Published online Jul 15, 2026. doi: 10.4239/wjd.121202
Revised: May 12, 2026
Accepted: June 9, 2026
Published online: July 15, 2026
Processing time: 113 Days and 7.5 Hours
Type 2 diabetes mellitus (T2DM) is not only a disorder of glucose and lipid metabolism, but also closely associated with disturbances in amino acid meta
To investigate the regulatory effects of DGF on the hepatic NAMPT/NAD+/SIRT1 axis and amino acid metabolism in T2DM rats.
A T2DM rat model was established by a high-glucose and high-fat diet combined with streptozotocin injection. Rats were randomly assigned into four groups, namely the control group, model group, DGF group (DFG, 20 g/kg), and metformin group (0.11 g/kg), with eight rats in each group. After 14 weeks of intervention, glucolipid metabolism-related indicators, expression of the NAMPT/NAD+/SIRT1 axis, and hepatic amino acid metabolism were evaluated.
Compared with the model group, the DFG and metformin groups exhibited significantly increased body weight and high-density lipoprotein cholesterol levels (P < 0.05 and P < 0.01), accompanied by reductions in fasting and postprandial blood glucose, liver weight, liver index, haemoglobin A1c, total cholesterol, triglycerides, low-density lipoprotein cholesterol, and free fatty acid levels (P < 0.05 and P < 0.01), along with alleviated hepatic histopathological damage and significantly upregulated NAMPT and SIRT1 mRNA and protein expression (P < 0.05 and P < 0.01), as well as elevated NAD+ content (P < 0.01). In the DFG group, several key metabolic pathways were significantly modulated, including riboflavin metabolism, pentose and glucuronate interconversions, purine metabolism, glycolysis/gluconeogenesis, and vitamin B6 metabolism, indicating significant modulation of amino acid metabolism.
DGF significantly ameliorates glucolipid metabolism in T2DM rats, an effect that may be mediated by regulation of the hepatic NAMPT/NAD+/SIRT1 axis and amino acid metabolism disorders.
Core Tip: This study demonstrated that Dangua Fang (DGF) ameliorated glucolipid metabolic disorders in type 2 diabetes mellitus rats. DGF reduced blood glucose and lipid levels and alleviated hepatic histopathological injury. These effects were accompanied by increased hepatic nicotinamide phosphoribosyltransferase, nicotinamide adenine dinucleotide, and sirtuin 1 expression. Metabolomic analysis further revealed that DGF significantly regulated abnormal hepatic amino acid metabolism in diabetic rats, which might be associated with modulation of the nicotinamide phosphoribosyltransferase/nicotinamide adenine dinucleotide/sirtuin 1 axis.
- Citation: Han Z, Wang ZT, Yang LQ, Heng XP. Regulatory effects of Dangua Fang on the NAMPT/NAD+/SIRT1 axis and amino acid metabolism in type 2 diabetic rats. World J Diabetes 2026; 17(7): 121202
- URL: https://www.wjgnet.com/1948-9358/full/v17/i7/121202.htm
- DOI: https://dx.doi.org/10.4239/wjd.121202
Diabetes mellitus is a metabolic disorder involving dysregulated glucolipid and amino acid metabolism[1,2]. Amino acid metabolism disorders are commonly observed in patients with diabetes and constitute a key factor limiting further improvements in clinical outcomes for diabetes[2]. By the end of 2022, the global number of individuals with diabetes reached approximately 828 million, more than fourfold the figure recorded in 1990, and it is projected to rise to 1.31 billion by 2050[3,4]. Persistent hyperglycaemia leads to progressive multisystem damage, affecting vital organs such as the heart, brain, and kidneys, and can ultimately be life-threatening[5]. Large-scale international evidence-based trials, including the Action to Control Cardiovascular Risk in Diabetes, Veterans Affairs Diabetes Trial, and Action in Diabetes and Vascular Disease: Preterax and Diamicron Modified Release Controlled Evaluation, have demonstrated that although intensive glycemic control can reduce micro- and macrovascular complications, current comprehensive treatment strategies - encompassing glucose, lipid, blood pressure, and weight management - still fail to yield additional long-term benefits for patients with diabetes and may even aggravate disturbances in amino acid metabolism[1,6]. Consequently, ameliorating amino acid metabolism disorders has emerged as a crucial bottleneck to overcome in the comprehensive management of diabetes and is increasingly recognized as a new focus of research[1].
Amino acid metabolism plays a crucial role in energy production, biosynthesis, and metabolic signaling regulation, and its dysregulation can activate the mechanistic target of rapamycin pathway, induce insulin resistance (IR), and promote the development of type 2 diabetes mellitus (T2DM) and related complications[2]. The nicotinamide phosphoribosyltransferase (NAMPT)/nicotinamide adenine dinucleotide (NAD+)/sirtuin 1 (SIRT1) axis serves as a key regulatory network that links energy metabolism to disease progression[7]. NAMPT, the rate-limiting enzyme in the NAD+ salvage pathway, catalyses the conversion of nicotinamide to NAD+, and its activity is modulated by SIRT1[8]. In turn, SIRT1 is NAD+-dependent for its deacetylase function, which further enhances NAMPT activity - forming a positive feedback loop critical for maintaining metabolic homeostasis and regulating insulin sensitivity[9]. Although the NAMPT/NAD+/SIRT1 axis has been widely studied in the context of energy metabolism, its role in modulating amino acid metabolism profiles to improve glucolipid metabolism remains largely unexplored[7]. Therefore, targeting amino acid metabolism via this regulatory axis may provide novel therapeutic strategies and theoretical foundations for the prevention and treatment of T2DM.
