Abstract Osthol (OST), a natural coumarin, exhibits anti-inflammatory and metabolism-regulating potential. This study investigated whether OST ameliorates obesity-associated metabolic dysregulation and inflammation by targeting ADRA1D-mediated T helper 17 (Th17) differentiation. High-fat diet (HFD)-induced obese mice were treated with OST. Metabolic parameters including body/organ weights, serum lipids, hepatic enzymes, and histopathology were assessed. Th17-related and inflammatory markers were evaluated via flow cytometry, ELISA, RT-qPCR, and Western blot. In vitro Th17 differentiation (primary murine CD4⁺ T cells) and lipid metabolism (3T3-L1 adipocytes) models were used. ADRA1D was identified as a key target via bioinformatics and validated through overexpression in cells and mice. OST significantly reduced HFD-induced weight gain, liver and fat mass, serum triglycerides (TG), free fatty acids (FFA), alanine aminotransferase (ALT), aspartate aminotransferase (AST), hepatic lipid deposition, and adipocyte hypertrophy. OST suppressed Th17 differentiation, CD4⁺IL-17A⁺ and CD4⁺RORγt⁺ cell proportions, and pro-inflammatory cytokines (IL-17A, IL-6, TNF-α), while elevating anti-inflammatory cytokines (IL-10, TGF-β). OST downregulated IL-17RA, TRAF6, and Act1 expression and inhibited ERK1/2 and PI3K phosphorylation. In vitro studies confirmed the dose-dependent inhibitory effect of OST on Th17 polarization. Mechanistically, OST modulated Th17-related signaling via ADRA1D. ADRA1D overexpression partially reversed OST-mediated suppression of Th17 differentiation, expression of lipogenic genes (FASN, PPARγ), and lipid droplet accumulation. In vivo, ADRA1D overexpression attenuated the beneficial effects of OST on metabolic parameters and tissue inflammation, confirming ADRA1D dependence. OST ameliorates obesity-related metabolic dysregulation and inflammation by inhibiting ADRA1D-mediated Th17 differentiation, highlighting ADRA1D as a key mediator and potential therapeutic target for immunometabolic disorders. Keywords: Osthol, Obesity, Lipid metabolism, Th17 cell differentiation, ADRA1D Subject terms: Biochemistry, Cell biology, Diseases, Drug discovery, Immunology, Medical research Introduction Obesity represents a critical public health challenge of the twenty-first century, constituting a worldwide epidemic that significantly compromises quality of life and contributes to numerous metabolic complications^[34]1. Core pathophysiological features encompass white adipose tissue (WAT) expansion, dysregulated lipid metabolism manifesting as hypertriglyceridemia and elevated free fatty acids (FFAs), and systemic chronic low-grade inflammation^[35]2,[36]3. These alterations collectively contribute to the development of insulin resistance (IR), non-alcoholic fatty liver disease, and atherosclerosis^[37]4. High-fat diet (HFD)-induced metabolic stress disrupts adipocyte homeostasis, precipitating excessive lipid droplet accumulation and increased secretion of pro-inflammatory cytokines such as interleukin (IL)-6 and tumor necrosis factor-α (TNF-α), thereby establishing a vicious cycle of metabolic and inflammatory dysregulation^[38]5,[39]6. Although lifestyle modifications and pharmacotherapy offer some benefits, the intricate pathogenesis continues to impede the development of effective targeted therapies^[40]7. Given the central role of chronic inflammation in obesity-associated metabolic disorders, elucidating the underlying immunoregulatory mechanisms, particularly the involvement of key immune cell subsets such as T helper 17 (Th17) cells, is critical for identifying novel therapeutic targets. Obesity-associated chronic inflammation is characterized by CD4⁺ T cell-mediated immune dysregulation, with hyperactivation of Th17 cells serving as a critical nexus linking immunity and metabolism^[41]8,[42]9. Th17 cells exacerbate IR and hepatic steatosis by secreting cytokines like IL-17A and IL-22, which promote macrophage infiltration in adipose tissue and liver and activate pro-inflammatory signaling pathways^[43]10,[44]11. In HFD-induced murine obesity models, specific genetic ablation of Th17 cells significantly ameliorates adipose inflammation and improves glucose tolerance^[45]12. Conversely, adoptive transfer of Th17 cells aggravates metabolic dysfunction, indicating that their dysregulated differentiation constitutes a key pathogenic driver of obesity progression^[46]13. Nevertheless, the upstream regulatory mechanisms governing Th17 cell differentiation, particularly the involvement of adrenergic receptors, remain incompletely defined. Targeting this Th17 cell differentiation imbalance presents a promising therapeutic approach, especially through identifying safe and effective natural compounds that modulate upstream signaling pathways such as the adrenergic receptor family^[47]14. Osthol (OST), a coumarin derivative isolated from the traditional medicinal herb Cnidium monnieri, exhibits multi-target regulatory properties^[48]15. Preliminary research demonstrates that OST blocks the AMP-activated protein kinase pathway to enhance mitochondrial oxidative metabolism in adipocytes, suppresses preadipocyte proliferation, and significantly reduces body weight and serum lipid levels in oleic acid-induced hepatic steatosis^[49]16. Furthermore, OST exerts anti-inflammatory effects by inhibiting macrophage M1 polarization and nuclear factor-κB (NF-κB) signaling^[50]17,[51]18. However, whether OST improves metabolic outcomes via modulating T cell immune responses, specifically Th17 cell differentiation, and its precise molecular targets remain unexplored. Given its natural origin and favorable safety profile, deciphering OST’s