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<p>Epigallocatechin-3-gallate (EGCG), a bioactive ingredient extracted in large amounts from green tea, is worthy of consideration for the prevention of renal injury. Nevertheless, there is a paucity of comprehensive and rigorous preclinical evidence to substantiate the therapeutic efficacy of EGCG in renal injury. To assess the therapeutic effect and potential mechanism of EGCG in rodent models of renal injury for future clinical research by meta-analysis and machine learning, a systematic search of preclinical rodent studies published before April 2, 2024, was conducted using four databases. Meta-analyses were performed on a variety of indicators, utilizing the STATA software. Additionally, a machine learning model was constructed using the Python software, which in turn predicted the relationship between the dosage and efficacy of EGCG in renal injury. Thirty-seven studies and 726 animals were included in the analysis. The findings suggest that EGCG can ameliorate kidney functional parameters in animals. This paper presents preliminary evidence indicating that consumption of EGCG may result in a statistically significant reduction in Scr, BUN, and urine protein levels while simultaneously increasing CCr. Moreover, EGCG can improve renal injury, which is highly correlated with the systemic regulation of multiple phenotypes. The results of machine learning analyses indicated a modest correlation between EGCG dosage and efficacy, with optimal dosages ranging from 94.25 to 107.76&#xa0;mg/kg/d. With regard to potential mechanisms for the treatment of renal injury, EGCG exerted the renoprotective properties possibly through Nrf2/ heme oxygenase-1, HIF-1α/ANGPTL4, Tgf-β1/Smad, Mapk, Erk, Tnf-α, Nf-κb, Nlrp3/Il-1β, and 67 kD laminin receptor pathways.</p> Graphical abstract <p></p>

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Quantitative analysis of epigallocatechin-3-gallate in treating renal injury via meta-analysis and machine learning

  • 期刊论文

  • 发表日期：

    2025年1月24日

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  • Jie Chen,
  • Jinna Tian,
  • Yuanhao Zhang,
  • Zexin Wang,
  • MaoYuan Zhao,
  • Cui Guo,
  • Jia Ma,
  • Hebin Zhang,
  • Jijun Zheng,
  • Xiao Ma,
  • Yueqiang Wen,
  • Jinhao Zeng,
  • Thomas Efferth

摘要

Epigallocatechin-3-gallate (EGCG), a bioactive ingredient extracted in large amounts from green tea, is worthy of consideration for the prevention of renal injury. Nevertheless, there is a paucity of comprehensive and rigorous preclinical evidence to substantiate the therapeutic efficacy of EGCG in renal injury. To assess the therapeutic effect and potential mechanism of EGCG in rodent models of renal injury for future clinical research by meta-analysis and machine learning, a systematic search of preclinical rodent studies published before April 2, 2024, was conducted using four databases. Meta-analyses were performed on a variety of indicators, utilizing the STATA software. Additionally, a machine learning model was constructed using the Python software, which in turn predicted the relationship between the dosage and efficacy of EGCG in renal injury. Thirty-seven studies and 726 animals were included in the analysis. The findings suggest that EGCG can ameliorate kidney functional parameters in animals. This paper presents preliminary evidence indicating that consumption of EGCG may result in a statistically significant reduction in Scr, BUN, and urine protein levels while simultaneously increasing CCr. Moreover, EGCG can improve renal injury, which is highly correlated with the systemic regulation of multiple phenotypes. The results of machine learning analyses indicated a modest correlation between EGCG dosage and efficacy, with optimal dosages ranging from 94.25 to 107.76 mg/kg/d. With regard to potential mechanisms for the treatment of renal injury, EGCG exerted the renoprotective properties possibly through Nrf2/ heme oxygenase-1, HIF-1α/ANGPTL4, Tgf-β1/Smad, Mapk, Erk, Tnf-α, Nf-κb, Nlrp3/Il-1β, and 67 kD laminin receptor pathways.

Graphical abstract