Dangua Fang (DGF), a traditional Chinese medicine (TCM) formulation, is employed to regulate glucolipid metabolism. It holds a national invention patent (patent No. 201410599300.6) and has been approved for clinical use by the Fujian Provincial Drug Administration (approval No. Min Z20150008). A three-year randomised controlled trial demonstrated that DGF significantly reduced insulin requirements in patients with T2DM, decreased lower-limb atherosclerosis ultrasound scores, improved left ventricular diastolic function, and lowered the incidence of new-onset coronary heart disease and all-cause adverse events[6]. In animal models, DGF has been shown to reduce blood glucose and lipid levels, decrease peritesticular and perirenal fat accumulation, upregulate hepatic NAMPT expression, increase the NAD+ content, and partially ameliorate amino acid metabolism disorders[10-12]. Based on these findings, the present study further explores the regulatory effects of DGF on the hepatic NAMPT/NAD+/SIRT1 axis and amino acid metabolism in T2DM rats, aiming to elucidate a potential novel mechanism through which DGF modulates metabolism and to broaden the scope of TCM in managing glucolipid metabolism (Figure 1).
Bayer blood glucose meter (Bayer Healthcare AG, Germany, CR2032); refrigerated centrifuge (Thermo Fisher Scientific, United States, Legend Micro 21R); electronic balance (Shanghai Shunyu Hengping Scientific Instruments Co., Ltd., JA2003); ultrapure water system (Millipore, United States, Direct-Q3); vortex mixer and constant temperature shaker (Qilinbell Instrument Manufacturing Co., MX-S, TS-1); micro-volume UV-visible spectrophotometer (Hangzhou Miao Instrument Co., Ltd., ND-100C); microplate reader (Shanghai Diken Experimental Equipment Co., Ltd., Infinite F50); electric blast drying oven (Shanghai Yiheng Scientific Instruments Co., Ltd., DHG-9070); embedding machine and rotary microtome (Leica, Germany, EG1150H, RM2016); optical microscope (Nikon, Japan, Eclipse E100); quantitative reverse-transcription polymerase chain reaction (qRT-PCR) system, vertical electrophoresis apparatus, and semi-dry transfer system (Bio-Rad, United States, CFX96 Touch, PowerPac Basic, Trans-Blot Turbo).
Streptozotocin (STZ) and ethyl carbamate (Sigma-Aldrich Trading Co., Ltd., S8050, PH006652); total cholesterol (TC), haemoglobin A1c (HbA1c), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), free fatty acid (FFA) and low-density lipoprotein cholesterol (LDL-C) assay kits (Nanjing Jiancheng Bioengineering Institute, A111-2-1, A056-1-1, A110-1-1, A112-1-1, A042-2-1, A113-1-1); haematoxylin and eosin (HE) staining kit (LandJeko Technology Co., Ltd., BL700B); Masson’s trichrome (Masson) stain kit and oil red O staining solution (Beijing Solarbio Technology Co., Ltd., G1340, G1261); 2 × SYBR Green qPCR mix (Shandong Sikejie Biotechnology Co., Ltd., AH0104-A); phosphate-buffered saline, bicinchoninic acid assay (BCA) kit, and antibody diluent (Wuhan Boshide Bioengineering Co., Ltd., PYG0072, AR0146, AR1017); radioimmunoprecipitation assay lysis buffer, 5 × sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) sample loading buffer, 10% SDS-PAGE rapid gel preparation kit, and ultra-sensitive chemiluminescence detection kit (Shanghai Yamei Biopharmaceutical Technology Co., Ltd., PC103, LT102 L, AR0146, SQ201).
Thirty-two specific pathogen-free SD rats (7 weeks old, body weight approximately 230 g). All procedures involving animals were reviewed and approved by the Institutional Animal Care and Use Committee of Fujian University of Traditional Chinese Medicine, approval No. 2024072. The animals were kept under standardized environmental conditions, including a temperature of 22 °C ± 2 °C, relative humidity of 50% ± 5%, daily temperature fluctuations below 4 °C, and a 12 hours light/dark photoperiod. All rats had free access to food and water, with bedding replaced regularly to maintain dry cages. An acclimatisation period of one week was provided. The procedures strictly adhered to ethical guidelines for animal experimentation and ensured animal welfare throughout the study.
