Taurine attenuates lipid accumulation via the eCB-CB1 axis: evidence from adipose metabolomics in HFD-fed mice and 3D adipocyte spheroids.

Abstract

Introduction

Obesity, driven by adipose tissue dysfunction, is a major global health challenge and a key contributor to metabolic disorders. Although taurine shows anti-obesity potential, its precise mechanisms for attenuating adipocyte lipid accumulation remain unclear.

Methods

In this study, high-fat diet (HFD)-induced obese mice were treated orally with taurine (700 mg/kg/day) for 14 weeks. Systemic obesity-related parameters were evaluated, with a focus on epididymal white adipose tissue (eWAT). UPLC-MS-based metabolomics combined with multivariate analysis was employed to characterize metabolic alterations in eWAT. Additionally, 3T3-L1 adipocyte spheroids were treated with taurine (0–0.5 mM), either alone or in combination with the cannabinoid receptor type 1 (CB1) agonist CP55940 or antagonist AM6545, to assess its effects on lipid accumulation and underlying mechanisms.

Results

Focusing on adipose tissue, taurine treatment effectively countered HFD-induced metabolic disturbances, particularly by suppressing epididymal fat mass accumulation and ameliorating adipocyte hypertrophy. Metabolomic profiling of eWAT revealed that taurine treatment reversed 15 out of 35 metabolic alterations, including the reduction of three anandamide (AEA) precursors, implying that taurine may alter endocannabinoid (eCB) biosynthesis by limiting precursor availability. Moreover, taurine suppressed lipid accumulation by inhibiting CB1 signaling, a mechanism supported by downregulation of lipogenic genes (including Srebf1, Acaca, Cd36, and Pparg) and upregulation of lipolytic genes (including Pnpla2, Lipe, and Ppargc1a).

Conclusion

Collectively, our findings demonstrate that taurine exerts its anti-obesity effects partially via modulation of eCB-CB1 signaling, coordinately inhibiting lipogenesis and promoting lipolysis, thereby highlighting its therapeutic potential for obesity management.

Untitled section

Keywords: cannabinoid receptor type 1, endocannabinoid, lipid accumulation, obesity, taurine

Graphical abstract

Article notes

Untitled section

Received 2026 Jan 7; Revised 2026 Feb 12; Accepted 2026 Feb 17; Collection date 2026.

Author notes

1.Introduction

Obesity is a global health challenge that increases the risk of cardiovascular disease, type 2 diabetes, and non-alcoholic fatty liver disease (1–3). According to a 2025 Lancet analysis spanning 204 countries and territories, the prevalence of overweight and obesity among adults rose steadily from 1990 to 2021, already affecting 1.00 billion men and 1.11 billion women in 2021. If current trends continue, this number is projected to reach 3.8 billion adults—more than half of the global adult population—by 2050 (4). Urgent action is needed to slow this trend and reduce the burden of type 2 diabetes and related chronic conditions. However, current pharmacotherapies often have significant adverse effects (5, 6), which promotes the search for safer alternatives, particularly from natural sources.

Taurine (2-aminoethanesulfonic acid; Tau) is a conditionally essential amino acid that is abundant in mammalian plasma and metabolically active tissues, such as the liver, heart, and white adipose tissue (WAT) (7, 8). Although synthesized endogenously, the majority of taurine is obtained exogenously through diet, particularly from seafood (9). Clinical evidence indicates that circulating taurine levels are significantly lower in individuals with obesity and/or diabetes compared to lean healthy controls (10–12). Taurine supplementation not only elevates plasma taurine and adiponectin levels, but also reduces body weight and ameliorates dyslipidemia—specifically lowering triglycerides (TG), total cholesterol (TC), and atherosclerotic index (13). Both rodent (14, 15) and human (16, 17) studies report that taurine administration significantly reduces adiposity without serious adverse effects, even at high doses. Thus, taurine is a safe, well-tolerated candidate for combating obesity.

Mechanistically, taurine regulates adipose lipid homeostasis by suppressing lipogenesis and promoting fatty acid oxidation. It suppresses de novo lipogenesis by downregulating the lipogenic transcription factors sterol regulatory element-binding protein-1c (SREBP-1c) and peroxisome proliferator-activated receptor-γ (PPAR-γ), and the enzyme fatty acid synthase (FAS) (18), while activating catabolic programs via upregulation of peroxisome proliferator-activated receptor-α (PPAR-α), peroxisome proliferator-activated receptor-γ coactivator-1α (PGC-1α), and 5’-AMP-activated protein kinase (AMPK), thereby accelerating fatty acid oxidation and lipid turnover (19, 20). Additionally, taurine promotes mitochondrial biogenesis and thermogenic capacity, as evidenced by the beiging of inguinal WAT and upregulation of PGC-1α and uncoupling protein 1 (UCP1) (21–25). Collectively, these findings cast taurine as a pivotal regulator of energy balance, lipid flux, and obesity-related metabolic dysfunction.

Notably, the adipose endocannabinoid (eCB) system—centered on cannabinoid receptor type 1 (CB1) and activated by its principal ligands, 2-arachidonoylglycerol (2-AG) and anandamide (AEA)—serves as a critical regulator of these lipid metabolic programs (26). CB1 activation stimulates lipoprotein lipase activity and fatty acid uptake, drives de novo lipogenesis via upregulation of SREBP-1c and PPAR-γ, suppresses AMPK-mediated fatty acid oxidation, and facilitates adipocyte differentiation, thereby expanding WAT and fostering insulin resistance (27–29). Conversely, peripheral CB1 antagonism normalizes metabolic defects in rodents by restoring leptin sensitivity, alleviating hyperleptinaemia, and improving glucose and lipid homeostasis, alongside resolving hepatic steatosis and fibrosis (30–33). This striking convergence on identical molecular targets (SREBP-1c, FAS, PPAR-γ, AMPK, and PGC-1α) suggests the eCB-CB1 axis to be a plausible upstream mediator of taurine’s metabolic benefits.

In obesity, adipose tissue exhibits sustained dysregulation of eCBs homostasis, characterized by elevated 2-AG and AEA (34, 35), along with upregulation of the biosynthetic enzymes diacylglycerol Lipase-α/β (DAGL-α/β) and N-acyl phosphatidylethanolamine phospholipase D (NAPE-PLD) (36). This pathological eCB overactivity drives CB1 hyperactivation, establishing a feed-forward loop that exacerbates adipocyte hypertrophy and ectopic lipid accumulation. Circulating eCBs levels correlate positively with every hallmark of metabolic dysfunction—visceral adiposity, insulin resistance, dyslipidaemia, and hepatic steatosis (34, 37–40). Importantly, Guo et al. (41) demonstrated that taurine supplementation reduced elevated hepatic Diacylglycerols (DGs) in high-fat diet (HFD)-fed mice. Given that DGs are direct precursors of 2-AG, the principal eCB activating CB1, these data position taurine as a potential modulator of adipose eCB signaling. However, whether taurine exerts its metabolic benefits through regulating the eCB-CB1 axis remains to be elucidated.

Here, we integrated untargeted UPLC-MS metabolomics of epididymal WAT (eWAT) from HFD-fed mice with mechanisms studies in three-dimensional (3D) adipocyte spheroids to determine whether taurine restores lipid metabolism by antagonizing or functionally desensitizing adipocyte cannabinoid receptors. The findings are expected to identify novel molecular targets and provide a theoretical framework for developing taurine-enriched functional foods or next-generation anti-obesity therapeutics.

2.Materials and methods

2.1.Chemicals and assay kits

Taurine (107-35-7) was from Shanghai Aladdin Biochemical Technology. The main chemicals and assay kits used in animal experiments are the same as those in Guo et al. (41). Methanol (67-56-1), acetonitrile (75–05-8), and Water (7732-18-5) were from Fisher Scientific (Pittsburgh, PA, United States). Formic Acid was from CNW Technologies GmbH. The TG (A110-1-1) kit was from Nanjing Jiancheng Bioengineering Institute (Jiangsu, China). Dexamethasone (HY-14648), insulin (HY-P0035), rosiglitazone (HY-17386), 3-Isobutyl-1-methylxanthine (IBMX; HY-12318), thyroxine (T3; HY-A0070AR), and AM6545 (CB1 antagonist, HY-110206) were from MedChemExpress LLC (China). CP55940 (CB1 agonist, C1112) was from Sigma-Aldrich (Shanghai) Trading Co., Ltd.

2.2.Animal experiment

The animal experiment was performed exactly as described in Guo et al. (41). All animals were housed under controlled conditions (22 ± 2 °C, 50 ± 10% relative humidity) on a 12-h light/dark cycle, with free access to food and water. Each cage housed two to three animals to promote social interaction while ensuring equal ad libitum feeding. For obesity induction, male C57BL/6 J mice (8 weeks old, 21 ± 1 g) were fed an HFD (41% kcal from fat, 43% kcal from carbohydrate, 16% kcal from protein) for 14 weeks. Mice were randomly assigned to three groups (n = 9 per group): (1) control group (CON), receiving normal diet (10% kcal from fat, 70% kcal from carbohydrate, 20% kcal from protein) and vehicle (distilled water); (2) HFD group (MOD), receiving HFD and vehicle; (3) TAU group, receiving HFD and taurine (TAU, 700 mg/kg). Tauirne or vehicle was administered daily by oral gavage beginning on the first day of HFD feeding.

