and enhanced antioxidant capacity can directly inhibit ferroptosis. When ferroptosis is suppressed, inflammation-related immune activation is correspondingly attenuated. Simultaneously, the balanced state of immune pathways conversely reduces oxidative stress triggers, ultimately forming the aforementioned dynamic regulatory network. (Notes: OH, Hydroxyl radical; PUFAs, polyunsaturated fatty acids; LOOH, lipid hydroperoxide; DAMPs, damage-associated molecular patterns; ROS, reactive oxygen species; SOD, superoxide dismutase; GSH, glutathione; Nrf2, nuclear factor erythroid 2-related factor 2; HO-1, heme oxygenase-1; NF-κB, nuclear transcription factor κB; GPX4, glutathione peroxidase 4; ↓, negative regulation, downregulate, inhibit; ↑, positive regulation, upregulate, promote.)

3.5. Anti-Fibrosis: A Key Intervention in Mid-to-Late-Stage DKD

The TGF-β1/Smad signaling pathway serves as a core driver of fibrosis in DKD [162]. Natural medicines can exert antifibrotic effects by directly blocking this pathway, synergistically interacting with other signaling pathways (e.g., MAPK, Wnt/β-catenin), and regulating upstream metabolic pathways, thereby providing crucial intervention strategies for mid-to-late-stage DKD (with detailed research findings summarized in Table 8).
In animal studies, natural medicines provide robust pathological evidence for ameliorating fibrosis in DKD: for example, Fuxin Granules can block epithelial–mesenchymal transition (EMT) by inhibiting the TGF-β1/Smad pathway [163], while asiatic acid simultaneously suppresses the TGF-β1/Smad3 signaling pathway and enhances extracellular matrix (ECM) degradation [164], resulting in reduced renal ECM deposition supported by clear pathological evidence. However, clinical translation faces substantial limitations: long-term administration of natural medicines lacks clinical evidence supporting their ability to reverse fibrosis in moderate-to-severe DKD, and their long-term efficacy remains unclear. The key contradiction lies in the unelucidated synergistic interaction mechanisms between inhibition of the TGF-β signaling pathway and autophagic/inflammatory pathways. For instance, whether combined therapy of antifibrotic and anti-inflammatory drugs produces additive effects has not been addressed by current research.
Table 8. Drugs involved in the regulation of TGF-β and its related pathways.
Table 8. Drugs involved in the regulation of TGF-β and its related pathways.
Natural ProductsExperiment TypeDisease ModelMechanismReference
Ginkgo biloba leaf extractin vivo
in vitro
STZ-induced rats
HBZY-1
TGF-β ↓[165]
Luteolinin vivoSTZ-induced miceAMPK pathway ↑, NF-κB pathway ↓, TGF-β1 ↓[166]
Scutellarinin vivoSTZ-induced miceTGF-β1 pathway ↓, MAPKs pathway ↓, Wnt/β-catenin pathway ↓[167]
Krill oilin vivo
in vitro
STZ-induced mice
MCs
TGF-β pathway ↓[168]
Danggui Buxue decoctionin vivoHFD-induced ratsTGF-β1/Smad pathway ↓[16]
Dendrobium mixturein vivodb/db miceTGF-β1/Smad pathway ↓[169]
Fuxin Granulesin vivodb/db miceTGF-β1/Smad pathway ↓, VEGF/VEGFR2 pathway ↓[163]
Astragaloside IVin vivo
in vitro
STZ-induced rats
RMC
TGF-β1/Smad/miR-192 pathway ↓[15]
The combination of ursolic acid and empagliflozinin vivo
in vitro
STZ-induced rats
HBZY-1
TGF-β/Smad/MAPK pathway ↓[170]
Qishen Yiqi Dripping Pillin vivoSTZ-induced ratsWnt/β-catenin pathway ↓, TGF-β/Smad2 pathway ↓[171]
Asiatic acidin vivo
in vitro
STZ-induced rats
HK-2
TGF-β1/Smad3 pathway ↓[164]
Crocinin vivoSTZ-induced miceCYP4A11/PPARγ pathway ↑, TGF-β1/Smad3 pathway ↓[172]
Magnoflorinein vivo
in vitro
STZ-induced rats
SV40-MES13
Ubiquitination of KDM3A ↑, TGIF1 ↑, TGF-β1/Smad2/3 pathway ↓[173]
Taurinein vivoSTZ-induced ratsTGF-β/Smad2/3 pathway ↓, p38 MAPK pathway↓[174]
Cyanidin-3-glucosidein vivoSTZ-induced ratsTGF-β1/Smad2/3 pathway ↓[175]
Chrysophanolin vivo
in vitro
STZ-induced mice
AB8/13
TGF-β/EMT pathway ↓[176]
Huangkui capsule in combination with metforminin vivo
in vitro
STZ-induced rats
HK-2
Klotho/TGF-β1/p38 pathway ↓[177]
Notes: STZ, streptozotocin; HBZY-1, rat mesangial cells; MCs, mouse mesangial cells; HK-2, human renal tubular epithelial cells; HFD, high fat diet; RMCs, rat mesangial cells; HRMCs, Primary human renal mesangial cells; SV40-MES13, mesangial cell line; AB8/13, the immortalized human podocytes AB8/13; TGF-β, transforming growth factor-β; VEGF, Vascular endothelial growth factor; AMPK, amp-activated protein kinase; NF-κB, nuclear transcription factor κB; MAPK, mitogen-activated protein kinases; VEGFR2, vascular endothelial growth factor receptor 2; miR, miRNA; CYP4A11, cytochrome P450 family 4 subfamily A member 11; PPARγ, peroxisome proliferator-activated receptor gamma; KDM3A, lysine demethylase 3A; TGIF1, tg—interacting factor 1; p38, p38 mitogen-activated protein kinase; EMT, epithelial–mesenchymal transition; ↓, negative regulation, downregulate, inhibit; ↑, positive regulation, upregulate, promote.

4. Limitations of Existing Research

Natural medicines exhibit unique advantages in the prevention and treatment of DKD through their core mechanisms: precision targeting, cross-mechanism synergy, and pathological coverage overlap. They particularly exert multidimensional protective effects through the “anti-ferroptosis–antioxidation–immunity” cascade regulation. However, existing research still faces substantial limitations, mainly manifested in three aspects:
  • Low-quality evidence: Over 90% of studies are conducted in cell and animal models, accompanied by limited clinical data and small sample sizes.
  • Inadequate model applicability: The commonly used streptozotocin (STZ)-induced DKD model predominantly displays acute kidney injury characteristics, which is severely inconsistent with the chronic pathological process of human DKD—marked by “long-term hyperglycemic injury followed by gradual glomerulosclerosis—and fails to replicate the complex clinical complications commonly seen in patients, such as metabolic disorders and vascular lesions. Consequently, experimental outcomes have limited clinical relevance, failing to recapitulate the “progressive renal function decline” observed in human DKD. Furthermore, it fails to replicate complex clinical complications commonly observed in clinical settings, such as metabolic disorders and vascular lesions, thereby limiting the clinical relevance of experimental findings [178].
  • Research design deficiencies: In animal studies, researchers often use drug doses far exceeding human tolerable levels to achieve obvious efficacy. However, the dose–response relationships and toxic reactions observed at these high doses do not directly correspond to the safe dosage range for human clinical use. This directly leads to the translational dilemma where treatments are effective in animals but ineffective in humans. Additionally, critical experimental parameters—such as optimal dosage, administration methods, and long-term safety profiles of natural medicines—are frequently lacking. Multi-targeted cross-regulatory networks and cascading molecular interaction mechanisms remain incompletely elucidated, while contradictions such as disease progression adaptation and clinical positioning strategies remain unresolved.
  • The “file-drawer problem”: This phenomenon is common in preclinical research—positive results are more likely to be published, while numerous negative or weakly positive findings are left unpublished due to “insufficient academic value.” This introduces a selective bias into the existing evidence chain in the literature, failing to accurately reflect a drug’s actual development potential.
Given these limitations, future research should focus on three key areas: First, it should conduct dose-escalation clinical trials for promising compounds such as astragaloside IV to systematically validate their clinical efficacy and safety. Second, it should define key parameters such as autophagy activity thresholds and iron metabolism-related biomarkers, and utilize molecular biology experiments to elucidate cascading interaction mechanisms, thereby resolving the aforementioned core contradictions. Third, it should establish a quantitative association model linking “target–biomarker–therapeutic efficacy” to provide high-quality evidence supporting the clinical translation of natural medicines for DKD.

5. Advantages of Natural Medicines

In the field of DKD treatment, compared to existing standard treatments such as chemically synthesized drugs and surgical interventions, natural medicines demonstrate irreplaceable advantages in multiple dimensions, owing to their strong compatibility with the pathological characteristics and treatment needs of DKD. These advantages can be summarized in four core aspects: cultural acceptance, resource availability, mechanism of action, and safety, collectively laying a robust foundation for effective DKD intervention.
From a cultural perspective, natural medicines have accumulated rich experience through long-term practice based on traditional Chinese medicine theory, particularly in chronic disease management, where a mature cognitive framework has formed. Patients also exhibit high acceptance of natural medicine-based treatments. As DKD requires long-term management, the use of natural medicines not only improves patients’ treatment adherence but also aligns with DKD’s treatment objectives, which emphasize “long-term control and delaying progression.”
In addition to the solid foundation laid by cultural identity, the inherent advantages of natural medicines in resource availability also offer a sustainable material foundation for DKD treatment. Natural medicines are rich in species diversity and widely sourced, not only meeting the basic requirements of clinical practice but also serving as an important source for the development of new DKD drugs. Many chemically synthesized drugs (such as certain anti-inflammatory and hypoglycemic drugs) were originally derived from natural products. However, DKD treatment still grapples with the shortage of drugs targeting multiple pathological pathways. The abundant resources of natural medicines provide broad prospects for developing new drugs tailored to DKD’s complex pathophysiology.
At the mechanistic level, unlike chemical drugs (such as MRAs) that act on a single pathway, the “multi-targeted, multi-step holistic regulation” characteristic of natural medicines precisely aligns with DKD’s core pathological feature—synergistic pathogenesis involving multiple mechanisms. Take the natural medicine rhubarb as an example. Its active components—including emodin, β-sitosterol, and aloe-emodin—can regulate multiple targets closely linked to DKD pathogenesis, such as TP53, CASP8/CASP3, MYC/JUN, and PTGS2, to simultaneously intervene through multiple pathways: “inhibiting excessive renal cell apoptosis, alleviating renal inflammation, and delaying fibrosis” [179]. This holistic regulatory effect can more comprehensively improve renal function indicators in DKD patients (such as urine protein and serum creatinine), offering new insights into addressing the complex pathological challenges of DKD.
The safety advantages of natural medicines further underscore their necessity in DKD’s long-term treatment. DKD patients typically require long-term medication to manage their condition, but chemically synthesized drugs (such as ACEIs) can cause adverse reactions like coughing and hyperkalemia with long-term use, adding to patients’ burden. In contrast, most natural medicines have been validated through centuries of clinical practice, and when used appropriately, the incidence of adverse reactions is significantly lower. Certain food–medicinal dual-purpose species (such as ginger, which can help dispel cold) are even more widely recognized for their safety due to their frequent daily use. This high level of safety not only reduces long-term medication-related risks for DKD patients but also supports treatment continuity, preventing treatment interruptions due to side effects.
In summary, the four major advantages of natural medicines are not isolated but precisely align with the core needs of DKD treatment: cultural acceptance can address compliance challenges in long-term DKD treatment, abundant resources can fill the gap in new DKD drug development, multi-targeted mechanisms can overcome intervention bottlenecks in complex DKD pathologies, and favorable safety profiles meet the core requirements for long-term DKD medication. It is precisely this high degree of alignment with DKD’s treatment needs that positions natural medicines uniquely in DKD treatment. They not only serve as an effective supplement to existing treatment regimens but also hold promise as a key direction to address current challenges in DKD treatment.

6. Development Bottlenecks of Natural Medicines

However, compared to chemically synthesized drugs, natural medicines also have notable drawbacks, mainly in three aspects: significant challenges in quality control, ongoing concerns regarding safety, and relatively slow therapeutic efficacy. These drawbacks pose significant challenges to the development and promotion of natural medicines. Specific analyses are as follows.

6.1. Difficulties in Drug Quality Control

Quality control for natural medicines is significantly more challenging than that for single-component chemically synthesized drugs. From a compositional perspective, each natural medicine typically contains hundreds or even thousands of chemical components, making it challenging to accurately identify the core therapeutic components and their mechanisms of action. Additionally, many natural medicines face challenges such as poor water solubility, chemical instability, and low bioavailability [180,181]. From an external perspective, factors such as the origin, harvest time, and processing methods of natural medicines vary significantly. Additionally, the current lack of established quality control standards, coupled with the complex market environment, further complicates quality control. These factors hinder the assurance of consistent active ingredients and quality stability in natural medicines, leading to fluctuations in therapeutic efficacy and posing significant challenges to quality control, clinical research, and standardized production.

6.2. Uncertainty About Drug Safety

Natural medicines are not absolutely safe and carry multiple safety risks. On the one hand, some natural medicines contain potentially toxic components—for example, Tripterygium wilfordii contains triptolide and other toxic constituents, and improper use can readily result in safety hazards. On the other hand, in clinical practice, natural medicines are often combined with other drugs. However, their complex composition makes it difficult to predict the likelihood and specific manifestations of drug–drug interactions. Furthermore, even if no apparent abnormalities occur during short-term use, long-term administration may lead to drug tolerance, and toxic constituents may accumulate in the body.
The real-world harm posed by these risks has been clinically validated: toxic constituents can result in serious adverse reactions. For example, improper use of Tripterygium wilfordii can lead to serious consequences such as myelosuppression and liver injury [182]; drug–drug interactions elevate the risk of clinical medication; and once adverse reactions occur, the complex composition of natural medicines makes it challenging to quickly and accurately identify the underlying cause and address the issue, further endangering patient safety.

6.3. Relatively Slow Treatment Effect

Compared to chemically synthesized drugs or surgical treatments, the therapeutic effects of natural medicines are generally milder and require a longer treatment course to achieve noticeable therapeutic outcomes. This characteristic stems from the “gentle regulation” mechanism of action of natural medicines and also determines the limitations in the onset of efficacy. Therefore, when used in treating diabetic nephropathy, natural medicines are more suitable for patients with relatively stable disease conditions. However, during acute disease flares or in severe cases, their therapeutic effects are far inferior to those of chemically synthesized drugs and cannot replace the emergency rescue function of surgical interventions.
Overall, the complexity of quality control, safety uncertainty, and delayed onset of efficacy collectively constitute the core bottlenecks in the development of natural medicines. These bottlenecks not only hinder their standardized, large-scale development but also limit their application in critical clinical scenarios to some extent. However, they precisely point the direction for technological innovation: by establishing precise quality control systems, developing toxicity detection technologies, and optimizing dosage forms, we can gradually overcome these bottlenecks.

7. Technological Innovations and Solutions

Natural compounds exhibit unique potential in the treatment of DKD, but issues such as low bioavailability, limited targeting precision, and safety concerns have long hindered their clinical translation. In recent years, the establishment of a translational roadmap centered on “nanodelivery platforms–formulation redesign–synthetic biology” (Figure 5), coupled with an R&D model supported by “multi-omics analysis–network pharmacology–AI-driven target prediction,” offers multidisciplinary solutions to overcome these bottlenecks through cross-disciplinary innovation. Key practical approaches and challenges are outlined below.
This figure visually presents the key directions of current pharmaceutical technology innovations, which mainly focus on four core areas: nanodelivery systems, formulation technologies, biotransformation technologies, and biological research methods.

7.1. Development of a Transformation Roadmap: Multi-Technology Synergy in Overcoming Natural Compound Application Barriers

Addressing the core limitations of natural compounds, the stepwise application of nanodelivery technology, formulation redesign, and synthetic biology constitutes a translational roadmap spanning “delivery–formulation–structure.” This approach enhances the feasibility of clinical translation through specific technical optimizations.

