PMID- 37089916
OWN - NLM
STAT- PubMed-not-MEDLINE
LR  - 20230425
IS  - 1663-9812 (Print)
IS  - 1663-9812 (Electronic)
IS  - 1663-9812 (Linking)
VI  - 14
DP  - 2023
TI  - Effect of botanical drugs in improving symptoms of hypertensive nephropathy: 
      Analysis of real-world data, retrospective cohort, network, and experimental 
      assessment.
PG  - 1126972
LID - 10.3389/fphar.2023.1126972 [doi]
LID - 1126972
AB  - Background/aim: Hypertensive nephropathy (HN) is a common complication of 
      hypertension. Traditional Chinese medicine has long been used in the clinical 
      treatment of Hypertensive nephropathy. However, botanical drug prescriptions have 
      not been summarized. The purpose of this study is to develop a prescription for 
      improving hypertensive nephropathy, explore the evidence related to clinical 
      application of the prescription, and verify its molecular mechanism of action. 
      Methods: In this study, based on the electronic medical record data on 
      Hypertensive nephropathy, the core botanical drugs and patients' symptoms were 
      mined using the hierarchical network extraction and fast unfolding algorithm, and 
      the protein interaction network between botanical drugs and Hypertensive 
      nephropathy was established. The K-nearest neighbors (KNN) model was used to 
      analyze the clinical and biological characteristics of botanical drug compounds 
      to determine the effective compounds. Hierarchical clustering was used to screen 
      for effective botanical drugs. The clinical efficacy of botanical drugs was 
      verified by a retrospective cohort. Animal experiments were performed at the 
      target and pathway levels to analyze the mechanism. Results: A total of 14 
      botanical drugs and five symptom communities were obtained from real-world 
      clinical data. In total, 76 effective compounds were obtained using the K-nearest 
      neighbors model, and seven botanical drugs were identified as Gao Shen Formula by 
      hierarchical clustering. Compared with the classical model, the Area under the 
      curve (AUC) value of the K-nearest neighbors model was the best; retrospective 
      cohort verification showed that Gao Shen Formula reduced serum creatinine levels 
      and Chronic kidney disease (CKD) stage [OR = 2.561, 95% CI (1.025-6.406), p < 
      0.05]. With respect to target and pathway enrichment, Gao Shen Formula acts on 
      inflammatory factors such as TNF-alpha, IL-1beta, and IL-6 and regulates the NF-kappaB 
      signaling pathway and downstream glucose and lipid metabolic pathways. 
      Conclusion: In the retrospective cohort, we observed that the clinical 
      application of Gao Shen Formula alleviates the decrease in renal function in 
      patients with hypertensive nephropathy. It is speculated that Gao Shen Formula 
      acts by reducing inflammatory reactions, inhibiting renal damage caused by 
      excessive activation of the renin-angiotensin-aldosterone system, and regulating 
      energy metabolism.
CI  - Copyright (c) 2023 Huan, Ma, Li, Hu, Chen, Wang, Su, Su and Wang.
FAU - Huan, Jia-Ming
AU  - Huan JM
AD  - School of Traditional Chinese Medicine, Shandong University of Traditional 
      Chinese Medicine, Jinan, China.
FAU - Ma, Xi-Ting
AU  - Ma XT
AD  - School of Chinese Medicine, Hong Kong Baptist University, Kowloon, Hong Kong 
      SAR,China.
FAU - Li, Si-Yi
AU  - Li SY
AD  - School of Traditional Chinese Medicine, Shandong University of Traditional 
      Chinese Medicine, Jinan, China.
FAU - Hu, Dong-Qing
AU  - Hu DQ
AD  - Medical Services Section, Affiliated Hospital of Shandong University of 
      Traditional Chinese Medicine, Jinan, China.
FAU - Chen, Hao-Yu
AU  - Chen HY
AD  - Department of Cardiovascular, Affiliated Hospital of Shandong University of 
      Traditional Chinese Medicine, Jinan, China.
FAU - Wang, Yi-Min
AU  - Wang YM
AD  - School of Traditional Chinese Medicine, Shandong University of Traditional 
      Chinese Medicine, Jinan, China.
FAU - Su, Xiao-Yi
AU  - Su XY
AD  - School of Traditional Chinese Medicine, Shandong University of Traditional 
      Chinese Medicine, Jinan, China.
FAU - Su, Wen-Ge
AU  - Su WG
AD  - Department of Cardiovascular, Affiliated Hospital of Shandong University of 
      Traditional Chinese Medicine, Jinan, China.
FAU - Wang, Yi-Fei
AU  - Wang YF
AD  - Department of Cardiovascular, Affiliated Hospital of Shandong University of 
      Traditional Chinese Medicine, Jinan, China.
LA  - eng
PT  - Journal Article
DEP - 20230404
PL  - Switzerland
TA  - Front Pharmacol
JT  - Frontiers in pharmacology
JID - 101548923
PMC - PMC10113664
OTO - NOTNLM
OT  - NF-kappaB signal pathway
OT  - clinical decision support
OT  - hypertensive nephropathy
OT  - machine learning
OT  - real-world data
COIS- The authors declare that the research was conducted in the absence of any 
      commercial or financial relationships that could be construed as a potential 
      conflict of interest.
EDAT- 2023/04/24 06:42
MHDA- 2023/04/24 06:43
PMCR- 2023/04/04
CRDT- 2023/04/24 03:35
PHST- 2022/12/18 00:00 [received]
PHST- 2023/03/13 00:00 [accepted]
PHST- 2023/04/24 06:43 [medline]
PHST- 2023/04/24 06:42 [pubmed]
PHST- 2023/04/24 03:35 [entrez]
PHST- 2023/04/04 00:00 [pmc-release]
AID - 1126972 [pii]
AID - 10.3389/fphar.2023.1126972 [doi]
PST - epublish
SO  - Front Pharmacol. 2023 Apr 4;14:1126972. doi: 10.3389/fphar.2023.1126972. 
      eCollection 2023.