Abstract
Squalene is known for its antioxidant and lipid-lowering effects, and some studies have suggested its antidiabetic potential. This study evaluated the effects of squalene in rats with alloxan-induced type 1 diabetes. Twenty-four rats were divided into four groups: healthy control, alloxan control, and two treatment groups receiving squalene at 100 mg/kg and 200 mg/kg for 30 days. Blood glucose, HbA1c, insulin, lipid profile, kidney function (creatinine), liver glycogen, antioxidant markers (malondialdehyde, superoxide dismutase, glutathione), and pro-inflammatory cytokines (IL-1β, IL-6, TNF-α) were measured. Squalene improved blood glucose control, insulin levels, and lipid profile. It also restored liver glycogen, reduced oxidative stress, and lowered inflammation markers. These effects were more prominent at the higher dose. In addition, network pharmacology and molecular docking analyses identified relevant targets involved in glucose regulation, lipid metabolism, and immune signaling. Squalene showed favorable binding interactions with key proteins such as IL1R1 and SQLE, supporting its role in modulating both inflammatory and metabolic pathways. Squalene showed beneficial effects in diabetic rats by improving metabolic, antioxidant, and inflammatory parameters. These results suggest that squalene may be a useful compound for supporting diabetes management, and further studies are needed to explore its potential.
Data availability
All data generated or analysed during this study are included in this published article and its supplementary information files. Protein structures used for molecular docking were obtained from the Protein Data Bank (PDB), and target information was retrieved from publicly available databases such as UniProt. No new protein sequences, gene expression datasets, or macromolecular structures were generated during this study.
References
Antar, S. A. et al. Diabetes mellitus: Classification, mediators, and complications; A gate to identify potential targets for the development of new effective treatments. Biomed. Pharmacother. 168, 115734 (2023).
Yang, T. et al. An update on chronic complications of diabetes mellitus: from molecular mechanisms to therapeutic strategies with a focus on metabolic memory. Mol. Med. 30, 1–19 (2024).
Usman, M. S., Khan, M. S. & Butler, J. The Interplay Between Diabetes, Cardiovascular Disease, and Kidney Disease. Compendia 2021, 13–18 (2021).
Rao, G. H. R. Cardiometabolic diseases: risk factors and novel approaches for the management of risks. Cardiometabolic Dis. 3–26. https://doi.org/10.1016/B978-0-323-95469-3.00022-X (2025).
Caturano, A. et al. Oxidative Stress and Cardiovascular Complications in Type 2 Diabetes: From Pathophysiology to Lifestyle Modifications. Antioxidants 14, (2025).
Islam, K. et al. Diabetes mellitus and associated vascular disease: Pathogenesis, Complications, and evolving treatments. Adv. Ther. 42, 2659–2678 (2025).
Guo, H., Wu, H. & Li, Z. The pathogenesis of diabetes. Int. J. Mol. Sci. 24, 6978 (2023).
Iheagwam, F. N. & Iheagwam, O. T. Diabetes mellitus: the pathophysiology as a canvas for management Elucidation and strategies. Med. Nov Technol. Devices. 25, 100351 (2025).
Lima, J. E. B. F., Moreira, N. C. S. & Sakamoto-Hojo, E. T. Mechanisms underlying the pathophysiology of type 2 diabetes: from risk factors to oxidative stress, metabolic dysfunction, and hyperglycemia. Mutat. Res. Toxicol. Environ. Mutagen. 874–875, 503437 (2022).
Association, A. D. 2. Classification and diagnosis of diabetes: standards of medical care in Diabetes-2021. Diabetes Care. 44, S15–S33 (2021).
Sami, A. et al. Genetics of diabetes and its complications: a comprehensive review. Diabetol. Metab. Syndr. 17, 1–21 (2025).
Westman, E. C. Type 2 diabetes mellitus: A pathophysiologic perspective. Front. Nutr. 8, 707371 (2021).
Redondo, M. J. & Morgan, N. G. Heterogeneity and endotypes in type 1 diabetes mellitus. Nat. Rev. Endocrinol. 19, 542–554 (2023).
Tan, S. Y. et al. Type 1 and 2 diabetes mellitus: A review on current treatment approach and gene therapy as potential intervention. Diabetes Metab. Syndr. Clin. Res. Rev. 13, 364–372 (2019).
