1. Academic Validation
  2. Puerarin mitigates tumor necrosis factor-nuclear factor-κB axis-driven macrophage inflammation and atherogenesis: Integrative network pharmacology and experimental validation

Puerarin mitigates tumor necrosis factor-nuclear factor-κB axis-driven macrophage inflammation and atherogenesis: Integrative network pharmacology and experimental validation

  • Phytomedicine. 2026 May:154:158025. doi: 10.1016/j.phymed.2026.158025.
Hailun Yao 1 Yao Zhang 2 Lizhong Lin 2 Shenhui Yang 3 Dexiang Chen 4 Lu He 5 Wu Jian 6
Affiliations

Affiliations

  • 1 Changde Hospital, Xiangya School of Medicine, Central South University (The First People's Hospital of Changde City), Changde, Hunan, 415003, China; Hunan Polytechnic of Environment and Biology, Hengyang, Hunan, 421001, China.
  • 2 Changde Hospital, Xiangya School of Medicine, Central South University (The First People's Hospital of Changde City), Changde, Hunan, 415003, China.
  • 3 Hunan Polytechnic of Environment and Biology, Hengyang, Hunan, 421001, China.
  • 4 Changde Hospital, Xiangya School of Medicine, Central South University (The First People's Hospital of Changde City), Changde, Hunan, 415003, China. Electronic address: [email protected].
  • 5 The First Affiliated Hospital, Department of Neurosurgery, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China. Electronic address: [email protected].
  • 6 Changde Hospital, Xiangya School of Medicine, Central South University (The First People's Hospital of Changde City), Changde, Hunan, 415003, China. Electronic address: [email protected].
Abstract

Background: Atherosclerosis (AS) is a chronic inflammatory disease that constitutes the primary pathological basis of cardiovascular disorders. Although the natural isoflavone C-glycoside puerarin (PU) has demonstrated promising anti-atherosclerotic effects, its underlying molecular mechanisms remain incompletely elucidated. In this study, we aimed to systematically characterize the pharmacological actions and mechanistic basis of PU in AS by integrating network pharmacology analyses with experimental validation.

Methods: Potential targets of PU were identified by integrating network pharmacology databases and intersecting them with AS-related genes. Protein-protein interaction analysis, functional enrichment, and machine-learning-based screening were subsequently performed to identify key regulatory targets. Molecular docking and molecular dynamics simulations were then conducted to evaluate the feasibility and stability of PU-target interactions. In addition, single-cell transcriptomic and immune infiltration analyses were used to determine the cellular localization and inflammatory relevance of the core targets. Finally, a high-fat diet (HFD)-induced apoE-/- mouse model, together with in vivo and in vitro experiments, was employed for mechanistic validation.

Results: This integrative analysis identified 56 potential PU-AS-related targets, among which TNF, NFKBIA, STAT3, Src, and PTGS2 emerged as central hub genes. Notably, TNF was consistently highlighted as a key regulatory target across differential expression analysis, molecular docking, and molecular dynamics simulations. Single-cell transcriptomic and immune infiltration analyses further revealed that TNF was predominantly expressed in macrophages and related immune cell subsets. Experimental validation demonstrated that PU treatment significantly attenuated inflammatory responses, reduced aortic plaque burden, enhanced plaque stability, and suppressed macrophage infiltration in HFD-induced apoE-/- mice. At the cellular level, PU markedly inhibited NF-κB activation in macrophages and reduced the levels of pro-inflammatory cytokines, including IL-6 and IL-1β.

Conclusions: PU ameliorates atherogenesis by suppressing TNF-NF-κB-mediated inflammatory responses. These findings identify the TNF-NF-κB axis as a key mechanistic pathway underlying the anti-atherosclerotic effects of PU and support its potential as a natural product-based therapeutic strategy for Cardiovascular Disease.

Keywords

Puerarin, Atherosclerosis, TNF–NF-κB signaling pathway, Machine learning, Single-cell RNA sequencing, Inflammation.

Figures
Products