Randomization was performed using a random number table to minimize bias. Throughout the intervention period, food intake and body weight were monitored daily. After 14 weeks, mice were fasted for 10 h, anesthetized with 4% isoflurane, and immediately euthanized by cervical dislocation. Serum and epididymal fat mass were collected for subsequent biochemical, histological, and metabolomic analyses. Epididymal fat masses were rinsed in ice-cold saline, blotted dry, and weighed to determine their wet weights. The epididymal fat mass-to-body weight ratio was calculated as (epididymal fat weight/body weight) × 100%. Body weight, serum lipid, and adipose tissue H&E images are presented as phenotypic validation. All outcome assessment and data analysis were performed by investigators blinded to the group assignments. This study used only animal procedures approved by the Experimental Animal Ethics Committee of the Functional Test Center for Health Food, College of Arts and Sciences, Beijing Union University (Approval No. 20220301) (41).

2.3.Metabolomics sample preparation

Adipose tissue (50 ± 5 mg) was homogenized in 400 μL ice-cold methanol/water (4:1, v/v), sonicated for 30 min at 5 °C (40 KHz), and centrifuged at 12,000 rpm for 15 min. After activation of CNWBONDHD-C18 SPE cartridges, the eluates were collected, centrifuged at 15,000 rpm for 20 min, and the supernatant was subjected to UPLC-MS analysis.

As part of system conditioning and quality control (QC), a pooled QC sample was prepared by mixing equal volumes of eWAT extracts from all individuals in each group (CON, MOD, and TAU). The QC sample was processed and analyzed identically to the study samples, with one injection every six analytical runs.

2.4.UPLC-MS conditions

Metabolites were separated on an ACQUITY UPLC HSST3 column (100 mm × 2.1 mm i.d., 1.8 μm; Waters, Milford, United States) at 40 °C, using a UHPLC-Orbitrap Exploris 240 system (Thermo Fisher Scientific, Waltham, MA, United States). The autosampler tray was held at 4 °C, and 3 μL of each extract was injected. Gradient elution was performed using (A) water/acetonitrile (95:5, v/v) and (B) acetonitrile/isopropanol/water (47.5:47.5:5, v/v/v), both containing 0.1% formic acid. One pooled QC sample was analyzed after every six study samples to monitor system stability.

Detection was carried out on a Q Exactive Plus mass spectrometer (Thermo Fisher Scientific, Waltham, MA, United States) with electrospray ionization in positive (ESI⁺) and negative (ESI⁻) ion modes (70–1,050 m/z). Source conditions: spray voltage 3.4 kV (ESI⁺) or 3.0 kV (ESI⁻); heater temperature 350 °C; capillary temperature 320 °C; sheath gas 60 arbitrary units; auxiliary gas 20 arbitrary units; S-lens RF 70. Data were acquired and processed with Xcalibur 4.1 (Thermo Fisher Scientific). MS/MS data were acquired in data-dependent acquisition (DDA) mode.

2.5.Multivariate statistical analysis and identification of potential differential metabolites

This study employed untargeted metabolomics for relative quantitative comparison of metabolites across groups, rather than absolute concentrations. The UPLC-MS raw data were imported into Progenesis QI software (Waters Corporation, Milford, United States) for peak picking, noise filtering, and automatic alignment. Metabolic features were characterized by retention time (RT), mass-to-charge ratio (m/z), and sum-normalized peak area. Features with missing values in more than 20% of samples within any group were excluded, and remaining missing values were imputed using the minimum value method. The data were log10-transformed before multivariate statistical analysis.

Metabolite features were identified by matching the accurate mass, MS/MS fragment spectra, and isotope patterns against reliable databases such as HMDB and METLIN. Analytical quality was assessed using pooled QC samples; features with a relative standard deviation (RSD) of more than 30% across QCs were excluded. Principal component analysis (PCA) of QC samples showed tight clustering, indicating negligible instrumental drift. Consequently, no batch correction was applied. The processed data matrix was subjected to PCA and orthogonal partial least squares discriminant analysis (OPLS-DA). PCA revealed a distinct metabolic profile among the CON, MOD, and TAU groups. The OPLS-DA model was validated using 200 permutation tests. Differential metabolites were selected based on variable importance in projection (VIP) > 1.0 (from OPLS-DA) and p < 0.05 (Student’s t-test). Given the exploratory nature of this untargeted profiling, features were prioritized by VIP and nominal p-values without stringent false discovery rate (FDR) correction, consistent with established practice for hypothesis-generating metabolomics studies (42, 43).

2.6.Pathway analysis

Differential metabolites were subjected to enrichment analysis using the Python package Scipy stats against the KEGG database and subsequently analyzed in MetaboAnalyst 5.0 to identify obesity-related pathways modulated by taurine.

2.7.Culture of 3T3-L1 preadipocytes

3T3-L1 preadipocytes (CL-0006, Wuhan Pricella) were cultured in high glucose (4.5 g/L, Genview) containing 10% newborn calf serum (NCS, 24060201, Sijiqing) and 1% w/v antibiotics (100 U/mL penicillin-0.1 mg/mL streptomycin) at 37 °C with 5% CO₂. Cells were passaged at approximately 70% confluence, and those between passages 4–8 with more than 90% viability were selected.

2.8.Spheroid fabrication

At 70% confluence, cells were trypsinized, counted, and resuspended in DMEM containing 10% NCS and 0.25% methylcellulose (9004-67-5, Solarbio) to a density of 8,000 cells per 15 μL. Fifteen-microliter drops were placed on the inverted lid of a 10-cm Petri dish containing 6 mL sterile PBS to prevent evaporation. After reattaching the lid, hanging drops were formed and incubated at 37 °C with 5% CO₂ for 48 h, allowing cells to aggregate into compact spheroids for subsequent experiments.

2.9.Adipogenic differentiation of spheroids

Spheroids were maintained in 96-well plates pre-coated with 60 μL of 1.5% (w/v) agarose to preserve their 3D architecture. Adipogenic differentiation was induced for 4 days in DMEM supplemented with 10% Fetal Bovine Serum (FBS, 10099141C, Invitrogen), 1% antibiotics, 1 μM dexamethasone, 1 μg/mL insulin, 0.5 mM IBMX, 10 μM rosiglitazone, and 10 nM T3 (200 μL per well, refreshed every 48 h), followed by 2 days in maintenance medium (DMEM/10% FBS, 1% antibiotics, 1 μg/mL insulin). On day 6, spheroids were randomized into experimental groups and cultured for an additional 2 days: differentiated control (DC) receiving maintenance medium only; taurine at 0.1, 0.25, or 0.5 mM (TAU-L, TAU-M, TAU-H); CB1 agonist (CB1-A, CP55940, 0.1 μM); CB1 antagonist (CB1-ANT, AM6545, 1 μM); and the corresponding combinations with 0.25 mM taurine (CB1-A + TAU, CB1-ANT + TAU). Undifferentiated controls (UDC) were maintained in DMEM containing 10% NCS for 8 days with medium exchange every 48 h. A schematic overview of the experimental design is presented in Figure 1. The effective concentrations of agonists/antagonists (determined by cAMP response plateaus) were selected following CCK-8 cytotoxicity screening (Supplementary Figure S1).

Diagram illustrating a timeline of pre-adipocyte to adipocyte spheroid differentiation over ten days, showing hanging drop culture, spheroid differentiation in a multi-well plate, pharmacological intervention step, and grouping into experimental conditions. — Figure 1Schematic overview of 3T3-L1 adipocyte spheroids generation and drug treatment. The process involves spheroids formation by the hanging drops culture, differentiation into adipocyte spheroids, followed by grouping and pharmacological intervention.

2.10.Lipid morphology

Lipid droplets and nuclei were visualized by sequential staining with BODIPY 493/503 (HY-W090090, MCE) and DAPI (GD3410, Genview). Spheroids were fixed in 4% (w/v) paraformaldehyde for 1 h, washed three times with PBS, and incubated with the dyes according to the manufacturer’s protocols, with PBS rinses between steps. Images were acquired on a Leica fluorescence microscope.

2.11.TG level determination

Intracellular TG was quantified using a commercial kit, normalized to total protein (BCA assay, BCA02, Beijing Dingguo Biotechnology), and expressed as μmol per gram protein.

2.12.Gene expression

Total RNA was isolated from the mouse eWAT and 3T3-L1 adipocyte spheroids with TRIzol reagent (10,057,841, Invitrogen). eWAT samples were dissected, snap-frozen, and homogenized before extraction. For spheroids, about 150 adipocyte spheroids were pooled and lysed per sample. Concentration and purity (A260/A280 ≈ 2.0, A260/A230 > 1.8) were verified using a NanoDrop spectrophotometer (Thermo Scientific). cDNA was synthesized from 1 μg of RNA with NovoScript Plus All-in-one SuperMix (E047, Novoprotein). qPCR was performed in triplicate on a Q9604 system (BioGenerator) with GS AntiQ SYBR Green Fast Mix (SQ410, Genesand). Relative expression was calculated by the 2^(-ΔΔCt) method, normalized to 18S rRNA. Primers sequences are listed in Table 1.

Table 1The primers sequences.