mechanism of action is crucial for developing safe therapeutics for metabolic diseases. Among potential upstream regulators of Th17 differentiation, adrenergic receptor alpha-1D (ADRA1D) is of interest due to its emerging role in metabolic regulation and its characterization as a G protein-coupled receptor, a common target class for natural compounds^[52]19–[53]22. While extensively studied in cardiovascular contexts^[54]23,[55]24, ADRA1D’s function in metabolic diseases and immune cell differentiation remains incompletely characterized. Based on our hypotheses that Th17 cell hyperactivation drives obesity-associated inflammation and that ADRA1D may mediate OST’s effects, this study aims to investigate whether OST ameliorates lipid metabolic disorders and systemic inflammation by inhibiting ADRA1D-dependent Th17 cell differentiation. Our findings will provide novel mechanistic insights into OST’s activity and validate ADRA1D as a therapeutic target in metabolic diseases. Methods 3T3-L1 adipocyte differentiation and treatment 3T3-L1 preadipocytes (400,107, Cytion, Eppelheim, Germany) were cultured in Dulbecco’s modified Eagle medium (DMEM; 11,885,084, Thermo Fisher Scientific, Waltham, MA, USA) supplemented with 10% fetal bovine serum (FBS; A5670401, Thermo Fisher Scientific) at 37 °C until reaching 100% confluence. Differentiation was induced using induction medium containing 0.5 mM 3-isobutyl-1-methylxanthine (IBMX; HY-12318, MedChemExpress, Monmouth Junction, NJ, USA), 1 µM dexamethasone (HY-14648, MedChemExpress), and 10 µg/mL insulin. On day 2, the medium was replaced with maintenance medium containing only 10 µg/mL insulin (92209ES10, Yeasen, China), and cells were maintained in this medium until day 8 to allow adipocyte maturation^[56]25. The maintenance medium was refreshed every 2 days during this culture period. Following the completion of the differentiation protocol and any experimental treatments, cells were harvested for subsequent oil red O staining to visualize lipid droplet accumulation, quantification of TG content, and analysis of relevant gene and protein expression. Animal subjects Forty-two six-week-old male C57BL/6 J mice, weighing 20 ± 2 g, were purchased from Beijing Vital River Laboratory Animal Technology Co., Ltd. All mice were housed under strictly controlled environmental conditions: a constant temperature of 22 ± 2 °C, relative humidity of 50 ± 5%, and a standardized 12-h light/dark cycle. Throughout the study period, the mice had ad libitum access to food and potable water. Following a one-week acclimatization period within the facility, the experimental procedures commenced. This animal study received prior approval from the Animal Ethics Committee of Hunan Evidence-based Biotechnology Co., Ltd. (No. XZ20250711). Animal grouping and modeling The 42 mice were randomly assigned to 7 experimental groups: Control (10% kcal fat, D06061303, Research Diets, New Brunswick, NJ, USA), HFD (60% kcal fat, D12492, Research Diets), OST-L (25 mg/kg, HY-N0054, MedChemExpress), OST-M (50 mg/kg), OST-H (100 mg/kg), OST + oe-NC, and OST + oe-ADRA1D. OST dosage was selected based on previous pharmacological research^[57]26 and our preliminary dose-ranging experiments. Randomization was performed using a computer-based random number generator to ensure equal distribution of baseline characteristics across groups. All mice received daily oral gavage administration of OST or an equivalent volume of physiological saline for eight consecutive weeks. To induce ADRA1D overexpression, mice were injected via the tail vein with adeno-associated virus (AAV, VectorBuilder) carrying the overexpression negative control construct (oe-NC) or the ADRA1D overexpression construct (oe-ADRA1D). Body weight was monitored weekly throughout the study period. At the end of week 8, mice were euthanized by intraperitoneal injection of an overdose of sodium pentobarbital (200 mg/kg, P3761, Sigma-Aldrich, St. Louis, MO, USA). Intraperitoneal adipose tissues and livers were subsequently harvested, rinsed gently with phosphate-buffered saline (PBS), blotted dry to remove surface moisture, and weighed using a precision electronic balance. All histological analyses were performed by investigators blinded to the experimental group assignments to minimize assessment bias. Enzyme-linked immunosorbent assay (ELISA) Blood samples were collected from mice via retro-orbital bleeding. Serum was isolated by centrifuging the blood at 3,000 rpm for 10 min. Multiple biochemical parameters in serum or cells were quantified using commercially available ELISA kits strictly according to the manufacturers’ protocols. These parameters included serum lipid profiles: triglycerides (TG, EEA028, Thermo Fisher Scientific), total cholesterol (TC, EEA026, Thermo Fisher Scientific), and FFA (MBS733261, MyBioSource, San Diego, CA, USA); markers of hepatic function: alanine aminotransferase (ALT, ab285263, Abcam, Cambridge, MA, USA) and aspartate aminotransferase (AST, ab263882, Abcam); as well as key inflammatory cytokines: IL-6 (88–7064-88, Invitrogen, Waltham, MA, USA), IL-1β (ab197742, Abcam), TNF-α (BMS607-3, Invitrogen), and IL-17A (ab199081, Abcam). Hematoxylin and eosin (HE) staining Processed adipose tissue samples were fixed in 4% paraformaldehyde (158,127, Sigma-Aldrich) for 24 h. Tissues were then dehydrated, cleared, paraffin-embedded, and sectioned. Sections were deparaffinized in xylene (534,056, Sigma-Aldrich; 5 min), rehydrated through ethanol (E7023, Sigma-Aldrich), and stained with hematoxylin (HHS16, Sigma-Aldrich; 5 min). Differentiation used 1% acid-alcohol, followed by blueing in 0.2% ammonia water (1 min). Counterstaining employed eosin (HT110132, Sigma-Aldrich; 1 min). Sections were subsequently dehydrated in ethanol, cleared, and permanently mounted with Organo/Limonene Mount™ medium (O8015, Sigma-Aldrich). Stained sections were examined and photographed using a Nikon Eclipse E200 microscope (Nikon, Tokyo, Japan). Hepatic oil red O staining Freshly harvested liver tissues were immediately embedded in optimal cutting temperature (OCT) compound and cryopreserved at -80 °C. Tissue Sects. (10 μm) were prepared using a cryostat, mounted onto pre-chilled glass slides, and air-dried at room temperature for 10 min prior to staining. The oil red O working solution was prepared by dissolving 0.5% oil red O (HY-D1168, MedChemExpress) in isopropanol, followed by thorough mixing at room temperature under light-protected conditions and filtration. Prior to staining, sections were immersed in 60% isopropanol for 1 min and subsequently incubated in oil red O working solution for 10 min. After staining, sections were rapidly rinsed in 60% isopropanol to remove non-specific background staining, followed by two washes with PBS. Cell nuclei were then counterstained with hematoxylin (HHS16, Sigma-Aldrich) and subjected to a bluing treatment. Following washing, sections were coverslipped. Stained sections were examined under a Nikon Eclipse E200 microscope (Nikon) to evaluate the deposition of neutral lipids (lipid droplets) within the hepatic tissue. Acquired images were quantitatively analyzed using ImageJ software to determine the percentage of lipid droplet area relative to the total field area, reflecting the extent of lipid accumulation. Flow cytometric analysis Single-cell suspensions were prepared from murine spleens. Following red blood cell lysis, cells were stimulated in RPMI-1640 complete medium (PM00032, Proteintech, Wuhan, China) supplemented with phorbol 12-myristate 13-acetate (PMA; 50 ng/mL, 524,400, Sigma-Aldrich), ionomycin (500 ng/mL, I0634, Sigma-Aldrich), and brefeldin A (B5936, Sigma-Aldrich) for 4 h at 37 °C. Post-incubation, cells were stained with fixable viability dye ([58]L34989, Thermo Fisher Scientific) to discriminate viable cells. Surface marker staining was subsequently performed using a fluorescein isothiocyanate (FITC)-conjugated anti-CD4 antibody (100,405, BioLegend, California, USA). Cells were then fixed and permeabilized, followed by intracellular staining with a phycoerythrin (PE)-conjugated anti-IL-17A antibody (F21IL1702, Lianke Biotech, Hangzhou, China). Finally, stained cells were acquired using a flow cytometer. Data analysis was conducted using FlowJo software to determine the proportion of CD4⁺IL-17A⁺ (Th17) cells. Immunohistochemistry Mouse liver sections underwent antigen retrieval in sodium citrate buffer (C9999, Sigma-Aldrich). Sections were blocked for 30–60 min at room temperature with 5% bovine serum albumin (BSA; A9647, Sigma-Aldrich), followed by overnight incubation at 4 °C with anti-IL-17A primary antibody (1:100, HY-[59]P81114, MedChemExpress). Sections were then incubated for 30 min at room temperature with horseradish peroxidase (HRP)-conjugated secondary antibody (1:1,000, 31,470, Thermo Fisher Scientific). Color development used 3,3’-diaminobenzidine (DAB; (SK-4100, Vector Laboratories, Burlingame, CA, USA). Sections were counterstained with hematoxylin, dehydrated, and mounted in neutral balsam. Stained sections were examined microscopically, and protein expression levels were semi-quantitatively analyzed using ImageJ software. Immunofluorescence staining Fresh liver sections were washed with PBS, permeabilized in 0.3% Triton X-100, and blocked with 5% BSA. Sections were then incubated overnight at 4 °C with primary antibodies: rabbit anti-retinoic acid receptor-related orphan receptor gamma t (RORγt; 1 µg/mL) and mouse anti-CD4 (1 µg/mL). Following primary incubation, sections were exposed to species-specific fluorescently labeled secondary antibodies at room temperature under light-protected conditions for 2 h: goat anti-rabbit IgG H&L (Alexa Fluor® 488, 1:200, ab150077, Abcam) and goat anti-mouse IgG (Alexa Fluor® 647, 1:200, ab150115, Abcam). Nuclei were counterstained with 4’,6-diamidino-2-phenylindole (DAPI)-containing Fluoroshield aqueous mounting medium Fluoroshield (ab04139, Abcam). Stained sections were visualized and images acquired using a fluorescence microscope. Image analysis was performed with ImageJ software to identify and count CD4^+, RORγt^+, and CD4^+RORγt^+ double-positive cells. The proportion of double-positive cells, reflecting the relative abundance of Th17 cells, was calculated relative to DAPI⁺ total cells. Reverse transcription-quantitative polymerase chain reaction (RT-qPCR) Total RNA was extracted from tissues/cells using TRI reagent (T9424, Merck) per manufacturer’s protocol. RNA concentration and purity were quantified using a NanoDrop 2000 spectrophotometer (Thermo Fisher Scientific). The extracted RNA was then reverse transcribed into complementary DNA (cDNA) using the SuperScript IV First-Strand Synthesis System (18,091,050, Thermo Fisher Scientific) as per the kit instructions. RT-qPCR was performed with SYBR Green Master Mix (HY-K0501, MedChemExpress) using GAPDH as the endogenous reference. Relative gene expression was calculated by the 2^−ΔΔCt method^[60]27. Primer sequences used are listed in Table [61]1. Table 1. The primer sequences for RT-qPCR. Gene Primer sequences (5’-3’) IL-17A Forward CAGACTACCTCAACCGTTCCAC Reverse TCCAGCTTTCCCTCCGCATTGA RORγt Forward GTGGAGTTTGCCAAGCGGCTTT Reverse CCTGCACATTCTGACTAGGACG ADRA1D Forward GTGTCTTCGTCCTGTGCTGGTT Reverse GCCAGAAGATGACCTTGAAGACG FASN Forward CACAGTGCTCAAAGGACATGCC Reverse CACCAGGTGTAGTGCCTTCCTC PPARγ Forward