Protective effect of Gastrodia elata Blume in a Caenorhabditis elegans model of Alzheimer's disease based on network pharmacology
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- Published online on: April 12, 2023 https://doi.org/10.3892/br.2023.1620
- Article Number: 37
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Copyright: © Shi et al. This is an open access article distributed under the terms of Creative Commons Attribution License.
Abstract
Introduction
Alzheimer's disease (AD) is a dementia with a complex pathogenesis. It is a slowly progressing neurodegenerative disease, with clinical manifestations including progressive memory loss, language and intellectual impairment, and the inability to take care of oneself. It is estimated that the number of patients with AD will exceed 78 million worldwide, in 2030 (World Alzheimer Report 2021; https://www.alzint.org/resource/world-alzheimer-report-2021/). The presence of extracellular β-amyloid (Aβ) deposits and the intracellular accumulation of hyperphosphorylated tau are still the main neuropathological criteria for the diagnosis of AD (1,2). Although significant progress has been made in elucidating the key pathogenetic mechanisms, the etiopathogenesis of AD is far from clear. Alternative medicines based on natural herbs have garnered attention in recent years due to their abundance, diversity, low toxicity, effectiveness, and low cost. Chinese herbal medicines with a wide range of pharmacological activities have become prospective interventions for the prevention and treatment of human diseases (3).
Tianma [Gastrodia elata Blume, (GEB)] is an exceptional traditional herb. The GEB dry tuber is featured in the 2015 edition of the Chinese Pharmacopoeia (4). Recent studies have revealed that GEB and its active components have diverse pharmacological effects on Parkinson's disease (5), AD (6,7), and improving ischemia-reperfusion injury (8). The water extract of GEB can be used as a food additive to promote the neuroregenerative process (9). It inhibits the production of stress-related proteins and activates the neuroprotective genes in humans (10). GEB also controls chaperone/proteasome degradation pathways in SH-SY5Y cells, such as the production of CALR and HSP70/90 proteins, to enhance synapse regeneration, thereby playing a role in neuroprotection (11). Gastrodin, the major bioactive component in GEB, was demonstrated to ameliorate memory deficits in mice by inhibiting the expression of β-site APP-cleaving enzyme 1 (BACE1) protein and reducing the levels of eIF2α and phosphorylated PKR in cells (12). Furthermore, gastrodin significantly improved cell viability in a cell culture model of AD induced by Aβ25-35 and reduced the release of lactate dehydrogenase (LDH), thereby protecting neurons from Aβ toxicity (13). p-Hydroxybenzyl alcohol is another key component in GEB. p-Hydroxybenzyl alcohol was revealed to reduce the accumulation of reactive oxygen species in Caenorhabditis elegans (C. elegans) and decrease Aβ plaque deposition (14). There are numerous studies on GEB and its active components (15,16), however the underlying mechanisms of action remain unclear due to the complexity of bioactive compounds in traditional Chinese medicine (TCM). It is therefore necessary to further study the therapeutic potential of GEB in AD.
Network pharmacology is a useful tool for identifying the bioactive substances in TCM formulations. It can also reveal the mechanisms that underlie the effects of TCM (17) and provide insight into the overall regulatory mechanism of the ‘component-target-pathway’. Using the network pharmacology approach, numerous studies have successfully investigated the mechanisms of action of active components in various Chinese herbal medicines, and have identified drugs with the potential to treat diseases. For example, Yizhiqingxin formula may exert its neuroprotective effect in AD via the PI3K/Akt signaling pathway. Polygonatine A, polygonatine C and 4',5-dihydroxyflavone were demonstrated to significantly increase the survival rate and calcium levels in a PC12 cell model of amyloid β toxicity, and exhibited potential in preventing and treating AD (18,19). Network pharmacology has been gradually applied to the study of TCM components. Whole-formula, multi-component and multi-target analyses can help optimize compound prescription, according to the tenets of TCM (20). The Gene Expression Omnibus (GEO) is a global database of high-quality gene expression data, with expansive information on gene expression profiles, including significant differences in expression between diseased tissues and normal tissues (18). Therefore, in the present study, network pharmacology was combined with the GEO database to investigate the mechanism of action of GEB in the treatment of AD.