Target gene	Sequence (5′ → 3′)
Rn18s	F: AGAGGGAAATCGTGCGTGAC R: CAATAGTGATGACCTGGCCGT
Cnr1	F: TGCACAAGCACGCCAATAAC R: ACAGTGCTCTTGATGCAGCTTTC
Srebf1	F: ACACAGCAACCAGAAACTCAAG R: AGTGTGTCCTCCACCTCAGTCT
Acaca	F: GGCAATGACATCACATACCG R: CAGTCCGATTCTTGCTCCAC
Cd36	F: ATGGGCTGTGATCGGAACTG R: GTCTTCCCAATAAGCATGTCTCC
Pparg	F: GACCACTCGCATTCCTTTGACA R: ATCGCACTTTGGTATTCTTGGA
Lipe	F: GCTGGGCTGTCAAGCACTGT R: GTAACTGGGTAGGCTGCCAT
Pnpla2	F: AGGACAGCTCCACCAACATC R: TGGTTCAGTAGGCCATTCCT
Ppargc1a	F: AACCTTAAGTGTGGAACTCTCTGGA R: CGTTTAGTCTTCCTTTCCTCGTGT
Faah	F: GTGGATAGCCTGGCATTGTG R: GGAGTGGGCATGGTGTAGTTG

2.13.Statistical analysis

Data are expressed as mean ± SD. Intergroup differences were analyzed using unpaired two-tailed Student’s t-tests, and one-way ANOVA followed by Dunnett’s post hoc test, with p < 0.05 considered significant.

3.Results

3.2.Taurine lowers endocannabinoid precursors in adipose tissue of obese mice

3.2.1.Comprehensive quality control and metabolic feature profiling

Representative total ion chromatograms (TIC) of eWAT samples in both ESI⁺ and ESI⁻ modes, acquired by UPLC-MS, are presented in Supplementary Figure S3 to visualize metabolic profiles and assess the effect of taurine in obese mice. Additionally, the overlaid TICs of QC samples, prepared from pooled eWAT extracts across all groups, are shown in Supplementary Figure S4, confirming the analytical stability and repeatability throughout the run. All subsequent data indicate directional trends in metabolite abundance.

To further evaluate data quality, the RSD of all detectable peaks in the QC samples was calculated. As summarized in Supplementary Figure S5, more than 96.7% (Pre QC) and 92.5% (Raw QC) of metabolic features exhibited RSD values below 30%, demonstrating high reproducibility and reliability of the dataset and supporting its suitability for subsequent statistical analysis.

Following preprocessing—including missing value screening, normalization, QC-based validation, and data transformation—a total of 1733 metabolic features were extracted from all samples. These comprised 824 in ESI⁺ and 909 in ESI⁻ mode, as detailed in Table 2.

Table 2Total ion number and database identification.

Ion mode	All peaks	Identified metabolites	Metabolites in library	Metabolites in KEGG
Pos	6,564	824	781	436
Neg	8,370	909	870	530

3.2.2.Multivariate statistical analysis reveals altered metabolic profiles

Unsupervised PCA was initially performed to visualize the overall metabolic distribution among the CON, MOD, and TAU groups. While the QC samples remained tightly clustered, indicating sustained analytical stability (Figure 3A), distinct group-specific metabolic signatures were observed alongside moderate separation between groups. This indicates that global metabolic differences among groups are modest at the unsupervised level, likely reflecting inherent biological variability. Subsequently, pairwise OPLS-DA models were constructed to compare metabolic profiles between groups. The MOD vs. CON comparison yielded a robust model (R²Y = 0.967, Q² = 0.706), indicating substantial metabolic perturbations induced by HFD. Similarly, the TAU vs. MOD comparison demonstrated strong predictive ability (R²Y = 0.896, Q² = 0.770), reflecting taurine-mediated metabolic alterations. Permutation tests (n = 200) confirmed model validity, as the regression lines of both Q² and R²Y intersected the Y-axis below zero (p < 0.05), effectively ruling out overfitting. Score plots revealed clear separation in both comparisons (Figure 3B).

Panel of scientific data visualizations and charts related to metabolomics analysis, including PCA and OPLS-DA plots (A, B), heatmaps of metabolite expression profiles with VIP scores (C, D), bar graphs showing compound classifications (E, F), a Venn diagram illustrating shared and unique metabolites among groups (G), and a KEGG pathway enrichment bar chart (H), indicating statistical significance and metabolic pathway involvement across experimental groups. — Figure 3Comprehensive metabolomics analysis of eWAT. **(A)** Principal component analysis (PCA) score plots in ESI⁺ (a) and ESI⁻ (b). **(B)** Orthogonal partial least squares discriminant analysis (OPLS-DA) score plots for pairwise comparisons in both ESI⁺ and ESI⁻ ionization modes: MOD vs. CON (a, b) and TAU vs. MOD (c, d). **(C,D)** Hierarchical clustering heatmaps of differential metabolites for **(C)** MOD vs. CON and **(D)** TAU vs. MOD. **(E,F)** Classification of differential compounds for **(E)** MOD vs. CON and **(F)** TAU vs. MOD. **(G)** Venn diagram illustrating the overlap of differential metabolites among the three groups. **(H)** KEGG pathway enrichment analysis for differential metabolites. *p < 0.05, **p < 0.01, ***p < 0.001. Metabolite prioritization was based on a combination of a variable importance in projection (VIP) score > 1.0 and a p-value < 0.05.

3.2.3.Screening and characterization of differential metabolites

Based on the OPLS-DA model, metabolites with VIP > 1.0 and a t-test p-value<0.05 were selected as significant contributors to inter-group differences. The clustering heatmaps of these differential metabolites clearly distinguished the MOD vs. CON groups (Figure 3C) and TAU vs. MOD groups (Figure 3D), highlighting the top 30 VIP-ranked metabolites in each comparison. These visualizations revealed distinct, group-specific metabolite signatures.

3.2.4.Classification of differential metabolites

A total of 500 significantly altered metabolites were identified between groups MOD and CON, primarily belonging to glycerophospholipids (GPs), eicosanoids, fatty acids, and monosaccharides (Figures 3E,G). In contrast, 93 metabolites were significantly altered between groups TAU and MOD (Figures 3F,G), mainly including GPs, monosaccharides, fatty acids, and amino acids.

3.2.5.Identification of common altered metabolites

A total of 35 differential metabolites were listed across all comparisons and are detailed in Table 3, along with their corresponding RT, m/z, VIP values, and change trends. Notably, of the 17 metabolites consistently altered in both comparisons, HFD feeding increased 7 and decreased 10 in MOD versus CON mice; taurine supplementation reversed 15 of these changes (6/7 increased and 9/10 decreased metabolites) in eWAT.

Table 3Significantly metabolites in adipose tissue samples.

No	Category	Metabolite	Mode	RT (min)	M/Z	VIP	Trend
No	Category	Metabolite	Mode	RT (min)	M/Z	VIP	MOD/CON	TAU/MOD
1	Glycerophospholipids	PE(18:4(6Z,9Z,12Z,15Z)/18:0)	Positive	7.28	762.50	1.56	Up	Down
2	Glycerophospholipids	GPEtn(18:3/18:1)	Positive	7.48	740.52	1.11	Up	Down
3	Sphingolipids	Sphinganine	Positive	6.17	302.31	1.83	Up	Down
4	Sphingolipids	SM(d18:1/14:0)	Negative	7.40	719.53	1.36	Up	Down
5	Fatty acids	Arachidonic acid	Negative	6.66	303.23	1.34	Down	Up
6	Fatty acids	Eicosapentaenoic Acid	Negative	6.56	301.22	1.62	Down	Up
7	Bile acids	24-NorUrsodeoxycholic Acid	Negative	6.76	399.25	1.89	Down	Up
8	Amino acids	L-2-Amino-3-oxobutanoic acid	Negative	1.03	116.04	1.17	Down	Up
9	Monosaccharides	Glucose	Positive	0.59	383.12	2.29	Up	Down
10	Other	Succinyladenosine	Positive	3.46	384.11	1.68	Up	Down
11	Other	Cromakalim	Negative	6.25	267.11	1.15	Down	Up
12	Other	Cilastatin	Negative	6.65	403.16	1.02	Down	Up
13	Other	Ibuprofen glucuronide	Negative	6.60	427.16	1.37	Down	Up
14	Other	Pulchinenoside B4	Positive	3.81	622.31	2.48	Down	Up
15	Other	(2-Acetyloxy-3-hydroxypropyl) (E)-octadec-9-enoate	Positive	6.60	421.29	1.00	Down	Up
16	Glycerophospholipids	LysoPC(20:0/0:0)	Negative	6.87	596.39	1.99	Down	Down
17	Amino acids	Glucaric acid	Positive	3.46	252.07	1.66	Down	Down
18	Diradylglycerols	DG(14:1(9Z)/15:0/0:0)	Negative	7.08	505.43	2.97	Up	–
19	Diradylglycerols	DG(22:6(4Z,7Z,10Z,13Z,16Z,19)/22:5(4Z,7Z,10Z,13Z,16Z)/0:0)	Positive	7.38	697.52	1.36	Up	–
20	Sphingolipids	Sphingosine 1-phosphate	Negative	6.42	424.25	2.19	Up	–
21	Glycerophospholipids	Sn-glycero-3-Phosphoethanolamine	Negative	0.59	214.0	1.66	–	Down
22	Fatty acids	Docosahexaenoic acid	Negative	6.60	327.23	1.82	Down	–
23	Fatty acids	Cervonoyl ethanolamide	Negative	6.43	371.26	2.81	Up	–
24	Fatty acids	Linoleic acid	Negative	6.69	279.23	1.11	Down	–
25	Eicosanoids	PG(i-15:0/LTE4)	Negative	7.18	872.47	1.31	Up	–
26	Eicosanoids	18-carboxy dinor Leukotriene B4	Negative	6.14	337.17	1.75	Up	–
27	Eicosanoids	DG(PGE2/0:0/8:0)	Positive	0.75	585.40	1.93	Up	–
28	Amino acids	N-hydroxy-L-tryptophan	Negative	4.41	659.25	2.48	Down	–
29	Amino acids	N-Acetyl-D-tryptophan	Negative	5.98	551.22	2.86	–	Down
30	Amino acids	Formiminoglutamic acid	Positive	0.66	157.06	2.04	Up	–
31	Amino acids	Tyrosylhydroxyproline	Positive	4.20	295.13	2.01	Down	–
32	Vitamin	24-Oxo-1alpha,25-dihydroxyvitamin D3	Negative	6.56	451.30	1.26	Down	–
33	Vitamin	Riboflavin (Vitamin B2)	Positive	4.49	337.15	1.85	Down	–
34	Vitamin	Pantothenic Acid(Vitamin B5)	Positive	3.40	220.12	1.63	–	Up
35	Organoheterocyclic compounds	Indoleacetaldehyde	Negative	5.80	204.07	2.94	Down	–

