Abstract
Background
Ganoderma (Lingzhi in Chinese) has shown good clinical outcomes in the
treatment of insomnia, restlessness, and palpitation. However, the
mechanism by which Ganoderma ameliorates insomnia is unclear. We
explored the mechanism of the anti-insomnia effect of Ganoderma using
systems pharmacology from the perspective of central-peripheral
multi-level interaction network analysis.
Methods
The active components and central active components of Ganoderma were
obtained from the TCMIP and TCMSP databases, then screened to determine
their pharmacokinetic properties. The potential target genes of these
components were identified using the Swiss Target Prediction and TCMSP
databases. The results were matched with the insomnia target genes
obtained from the GeneCards, OMIM, DisGeNET, and TCMIP databases.
Overlapping targets were subjected to multi-level interaction network
analysis and enrichment analysis using the STRING, Metascape, and
BioGPS databases. The networks analysed were protein-protein
interaction (PPI), drug-component-target gene, component-target
gene-organ, and target gene-extended disease; we also performed gene
ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG)
analyses.
Results
In total, 34 sedative-hypnotic components (including 5 central active
components) were identified, corresponding to 51 target genes.
Multi-level interaction network analysis and enrichment analysis
demonstrated that Ganoderma exerted an anti-insomnia effect via
multiple central-peripheral mechanisms simultaneously, mainly by
regulating cell apoptosis/survival and cytokine expression through core
target genes such as TNF, CASP3, JUN, and HSP90αA1; it also affected
immune regulation and apoptosis. Therefore, Ganoderma has potential as
an adjuvant therapy for insomnia-related complications.
Conclusion
Ganoderma exerts an anti-insomnia effect via complex central-peripheral
multi-level interaction networks.
Keywords: Ganoderma, Insomnia, Systems pharmacology, Central,
Peripheral
Background
Insomnia is a common sleep disorder that is generally defined as
dissatisfaction with sleep quantity or quality. The treatment of
insomnia usually consumes substantial medical resources. Insomnia is
experienced by 33–50% of the adult population. Its prevalence ranges
from 10 to 15% in the general population [[31]1]. An epidemiological
study in China [[32]2] showed that 45.4% of the respondents experienced
varying degrees of insomnia in the previous month. Daytime dysfunction
caused by insomnia includes fatigue, depression or irritation, physical
discomfort, and cognitive impairment. It is also a common complication
and trigger of cardiovascular, cerebrovascular, and mental diseases
[[33]3].
Compared with Western medicine, which relies on sedative and hypnotic
drugs, traditional Chinese medicine (TCM) for insomnia has lower
tolerance and dependence, as well as fewer adverse reactions; thus, it
has become an important alternative therapy in East Asia, North
America, Europe, and other regions [[34]4]. Ganoderma is a medicinal
mushroom that contains various pharmacological compounds. Medicinal
Ganoderma is usually the dried fruiting body of Ganoderma lucidum
(Leyss. ex Fr.) Karst or Ganoderma sinense Zhao, Xu et Zhang. According
to the Chinese pharmacopoeia records, Ganoderma invigorates Qi (‘life
energy’ or ‘life force’ in TCM); tranquilises the mind; and is used for
the treatment of insomnia, palpitations, cough, and asthma [[35]5]. To
our knowledge, there have been few studies regarding the
neuropharmacological activities of Ganoderma, including its sedative,
hypnotic, neuroprotective, antinociceptive, analgesic, antiepileptic,
and antidepressant effects [[36]6]. Randomised controlled trials for
insomnia have shown that Ganoderma can improve sleep quality and reduce
the incidences of adverse effects and dependence [[37]7, [38]8]. In
animal studies, Ganoderma extract reduced sleep latency and prolonged
sleep duration, which might be related to tumour necrosis factor (TNF)
and γ-aminobutyric acid receptor activities [[39]9, [40]10]. Ganoderma
has anti-inflammatory, anti-oxidant, anti-hyperglycaemic, anti-ulcer,
and immunostimulatory effects [[41]11]. Therefore, Ganoderma can be
used for the prevention and treatment of insomnia; the underlying
mechanism warrants investigation.
Because Ganoderma contains large numbers of active components, which
may interact with each other, it may have preventive and/or therapeutic
effects against various diseases in multiple systems. This complex
pharmacological network hampers systematic research regarding
Ganoderma. Systematic pharmacology provides a new choice and direction
for the study of drugs with complex pharmacological networks by
integrating systems biology with pharmacology.
Here, we explored the sedative and hypnotic effects of Ganoderma to
analyse the mechanism of its effects on insomnia. Because insomnia is
complex and regulated by central and peripheral mechanisms, we first
identified the anti-insomnia components of Ganoderma, isolated active
components and central active components, classified the target genes
by two-dimensional (2D) and three-dimensional (3D) similarity
measurements, and matched the results with the insomnia target genes in
multiple databases to identify overlapping targets. By using this
process, multi-component, −target, −pathway, −organ, and -interaction
networks were constructed. Compared with a single-level network
analysis, which explains the mechanism from a single perspective,
multi-level networks are more similar to in vivo pharmacodynamics. This
is particularly relevant for insomnia, which is regulated by central
and peripheral mechanisms. The experimental process is shown in
Fig. [42]1.