Shahzad, A. et al. Integrated in vitro, in silico, and in vivo approaches to elucidate the antidiabetic mechanisms of Cicer arietinum and hordeum vulgare extract and secondary metabolites. Sci. Rep. 15, 1–26 (2025).
Saini, T. et al. Role of bioactive phytochemicals in plant seeds and leaves for diabetes control and prevention: a comprehensive review. Phytochem Rev. 2025, 1–26. https://doi.org/10.1007/S11101-025-10065-1 (2025).
Lozano-Grande, M. A., Gorinstein, S., Espitia-Rangel, E., Dávila-Ortiz, G. & Martínez-Ayala, A. L. Plant Sources, Extraction Methods, and Uses of Squalene. Int. J. Agron. 2018, 1829160 (2018).
Cheng, L., Ji, T., Zhang, M. & Fang, B. Recent advances in squalene: biological activities, sources, extraction, and delivery systems. Trends Food Sci. Technol. 146, 104392 (2024).
Ibrahim, N. I. & Mohamed, I. N. Interdependence of anti-inflammatory and antioxidant properties of squalene–implication for cardiovascular health. Life 11, 1–19 (2021).
Widyawati, T., Syahputra, R. A., Syarifah, S. & Sumantri, I. B. Analysis of antidiabetic activity of squalene via in Silico and in vivo assay. Mol 28, 3783 (2023).
Marino, F. et al. Streptozotocin-induced type 1 and 2 diabetes mellitus mouse models show different functional, cellular and molecular patterns of diabetic cardiomyopathy. International Journal of Molecular Sciences 24, 1132 (2023).
Athmuri, D. N. & Shiekh, P. A. Experimental diabetic animal models to study diabetes and diabetic complications. MethodsX 11, 102474 (2023).
Matsuura, Y. et al. Altered glucose metabolism and hypoxic response in alloxan-induced diabetic atherosclerosis in rabbits. PLoS One. 12, e0175976 (2017).
Kottaisamy, C. P. D., Raj, D. S., Kumar, P., Sankaran, U. & V. & Experimental animal models for diabetes and its related complications-a review. Lab. Anim. Res. 37, 1–14 (2021).
Zou, Y., Zhang, H., Bi, F., Tang, Q. & Xu, H. Targeting the key cholesterol biosynthesis enzyme squalene monooxygenasefor cancer therapy. Frontiers in Oncology 12, 938502 (2022)
Zhukova, J. V., Lopatnikova, J. A., Alshevskaya, A. A. & Sennikov, S. V. Molecular mechanisms of regulation of IL-1 and its receptors. Cytokine Growth Factor. Rev. 80, 59–71 (2024).
Yamashita, A. et al. Alteration of Glycolysis Metabolite Levels and Impaired Hypoxic Response in Diabetic Atherosclerosis. Arteriosclerosis, Thrombosis, and Vascular Biology 37, A550-A550 (2017).
Matsuda, M., Komiyama, Y., Suzuki, T. & Moriyama, M. Effect of rapid centrifugation using high centrifugal force on procoagulant activity in plasma samples. Clin. Lab. 68, 2422–2427 (2022).
Soni, L. K. et al. In vitro and in vivo antidiabetic activity of isolated fraction of prosopis cineraria against streptozotocin-induced experimental diabetes: A mechanistic study. Biomed. Pharmacother. 108, 1015–1021 (2018).
Senthilkumar, M., Amaresan, N. & Sankaranarayanan, A. Estimation of superoxide dismutase (SOD). 117–118 (2021). https://doi.org/10.1007/978-1-0716-1080-0_29
Yuan, L. et al. A rapid colorimetric method for determining glutathione based on the reaction between Cobalt oxyhydroxide nanosheets and 3,3′,5,5′-Tetramethylbenzidine. Microchem J. 160, 105639 (2021).
Akbari, B., Najafi, F., Bahmaei, M., Mahmoodi, N. M. & Sherman, J. H. Modeling and optimization of malondialdehyde (MDA) absorbance behavior through response surface methodology (RSM) and artificial intelligence network (AIN): an endeavor to estimate lipid peroxidation by determination of MDA. J. Chemom. 37, e3468 (2023).
Madiraju, C. et al. A unique multiplex ELISA to profile growth factors and cytokines in cerebrospinal fluid. Methods Mol. Biol. 2612, 157–168 (2023).