3.2.6.Pathway enrichment analysis

The KEGG pathway enrichment analysis revealed that the 15 reversed differential metabolites were significantly enriched in several pathways, with the retrograde endocannabinoid signaling pathway being among the most prominently impacted (Figure 3H). Notably, three candidate metabolites among these top 15 common differential metabolites—Glycerophosphoethanolamine (GPEtn, 18:3/18:1), phosphatidylethanolamine (PE, 18:4/18:0), and arachidonic acid (AA)—participate in eCB biosynthesis (Table 3). Their MS/MS spectra have been provided in Supplementary Figure S6. All three metabolites exhibited HFD-driven perturbations (GPEtn and PE increased, AA decreased) that were reversed by taurine supplementation, suggesting them as key precursors whose taurine-mediated restoration implies suppression of eCB synthesis. Moreover, HFD elevated levels of key eCB pathway components, including the direct synthesis substrates DGs (DG (22:6/22:5/0:0) and DG (14:1/15:0/0:0)) and downstream sphingolipid mediators sphingosine-1-phosphate and sphinganine, which were not reversed by taurine. However, taurine did markedly reduce sn-glycero-3-phosphoethanolamine, a molecule convertible to PE.

In summary, our metabolomics analysis revealed that taurine supplementation reversed HFD-induced alterations in 15 specific metabolites, with a pronounced impact centered on the endocannabinoid signaling through modulation of precursor availability.

3.3.Taurine attenuates lipid accumulation in differentiating 3T3-L1 spheroids via CB1 regulation

Based on the morphological and metabolomics alterations observed in HFD-fed mice, we employed 3T3-L1 adipocyte spheroids to further elucidate the mechanisms by which taurine regulates lipid metabolism. A schematic overview of the experimental design is presented in Figure 4A.

Panel A presents a flowchart of pre-adipocyte spheroid differentiation, experimental group assignments, and staining or triglyceride measurement endpoints. Panels B and C display representative fluorescent microscopy images showing Bodipy (lipid, green), DAPI (nucleus, blue), and merged channels for each condition. Panels D and F are bar graphs quantifying Bodipy fluorescent area, while panels E and G are bar graphs quantifying triglyceride content, each with statistical significance indicated by asterisks. — Figure 4Taurine attenuates lipid accumulation in differentiated 3 T3-L1 spheroids via CB1 regulation. **(A)** Schematic of the experimental design. **(B)** Representative fluorescence images of 3 T3-L1 spheroids. From top to bottom: undifferentiated control spheroids (UDC), differentiated control spheroids (DC), and differentiated spheroids treated with taurine at concentrations of 0.1 mM (Tau-L), 0.25 mM (Tau-M), and 0.5 mM (Tau-H). Nuclei were stained with DAPI (blue), and lipid droplets were stained with BODIPY (green). **(C)** Representative fluorescence images of differentiated spheroids under various treatments: differentiated control (DC), taurine-treated (TAU), CP-55940 (CB1 agonist)-treated (CB1-A), CP-55940 and taurine co-treated (CB1-A + TAU), AM6545 (CB1 antagonist)-treated (CB1-ANT), and AM6545 and taurine co-treated (CB1-ANT + TAU). Staining is as in **(B)**. **(D,E)** Quantification of the fluorescence area and intracellular TG from **(B)**. **(F,G)** Quantification of the fluorescence area and intracellular TG from **(C)**. Data are presented as mean ± SD. *p < 0.05.

As shown in Figures 4B,D,E, differentiated control spheroids (DC) exhibited markedly enlarged lipid droplets (BODIPY-positive staining), increased fluorescence area, and elevated intracellular TG content compared to undifferentiated controls (UDC), confirming successful adipogenic maturation. Corroborating the in vivo findings in HFD-fed mice, taurine treatment dose-dependently attenuated these adipogenic markers in differentiated spheroids, with lipid droplet size, fluorescence area, and TG level all progressively decreasing at increasing concentrations (0.1, 0.25, and 0.5 mM, TAU-L~H; 48 h), demonstrating effective suppression of lipid accumulation.

To determine whether CB1 signaling contributes to this lipid-lowering effect of taurine, we performed pharmacological intervention experiments in differentiated adipocyte spheroids, assessing lipid accumulation by BODIPY staining (qualitative and quantitative fluorescence analysis) and intracellular TG content measurement. Taurine (0.25 mM, 48 h) significantly reduced lipid droplets (Figure 4C), fluorescence area (Figure 4F), and intracellular TG levels (Figure 4G), indicating potent attenuation of lipid accumulation. Activation of CB1 with CP55940 (0.1 μM, CB1-A) increased lipid accumulation compared to vehicle controls. Notably, the lipid-lowering efficacy of taurine was partially attenuated under CB1 activation, as evidenced by diminished reductions in both fluorescence area and TG content, suggesting that taurine acts, at least in part, through CB1-dependent mechanisms. In contrast, selective CB1 blockade with AM6545 (1 μM, CB1-ANT) reduced lipid accumulation to an extent comparable to taurine alone across all measured parameters. Co-treatment with taurine and CB1-ANT did not produce further reduction, indicating saturation of the lipid-lowering response. Collectively, these findings demonstrate that taurine suppresses adipocyte lipid accumulation through partially CB1-dependent mechanisms.

3.4.Taurine regulates mRNA expression of adipogenic and lipolysis-related factors by inhibiting CB1

Numerous studies have reported markedly increased CB1 levels in obese individuals (34, 35, 44). Consistently, mRNA expression of Cnr1 and the eCB-degrading enzyme fatty acid amide hydrolase (Faah) was also observed to be significantly elevated in the MOD group relative to CON (Figures 5A,D). Given the established crosstalk between the eCB system and adipogenic metabolism, we concurrently quantified Pparg and Ppargc1a expression. Correspondingly, the levels of the lipogenic regulator Pparg and the master driver of fatty acid oxidation, Ppargc1a, were also upregulated in the MOD group (Figures 5B,C). Taurine supplementation substantially normalized Cnr1 levels, partially reduced Pparg expression, and further enhanced Ppargc1a mRNA levels beyond those in the MOD group, while it had no significant effect on Faah expression. The coordinated effect of taurine on the CB1 pathway and these opposing metabolic phenotypes (Pparg downregulation and Ppargc1a upregulation) prompted us to determine the underlying cellular mechanisms, specifically whether CB1 mediates these effects, in a more controlled system.

Panel of twelve bar graphs labeled A to L showing relative mRNA expression levels of various genes in mouse and adipose tissue experimental groups. Panels A-D (mouse, genes Cnr1, Pparg, Ppargc1a, Faah) and E-L (adipose, genes Cnr1, Srebf1, Acaca, Cd36, Pparg, Lipe, Pnpla2, Ppargc1a) display statistically significant differences between groups, indicated by asterisks and brackets above bars. Group labels include CON, MOD, TAU, DC, TAU, CB1A, CB1A+TAU, CB1-AMT, and CB1-AMT+TAU. Each panel includes relevant axis labels and gene names. — Figure 5Taurine regulates adipogenic and lipolytic gene networks through CB1 inhibition. **(A–D)** mRNA expression levels of key regulatory genes in adipose tissue of HFD-induced mice: **(A)** *Cnr1*, **(B)** *Pparg*, **(C)** *Ppargc1a*, and **(D)** *Faah*. **(E–L)** mRNA expression profiles of adipogenesis and lipolysis-related genes in 3T3-L1 adipocyte spheroids: **(E)** *Cnr1*, **(F)** *Srebf1*, **(G)** *Acaca*, **(H)** *Cd36*, **(I)** *Pparg*, **(J)** *Lipe*, **(K)** *Pnpla2*, and **(L)** *Ppargc1a*. *p < 0.05.

In adipocytes, lipid accumulation represents a balance between anabolism (governed by adipogenic factors including Srebf1, Acaca, and Pparg (45) and fatty acid uptake via Cd36) and catabolism [via lipolytic enzymes Lipe and Pnpla2, and mitochondrial fatty acid oxidation regulated by Ppargc1a (46, 47)]. To delineate how taurine modulates this balance through the Cnr1, we assessed the expression of these key regulators in our 3D adipocyte model. As shown in Figure 5E, taurine treatment (TAU) significantly downregulated Cnr1 mRNA expression, whereas the CB1 agonists (CB1-A) markedly increased it. Importantly, taurine counteracted the agonist-induced upregulation of Cnr1, demonstrating its inhibitory effect even under CB1-stimulated conditions. Moreover, the CB1 antagonist (CB1-ANT) alone similarly downregulated Cnr1, and no additive suppression was observed upon co-treatment with taurine, consistent with CB1-mediated action.