A component-target-gene network was first constructed to explore the underlying molecular mechanisms. The core network and targets of GEB were then identified using a protein-protein interaction (PPI) network, and the key pathways were clarified using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. Finally, molecular docking and reverse transcription-quantitative polymerase chain reaction (RT-qPCR) experiments were used to verify the association between key targets and components.
Materials and methods
Network pharmacology analysis. Analysis of active components
The active components of GEB were obtained by searching for ‘TIAN MA’ or ‘Gastrodia elata BI’ in the Encyclopedia of Traditional Chinese Medicine (ETCM; http://www.tcmip.cn/ETCM/index.php/Home/Index/), Bioinformatics Analysis Tool for Molecular mechANisms of Traditional Chinese Medicine (BATMAN-TCM; http://bionet.ncpsb.org.cn/batman-tcm/) and literature from China National Knowledge Infrastucture (CNKI). Subsequently, using the PubChem database (http://pubchem.ncbi.nlm.nih.gov/), the obtained active components were converted to Canonical SMILES format and imported into the SwissTargetPrediction database (http://swisstargetprediction.ch/) (21) with species set to ‘Homo sapiens’ to acquire the targets of the active components of GEB.
Obtaining gene targets related to AD
GeneCards (https://www.genecards.org/), OMIM (https://omim.org/), CTD (http://ctdbase.org/) and DisGeNET (http://www.disgenet.org/) databases (22,23) were used to screen potential targets associated with AD by searching for the keyword ‘Alzheimer disease’. The results from the four databases were integrated and deduplicated for the following analyses.
Construction of the drug-active component-target-AD network
Limma (version 3.44.3) (24) R package was used to screen for differential genes (DEGs) between 10 AD and 13 control samples in GSE5281(18) with |log2FC|>1 and adjusted P-value <0.05. The potential therapeutic targets for the anti-AD effects of GEB were obtained by overlapping targets of active components, AD-related targets and DEGs. The drug-active component-target-AD network was then constructed and visualized using Cytoscape software (version 3.2.1) (25).
Construction of a PPI network
Next, potential therapeutic targets were input into STRING database (https://string-db.org). In order to build a PPI network with a confidence level >0.4, Cytoscape software (version 3.2.1) was used to visualize the PPI network and calculate the degree of each node in the PPI network to obtain the core target. Core targets were defined as the top five nodes with the highest degrees. Heat maps were created using the Pheatmap (version 0.7.7) (26) package in R for potential targets.
GO and KEGG enrichment analyses
ClusterProfiler (version 3.18.0) (27) R package was used for GO and KEGG enrichment analyses of GEB-AD-related core targets. The GO system contains three main categories including biological process (BP), cellular component (CC) and molecular function (MF). An adjusted P-value of <0.05 was considered to indicate significant enrichment.
Molecular docking
Core targets acting as large molecular receptors, and the corresponding active compounds, acting as small molecule ligands, were selected for molecular docking analysis. The 3D structures of the core targets were downloaded from the PDB database (https://www.rcsb.org/). The 2D structures of the corresponding active ingredients were downloaded from the PubChem database (https://pubchem.ncbi.nlm.nih.gov/). The raw files of core targets and the corresponding active components were processed with the AutoDock (version 4.2) (28) tool and converted to PDBQT format for molecular docking. Binding activity was expressed as binding energy; the lower the bonding energy, the more stable the docking module (29). In general, a docking energy <-5 kcal/mol indicates good docking (30).