GTACTGTCGGTTTCAGAAGTGCC Reverse ATCTCCGCCAACAGCTTCTCCT GAPDH Forward CATCACTGCCACCCAGAAGACTG Reverse ATGCCAGTGAGCTTCCCGTTCAG [62]Open in a new tab Western blot (WB) analysis Cells or splenic tissue cells were lysed in RIPA buffer (R0278, Merck) on ice for 30 min with intermittent vortexing every 5 min. The lysates were centrifuged at 12,000 rpm for 10 min at 4 °C, and the supernatants were collected. Protein concentration for each sample was determined using a bicinchoninic acid (BCA) protein assay kit (23,227, Thermo Fisher Scientific). Following separation by sodium dodecyl sulfate–polyacrylamide gel electrophoresis (SDS-PAGE), proteins were transferred onto polyvinylidene fluoride (PVDF) membranes (88,518, Thermo Fisher Scientific). Membranes were blocked for 1 h with 5% non-fat dry milk. Subsequently, the blocked membranes were immunoblotted overnight at 4 °C with primary antibodies specific for IL-17A (1:1,000, HY-[63]P81114, MedChemExpress), RORγt (1:1,000, YB-23110R, Bioon Technology, Shanghai, China), IL-17RA (1:1,000, A5163, ABclonal Technology, Düsseldorf, Germany), TRAF6 (1:1,000, A23385, ABclonal Technology), Act1 (1:1,000, ABclonal Technology), ERK1/2 (1:4,000, A4782, ABclonal Technology), P-ERK1/2 (1:1,000, AP0485, ABclonal Technology), PI3K (1:5,000, A27717, ABclonal Technology), p-PI3K (1:1,000, Cell Signaling Technology, Massachusetts, USA), ADRA1D (1:1,000, ABIN790781, Antibodies-online, Pennsylvania, USA), fatty acid synthase (FASN; 1:1,000, HY-[64]P80668, MedChemExpress), and PPARγ (1:1,000, 95,128, Cell Signaling Technology). After primary antibody incubation, membranes were probed with an HRP-conjugated goat anti-rabbit IgG secondary antibody (1:10,000, 31,460, Invitrogen) diluted in 5% non-fat dry milk for 1 h at room temperature. Protein bands were finally visualized using enhanced chemiluminescence (ECL) substrate (32,106, Thermo Fisher Scientific). The relative optical density of protein bands was analyzed using ImageJ software, normalized to β-actin as a loading control. Isolation of murine primary CD4^+ T cells and Th17 polarization Single-cell suspensions prepared from murine spleens were subjected to CD4^+ T cell isolation using the EasySep™ mouse CD4^+ T cell isolation kit (19,852, STEMCELL Technologies, Shanghai, China) strictly following the manufacturer’s protocol. Purified CD4^+ T cells were then cultured in RPMI-1640 complete medium and polarized towards the Th17 lineage under specific cytokine conditions: 20 ng/mL recombinant IL-6 (216–16-10UG, Thermo Fisher Scientific) and 2 ng/mL transforming growth factor-β (TGF-β; HY-[65]P70648, MedChemExpress). Cells were incubated under these polarizing conditions for 72 h. Prior to the initiation of polarization, cells were pre-treated with varying concentrations of OST (25, 50, and 100 μM) (Table [66]2). Table 2. Abbreviations. Abbreviation Full name OST Osthol HFD High-fat diet WAT White adipose tissue TG Triglycerides TC Total cholesterol FFA Free fatty acids ALT Alanine aminotransferase AST Aspartate aminotransferase Th17 T helper 17 IL Interleukin TNF-α Tumor necrosis factor-alpha TGF-β Transforming growth factor-beta RORγt Retinoic acid receptor-related orphan receptor gamma t IL-17RA Interleukin-17 receptor A TRAF6 TNF receptor-associated factor 6 Act1 NF-κB activator 1 (also known as CIKS) ADRA1D Alpha-1D adrenergic receptor PPARγ Peroxisome proliferator-activated receptor gamma FASN Fatty acid synthase ERK1/2 Extracellular signal-regulated kinase 1/2 PI3K Phosphoinositide 3-kinase [67]Open in a new tab Statistical analysis Statistical analyses were performed using Prism 9 software (GraphPad Software, USA). Data are presented as mean ± standard deviation (SD). Comparisons between two groups were analyzed using unpaired t-tests. For comparisons among three or more groups, one-way or two-way analysis of variance (ANOVA) was applied as appropriate, followed by Tukey’s post hoc test for multiple comparisons. Statistical significance was defined as P < 0.05. Results OST ameliorates HFD-induced adipose metabolic dysregulation and hepatic lipid deposition in mice To evaluate the therapeutic potential of OST against obesity-associated metabolic disorders, we employed a HFD-induced murine obesity model treated with varying doses of OST. Results demonstrated that OST dose-dependently suppressed body weight gain (Fig. [68]1A) and significantly reduced the weights of both the liver and WAT (Fig. [69]1B,C), suggesting an amelioration of hepatic steatosis. Serum biochemical analysis revealed markedly elevated levels of TG, TC, and FFA in the HFD group, which were significantly attenuated by OST treatment, with the most pronounced reductions observed in the high-dose group (Fig. [70]1D). Concurrently, OST administration dose-dependently decreased serum levels of ALT and AST, indicating hepatoprotective properties (Fig. [71]1E). Histological examination showed that HFD feeding induced substantial adipocyte hypertrophy and disorganized arrangement, whereas OST treatment resulted in reduced adipocyte size, more regular cellular organization, and overall improved morphology (Fig. [72]1F). Oil red O staining of liver sections further confirmed that OST dose-dependently diminished intrahepatic lipid accumulation (Fig. [73]1G). Collectively, these findings indicate that OST effectively ameliorates HFD-induced dysregulation of lipid metabolism and hepatic lipid deposition in mice. Fig. 1. [74]Fig. 1 [75]Open in a new tab OST Ameliorates HFD-Induced Adipose Metabolic Dysregulation and Hepatic Lipid Deposition in Mice. (A) Body weight changes in HFD-fed mice treated with different doses of OST. (B, C) Liver and white adipose tissue (WAT) weights were