The DGF decoction is an in-hospital formulation, prepared by mixing multiple medicinal herbs according to the prescribed ratios. The botanical names of the medicinal plants were verified via the World Flora Online database on 30 May 2025 (Table 1). After cleaning and necessary processing, the herbs were added to 500 mL of distilled water, decocted, filtered, and concentrated to obtain a solution containing 2 g/mL of the raw herbs. Quality control and phytochemical analysis of DGF have been reported in our previous study[13]. Based on prior dose-finding studies, 20 g/kg administered via gavage was determined to be the optimal dose for improving glucolipid metabolism in rats[10-12]. Metformin hydrochloride tablets (0.25 g, Shanghai Xinyi Pharmaceutical Co., Ltd., H31022081) were pulverized and dispersed in sterile water to obtain a 10 mg/mL suspension, which was subsequently stored at 4 °C.
| Chinese name | Scientific name | Used parts | Per 100 g (g) |
| Danshen | Salvia miltiorrhiza Bunge | Root | 18.75 |
| Gualou | Trichosanthes kirilowii Maxim | Fruit and seeds | 18.75 |
| Chuanxiong | Conioselinum anthriscoides “Chuanxiong” | Rhizome | 12.5 |
| Yujin | Curcuma longa L | Root | 12.5 |
| Xiebai | Allium macrostemon Bunge | Bulb | 12.5 |
| Chishao | Paeonia lactiflora Pall | Root | 12.5 |
| Banxia | Pinellia ternata (Thunb) Makino | Rhizome | 6.25 |
| Jiangcan | Bombyx batryticatus | Whole insect | 6.25 |
Eight rats were randomly assigned to the control group (CON) and maintained on a standard chow diet, whereas the remaining animals received a high-glucose and high-fat diet consisting of 70.7% standard chow, 20% sucrose, 7% refined lard, 2% cholesterol, and 0.3% pig bile salt. After 4 weeks of dietary intervention, body weight was recorded following a 10-hour fast with unrestricted access to water. Diabetes was induced by intraperitoneal administration of 10 mg/mL STZ at a dose of 25 mg/kg for two consecutive days under light-protected conditions. Fasting blood glucose (FBG) levels were determined 48 hours and 72 hours after the final injection following a 10 hours fasting period with free access to water. Rats meeting either of the criteria - two consecutive FBG readings ≥ 11.1 mmol/L or two random blood glucose measurements ≥ 16.7 mmol/L on different days with at least 24 hours interval - were considered successfully modelled[10-12].
Successfully modelled rats were randomly assigned into three groups using a random number table, namely the model group (MOD), DGF group (DFG), and metformin group (MET), with 8 rats per group. The CON and MOD groups received sterile water (10 mL/kg), while the DGF and MET groups were administered DGF decoction (20 g/kg) and metformin solution (0.11 g/kg), respectively. All treatments were delivered via gavage once daily for 14 weeks[10-12].
Rats were fasted for 10 hours (water allowed), then intraperitoneally injected with 200 mg/mL ethyl carbamate solution (5 mL/kg), with additional CO2 anaesthesia to ensure sufficient depth. Under full anaesthesia, blood was collected from the abdominal aorta, allowed to clot at room temperature for 30 minutes, and centrifuged at 3000 rpm at 4 °C for 15 minutes to separate serum, which was stored at -80 °C. The liver was rapidly excised, rinsed three times with pre-chilled phosphate-buffered saline, gently blotted dry with filter paper, weighed, and photographed. The left median lobe was fixed in 40 mg/mL paraformaldehyde, while the remaining liver tissue was snap-frozen and stored at -80 °C for subsequent analyses.
Glucolipid metabolism-related indicators: Food and water intake, behavioural changes, activity levels, and faecal characteristics were monitored and recorded throughout the experimental period. Fasted body weight was measured every two weeks, while FBG and postprandial blood glucose (PBG) were assessed at 5-week intervals. At the end of the study, liver weight was recorded and the liver index was calculated as liver weight divided by final body weight × 100%. Serum biochemical indices, including TC, HbA1c, TG, HDL-C, FFA and LDL-C.
HE, Masson, and oil red O staining: Liver tissues were subjected to HE, Masson, and oil red O staining. For HE staining, fixed tissues were dehydrated through a graded ethanol series, cleared, embedded in paraffin, and sectioned at 4 μm. Sections were then dewaxed to water, stained with haematoxylin for 5 minutes, differentiated in hydrochloric acid-ethanol, rinsed under running water for bluing, and subsequently stained with eosin for 3 minutes. After dehydration through graded ethanol and clearing with xylene, the sections were mounted with neutral resin. For Masson’s trichrome staining, paraffin sections were dewaxed to water and stained with Weigert’s iron haematoxylin for 7 minutes, followed by differentiation in acid ethanol and rinsing under running water. Sections were then blued with Masson’s blue solution for 5 minutes, stained with ponceau-fuchsin for 7 minutes, rinsed with weak acid solution, differentiated with phosphomolybdic acid for 1 minute, and stained with aniline blue for 3 minutes. After a final rinse in weak acid solution, the sections were dehydrated, cleared with xylene, and mounted with neutral resin. For oil red O staining, liver tissues were embedded in optimal cutting temperature compound and sectioned at -20 °C. Frozen sections were fixed in neutral formalin for 10 minutes, rinsed with distilled water, and immersed in isopropanol for 1 minute. Sections were then stained with oil red O solution in the dark for 15 minutes, differentiated in isopropanol, counterstained with Mayer’s haematoxylin for 2 minutes, and mounted using glycerol gelatin.