Experimental verification. Materials
4,4'-Dihydroxydiphenyl methane (DM) and protocatechuic aldehyde (PA) were purchased from Chengdu Alfa Biotechnology Co., Ltd. (purity ≥98%). Other reagents included RNAsimple Total RNA Kit (cat. no. DP419; Tiangen Biotech Co., Ltd.), GoScript™ Reverse Transcription System (cat. no. A5000; Promega Corporation), GoTaq® qPCR Master Mix (cat. no. A6001; Promega Corporation). Transgenic C. elegans strains CL4176 [dvIs27 (myo-3p::Aβ1-42::let-851 3'UTR) + rol-6 (su1006)] and CL2006 [dvIs2 (pCL12 (unc-54/human Aβ1-42 minigene) + pRF4)], and Escherichia coli OP50 were obtained from the Caenorhabditis Genetics Center (CGC) of the University of Minnesota (Minneapolis, USA). The network pharmacology workflow is presented in Fig. 1.
C. elegans strains and drug treatment
The strain CL2006 was propagated at 20˚C, and the strain CL4176 was propagated at 16˚C. All C. elegans strains were routinely propagated on solid nematode growth medium (NGM; consisting of 300 ml deionized water including 0.82 g peptone, Oxoid Limited; Thermo Fisher Scientific; 1.2 g NaCl, Tianjin Fengchuan Chemical Reagent Co., Ltd.; 5.15 g agar, Beijing Solarbio Science & Technology Co., Ltd.; autoclaved and supplemented 1 mM MgSO4, 1 mM CaCl2, Tianjin Fengchuan Chemical Reagent Co., Ltd.; 12.9 mM cholesterol solution, MACKLIN) with E. coli OP50 as a food source. C. elegans was treated with sodium hypochlorite, and synchronized larvae (L1 stage) were obtained after eggs were incubated overnight in M9 buffer (containing 22 mM KH2PO4, 42 mM Na2HPO4, autoclaved and supplemented with 1 mM MgSO4; all the reagents were from Tianjin Fengchuan Chemical Reagent Co., Ltd.) for experiment. Transgenic C. elegans strains CL2006 and CL4176 were used as AD animal models. C. elegans were randomly divided into control and drug pretreatment groups. The preparation was dissolved in 0.1% DMSO and diluted with ultrapure water to the appropriate concentration. Based on a previous study (31), various concentrations of DM (0.125, 0.25, 0.5, 1, 2 mM) and PA (0.125, 0.25, 0.5, 1 mM) were used to assess safety and efficacy in C. elegans.
Paralysis assay
CL4176, a temperature-sensitive transgenic model, has been demonstrated to inactivate the smg-1 system when the temperature increases from 16˚C to 25˚C, which leads to overexpression of Aβ in muscles and a paralysis phenotype. CL4176 nematodes synchronized to the L1 stage were transferred to 35 mm culture plates with or without OP50 and drugs, cultured at 16˚C for 36 h and then at 25˚C for transgene induction. After 24 h of culture at 25˚C, the paralyzed worms were observed every 2 h. When they could not move or respond to platinum wire stimulation, they were considered paralyzed (32).
Fluorescence staining of Aβ deposits
Transgenic CL2006 worms synchronized to the L4 stage (early adult stage) were inoculated on NGM plates with or without drugs, and N2 was used as a negative control for Aβ deposition (32). Following incubation at 20˚C for 48 h, the worms were collected with M9 buffer and fixed in 4% paraformaldehyde/PBS (pH 7.4) (cat. no. BL539A; Biosharp Life Sciences) at 4˚C for 24 h. The worms were then treated with 5% β-mercaptoethanol (cat. no. M828395; Macklin, Inc.), 1% Triton X-100 (cat. no. MB2486; Dalian Meilun Biology Technology Co., Ltd.) and 125 mM Tris (pH 7.4) (cat. no. T8060; Beijing Solarbio Science & Technology Co., Ltd.) at 37˚C for 24 h. The samples were stained with 0.125% thioflavin S (cat. no. S19293; Shanghai Yuanye Bio-Technology Co., Ltd.) in 50% ethanol at room temperature for 2 min, and then with 50% ethanol. The samples were thereafter rinsed and transferred to a glass slide for observation under a laser scanning confocal microscope (LSM900; Carl Zeiss AG). The number of thioflavin S-reactive deposits in the area anterior to the pharyngeal bulb was counted.