7.1.1. Nanodelivery Systems

Nanodelivery systems utilize carriers such as natural polymers, synthetic polymers, or exosomes to load natural compounds through mechanisms like hydrophobic interactions and electrostatic adsorption. By regulating particle size and surface charge, these systems achieve controlled drug release and targeted accumulation [183,184]. Through modification of carrier materials and structural design, they address issues such as poor water solubility and susceptibility to degradation in vivo, while simultaneously enhancing renal targeting efficiency [185]. For instance, curcumin and epigallocatechin gallate exhibit therapeutic potential for diabetic nephropathy, but both suffer from poor water solubility and low bioavailability. Free curcumin exhibits a solubility of merely 1.268 ± 0.120 μg/mL, whereas shellac and locust bean gum-coacervated curcumin/epigallocatechin gallate nanoparticles (CESL-NP) exhibit a solubility of 75.833 ± 1.896 μg/mL—nearly 60-fold higher. In STZ-induced diabetic nephropathy mouse models, CESL-NPs significantly reduced fasting blood glucose, creatinine, and blood urea nitrogen levels while improving renal and pancreatic function [186]; PLA nanoparticles loaded with Tinospora cordifolia Willd. (TC-PLA NPs) exerted renal protective effects in STZ-induced diabetic nephropathy rats by reducing the expression of inflammatory factors (TNF-α, IL-6) and stabilizing renal function indicators (Scr, BUN) [64].
Despite the remarkable efficacy of nanodelivery systems, technical limitations persist: While PLA-PEG nanomicelles can enhance targeting through surface modification, they lack DKD-specific ligands (such as molecules binding to kidney epithelial cell-specific receptors) [187,188,189,190]. Although exosome delivery systems exhibit excellent biocompatibility, they face challenges such as low extraction yields and targeting efficiency that is susceptible to interference from the in vivo microenvironment. Furthermore, empirical studies directly employing natural drugs for DKD treatment remain scarce [191,192,193,194].

7.1.2. Formulation Redesign

Beyond addressing natural compound delivery challenges through carrier-based nanodelivery systems, formulation redesign further breaks through application bottlenecks by improving dosage forms: Solid dispersion technology reduces drug crystallinity to enhance natural compound solubility [195]; liposome technology constructs bilayer membranes for controlled release to prolong the drug’s in vivo circulation time [196]; lysosomal conjugates utilize biomolecular specificity to achieve kidney-targeted delivery [197]; and combination formulations of natural compounds reduce the dosage of individual components and mitigate toxicity risks [177].
Specifically, addressing the low bioavailability of berberine due to poor solubility and insufficient membrane permeability, a highly bioavailable berberine solid dispersion formulation increases its bioavailability by 4-fold through inhibiting drug crystallization. In the db/db mouse DKD model, it effectively improves glomerular mesangial proliferation and renal function impairment [91]. Another example involves glycyrrhetinic acid liposomes loaded with carthamin yellow, which facilitate controlled release of carthamin yellow while enhancing drug stability, reducing side effects, and improving pharmacokinetic properties. This formulation effectively alleviates renal interstitial fibrosis in STZ-induced DKD rats [198]. Furthermore, baicalin–lysozyme conjugates leverage the specific affinity of lysosomes for renal tissue to elevate local drug concentrations in the kidney, significantly enhancing therapeutic efficacy in STZ-induced DKD rats [199]. Notably, a combined formulation of ursodeoxycholic acid and empagliflozin reduced urinary tract infections caused by high-dose empagliflozin monotherapy while lowering blood glucose levels in DKD model rats, and demonstrated superior inhibition of renal fibrosis compared to either drug alone [170].
However, formulation redesign still faces challenges at the clinical translation level: research on using lysosomal conjugates for the targeted treatment of diabetic kidney disease remains scarce, and there is a lack of data on combined use with commonly used DKD therapies such as SGLT2 inhibitors and ACE inhibitors. Standardized methods for optimizing the composition ratios in compound formulations are absent, making it difficult to ensure batch-to-batch consistency in therapeutic efficacy.

7.1.3. Bioconversion and Synthetic Biology

Beyond delivery optimization and formulation improvements, bioconversion and synthetic biology technologies provide innovative support for transformation roadmaps by leveraging the structural and functional properties of natural compounds: solid-state fermentation of edible fungi converts active ingredients in traditional Chinese medicine, enhancing their water solubility and absorption efficiency [200]; synthetic biology techniques modify the structures of natural compounds to retain activity while reducing toxicity [201].
For example, the efficacy of Astragalus membranaceus enhanced through solid-state fermentation with Paecilomyces cicadae demonstrated superior renal protective effects in STZ-induced DKD mouse models by regulating gut microbiota balance and protecting podocytes [93,202]; for natural compounds like celastrol, which possesses both activity and toxicity, demethylzeylasteral retains therapeutic effects on DKD rats through structural modification while reducing side effects [182]. Meanwhile, selenized tripterine phytosomes overcome application bottlenecks in high-glucose-induced podocyte models by enhancing water solubility and imparting sustained-release properties [83].
However, this technological approach also faces pressing challenges: the types and concentrations of microbial metabolites produced during solid-state fermentation are highly susceptible to environmental factors, and standardized fermentation processes remain elusive [203]. Furthermore, the long-term safety and in vivo metabolic pathways of synthetic biology-modified natural compound analogs remain unclear, necessitating additional toxicological data to support clinical translation.

7.2. Multi-Technology Integration Supports Precision Development of Natural Medicines for DKD

Building upon the resolution of core application barriers for natural compounds through transformation roadmaps, a multi-technology-integrated R&D model further supports the efficient development of natural medicines for DKD by addressing their complex composition and ambiguous mechanisms of action. By integrating multi-omics analysis, network pharmacology, and AI-based target prediction, a predictive model system linking “constituents-targets-pathways-diseases” has been established, providing technical assurance for drug screening and mechanism elucidation.

7.2.1. Synergistic Application of Multi-Omics and Network Pharmacology

This collaborative approach employs multi-omics technologies—including transcriptomics, metabolomics, and lipidomics—to first identify differentially expressed molecules (genes, lipids, metabolites) in the DKD pathological state. It then integrates network pharmacology to construct association networks linking natural compounds, potential targets, and disease pathways, thereby screening core functional targets. Finally, efficacy is validated through in vitro cell and in vivo animal experiments.
For instance, Xiao et al. predicted 85 potential targets for total berberine alkaloids via network pharmacology. Integrating STZ-DKD rat transcriptome data (121 differentially expressed genes), they identified AGEs-RAGE-TGFβ/Smad2 and PI3K-Akt as core pathways. Subsequent experiments further validated that modulating these pathways alleviates renal injury and fibrosis [204]. Similarly, Zhang et al. employed a combined approach of transcriptomics, network pharmacology, machine learning, and molecular docking/simulation techniques to reveal that Berberis integerrima targets 10 key genes through six active components. By synergistically regulating multiple signaling pathways, it exerts a protective effect against DKD [205].
However, this collaborative application model still faces practical bottlenecks: the fragmented nature of multi-omics data sources (such as inconsistent gene annotation standards across databases) complicates data integration and cross-validation [206]. Additionally, network pharmacology predictions yield false positives in target identification and pathway analysis, necessitating extensive experimental validation to narrow down candidates—significantly increasing R&D costs [207].

7.2.2. AI Target Prediction: A Critical Complement to Precision Screening

As a crucial complement to multi-omics and network pharmacology, AI-based target prediction technology enhances the precision of natural product screening through its efficient data processing capabilities. By integrating the structural data of natural compounds (e.g., from the PubChem database), DKD-related target data (e.g., from the OMIM database), and multi-omics differential molecular data, target prediction models are constructed. This approach enables the rapid matching of natural compounds with core DKD targets and the prediction of their binding affinities. [123,208].
Currently, Hakime Öztürk et al. have developed an end-to-end deep learning model named DeepDTA based on convolutional neural networks, which can predict drug-target affinities and provides an efficient tool for drug screening [209]. In the future, integrating DKD pathological microenvironment data (such as inflammatory factor concentrations and pH levels) to optimize the model could enable dynamic matching predictions across “compound–target–microenvironment.”
However, the application of current AI target prediction models remains constrained by data quality: model training relies on high-quality annotated data, yet natural compound activity data suffers from inconsistent annotation and insufficient sample sizes.
In summary, the translational roadmap integrating nanodelivery systems, formulation redesign, and synthetic biology constructs holds promise for systematically overcoming clinical translation barriers of natural compounds. Meanwhile, the R&D model integrating multi-omics, network pharmacology, and AI-based target prediction provides the technological foundation for efficient development of natural medicines for DKD. The industry currently faces challenges including insufficient targeting efficiency of nanocarriers, unclear safety profiles of synthetic biology-modified products, and limited data quality in AI models. Future efforts should focus on establishing standardized technical processes, conducting large-scale multicenter clinical studies, and building interdisciplinary data-sharing platforms. These measures will advance natural drug development toward precision, controllability, and clinical applicability, thereby generating more novel therapeutic candidates for DKD treatment.

8. Clinical Practice of Natural Medicines

However, current clinical treatment regimens for DKD still have limitations such as insufficient therapeutic specificity and poor long-term safety. Natural products, with their unique advantages of multi-target regulation and good safety, are gradually becoming an important direction for complementary treatment of DKD. The following section will summarize and analyze natural products with potential applications based on specific clinical research data, providing references for clinical treatment selection and future research directions (Table 9).
Table 9. Current Clinical Trial Evidence Supporting the Use of Natural Products for Treating DKD.
Table 9. Current Clinical Trial Evidence Supporting the Use of Natural Products for Treating DKD.
Natural ProductsConditionsDoseTest DurationPrimary OutcomeReference
Abelmoschus manihot2054 patients with CKD and proteinuria (≥150 mg/d)12 years: 2.5 g TID; 6 to 12 years: 1.5 g TID; 2 to 6 years: 1 g TID24 weeksProteinuria ↓[210]
Abelmoschus manihot413 patients with T2DM and DKD2.5 g TID24 weeksUrine albumin-to-creatinine ratio ↓[211]
Triptery
gium wilfordii hook f extract
65 patients with T2DM and DKD who had proteinuria levels ≥ 2.5 g/24 h and serum creatinine levels < 3 mg/dL120 mg daily for 3 months, followed by 60 mg daily for 3 months.6 monthsProteinuria ↓[212]
Resveratrol60 patients with T2DM and DKD500mg daily90 daysAlbuminuria ↓[213]
Zicuiyin88 patients with T2DM and DKDcrude drug amount 75 g, 150 mL, BID8 weekseGFR ↑[214]
Qidan Tangshen Granule219 patients with T2DM and DKD-3 months and 12 monthsHemoglobin A1c and albumin-to-creatinine ratio ↓[215]
Turmeric40 patients with T2DM and DKD22.1 mg, TID2 monthsProteinuria ↓, TGF-β ↓, IL-8 ↓[216]
Notes: DKD, diabetic kidney disease; CKD, Chronic Kidney Disease; T2DM, Type 2 Diabetes Mellitus; TID, three times daily; BID, twice daily; eGFR, estimated glomerular filtration rate; TGF-β, transforming growth factor-β; IL-8, interleukin 8; ↓, negative regulation, downregulate, inhibit; ↑, positive regulation, upregulate, promote.
  • Abelmoschus manihot
As the most well-established natural product for DKD treatment, it has been validated through multicenter clinical trials and long-term data and has been approved by the National Medical Products Administration for the treatment of chronic nephritis. It has a clear clinical application basis and is widely used in DKD treatment.
In patients with early-stage DKD, it demonstrated superior efficacy in reducing urinary albumin compared to losartan (50 mg/day), and the combination therapy with losartan showed significantly better efficacy than monotherapy [123]; A study involving 413 patients with type 2 diabetes (T2D) and DKD confirmed that its combination with irbesartan effectively reduces albuminuria and proteinuria [211]; further analysis of 2054 patients with CKD showed that the drug can reduce proteinuria while preserving kidney function, making it suitable for patients at different stages of kidney disease [210].
The existing evidence is based on multicenter, large-sample studies and includes long-term validation data, indicating a high level of evidence. However, data on the efficacy and safety of treatment for patients with end-stage DKD remain limited, and further studies are needed to address this gap.
  • Tripterygium wilfordii Hook. f. Extract
It is primarily used for controlling proteinuria in patients with DKD, particularly in advanced stages and those with overt proteinuria. It can serve as an adjunctive option when conventional treatments are ineffective. It has a distinct effect on reducing urinary protein levels: not only does it reduce the rate of kidney function decline in patients with advanced DKD, but it also demonstrates superior efficacy to valsartan. It also demonstrates greater efficacy in reducing overt proteinuria and controlling proteinuria in patients with normal estimated glomerular filtration rate (eGFR). However, its safety profile is a notable weakness, with a higher incidence of adverse reactions in clinical use, which may limit its widespread application. Close monitoring of adverse reactions is necessary during treatment [212,217].
Current studies have only confirmed short-term efficacy, and there is insufficient data to support long-term efficacy, leaving a significant gap in the evidence chain. The prospective clinical trial conducted by Xu, Zhao, and others [218] may provide additional evidence for assessing its long-term efficacy and safety, but no conclusive results have been reached yet.
  • Zicuiyin Decoction
It demonstrates unique advantages in patients with DKD and declining eGFR, particularly in those requiring improvement in renal function and gut microbiota balance, offering a new treatment direction for specific populations. Its efficacy is comprehensive and significant: it effectively improves renal function (reduces serum creatinine, increases eGFR), alleviates albuminuria and clinical symptoms, while regulating intestinal microbiota; studies have confirmed that its efficacy is even superior to that of Huangqi Capsules, performing better in patients with declining eGFR. No significant adverse reactions were observed in clinical observations, indicating good safety and high patient acceptance [214].
Current conclusions are based solely on data from small-scale trials and lack large-scale multicenter validation; the stability of long-term efficacy remains unclear, and the underlying mechanisms of action of the drug have not been fully elucidated, necessitating further research.
  • Resveratrol
It is primarily used as adjunctive therapy to angiotensin II receptor blockers (ARBs) for controlling urinary albumin in patients with T2DM and DKD. Preliminary studies suggest it may reduce urinary albumin excretion in patients with DKD, offering an alternative approach to patients with inadequate response to ARB therapy. No specific adverse reactions have been reported in existing small-scale studies; however, safety data remain insufficient and require validation through larger-scale studies [213].
The current level of evidence in this field remains low, with existing studies featuring limited sample sizes. There is a lack of comparative efficacy data across different dosage gradients, and no long-term follow-up results to support its claims. The precise efficacy and mechanism of action require further elucidation.
Notably, although numerous preclinical studies confirm that resveratrol significantly improves various pathological indicators of diabetic kidney disease (such as creatinine, blood urea nitrogen, and urine albumin-to-creatinine ratio) [219,220], the results of existing human clinical trials on resveratrol intervention for DKD exhibit heterogeneity. This may be related to its low water solubility and poor oral bioavailability [221,222].
  • Qidan Tangshen Granule and Curcumin
Both are being explored as adjunctive therapies for DKD: Qidan Tangshen Granule targets patients with T2DM and DKD, while short-term curcumin supplementation targets patients with overt DKD in T2DM. Qidan Tangshen Granule may provide clinical benefits by reducing oxidative stress, improving blood glucose levels, and enhancing renal function, demonstrating potential as an adjunctive therapy; short-term curcumin supplementation can reduce proteinuria and inflammatory factors (TGF-β, IL-8) in patients with overt T2DM-related DKD. Safety data for Qidan Tangshen Granule remain incomplete, while no adverse reactions were observed in studies of short-term curcumin supplementation, indicating good safety. Evidence for Qidan Tangshen Granule remains at the preliminary efficacy observation stage, lacking in-depth mechanistic studies and long-term validation; curcumin lacks large-scale, long-term follow-up validation data, with efficacy stability and applicable population boundaries still unclear [215,216].
  • Other natural products
Clinical trials of natural products such as Liuwei Dihuang Pills [223] and Tangshen Formula [224,225] for DKD are gradually being conducted, but research progress is currently limited, and no mature evidence chain has been established. Their efficacy and safety still need to be further supported by subsequent research data.
The incidence of DKD continues to rise, and existing treatment options struggle to fully meet clinical demands, making the clinical translation of natural products increasingly urgent. However, most studies in this field remain at the preliminary exploration or small-sample validation stage, facing significant limitations: on one hand, there is a lack of unified standards for precise efficacy assessment—differences in endpoint indicators (such as urine albumin-to-creatinine ratio, estimated glomerular filtration rate) and evaluation timepoints across studies make it difficult to compare results horizontally and integrate them systematically; on the other hand, the elucidation of mechanisms of action remains at the level of “phenomenological description.” The key molecular targets and signaling pathway interactions through which natural products modulate DKD pathological pathways (such as AGEs-RAGE and NLRP3 inflammasome) have not been fully elucidated, failing to provide a reasonable explanation for therapeutic efficacy variations. Second, there is a severe lack of safety evidence. Existing studies predominantly focus on short-term efficacy observations, with scarce long-term safety follow-up data spanning one year or more. Coverage of critical safety information—such as effects on hepatic and renal metabolism and drug interactions—remains extremely limited. Industrial-level challenges are equally pronounced: the uncertainty in efficacy stemming from the aforementioned research limitations, coupled with the complex composition of natural products and difficulty in quality control, has resulted in low participation willingness among pharmaceutical companies capable of conducting multi-center clinical trials. This further exacerbates a vicious cycle where insufficient research evidence leads to limited industrial investment, making it even harder to accumulate relevant evidence.
Moreover, the inherent properties of natural substances pose inherent challenges for research: they are typically multicomponent mixtures containing various bioactive compounds that may exhibit synergistic or antagonistic effects. This not only complicates the identification of the basis for pharmacological efficacy but may also mask the specific effects of the core target compound, posing significant challenges for elucidating mechanisms of action and ensuring quality control.
To overcome existing bottlenecks, generate high-quality research outcomes, and provide patients with more effective treatment options, a multidimensional approach is required: on one hand, comprehensively elevate the level of evidence by expanding sample sizes, extending follow-up periods, clarifying dose–response relationships, optimizing formulation processes to enhance bioavailability, establishing standardized dose conversion systems, and strengthening multidimensional safety monitoring. On the other hand, leveraging new technologies to specifically address pain points such as insufficient sample size, unclear mechanisms, and inadequate monitoring, while emphasizing international collaboration and multidisciplinary integration; cross-regional, multicenter trials can reduce the limitations of single studies, and synergistic collaboration among basic medicine, clinical medicine, data science, and other disciplines can form a complete closed-loop from mechanism research through clinical trial design to outcome analysis, further enhancing research quality. Advancing research along these directions will provide more reliable support for the clinical application of natural products in DKD treatment.