Fig. 1.
[43]Fig. 1
[44]Open in a new tab
Diagram of experimental process. TCMSP: Traditional Chinese Medicine
Systems Pharmacology Database and Analysis Platform; TCMIP: Integrative
Pharmacology-based Research Platform of Traditional Chinese Medicine;
OB: Oral bioavailability; DL: Drug-likeness; QED: Quantitative
Estimation of Drug-likeness; BBB:blood-brain barrier
Methods
Establishment of Ganoderma active-components dataset
The Integrative Pharmacology-based Research Platform of Traditional
Chinese Medicine (TCMIP, [45]http://www.tcmip.cn/) v. 2.0 is a
data-mining platform that uses the database resources of the
Encyclopedia of Traditional Chinese Medicine; it provides insights into
the material basis and molecular mechanism of TCM efficacy. By
inputting the Latin name of Ganoderma into the database, we retrieved
all chemical constituents, then screened them by quantitative
estimation of drug-likeness (QED score; calculated according to the
Pipeline Pilot ADMET collection model, including aqueous solubility,
blood brain barrier penetration, CYP450 2D6 inhibition, hepatotoxicity,
human intestinal absorption, and plasma protein binding). The reported
mean QED values for attractive and unattractive components in drug
development were 0.67 and 0.49. The components of Ganoderma with
moderate and good QED scores (QED ≥ 0.49) were retained [[46]12].
The Traditional Chinese Medicine Systems Pharmacology Database and
Analysis Platform (TCMSP, [47]https://tcmspw.com/tcmsp.php) is an
efficient database for systems pharmacology research regarding TCM.
TCMSP was used to supplement the information regarding Ganoderma
chemical composition. Oral bioavailability (OB) refers to the
proportion of an orally administered drug that reaches the systemic
circulation; this is a key indicator of the properties of bioactive
molecules and drugs, and it has a high effect ratio. In this study, the
oral bioavailability predicting model was supported by a dataset of 805
structurally diverse drugs with determination coefficients (R^2) of
0.80 and standard errors of estimate of 0.31 for test sets; the model
integrated P450, 3A4, and P-glycoprotein information. Drug-likeness
(DL) represents the ‘drug-like’ degree of the target compound; this
metric was used to remove chemically unsuitable compounds. TCMSP used
the Tanimoto coefficient to calculate the drug-likeness index by
comparing the target compound with all 6511 molecules in the DrugBank
database (Eq. [48]1).
[MATH: FX,Y=XYX2+Y2-XY :MATH]
1
where X represents the molecular properties of the compound in
Ganoderma, and Y represents the mean molecular properties of all
compounds in the DrugBank database ([49]https://www.drugbank.ca).
To identify components that may be absorbed orally and exert curative
effects, based on the mean value for all compounds in the DrugBank
database, we selected the following threshold conditions for screening
active components: OB ≥ 30% and DL ≥ 0.18.
The active components of Ganoderma identified by TCMIP and TCMSP were
combined, the names were standardised in the PubChem database
([50]https://pubchem.ncbi.nlm.nih.gov/) [[51]13], and duplicates and
invalid data were removed. Thus, the Ganoderma active component dataset
was created. Because insomnia is closely related to the central nervous
system, the central active components with a blood-brain barrier (BBB)
score ≥ − 0.3 were extracted to facilitate exploration of the
drug-disease relationship; higher scores indicate greater blood-brain
barrier permeability. These were presumed to directly affect the
central nervous system and used to explore the central-peripheral
regulatory mechanism of Ganoderma.
Prediction of target genes of Ganoderma active components
The SMILES string of the active components of Ganoderma or the SDF
files of their molecular structures were searched in the PubChem
database, then imported into the Swiss Target Prediction database
(http:∥swisstargetprediction.ch/) [[52]14]. The species was defined as
Homo sapiens. Predictions were performed by searching for similar
molecules, in 2D and 3D, among 376,342 compounds known to be
experimentally active on an extended set of 3068 macromolecular
targets. The 2D approach compares fingerprints describing each
molecule; similarity is computed as the Tanimoto coefficient. In the 3D
approach, molecules are represented by an 18-dimensional vector. The
Manhattan distance is used to compare vectors (X and Y) describing two
different molecules (Eq. [53]2). The final 3D similarity value between
molecules I and j is computed, where dij is the smallest Manhattan
distance among the 20 × 20 distances calculated over all possible
conformations of each molecule (Eq. [54]3).