RNA extraction and quantitation
Synchronized L1 stage CL4176 nematodes were transferred to NGM medium with or without drugs (~500 nematodes in each plate) and cultured at 15˚C for 36 h, and then at 25˚C for a further 36 h. The worms were collected in an EP tube with M9 buffer, rinsed, and the supernatant was discarded (33). Total RNA was extracted using RNAsimple Total RNA Kit, and the concentration and purity were measured with an ultra-micro spectrophotometer (SMA6000; Merinton Instrument, Inc.). cDNA was obtained by reverse transcription using GoScript™ Reverse Transcription System and a thermocycler (Veriti Applied Biosystems; Thermo Fisher Scientific, Inc.), and target mRNA was quantified using GoTaq® qPCR Master Mix and real-time PCR (C1000 Touch PCR; Bio-Rad Laboratories, Inc.). Reverse transcription-quantitative polymerase chain reaction (RT-qPCR) was performed under the following operating conditions: 95˚C for 10 min, followed by 40 cycles of 95˚C for 15 sec, 55˚C for 30 sec and 72˚C for 30 sec. The reaction was then cooled and maintained at 4˚C. β-actin was used as a housekeeping gene. Relative gene expression was calculated using the 2-ΔΔCq method (34), and each reaction was repeated three times. The primers used in this assay are listed in Table SI.
Statistical analysis
GraphPad Prism software 8.0 (GraphPad Software, Inc.) was used for statistical analyses. All data are presented as the means ± SD. All experiments were repeated three times. Curves were plotted using Kaplan-Meier survival curves and statistical analyses of differences between groups in the paralysis assays were performed using the log-rank test. In addition, unpaired Student's t-test was used to compare differences between two groups. P<0.05 was considered to indicate a statistically significant difference.
Results
Prediction of components and targets based on network pharmacology. Analysis of active components
A total of 21 and 23 active components in GEB were obtained from the ETCM and BATMAN-TCM databases, respectively. After integrating and de-duplicating the data, 34 active components were obtained. After removing three active components (bis(4-hydroxybenzyl)ether mono-β'-d-glucopyranoside, tris-[4-(β'-d-glucopyranosyloxy)benzyl]citrate and vanillyl alcohol) with no canonical SMILES format, the remaining 31 active components (Table I) were imported into the SwissTargetPrediction database. A total of 869 targets of the active components of GEB were obtained. By mining the GeneCards, OMIM, CTD and DisGeNET databases, and after removing duplicate data, a total of 26,255 AD-related targets were obtained.
Obtaining gene targets related to AD
To obtain more robust AD-related targets, a total of 1,684 DEGs between AD and control samples were identified, among which 975 were upregulated and 709 were downregulated. The red dots represent upregulated genes, the green dots represent downregulated genes, and the gray dots represent genes with no significant difference (Fig. S1). Thereafter, by overlapping 869 targets of the active components of GEB (26,255 AD-related targets and 1,684 DEGs), a total of 59 potential targets of the anti-AD therapeutic effects of GEB were obtained (Fig. 2A and Table SII). The heat map shows the expression of 59 potential therapeutic targets in AD and control samples (Fig. S2). Each square represents a gene. The greater the expression, the darker the color (red, upregulated; blue, downregulated). Each row represents the expression of each gene in different samples; the column represents expression of all genes in each sample.