measured to assess adiposity. (D) Serum levels of triglycerides (TG), total cholesterol (TC), and free fatty acids (FFA) were evaluated. (E) Serum alanine aminotransferase (ALT) and aspartate aminotransferase (AST) levels were measured to assess liver injury. (F) H&E staining of WAT sections was performed to examine adipocyte morphology. (G) Oil red O staining of liver sections was conducted to assess hepatic lipid accumulation. n = 6. ***P < 0.001, ****P < 0.0001. For three or more groups, one-way or two-way analysis of variance (ANOVA) was applied, followed by Tukey’s post hoc test. OST attenuates systemic inflammation and downregulates Th17-related factor expression To further investigate the potential mechanism by which OST modulates obesity-associated inflammation, downstream targets of OST were predicted using SwissTargetPrediction ([76]https://www.molecular-modelling.ch/swiss-drug-design.html). KEGG pathway enrichment analysis of these putative target genes was then performed via Bioinformatics.com.cn ([77]https://www.bioinformatics.com.cn/) to identify significantly involved signaling pathways and biological processes^[78]28–[79]30. Analysis utilizing this platform revealed significant enrichment of associated genes in the Th17 cell differentiation pathway (hsa04659), suggesting OST may exert its effects through the regulation of this pathway (Fig. [80]2A). To explore OST’s regulatory impact on obesity-related inflammatory responses and Th17 cell differentiation, multiple inflammatory markers were assessed in HFD-fed mice. Flow cytometry results demonstrated a significant increase in the proportion of CD4^+IL-17A^+ cells within the spleen of the HFD group, which was dose-dependently reduced by OST treatment (Fig. [81]2B). Immunohistochemical staining further verified that HFD-induced enhancement of IL-17A expression in liver tissue was markedly attenuated by OST intervention (Fig. [82]2C). Immunofluorescence co-staining indicated a significant elevation in CD4^+RORγt^+ double-positive cells in the HFD group, a finding significantly reversed following OST administration, suggesting suppression of Th17 cell differentiation (Fig. [83]2D). Serum inflammatory cytokine quantification revealed markedly elevated levels of IL-6, IL-1β, TNF-α, and IL-17A in the HFD group. OST intervention resulted in a dose-dependent reduction in the concentrations of all these factors (Fig. [84]2E). Collectively, these findings indicate that OST alleviates HFD-induced systemic inflammation by reducing Th17 cell differentiation and the expression of associated factors. Fig. 2. [85]Fig. 2 [86]Open in a new tab OST Attenuates Systemic Inflammation and Downregulates Th17-Related Factor Expression. (A) KEGG pathway enrichment analysis of downstream targets of OST. This figure is based on data from KEGG (Kyoto Encyclopedia of Genes and Genomes) at [87]https://www.kegg.jp/; © Kanehisa Laboratories. (B) Flow cytometry was used to evaluate the proportion of CD4⁺IL-17A⁺ cells in the spleen. (C) Immunohistochemical staining of liver tissues was performed to assess IL-17A expression. (D) Immunofluorescence staining was conducted to detect CD4⁺RORγt⁺ double-positive cells in liver sections. (E) Serum levels of IL-6, IL-1β, TNF-α, and IL-17A were measured using ELISA. n = 6. ****P < 0.0001. One-way ANOVA followed by Tukey’s post hoc test was used for multiple group comparisons. OST inhibits Th17 cell differentiation in vitro To further delineate the regulatory effect of OST on Th17 cell differentiation, an in vitro Th17-polarization model was established. Flow cytometric analysis revealed a significant increase in the proportion of CD4⁺IL-17A⁺ cells within the Th17-polarized group compared to controls, an effect that was dose-dependently suppressed by OST treatment (Fig. [88]3A). Concomitantly, RT-qPCR analysis showed that the mRNA expression levels of RORγt and IL-17A were markedly upregulated following Th17 induction. WB analyses further demonstrated increased protein expression of RORγt, IL-17A, IL-17RA, TRAF6, and Act1. OST administration significantly suppressed these changes, leading to a dose-dependent reduction in transcript levels of RORγt and IL-17A as well as in protein levels of all detected molecules (Fig. [89]3B,C). Furthermore, ELISA quantification showed that Th17 polarization potently stimulated the secretion of IL-6, IL-1β, and TNF-α, while concomitantly reducing the levels of IL-10 and TGF-β. OST treatment dose-dependently suppressed the production of pro-inflammatory cytokines (IL-6, IL-1β, and TNF-α) and restored the secretion of IL-10 and TGF-β across all concentrations tested (Fig. [90]3D). Collectively, these in vitro findings demonstrate that OST exerts potent anti-inflammatory and immunomodulatory effects by inhibiting Th17 cell differentiation and the expression of associated inflammatory cytokines. Fig. 3. [91]Fig. 3 [92]Open in a new tab OST Inhibits Th17 Cell Differentiation in Vitro. (A) Flow cytometry was used to assess the proportion of CD4⁺IL-17A⁺ cells in a Th17-polarized cell model treated with different doses of OST. (B) RT-qPCR was performed to evaluate mRNA expression levels of RORγt and IL-17A. (C) Western blot was performed to evaluate protein expression levels of RORγt, IL-17A, IL-17RA, TRAF6, and Act1. (D) ELISA was used to quantify the secretion of IL-6, IL-1β, TNF-α, IL-10, and TGF-β in the culture supernatants. n = 3. *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001. One-way ANOVA followed by Tukey’s post hoc test was used for multiple group comparisons. OST suppresses Th17 differentiation via an ADRA1D-dependent mechanism To elucidate the mechanism underlying OST-mediated suppression of