9. Conclusions

Natural products have demonstrated distinct advantages in DKD intervention. Integrating core research evidence, their mechanisms of action can be summarized into three key patterns: First, they precisely target critical nodes in pathological pathways such as AGEs-RAGE and NLRP3 inflammasome, directly acting on core pathological processes. Second, they form multidimensional protective chains through cross-mechanism synergistic regulation. Third, they cover cross-linkages across multidimensional pathological stages, ultimately constructing a comprehensive renal protection network. Preclinical experiments not only validate that these natural products effectively alleviate typical symptoms like proteinuria and delay renal fibrosis progression but also, for the first time, clarify their specific mechanisms of action in iron death regulation and metabolism, podocyte protection, anti-inflammation, and anti-fibrosis. This provides crucial theoretical and experimental foundations for subsequent research.
However, current research still faces several core challenges: First, the overall level of evidence remains low, with limited clinical data and generally small sample sizes in existing studies, resulting in limited persuasiveness. Second, the commonly used STZ model exhibits significant differences from the chronic progression of human DKD. Combined with high-dose experimental designs in some studies, this further exacerbates the difficulties in clinical translation. Third, natural products inherently suffer from low bioavailability and insufficient targeting specificity. Their complex composition significantly complicates quality control and dose management. Finally, their multi-targeted mechanisms remain incompletely elucidated, with critical regulatory parameters—such as autophagy activation thresholds—not fully defined. This undoubtedly limits the depth of mechanistic studies and reduces the willingness of pharmaceutical companies capable of conducting multi-center clinical trials to participate.
Fortunately, a series of innovative achievements has emerged, providing crucial support for overcoming these bottlenecks. Examples include the “anti-ferroptosis–antioxidation–immunity” cascade regulatory framework, the “nanodelivery–formulation reconstruction–synthetic biology” synergistic translation roadmap, and the “multi-omics–network pharmacology–AI target prediction” precision R&D paradigm. These achievements lay the groundwork for research breakthroughs across multiple dimensions, including technology, modeling, and pathways.
Moving forward, natural product research in DKD intervention should prioritize the following directions: First, optimize clinical translation technologies by developing DKD-specific targeted nanocarriers while standardizing formulation production processes and synthetic biology-related techniques to enhance translational feasibility. Second, establish a precision R&D system by building interdisciplinary data-sharing platforms to integrate multi-domain research data, further refining AI-based target prediction and mechanism analysis models to boost R&D efficiency. Third, conduct phased, multi-center clinical trials to systematically validate candidate drug efficacy and safety while actively exploring the potential of combination therapies, providing more comprehensive evidence for clinical application. Fourth, deepen research on mechanisms of action to clarify key parameter thresholds (e.g., autophagy activity thresholds) and intermolecular interaction mechanisms. Ultimately, establish a quantitative linkage system connecting “target–biomarker–efficacy” to advance the transformation of natural products into precision therapeutics for DKD.

Author Contributions

L.N. and X.W. conceived and designed the study. M.G. and L.N. wrote the article. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by grants from the National Natural Science Foundation of China (82200807, 82370696). Outstanding Young and Middle-aged Talents Training Program of Zhongnan Hospital of Wuhan University (ZNYQ2022007). Translational Medicine and Interdisciplinary Research Joint Fund of Zhongnan Hospital of Wuhan University (ZNJC202313). Medical Science and Technology Innovation Platform Support Project of Zhongnan Hospital of Wuhan University (PTXM2025002). Basic–Clinical Joint Construction Project of Wuhan University (JCZN2022005). Open Foundation of Hubei Provincial Key Laboratory of Tumor Microenvironment and Immunotherapy (China Three Gorges University: 2025ZLKF03).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

The following abbreviations are used in this manuscript:
DKDdiabetic kidney disease
TGF-βtransforming growth factor-β
T2DMtype 2 diabetes mellitus
CKDchronic kidney disease
SGLT2sodium-glucose cotransporter 2
ESKDend-stage kidney disease
GLP-1glucagon-like peptide 1
MRAsmineralocorticoid receptor antagonists
SGLT2iSGLT-2 inhibitors
Smadsmall mothers against decapentaplegic
AGEsadvanced glycation end products
GIPglucose-dependent insulinotropic polypeptide
GLP-1glucagon-like peptide-1
GFRglomerular filtration rate
RAASrenin–angiotensin–aldosterone system
ECMextracellular matrix
ILinterleukin
TNF-αtumor necrosis factor-α
ROSreactive oxygen species
RAGEreceptor for advanced glycation end products
NF-κBnuclear transcription factor κB
p38p38 mitogen-activated protein kinase
MAPKmitogen-activated protein kinases
NLRP3NOD-like receptor family pyrin domain containing 3
Nrf2nuclear factor erythroid 2-related factor 2
JAK1janus kinase 1
STAT3signal transducer and activator of transcription 3
GPX4glutathione peroxidase 4
TGtriglycerides
ATGLadipose triglyceride lipase
SIRT1silent information regulator sirtuin 1
AMPKamp-activated protein kinase
HNF4Ahepatocyte nuclear factor 4 alpha
SCAPsterol regulatory element-binding protein cleavage-activating protein
SREBP2sterol regulatory element-binding protein 2
LDLrlow density lipoprotein receptor
PCp-cresol
PCSp-cresol sulfate
TLR4toll-like receptor 4
mTORmechanistic target of rapamycin
TFEBtranscription factor EB
S6K1ribosomal protein S6 kinase beta-1
LC3microtubule-associated protein 1 light chain 3
PI3Kphosphoinositide 3-kinase
AKTprotein kinase B
PERKprotein kinase R-like endoplasmic reticulum kinase
eIF2αeukaryotic translation initiation factor 2 alpha
ATF4activating transcription factor 4
EGFRepidermal growth factor receptor
PPARγperoxisome proliferator-activated receptor gamma
FoxO1forkhead box O1
IRE-1αinositol requiring enzyme 1 alpha
Bcl-2B-cell Lymphoma 2 protein
BaxBcl-2 Associated X protein
NOX 4nadph oxidase 4
ASCapoptosis-associated speck-like protein containing a CARD
PAR-1protease-activated receptor 1
α-SMAalpha-smooth muscle actin
HO-1heme oxygenase-1
AREantioxidant response element
miRmiRNA
ARandrogen receptor
ERKextracellular signal-regulated kinase
ACSL4acyl-CoA synthetase long-chain family member 4
xCTsolute carrier family 7 member 11
FTH1ferritin heavy chain 1
NCOA4nuclear receptor coactivator 4 downregulated
ELAVL1elav like rna binding protein 1
AdipoR1adiponectin receptor 1
mtDNAmitochondrial DNA
cGAScyclic GMP-AMP synthase
STINGstimulator of interferon genes
VEGFvascular endothelial growth factor
KDM3Alysine demethylase 3A
CYP4A11cytochrome P450 family 4 subfamily A member 11
EMTepithelial–mesenchymal transition
TP53tumor protein p53
CASP8caspase 8
CASP3caspase 3
MYCv-myc avian myelocytomatosis viral oncogene homolog
JUNv-jun avian sarcoma virus 17 oncogene homolog
PTGS2prostaglandin-endoperoxide synthase 2
ACEIangiotensin converting enzyme inhibitor
PLA-PEGpoly lactic acid-polyethylene glycol
ARBangiotensin II receptor blocker

