Association Rule Analysis of HQC and Immune Inflammatory Indicators
The minimum confidence and minimum support were set to 50% and 30%, respectively. The relationships between HQC and immune-inflammatory indicators were obtained by using the Apriori module. HQC improved CRP and ESR with a confidence of 65.85% and 50.62%, respectively, based on the association rule analysis. Besides, all the lifting degrees exceeded 1. These results indicate that HQC is closely correlated with improved immune-inflammatory indices of AS (Table 1).
Table 1: Association rule analysis of HQC with immune-inflammatory indicators.
Items (LHS ⇒ RHS)
|
Support
|
Confidence
|
Lift
|
{HQC} ⇒ {CPR↓}
|
32.92%
|
65.85%
|
1.15
|
{HQC} ⇒ {ESR↓}
|
25.31%
|
50.62%
|
1.15
|
{HQC} ⇒ {C4↓}
|
17.69%
|
35.40%
|
1.11
|
{HQC} ⇒ {IGA↓}
|
15.23%
|
30.45%
|
1.08
|
Note: CRP, C-reactive protein; ESR, erythrocyte sedimentation rate; C4, complement C4; IgA, immunoglobulin A. Values are regarded to be % degrees of relevancy.
Improvement of Immune Inflammatory Indices
The clinical immune inflammatory indices, such as ESR, CRP, IgA, IgM, IgG, and C4, were selected for validation to observe the specific situations of AS patients in the two groups after treatment. The standards of the aforesaid indices in both groups were reduced after treatment in comparison to those before treatment (all p ≤ 0.01, Table 2), while no change was observed in the IgM level. Meanwhile, the application of HQC could better reduce the levels of ESR, CRP, IgM, and IgA in AS patients compared with healthy individuals(Table 2).
Table 2: Changes in immune-inflammatory indices in two groups.
|
Control Group
|
Treatment Group
|
|
|
Before treatment
|
After treatment
|
P1 value
|
Before treatment
|
After treatment
|
P2 value
|
P3 value
|
ESR (mm/h)
|
19.50(10.00,34.00)
|
18.00(9.50,30.00)
|
≤0.001
|
29(15.00,55.00)
|
22.00(12.00,40.00)
|
≤0.001
|
≤0.001
|
CRP (mg/L)
|
15.67(4.79,36.80)
|
11.17(3.11,24.95)
|
≤0.001
|
21.55(9.04,46.18)
|
13.12(3.97,32.5)
|
≤0.001
|
≤0.001
|
IgA (g/L)
|
2.57(1.85,3.43)
|
2.53(1.85,3.38)
|
≤0.001
|
2.44(1.93,3.23)
|
2.41(1.87,3.17)
|
≤0.001
|
≤0.001
|
IgM (g/L)
|
1.00(0.75,1.34)
|
1.00(0.75,1.31)
|
0.483
|
1.07(0.83,1.34)
|
1.09(0.81,1.39)
|
≤0.001
|
≤0.001
|
IgG (g/L)
|
11.79(9.77,14.43)
|
11.74(9.72,14.3)
|
≤0.001
|
12.7(10.04,15.33)
|
12.50(10.05,14.70)
|
≤0.001
|
0.176
|
C4 (g/L)
|
24.30(0.37,31.10)
|
24.00(0.36,29.70)
|
≤0.001
|
27.00(0.40,31.10)
|
24.00(0.36,29.70)
|
≤0.001
|
0.683
|
Note: ESR, erythrocyte sedimentation rate; CRP, C-reactive protein; IgA, M, and G, immunoglobulin A, M, and G; C4, complement C4. P3 value: Comparison of inflammatory and immune indices between the two groups post-treatment.