[MATH: d=∑s=1
18Xs-Ys :MATH]
2
[MATH: 1/1+118
dij :MATH]
3
The potential target genes of Ganoderma active components could be
predicted after running [[55]15]. The target genes with high
credibility were screened with a probability value ≥0.50 as the
threshold. For active components without results under the screening
conditions, the MOL number was input into the TCMSP database to
supplement the target gene information. In this study, TCMSP used the
systems drug targeting model, based on a random forest and support
vector machine method, to identify potential therapeutic targets of
candidate compounds. The training set for the systems drug targeting
model included 6511 drug molecules and almost 4000 proteins that
interact with drug molecules in the DrugBank database. The results
indicated good ability to predict drug-target interactions; the
consistency, sensitivity, and specificity values were 82.83, 81.33, and
93.62%, respectively.
The active components and target genes were integrated to establish a
dataset of the effective components and corresponding target genes of
Ganoderma. The relationships between the components and target genes
were input into Cytoscape ([56]http://www.Cytoscape.org/) for visual
analysis. The attributes of the components were classified as the
source node, the attributes of target genes were classified as target
nodes, the attributes of node type were classified as interaction type,
and treated the network as undirected.
Recognition of disease target genes based on multiple databases
To identify potential insomnia target genes, we used the keywords
‘insomnia’, ‘somnipathy’, and ‘sleep disorders’ to search the GeneCards
([57]https://www.genecards.org/) [[58]16], OMIM ([59]https://omim.org/)
[[60]17], DisGeNET ([61]https://www.disgenet.org/) [[62]18], and TCMIP
([63]https://www.tcmip.cn/) [[64]12] databases. We merged the database
findings and deleted repeated target genes, thus producing
insomnia-related disease target genes.
Construction of overlapping data of drugs and disease target genes
The active component target genes and insomnia target genes of
Ganoderma were input into the Jvenn online tool
([65]http://jvenn.toulouse.inra.fr/app/index.html). This tool was used
to create a Venn diagram to assess the intersections of target genes
between Ganoderma and insomnia, or the potential target genes of
Ganoderma for insomnia treatment. This facilitated PPI network analysis
and the construction of a multidimensional network.
Construction of the PPI network
The STRING database ([66]https://string-db.org/) [[67]19] contains
known protein interactions, enabling the construction of PPI networks.
To assess the expression of intersection target genes, the potential
target genes of Ganoderma for insomnia treatment were imported into the
STRING database. The interaction credibility is determined by the
confidence level (highest confidence, score ≥ 0.9; high confidence or
better, score ≥ 0.7; medium confidence or better, score ≥ 0.4; and low
confidence or better, score ≥ 0.15). In this study, the minimum
required score was set to 0.4. The species was set as Homo sapiens.
Free protein was removed. The PPI network of potential target genes for
insomnia in Ganoderma was obtained and input into Cytoscape for
visualisation. The complex network relationship was analysed using the
AnalysisNetwork module; the following topological parameters were
obtained: average shortest path length (ASPL), betweenness centrality
(BC), closeness centrality (CC), and degree. The degree of each node
represents the number of other nodes to which it is directly connected;
BC refers to the number of times a node passes through the shortest
path between any two other nodes; CC represents the reciprocal of the
mean distance to all other nodes; and ASPL represents the mean of the
shortest path between any two nodes. Larger degree, closeness
centrality, and betweenness centrality values are associated with
smaller average shortest path length values and stronger node
centrality values. Using these parameters, the core proteins were
identified by digitising the complex network relationship.
Construction of the drug-component-target gene network
The effective component-target gene data of Ganoderma were input into
Excel to determine the intersection target genes screened by PPI;
components that exhibited no relationships with the intersection target
gene were deleted. Thus, components of Ganoderma with potential
sedative and hypnotic effects were obtained. The correlations among
components, target genes, diseases, and drugs were input into Cytoscape
to construct a visual drug-component-target gene network map. By
analysing the degree of the target gene, it was determined that the
target gene was jointly affected by several effective components, based
on which the credibility of intervention by the target gene was
examined. By analysing the connectivities of the active components, we
determined which active components simultaneously acted on the target
gene, then examined their biological activities.
Pathway enrichment analysis of sedative and hypnotic target genes
The sedative-hypnotic target genes screened by PPI were integrated and
input into the online platform Metascape ([68]http://metascape.org/)
[[69]20] for enrichment analysis of GO biological processes and KEGG
pathways [[70]21]. P-values were calculated based on the cumulative
hypergeometric distribution; they were corrected by the
Benjamini-Hochberg method. The most representative enrichment analysis
results were selected with P < 0.01 [[71]22]. Eventually, those results
were visualized by bioinformatics online tool
([72]http://www.bioinformatics.com.cn).