References

  1. IDF. Diabetes Atlas. Available online: https://diabetesatlas.org/ (accessed on 12 March 2025).
  2. Forouhi, N.G.; Wareham, N.J. Epidemiology of Diabetes. Medicine 2014, 42, 698–702. [Google Scholar] [CrossRef]
  3. Thomas, M.C.; Cooper, M.E.; Zimmet, P. Changing Epidemiology of Type 2 Diabetes Mellitus and Associated Chronic Kidney Disease. Nat. Rev. Nephrol. 2016, 12, 73–81. [Google Scholar] [CrossRef]
  4. Stevens, P.E.; Ahmed, S.B.; Carrero, J.J.; Foster, B.; Francis, A.; Hall, R.K.; Herrington, W.G.; Hill, G.; Inker, L.A.; Kazancıoğlu, R.; et al. Kidney Disease: Improving Global Outcomes (KDIGO). CKD Work Group KDIGO 2024 Clinical Practice Guideline for the Evaluation and Management of Chronic Kidney Disease. Kidney Int. 2024, 105, S117–S314. [Google Scholar] [CrossRef]
  5. Luk, A.; Chan, J.C.N. Diabetic Nephropathy—What Are the Unmet Needs? Diabetes Res. Clin. Pract. 2008, 82 (Suppl. S1), S15–S20. [Google Scholar] [CrossRef]
  6. Heerspink, H.J.L.; Parving, H.-H.; Andress, D.L.; Bakris, G.; Correa-Rotter, R.; Hou, F.-F.; Kitzman, D.W.; Kohan, D.; Makino, H.; McMurray, J.J.V.; et al. Atrasentan and Renal Events in Patients with Type 2 Diabetes and Chronic Kidney Disease (SONAR): A Double-Blind, Randomised, Placebo-Controlled Trial. Lancet 2019, 393, 1937–1947, Erratum in Lancet 2019, 393, 1936. [Google Scholar] [CrossRef]
  7. Pandey, A.K.; Bhatt, D.L.; Cosentino, F.; Marx, N.; Rotstein, O.; Pitt, B.; Pandey, A.; Butler, J.; Verma, S. Non-Steroidal Mineralocorticoid Receptor Antagonists in Cardiorenal Disease. Eur. Heart J. 2022, 43, 2931–2945, Erratum in Eur. Heart J. 2022, 43, 4391. [Google Scholar] [CrossRef] [PubMed]
  8. Kintscher, U.; Bakris, G.L.; Kolkhof, P. Novel Non-Steroidal Mineralocorticoid Receptor Antagonists in Cardiorenal Disease. Br. J. Pharmacol. 2022, 179, 3220–3234. [Google Scholar] [CrossRef] [PubMed]
  9. Kaze, A.D.; Zhuo, M.; Kim, S.C.; Patorno, E.; Paik, J.M. Association of SGLT2 Inhibitors with Cardiovascular, Kidney, and Safety Outcomes among Patients with Diabetic Kidney Disease: A Meta-Analysis. Cardiovasc. Diabetol. 2022, 21, 47. [Google Scholar] [CrossRef]
  10. Guedes, M.; Pecoits-Filho, R. Can We Cure Diabetic Kidney Disease? Present and Future Perspectives from a Nephrologist’s Point of View. J. Intern. Med. 2022, 291, 165–180. [Google Scholar] [CrossRef]
  11. Sun, D.L.; Guo, Z.Y.; Liu, W.Y.; Zhang, L.; Zhang, Z.Y.; Hu, Y.L.; Li, S.F.; Zhang, M.Y.; Zhang, G.; Wang, J.J.; et al. Astragaloside IV Alleviates Podocyte Injury in Diabetic Nephropathy through Regulating IRE-1α/NF-κ B/NLRP3 Pathway. Chin. J. Integr. Med. 2025, 31, 422–433. [Google Scholar] [CrossRef] [PubMed]
  12. Xing, L.; Fang, J.; Zhu, B.; Wang, L.; Chen, J.; Wang, Y.; Huang, J.; Wang, H.; Yao, X. Astragaloside IV Protects against Podocyte Apoptosis by Inhibiting Oxidative Stress via Activating PPARγ-Klotho-FoxO1 Axis in Diabetic Nephropathy. Life Sci. 2021, 269, 119068. [Google Scholar] [CrossRef]
  13. He, J.; Cui, J.; Shi, Y.; Wang, T.; Xin, J.; Li, Y.; Shan, X.; Zhu, Z.; Gao, Y. Astragaloside IV Attenuates High-Glucose-Induced Impairment in Diabetic Nephropathy by Increasing Klotho Expression via the NF-κ B/NLRP3 Axis. J. Diabetes Res. 2023, 2023, 7423661. [Google Scholar] [CrossRef]
  14. Lyu, X.; Zhang, T.-T.; Ye, Z.; Chen, C. Astragaloside IV Mitigated Diabetic Nephropathy by Restructuring Intestinal Microflora and Ferroptosis. Mol. Nutr. Food Res. 2024, 68, e2300734. [Google Scholar] [CrossRef] [PubMed]
  15. Mao, Q.; Chen, C.; Liang, H.; Zhong, S.; Cheng, X.; Li, L. Astragaloside IV Inhibits Excessive Mesangial Cell Proliferation and Renal Fibrosis Caused by Diabetic Nephropathy via Modulation of the TGF-Β1/Smad/miR-192 Signaling Pathway. Exp. Ther. Med. 2019, 18, 3053–3061. [Google Scholar] [CrossRef] [PubMed]
  16. Zhao, Y.; Wang, X.; Gu, L.; Li, Z.; Zhu, J.; Wang, W.; Zhang, L.; Xue, M. Efficacy of Danggui Buxue Decoction on Diabetic Nephropathy-Induced Renal Fibrosis in Rats and Possible Mechanism. J. Tradit. Chin. Med. 2023, 43, 507–513. [Google Scholar] [CrossRef]
  17. Zhang, Z.T.; Qi, Y.; Chen, P.; Chen, L.; Jiang, Y.; Fan, Z.; Guan, H.; Bai, L.; Liu, J.; Zhao, D.; et al. Dang-Gui-Bu-Xue Decoction against Diabetic Nephropathy via Modulating the Carbonyl Compounds Metabolic Profile and AGEs/RAGE Pathway. Phytomed. Int. J. Phytother. Phytopharm. 2024, 135, 156104. [Google Scholar] [CrossRef]
  18. Cohen, M.P. Aldose Reductase, Glomerular Metabolism, and Diabetic Nephropathy. Metabolism 1986, 35, 55–59. [Google Scholar] [CrossRef] [PubMed]
  19. Hodgkinson, A.D.; Søndergaard, K.L.; Yang, B.; Cross, D.F.; Millward, B.A.; Demaine, A.G. Aldose Reductase Expression Is Induced by Hyperglycemia in Diabetic Nephropathy. Kidney Int. 2001, 60, 211–218. [Google Scholar] [CrossRef]
  20. Vistoli, G.; De Maddis, D.; Cipak, A.; Zarkovic, N.; Carini, M.; Aldini, G. Advanced Glycoxidation and Lipoxidation End Products (AGEs and ALEs): An Overview of Their Mechanisms of Formation. Free. Radic. Res. 2013, 47, 3–27. [Google Scholar] [CrossRef]
  21. Mitrofanova, A.; Fontanella, A.M.; Merscher, S.; Fornoni, A. Lipid Deposition and Metaflammation in Diabetic Kidney Disease. Curr. Opin. Pharmacol. 2020, 55, 60–72. [Google Scholar] [CrossRef]
  22. Hou, Y.; Tan, E.; Shi, H.; Ren, X.; Wan, X.; Wu, W.; Chen, Y.; Niu, H.; Zhu, G.; Li, J.; et al. Mitochondrial Oxidative Damage Reprograms Lipid Metabolism of Renal Tubular Epithelial Cells in the Diabetic Kidney. Cell. Mol. Life Sci. 2024, 81, 23. [Google Scholar] [CrossRef]
  23. Mitrofanova, A.; Burke, G.; Merscher, S.; Fornoni, A. New Insights into Renal Lipid Dysmetabolism in Diabetic Kidney Disease. World J. Diabetes 2021, 12, 524–540. [Google Scholar] [CrossRef]
  24. Herman-Edelstein, M.; Scherzer, P.; Tobar, A.; Levi, M.; Gafter, U. Altered Renal Lipid Metabolism and Renal Lipid Accumulation in Human Diabetic Nephropathy. J. Lipid Res. 2014, 55, 561–572. [Google Scholar] [CrossRef]
  25. Tu, Q.M.; Jin, H.M.; Yang, X.H. Lipid Abnormality in Diabetic Kidney Disease and Potential Treatment Advancements. Front. Endocrinol. 2025, 16, 1503711. [Google Scholar] [CrossRef]
  26. Freeman, J.S. Role of the Incretin Pathway in the Pathogenesis of Type 2 Diabetes Mellitus. Cleve. Clin. J. Med. 2009, 76 (Suppl. S5), S12–S19. [Google Scholar] [CrossRef]
  27. Zhang, L.; Wang, Z.; Zhang, X.; Zhao, L.; Chu, J.; Li, H.; Sun, W.; Yang, C.; Wang, H.; Dai, W.; et al. Alterations of the Gut Microbiota in Patients with Diabetic Nephropathy. Microbiol. Spectr. 2022, 10, e00324-22. [Google Scholar] [CrossRef] [PubMed]
  28. Iatcu, C.O.; Steen, A.; Covasa, M. Gut Microbiota and Complications of Type-2 Diabetes. Nutrients 2021, 14, 166. [Google Scholar] [CrossRef] [PubMed]
  29. Yu, J.-X.; Chen, X.; Zang, S.-G.; Chen, X.; Wu, Y.-Y.; Wu, L.-P.; Xuan, S.-H. Gut Microbiota Microbial Metabolites in Diabetic Nephropathy Patients: Far to Go. Front. Cell. Infect. Microbiol. 2024, 14, 1359432. [Google Scholar] [CrossRef] [PubMed]
  30. Cao, M.; Zhao, X.; Xia, F.; Shi, M.; Zhao, D.; Li, L.; Jiang, H. Mitochondrial Dysfunction and Metabolic Reprogramming in Acute Kidney Injury: Mechanisms, Therapeutic Advances, and Clinical Challenges. Front. Physiol. 2025, 16, 1623500. [Google Scholar] [CrossRef]
  31. Amorim, R.G.; Guedes, G.D.S.; Vasconcelos, S.M.L.; Santos, J.C.D.F. Kidney Disease in Diabetes Mellitus: Cross-Linking between Hyperglycemia, Redox Imbalance and Inflammation. Arq. Bras. Cardiol. 2019, 112, 577–587, Erratum in Arq. Bras. Cardiol. 2019, 113, 182. [Google Scholar] [CrossRef]
  32. Helal, I.; Fick-Brosnahan, G.M.; Reed-Gitomer, B.; Schrier, R.W. Glomerular Hyperfiltration: Definitions, Mechanisms and Clinical Implications. Nat. Rev. Nephrol. 2012, 8, 293–300. [Google Scholar] [CrossRef]
  33. Lassén, E.; Daehn, I.S. Molecular Mechanisms in Early Diabetic Kidney Disease: Glomerular Endothelial Cell Dysfunction. Int. J. Mol. Sci. 2020, 21, 9456. [Google Scholar] [CrossRef]
  34. Giacchetti, G.; Sechi, L.A.; Rilli, S.; Carey, R.M. The Renin-Angiotensin-Aldosterone System, Glucose Metabolism and Diabetes. Trends Endocrinol. Metab. 2005, 16, 120–126. [Google Scholar] [CrossRef] [PubMed]
  35. Luther, J.M.; Brown, N.J. Renin-Angiotensin-Aldosterone System and Glucose Homeostasis. Trends Pharmacol. Sci. 2011, 32, 734–739. [Google Scholar] [CrossRef] [PubMed]
  36. Peng, H.; Xing, Y.-F.; Ye, Z.-C.; Li, C.-M.; Luo, P.-L.; Li, M.; Lou, T.-Q. High Glucose Induces Activation of the Local Renin-Angiotensin System in Glomerular Endothelial Cells. Mol. Med. Rep. 2014, 9, 450–456. [Google Scholar] [CrossRef] [PubMed]
  37. Gómez-Garre, D.; Ruiz-Ortega, M.; Ortego, M.; Largo, R.; López-Armada, M.J.; Plaza, J.J.; González, E.; Egido, J. Effects and Interactions of Endothelin-1 and Angiotensin II on Matrix Protein Expression and Synthesis and Mesangial Cell Growth. Hypertension 1996, 27, 885–892. [Google Scholar] [CrossRef]
  38. Liu, C.X.; Hu, Q.; Wang, Y.; Zhang, W.; Ma, Z.Y.; Feng, J.B.; Wang, R.; Wang, X.P.; Dong, B.; Gao, F.; et al. Angiotensin-Converting Enzyme (ACE) 2 Overexpression Ameliorates Glomerular Injury in a Rat Model of Diabetic Nephropathy: A Comparison with ACE Inhibition. Mol. Med. 2011, 17, 59–69, Erratum in Mol. Med. 2022, 28, 53. [Google Scholar] [CrossRef]
  39. Gyawali, P.; Richards, R.S. Association of Altered Hemorheology with Oxidative Stress and Inflammation in Metabolic Syndrome. Redox Rep. Commun. Free Radic. Res. 2015, 20, 139–144. [Google Scholar] [CrossRef]
  40. Donath, M.Y.; Shoelson, S.E. Type 2 Diabetes as an Inflammatory Disease. Nat. Rev. Immunol. 2011, 11, 98–107. [Google Scholar] [CrossRef]
  41. Donate-Correa, J.; Ferri, C.M.; Sánchez-Quintana, F.; Pérez-Castro, A.; González-Luis, A.; Martín-Núñez, E.; Mora-Fernández, C.; Navarro-González, J.F. Inflammatory Cytokines in Diabetic Kidney Disease: Pathophysiologic and Therapeutic Implications. Front. Med. 2021, 7, 628289. [Google Scholar] [CrossRef]
  42. Rayego-Mateos, S.; Morgado-Pascual, J.L.; Opazo-Ríos, L.; Guerrero-Hue, M.; García-Caballero, C.; Vázquez-Carballo, C.; Mas, S.; Sanz, A.B.; Herencia, C.; Mezzano, S.; et al. Pathogenic Pathways and Therapeutic Approaches Targeting Inflammation in Diabetic Nephropathy. Int. J. Mol. Sci. 2020, 21, 3798. [Google Scholar] [CrossRef]
  43. Lin, Y.-C.; Chang, Y.-H.; Yang, S.-Y.; Wu, K.-D.; Chu, T.-S. Update of Pathophysiology and Management of Diabetic Kidney Disease. J. Formos. Med. Assoc. 2018, 117, 662–675. [Google Scholar] [CrossRef]
  44. Li, J.; Li, L.; Zhang, Z.; Chen, P.; Shu, H.; Yang, C.; Chu, Y.; Liu, J. Ferroptosis: An Important Player in the Inflammatory Response in Diabetic Nephropathy. Front. Immunol. 2023, 14, 1294317. [Google Scholar] [CrossRef]
  45. Tang, D.; Kroemer, G.; Kang, R. Ferroptosis in Immunostimulation and Immunosuppression. Immunol. Rev. 2024, 321, 199–210. [Google Scholar] [CrossRef] [PubMed]
  46. Antar, S.A.; Ashour, N.A.; Marawan, M.E.; Al-Karmalawy, A.A. Fibrosis: Types, Effects, Markers, Mechanisms for Disease Progression, and Its Relation with Oxidative Stress, Immunity, and Inflammation. Int. J. Mol. Sci. 2023, 24, 4004. [Google Scholar] [CrossRef] [PubMed]
  47. Hills, C.E.; Squires, P.E. The Role of TGF-β and Epithelial-to Mesenchymal Transition in Diabetic Nephropathy. Cytokine Growth Factor. Rev. 2011, 22, 131–139. [Google Scholar] [CrossRef]
  48. Jiang, S.; Jia, H.; Hou, Q.; Jin, L.; Ahsan, M.A.; Li, G.; Guan, T.; Zhao, J.; Liu, Z.; Xie, J.; et al. Multimodal Analysis Stratifies Genetic Susceptibility and Reveals the Pathogenic Mechanism of Kidney Injury in Diabetic Nephropathy. Cell Rep. Med. 2025, 6, 102249. [Google Scholar] [CrossRef] [PubMed]
  49. Seaquist, E.R.; Goetz, F.C.; Rich, S.; Barbosa, J. Familial Clustering of Diabetic Kidney Disease. Evidence for Genetic Susceptibility to Diabetic Nephropathy. N. Engl. J. Med. 1989, 320, 1161–1165. [Google Scholar] [CrossRef]
  50. Rizvi, S.; Raza, S.T.; Mahdi, F. Association of Genetic Variants with Diabetic Nephropathy. World J. Diabetes 2014, 5, 809–816. [Google Scholar] [CrossRef]
  51. Florez, J.C. Genetics of Diabetic Kidney Disease. Semin. Nephrol. 2016, 36, 474–480. [Google Scholar] [CrossRef]
  52. Salazar, J.; Navarro, C.; Ortega, Á.; Nava, M.; Morillo, D.; Torres, W.; Hernández, M.; Cabrera, M.; Angarita, L.; Ortiz, R.; et al. Advanced Glycation End Products: New Clinical and Molecular Perspectives. Int. J. Environ. Res. Public Health 2021, 18, 7236. [Google Scholar] [CrossRef]