Th17 differentiation, potential targets of OST predicted by SwissTargetPrediction were intersected with genes differentially expressed in obesity (dataset [93]GSE110729), yielding 5 key candidates: BDKRB2, RGS4, ADRA1D, KCNN4, and HMOX1 (Fig. [94]4A, [95]B). Given prior evidence implicating ADRA1D in cardiac metabolic stress and lipid metabolism^[96]19, we hypothesized that OST might exert its anti-obesity effects through modulation of the ADRA1D pathway. To functionally validate whether OST inhibits Th17 cell differentiation in an ADRA1D-dependent manner, we performed ADRA1D overexpression in primary mouse CD4⁺ T cells undergoing Th17 polarization. RT-qPCR analysis demonstrated that OST treatment significantly decreased the mRNA expression levels of ADRA1D, IL-17A, and RORγt, and this suppressive effect was partially reversed by ADRA1D overexpression (Fig. [97]4C). Consistently, WB analyses revealed that OST markedly reduced the protein levels of ADRA1D, IL-17A, RORγt, IL-17RA, TRAF6, and Act1, while ADRA1D overexpression attenuated these inhibitory effects (Fig. [98]4D). Further ELISA results revealed that OST significantly attenuated the secretion of pro-inflammatory cytokines IL-6, IL-1β, and TNF-α, while simultaneously increasing the levels of anti-inflammatory cytokines IL-10 and TGF-β during Th17 polarization. Conversely, ADRA1D overexpression partially reversed these effects, restoring higher levels of IL-6, IL-1β, and TNF-α and reducing IL-10 and TGF-β secretion (Fig. [99]4E). Collectively, these data indicate that the inhibition of Th17 cell differentiation and inflammatory cytokine expression by OST is mediated through an ADRA1D-dependent mechanism. Fig. 4. [100]Fig. 4 [101]Open in a new tab OST Suppresses Th17 Differentiation via an ADRA1D-Dependent Mechanism. (A) Volcano plot of differentially expressed genes (DEGs) in the [102]GSE110729 obesity dataset. (B) Venn diagram showing the intersection between OST’s potential targets and DEGs from the [103]GSE110729 dataset. (C) RT-qPCR was performed to assess the expression of ADRA1D, IL-17A, and RORγt in Th17-polarized CD4⁺ T cells with or without ADRA1D overexpression. (D) Western blot was conducted to evaluate the protein expression of ADRA1D, IL-17A, RORγt, IL-17RA, TRAF6, and Act1. (E) ELISA was used to measure the levels of IL-6, IL-1β, TNF-α, IL-10, and TGF-β in the culture supernatants. n = 3. ***P < 0.001, ****P < 0.0001. One-way ANOVA followed by Tukey’s post hoc test was used for multiple group comparisons. OST regulates adipocyte lipid metabolism via ADRA1D To further elucidate the mechanism by which OST modulates lipid metabolism in adipocytes, we established an ADRA1D overexpression model in 3T3-L1 adipocytes and analyzed lipid accumulation and metabolic markers. Oil red O staining revealed that OST treatment significantly reduced lipid droplet accumulation. Conversely, this reduction was substantially reversed upon ADRA1D overexpression, resulting in markedly increased lipid deposition (Fig. [104]5A). Consistent with the staining pattern, TG quantification demonstrated that OST significantly decreased TG levels, an effect that was counteracted by ADRA1D overexpression, which restored TG content (Fig. [105]5B). RT-qPCR and WB analyses indicated that OST administration significantly downregulated both mRNA and protein expression of FASN, a key enzyme involved in lipid synthesis. Concurrently, OST upregulated expression of the lipid metabolism transcription factor PPARγ and significantly suppressed ADRA1D expression. Following ADRA1D overexpression, FASN expression was notably restored, while the OST-induced upregulation of PPARγ expression was attenuated (Fig. [106]5C, [107]D). In addition, WB analysis showed that OST administration significantly inhibited ERK1/2 and PI3K phosphorylation, while overexpression of ADRA1D reversed this change (Fig. [108]5E). Collectively, these findings demonstrate that OST ameliorates dysregulated lipid metabolism in adipocytes by downregulating ADRA1D expression and consequently inhibiting lipid synthesis-associated factors. This suggests that OST’s metabolic regulatory effects are mediated through an ADRA1D-dependent signaling mechanism. Fig. 5. [109]Fig. 5 [110]Open in a new tab OST Regulates Adipocyte Lipid Metabolism via ADRA1D. (A) Oil red O staining was performed to assess lipid droplet accumulation in 3T3-L1 adipocytes treated with OST. (B) Intracellular triglyceride (TG) content was quantified to evaluate lipid accumulation. (C, D) RT-qPCR and western blotting were used to measure the mRNA and protein expression levels of FASN, PPARγ, and ADRA1D. (E) Western blot was used to detect the phosphorylation levels of ERK1/2 and PI3K. n = 3. **P < 0.01, ****P < 0.0001. One-way ANOVA followed by Tukey’s post hoc test was used for multiple group comparisons. ADRA1D overexpression attenuates the metabolic and immunomodulatory effects of OST in vivo To validate whether the in vivo ameliorative effects of OST on metabolic dysregulation and inflammatory responses are dependent on the ADRA1D signaling pathway, we established an ADRA1D overexpression system within a HFD-induced murine obesity model and assessed its impact on OST intervention. Results demonstrated that OST significantly suppressed body weight gain in HFD-fed mice, an effect markedly counteracted by ADRA1D overexpression (Fig. [111]6A). Regarding organ weights, OST administration significantly reduced the mass of both adipose tissue and liver, effects that were substantially reversed upon ADRA1D overexpression (Fig. [112]6B). Serum biochemical analysis revealed that OST effectively lowered the levels of TG, TC, FFA, ALT, and AST. Conversely, these parameters