qRT-PCR: Total RNA was extracted from frozen liver tissue using the TRIzol method for qRT-PCR analysis of NAMPT and SIRT1 mRNA expression. After grinding tissues under liquid nitrogen, RNA was isolated via chloroform extraction and isopropanol precipitation. RNA purity was verified by measuring the A260/A280 ratio (acceptable range: 1.8-2.0) using a NanoDrop 2000 spectrophotometer. cDNA synthesis and qRT-PCR were performed following the manufacturer’s protocols. The 20 μL reaction system included 2 × SYBR qPCR Mix (10 μL), forward and reverse primers (0.4 μL each), cDNA template (1 μL), and RNase-free water (8.2 μL). Primers were synthesised and purified by Fuzhou Bellman Biotechnology Co., Ltd (Table 2). β-actin was used as an internal reference for standardised quantification.
| Name | Sequences (5’-3’) | Length (bp) |
| NAMPT | F: GTTGCTGCCACCTTACCTTAG | 126 |
| R: CCACCAGAACCAAAGGAGAC | ||
| SIRT1 | F: GACGCCTTATCCTCTAGTTCCT | 130 |
| R: CAGCATCATCTTCCAAGCCATT | ||
| β-actin | F: CGCGAGTACAACCTTCTTGC | 211 |
| R: CCTTCTGACCCATACCCACC |
Western blot: Total protein was extracted from liver tissue using radioimmunoprecipitation assay lysis buffer containing broad-spectrum protease and phosphatase inhibitors to detect NAMPT and SIRT1 protein expression. After homogenisation and centrifugation at 12000 × g for 10 minutes at 4 °C, the supernatant was collected, and protein concentration was determined using the BCA assay. Equal amounts of protein were mixed with 5 × SDS-PAGE loading buffer, denatured at 100 °C for 5 minutes, separated by 10% SDS-PAGE and transferred to polyvinylidene fluoride membranes. Membranes were blocked with skimmed milk for 1 hour at room temperature and incubated overnight at 4 °C with primary antibodies (1:5000 dilution). The next day, membranes were washed three times and incubated with horseradish peroxidase-conjugated secondary antibodies (1:12000 dilution) for 1 h at room temperature. Protein bands were visualised using the Bio-Rad ChemiDoc XRS+ system, and band intensities were quantified using ImageJ software. β-actin was used as an internal reference for standardised quantification.
Immunohistochemical analysis: Liver sections were deparaffinized, rehydrated, and incubated with hydrogen peroxide for 10 minutes to quench endogenous peroxidase activity. Antigen retrieval was then carried out in citrate buffer (pH 6.0). After blocking with BSA at 37 °C for 30 minutes, the sections were incubated overnight at 4 °C with the primary antibody. On the following day, slides were washed and sequentially incubated with biotinylated goat anti-rabbit IgG, the streptavidin-biotin complexcomplex, and 3,3′-diaminobenzidine chromogen. Finally, sections were counterstained with haematoxylin, followed by dehydration, clearing, and mounting. Images were captured and quantified using ImageJ software.
Targeted metabolomics analysis: Liquid chromatography-tandem mass spectrometry was used to measure NAD+ levels in rat liver and analyse amino acid metabolism. Appropriate amounts of liver tissue were homogenised with pre-cooled methanol/acetonitrile mixture [1:1, volume/volume (v/v)] containing isotopic internal standards, centrifuged at 12000 × g for 10 minutes, then nitrogen-dried and reconstituted in acetonitrile solution, followed by a second centrifugation, and the supernatant collected. Standard stock solutions were mixed in different volumes to prepare working solutions and serial calibration standards by gradient dilution (containing isotopic internal standard concentrations consistent with samples). Chromatographic separation was performed on an agilent 1290 ultra-high-performance liquid chromatography system equipped with a Waters Atlantis Premier BEH Z-HILIC column (1.7 μm, 2.1 mm × 150 mm). Mobile phase A consisted of 10 mmol/L ammonium formate aqueous solution-acetonitrile (9:1, v/v), mobile phase B was 10 mmol/L ammonium formate aqueous solution-acetonitrile (1:9, v/v). The autosampler temperature was maintained at 4 °C, and injection volume was 1 μL. Mass spectrometry was performed using an AB Sciex QTrap 6500 plus triple quadrupole mass spectrometer with electrospray ionisation voltage at +5500 V/-4500 V (positive/negative ion modes), curtain gas pressure of 35 pounds per square inch, ion source temperature of 400 °C, and nebuliser gas pressure of 50 pounds per square inch. Raw data were processed with SCIEX Analyst software, metabolites quantified using BIOTREE BioBu software, and metabolic pathway analysis conducted based on the Kyoto Encyclopedia of Genes and Genomes.
Statistical analyses were conducted using SPSS version 28.0. Data conforming to normal distribution and homogeneity of variance are presented as mean ± SD and were analysed using analysis of variance, followed by the least significant difference post hoc test. For data that did not meet the assumption of equal variance, logarithmic transformation was applied prior to analysis using one-way analysis of variance with the same post hoc procedure. Statistical significance was defined at P < 0.05 and P < 0.01.