We next examined downstream transcriptional changes (Figures 5F–L). Taurine downregulated adipogenic genes (Srebf1, Acaca, Pparg) and the fatty acid transporter Cd36, while upregulating lipolytic genes (Lipe, Pnpla2) and Ppargc1a. Conversely, CB1 activation promoted adipogenic gene expression but suppressed lipolytic and oxidative transcripts. These effects were effectively counteracted by taurine. Furthermore, the CB1 antagonist alone largely recapitulated the regulatory pattern of taurine, and no synergistic effects were detected in combination treatments.

Together, these results demonstrate that taurine modulates adipogenic and lipolytic gene expression through a CB1-dependent pathway.

4.Discussion

Obesity, a global pandemic, contributes significantly to metabolic disorders primarily through dysfunctional adipose tissue. Taurine, a naturally occurring amino acid, exhibits anti-obesity potential and a favorable safety profile, yet the precise mechanisms by which it attenuates lipid accumulation in adipocytes remain elusive. This study identifies a novel role for taurine in combating obesity via CB1 signaling-dependent regulation of adipose tissue metabolism. Specifically, eWAT metabolomics analysis revealed that taurine treatment reversed 15 out of 35 molecular alterations, including the reduction of three AEA precursors, implying that taurine may suppress eCB biosynthesis by limiting precursor availability. Furthermore, using in vitro adipocyte spheroids, we found that taurine suppresses lipid accumulation by attenuating CB1 signaling, a mechanism corroborated by reduced lipogenic and enhanced lipolytic gene expression. Collectively, these results suggest that taurine is a potent therapeutic agent targeting the eCB-CB1 axis for the treatment of obesity.

In the present study, mice received taurine at a dose of 700 mg/kg via daily gavage for 14 weeks, which ensured more accurate dosing than administration via diet or drinking water. The mouse dose of 700 mg/kg corresponds to a human equivalent dose of approximately 57 mg/kg, which equates to a total dose of about 3.4 g for a 60 kg adult, based on body surface area conversion. It is important to note that the safety of taurine in humans has been established in clinical settings. Published studies report that even at relatively high oral doses, such as 3 g/day for 7 weeks or 6 g/day for 4 weeks, they showed a favorable safety profile (48). Consistent with these safety data, previous murine studies have employed taurine at doses of 500–1,000 mg/kg/day and reported beneficial metabolic effects without adverse outcomes (49). Collectively, these findings support the safety of our selected taurine dose for metabolic intervention.

A key finding from our animal studies is that taurine ameliorates lipid metabolic disorders by precisely modulating the eCB system in adipose tissue. Our metabolomics results revealed that an HFD elevated levels of key phospholipid metabolites, including PE, its derivative GPEtn, and DG, while concurrently depleting free AA. This profile is consistent with membrane phospholipid remodeling and increased eCB precursor availability for eCB synthesis (50, 51). The reduction in AA likely reflects its heightened conversion into inflammatory mediators (10, 52, 53); metabolomic data also showed elevated levels of AA-derived metabolites such as PG(i-15:0/LTE4), DG(PGE2/0:0/8:0), and 18-carboxy dinor Leukotriene B4, supporting increased AA utilization in eicosanoid pathways (54, 55). Therefore, AA decrease does not oppose eCB system upregulation but suggests augmented metabolic flux, aligning with reported eCB upregulation in obesity (56, 57). Crucially, taurine treatment selectively reversed this profile by normalizing PE/GPEtn and AA levels without altering DGs in eWAT, while our previous report suggests that taurine reversed DG abnormalities in the liver tissue of HFD mice (41), indicating that taurine has tissue or pathway specificity in its effects. This selective efficacy provides insight into the mechanism of taurine. The reversal by taurine of both PE and GPEtn—specific substrates for the NAPE-PLD-mediated biosynthesis for AEA (58, 59)—suggests a targeted effect on this branch of the eCB biosynthetic pathway. Furthermore, as a recognized anti-inflammatory agent, taurine may promote AA accumulation by lowering inflammatory factors and reducing the demand for AA in eicosanoids. In contrast, the lack of an effect on DGs, the primary precursor for 2-AG synthesis via DAGL (60), indicates that taurine does not broadly inhibit all eCB production but rather acts with specificity. This alteration in precursor lipid levels is further reinforced by the downregulation of CB1 mRNA following taurine intervention. Since elevated eCB signaling promotes adiposity and metabolic dysfunction (61, 62), our findings indicate that taurine alleviates obesity, at least in part, by attenuating the adipose tissue eCB-CB1 axis through limiting precursor availability and receptor expression.

In addition to the eCB pathway, we also found that taurine’s anti-obesity effects involve other processes, including the cAMP and phospholipase D signaling pathway, as well as GP and sphingolipid metabolism. These pathways do not operate in isolation but exhibit extensive crosstalk with the eCB signal network (63–65). For example, eCB inhibited the production of cAMP—a key second messenger for lipolysis—through the CB1 receptor (66). Furthermore, beyond serving as the source of eCB and its precursors (as previously mentioned), GPs and other membrane phospholipids contribute to the metabolic environment that supports the corrective effects of the eCB pathway in obesity. Therefore, taurine’s synergistic regulation of these pathways, including their extensive crosstalk with the eCB signaling, fosters a metabolic environment that inhibits lipogenesis and promotes lipolysis.

To elucidate the mechanistic actions of taurine in adipocytes, we employed a 3D spheroid culture system of 3 T3-L1 cells. This model recapitulates key aspects of the in vivo adipose tissue microenvironment, thereby enhancing adipocyte maturation and promoting lipid droplet formation and TG accumulation compared to 2D culture (50), thus providing a robust platform for our mechanistic studies. Treatment with taurine resulted in an expected and dose-dependent reduction of lipid droplets and TG levels, confirming taurine’s efficacy within this improved model. Furthermore, our results demonstrated that taurine suppresses lipid accumulation primarily through attenuating CB1 signaling, as evidenced by pharmacological studies utilizing both CB1 activation and blockade. Activation of the CB1 promotes lipogenesis and inhibits lipolysis (67–69). CB1 activation promotes fatty acid uptake, inhibits AMPK-mediated lipid oxidation, and promotes adipocyte differentiation. On the contrary, peripheral CB1 antagonism normalizes these defects, restores various indicators, and improves glucose and lipid status (27–29). Taurine is similar to CB1 antagonists in improving metabolic phenotype, which further demonstrates the regulatory effect of taurine on the activity of the eCB system. Thus, taurine ameliorates lipid accumulation in adipocytes by targeting the CB1, paving the way for its development as a novel anti-obesity therapeutic strategy.

Elevated eCB levels and the subsequent CB1 activation are key hallmarks of obesity, driving lipid metabolic disorders through a well-characterized signaling axis (70). Specifically, activated CB1 promotes lipogenesis by upregulating Srebf1 and Acaca (71, 72), enhances fatty acid uptake via Cd36 (73), stimulates adipocyte differentiation through Pparg (74, 75), and suppresses lipolysis by inhibiting Pnpla2 and Lipe (76, 77). Moreover, CB1 activation reduces mitochondrial fatty acid oxidation via downregulation of Ppargc1a (78). In this study, taurine’s reversal of the CB1 agonist-induced metabolic shift (from lipolysis to lipogenesis) provides functional evidence that taurine actively opposes CB1-mediated signaling. Furthermore, the finding that taurine does not synergistically enhance the lipid-catabolic response elicited by a CB1 inhibitor suggests convergence on shared downstream signaling events, consistent with taurine acting upstream of the receptor. This interpretation is supported by previous studies demonstrating that taurine downregulates lipogenic factors (Srebf1, Acaca, Cd36, and Pparg (79–82)) and upregulates critical lipolytic and oxidative mediators [such as Pnpla2, Lipe, and Ppargc1a (83, 84)]. Therefore, our results, as summarized in Figure 6, suggest that modulation of the eCB-CB1 axis represents a potential upstream mechanism through which taurine coordinates its broad transcriptional regulation of lipid storage and mobilization pathways.

Biochemical diagram showing taurine’s effect on lipid metabolism through modulation of the cannabinoid 1 receptor. Key pathways depicted include lipolysis and lipogenesis, with arrows indicating enzymes, intermediates, and their regulatory directions. Cellular structure boundaries and mitochondria are illustrated. — Figure 6Working model: taurine regulates adipose lipid metabolism through partial modulation of the eCB-CB1 axis.

While these findings implicate the eCB-CB1 axis in taurine’s metabolic effects, the precise molecular mechanisms warrant further investigation. Our conclusions are based on pharmacological interventions and precursor lipid alterations. However, direct assessment of CB1 receptor activation states (e.g., cAMP inhibition, receptor phosphorylation) and absolute quantification of eCB levels (AEA and 2-AG) by targeted LC–MS/MS were not performed and will be addressed in future studies. Consequently, whether taurine acts as a direct CB1 antagonist or indirectly modulates the pathway through upstream regulation remains to be elucidated. Future studies incorporating stable isotope-labeled internal standards for absolute quantification will address this gap.

5.Conclusion

Overall, our work reveals that taurine alleviates obesity by attenuating the adipose tissue eCB-CB1 axis. This inhibition coordinates a transcriptional program that concurrently suppresses lipogenesis and promotes lipolysis. Collectively, these results provide mechanistic insight into how taurine alleviates obesity and support its further development as a novel therapy targeting the eCB-CB1 axis.

Acknowledgments

The authors would like to acknowledge reviewers for providing constructive suggestions.