were significantly restored under ADRA1D overexpression conditions (Fig. [113]6C). In terms of immunoinflammatory modulation, flow cytometric analysis indicated that OST treatment significantly decreased the proportion of CD4⁺IL-17A⁺ cells, reduced the infiltration of CD4⁺RORγt⁺ double-positive cells, and diminished IL-17A protein expression. These suppressive effects were partially reversed by ADRA1D overexpression (Fig. [114]6D-F). Protein analysis further confirmed that OST downregulated ADRA1D protein levels, while ADRA1D overexpression significantly restored its expression (Fig. [115]6G). Furthermore, OST inhibited the phosphorylation of ERK1/2 and PI3K, while ADRA1D overexpression restored their phosphorylation (Fig. [116]6H). Histological assessment demonstrated that OST intervention ameliorated adipocyte hypertrophy and disorganized arrangement (HE staining) and reduced hepatic lipid droplet deposition (oil red O staining). However, these histological improvements were significantly attenuated following ADRA1D overexpression (F[117]ig. [118]6I-J). Collectively, these findings indicate that ADRA1D overexpression substantially attenuates the beneficial effects of OST on aberrant lipid metabolism and inflammatory responses. This demonstrates that the metabolic and immunomodulatory actions of OST in vivo are mediated through an ADRA1D-dependent signaling mechanism, further establishing the pivotal regulatory role of ADRA1D in this process. Fig. 6. [119]Fig. 6 [120]Open in a new tab ADRA1D Overexpression Attenuates the Metabolic and Immunomodulatory Effects of OST in Vivo. (A) Body weight changes were monitored in HFD-fed mice treated with OST. (B) Weights of adipose tissue and liver were measured to assess the effect on organ hypertrophy. (C) Serum levels of TG, TC, FFA, ALT, and AST were evaluated by biochemical assays. (D) Flow cytometry was performed to assess the proportion of CD4⁺IL-17A⁺ cells in the spleen. (E) Immunofluorescence staining of liver tissue was used to detect CD4⁺RORγt⁺ double-positive cell infiltration. (F) Immunohistochemistry was performed to evaluate hepatic IL-17A protein expression. (G) Western blotting was conducted to assess ADRA1D protein expression in liver tissue. (H) Western blot was used to detect the phosphorylation levels of ERK1/2 and PI3K in liver tissue. (I) H&E staining of adipose tissue was used to assess adipocyte morphology. (J) Oil red O staining of liver sections was performed to evaluate hepatic lipid deposition. n = 6. **P < 0.01, ****P < 0.0001. For three or more groups, one-way or two-way analysis of variance (ANOVA) was applied, followed by Tukey’s post hoc test. P < 0.05 was considered statistically significant. Discussion The core pathophysiological paradigm of obesity-associated metabolic disorders involves a self-perpetuating cycle of lipid dysmetabolism and chronic inflammation^[121]31. Despite existing therapeutic approaches, significant limitations persist^[122]32, underscoring the urgent need to identify novel targets and intervention strategies. This study provides the first demonstration that the natural compound OST ameliorates HFD-induced metabolic dysregulation and inflammation through a novel mechanism: the suppression of ADRA1D-mediated Th17 cell differentiation. This finding not only elucidates a key aspect of OST’s polypharmacology but also validates ADRA1D as a promising therapeutic target, while establishing a foundation for translating natural compounds into therapeutics for metabolic diseases. Consistent with its proposed mechanism^[123]33, OST administration yielded significant improvements in lipid metabolism and hepatic steatosis in HFD-fed mice. Treatment resulted in dose-dependent reductions in body weight, adipose tissue mass, and liver weight, accompanied by improved serum lipid profiles (TG, FFA) and liver function markers (ALT, AST). These metabolic benefits are consistent with earlier findings that the nutraceutical compound OST slows the progression of HFD/high-sugar diet-induced metabolic syndrome and kidney damage, reducing TG concentrations, local hypoxia, and oxidative stress^[124]15. Histological analysis confirmed OST’s efficacy, revealing reduced adipocyte hypertrophy and hepatic lipid accumulation. This pattern suggests OST modulates adipocyte differentiation and lipid metabolism-related gene expression. Particularly noteworthy are the observed hepatoprotective effects, representing a novel finding. This protection is likely mediated by OST’s suppression of inflammatory cascades, thereby mitigating hepatocyte damage. This interpretation aligns with a prior study showing OST ameliorates early diabetic kidney damage through suppression of oxidative stress, inflammation, and the TGF-β1/Smads signaling pathway^[125]34. Crucially, OST’s potent anti-inflammatory effects were mechanistically linked to its regulation of Th17 cell differentiation. Consistent across both in vivo and in vitro models, OST treatment dose-dependently reduced the CD4⁺IL-17A⁺ Th17 population, downregulated key Th17-associated transcripts (RORγt, IL-17A), and diminished secretion of pro-inflammatory cytokines (IL-6, TNF-α). Moreover, OST treatment significantly enhanced the production of anti-inflammatory cytokines, including IL-10 and TGF-β, further contributing to the restoration of immune balance. These findings directly substantiate the established role of Th17 cells as pivotal drivers of obesity-associated inflammation^[126]35. Supporting this, our KEGG pathway enrichment analysis implicated direct targeting of Th17 differentiation pathways in OST’s anti-inflammatory action. And recent studies have found that regulating Th17 cell polarization