  53. Sun, J.; Wei, N.; Yu, C.; Li, C.; Li, W.; Sun, X.; Zhang, Y.; Li, Y.; Xie, J. Natural Polysaccharides: The Potential Biomacromolecules for Treating Diabetes and Its Complications via AGEs-RAGE-Oxidative Stress Axis. Int. Immunopharmacol. 2024, 143, 113426. [Google Scholar] [CrossRef]
  54. Yu, H.; Fu, L.; Zhang, C.; Wang, S.; Song, J.; Zhu, Y.; Wang, F. Targeting Ferroptosis With Natural Products to Treat Diabetes and Its Complications: Opportunities and Challenges. Phytother. Res. 2025, 0, 1–22. [Google Scholar] [CrossRef]
  55. Brown, E.M.; Clardy, J.; Xavier, R.J. Gut Microbiome Lipid Metabolism and Its Impact on Host Physiology. Cell Host Microbe 2023, 31, 173–186. [Google Scholar] [CrossRef]
  56. Ni, Y.; Zheng, L.; Nan, S.; Ke, L.; Fu, Z.; Jin, J. Enterorenal Crosstalks in Diabetic Nephropathy and Novel Therapeutics Targeting the Gut Microbiota. Acta Biochim. Biophys. Sin. 2022, 54, 1406–1420. [Google Scholar] [CrossRef] [PubMed]
  57. Leng, C.-L.; Lin, K.; Zhou, M.; Ye, X.-S.; Shu, X.-J.; Liu, W. Protective Effect of Salidroside on Renal Damage in Diabetic Nephropathy Mice by Regulating RAGE/JAK1/STAT Signaling Pathway. Zhongguo Zhong Yao Za Zhi 2024, 49, 2188–2196. [Google Scholar] [CrossRef]
  58. Chen, J.; Ou, Z.; Gao, T.; Yang, Y.; Shu, A.; Xu, H.; Chen, Y.; Lv, Z. Ginkgolide B Alleviates Oxidative Stress and Ferroptosis by Inhibiting GPX4 Ubiquitination to Improve Diabetic Nephropathy. Biomed. Pharmacother. 2022, 156, 113953. [Google Scholar] [CrossRef] [PubMed]
  59. Jiang, X.; Yu, J.; Wang, X.; Ge, J.; Li, N. Quercetin Improves Lipid Metabolism via SCAP-SREBP2-LDLr Signaling Pathway in Early Stage Diabetic Nephropathy. Diabetes Metab. Syndr. Obes. Targets Ther. 2019, 12, 827–839. [Google Scholar] [CrossRef] [PubMed]
  60. Zhu, N.; Duan, H.; Feng, Y.; Xu, W.; Shen, J.; Wang, K.; Liu, J. Magnesium Lithospermate B Ameliorates Diabetic Nephropathy by Suppressing the Uremic Toxin Formation Mediated by Gut Microbiota. Eur. J. Pharmacol. 2023, 953, 175812. [Google Scholar] [CrossRef]
  61. Ju, C.G.; Zhu, L.; Wang, W.; Gao, H.; Xu, Y.B.; Jia, T.Z. Cornus officinalis Prior and Post-Processing: Regulatory Effects on Intestinal Flora of Diabetic Nephropathy Rats. Front. Pharmacol. 2022, 13, 1039711. [Google Scholar] [CrossRef]
  62. Li, T.; Yang, Y.; Wang, X.; Dai, W.; Zhang, L.; Piao, C. Flavonoids Derived from Buckwheat Hull Can Break Advanced Glycation End-Products and Improve Diabetic Nephropathy. Food Funct. 2021, 12, 7161–7170. [Google Scholar] [CrossRef]
  63. Luo, Z.; Li, T.; Gao, Q.; Chen, Y.; Su, G.; Zhao, Y. Impact of Licochalcone a on the Progression of Diabetic Nephropathy in Type 2 Diabetes Mellitus of C57BL/6 Mice. Food Funct. 2021, 12, 10676–10689. [Google Scholar] [CrossRef]
  64. Ambalavanan, R.; John, A.D.; Selvaraj, A.D. Nephroprotective Role of Nanoencapsulated Tinospora cordifolia (Willd.) Using Polylactic Acid Nanoparticles in Streptozotocin-Induced Diabetic Nephropathy Rats. IET Nanobiotechnol. 2021, 15, 411–417. [Google Scholar] [CrossRef]
  65. Cho, C.-H.; Yoo, G.; Kim, M.; Kurniawati, U.D.; Choi, I.-W.; Lee, S.-H. Dieckol, Derived from the Edible Brown Algae Ecklonia cava, Attenuates Methylglyoxal-Associated Diabetic Nephropathy by Suppressing AGE-RAGE Interaction. Antioxidants 2023, 12, 593. [Google Scholar] [CrossRef]
  66. Zhu, D.; Ni, Y.; Chen, C.; Dong, Z.; Wang, L.; Zhang, W. Geniposide Ameliorates Diabetic Nephropathy in Type 2 Diabetic Mice by Targeting AGEs-RAGE-Dependent Inflammatory Pathway. Phytomed. Int. J. Phytother. Phytopharm. 2024, 135, 156046. [Google Scholar] [CrossRef] [PubMed]
  67. Iem, Z.; Mn, A.; Mm, E.-S. Protective Effect of Vanillin on Diabetic Nephropathy by Decreasing Advanced Glycation End Products in Rats. Life Sci. 2019, 239, 117088. [Google Scholar] [CrossRef] [PubMed]
  68. Apte, M.M.; Khattar, E.; Tupe, R.S. Mechanistic Role of Syzygium cumini (L.) Skeels in Glycation Induced Diabetic Nephropathy via RAGE-NF-κB Pathway and Extracellular Proteins Modifications: A Molecular Approach. J. Ethnopharmacol. 2024, 322, 117573. [Google Scholar] [CrossRef] [PubMed]
  69. Chen, Y.; Chen, J.; Jiang, M.; Fu, Y.; Zhu, Y.; Jiao, N.; Liu, L.; Du, Q.; Wu, H.; Xu, H.; et al. Loganin and Catalpol Exert Cooperative Ameliorating Effects on Podocyte Apoptosis upon Diabetic Nephropathy by Targeting AGEs-RAGE Signaling. Life Sci. 2020, 252, 117653. [Google Scholar] [CrossRef]
  70. Tang, D.; He, W.-J.; Zhang, Z.-T.; Shi, J.-J.; Wang, X.; Gu, W.-T.; Chen, Z.-Q.; Xu, Y.-H.; Chen, Y.-B.; Wang, S.-M. Protective Effects of Huang-Lian-Jie-Du Decoction on Diabetic Nephropathy through Regulating AGEs/RAGE/Akt/Nrf2 Pathway and Metabolic Profiling in Db/Db Mice. Phytomedicine 2022, 95, 153777. [Google Scholar] [CrossRef]
  71. Shu, A.; Du, Q.; Chen, J.; Gao, Y.; Zhu, Y.; Lv, G.; Lu, J.; Chen, Y.; Xu, H. Catalpol Ameliorates Endothelial Dysfunction and Inflammation in Diabetic Nephropathy via Suppression of RAGE/RhoA/ROCK Signaling Pathway. Chem.-Biol. Interact. 2021, 348, 109625. [Google Scholar] [CrossRef]
  72. Zhang, J.; Li, S.-L.; Lin, W.; Pan, R.-H.; Dai, Y.; Xia, Y.-F. Tripterygium Glycoside Tablet Attenuates Renal Function Impairment in Diabetic Nephropathy Mice by Regulating Triglyceride Metabolism. J. Pharm. Biomed. Anal. 2022, 221, 115028. [Google Scholar] [CrossRef] [PubMed]
  73. Zhang, Y.; Yao, H.; Li, C.; Sun, W.; Chen, X.; Cao, Y.; Liu, Y.; Liu, Y.; Chen, J.; Qi, J.; et al. Gandi Capsule Improved Podocyte Lipid Metabolism of Diabetic Nephropathy Mice through SIRT1/AMPK/HNF4A Pathway. Oxidative Med. Cell. Longev. 2022, 2022, 6275505. [Google Scholar] [CrossRef] [PubMed]
  74. Zhou, Y.; Tao, H.; Xu, N.; Zhou, S.; Peng, Y.; Zhu, J.; Liu, S.; Chang, Y. Chrysin Improves Diabetic Nephropathy by Regulating the AMPK-Mediated Lipid Metabolism in HFD/STZ-Induced DN Mice. J. Food Biochem. 2022, 46, e14379. [Google Scholar] [CrossRef]
  75. Zhao, T.; Xiang, Q.; Lie, B.; Chen, D.; Li, M.; Zhang, X.; Yang, J.; He, B.; Zhang, W.; Dong, R.; et al. Yishen Huashi Granule Modulated Lipid Metabolism in Diabetic Nephropathy via PI3K/AKT/mTOR Signaling Pathways. Heliyon 2023, 9, e14171. [Google Scholar] [CrossRef]
  76. Yasuda-Yamahara, M.; Kume, S.; Tagawa, A.; Maegawa, H.; Uzu, T. Emerging Role of Podocyte Autophagy in the Progression of Diabetic Nephropathy. Autophagy 2015, 11, 2385–2386. [Google Scholar] [CrossRef]
  77. Lin, Q.; Banu, K.; Ni, Z.; Leventhal, J.S.; Menon, M.C. Podocyte Autophagy in Homeostasis and Disease. J. Clin. Med. 2021, 10, 1184. [Google Scholar] [CrossRef]
  78. Chen, Y.; Liu, Q.; Shan, Z.; Mi, W.; Zhao, Y.; Li, M.; Wang, B.; Zheng, X.; Feng, W. Catalpol Ameliorates Podocyte Injury by Stabilizing Cytoskeleton and Enhancing Autophagy in Diabetic Nephropathy. Front. Pharmacol. 2019, 10, 1477. [Google Scholar] [CrossRef]
  79. Lou, Y.; Luan, Y.-T.; Rong, W.-Q.; Gai, Y. Corilagin Alleviates Podocyte Injury in Diabetic Nephropathy by Regulating Autophagy via the SIRT1-AMPK Pathway. World J. Diabetes 2024, 15, 1916–1931. [Google Scholar] [CrossRef]
  80. Li, X.; Zhu, Q.; Zheng, R.; Yan, J.; Wei, M.; Fan, Y.; Deng, Y.; Zhong, Y. Puerarin Attenuates Diabetic Nephropathy by Promoting Autophagy in Podocytes. Front. Physiol. 2020, 11, 73. [Google Scholar] [CrossRef] [PubMed]
  81. Xu, X.; Chen, B.; Huang, Q.; Wu, Y.; Liang, T. The Effects of Puerarin on Autophagy through Regulating of the PERK/eIF2α/ATF4 Signaling Pathway Influences Renal Function in Diabetic Nephropathy. Diabetes Metab. Syndr. Obes. Targets Ther. 2020, 13, 2583–2592. [Google Scholar] [CrossRef]
  82. Liu, Y.; Liu, W.; Zhang, Z.; Hu, Y.; Zhang, X.; Sun, Y.; Lei, Q.; Sun, D.; Liu, T.; Fan, Y.; et al. Yishen Capsule Promotes Podocyte Autophagy through Regulating SIRT1/NF-κB Signaling Pathway to Improve Diabetic Nephropathy. Ren. Fail. 2021, 43, 128–140. [Google Scholar] [CrossRef]
  83. Zhu, S.; Liu, Q.; Chang, Y.; Luo, C.; Zhang, X.; Sun, S. Integrated Network Pharmacology and Cellular Assay to Explore the Mechanisms of Selenized Tripterine Phytosomes (Se@tri-PTs) Alleviating Podocyte Injury in Diabetic Nephropathy. Curr. Pharm. Des. 2023, 29, 3073–3086. [Google Scholar] [CrossRef]
  84. Xu, Y.; Xu, C.; Huang, J.; Xu, C.; Xiong, Y. Astragalus Polysaccharide Attenuates Diabetic Nephropathy by Reducing Apoptosis and Enhancing Autophagy through Activation of Sirt1/FoxO1 Pathway. Int. Urol. Nephrol. 2024, 56, 3067–3078. [Google Scholar] [CrossRef] [PubMed]
  85. Liu, H.; Wang, Q.; Shi, G.; Yang, W.; Zhang, Y.; Chen, W.; Wan, S.; Xiong, F.; Wang, Z. Emodin Ameliorates Renal Damage and Podocyte Injury in a Rat Model of Diabetic Nephropathy via Regulating AMPK/mTOR-Mediated Autophagy Signaling Pathway. Diabetes Metab. Syndr. Obes. Targets Ther. 2021, 14, 1253–1266. [Google Scholar] [CrossRef] [PubMed]
  86. Sheng, H.; Zhang, D.; Zhang, J.; Zhang, Y.; Lu, Z.; Mao, W.; Liu, X.; Zhang, L. Kaempferol Attenuated Diabetic Nephropathy by Reducing Apoptosis and Promoting Autophagy through AMPK/mTOR Pathways. Front. Med. 2022, 9, 986825. [Google Scholar] [CrossRef] [PubMed]
  87. Khodir, S.A.; Samaka, R.M.; Ameen, O. Autophagy and mTOR Pathways Mediate the Potential Renoprotective Effects of Vitamin D on Diabetic Nephropathy. Int. J. Nephrol. 2020, 2020, 7941861. [Google Scholar] [CrossRef] [PubMed]
  88. Chen, L.; Dai, L.; Liu, Y.; Li, X.; Wang, H. Yiqi Huoxue Recipe Regulates Autophagy through Degradation of Advanced Glycation End Products via mTOR/S6K1/LC3 Pathway in Diabetic Nephropathy. Evid.-Based Complement. Altern. Med. ECAM 2021, 2021, 9942678. [Google Scholar] [CrossRef]
  89. Dusabimana, T.; Park, E.J.; Je, J.; Jeong, K.; Yun, S.P.; Kim, H.J.; Kim, H.; Park, S.W. Geniposide Improves Diabetic Nephropathy by Enhancing ULK1-Mediated Autophagy and Reducing Oxidative Stress through AMPK Activation. Int. J. Mol. Sci. 2021, 22, 1651. [Google Scholar] [CrossRef] [PubMed]
  90. Yan, L.; Xu, X.; Fan, Y.; Zhang, L.; Niu, X.; Hu, A. Tangshen Decoction Enhances Podocytes Autophagy to Relieve Diabetic Nephropathy through Modulation of P-AMPK/p-ULK1 Signaling. Evid.-Based Complement. Altern. Med. ECAM 2022, 2022, 3110854. [Google Scholar] [CrossRef]
  91. Zhang, M.; Zhang, Y.; Xiao, D.; Zhang, J.; Wang, X.; Guan, F.; Zhang, M.; Chen, L. Highly Bioavailable Berberine Formulation Ameliorates Diabetic Nephropathy through the Inhibition of Glomerular Mesangial Matrix Expansion and the Activation of Autophagy. Eur. J. Pharmacol. 2020, 873, 172955. [Google Scholar] [CrossRef]
  92. Li, Y.; Wu, T.; Li, H.; Liu, M.; Xu, H. Tanshinone IIA Promoted Autophagy and Inhibited Inflammation to Alleviate Podocyte Injury in Diabetic Nephropathy. Diabetes Metab. Syndr. Obes. 2024, 17, 2709–2724. [Google Scholar] [CrossRef]
  93. Yang, F.; Qu, Q.; Zhao, C.; Liu, X.; Yang, P.; Li, Z.; Han, L.; Shi, X. Paecilomyces Cicadae-Fermented Radix Astragali Activates Podocyte Autophagy by Attenuating PI3K/AKT/mTOR Pathways to Protect against Diabetic Nephropathy in Mice. Biomed. Pharmacother. 2020, 129, 110479. [Google Scholar] [CrossRef] [PubMed]
  94. Nie, Y.; Fu, C.; Zhang, H.; Zhang, M.; Xie, H.; Tong, X.; Li, Y.; Hou, Z.; Fan, X.; Yan, M. Celastrol Slows the Progression of Early Diabetic Nephropathy in Rats via the PI3K/AKT Pathway. BMC Complement. Med. Ther. 2020, 20, 321. [Google Scholar] [CrossRef] [PubMed]
  95. QTu, Q.; Li, Y.; Jin, J.; Jiang, X.; Ren, Y.; He, Q. Curcumin Alleviates Diabetic Nephropathy via Inhibiting Podocyte Mesenchymal Transdifferentiation and Inducing Autophagy in Rats and MPC5 Cells. Pharm. Biol. 2019, 57, 778–786. [Google Scholar] [CrossRef] [PubMed]
  96. Zhang, P.; Fang, J.; Zhang, J.; Ding, S.; Gan, D. Curcumin Inhibited Podocyte Cell Apoptosis and Accelerated Cell Autophagy in Diabetic Nephropathy via Regulating Beclin1/UVRAG/Bcl2. Diabetes Metab. Syndr. Obes. Targets Ther. 2020, 13, 641–652. [Google Scholar] [CrossRef]
  97. Kong, Z.; Xiao, M.; Wang, B.; Zhang, W.; Che, K.; Lv, W.; Wang, Y.; Huang, Y.; Zhao, H.; Zhao, Y.; et al. Renoprotective Effect of Isoorientin in Diabetic Nephropathy via Activating Autophagy and Inhibiting the PI3K-AKT-TSC2-mTOR Pathway. Am. J. Chin. Med. 2023, 51, 1269–1291. [Google Scholar] [CrossRef]