Compared with the CON group, rats in the MOD group exhibited significantly decreased body weight and HDL-C levels (P < 0.05 and P < 0.01), whereas levels of FBG, PBG, liver weight, liver index, HbA1c, TC, TG, LDL-C, and FFA were significantly elevated (P < 0.01). Compared with the MOD group, body weight (weeks 7-15) in the DFG and MET groups increased significantly (P < 0.05 and P < 0.01), and HDL-C levels also rose, though not significantly. FBG (weeks 7-15), PBG (weeks 7-15), liver weight, liver index, HbA1c, TC, TG (the MET group), LDL-C, and FFA levels were significantly reduced (P < 0.05 and P < 0.01). Although TG levels declined in the DFG group, the reduction was not statistically significant (Figure 2; Tables 3 and 4).
| Group | FBG (mmol/L) | PBG (mmol/L) | ||||
| Week 1 | Week 7 | Week 15 | Week 1 | Week 7 | Week 15 | |
| CON | 6.41 ± 0.83 | 5.30 ± 0.90 | 6.66 ± 0.82 | 7.14 ± 0.72 | 6.06 ± 0.74 | 6.16 ± 0.68 |
| MOD | 16.53 ± 1.72a | 18.17 ± 2.38a | 19.77 ± 1.45a | 20.20 ± 2.52a | 22.23 ± 3.28a | 25.25 ± 2.95a |
| DFG | 15.98 ± 2.17 | 12.18 ± 1.61c | 14.37 ± 1.89c | 20.18 ± 2.33 | 12.76 ± 2.71c | 22.06 ± 3.31b |
| MET | 15.94 ± 1.94 | 9.71 ± 1.95c | 13.41 ± 1.77c | 19.89 ± 2.34 | 13.07 ± 3.16c | 15.79 ± 3.28c |
| Group | Liver weight (g) | Liver index (%) | HbA1c (mg/L) | TC (mmol/L) | TG (mmol/L) | HDL-C (mmol/L) | LDL-C (mmol/L) | FFA (mmol/L) |
| CON | 12.32 ± 2.75 | 3.28 ± 1.22 | 0.52 ± 0.08 | 2.27 ± 1.34 | 4.09 ± 1.38 | 1.60 ± 0.28 | 0.15 ± 0.08 | 0.80 ± 0.24 |
| MOD | 24.79 ± 2.75a | 8.39 ± 2.39a | 1.82 ± 0.25a | 22.12 ± 2.45a | 11.08 ± 2.62a | 0.85 ± 0.25a | 1.40 ± 0.18a | 1.55 ± 0.33a |
| DFG | 21.53 ± 2.78b | 6.15 ± 1.66b | 1.23 ± 0.21c | 11.16 ± 1.66c | 9.09 ± 2.08 | 1.01 ± 0.23 | 0.87 ± 0.15c | 0.73 ± 0.26c |
| MET | 21.02 ± 2.55b | 5.86 ± 1.57b | 0.98 ± 0.16c | 10.88 ± 2.42c | 8.77 ± 2.17b | 1.05 ± 0.22 | 0.80 ± 0.14c | 0.65 ± 0.24c |
HE staining revealed that in the CON group, hepatic lobule architecture was intact, hepatocytes were polygonal with homogeneous cytoplasm, nuclei were large, round, and centrally located, and hepatic cords were radially arranged, with no visible inflammatory infiltration or necrosis. In the MOD, DFG, and MET groups, lobular architecture was disrupted, hepatocytes appeared swollen, deformed, and densely packed, with pale cytoplasm, vacuolation or eosinophilic granules, nuclear pyknosis or displacement, and inflammatory cell infiltration in the portal area, most pronounced in the MOD group (Figure 3A). Masson staining demonstrated that collagen fibres in the CON, DFG, and MET groups were lightly stained and localised primarily to the portal and perivascular regions, with no obvious collagen deposition in the hepatic parenchyma. In the MOD group, extensive collagen accumulation was observed within the parenchyma, forming fibrous septa that encircled hepatic lobules and led to the formation of pseudolobules (Figure 3B). Oil red O staining showed minimal lipid accumulation in the hepatocytes of the CON group, with only a few small red lipid droplets observed. In contrast, the MOD, DFG, and MET groups exhibited significant cytoplasmic lipid droplet accumulation, either diffusely or focally distributed, accompanied by peripheral displacement of the nucleus. The extent of lipid deposition was most pronounced in the MOD group (Figure 3C).