Glossary

2-AG: 2-arachidonoyl glycerol
3D: three-dimensional
AA: arachidonic acid
AEA: anandamide
AMPK: 5’-AMP-activated protein kinase
CB1: cannabinoid receptor type-1
DAGL-α/β: diacylglycerol lipase-alpha/beta
DDA: data-dependent acquisition
DG: diacylglycerol
eCB: endocannabinoid
eWAT: epididymal white adipose tissue
FAAH: fatty acid amide hydrolase
FAS: fatty acid synthase
FBS: Fetal Bovine Serum
GP: glycerophospholipid
GPEtn: glycerophosphoethanolamine
HDL-C: high-density lipoprotein cholesterol
HFD: high-fat diet
IBMX: 3-Isobutyl-1-methylxanthine
LDL-C: low-density lipoprotein cholesterol
M/Z: mass-to-charge ratio
NAPE-PLD: NAPE phospholipase D
NCS: newborn calf serum
OPLS-DA: orthogonal partial least squares discriminant analysis
PCA: principal component analysis
PE: phosphatidylethanolamine
PGC-1α: PPARγ coactivator-1α
PPAR-α: peroxisome proliferator-activated receptor-alpha
PPAR-γ: peroxisome proliferator-activated receptor-gamma
QC: quality control
RSD: relative standard deviation
RT: retention time
SREBP-1c: sterol regulatory element-binding protein-1c
T3: thyroxine
Tau: taurine
TC: total cholesterol
TG: triglycerides
TIC: total ion chromatogram
UCP1: uncoupling protein 1
VIP: variable importance in projection
WAT: white adipose tissue

Funding Statement

The author(s) declared that financial support was received for this work and/or its publication. This research was funded by the Academic Research Projects of Beijing Union University, grant number ZK10202206.

Footnotes

Footnote Group

Data availability statement

The datasets for this study can be found in the Figshare repository (https://doi.org/10.6084/m9.figshare.31007782).

Ethics statement

The animal study was approved by the Experimental Animal Ethics Committee of the Functional Test Center for Health Food, College of Arts and Sciences, Beijing Union University (20220301). The study was conducted in accordance with the local legislation and institutional requirements.

Author contributions

QW: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Software, Visualization, Writing – original draft. YS: Formal analysis, Investigation, Methodology, Writing – original draft. LZ: Data curation, Methodology, Writing – original draft. XG: Data curation, Methodology, Writing – original draft. SM: Formal analysis, Software, Writing – review & editing. YZ: Funding acquisition, Methodology, Writing – review & editing. PC: Investigation, Project administration, Writing – review & editing. CX: Visualization, Writing – original draft. JG: Conceptualization, Data curation, Funding acquisition, Methodology, Project administration, Writing – review & editing.

Conflict of interest

The author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Generative AI statement

The author(s) declared that Generative AI was not used in the creation of this manuscript.

Any alternative text (alt text) provided alongside figures in this article has been generated by Frontiers with the support of artificial intelligence and reasonable efforts have been made to ensure accuracy, including review by the authors wherever possible. If you identify any issues, please contact us.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Supplementary material

The Supplementary material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fnut.2026.1782392/full#supplementary-material