  98. Li, X.-Z.; Jiang, H.; Xu, L.; Liu, Y.-Q.; Tang, J.-W.; Shi, J.-S.; Yu, X.-J.; Wang, X.; Du, L.; Lu, Q.; et al. Sarsasapogenin Restores Podocyte Autophagy in Diabetic Nephropathy by Targeting GSK3β Signaling Pathway. Biochem. Pharmacol. 2021, 192, 114675. [Google Scholar] [CrossRef]
  99. Liu, Y.; Li, Y.; Xu, L.; Shi, J.; Yu, X.; Wang, X.; Li, X.; Jiang, H.; Yang, T.; Yin, X.; et al. Quercetin Attenuates Podocyte Apoptosis of Diabetic Nephropathy Through Targeting EGFR Signaling. Front. Pharmacol. 2021, 12, 792777. [Google Scholar] [CrossRef]
  100. Zhu, B.; Fang, J.; Ju, Z.; Chen, Y.; Wang, L.; Wang, H.; Xing, L.; Cao, A. Zuogui Wan Ameliorates High Glucose-Induced Podocyte Apoptosis and Improves Diabetic Nephropathy in Db/Db Mice. Front. Pharmacol. 2022, 13, 991976. [Google Scholar] [CrossRef]
  101. Yang, K.; Bai, Y.; Yu, N.; Lu, B.; Han, G.; Yin, C.; Pang, Z. Huidouba Improved Podocyte Injury by Down-Regulating Nox4 Expression in Rats With Diabetic Nephropathy. Front. Pharmacol. 2020, 11, 587995. [Google Scholar] [CrossRef]
  102. Wang, F.; Li, R.; Zhao, L.; Ma, S.; Qin, G. Resveratrol Ameliorates Renal Damage by Inhibiting Oxidative Stress-Mediated Apoptosis of Podocytes in Diabetic Nephropathy. Eur. J. Pharmacol. 2020, 885, 173387. [Google Scholar] [CrossRef]
  103. Cui, F.-Q.; Tang, L.; Gao, Y.-B.; Wang, Y.-F.; Meng, Y.; Shen, C.; Shen, Z.-L.; Liu, Z.-Q.; Zhao, W.-J.; Liu, W.J. Effect of Baoshenfang Formula on Podocyte Injury via Inhibiting the NOX-4/ROS/P38 Pathway in Diabetic Nephropathy. J. Diabetes Res. 2019, 2019, 2981705. [Google Scholar] [CrossRef] [PubMed]
  104. Li, J.; Ling, Y.; Yin, S.; Yang, S.; Kong, M.; Li, Z. Baicalin Serves a Protective Role in Diabetic Nephropathy through Preventing High Glucose-Induced Podocyte Apoptosis. Exp. Ther. Med. 2020, 20, 367–374. [Google Scholar] [CrossRef]
  105. Zhang, H.; Sun, S.-C. NF-κB in Inflammation and Renal Diseases. Cell Biosci. 2015, 5, 63. [Google Scholar] [CrossRef] [PubMed]
  106. Afonina, I.S.; Zhong, Z.; Karin, M.; Beyaert, R. Limiting Inflammation—The Negative Regulation of NF-κB and the NLRP3 Inflammasome. Nat. Immunol. 2017, 18, 861–869. [Google Scholar] [CrossRef]
  107. Zhai, J.; Li, Z.; Zhang, H.; Lu, Z.; Zhang, Y.; Li, M.; Kang, J.; Yang, Z.; Ma, L.; Ma, L.; et al. Coptisine Mitigates Diabetic Nephropathy via Repressing the NRLP3 Inflammasome. Open Life Sci. 2023, 18, 20220568. [Google Scholar] [CrossRef]
  108. Liu, K.; Zhou, S.; Liu, J.; Wang, Y.; Zhu, F.; Liu, M. Silibinin Attenuates High-Fat Diet-Induced Renal Fibrosis of Diabetic Nephropathy. Drug Des. Dev. Ther. 2019, 13, 3117–3126. [Google Scholar] [CrossRef]
  109. Chu, C.; Li, D.; Zhang, S.; Ikejima, T.; Jia, Y.; Wang, D.; Xu, F. Role of Silibinin in the Management of Diabetes Mellitus and Its Complications. Arch. Pharmacal Res. 2018, 41, 785–796. [Google Scholar] [CrossRef]
  110. Ma, R.; He, Y.; Fang, Q.; Xie, G.; Qi, M. Ferulic Acid Ameliorates Renal Injury via Improving Autophagy to Inhibit Inflammation in Diabetic Nephropathy Mice. Biomed. Pharmacother. 2022, 153, 113424. [Google Scholar] [CrossRef] [PubMed]
  111. Pan, S.; Jiang, S.-S.; Li, R.; Tian, B.; Huang, C.-Y.; Wang, R.; Li, Y.-Y.; Zhu, H.; Yuan, Y.-F.; Hu, X. Hong Guo Ginseng Guo (HGGG) Protects against Kidney Injury in Diabetic Nephropathy by Inhibiting NLRP3 Inflammasome and Regulating Intestinal Flora. Phytomed. Int. J. Phytother. Phytopharm. 2024, 132, 155861. [Google Scholar] [CrossRef]
  112. Zhang, L.; Jing, M.; Liu, Q. Crocin Alleviates the Inflammation and Oxidative Stress Responses Associated with Diabetic Nephropathy in Rats via NLRP3 Inflammasomes. Life Sci. 2021, 278, 119542. [Google Scholar] [CrossRef] [PubMed]
  113. Ma, Z.; Zhu, L.; Wang, S.; Guo, X.; Sun, B.; Wang, Q.; Chen, L. Berberine Protects Diabetic Nephropathy by Suppressing Epithelial-to-Mesenchymal Transition Involving the Inactivation of the NLRP3 Inflammasome. Ren. Fail. 2022, 44, 923–932. [Google Scholar] [CrossRef] [PubMed]
  114. Liu, Y.-W.; Hao, Y.-C.; Chen, Y.-J.; Yin, S.-Y.; Zhang, M.-Y.; Kong, L.; Wang, T.Y. Protective Effects of Sarsasapogenin against Early Stage of Diabetic Nephropathy in Rats. Phytother. Res. 2019, 33, 2470. [Google Scholar] [CrossRef]
  115. Tang, Z.-Z.; Zhang, Y.-M.; Zheng, T.; Huang, T.-T.; Ma, T.-F.; Liu, Y.-W. Sarsasapogenin Alleviates Diabetic Nephropathy through Suppression of Chronic Inflammation by Down-Regulating PAR-1: In Vivo and in Vitro Study. Phytomed. Int. J. Phytother. Phytopharm. 2020, 78, 153314. [Google Scholar] [CrossRef]
  116. Ren, C.; Zhou, X.; Bao, X.; Zhang, J.; Tang, J.; Zhu, Z.; Zhang, N.; Bai, Y.; Xi, Y.; Zhang, Q.; et al. Dioscorea zingiberensis Ameliorates Diabetic Nephropathy by Inhibiting NLRP3 Inflammasome and Curbing the Expression of p66Shc in High-Fat Diet/Streptozotocin-Induced Diabetic Mice. J. Pharm. Pharmacol. 2021, 73, 1218–1229. [Google Scholar] [CrossRef]
  117. Yoon, J.-J.; Park, J.-H.; Lee, Y.-J.; Kim, H.-Y.; Han, B.-H.; Jin, H.-G.; Kang, D.-G.; Lee, H.-S. Protective Effects of Ethanolic Extract from Rhizome of Polygoni Avicularis against Renal Fibrosis and Inflammation in a Diabetic Nephropathy Model. Int. J. Mol. Sci. 2021, 22, 7230. [Google Scholar] [CrossRef] [PubMed]
  118. Zhang, S.; Zhang, S.; Bai, X.; Wang, Y.; Liu, Y.; Liu, W. Thonningianin a Ameliorated Renal Interstitial Fibrosis in Diabetic Nephropathy Mice by Modulating Gut Microbiota Dysbiosis and Repressing Inflammation. Front. Pharmacol. 2024, 15, 1389654. [Google Scholar] [CrossRef]
  119. Luo, J.; Tan, J.; Zhao, J.; Wang, L.; Liu, J.; Dai, X.; Sun, Y.; Kuang, Q.; Hui, J.; Chen, J.; et al. Cynapanoside a Exerts Protective Effects against Obesity-Induced Diabetic Nephropathy through Ameliorating TRIM31-Mediated Inflammation, Lipid Synthesis and Fibrosis. Int. Immunopharmacol. 2022, 113, 109395. [Google Scholar] [CrossRef]
  120. Aboismaiel, M.G.; Amin, M.N.; Eissa, L.A. Renoprotective Effect of a Novel Combination of 6-Gingerol and Metformin in High-Fat Diet/Streptozotocin-Induced Diabetic Nephropathy in Rats via Targeting miRNA-146a, miRNA-223, TLR4/TRAF6/NLRP3 Inflammasome Pathway and HIF-1α. Biol. Res. 2024, 57, 47. [Google Scholar] [CrossRef]
  121. Chen, X.; Xie, N.; Feng, L.; Huang, Y.; Wu, Y.; Zhu, H.; Tang, J.; Zhang, Y. Oxidative Stress in Diabetes Mellitus and Its Complications: From Pathophysiology to Therapeutic Strategies. Chin. Med. J. 2025, 138, 15–27. [Google Scholar] [CrossRef]
  122. Sun, D.; Wang, L.; Wu, Y.; Yu, Y.; Yao, Y.; Yang, H.; Hao, C. Lipid Metabolism in Ferroptosis: Mechanistic Insights and Therapeutic Potential. Front. Immunol. 2025, 16, 1545339. [Google Scholar] [CrossRef]
  123. Zhang, L.; Li, P.; Xing, C.; Zhao, J.; He, Y.; Wang, J.; Wu, X.; Liu, Z.; Zhang, A.; Lin, H.; et al. Efficacy and Safety of Abelmoschus manihot for Primary Glomerular Disease: A Prospective, Multicenter Randomized Controlled Clinical Trial. Am. J. Kidney Dis. Off. J. Natl. Kidney Found. 2014, 64, 57–65. [Google Scholar] [CrossRef]
  124. Bao, T.; Zhang, X.; Xie, W.; Wang, Y.; Li, X.; Tang, C.; Yang, Y.; Sun, J.; Gao, J.; Yu, T.; et al. Natural Compounds Efficacy in Complicated Diabetes: A New Twist Impacting Ferroptosis. Biomed. Pharmacother. 2023, 168, 115544. [Google Scholar] [CrossRef]
  125. Chattopadhyay, S.; Hazra, R.; Mallick, A.; Gayen, S.; Roy, S. A Review on Comprehending Immunotherapeutic Approaches Inducing Ferroptosis: Managing Tumour Immunity. Immunology 2024, 172, 547–565. [Google Scholar] [CrossRef]
  126. Tanase, D.M.; Gosav, E.M.; Anton, M.I.; Floria, M.; Seritean Isac, P.N.; Hurjui, L.L.; Tarniceriu, C.C.; Costea, C.F.; Ciocoiu, M.; Rezus, C. Oxidative Stress and NRF2/KEAP1/ARE Pathway in Diabetic Kidney Disease (DKD): New Perspectives. Biomolecules 2022, 12, 1227. [Google Scholar] [CrossRef] [PubMed]
  127. Li, F.; Zhang, J.; Luo, L.; Hu, J. Protective Effects of Xanthohumol against Diabetic Nephropathy in a Mouse Model. Kidney Blood Press. Res. 2023, 48, 92–101. [Google Scholar] [CrossRef] [PubMed]
  128. LMa, L.; Wu, F.; Shao, Q.; Chen, G.; Xu, L.; Lu, F. Baicalin Alleviates Oxidative Stress and Inflammation in Diabetic Nephropathy via Nrf2 and MAPK Signaling Pathway. Drug Des. Dev. Ther. 2021, 15, 3207–3221. [Google Scholar] [CrossRef] [PubMed]
  129. Forcina, G.C.; Dixon, S.J. GPX4 at the Crossroads of Lipid Homeostasis and Ferroptosis. Proteomics 2019, 19, e1800311. [Google Scholar] [CrossRef]
  130. Zhang, S.; Zhang, S.; Wang, H.; Chen, Y. Vitexin Ameliorated Diabetic Nephropathy via Suppressing GPX4-Mediated Ferroptosis. Eur. J. Pharmacol. 2023, 951, 175787. [Google Scholar] [CrossRef]
  131. Zhou, Z.; Niu, H.; Bian, M.; Zhu, C. Kidney Tea [Orthosiphon aristatus (Blume) Miq.] Improves Diabetic Nephropathy via Regulating Gut Microbiota and Ferroptosis. Front. Pharmacol. 2024, 15, 1392123. [Google Scholar] [CrossRef]
  132. Huang, Y.; Xu, W.; Zhou, R. NLRP3 Inflammasome Activation and Cell Death. Cell Mol. Immunol. 2021, 18, 2114–2127. [Google Scholar] [CrossRef]
  133. Zhong, Z.; Zhai, Y.; Liang, S.; Mori, Y.; Han, R.; Sutterwala, F.S.; Qiao, L. TRPM2 Links Oxidative Stress to NLRP3 Inflammasome Activation. Nat. Commun. 2013, 4, 1611. [Google Scholar] [CrossRef]
  134. Yu, X.; Li, Y.; Zhang, Y.; Yin, K.; Chen, X.; Zhu, X. Leonurine Ameliorates Diabetic Nephropathy through GPX4-Mediated Ferroptosis of Endothelial Cells. Front. Biosci. (Landmark Ed.) 2024, 29, 270. [Google Scholar] [CrossRef]
  135. Qi, X.-Y.; Peng, G.-C.; Han, Q.-T.; Yan, J.; Chen, L.-Z.; Wang, T.; Xu, L.-T.; Liu, M.-J.; Xu, Z.-P.; Wang, X.-N.; et al. Phthalides from the Rhizome of Ligusticum chuanxiong Hort. Attenuate Diabetic Nephropathy in Mice. J. Ethnopharmacol. 2024, 319, 117247. [Google Scholar] [CrossRef]
  136. Sherkhane, B.; Yerra, V.G.; Sharma, A.; Kumar, A.K.; Chayanika, G.; Kumar, A.V.; Kumar, A. Nephroprotective Potential of Syringic Acid in Experimental Diabetic Nephropathy: Focus on Oxidative Stress and Autophagy. Indian. J. Pharmacol. 2023, 55, 34–42. [Google Scholar] [CrossRef]
  137. A AlMousa, L.; A AlFaris, N.; Alshammari, G.M.; Alsayadi, M.M.; Altamimi, J.Z.; I Alagal, R.; Yahya, M.A. Rumex nervosus Could Alleviate Streptozotocin-Induced Diabetic Nephropathy in Rats by Activating Nrf2 Signaling. Sci. Prog. 2022, 105, 1–23. [Google Scholar] [CrossRef]
  138. AlTamimi, J.Z.; AlFaris, N.A.; Alshammari, G.M.; Alagal, R.I.; Aljabryn, D.H.; Yahya, M.A. Protective Effect of Eriodictyol against Hyperglycemia-Induced Diabetic Nephropathy in Rats Entails Antioxidant and Anti-Inflammatory Effects Mediated by Activating Nrf2. Saudi Pharm. J. SPJ Off. Publ. Saudi Pharm. Soc. 2023, 31, 101817. [Google Scholar] [CrossRef] [PubMed]
  139. Zhang, L.; Wang, X.; Chang, L.; Ren, Y.; Sui, M.; Fu, Y.; Zhang, L.; Hao, L. Quercetin Improves Diabetic Kidney Disease by Inhibiting Ferroptosis and Regulating the Nrf2 in Streptozotocin-Induced Diabetic Rats. Ren. Fail. 2024, 46, 2327495. [Google Scholar] [CrossRef] [PubMed]
  140. Zhang, H.; Qi, S.; Song, Y.; Ling, C. Artemisinin Attenuates Early Renal Damage on Diabetic Nephropathy Rats through Suppressing TGF-Β1 Regulator and Activating the Nrf2 Signaling Pathway. Life Sci. 2020, 256, 117966. [Google Scholar] [CrossRef]
  141. Bao, L.; Gong, Y.; Xu, W.; Dao, J.; Rao, J.; Yang, H. Chlorogenic Acid Inhibits NLRP3 Inflammasome Activation through Nrf2 Activation in Diabetic Nephropathy. PLoS ONE 2025, 20, e0316615. [Google Scholar] [CrossRef] [PubMed]
  142. Huang, Q.; Ouyang, D.; Liu, Q. Isoeucommin a Attenuates Kidney Injury in Diabetic Nephropathy through the Nrf2/HO-1 Pathway. FEBS Open Bio 2021, 11, 2350–2363. [Google Scholar] [CrossRef]
  143. Jin, T.; Chen, C. Umbelliferone Delays the Progression of Diabetic Nephropathy by Inhibiting Ferroptosis through Activation of the Nrf-2/HO-1 Pathway. Food Chem. Toxicol. Int. J. Publ. Br. Ind. Biol. Res. Assoc. 2022, 163, 112892. [Google Scholar] [CrossRef] [PubMed]
  144. Su, L.; Cao, P.; Wang, H. Tetrandrine Mediates Renal Function and Redox Homeostasis in a Streptozotocin-Induced Diabetic Nephropathy Rat Model through Nrf2/HO-1 Reactivation. Ann. Transl. Med. 2020, 8, 990. [Google Scholar] [CrossRef]
  145. Alaofi, A.L. Sinapic Acid Ameliorates the Progression of Streptozotocin (STZ)-Induced Diabetic Nephropathy in Rats via NRF2/HO-1 Mediated Pathways. Front. Pharmacol. 2020, 11, 1119. [Google Scholar] [CrossRef]