Construction of the component-target gene-organ network
The BioGPS database ([73]http://biogps.org/#goto=welcome) [[74]23] is a
centralised gene portal for aggregating distributed gene annotation
resources; targets can be located by querying the expression patterns
of genes in cells or tissues. In this study, the BioGPS database was
used to identify sedative and hypnotic targets of Ganoderma. After
inputting the targets, human was chosen as the species and ‘GeneAtlas
U133A, gcrma’ in the default dataset was selected. After correlation
sorting and removal of meaningless results, the positioning results
were integrated with the sedative and hypnotic components-target gene
dataset; Cytoscape was used to draw the Ganoderma positioning network
map. Because the brain regulates sleep, organs or tissues related to
the brain were listed separately in the organ-mapping diagram to
explore the relationships of different brain functional areas with the
improvement of insomnia and to examine the target organs of the
central-peripheral mechanism.
Construction of the target gene-extended disease network
To explore the pharmacological effects of Ganoderma on insomnia, the
sedative and hypnotic target genes of Ganoderma were reversely enriched
in the DisGeNET database based on the Metascape online platform
(P < 0.01). The data were input into Cytoscape for visualisation to
explore the therapeutic effect of Ganoderma on insomnia, then determine
its utility as a treatment or adjuvant therapy for insomnia
complications.
Results
Ganoderma active-component dataset
Using the TCMSP and TCMIP databases, duplicate items were deleted, and
the names were standardised. Based on their pharmacokinetics (OB, DL,
and BBB), 80 active components of Ganoderma were obtained, including 16
potential central active components (BBB ≥ − 0.3) (Table [75]1).
Ganoderma contained a large number of active components, mostly
triterpenoids (ganoderic acid, ganoderma alcohols, and ganoderma
aldehydes) and sterols.
Table 1.
Information of potential central active components
PubChem CID chemical name Molecular Formula BBB OB
444,679 Ergosterol C28H44O 1.66 14.29
56,676,695 (24xi)-Ergosta-4,6,8(14),22-tetraene-3-one C28H40O 1.15
48.32
222,284 Beta-Sitosterol C29H50O 0.99 36.91
5,283,669 Stellasterol C28H46O 0.98 43.51
101,449,382 Ergosta-7,22-diene-3beta-yl pentadecanoa C43H74O2 0.72
38.25
69,888,957 Ergosta-7,22-diene-3beta-ol palmitate C44H76O2 0.63 37.60
6,449,869 Ergosta-7,22-dien-3-yl linoleate C46H76O2 0.53 45.11
11,177,299 Ganodesterone C28H40O2 0.47 47.86
5,351,516 Ergosterol peroxide C28H44O3 0.43 44.39
21,159,042 26,27-Dihydroxy-Lanosta-7,9(11),24-Trien-3,16-Dione C30H44O4
0.13 28.95
11,048,424 Lucialdehyde A C30H46O2 0.13 44.78
3,001,811 Ganodermanontriol C30H48O4 0.07 28.92
471,007 Ganoderiol B C30H46O4 −0.03 28.95
73,082,616 Ganoderol A C30H46O2 −0.04 44.69
101,602,260
(22S)-22beta-Acetoxy-3alpha,15alpha-dihydroxy-5alpha-lanosta-7,9(11),24
-trien-26-oic acid C32H48O6 −0.06 37.64
68,018,655 Ganoderic acid Z C30H48O3 −0.19 37.67
[76]Open in a new tab
Target genes of Ganoderma active components
Data from the Swiss Target Prediction tool and the TCMSP database
indicated that 36 of the 80 active components had 56 target genes with
high reliability (Fig. [77]2). The target genes and active components
intersected, and the same active component could correspond to multiple
target genes. For example, beta-sitosterol corresponded to 37 target
genes. Beta-sitosterol has cholesterol-reduction, anti-inflammatory,
and antitumour activities [[78]24]; it may have an important role in
the effects of Ganoderma. Beta-sitosterol extracted from herbs has
sedative-hypnotic potential [[79]25, [80]26]. In this study,
beta-sitosterol showed good blood-brain barrier permeability (0.99),
indicating that it comprises a potential central active component. We
speculate that this Ganoderma component regulates the insomnia network.
Fig. 2.
[81]Fig. 2
[82]Open in a new tab
Target gene network of active components. The blue arrows represent the
active components; the yellow arrows represent the central active
components; the yellow diamonds represent diseases; the red diamonds
represent target genes
The same target gene could be affected simultaneously by multiple
active components. Ganoderma triterpenes had several physiological
activities, including antitumour, liver protection, anti-human
immunodeficiency virus, and cholesterol reduction [[83]27]. TNF was
jointly affected by 15 components, mainly triterpenoids, of Ganoderma;
thus, Ganoderma may participate in sleep regulation by affecting TNF.
Sleep is closely related to immunity. Sleep deprivation affects
metabolism and increases the secretion of C-reactive protein, TNF, and
interleukin-6 [[84]28]; TNF activity increases non-rapid eye movement
sleep [[85]29]. These results will facilitate the improvement of
Ganoderma pharmacological activity. In summary, the active components
of Ganoderma are complex and interact with each other.