References

Untitled section

References

1.Tutor AW, Lavie CJ, Kachur S, Milani RV, Ventura HO. Updates on obesity and the obesity paradox in cardiovascular diseases. Prog Cardiovasc Dis. (2023) 78:2–10. doi: 10.1016/j.pcad.2022.11.013
2.Boutari C, DeMarsilis A, Mantzoros CS. Obesity and diabetes. Diabetes Res Clin Pract. (2023) 202:110773. doi: 10.1016/j.diabres.2023.110773,
3.Lee E, Korf H, Vidal-Puig A. An adipocentric perspective on the development and progression of non-alcoholic fatty liver disease. J Hepatol. (2023) 78:1048–62. doi: 10.1016/j.jhep.2023.01.024,
4.Collaborators GAB. Global, regional, and national prevalence of adult overweight and obesity, 1990-2021, with forecasts to 2050: a forecasting study for the global burden of disease study 2021. Lancet. (2025) 405:813–38. doi: 10.1016/s0140-6736(25)00355-1
5.Chang YH, Hung HY. Recent advances in natural anti-obesity compounds and derivatives based on in vivo evidence: a mini-review. Eur J Med Chem. (2022) 237:114405. doi: 10.1016/j.ejmech.2022.114405,
6.De Vry J, Schreiber R, Eckel G, Jentzsch KR. Behavioral mechanisms underlying inhibition of food-maintained responding by the cannabinoid receptor antagonist/inverse agonist SR141716A. Eur J Pharmacol. (2004) 483:55–63. doi: 10.1016/j.ejphar.2003.10.012,
7.Jong CJ, Sandal P, Schaffer SW. The role of taurine in mitochondria health: more than just an antioxidant. Molecules. (2021) 26:4913. doi: 10.3390/molecules26164913,
8.Wen C, Li F, Zhang L, Duan Y, Guo Q, Wang W, et al. Taurine is involved in energy metabolism in muscles, adipose tissue, and the liver. Mol Nutr Food Res. (2019) 63:e1800536. doi: 10.1002/mnfr.201800536,
9.Duan H, Song W, Guo J, Yan W. Taurine: a source and application for the relief of visual fatigue. Nutrients. (2023) 15:1843. doi: 10.3390/nu15081843,
10.Franconi F, Bennardini F, Mattana A, Miceli M, Ciuti M, Mian M, et al. Plasma and platelet taurine are reduced in subjects with insulin-dependent diabetes mellitus: effects of taurine supplementation. Am J Clin Nutr. (1995) 61:1115–9. doi: 10.1093/ajcn/61.4.1115
11.Merheb M, Daher RT, Nasrallah M, Sabra R, Ziyadeh FN, Barada K. Taurine intestinal absorption and renal excretion test in diabetic patients: a pilot study. Diabetes Care. (2007) 30:2652–4. doi: 10.2337/dc07-0872,
12.Rafiee Z, García-Serrano AM, Duarte JMN. Taurine supplementation as a neuroprotective strategy upon brain dysfunction in metabolic syndrome and diabetes. Nutrients. (2022) 14:1292. doi: 10.3390/nu14061292,
13.Zhang M, Bi LF, Fang JH, Su XL, Da GL, Kuwamori T, et al. Beneficial effects of taurine on serum lipids in overweight or obese non-diabetic subjects. Amino Acids. (2004) 26:267–71. doi: 10.1007/s00726-003-0059-z
14.Geng X, Feng Y, Yu C, Yao Y, Chen W, Guo J, et al. Taurine supplementation decreases fat accumulation by suppressing FAS and enhancing ATGL through the ATGL pathway. Iran J Basic Med Sci. (2024) 27:1529–35. doi: 10.22038/ijbms.2024.76625.16590,
15.Wei W, Lyu X, Markhard AL, Fu S, Mardjuki RE, Cavanagh PE, et al. PTER is a N-acetyltaurine hydrolase that regulates feeding and obesity. Nature. (2024) 633:182–8. doi: 10.1038/s41586-024-07801-6,
16.Rosa FT, Freitas EC, Deminice R, Jordão AA, Marchini JS. Oxidative stress and inflammation in obesity after taurine supplementation: a double-blind, placebo-controlled study. Eur J Nutr. (2014) 53:823–30. doi: 10.1007/s00394-013-0586-7,
17.Sun Q, Wang J, Wang H, Yu H, Wan K, Ma F, et al. Effect of long-term taurine supplementation on the lipid and glycaemic profile in adults with overweight or obesity: a systematic review and meta-analysis. Nutrients. (2024) 17:55. doi: 10.3390/nu17010055,
18.Karikkakkavil Prakashan AD, Muthukumar SP, Martin A. Taurine activates SIRT1/AMPK/FOXO1 signaling pathways to favorably regulate lipid metabolism in C57BL6 obese mice. Mol Nutr Food Res. (2024) 68:e2200660. doi: 10.1002/mnfr.202200660,
19.Meng L, Lu F, Zhang B, Ma Y, Gao J. Taming fatty liver: can taurine combat metabolic dysfunction in MASLD? Cell Commun Signal. (2025) 23:439. doi: 10.1186/s12964-025-02439-x,
20.Guo Q, Zhang L, Yin Y, Gong S, Yang Y, Chen S, et al. Taurine attenuates oxidized fish oil-induced oxidative stress and lipid metabolism disorder in mice. Antioxidants. (2022) 11:1391. doi: 10.3390/antiox11071391,
21.Guo YY, Li BY, Peng WQ, Guo L, Tang QQ. Taurine-mediated browning of white adipose tissue is involved in its anti-obesity effect in mice. J Biol Chem. (2019) 294:15014–24. doi: 10.1074/jbc.RA119.009936,
22.Tsai PY, Shui B, Lee S, Liu Y, Qu Y, Cheng C, et al. Ado-mediated depletion of taurine impairs mitochondrial respiratory capacity and alters the chromatin landscape of inguinal adipose tissue. Nutrients. (2023) 15:3532. doi: 10.3390/nu15163532,
23.El Idrissi A, El Hilali F, Rotondo S, Sidime F. Effects of taurine supplementation on neuronal excitability and glucose homeostasis. Adv Exp Med Biol. (2017) 975 Pt 1:271–9. doi: 10.1007/978-94-024-1079-2_24,
24.Leão VF, Ferreira L, Melo CM, Bonfleur ML, da Silva LL, Carneiro EM, et al. Taurine supplementation prevents endothelial dysfunction and attenuates structural changes in aortas from hypothalamic obese rats. Eur J Nutr. (2019) 58:551–63. doi: 10.1007/s00394-018-1616-2,
25.Wang Z, Ohata Y, Watanabe Y, Yuan Y, Yoshii Y, Kondo Y, et al. Taurine improves lipid metabolism and increases resistance to oxidative stress. J Nutr Sci Vitaminol. (2020) 66:347–56. doi: 10.3177/jnsv.66.347,
26.Mock ED, Gagestein B, van der Stelt M. Anandamide and other N-acylethanolamines: a class of signaling lipids with therapeutic opportunities. Prog Lipid Res. (2023) 89:101194. doi: 10.1016/j.plipres.2022.101194,
27.Matias I, Gonthier MP, Orlando P, Martiadis V, De Petrocellis L, Cervino C, et al. Regulation, function, and dysregulation of endocannabinoids in models of adipose and beta-pancreatic cells and in obesity and hyperglycemia. J Clin Endocrinol Metab. (2006) 91:3171–80. doi: 10.1210/jc.2005-2679, 16684820
28.Cota D, Marsicano G, Tschöp M, Grübler Y, Flachskamm C, Schubert M, et al. The endogenous cannabinoid system affects energy balance via central orexigenic drive and peripheral lipogenesis. J Clin Invest. (2003) 112:423–31. doi: 10.1172/jci17725,
29.Matias I, Bisogno T, Di Marzo V. Endogenous cannabinoids in the brain and peripheral tissues: regulation of their levels and control of food intake. Int J Obes. (2006) 30 Suppl 1:S7–s12. doi: 10.1038/sj.ijo.0803271,
30.Fong TM, Guan XM, Marsh DJ, Shen CP, Stribling DS, Rosko KM, et al. Antiobesity efficacy of a novel cannabinoid-1 receptor inverse agonist, N-[(1S,2S)-3-(4-chlorophenyl)-2-(3-cyanophenyl)-1-methylpropyl]-2-methyl-2-[[5-(trifluoromethyl)pyridin-2-yl]oxy]propanamide (MK-0364), in rodents. J Pharmacol Exp Ther. (2007) 321:1013–22. doi: 10.1124/jpet.106.118737,
31.Gary-Bobo M, Elachouri G, Gallas JF, Janiak P, Marini P, Ravinet-Trillou C, et al. Rimonabant reduces obesity-associated hepatic steatosis and features of metabolic syndrome in obese Zucker fa/fa rats. Hepatology. (2007) 46:122–9. doi: 10.1002/hep.21641,
32.Tam J, Godlewski G, Earley BJ, Zhou L, Jourdan T, Szanda G, et al. Role of adiponectin in the metabolic effects of cannabinoid type 1 receptor blockade in mice with diet-induced obesity. Am J Physiol Endocrinol Metab. (2014) 306:E457–68. doi: 10.1152/ajpendo.00489.2013,
33.Bell-Anderson KS, Aouad L, Williams H, Sanz FR, Phuyal J, Larter CZ, et al. Coordinated improvement in glucose tolerance, liver steatosis and obesity-associated inflammation by cannabinoid 1 receptor antagonism in fat Aussie mice. Int J Obes. (2011) 35:1539–48. doi: 10.1038/ijo.2011.55,
34.Blüher M, Engeli S, Klöting N, Berndt J, Fasshauer M, Bátkai S, et al. Dysregulation of the peripheral and adipose tissue endocannabinoid system in human abdominal obesity. Diabetes. (2006) 55:3053–60. doi: 10.2337/db06-0812,
35.Fisk HL, Childs CE, Miles EA, Ayres R, Noakes PS, Paras-Chavez C, et al. Dysregulation of endocannabinoid concentrations in human subcutaneous adipose tissue in obesity and modulation by omega-3 polyunsaturated fatty acids. Clin Sci Lond. (2021) 135:185–200. doi: 10.1042/cs20201060,
36.Kuipers EN, Kantae V, Maarse BCE, van den Berg SM, van Eenige R, Nahon KJ, et al. High fat diet increases circulating endocannabinoids accompanied by increased synthesis enzymes in adipose tissue. Front Physiol. (2018) 9:1913. doi: 10.3389/fphys.2018.01913,
37.Simon V, Cota D. MECHANISMS IN ENDOCRINOLOGY: endocannabinoids and metabolism: past, present and future. Eur J Endocrinol. (2017) 176:R309–24. doi: 10.1530/eje-16-1044,
38.Engeli S, Böhnke J, Feldpausch M, Gorzelniak K, Janke J, Bátkai S, et al. Activation of the peripheral endocannabinoid system in human obesity. Diabetes. (2005) 54:2838–43. doi: 10.2337/diabetes.54.10.2838,
39.Côté M, Matias I, Lemieux I, Petrosino S, Alméras N, Després JP, et al. Circulating endocannabinoid levels, abdominal adiposity and related cardiometabolic risk factors in obese men. Int J Obes. (2007) 31:692–9. doi: 10.1038/sj.ijo.0803539,
40.Avalos B, Argueta DA, Perez PA, Wiley M, Wood C, DiPatrizio NV. Cannabinoid CB(1) receptors in the intestinal epithelium are required for acute Western-diet preferences in mice. Nutrients. (2020) 12:2874. doi: 10.3390/nu12092874,
41.Guo X, Ou T, Yang X, Song Q, Zhu L, Mi S, et al. Untargeted metabolomics based on ultra-high performance liquid chromatography-mass spectrometry/MS reveals the lipid-lowering mechanism of taurine in hyperlipidemia mice. Front Nutr. (2024) 11:1367589. doi: 10.3389/fnut.2024.1367589,
42.Pathmasiri W, Rushing BR, McRitchie S, Choudhari M, Du X, Smirnov A, et al. Untargeted metabolomics reveal signatures of a healthy lifestyle. Sci Rep. (2024) 14:13630. doi: 10.1038/s41598-024-64561-z,
43.Xu J, Li S, Jin Y, Yao H, Hu X, Cao S, et al. Network pharmacology combined with untargeted metabolomics reveals the intervention mechanism and compatibility of chenpi-rougui herb pair in nonalcoholic fatty liver disease. Front Mol Biosci. (2025) 12:1553162. doi: 10.3389/fmolb.2025.1553162,
44.Serefko A, Lachowicz-Radulska J, Jach ME, Świąder K, Szopa A. The endocannabinoid system in the development and treatment of obesity: searching for new ideas. Int J Mol Sci. (2025) 26:9549. doi: 10.3390/ijms26199549,
45.Rossi F, Punzo F, Umano GR, Argenziano M, Miraglia Del Giudice E. Role of cannabinoids in obesity. Int J Mol Sci. (2018) 19:2690. doi: 10.3390/ijms19092690,
46.Zhao Y, Ling F, Griffin TM, He T, Towner R, Ruan H, et al. Up-regulation of the Sirtuin 1 (Sirt1) and peroxisome proliferator-activated receptor γ coactivator-1α (PGC-1α) genes in white adipose tissue of Id1 protein-deficient mice: implications in the protection against diet and age-induced glucose intolerance. J Biol Chem. (2014) 289:29112–22. doi: 10.1074/jbc.M114.571679,
47.Liang H, Ward WF. PGC-1alpha: a key regulator of energy metabolism. Adv Physiol Educ. (2006) 30:145–51. doi: 10.1152/advan.00052.2006
48.Xu YJ, Arneja AS, Tappia PS, Dhalla NS. The potential health benefits of taurine in cardiovascular disease. Exp Clin Cardiol. (2008) 13:57–65. doi: 10.3969/j.issn.1008-6579.2007.03.004
49.Singh P, Gollapalli K, Mangiola S, Schranner D, Yusuf MA, Chamoli M, et al. Taurine deficiency as a driver of aging. Science. (2023) 380:eabn9257. doi: 10.1126/science.abn9257,
50.Avelino TM, Provencio MG, Peroni LA, Domingues RR, Torres FR, de Oliveira PSL, et al. Improving obesity research: unveiling metabolic pathways through a 3D in vitro model of adipocytes using 3T3-L1 cells. PLoS One. (2024) 19:e0303612. doi: 10.1371/journal.pone.0303612
51.Dyall SC. Interplay between n-3 and n-6 Long-chain polyunsaturated fatty acids and the endocannabinoid system in brain protection and repair. Lipids. (2017) 52:885–900. doi: 10.1007/s11745-017-4292-8,
52.Zheng D, Fan C, Zhu H, Jiang J, Qi K. Changes of plasma long-chain fatty acids in obese children. Chin J Child Health Care. (2007) 3:224–6. doi: 10.3969/j.issn.1008-6579.2007.03.004
53.Yumo L. Research of fatty acids in type 2 diabetes patients with metabolic-dysfunction-associated fatty liver. Dalian Medical University; (2021). doi: 10.26994/d.cnki.gdlyu.2021.000544
54.Cockcroft S. A retrospective on phosphatidylinositol transfer proteins (PITPs) – a fifty-year journey. Biochim Biophys Acta Mol Cell Biol Lipids. (2025) 1871:159714. doi: 10.1016/j.bbalip.2025.159714
55.Williams ES, Baylin A, Campos H. Adipose tissue arachidonic acid and the metabolic syndrome in Costa Rican adults. Clin Nutr. (2007) 26:474–82. doi: 10.1016/j.clnu.2007.03.004,
56.Rakotoarivelo V, Allam-Ndoul B, Martin C, Biertho L, Di Marzo V, Flamand N, et al. Investigating the alterations of endocannabinoidome signaling in the human small intestine in the context of obesity and type 2 diabetes. Heliyon. (2024) 10:e26968. doi: 10.1016/j.heliyon.2024.e26968,
57.Wood CP, Alvarez C, DiPatrizio NV. Cholinergic neurotransmission controls orexigenic endocannabinoid signaling in the gut in diet-induced obesity. J Neurosci. (2024) 44:e0813232024. doi: 10.1523/jneurosci.0813-23.2024
58.Jung KM, Lin L, Piomelli D. The endocannabinoid system in the adipose organ. Rev Endocr Metab Disord. (2022) 23:51–60. doi: 10.1007/s11154-020-09623-z,
59.Di Marzo V, Fontana A, Cadas H, Schinelli S, Cimino G, Schwartz JC, et al. Formation and inactivation of endogenous cannabinoid anandamide in central neurons. Nature. (1994) 372:686–91. doi: 10.1038/372686a0,
60.Murataeva N, Straiker A, Mackie K. Parsing the players: 2-arachidonoylglycerol synthesis and degradation in the CNS. Br J Pharmacol. (2014) 171:1379–91. doi: 10.1111/bph.12411,
61.Ruiz S, Vázquez F, Pellitero S, Puig-Domingo M. ENDOCRINE OBESITY: pituitary dysfunction in obesity. Eur J Endocrinol. (2022) 186:R79–r92. doi: 10.1530/eje-21-0899
62.Osei-Hyiaman D, DePetrillo M, Pacher P, Liu J, Radaeva S, Bátkai S, et al. Endocannabinoid activation at hepatic CB1 receptors stimulates fatty acid synthesis and contributes to diet-induced obesity. J Clin Invest. (2005) 115:1298–305. doi: 10.1172/jci23057,
63.Heifets BD, Castillo PE. Endocannabinoid signaling and long-term synaptic plasticity. Annu Rev Physiol. (2009) 71:283–306. doi: 10.1146/annurev.physiol.010908.163149,
64.Rouzer CA, Marnett LJ. Endocannabinoid oxygenation by cyclooxygenases, lipoxygenases, and cytochromes P450: cross-talk between the eicosanoid and endocannabinoid signaling pathways. Chem Rev. (2011) 111:5899–921. doi: 10.1021/cr2002799,
65.Yoon S, Myczek K, Penzes P. cAMP signaling-mediated phosphorylation of Diacylglycerol lipase α regulates interaction with Ankyrin-G and dendritic spine morphology. Biol Psychiatry. (2021) 90:263–74. doi: 10.1016/j.biopsych.2021.03.023,
66.Pagano Zottola AC, Severi I, Cannich A, Ciofi P, Cota D, Marsicano G, et al. Expression of functional cannabinoid type-1 (CB(1)) receptor in mitochondria of white adipocytes. Cells. (2022) 11:2582. doi: 10.3390/cells11162582,
67.Darling JC, Rudolf MCJ, Rubino F, Greenough A. Tackling obesity while preventing obesity stigma. Arch Dis Child. (2024) 110:8–11. doi: 10.1136/archdischild-2023-325894,
68.O'Sullivan SE, Yates AS, Porter RK. The peripheral cannabinoid receptor type 1 (CB(1)) as a molecular target for modulating body weight in man. Molecules. (2021) 26:6178. doi: 10.3390/molecules26206178,
69.Rohbeck E, Eckel J, Romacho T. Cannabinoid receptors in metabolic regulation and diabetes. Physiology. (2021) 36:102–13. doi: 10.1152/physiol.00029.2020,
70.Burstein S. PPAR-gamma: a nuclear receptor with affinity for cannabinoids. Life Sci. (2005) 77:1674–84. doi: 10.1016/j.lfs.2005.05.039,
71.Bazwinsky-Wutschke I, Zipprich A, Dehghani F. Endocannabinoid system in hepatic glucose metabolism, fatty liver disease, and cirrhosis. Int J Mol Sci. (2019) 20:2516. doi: 10.3390/ijms20102516,
72.Yan W, Kan X, Wang Y, Zhang Y. Expression of key genes involved in lipid deposition in intramuscular adipocytes of sheep under high glucose conditions. J Anim Physiol Anim Nutr. (2023) 107:444–52. doi: 10.1111/jpn.13750,
73.Jiang LS, Pu J, Han ZH, Hu LH, He B. Role of activated endocannabinoid system in regulation of cellular cholesterol metabolism in macrophages. Cardiovasc Res. (2009) 81:805–13. doi: 10.1093/cvr/cvn344,
74.Roberto V, Claudio P, Catia P, Alessandra C, Riccardo U, Marco R, et al. Activation of the endogenous cannabinoid system stimulates ADIPOGENESIS in human adipose tissue. Eur J Intern Med. (2008) 19:S45–S. doi: 10.1016/s0953-6205(08)60148-x
75.Xiao Y, Yang M, Cai M, Zhang H, Hu K, Duan Y. EGCG and taurine synergistically ameliorate lipid metabolism disorder by modulating gut microbiota and PPARα/FAS signaling pathway. Nutrients. (2025) 17:2595. doi: 10.3390/nu17162595,
76.Yang Q, Sun S, Liu W, Liu Q, Wang J. Hypoxia training improves hepatic steatosis partly by downregulation of CB1 receptor in obese mice. Biochem Biophys Res Commun. (2020) 525:639–45. doi: 10.1016/j.bbrc.2020.02.134,
77.Liu R, Liu X, Bai X, Xiao C, Dong Y. A study of the regulatory mechanism of the CB1/PPARγ2/PLIN1/HSL pathway for fat metabolism in cattle. Front Genet. (2021) 12:631187. doi: 10.3389/fgene.2021.631187,
78.Howlett AC, Abood ME. CB(1) and CB(2) receptor pharmacology. Adv Pharmacol. (2017) 80:169–206. doi: 10.1016/bs.apha.2017.03.007,
79.Yang JS, Tongson J, Kim KH, Park Y. Piceatannol attenuates fat accumulation and oxidative stress in steatosis-induced HepG2 cells. Curr Res Food Sci. (2020) 3:92–9. doi: 10.1016/j.crfs.2020.03.008,
80.Kim JB, Wright HM, Wright M, Spiegelman BM. ADD1/SREBP1 activates PPAR gamma through the production of endogenous ligand. Proc Natl Acad Sci USA. (1998) 95:4333–7. doi: 10.1073/pnas.95.8.4333,
81.Miao Y, Zhang C, Yang L, Zeng X, Hu Y, Xue X, et al. The activation of PPARγ enhances Treg responses through up-regulating CD36/CPT1-mediated fatty acid oxidation and subsequent N-glycan branching of TβRII/IL-2Rα. Cell Commun Signal. (2022) 20:48. doi: 10.1186/s12964-022-00849-9,
82.Zeng S, Wu F, Chen M, Li Y, You M, Zhang Y, et al. Inhibition of fatty acid translocase (FAT/CD36) Palmitoylation enhances hepatic fatty acid β-oxidation by increasing its localization to mitochondria and interaction with Long-chain acyl-CoA Synthetase 1. Antioxid Redox Signal. (2022) 36:1081–100. doi: 10.1089/ars.2021.0157,
83.Olivecrona G. The crucial role of ATGL for energy supply of muscles. J Lipid Res. (2010) 51:449–50. doi: 10.1194/jlr.E004770,
84.Lefevre C, Thibaut MM, Loumaye A, Thissen JP, Neyrinck AM, Navez B, et al. Tumoral acidosis promotes adipose tissue depletion by fostering adipocyte lipolysis. Mol Metab. (2024) 83:101930. doi: 10.1016/j.molmet.2024.101930,