  146. Wen, Y.; Liu, Y.; Huang, Q.; Liu, R.; Liu, J.; Zhang, F.; Liu, S.; Jiang, Y. Moringa oleifera Lam. Seed Extract Protects Kidney Function in Rats with Diabetic Nephropathy by Increasing GSK-3β Activity and Activating the Nrf2/HO-1 Pathway. Phytomed. Int. J. Phytother. Phytopharm. 2022, 95, 153856, Erratum in Phytomed. Int. J. Phytother. Phytopharm. 2022, 100, 154043.. [Google Scholar] [CrossRef]
  147. Zhuang, L.-G.; Zhang, R.; Jin, G.-X.; Pei, X.-Y.; Wang, Q.; Ge, X.-X. Asiaticoside Improves Diabetic Nephropathy by Reducing Inflammation, Oxidative Stress, and Fibrosis: An in Vitro and in Vivo Study. World J. Diabetes 2024, 15, 2111–2122. [Google Scholar] [CrossRef]
  148. Alshehri, A.S. Kaempferol Attenuates Diabetic Nephropathy in Streptozotocin-Induced Diabetic Rats by a Hypoglycaemic Effect and Concomitant Activation of the Nrf-2/Ho-1/Antioxidants Axis. Arch. Physiol. Biochem. 2023, 129, 984–997. [Google Scholar] [CrossRef]
  149. Huang, H.; Yang, M.; Li, T.; Wang, D.; Li, Y.; Tang, X.; Yuan, L.; Gu, S.; Xu, Y. Neferine Inhibits the Progression of Diabetic Nephropathy by Modulating the miR-17-5p/Nuclear Factor E2-Related Factor 2 Axis. J. Tradit. Chin. Med. 2024, 44, 44–53. [Google Scholar] [CrossRef]
  150. Huang, Q.; Zhang, Y.; Jiang, Y.; Huang, L.; Liu, Q.; Ouyang, D. Eucommia Lignans Alleviate the Progression of Diabetic Nephropathy through Mediating the AR/Nrf2/HO-1/AMPK Axis in Vivo and in Vitro. Chin. J. Nat. Med. 2023, 21, 516–526. [Google Scholar] [CrossRef] [PubMed]
  151. Fan, D.; Ying, Z.; Yang, Y.; Qian, Q.; Li, Y.; Wang, P.; An, X.; Yan, M. Deciphering the Anti-Renal Fibrosis Mechanism of Triptolide in Diabetic Nephropathy by the Integrative Approach of Network Pharmacology and Experimental Verification. J. Ethnopharmacol. 2023, 316, 116774. [Google Scholar] [CrossRef] [PubMed]
  152. Lv, C.; Cheng, T.; Zhang, B.; Sun, K.; Lu, K. Triptolide Protects against Podocyte Injury in Diabetic Nephropathy by Activating the Nrf2/HO-1 Pathway and Inhibiting the NLRP3 Inflammasome Pathway. Ren. Fail. 2023, 45, 2165103. [Google Scholar] [CrossRef]
  153. Chen, L.; Fan, D.; Guo, F.; Deng, J.; Fu, L. The Effect of Moringa Isothiocyanate-1 on Renal Damage in Diabetic Nephropathy. Iran. J. Kidney Dis. 2023, 17, 245–254. [Google Scholar] [PubMed]
  154. Mohan, T.; Narasimhan, K.K.S.; Ravi, D.B.; Velusamy, P.; Chandrasekar, N.; Chakrapani, L.N.; Srinivasan, A.; Karthikeyan, P.; Kannan, P.; Tamilarasan, B.; et al. Role of Nrf2 Dysfunction in the Pathogenesis of Diabetic Nephropathy: Therapeutic Prospect of Epigallocatechin-3-Gallate. Free Radic. Biol. Med. 2020, 160, 227–238. [Google Scholar] [CrossRef]
  155. Ou, Y.; Zhang, W. Obacunone Inhibits Ferroptosis through Regulation of Nrf2 Homeostasis to Treat Diabetic Nephropathy. Mol. Med. Rep. 2025, 31, 135. [Google Scholar] [CrossRef]
  156. Lv, S.; Fan, L.; Chen, X.; Su, X.; Dong, L.; Wang, Q.; Wang, Y.; Zhang, H.; Cui, H.; Zhang, S.; et al. Jian-Pi-Gu-Shen-Hua-Yu Decoction Alleviated Diabetic Nephropathy in Mice through Reducing Ferroptosis. J. Diabetes Res. 2024, 2024, 9990304. [Google Scholar] [CrossRef]
  157. Xiong, D.; Hu, W.; Han, X.; Cai, Y. Rhein Inhibited Ferroptosis and EMT to Attenuate Diabetic Nephropathy by Regulating the Rac1/NOX1/β-Catenin Axis. Front. Biosci. (Landmark Ed.) 2023, 28, 100. [Google Scholar] [CrossRef]
  158. Lv, S.; Li, H.; Zhang, T.; Su, X.; Sun, W.; Wang, Q.; Wang, L.; Feng, N.; Zhang, S.; Wang, Y.; et al. San-Huang-Yi-Shen Capsule Ameliorates Diabetic Nephropathy in Mice through Inhibiting Ferroptosis. Biomed. Pharmacother. 2023, 165, 115086. [Google Scholar] [CrossRef] [PubMed]
  159. Wang, Y.; He, X.; Xue, M.; Sun, W.; He, Q.; Jin, J. Germacrone Protects Renal Tubular Cells against Ferroptotic Death and ROS Release by Re-Activating Mitophagy in Diabetic Nephropathy. Free Radic. Res. 2023, 57, 413–429. [Google Scholar] [CrossRef]
  160. Zhu, S.; Kang, Z.; Zhang, F. Tanshinone IIA Suppresses Ferroptosis to Attenuate Renal Podocyte Injury in Diabetic Nephropathy through the Embryonic Lethal Abnormal Visual-like Protein 1 and Acyl-Coenzyme a Synthetase Long-Chain Family Member 4 Signaling Pathway. J. Diabetes Investig. 2024, 15, 1003–1016. [Google Scholar] [CrossRef] [PubMed]
  161. Wang, X.; Li, Q.; Sui, B.; Xu, M.; Pu, Z.; Qiu, T. Schisandrin A from Schisandra chinensis Attenuates Ferroptosis and NLRP3 Inflammasome-Mediated Pyroptosis in Diabetic Nephropathy through Mitochondrial Damage by AdipoR1 Ubiquitination. Oxid. Med. Cell Longev. 2022, 2022, 5411462. [Google Scholar] [CrossRef]
  162. Jiao, H.; Zhang, M.; Chen, L.; Zhang, Z. Traditional Chinese Medicine Targeting the TGF-β/Smad Signaling Pathway as a Potential Therapeutic Strategy for Renal Fibrosis. Front. Pharmacol. 2025, 16, 1513329. [Google Scholar] [CrossRef] [PubMed]
  163. Zheng, W.; Qian, C.; Xu, F.; Cheng, P.; Yang, C.; Li, X.; Lu, Y.; Wang, A. Fuxin Granules Ameliorate Diabetic Nephropathy in Db/Db Mice through TGF-Β1/Smad and VEGF/VEGFR2 Signaling Pathways. Biomed. Pharmacother. 2021, 141, 111806. [Google Scholar] [CrossRef] [PubMed]
  164. Zhang, X.-X.; Liu, Y.; Xu, S.-S.; Yang, R.; Jiang, C.-H.; Zhu, L.-P.; Xu, Y.-Y.; Pan, K.; Zhang, J.; Yin, Z.-Q. Asiatic Acid from Cyclocarya paliurus Regulates the Autophagy-Lysosome System via Directly Inhibiting TGF-β Type I Receptor and Ameliorates Diabetic Nephropathy Fibrosis. Food Funct. 2022, 13, 5536–5546. [Google Scholar] [CrossRef]
  165. Yu, X.; Su, Q.; Geng, J.; Liu, H.; Liu, Y.; Liu, J.; Shi, Y.; Zou, Y. Ginkgo biloba Leaf Extract Prevents Diabetic Nephropathy through the Suppression of Tissue Transglutaminase. Exp. Ther. Med. 2021, 21, 333. [Google Scholar] [CrossRef]
  166. Huang, R.; Zeng, J.; Yu, X.; Shi, Y.; Song, N.; Zhang, J.; Wang, P.; Luo, M.; Ma, Y.; Xiao, C.; et al. Luteolin Alleviates Diabetic Nephropathy Fibrosis Involving AMPK/NLRP3/TGF-β Pathway. Diabetes Metab. Syndr. Obes. 2024, 17, 2855–2867. [Google Scholar] [CrossRef]
  167. Huang, B.; Han, R.; Tan, H.; Zhu, W.; Li, Y.; Jiang, F.; Xie, C.; Ren, Z.; Shi, R. Scutellarin Ameliorates Diabetic Nephropathy via TGF-Β1 Signaling Pathway. Nat. Prod. Bioprospect 2024, 14, 25. [Google Scholar] [CrossRef] [PubMed]
  168. Sun, X.; Yang, Y.; Sun, X.; Meng, H.; Hao, W.; Yin, J.; Ma, F.; Guo, X.; Du, L.; Sun, L.; et al. Krill Oil Turns Off TGF-Β1 Profibrotic Signaling in the Prevention of Diabetic Nephropathy. J. Agric. Food Chem. 2022, 70, 9865–9876. [Google Scholar] [CrossRef]
  169. Chen, Y.; Lin, X.; Zheng, Y.; Yu, W.; Lin, F.; Zhang, J. Dendrobium Mixture Ameliorates Diabetic Nephropathy in Db/Db Mice by Regulating the TGF-β 1/Smads Signaling Pathway. Evid.-Based Complement. Altern. Med. 2021, 2021, 9931983. [Google Scholar] [CrossRef]
  170. Wu, X.; Li, H.; Wan, Z.; Wang, R.; Liu, J.; Liu, Q.; Zhao, H.; Wang, Z.; Zhang, H.; Guo, H.; et al. The Combination of Ursolic Acid and Empagliflozin Relieves Diabetic Nephropathy by Reducing Inflammation, Oxidative Stress and Renal Fibrosis. Biomed. Pharmacother. 2021, 144, 112267. [Google Scholar] [CrossRef]
  171. Zhang, Q.; Xiao, X.; Zheng, J.; Li, M.; Yu, M.; Ping, F.; Wang, T.; Wang, X. Qishen Yiqi Dripping Pill Protects against Diabetic Nephropathy by Inhibiting the Wnt/β-Catenin and Transforming Growth Factor-β/Smad Signaling Pathways in Rats. Front. Physiol. 2021, 11, 613324. [Google Scholar] [CrossRef]
  172. Chen, W.; Su, J.; Liu, Y.; Gao, T.; Ji, X.; Li, H.; Li, H.; Wang, Y.; Zhang, H.; Lv, S. Crocin Ameliorates Diabetic Nephropathy through Regulating Metabolism, CYP4A11/PPARγ, and TGF-β/Smad Pathways in Mice. Curr. Drug Metab. 2023, 24, 709–722. [Google Scholar] [CrossRef]
  173. Chang, L.; Wang, Q.; Ju, J.; Li, Y.; Cai, Q.; Hao, L.; Zhou, Y. Magnoflorine Ameliorates Inflammation and Fibrosis in Rats with Diabetic Nephropathy by Mediating the Stability of Lysine-Specific Demethylase 3A. Front. Physiol. 2020, 11, 580406. [Google Scholar] [CrossRef]
  174. Ural, C.; Celik, A.; Ozbal, S.; Guneli, E.; Arslan, S.; Ergur, B.U.; Cavdar, C.; Akdoğan, G.; Cavdar, Z. The Renoprotective Effects of Taurine against Diabetic Nephropathy via the P38 MAPK and TGF-β/Smad2/3 Signaling Pathways. Amino Acids 2023, 55, 1665–1677. [Google Scholar] [CrossRef] [PubMed]
  175. Zheng, H.X.; Qi, S.S.; He, J.; Hu, C.Y.; Han, H.; Jiang, H.; Li, X.S. Cyanidin-3-Glucoside from Black Rice Ameliorates Diabetic Nephropathy via Reducing Blood Glucose, Suppressing Oxidative Stress and Inflammation, and Regulating Transforming Growth Factor Β1/Smad Expression. J. Agric. Food Chem. 2020, 68, 4399–4410. [Google Scholar] [CrossRef]
  176. Guo, C.; Wang, Y.; Piao, Y.; Rao, X.; Yin, D. Chrysophanol Inhibits the Progression of Diabetic Nephropathy via Inactivation of TGF-β Pathway. Drug Des. Devel Ther. 2020, 14, 4951–4962. [Google Scholar] [CrossRef] [PubMed]
  177. Gu, L.-Y.; Sun, Y.; Tang, H.-T.; Xu, Z.-X. Huangkui Capsule in Combination with Metformin Ameliorates Diabetic Nephropathy via the Klotho/TGF-Β1/p38MAPK Signaling Pathway. J. Ethnopharmacol. 2021, 281, 113548. [Google Scholar] [CrossRef] [PubMed]
  178. Luo, W.; Tang, S.; Xiao, X.; Luo, S.; Yang, Z.; Huang, W.; Tang, S. Translation Animal Models of Diabetic Kidney Disease: Biochemical and Histological Phenotypes, Advantages and Limitations. Diabetes Metab. Syndr. Obes. Targets Ther. 2023, 16, 1297–1321. [Google Scholar] [CrossRef]
  179. Fu, S.; Zhou, Y.; Hu, C.; Xu, Z.; Hou, J. Network Pharmacology and Molecular Docking Technology-Based Predictive Study of the Active Ingredients and Potential Targets of Rhubarb for the Treatment of Diabetic Nephropathy. BMC Complement. Med. Ther. 2022, 22, 210. [Google Scholar] [CrossRef]
  180. Selby-Pham, S.N.B.; Miller, R.B.; Howell, K.; Dunshea, F.; Bennett, L.E. Physicochemical Properties of Dietary Phytochemicals Can Predict Their Passive Absorption in the Human Small Intestine. Sci. Rep. 2017, 7, 1931. [Google Scholar] [CrossRef]
  181. Peng, S.; Wang, Y.; Sun, Z.; Zhao, L.; Huang, Y.; Fu, X.; Luo, R.; Xue, J.; Yang, S.; Ling, L.; et al. Nanoparticles Loaded with Pharmacologically Active Plant-Derived Natural Products: Biomedical Applications and Toxicity. Colloids Surf. B Biointerfaces 2023, 225, 113214. [Google Scholar] [CrossRef]
  182. Xu, L.; Zhao, B.; Yang, L.; Dong, X.; Yang, X.; Mao, Y. Demethylzeylasteral Reduces the Level of Proteinuria in Diabetic Nephropathy: Screening of Network Pharmacology and Verification by Animal Experiment. Pharmacol. Res. Perspect. 2022, 10, e00976. [Google Scholar] [CrossRef]
  183. Alvarez-Erviti, L.; Seow, Y.; Yin, H.; Betts, C.; Lakhal, S.; Wood, M.J.A. Delivery of siRNA to the Mouse Brain by Systemic Injection of Targeted Exosomes. Nat. Biotechnol. 2011, 29, 341–345. [Google Scholar] [CrossRef]
  184. Patra, J.K.; Das, G.; Fraceto, L.F.; Campos, E.V.R.; Rodriguez-Torres, M.D.P.; Acosta-Torres, L.S.; Diaz-Torres, L.A.; Grillo, R.; Swamy, M.K.; Sharma, S.; et al. Nano Based Drug Delivery Systems: Recent Developments and Future Prospects. J. Nanobiotechnol. 2018, 16, 71. [Google Scholar] [CrossRef]
  185. Uppal, S.; Italiya, K.S.; Chitkara, D.; Mittal, A. Nanoparticulate-Based Drug Delivery Systems for Small Molecule Anti-Diabetic Drugs: An Emerging Paradigm for Effective Therapy. Acta Biomater. 2018, 81, 20–42. [Google Scholar] [CrossRef]
  186. Bhutia, G.T.; De, A.K.; Bhowmik, M.; Bera, T. Shellac and Locust Bean Gum Coacervated Curcumin, Epigallocatechin Gallate Nanoparticle Ameliorates Diabetic Nephropathy in a Streptozotocin-Induced Mouse Model. Int. J. Biol. Macromol. 2024, 271, 132369. [Google Scholar] [CrossRef] [PubMed]
  187. Sun, S.; Du, X.; Fu, M.; Khan, A.R.; Ji, J.; Liu, W.; Zhai, G. Galactosamine-Modified PEG-PLA/TPGS Micelles for the Oral Delivery of Curcumin. Int. J. Pharm. 2021, 595, 120227. [Google Scholar] [CrossRef] [PubMed]
  188. Rostami, N.; Davarnejad, R. Characterization of Folic Acid-functionalized PLA–PEG Nanomicelle to Deliver Letrozole: A Nanoinformatics Study. IET Nanobiotechnol. 2021, 16, 103–114. [Google Scholar] [CrossRef] [PubMed]
  189. Xiong, F.; Hu, K.; Yu, H.; Zhou, L.; Song, L.; Zhang, Y.; Shan, X.; Liu, J.; Gu, N. A Functional Iron Oxide Nanoparticles Modified with PLA-PEG-DG as Tumor-Targeted MRI Contrast Agent. Pharm. Res. 2017, 34, 1683–1692. [Google Scholar] [CrossRef]