Compared with the CON group, the MOD group exhibited significantly decreased hepatic expression levels of NAMPT and SIRT1 mRNA and proteins (P < 0.01), along with a marked decrease in NAD+ content (P < 0.01). In contrast, both the DFG and MET groups exhibited significantly increased expression of NAMPT and SIRT1 mRNA and proteins (P < 0.05 and P < 0.01), as well as significantly elevated NAD+ content (P < 0.01), compared with the MOD group (Figure 4A-C;Table 5).
| Group | NAD+ | NAMPT | SIRT1 | ||||
| mRNA | Protein | Positive area (%) | mRNA | Protein | Positive area (%) | ||
| CON | 77.12 ± 13.19 | 1.28 ± 0.21 | 1.69 ± 0.21 | 58.75 ± 7.55 | 1.18 ± 0.19 | 1.37 ± 0.21 | 61.14 ± 6.09 |
| MOD | 9.62 ± 3.22a | 0.73 ± 0.22a | 0.82 ± 0.22a | 19.77 ± 3.92a | 0.56 ± 0.23a | 0.81 ± 0.19a | 23.67 ± 3.98a |
| DFG | 26.34 ± 7.73c | 1.08 ± 0.23c | 1.54 ± 0.23c | 43.83 ± 5.31c | 0.99 ± 0.20c | 1.24 ± 0.24c | 47.77 ± 5.03c |
| MET | 29.63 ± 10.68c | 1.01 ± 0.22b | 1.49 ± 0.19c | 50.22 ± 5.34c | 1.04 ± 0.18c | 1.29 ± 0.23c | 36.21 ± 5.08c |
Principal component analysis: Principal component analysis showed that samples within each group clustered tightly, with clear discrimination between different groups (Figure 5A). A pronounced separation was observed between the CON and MOD groups, suggesting that the high-glucose and high-fat diet combined with STZ induced marked disturbances in hepatic amino acid metabolism (Figure 5B). Both the DFG and MET groups were separated from the MOD group and located closer to the CON group, indicating that these interventions partially ameliorated amino acid metabolic disorders (Figure 5C and D). Nevertheless, owing to the intrinsic complexity of amino acid metabolism and potential confounding factors, complete separation among all groups was not achieved.
Orthogonal projections to latent structures discriminant analysis: To further characterize intergroup metabolic differences, orthogonal projections to latent structures discriminant analysis was conducted. Distinct separations were observed between the CON and MOD groups (Q2 = 0.80, P2Y = 0.98), the MOD and DFG groups (Q2 = 0.04, P2Y = 0.93), and the MOD and MET groups (Q2 = 0.39, P2Y = 0.94), indicating notable differences in amino acid metabolic profiles among the groups. The robustness of the models was assessed using 200 permutation tests. All permuted Q2 values were lower than those of the original model at the right endpoint, and the Q2 regression intercept on the Y-axis was below zero, suggesting good predictive ability and no evidence of overfitting (Figure 5B-D).
Identification of differential metabolites: Based on the orthogonal projections to latent structures discriminant analysis results, a total of 144 differential metabolites were identified using variable importance in projection > 1 and P < 0.05 as criteria for selection (Figure 5E). These metabolites were classified into major categories, including amino acids, peptides, and analogues (28.96%); nucleosides, nucleotides, and analogues (14.21%); organic acids and derivatives (10.66%); and carbohydrates and carbohydrate conjugates (10.11%). Among them, taurine, L-carnitine, trigonelline, L-tryptophan, and guanidinosuccinic acid ranked among the top and are closely associated with energy metabolism (Figure 5F and G). Compared with the CON group, 25 metabolites were significantly upregulated in the MOD group, including calcifediol, glycoursodeoxycholic acid, and gluconic acid, while 86 metabolites were significantly downregulated, including taurine, hypotaurine, and 5-methyl-2’-deoxycytidine. Compared with the MOD group, 6 metabolites were significantly upre
Metabolic pathway analysis: By integrating enrichment analysis with topological analysis and referencing authoritative metabolite databases such as PubChem, key metabolic pathways were more accurately identified. Compared with the CON group, the MOD group exhibited significant alterations in phenylalanine/tyrosine/tryptophan biosynthesis, phenylalanine metabolism, taurine and hypotaurine metabolism, niacin and nicotinamide metabolism, and ubiquinone and other terpenoid-quinone biosynthesis (Figure 6A). These pathways may be critically involved in the pathogenesis of T2DM. Compared with the MOD group, the DFG group showed notable changes in riboflavin metabolism, pentose and glucuronate interconversions, purine metabolism, glycolysis/gluconeogenesis, and vitamin B6 metabolism (Figure 6B). In the MET group, significantly altered pathways included alpha-linolenic acid metabolism, purine metabolism, histidine metabolism, glycine/serine/threonine metabolism, and alanine/aspartate/glutamate metabolism (Figure 6C). These pathways may represent key metabolic processes underlying the therapeutic effects of the two interventions.
Receiver operating characteristic analysis: Differential metabolites from each comparison group were subjected to receiver operating characteristic analysis, and their diagnostic or therapeutic potential was assessed using the area under the curve. Between the CON and MOD groups, a total of 20 metabolites demonstrated potential diagnostic value for T2DM, including 5-methyl-2’-deoxycytidine, hydroxyphenyllactic acid, hypotaurine, calcifediol, and cholecalciferol (Figure 6D). Fourteen metabolites were identified between the MOD and DFG groups as potential targets of DGF, including 2-hydroxyadipic acid, pyridoxamine, flavin mononucleotide, uridine diphosphate glucose, and tryptamine (Figure 6E). Similarly, 20 metabolites were identified between the MOD and MET groups as potential targets of metformin, including metformin, phosphoenolpyruvate, methylsuccinic acid, 4-(trimethylammonio) butyrate, and 2-aminoisobutyric acid (Figure 6F). These metabolites may serve as potential biomarkers for disease diagnosis or therapeutic response; however, further validation in independent studies is still required.