Disease target genes in multi-source databases
In total, 8092 target genes were obtained by integrating disease target
genes from the GeneCards, DisGeNET, OMIM, and TCMIP databases. The
mechanism of insomnia was complex, involving large numbers of target
genes.
Intersections of drugs and disease target genes
A Venn diagram was created by crossing the target genes of active
components of Ganoderma with insomnia-related targets (Fig. [86]3).
There were 51 targets for the treatment of insomnia, constituting
91.07% of the total. Ganoderma has therapeutic potential for insomnia;
clarification of its anti-insomnia mechanism is important for clinical
application and drug development.
Fig. 3.
Fig. 3
[87]Open in a new tab
Venn diagram of drug-disease target genes. The red region represents
the insomnia target genes, and the blue region represents the Ganoderma
target genes
PPI network
The potential target genes of Ganoderma for insomnia were imported into
the STRING database for PPI network analysis, using nodes to represent
the target genes and edges to represent the relationships between
target genes. The number of nodes in the PPI network of Ganoderma
target genes was 51 (without free targets); the number of edges was
194. The mean node degree was 7.61 and the mean local clustering
coefficient was 0.554. Network data analysis showed close relationships
among Ganoderma target genes in insomnia treatment.
To identify core target genes in the PPI network, the network data were
input into Cytoscape for visualisation (Fig. [88]4) and topology
analysis (Table [89]2). The central properties of target genes were
evaluated by topological analysis. TNF, caspase-3 (CASP3),
transcription factor AP-1 (JUN), glucocorticoid receptor (NR3C1), heat
shock protein 90-alpha (HSP90αA1), estrogen receptor 1, prostaglandin
G/H synthase 2, cytochrome P450 family 19 subfamily A member 1,
androgen receptor, and others were core proteins in the PPI network;
they had important roles in the regulatory network.
Fig. 4.
[90]Fig. 4
[91]Open in a new tab
PPI network and core protein network. All node color and size depended
on the Degree value. Topological Screening of Proteins with
Degree≥8(The average value of Degree), 11 core proteins with median
topological feature values above/below the median were identified. CC:
Closeness Centrality; BC: Betweenness Centrality; ASPL: Average
Shortest Path Length
Table 2.
Topological analysis of PPI network (top 20 sorted by degree)
Targets Degree ASPL BC CC
TNF 21 1.720 0.236 0.581
CASP3 19 1.780 0.090 0.562
JUN 19 1.720 0.120 0.581
NR3C1 17 1.780 0.132 0.562
HSP90αA1 17 1.880 0.120 0.532
ESR1 16 1.940 0.029 0.515
PTGS2 15 1.960 0.020 0.510
CYP19A1 15 1.880 0.094 0.532
AR 13 2.000 0.019 0.500
SLC6A4 10 2.120 0.066 0.472
CHRM1 10 2.160 0.079 0.463
PGR 10 2.180 0.003 0.459
CASP8 10 2.160 0.003 0.463
CHRM2 9 2.440 0.031 0.410
CASP9 9 2.180 0.003 0.459
NOS2 9 2.100 0.030 0.476
ADORA1 8 2.260 0.041 0.442
ADRA1B 8 2.540 0.016 0.394
ADRB2 8 2.080 0.033 0.481
NCOA2 8 2.360 0.005 0.424
[92]Open in a new tab
Drug-component-target gene network
Using Excel and visualisation in Cytoscape, the drug-component-target
gene network of Ganoderma for insomnia treatment was obtained
(Fig. [93]5). The network included 51 sedative-hypnotic target genes
and 34 sedative-hypnotic components (including 5 central
sedative-hypnotic components) of Ganoderma.
Fig. 5.
[94]Fig. 5
[95]Open in a new tab
Drug-component-target gene network. The green rhombus represents
Ganoderma; the blue arrow represents the active components; the yellow
arrow represents the central active components; the red rhombus
represents the target genes; and the red ellipse represents insomnia
TNF was the target gene with the highest degree value of 16, followed
by 10 for mineralocorticoid receptor (NR3C2), 6 for androgen receptor
and progesterone receptor, and 4 for nitric oxide synthase 2 and
nuclear receptor coactivator 2. These results indicate that the target
gene is affected by multiple components, and the reliability of the
intervention is high.
Among the sedative and hypnotic components, the component with the
highest degree value was beta-sitosterol (38), followed by adenosine
(6), stellasterol (5), lucialdehyde B (5), ganoderic aldehyde A (4),
and ganoderic acid DM (4). These components had high connectivity,
suggesting that they interfere with the development of insomnia through
multiple target genes and pathways.
GO enrichment analysis
Using the Metascape online platform for GO enrichment analysis, 694
representative functional clusters were obtained. According to the
number of target genes involved, the top 20 enrichment results were
retained for analysis (Fig. [96]6). The GO enrichment results were
concentrated in cyclic metabolism, synaptic signalling, cell secretion
and response, and G protein-coupled receptor signalling pathway.
Fig. 6.
[97]Fig. 6
[98]Open in a new tab
Bubble diagram of GO Biological Processes
Cyclic metabolism included blood circulation (GO: 0008015), the
circulatory system process (GO: 0003013), and regulation of the system
process (GO: 0044057). Synaptic signals included chemical synaptic
transmission (GO: 0007268), anterograde trans-synaptic signalling (GO:
0098916), trans-synaptic signalling (GO: 0099537), and synaptic
signalling (GO: 0099536). Cell secretion and response included
regulation of secretion by cells (GO: 1903530), regulation of secretion
(GO:0051046), response to steroid hormone (GO: 0048545), cellular
response to lipid (GO: 0071396), and cellular response to hormone
stimulation (GO: 0032870). The G protein-coupled receptor signalling
pathway included G protein-coupled receptor signalling pathway, coupled
to cyclic nucleotide second messenger (GO: 0007187), and adenylate
cyclase-modulating G protein-coupled receptor signalling pathway (GO:
0007188). The rhythmic process (GO: 0048511) is closely related to
sleep regulation, suggesting that Ganoderma improves insomnia by
affecting biological rhythms.
KEGG enrichment analysis
Using the Metascape online platform for KEGG enrichment analysis, 93
representative functional clusters were identified after the removal of
signalling pathways that exhibited weak correlations with insomnia;
these included pathways in cancer (hsa05200), tuberculosis (hsa05152),
toxoplasmosis (hsa05145), and small-cell lung cancer (hsa05222).
According to the number of target genes involved in sorting, and after
the retention of results with ≥5 target genes, 24 targets were obtained
(Fig. [99]7). Next, seven pathways with high analytical values were
selected for sorting; the pathway diagram of Ganoderma for insomnia
treatment is shown in Fig. [100]8. The largest number of targets was
involved in the neuroactive ligand-receptor interaction signalling
pathway (hsa04080), which is a collection of plasma membrane receptors
and ligands related to intracellular and extracellular signalling
pathways, suggesting that Ganoderma affects receptor–ligand
interactions. Through analyses of the calcium signalling pathway
(hsa04020), cyclic adenosine monophosphate (cAMP) signalling pathway
(hsa04024), apoptosis (hsa04210), interleukin-17 signalling pathway
(hsa04657), phosphatidylinositol 3-kinase-protein kinase B (PI3K-Akt)
signalling pathway (hsa04151), TNF signalling pathway (hsa04668), and
other pathways, we found that TNF, JUN, HSP90αA1, and other core target
genes ameliorate insomnia by interfering with the above target genes
related to apoptosis/survival, cell cycle regulation, cytokines, and
inflammation. In addition, cholinergic synapse (hsa04725) and
serotonergic synapse (hsa04726) were notable pathways because they are
reportedly related to insomnia and the regulation of sleep and arousal
[[101]30, [102]31].
Fig. 7.
[103]Fig. 7
[104]Open in a new tab
KEGG enrichment pathway
Fig. 8.
[105]Fig. 8
[106]Open in a new tab
Mechanism diagram of Ganoderma treating insomnia. IL-17: Interleukin
17; TNF-α:Tumor necrosis factor-alpha; TNF-R: Tumor necrosis
factor-Receptor; ER: Estrogen receptor; GPCR: G protein-coupled
receptor; HSP90αA1: Heat shock protein 90-alpha; CASP: Caspase; PRKCA:
Protein kinase C alpha type; BAX: Apoptosis regulator BAX; JUN:
Transcription factor AP-1; COX2: Cytochrome c oxidase subunit 2; TGFB1:
Transforming growth factor beta-1; cAMP: Cyclic adenosine
monophosphate; PKA: Protein kinase A; PDE3A: Phosphodiesterase 3A;
PI3K: Phosphatidylinositol 3-kinase; AKT(PKB): Kinase-protein kinase B;
BCL2: B-cell lymphoma 2; NOS2: Nitric oxide synthase
Several neurodegenerative disease-related pathways were detected, such
as Huntington disease (hsa05016), Parkinson disease (hsa05012), and
Alzheimer disease (hsa05010); there is often a bidirectional
relationship between the above neurodegenerative diseases and insomnia
[[107]32]. Hepatitis B, hepatitis C, non-alcoholic fatty liver disease,
and other liver-related disease pathways were also enriched. A
considerable proportion of hepatitis B patients have insomnia
[[108]33]. The relationship between liver and insomnia is weak, and the
mechanism is unknown.
Component-target gene-organ network
Organ localisation of Ganoderma sedative and hypnotic target genes was
performed using the BioGPS database. The results were integrated with
the component-target gene dataset, then input into Cytoscape for visual
mapping and analysis (Fig. [109]9). Although the central active
components of Ganoderma comprised only a small portion of the total,
the number of target genes affected by Ganoderma was greater than the
number of genes affected by other components. Ganoderma may affect the
central nervous system in the treatment of insomnia; beta-sitosterol
made the greatest contribution to this process. However, the target
organs of the central active components included—but were not limited
to—the central organs. Furthermore, other target genes were also highly
expressed in the central and peripheral organs. Therefore, we speculate
that Ganoderma exerts its anti-insomnia effects by influencing the
expression of the same target genes in multiple organs simultaneously
(i.e., a central-peripheral mechanism).
Fig. 9.
[110]Fig. 9
[111]Open in a new tab
Component-target gene-organ network. The arrow represents the sedative
and hypnotic components of Ganoderma: the red arrow represents the
central active component; the red rhombus represents the target genes
corresponding to the central active components; the blue rhombus
represents other target genes; the right circle represents the organ.
The node size and color depend on Degree
In the central mechanism, Ganoderma mainly affected the pineal body,
amygdala nucleus, prefrontal cortex, cerebellum, and other regions. The
pineal body is an important regulatory hub of the human biological
clock, to which melatonin and 5-hydroxytryptamine are closely related
[[112]34]. The amygdala nucleus and prefrontal cortex are important
functional areas of emotion control and have roles in sleep regulation
[[113]35]. In the peripheral mechanism, the heart, thyroid gland, and
liver exhibited more target genes. Cardiovascular disease is closely
related to circadian rhythm disorder [[114]36]; TCM theory postulates a
close relationship among the heart, brain, and spirit. Our results
provide a scientific explanation for ‘heart and brain jointly dominate
the spirit.’ Changes in thyroid gland function affect the peripheral
biological clock [[115]37], possibly improving insomnia. The liver
metabolises vitamins and hormones [[116]38]. To our knowledge, there
have been few modern studies regarding the relationship between liver
and insomnia, and the underlying mechanism warrants further
investigation.
Target gene-extended disease network
Reverse disease enrichment of Ganoderma sedative hypnotic target genes
was carried out using the Metascape online platform; it yielded 1874
enrichment values. Results with > 10 enriched target genes were
selected for analysis, and less valuable results were deleted (e.g., 48
tumour-related diseases). The appropriate results were retained and
entered into Cytoscape for visualisation (Fig. [117]10). Neurological,
cardiovascular and cerebrovascular, and digestive system diseases were
the most common diseases.
Fig. 10.
[118]Fig. 10
[119]Open in a new tab
Target gene-extended diseases network. The purple rectangle represents
the target gene; the blue circle represents the disease; the cyan
circle represents the disease type
Discussion
Sleep is important for maintenance of normal physiological and
psychological activities. Disturbance of the natural sleep rhythm can
cause insomnia and various pathophysiological changes. Central
pacemaker neurons are the main nodes of rhythm regulation, driving the
biological clock of peripheral tissues. They jointly regulate the sleep
rhythm process; thus, the development and formation of insomnia are
affected by the central-peripheral mechanism [[120]39]. Current drugs
for insomnia include benzodiazepine receptor agonists, melatonin
receptor agonists, orexin receptor antagonists, and antidepressants
with sedative and hypnotic effects. They typically act on specific
receptors (e.g., γ-aminobutyric acid receptor A and melatonin MT
receptor), but these drugs can cause dependence and adverse reactions
[[121]40].
Ganoderma, a commonly used Chinese medicine for the treatment of
insomnia, is rich in various active components. In this study, we
identified 80 active components, mainly triterpenoids and sterols. We
set a high screening threshold (probability value ≥0.50) in Swiss
Target Prediction and TCMSP; we found 36 components corresponding to 56
target genes (34 sedative-hypnotic components corresponding to 51
target genes), including 5 central active components. The
pharmacological action of Ganoderma was not limited to a single
receptor or organ; it affected related proteins in multiple tissues or
organs. Thus, Ganoderma exerts its pharmacological effects by
simultaneously affecting multiple central-peripheral mechanisms,
whereas commonly used insomnia drugs typically affect a single
receptor.
Analysis of the drug-component-target gene network showed that the
components beta-sitosterol, adenosine, stellasterol, lucialdehyde B,
ganoderic aldehyde A, and ganoderic acid DM had high degree values,
indicating that they had important roles in the regulatory network.
Beta-sitosterol and stellasterol have a wide range of physiological
functions. Thus far, research regarding their pharmacological
activities mainly focuses on lowering cholesterol and blood lipid
levels, as well as their anti-inflammatory effects. Beta-sitosterol and
related fatty acids have anti-anxiety and sedative effects [[122]25],
but the underlying mechanisms are unclear. However, our results suggest
that beta-sitosterol has great potential in sedation and hypnosis;
moreover, Ganoderma has high sterol content [[123]41]. Therefore,
regardless of component activity or content, Ganoderma sterols may have
important roles in sedation and hypnosis. Adenosine, an active
component of Ganoderma, has a role in sleep-wake regulation. Adenosine
is a key signal molecule in prostaglandin D2-induced sleep, and its
receptor has an important role in driving sleep [[124]42]. In addition,
the active components contain various Ganoderma triterpenes; some act
on the same target genes (e.g., TNF and NR3C2). This synergistic effect
may strengthen interventions against the target gene.