  190. Pulkkinen, M.; Pikkarainen, J.; Wirth, T.; Tarvainen, T.; Haapa-aho, V.; Korhonen, H.; Seppälä, J.; Järvinen, K. Three-Step Tumor Targeting of Paclitaxel Using Biotinylated PLA-PEG Nanoparticles and Avidin-Biotin Technology: Formulation Development and in Vitro Anticancer Activity. Eur. J. Pharm. Biopharm. Off. J. Arbeitsgemeinschaft Fur Pharm. Verfahrenstechnik E.V 2008, 70, 66–74. [Google Scholar] [CrossRef]
  191. Chen, X.; Zhou, Y.; Yu, J. Exosome-like Nanoparticles from Ginger Rhizomes Inhibited NLRP3 Inflammasome Activation. Mol. Pharm. 2019, 16, 2690–2699. [Google Scholar] [CrossRef]
  192. Zou, Z.; Li, H.; Xu, G.; Hu, Y.; Zhang, W.; Tian, K. Current Knowledge and Future Perspectives of Exosomes as Nanocarriers in Diagnosis and Treatment of Diseases. Int. J. Nanomed. 2023, 18, 4751–4778. [Google Scholar] [CrossRef]
  193. Yin, Y.; Han, X.; Li, C.; Sun, T.; Li, K.; Liu, X.; Liu, M. The Status of Industrialization and Development of Exosomes as a Drug Delivery System: A Review. Front. Pharmacol. 2022, 13, 961127. [Google Scholar] [CrossRef]
  194. Sun, D.; Zhuang, X.; Xiang, X.; Liu, Y.; Zhang, S.; Liu, C.; Barnes, S.; Grizzle, W.; Miller, D.; Zhang, H.-G. A Novel Nanoparticle Drug Delivery System: The Anti-Inflammatory Activity of Curcumin Is Enhanced When Encapsulated in Exosomes. Mol. Ther. 2010, 18, 1606–1614. [Google Scholar] [CrossRef] [PubMed]
  195. Davis, D.A.; Miller, D.A.; Santitewagun, S.; Zeitler, J.A.; Su, Y.; Williams, R.O. Formulating a Heat- and Shear-Labile Drug in an Amorphous Solid Dispersion: Balancing Drug Degradation and Crystallinity. Int. J. Pharm. X 2021, 3, 100092. [Google Scholar] [CrossRef]
  196. Binaymotlagh, R.; Hajareh Haghighi, F.; Chronopoulou, L.; Palocci, C. Liposome-Hydrogel Composites for Controlled Drug Delivery Applications. Gels 2024, 10, 284. [Google Scholar] [CrossRef]
  197. Haas, M.; Kluppel, A.C.; Wartna, E.S.; Moolenaar, F.; Meijer, D.K.; de Jong, P.E.; de Zeeuw, D. Drug-Targeting to the Kidney: Renal Delivery and Degradation of a Naproxen-Lysozyme Conjugate in Vivo. Kidney Int. 1997, 52, 1693–1699. [Google Scholar] [CrossRef]
  198. Wang, Y.; He, W.; Ren, P.; Zhao, L.; Zheng, D.; Jin, J. Carthamin Yellow-Loaded Glycyrrhetinic Acid Liposomes Alleviate Interstitial Fibrosis in Diabetic Nephropathy. Ren. Fail. 2025, 47, 2459356. [Google Scholar] [CrossRef]
  199. Zheng, X.-P.; Nie, Q.; Feng, J.; Fan, X.-Y.; Jin, Y.-L.; Chen, G.; Du, J.-W. Kidney-Targeted Baicalin-Lysozyme Conjugate Ameliorates Renal Fibrosis in Rats with Diabetic Nephropathy Induced by Streptozotocin. BMC Nephrol. 2020, 21, 174. [Google Scholar] [CrossRef]
  200. Li, L.; Wang, L.; Fan, W.; Jiang, Y.; Zhang, C.; Li, J.; Peng, W.; Wu, C. The Application of Fermentation Technology in Traditional Chinese Medicine: A Review. Am. J. Chin. Med. 2020, 48, 899–921. [Google Scholar] [CrossRef] [PubMed]
  201. Yñigez-Gutierrez, A.E.; Bachmann, B.O. Fixing the Unfixable: The Art of Optimizing Natural Products for Human Medicine. J. Med. Chem. 2019, 62, 8412–8428. [Google Scholar] [CrossRef] [PubMed]
  202. Zhou, Q.; Yang, F.; Li, Z.; Qu, Q.; Zhao, C.; Liu, X.; Yang, P.; Han, L.; Shi, Y.; Shi, X. Paecilomyces cicadae-Fermented Radix astragali Ameliorate Diabetic Nephropathy in Mice by Modulating the Gut Microbiota. J. Med. Microbiol. 2022, 71, 001535. [Google Scholar] [CrossRef]
  203. Xie, Y.; Liu, D.; Liu, Y.; Tang, J.; Zhao, H.; Chen, X.; Tian, G.; Liu, G.; Cai, J.; Jia, G. The Microbiota and Metabolome Dynamics and Their Interactions Modulate Solid-State Fermentation Process and Enhance Clean Recycling of Brewers’ Spent Grain. Front. Microbiol. 2024, 15, 1438878. [Google Scholar] [CrossRef]
  204. Xiao, Y.; Liu, Y.; Lai, Z.; Huang, J.; Li, C.; Zhang, Y.; Gong, X.; Deng, J.; Ye, X.; Li, X. An Integrated Network Pharmacology and Transcriptomic Method to Explore the Mechanism of the Total Rhizoma Coptidis Alkaloids in Improving Diabetic Nephropathy. J. Ethnopharmacol. 2021, 270, 113806. [Google Scholar] [CrossRef]
  205. Zhang, X.; Chao, P.; Zhang, L.; Lu, J.; Yang, A.; Jiang, H.; Lu, C. Integrating Network Pharmacology, Molecular Docking and Simulation Approaches with Machine Learning Reveals the Multi-Target Pharmacological Mechanism of Berberis integerrima against Diabetic Nephropathy. J. Biomol. Struct. Dyn. 2025, 43, 2092–2108. [Google Scholar] [CrossRef]
  206. Tarazona, S.; Arzalluz-Luque, A.; Conesa, A. Undisclosed, Unmet and Neglected Challenges in Multi-Omics Studies. Nat. Comput. Sci. 2021, 1, 395–402. [Google Scholar] [CrossRef] [PubMed]
  207. Tan, D.; Chen, Y.; Ilboudo, Y.; Liang, K.Y.H.; Butler-Laporte, G.; Richards, J.B. Caution When Using Network Partners for Target Identification in Drug Discovery. Hum. Genet. Genom. Adv. 2025, 6, 100409. [Google Scholar] [CrossRef] [PubMed]
  208. Shin, S.H.; Oh, S.M.; Yoon Park, J.H.; Lee, K.W.; Yang, H. OptNCMiner: A Deep Learning Approach for the Discovery of Natural Compounds Modulating Disease-Specific Multi-Targets. BMC Bioinf. 2022, 23, 218. [Google Scholar] [CrossRef] [PubMed]
  209. Öztürk, H.; Özgür, A.; Ozkirimli, E. DeepDTA: Deep Drug-Target Binding Affinity Prediction. Bioinformatics 2018, 34, i821–i829. [Google Scholar] [CrossRef]
  210. Sun, X.; Li, P.; Lin, H.; Ni, Z.; Zhan, Y.; Cai, G.; Liu, C.; Chen, Q.; Wang, W.; Wang, X.; et al. Efficacy and Safety of Abelmoschus manihot in Treating Chronic Kidney Diseases: A Multicentre, Open-Label and Single-Arm Clinical Trial. Phytomedicine 2022, 99, 154011. [Google Scholar] [CrossRef]
  211. Zhao, J.; Tostivint, I.; Xu, L.; Huang, J.; Gambotti, L.; Boffa, J.-J.; Yang, M.; Wang, L.; Sun, Z.; Chen, X.; et al. Efficacy of Combined Abelmoschus manihot and Irbesartan for Reduction of Albuminuria in Patients with Type 2 Diabetes and Diabetic Kidney Disease: A Multicenter Randomized Double-Blind Parallel Controlled Clinical Trial. Diabetes Care 2022, 45, e113–e115. [Google Scholar] [CrossRef]
  212. Ge, Y.; Xie, H.; Li, S.; Jin, B.; Hou, J.; Zhang, H.; Shi, M.; Liu, Z. Treatment of Diabetic Nephropathy with Tripterygium wilfordii Hook F Extract: A Prospective, Randomized, Controlled Clinical Trial. J. Transl. Med. 2013, 11, 134. [Google Scholar] [CrossRef]
  213. Sattarinezhad, A.; Roozbeh, J.; Shirazi Yeganeh, B.; Omrani, G.R.; Shams, M. Resveratrol Reduces Albuminuria in Diabetic Nephropathy: A Randomized Double-Blind Placebo-Controlled Clinical Trial. Diabetes Metab. 2019, 45, 53–59. [Google Scholar] [CrossRef]
  214. Liu, J.; Gao, L.-D.; Fu, B.; Yang, H.-T.; Zhang, L.; Che, S.-Q.; Xu, Y.; Du, X.; Liu, Z.-C.; Xue, Y.; et al. Efficacy and Safety of Zicuiyin Decoction on Diabetic Kidney Disease: A Multicenter, Randomized Controlled Trial. Phytomedicine 2022, 100, 154079. [Google Scholar] [CrossRef]
  215. Yang, H.; Xia, S.; Cong, Y.; Yang, X.; Min, J.; Wu, T. Effects of Qidan Tangshen Granule on Diabetic Kidney Disease in Patients with Type 2 Diabetes. Diabetes Res. Clin. Pract. 2024, 209, 111128. [Google Scholar] [CrossRef]
  216. Khajehdehi, P.; Pakfetrat, M.; Javidnia, K.; Azad, F.; Malekmakan, L.; Nasab, M.H.; Dehghanzadeh, G. Oral Supplementation of Turmeric Attenuates Proteinuria, Transforming Growth Factor-β and Interleukin-8 Levels in Patients with Overt Type 2 Diabetic Nephropathy: A Randomized, Double-Blind and Placebo-Controlled Study. Scand. J. Urol. Nephrol. 2011, 45, 365–370. [Google Scholar] [CrossRef]
  217. Xiong, C.; Li, L.; Bo, W.; Chen, H.; XiaoWei, L.; Hongbao, L.; Peng, Z. Evaluation of the Efficacy and Safety of TWHF in Diabetic Nephropathy Patients with Overt Proteinuria and Normal eGFR. J. Formos. Med. Assoc. 2020, 119, 685–692. [Google Scholar] [CrossRef]
  218. Lengnan, X.; Ban, Z.; Haitao, W.; Lili, L.; Aiqun, C.; Huan, W.; Ping, Z.; Yonghui, M. Tripterygium wilfordii Hook F Treatment for Stage IV Diabetic Nephropathy: Protocol for a Prospective, Randomized Controlled Trial. Biomed. Res. Int. 2020, 2020, 9181037. [Google Scholar] [CrossRef]
  219. Cai, T.-T.; Ye, X.-L.; Li, R.-R.; Chen, H.; Wang, Y.-Y.; Yong, H.-J.; Pan, M.-L.; Lu, W.; Tang, Y.; Miao, H.; et al. Resveratrol Modulates the Gut Microbiota and Inflammation to Protect against Diabetic Nephropathy in Mice. Front. Pharmacol. 2020, 11, 1249. [Google Scholar] [CrossRef]
  220. Liu, X.; Gu, X.; Zhang, J.; Li, X.; Wei, X.; Jiang, S.; Li, W. Resveratrol Delays the Progression of Diabetic Nephropathy through Multiple Pathways: A Dose-Response Meta-Analysis Based on Animal Models. J. Diabetes 2024, 16, e13608. [Google Scholar] [CrossRef]
  221. Walle, T.; Hsieh, F.; DeLegge, M.H.; Oatis, J.E.; Walle, U.K. High Absorption but Very Low Bioavailability of Oral Resveratrol in Humans. Drug Metab. Dispos. Biol. Fate Chem. 2004, 32, 1377–1382. [Google Scholar] [CrossRef]
  222. Smoliga, J.M.; Blanchard, O. Enhancing the Delivery of Resveratrol in Humans: If Low Bioavailability Is the Problem, What Is the Solution? Molecules 2014, 19, 17154–17172. [Google Scholar] [CrossRef] [PubMed]
  223. Liao, T.; Zhao, K.; Huang, Q.; Tang, S.; Chen, K.; Xie, C.; Zhang, C.; Gan, W. A Randomized Controlled Clinical Trial Study Protocol of Liuwei Dihuang Pills in the Adjuvant Treatment of Diabetic Kidney Disease. Medicine 2020, 99, e21137. [Google Scholar] [CrossRef]
  224. Jin, D.; Huang, W.-J.; Meng, X.; Yang, F.; Bao, Q.; Zhang, M.; Yang, Y.; Ni, Q.; Lian, F.-M.; Tong, X.-L. Chinese Herbal Medicine Tangshen Formula Treatment for Type 2 Diabetic Kidney Disease in the Early Stage: Study Protocol for a Randomized Controlled Trial. Trials 2019, 20, 756. [Google Scholar] [CrossRef] [PubMed]
  225. Yan, M.; Wen, Y.; Yang, L.; Wu, X.; Lu, X.; Zhang, B.; Huang, W.; Li, P. Chinese Herbal Medicine Tangshen Formula Treatment of Patients with Type 2 Diabetic Kidney Disease with Macroalbuminuria: Study Protocol for a Randomized Controlled Trial. Trials 2016, 17, 259. [Google Scholar] [CrossRef] [PubMed]
Figure 1. Schematic diagram of the pathogenesis of diabetic kidney disease (DKD).
Figure 1. Schematic diagram of the pathogenesis of diabetic kidney disease (DKD).
Ijms 26 11637 g001
Figure 2. Schematic diagram of the key pathological cascade of diabetic kidney disease (DKD) kidney injury and the regulatory role of natural medicines.
Figure 2. Schematic diagram of the key pathological cascade of diabetic kidney disease (DKD) kidney injury and the regulatory role of natural medicines.
Ijms 26 11637 g002
Figure 3. Schematic diagram illustrating the mechanism of natural medicines blocking inflammation-mediated kidney damage progression in diabetic kidney disease (DKD) via regulating the NF-κB pathway.
Figure 3. Schematic diagram illustrating the mechanism of natural medicines blocking inflammation-mediated kidney damage progression in diabetic kidney disease (DKD) via regulating the NF-κB pathway.
Ijms 26 11637 g003
Figure 4. Schematic diagram illustrating the regulatory “antioxidation-ferroptosis-immunity” dynamic network of natural products.
Figure 4. Schematic diagram illustrating the regulatory “antioxidation-ferroptosis-immunity” dynamic network of natural products.
Ijms 26 11637 g004
Figure 5. Schematic diagram illustrating the main areas of pharmaceutical technology innovations.
Figure 5. Schematic diagram illustrating the main areas of pharmaceutical technology innovations.
Ijms 26 11637 g005
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Guo, M.; Ni, L.; Wu, X. Natural Products as Potential Therapeutic Candidates for Diabetic Kidney Disease: Molecular Mechanisms, Translational Challenges, and Future Prospects. Int. J. Mol. Sci. 2025, 26, 11637. https://doi.org/10.3390/ijms262311637

AMA Style

Guo M, Ni L, Wu X. Natural Products as Potential Therapeutic Candidates for Diabetic Kidney Disease: Molecular Mechanisms, Translational Challenges, and Future Prospects. International Journal of Molecular Sciences. 2025; 26(23):11637. https://doi.org/10.3390/ijms262311637

Chicago/Turabian Style

Guo, Manqi, Lihua Ni, and Xiaoyan Wu. 2025. "Natural Products as Potential Therapeutic Candidates for Diabetic Kidney Disease: Molecular Mechanisms, Translational Challenges, and Future Prospects" International Journal of Molecular Sciences 26, no. 23: 11637. https://doi.org/10.3390/ijms262311637

APA Style

Guo, M., Ni, L., & Wu, X. (2025). Natural Products as Potential Therapeutic Candidates for Diabetic Kidney Disease: Molecular Mechanisms, Translational Challenges, and Future Prospects. International Journal of Molecular Sciences, 26(23), 11637. https://doi.org/10.3390/ijms262311637

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop