This study analyzed the molecular mechanism of Huangjing Qianshi Decoction(HQD) in the treatment of prediabetes based on network pharmacology and molecular docking. The active components of HQD were identified and screened based on Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform(TCMSP, http://Lsp.nwu.edu.cn/tcmsp.php) and then the targets of the components and the genes related to prediabetes were retrieved, followed by identifying the common targets of the decoction and the disease. The medicinal component-target network was constructed by Cytoscape to screen key components. The protein-protein interaction(PPI) network was established by STRING and hub genes were identified by Cytoscape-CytoNCA, followed by Gene Ontology(GO) term enrichment and Kyoto Encyclopedia of Genes and Genomes(KEGG) of the hub genes with R-clusterProfi-ler. Thereby, the possible signaling pathways were predicted and the molecular mechanism was deduced. A total of 79 active components of HQD and 785 diabetes-related targets of the components were screened out. The hub genes mainly involved the GO terms of tricarboxylic acid cycle, peptide binding, amide binding, hydrolase activity, and kinase activity regulation, and the KEGG pathways of AGE-RAGE signaling pathway, TNF signaling pathway, AMPK signaling pathway, IL-17 signaling pathway, and insulin signaling pathway. Western blot result showed that HQD-containing serum significantly reduced the expression of AKT1, AGE, and RAGE proteins in insulin resistance model cells. HQD's treatment of prediabetes is characterized by multiple pathways, multiple targets, and multiple levels. The main mechanism is that the components zhonghualiaoine, baicalein, kaempferol, and luteolin act on AKT1 and inhibit the AGE-RAGE axis.
Drugs, Chinese Herbal/pharmacology* ; Humans ; Medicine, Chinese Traditional ; Molecular Docking Simulation ; Network Pharmacology ; Prediabetic State/genetics*

BACKGROUNDPrediabetes is an early stage of β-cell dysfunction presenting as insulin resistance. Evidences suggest that endoplasmic reticulum (ER) stress is involved in the pathogenesis of type 2 diabetes mellitus and prediabetes. In a Chinese population with prediabetes, we investigated single nucleotide polymorphisms (SNPs) in the genes of PERK, JNK, XBP1, BIP and CHOP which encode molecular proteins involved in ER stress pathways.

METHODSNine SNPs at the PERK, JNK, XBP1, BIP and CHOP loci were genotyped by mass spectrometry in 1 448 unrelated individuals. By using a 75 g oral glucose tolerance test (OGTT), 828 subjects were diagnosed as prediabetes and 620 subjects aged 55 years and over as normal controls based on WHO diagnostic criteria (1999) for diabetes mellitus.

RESULTSThe allele C of SNP rs867529 at PERK locus was a risk factor for prediabetes, with the carriers of C allele genotype at a higher risk of prediabetes compared to non-carriers (OR = 1.279, 95% CI: 1.013-1.614, P = 0.039, after adjustment for age, sex and body mass index (BMI). The SNPs rs6750998 at PERK locus was associated with homeostasis model assessments of insulin resistance (HOMA-IR) (P = 0.019), and rs17037621 with BMI (P = 0.044). The allele G of SNP rs10986663 in BIP gene was associated with a decreased risk of prediabetes (OR = 0.699, 95% CI: 0.539-0.907, P = 0.007). The SNP rs2076431 in JNK gene was associated with fasting plasma glucose levels (P = 0.006) and waist-hip ratios (P = 0.019). The SNP rs2239815 in XBP1 gene was associated with 2-hour plasma glucose levels after 75 g oral glucose load (P = 0.048) in the observed population.

CONCLUSIONCommon variants at PERK and BIP loci contributed to the risk of prediabetes, and the genetic variations in JNK and XBP1 genes are associated with diabetes-related clinical parameters in this Chinese population.

Aged ; DNA-Binding Proteins ; genetics ; Diabetes Mellitus, Type 2 ; genetics ; Female ; Genotype ; Humans ; MAP Kinase Kinase 4 ; genetics ; Male ; Middle Aged ; Polymorphism, Single Nucleotide ; genetics ; Prediabetic State ; genetics ; Regulatory Factor X Transcription Factors ; Transcription Factor CHOP ; genetics ; Transcription Factors ; genetics ; X-Box Binding Protein 1 ; eIF-2 Kinase ; genetics