can control metabolic homeostasis in obesity^[127]35. The observed in vitro suppression of Th17 polarization by OST further indicates a direct cellular mechanism for interrupting inflammatory initiation, enhancing the compound’s translational relevance. Central to this mechanism could be OST’s disruption of leptin-driven Th17 potentiation. Leptin enhances Th17 polarization via metabolic reprogramming, upregulating the glucose transporter Glut1 to accelerate glycolytic flux in developing Th17 cells. This metabolic shift fuels pro-inflammatory cytokine production (e.g., IL-17A)^[128]36. Our data suggest that OST may antagonize this axis, inhibiting leptin-mediated metabolic activation of Th17 precursors. By disrupting this energy-intensive differentiation process, OST ablates pathogenic Th17 expansion, thereby mitigating obesity-associated inflammation at its cellular origin. OST’s broader capacity to modulate T helper responses aligns with established literature^[129]37, further cementing its role as a multifaceted immunomodulatory agent. A central and novel finding of our study is the identification of ADRA1D as the critical target mediating OST’s effects on both Th17 differentiation and lipid metabolism. Overexpression of ADRA1D, both in vitro and in vivo, effectively counteracted OST’s suppression of Th17-associated markers (IL-17A, RORγt) and pro-inflammatory cytokines, while concurrently reversing OST’s inhibition of lipogenic genes (FASN, PPARγ). Mechanistically, OST inhibited the phosphorylation of key downstream ADRA1D effectors, including ERK1/2 and PI3K, thereby blocking pro-inflammatory and pro-lipogenic signaling cascades. This is in line with a previous study linking a vaccine targeting ADRA1D to metabolic syndrome in obesity, improving dyslipidemia, attenuating fat accumulation and inflammation in the epididymal WAT, and alleviating hepatic steatosis^[130]38. We propose that OST exerts its dual modulatory action by inhibiting ADRA1D activity and its downstream signaling, contributing to both immunomodulation and metabolic regulation. Furthermore, the druggability of ADRA1D, as a GPCR, significantly enhances its appeal as a therapeutic target. The in vivo ADRA1D overexpression model provided compelling validation of this target’s centrality. ADRA1D overexpression markedly attenuated OST’s beneficial effects on body weight, serum lipids, liver function, and systemic inflammation. Moreover, it abolished OST’s protective effects on adipose tissue morphology and hepatic lipid deposition observed histologically. These findings robustly demonstrate that OST’s in vivo metabolic and immunomodulatory efficacy is critically dependent on ADRA1D signaling and its downstream ERK1/2 and PI3K pathways. Integrating our in vitro and in vivo data, ADRA1D emerges as a convergent signaling hub through which OST orchestrates its intervention in Th17-mediated inflammation and lipid dysregulation during obesity. While this study establishes a significant mechanistic link, certain limitations need consideration. Firstly, our findings are derived exclusively from murine models and cell lines, lacking validation in human primary cells or clinical samples, which limits the translational relevance of our conclusions. Secondly, although we identified several potential OST targets through bioinformatics analysis, we focused specifically on ADRA1D validation and did not perform pathway enrichment analysis for all differentially expressed genes in the obesity-related RNA sequencing data. Thirdly, the absence of pharmacokinetic and safety profiles for OST in relevant models weakens the assessment of its therapeutic potential. Future investigations employing ADRA1D knockout models, comprehensive preclinical pharmacokinetic/pharmacodynamic studies, validation in human-based systems, and exploration of combination therapies will provide deeper insights to support OST’s clinical translation. In conclusion, this study systematically delineates a novel mechanism by which OST ameliorates obesity-associated metabolic inflammation and lipid dysregulation: specific inhibition of ADRA1D-mediated Th17 cell differentiation (Figure [131]S1). This discovery significantly advances our understanding of ADRA1D’s previously unrecognized role at the immunometabolic interface and provides a robust experimental foundation for developing OST-based therapeutics. Future research focused on precisely modulating the ADRA1D signaling axis will be instrumental in optimizing OST-derived strategies to combat obesity and its debilitating comorbidities. Supplementary Information [132]Supplementary Information 1.^ (126KB, docx) [133]Supplementary Information 2.^ (173.6KB, pdf) [134]Supplementary Information 3.^ (2MB, pdf) Author contributions Pei Li, Chao He and Chao Wu conceived and designed the study. Xinbo Zhou collected and analyzed the data. Yiran Ma and Qi Deng wrote the paper. All authors have read and approved the final version. Data availability The data that support the findings of this study are available from the corresponding author upon reasonable request. Declarations Competing interests The authors declare no competing interests. Ethics statement This animal study received prior approval from the Hunan Evidence-based Biotechnology Co., Ltd. Animal Ethics Committee (No. XZ20250711). All experiments were performed in accordance with relevant guidelines and regulations. All methods are reported in accordance with ARRIVE guidelines ([135]https://arriveguidelines.org). Footnotes Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Supplementary Information The online version contains supplementary material available at 10.1038/s41598-025-20719-x. References