Associated Data

Supplementary Materials

Data Availability Statement

The datasets for this study can be found in the Figshare repository (https://doi.org/10.6084/m9.figshare.31007782).

Studies

Conditions

Cannabinoids and active compounds

Additional materials

Abstract

Introduction

Methods

Results

Conclusion

Untitled section

Graphical abstract

Article notes

Untitled section

Author notes

1.Introduction

2.Materials and methods

2.1.Chemicals and assay kits

2.2.Animal experiment

2.3.Metabolomics sample preparation

2.4.UPLC-MS conditions

2.5.Multivariate statistical analysis and identification of potential differential metabolites

2.6.Pathway analysis

2.7.Culture of 3T3-L1 preadipocytes

2.8.Spheroid fabrication

2.9.Adipogenic differentiation of spheroids

2.10.Lipid morphology

2.11.TG level determination

2.12.Gene expression

2.13.Statistical analysis

3.Results

3.1.Taurine ameliorates obesity-related metabolic dysregulation and adipose tissue expansion

3.2.Taurine lowers endocannabinoid precursors in adipose tissue of obese mice

3.2.1.Comprehensive quality control and metabolic feature profiling

3.2.2.Multivariate statistical analysis reveals altered metabolic profiles

3.2.3.Screening and characterization of differential metabolites

3.2.4.Classification of differential metabolites

3.2.5.Identification of common altered metabolites

3.2.6.Pathway enrichment analysis

3.3.Taurine attenuates lipid accumulation in differentiating 3T3-L1 spheroids via CB1 regulation

3.4.Taurine regulates mRNA expression of adipogenic and lipolysis-related factors by inhibiting CB1

4.Discussion

5.Conclusion

Acknowledgments

Glossary

Funding Statement

Footnotes

Footnote Group

Data availability statement

Ethics statement

Author contributions

Conflict of interest

Generative AI statement

Publisher’s note

Supplementary material

References

Untitled section

References

Associated Data

Supplementary Materials

Data Availability Statement