Szklarczyk, D. et al. STITCH 5: augmenting protein-chemical interaction networks with tissue and affinity data. Nucleic Acids Res. 44, D380–D384 (2016).
Amberger, J. S., Bocchini, C. A., Scott, A. F. & Hamosh, A. OMIM.org: leveraging knowledge across phenotype–gene relationships. Nucleic Acids Res. 47, D1038 (2018).
Stelzer, G. et al. The GeneCards suite: From gene data mining to disease genome sequence analyses. Curr. Protoc. Bioinforma. 2016, 1.30.1–1.30.33 (2016).
Szklarczyk, D. et al. The STRING database in 2021: customizable protein-protein networks, and functional characterization of user-uploaded gene/measurement sets. Nucleic Acids Res. 49, D605–D612 (2021).
Zhou, Y. et al. Metascape provides a biologist-oriented resource for the analysis of systems-level datasets. Nat. Commun. 10, 1–10 (2019).
Kanehisa, M., Sato, Y., Kawashima, M., Furumichi, M. & Tanabe, M. KEGG as a reference resource for gene and protein annotation. Nucleic Acids Res. 44, D457–D462 (2016).
Kanehisa, M., Furumichi, M., Sato, Y., Matsuura, Y. & Ishiguro-Watanabe, M. KEGG: biological systems database as a model of the real world. Nucleic Acids Res. 53, D672–D677 (2025).
Vigers, G. P. A., Anderson, L. J., Caffes, P. & Brandhuber, B. J. Crystal structure of the type-I interleukin-1 receptor complexed with interleukin-1β. Nature 386, 190–194 (1997).
Padyana, A. K. et al. Structure and Inhibition mechanism of the catalytic domain of human squalene epoxidase. Nat. Commun. 10, 1–10 (2019).
Eberhardt, J., Santos-Martins, D., Tillack, A. F., Forli, S. & Bindings, P. AutoDock Vina 1.2.0: New Docking Methods, Expanded Force Field, and J. Chem. Inf. Model. 61, 3891–3898 (2021).
Kohli, K., Pillarisetty, V. G. & Kim, T. S. Key chemokines direct migration of immune cells in solid tumors. Cancer Gene Ther. 29, 10–21 (2021).
Picón, D. F. & Skouta, R. Unveiling the therapeutic potential of squalene synthase: Deciphering its biochemical Mechanism, disease Implications, and intriguing ties to ferroptosis. Cancers (Basel). 15, 3731 (2023).
Bansode, T., Salalkar, B., Dighe, P., Nirmal, S. & Dighe, S. Comparative evaluation of antidiabetic potential of partially purified bioactive fractions from four medicinal plants in alloxan-induced diabetic rats. Ayu 38, 165 (2017).
Belhadj, S. et al. Metabolic impairments and tissue disorders in alloxan-induced diabetic rats are alleviated by salvia officinalis L. essential oil. Biomed. Pharmacother. 108, 985–995 (2018).
Gu, Y. et al. Combinatorial metabolic engineering of Saccharomyces cerevisiae for improved production of 7-dehydrocholesterol. Eng. Microbiol. 3, 100100 (2023).
Besnard, T. et al. Biallelic pathogenic variants in the lanosterol synthase gene LSS involved in the cholesterol biosynthesis cause alopecia with intellectual disability, a rare recessive neuroectodermal syndrome. Genet. Med. 21, 2025–2035 (2019).
Zhou, Y. et al. Post-translational switch of DHCR24 acetylation sustains sterol synthesis and promotes HCC via the 7-ketocholesterol/p62 axis. Cell. Rep. 44, 116640 (2025).
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Conceptualization: AIO, FRJMethodology (in vivo & biochemical assays): FRJ, ESN, AIOInvestigation (animal work, sample collection, assays): FRJ, ESNNetwork pharmacology & molecular docking: AA, HA, AIOFormal analysis & statistics: AIO, ESNData curation: FRJ, ESN, AAVisualization: AA, AIOWriting – original draft: AIO, FRJ, EMA, Writing – review & editing: AIO, HA, AA, ESN.
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Jaafar, F.R., Nassir, E.S., Oraibi, A.I. et al. Network and molecular insights into the antidiabetic potential of squalene in alloxan-induced diabetes. Sci Rep (2026). https://doi.org/10.1038/s41598-026-38233-z
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DOI: https://doi.org/10.1038/s41598-026-38233-z