Construction of the drug-active component-target-AD network
Based on these results, a drug-active component-target-AD network with 92 nodes (AD, TIANMA, 31 active compounds, and 59 target genes) and 269 edges (Fig. 2B) was constructed. Furthermore, to investigate the interactions of the 59 therapeutic targets of GEB, a PPI network was constructed using the STRING database. The PPI network was composed of 47 nodes and 119 edges, revealing that therapeutic targets had a strong and complex association with each other. The color of the nodes, ranging from blue to purple, indicates the degree, ranging from small to large (Fig. 2C). GAPDH, EP300, HSP90AB1, KDM6B and CREBBP had the highest degrees, and where therefore considered to be core targets and were used for molecular docking analysis.
GO and KEGG enrichment analyses
Next, the biological functions of the 59 potential therapeutic targets were explored, which were significantly enriched in the 163 BP, 9 CC, 38 MF and 21 KEGG pathways. The top 10 BP, MF and CC pathways were involved in gene transcription, such as ‘histone demethylation’, ‘histone modification’, ‘covalent chromatin modification’, ‘DNA-binding transcription factor binding’, ‘transcription coactivator activity’ and ‘NAD binding’ (Fig. 3A). The top 10 enriched KEGG pathways were closely associated with neurodegeneration and neuroendocrinology, including the ‘cAMP signaling pathway’, ‘HIF-1 signaling pathway’ and ‘Glucagon signaling pathway’ (Fig. 3B and Table SIII).
Results of molecular docking
As mentioned above, GAPDH, EP300, HSP90AB1, KDM6B and CREBBP may be the core potential targets of GEB in the treatment of AD. GAPDH is an internal reference, and was therefore not considered further. DM and PA, two components which are at the forefront in the network diagram were investigated. These two components, with high moderate values in the network diagram, were matched with four core protein targets, and their docking potential was studied. The binding energies were between -8.12 and -5.04 kcal/mol (Table II), exhibiting good docking activity (the more negative the value, the stronger the molecular docking). Both compounds interact with the four target proteins mainly through hydrogen bonds.
The results revealed that DM forms a hydrogen bond with MET-1124 on EP300 (Fig. 4A). DM forms five hydrogen bonds with ASN-1163 and MET-1133 on CREBBP (Fig. 4B). DM forms three hydrogen bonds, with GLN-1489, SER-1184 and PRO-1181, on KDM6B (Fig. 4C). DM forms two hydrogen bonds, with GLN-18, on HSP90AB1 (Fig. 4D). PA forms four hydrogen bonds, with GLN-1077, ASP-1080 and PRO-1078, on EP300 (Fig. 4E). PA forms five hydrogen bonds, with ASN-1163 and MET-1133, on CREBBP (Fig. 4F). PA forms five hydrogen bonds, with LEU-1438, ASP-1251, TRP-1435 and PRO-1436, on KDM6B (Fig. 4G). PA forms five hydrogen bonds, with GLY-103, ASP-97 and TRP-157, on HSP90AB1 (Fig. 4H).
Effect of GEB on transgenic C. elegans. Effects of DM and PA on paralysis in C. elegans
DM (0, 0.125, 0.25, 0.5, 1, 2 mM) and PA (0, 0.125, 0.25, 0.5 mM) had no obvious toxicity. When the concentration of DM exceeded 0.5 mM, the effect of delaying C. elegans paralysis exhibited a downward trend, and 0.5 mM DM exerted the most marked effect (P<0.01) (Fig. 5A). When the concentration of PA exceeded 0.5 mM, it displayed a toxic effect; a PA concentration of 0.25 mM exhibited the most marked therapeutic effect (P<0.01) (Fig. 5B). Therefore, DM and PA have potential anti-AD activity.