Correlation analysis of NAMPT/NAD+/SIRT1 axis and metabolites: To further explore the relationship between the NAMPT/NAD+/SIRT1 axis and amino acid metabolism alterations, we performed correlation analysis between the expression levels of NAMPT, NAD+, and SIRT1 and the top 10 differential metabolites across all groups. The results showed that NAD+ exhibited a consistently strong positive correlation with multiple differential metabolites, whereas NAMPT and SIRT1 displayed relatively moderate but highly concordant variation trends. These findings suggest that, under DFG intervention, coordinated regulation of the NAMPT/NAD+/SIRT1 axis may be closely associated with amino acid metabolic reprogramming (Figure 7).
In the present study, we found that DGF significantly ameliorates glucolipid metabolism in T2DM rats, an effect that may be mediated by regulation of the hepatic NAMPT/NAD+/SIRT1 axis and amino acid metabolism disorders. Amino acid metabolism serves as a central pathway for energy supply and biosynthesis in the body. The classification of amino acids into glucogenic, ketogenic, and mixed types enables a diverse range of physiological functions[14]. Under increased energy demand, glucogenic amino acids undergo deamination or transamination, producing intermediates such as pyruvate, α-ketoglutarate, and oxaloacetate. These intermediates enter gluconeogenesis to maintain glucose homeostasis[15]. In contrast, ketogenic amino acids are metabolized to acetyl-CoA or ketone bodies, which can either enter the tricarboxylic acid (TCA) cycle for energy production or act as substrates for lipid biosynthesis[16]. The liver, as the primary metabolic organ, plays a pivotal role in amino acid metabolism. It houses abundant transaminases and urea cycle enzymes that convert ammonia, a byproduct of deamination, into urea to prevent hyperammonaemia[14]. Furthermore, the liver dynamically integrates glucogenic amino acid metabolism with overall energy metabolism by regulating key gluconeogenic enzymes, and preferentially catabolizes branched-chain amino acids (BCAAs) during fasting or stress to meet energy demands[17]. Amino acid metabolism is fundamental not only to life processes but also to maintaining glucolipid metabolism, nitrogen balance, and cellular homeostasis. Dysregulation of this metabolism is a key pathological factor in metabolic disorders such as diabetes, obesity, and metabolic syndrome[1,2].
Disrupted amino acid metabolism is a hallmark of T2DM and serves as an important prognostic indicator[2]. Compared with healthy individuals, patients with T2DM exhibit significantly decreased plasma levels of arginine, phosphoethanolamine, glutamine and γ-aminobutyric acid, together with increased urinary excretion of tryptophan, cysteine, phenylalanine, tyrosine and arginine[18]. Among individuals with impaired glucose tolerance, decreases in plasma γ-aminobutyric acid and increases in tyrosine correlate positively with fasting and post-load blood glucose, fasting C-peptide, homeostasis model assessment of insulin resistance index, and fasting glucagon levels[19]. Recent evidence links elevated levels of BCAAs and aromatic amino acids with an increased risk of developing T2DM[20]. BCAAs may worsen IR through activation of the mechanistic target of rapamycin signalling pathway, impairing insulin signalling, promoting fatty acid accumulation, oxidative stress, inflammatory responses, and producing toxic intermediates such as isovaleryl-CoA and methylmalonyl-CoA[21]. Similarly, dysregulated aromatic amino acids metabolism can induce inflammatory cytokine release, reduce insulin sensitivity, and exacerbate metabolic and inflammatory disturbances[20].
In our study, taurine, L-carnitine, trigonelline, L-tryptophan, and guanidinosuccinic acid were identified as key differential metabolites, all closely related to energy metabolism. Taurine and L-carnitine directly participate in lipid catabolism and energy production, thereby reducing lipid accumulation[22]. Trigonelline, a niacin metabolite with antidiabetic properties, regulates glucose metabolism and influences skeletal health[23]. L-tryptophan functions beyond protein synthesis as a precursor for serotonin and nicotinamide[24]. Guanidinosuccinic acid impairs mitochondrial function, decreases adenosine triphosphate production, and disrupts ammonia detoxification and gluconeogenesis[25]. Additionally, receiver operating characteristic analysis revealed that 2-hydroxyadipic acid, pyridoxamine, flavin mononucleotide, uridine diphosphate glucose, and tryptamine could be potential targets of DGF. 2-Hydroxyadipic acid, involved in fatty acid oxidation and amino acid metabolism, is an intermediate in mitochondrial energy metabolism[26]. Pyridoxamine, a coenzyme in amino acid metabolism, helps maintain homocysteine homeostasis[27]. Flavin mononucleotide drives mitochondrial energy production and participates in fatty acid oxidation and degradation[28]. Uridine diphosphate glucose regulates hepatic glycogen storage, maintaining glucose homeostasis[29]. Tryptamine, a precursor of serotonin and melatonin, modulates energy expenditure and lipolysis via the trace amine-associated receptor signalling pathway[30].