A PPI network topology analysis yielded the core target genes in the
Ganoderma protein interaction network, including TNF, CASP3, JUN,
NR3C1, and HSP90αA1. Sleep and immunity are mutually regulated. TNF and
HSP90αA1, two important factors in the immune system, are closely
related to sleep regulation [[125]43]. The proinflammatory cytokine TNF
increases non-rapid eye movement sleep [[126]29]. HSP90αA1 participates
in cell cycle regulation and signal transduction; it also mediates
inflammatory responses and apoptosis [[127]44]. CASP3, JUN, and other
core proteins are closely related to apoptosis, which may involve TNF
[[128]45], although the underlying mechanism is unclear. In summary,
the effect of Ganoderma on insomnia is at least partly mediated by
immunity and apoptosis, although this hypothesis should be confirmed by
KEGG analysis.
The GO results showed that Ganoderma modulates mainly circulatory
metabolism, synaptic signalling, cell secretion and response, G
protein-coupled receptor signalling, and other categories; these
results indicated effects on various biological processes, among which
biological rhythm is most closely related to insomnia. The KEGG
enrichment results showed that during the treatment of insomnia by
Ganoderma, the neuroactive ligand-receptor interaction signalling
pathway is active; furthermore, core target genes (e.g., TNF, JUN, and
HSP90αA1) regulate the calcium, apoptosis, cAMP, PI3K/Akt, and TNF
signalling pathways, thereby modulating apoptosis/survival and the
expression of various cytokines. Calcium signal transduction in
astrocytes is reduced during sleep; it is involved in the regulation of
slow-wave sleep [[129]46]. Moreover, calcium signalling is important in
the apoptosis pathway, and there are interactions between these
pathways [[130]47]. Therefore, calcium signalling may have a key role
in the regulation of insomnia by Ganoderma. Cholinergic and
serotonergic synapses are also related to insomnia [[131]30, [132]31]
and have important regulatory roles in both sleep and arousal; they may
be targets of Ganoderma.
There was a high degree of cross-correlation among central active
components, other components, and target genes of Ganoderma. In the
central mechanism, Ganoderma mainly affects target genes in the pineal
body, amygdala nucleus, prefrontal cortex, cerebellum, and other
regions, which regulate rhythm-related physiological processes. In the
peripheral mechanism, Ganoderma mainly affects target genes in the
heart, thyroid gland, liver, and other organs. The target genes of
active components were highly expressed in the central and peripheral
organs, consistent with the important roles of active components.
Therefore, Ganoderma ameliorated insomnia by regulating central and
peripheral mechanisms.
The reverse disease enrichment results showed that Ganoderma has
potential as an adjuvant treatment for insomnia or for treating
neurological, cardiovascular, cerebrovascular, and digestive system
diseases through the extensive pharmacological activities of the
triterpenoid and sterol components. There is a bidirectional
relationship between the above diseases and insomnia. Accordingly, the
above diseases may change organism status and affect sleep. Therefore,
Ganoderma can carry out bidirectional intervention on insomnia and its
complications in the treatment of insomnia. This therapeutic advantage
is a result of multi-component and -target TCM. There may be active
components and targets in TCMs that have not been experimentally
verified, suggesting that additional pharmacological mechanisms should
be identified. The mechanism of action of Ganoderma must be verified in
various models, including—but not limited to—animal, network, and
multi-view models. In the future, updating and optimisation of
artificial intelligence algorithms and their fusion with multi-modal
data can provide new approaches to assess the molecular mechanisms of
action of TCMs with multiple components and targets.
Conclusions
Ganoderma is rich in multiple active components, corresponding to a
considerable number of target genes. On this basis, Ganoderma
intervenes in various biological processes and signalling pathways.
Macroscopically, Ganoderma intervenes in the central mechanism (pineal
body, amygdala nucleus, prefrontal cortex, and cerebellum) and
peripheral mechanism (heart, thyroid gland, and liver) to ameliorate
insomnia. In terms of the pharmacological mechanism, Ganoderma induces
immune regulation, cell apoptosis/survival, and cell cycle regulation;
it may affect biological processes such as circulatory metabolism,
synaptic signal regulation, and rhythm regulation. There is a high
degree of cross-correlation among the components, target genes, and
target organs of Ganoderma, which provides a scientific explanation for
its pharmacological activities. The findings of this study provide a
reference for determining the mechanism underlying the effect of
Ganoderma on insomnia and offer insights for future research.
Acknowledgements