DM and PA inhibit the deposition of Aβ in transgenic C. elegans
In order to study the effects of DM and PA on the aggregation of Aβ, the formation of amyloid fibrils was observed using the thioflavin-S fluorescence method. The transgenic strain CL2006 used in this experiment expressed the Aβ protein fragment related to the development of AD. These worms showed expression and aggregation of Aβ in muscle, leading to progressive paralysis. CL2006 was stained with triterpenes for Aβ at the end of DM and PA treatment (green fluorescent labeling). The fluorescence image of the head area of CL2006 nematodes showed that compared with untreated worms (negative control), Aβ deposition in those treated with 0.5 mM DM or 0.25 mM PA significantly decreased. The wild N2 strain exhibited no Aβ deposition in any part of the animal (Fig. 6A). These results indicated that both DM and PA inhibit the aggregation and deposition of Aβ in muscle cells of transgenic worms (Fig. 6B).
Effects of DM and PA on gene expression in C. elegans
Based on the results of network pharmacology and molecular docking, the regulatory effects of two active components of DM and PA with the core targets EP300, HSP90AB1, KDM6B and CREBBP were analyzed and verified using RT-qPCR. In C. elegans, the gene homologue of EP300 and CREBBP is CBP-1, that for KDM6B is JMJD3.1, and that for HSP90AB1 is HSP90 (35-37). Therefore, CBP-1, JMJD3.1 and HSP90 were examined. Compared with the control group, the expression levels of HSP90 in the DM and PA groups were significantly increased (P<0.01) (Fig. 7). There was no significant effect on the expression levels of CBP-1 in the DM or PA group. JMJD3.1 was upregulated in the DM group (P<0.01).
Discussion
In the present study, the combined power of network pharmacology and GEO were utilized to analyze the effects of GEB in AD. Firstly, a regulatory network of 31 active constituents and 59 key targets was constructed, and it was revealed that most compounds in GEB have overlapping targets and synergistic effects, suggesting that GEB has the capacity for multi-component and multi-target treatment of diseases, which is consistent with the concept of diseases having multiple pathogenic factors and complex pathogeneses. In the network diagram ‘drug-compound-target-AD’, the two components with the highest degree values were DM and PA, strongly indicating that they have potential anti-AD activity. Most previous studies on the anti-AD effects of GEB focused on extracts and gastrodin, while DM and PA have not been investigated. New components in GEB for the treatment of AD may be identified (38,39).
GO analysis revealed that GEB may be associated with the biological process of regulating epigenetic histone modification (40). KEGG analysis showed that GEB may be associated with the cAMP signaling pathway that regulates the accumulation of Aβ and neuronal apoptosis (41). Among the 59 key targets, five core targets were obtained through PPI: GAPDH, EP300, HSP90AB1, KDM6B and CREBBP. GAPDH was excluded as it was used as the internal reference. Among the four remaining proteins, HSP90AB1 is a stress-induced heat shock protein (HSP). HSPs can protect neurons by preventing protein misfolding to ensure proteome homeostasis and play a role in resisting oxidative stress and inhibiting apoptosis (42,43). HSP90AB1 is significantly downregulated in AD patients (44). Some studies suggest that HSP90AB1 is closely linked to astrocytes. Aβ and tau proteins may be degraded by HSP90AB1 through autophagy (45,46). KDM6B is a specific histone 3 lysine 27 (H3K27) demethylase. KDM6B regulates the deposition of zebrafish glial cells by regulating the expression of chemokine, Wnt and FGF signaling pathway genes (47). In addition, KDM6B serves as an effective target for black chokeberry ethanolic extract to inhibit Aβ-induced neuronal cell death (48). EP300 is a major acetylase involved in tau protein aggregation and neurodegeneration in AD (49). A previous study revealed that histone acetyltransferase, P300, can prevent and treat AD by regulating acetylation of AD-related gene promoters such as PS1 and BACE1(50). CREBBP is an acetylated histone that affects age-related memory loss (51). The inhibition of CREBBP exerts an anti-inflammatory effect. Furthermore, studies have shown that CCC protects nerve cells and ameliorates cognitive impairment in an AD mouse model by regulating CREBBP (52). CREBBP is therefore considered an attractive target in drug design and development (53). In future studies, the regulatory effects of DM and PA on core targets will be examined through molecular docking and other experiments.