Quantitative analysis of differential metabolites alone is insufficient to fully reveal global changes in the metabolic network. Key pathway analysis showed that DGF intervention induced significant modulation in riboflavin metabolism, pentose and glucuronic acid interconversions, purine metabolism, glycolysis and gluconeogenesis, and vitamin B6 metabolism. Riboflavin, converted into flavin mononucleotide and flavin adenine dinucleotide, participates in redox reactions and regulates mitochondrial energy metabolism, fatty acid oxidation, and antioxidant processes[31]. Pentose and glucuronic acid interconversions contribute to lipid synthesis and detoxification via reduced NAD+ phosphate generation and support glycosaminoglycan biosynthesis[32]. Purine metabolism is involved in adenosine triphosphate regulation and the dual roles of uric acid in antioxidant defence and inflammation modulation[33]. Glycolysis and gluconeogenesis synergistically regulate energy and glucose-lipid metabolism by balancing glucose degradation and synthesis[34]. Vitamin B6, in its active form pyridoxal phosphate, functions as a coenzyme in glycogenolysis and amino acid metabolism, facilitating energy production and gluconeogenesis[35].
The NAMPT/NAD+/SIRT1 axis represents a critical pathway for cellular energy sensing and systemic metabolic adaptation[7]. NAMPT is the rate-limiting enzyme in the salvage pathway of intracellular NAD+ biosynthesis, responsible for converting nicotinamide to nicotinamide mononucleotide, thereby sustaining cellular NAD+ levels[8]. NAD+ is essential not only for redox reactions but also as a substrate for the deacetylase activity of SIRT1[36]. SIRT1 promotes mitochondrial biogenesis, fatty acid oxidation, and glucose homeostasis by deacetylating various metabolic regulators, thus enhancing oxidative metabolism[9]. Under metabolic stress, NAMPT, NAD+, and SIRT1 form a regulatory cascade. Upregulation of NAMPT increases NAD+ levels, activates SIRT1, and improves energy-deficit adaptation, thereby enhancing insulin sensitivity and antioxidant defences[7]. Our findings show that hepatic mRNA and protein expression of NAMPT and SIRT1, along with NAD+ content, are significantly decreased in T2DM rats but are effectively restored by DGF treatment, suggesting that DGF ameliorates energy metabolism disorders via this axis.
Moreover, the NAMPT/NAD+/SIRT1 axis coordinates hepatic amino acid metabolism on multiple levels[37]. Through a regulatory cascade dependent on the deacetylase activity of SIRT1, the axis enhances BCAAs oxidation, promoting their conversion into TCA cycle intermediates for energy production[7]. It also modulates transcription factors regulating lysosomal function and mitochondrial metabolism, indirectly enhancing amino acid utilization, such as glutamine[38]. Studies indicate that obesity and chronic inflammation upregulate the hepatic miR-34a, which inhibits NAMPT and SIRT1 translation, reduces NAD+ content, suppresses SIRT1/SIRT5 activity, and impairs amino acid catabolism and the urea cycle, causing hyperammonaemia; Conversely, inhibiting miR-34a restores the function of the NAMPT/SIRT1 axis, increases hepatic NAD+, and improves amino acid metabolism disorders[39]. Previous work showed that DGF regulates the miR-34a/NAMPT axis, increases hepatic NAD+ content, enhances TCA cycle function, and elevates metabolites such as citrate, isocitrate, α-ketoglutarate, glutamine, and arginine in T2DM rats[10-12]. Our current results align with these findings, demonstrating that DGF enhances the NAMPT/NAD+/SIRT1 axis expression, improves hepatic amino acid metabolism, and facilitates glucolipid metabolism in T2DM rats.
In conclusion, DGF significantly improves glucolipid metabolism in T2DM rats. Its mechanism may involve modulation of the hepatic NAMPT/NAD+/SIRT1 axis and amelioration of amino acid metabolism disorders. Although correlation analysis revealed significant associations between the NAMPT/NAD+/SIRT1 axis and differential amino acid metabolites, these findings do not establish a direct causal or regulatory relationship, and therefore should be interpreted cautiously. Nevertheless, the observed associations provide supportive evidence for the potential involvement of the NAMPT/NAD+/SIRT1 axis in metabolic remodeling under DGF intervention. This mechanism corresponds well with the TCM theory of “regulating the pivotal qi mechanism to resolve turbidity”, reflecting the multi-target and systemic regulatory characteristics of TCM. This study not only reveals a potential mechanism by which DGF improves amino acid metabolism, but also provides new theoretical support and research directions for the TCM-based treatment of T2DM. Further mechanistic studies and functional validation experiments are needed to clarify the precise relationship between the NAMPT/NAD+/SIRT1 axis and amino acid metabolism and to promote the clinical translation and application of DGF in diabetes prevention and treatment.
DGF effectively improves glucolipid metabolic disorders in T2DM rats. These beneficial effects may be associated with the regulation of the hepatic NAMPT/NAD+/SIRT1 axis and the correction of amino acid metabolism disturbances, suggesting a potential multi-target therapeutic mechanism in diabetes treatment.
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