Among the pathological mechanisms of AD, that of Aβ deposition is a hot research topic, and inhibiting Aβ plaque aggregation is an effective strategy for preventing and treating AD (54). C. elegans is a classic model organism for studying AD and plays an important role in drug screening (55). There are numerous AD transgenic C. elegans lines (56,57), which exhibit a number of advantages such as a short life cycle, easy culture and high gene homology (58). Transgenic C. elegans can directly produce Aβ plaques, which renders the observation and research of Aβ convenient (59). In the present study, it was determined that both DM and PA effectively delayed the paralysis phenotype and inhibited Aβ deposition in C. elegans. DM and PA exhibited similar efficacies, indicating that they directly inhibit Aβ aggregation. Both DM and PA belong to the phenolic components of GEB. Consistent with a previous study, including p-hydroxybenzyl alcohol, they can inhibit the deposition of Aβ in C. elegans, exert anti-aging and antioxidative effects in C. elegans, as well as exert anti-AD biological activities (14). Notably, RT-qPCR revealed that both DM and PA regulate the expression of the heat shock protein HSP90, but have no impact on CBP-1. Only DM positively regulated JMJD3.1. Collectively, these findings suggest that DM and PA may have therapeutic potential for AD, and can serve as focal points of future studies of GEB.
There are some limitations to the present study. The network pharmacology approach is based on reported components and targets. There may be more disease targets and components that have yet to be discovered and the composition of GEB is complex, and therefore, network pharmacology may not fully reflect the effect of GEB in AD. Furthermore, studies using other animals, such as mice and rats, are required to better model the therapeutic actions of DM and PA in AD. In future studies, the anti-AD effect of DM and PA, two active components of GEB, will be further explored and the mechanism in combination with animal models such as rats and mice will be studied, in order to obtain data that may be clinically used.
In conclusion, network pharmacology identified two core components in GEB, DM and PA, and the core targets, KDM6B, HSP90AB1, EP300 and CREBBP. Molecular docking revealed that DM and PA stably bound to the four core targets. DM (5 mM) and PA (0.25 mM) significantly delayed paralysis and inhibited the accumulation and deposition of Aβ plaques. Both DM and PA upregulated the core target gene HSP90AB1, while DM upregulated KDM6B. DM and PA may be therapeutic candidates for AD.
Supplementary Material
Volcano map of differentially expressed genes. The abscissa log2foldchange represents the difference (Alzheimer's disease/normal) and the ordinate represents the confidence level [-log10(adj. P. value)]. Each point in the figure represents a gene. The dashed lines on the horizontal and vertical axes represent the log2foldchange absolute threshold of 0.5 and P-value threshold of 0.05, respectively.
Heat map of 59 key targets in control and AD samples. Each square represents a gene. The greater the expression, the darker the color (red, upregulated; blue, downregulated expression). Each row represents the expression of each gene in different samples; each column represents the expression of all genes in each sample.
Primer sequences used for PCR.
Potential targets associated with AD and GEB.
Results of KEGG analysis (top 20).
Acknowledgements
Not applicable.
Funding
Funding: The present study was supported by the National Natural Science Foundation of China (grant no. 81960733), the Open Project of Yunnan Key Laboratory of Dai and Yi Medicines (grant no. 202210ZD2206), the Xingdian Talent Support Program-Special for Young Talent (2022), the National Administration of Traditional Chinese Medicine High-level Key Discipline Construction Project ‘Dai Medicine’.
Availability of data and materials
The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.
Authors' contributions
XS, YL and XD made considerable contributions to the experimental design, statistical data analysis and English language editing. XD and LY are responsible for drafting the manuscript and revising it for important intellectual content. XS and LY confirm the authenticity of all the raw data. All authors read and approved the final manuscript.
Ethics approval and consent to participate
Not applicable.
Patient consent for publication
Not applicable.
Competing interests
The authors declare that they have no competing interests.
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