Assessment of Immune Inflammation Indicators by the Random Walking Model
For the indicator of ESR, there were 180 comprehensive evaluations recorded in the control group, and 280 comprehensive evaluations recorded in the treatment group. The improvement coefficient of the control and the treatment groups was 0.2944 and 0.3036, respectively. For each improvement of the patient's comprehensive indicators, 7.87 steps were needed for the clinical significance of the control group, while only 6.07 steps were needed for the treatment group. For the CRP index, the control group recorded 194 comprehensive evaluations, and the treatment group recorded 300 comprehensive evaluations. The improvement coefficient of the control and the treatment groups was 0.2629 and 0.4433, respectively. For each improvement of the patient's comprehensive indicators, 8.57 steps were needed for the clinical significance of the control group, while only 4.04 steps were needed for the treatment group. For the indicator of C4, 141 comprehensive evaluations were recorded in the control group, and 158 comprehensive evaluations were recorded in the treatment group. The improvement coefficient of the control and the treatment groups was 0.3901 and 0.4304, respectively. For each improvement of the patient’s comprehensive indicators, 6.87 steps were needed for the clinical significance of the control group, while only 5.84 steps were needed for the treatment group. For the index of IgA, 141 comprehensive evaluations were recorded in the control group, and 158 comprehensive evaluations were recorded in the treatment group. The improvement coefficient of the control g and the treatment groups was 0.2340 and 0.2405, respectively. For each improvement of the patient's comprehensive indices, 11.45 steps were needed for the clinical significance of the control group, while only 10.45 steps were needed for the treatment group. For the index of IgG, 141 comprehensive evaluations were recorded in the control group and 158 comprehensive evaluations were recorded in the treatment group. The improvement coefficient of the control and the treatment groups was 0.1560 and 0.2025, respectively. For each improvement of the patient's comprehensive indices, 17.18 steps were needed for the clinical significance of the control group, while only 12.41 steps were needed for the treatment group. Collectively, we conclude that HQC can better improve patients' immune inflammatory indicators (Table 3, Figure 1).
Table 3: Assessment of immune inflammation factors by the random walking model.
Index
|
Group
|
Maximum random Fluctuation
|
Walking positive
growth rate
|
Random fluctuation
power law value
|
Improvement
coefficient
|
Comprehensive evaluation records
|
Ratio
|
ESR
|
Control Group
|
53
|
0.1271
|
0.2472±0.1117
|
0.2944
|
180
|
7.87
|
Treatment Group
|
85
|
0.1647
|
0.2826±0.1331
|
0.3036
|
280
|
6.07
|
CRP
|
Control Group
|
51
|
0.1167
|
0.3493±0.1517
|
0.2629
|
194
|
8.57
|
Treatment Group
|
133
|
0.2477
|
0.2931±0.1184
|
0.4433
|
300
|
4.04
|
C4
|
Control Group
|
55
|
0.1455
|
0.4297±0.2025
|
0.3901
|
141
|
6.87
|
Treatment Group
|
68
|
0.1713
|
0.1947±0.1067
|
0.4304
|
158
|
5.84
|
IgA
|
Control Group
|
33
|
0.0873
|
0.2899±0.1495
|
0.2405
|
141
|
11.45
|
Treatment Group
|
38
|
0.0957
|
0.2769±0.1181
|
0.2340
|
158
|
10.45
|
IgG
|
Control Group
|
22
|
0.0582
|
0.1682±0.0950
|
0.1560
|
141
|
17.18
|
Treatment Group
|
32
|
0.0806
|
0.2640±0.1168
|
0.2025
|
158
|
12.41
|
Note: ESR, erythrocyte sedimentation rate; CRP, C-reactive protein; IgA, M, and G, immunoglobulin A, M, and G; C4, complement C4.
Potential Active Ingredients of HQC Drugs
Finally, 90 kinds of active ingredients of HQC were obtained, including 36 kinds of Scutellariae Radix, 15 kinds of Gardeniae Fructus, 23 kinds of Persicae Semen, 7 kinds of Radix Clematidis, and 9 kinds of Coicis Semen. Two kinds of ingredients were shared by more than two kinds of TCM. As there are many active ingredients in HQC, only 25 items are listed, as shown in Table 4.
Table 4: Some active ingredients of Huangqin Qingre Chubi Capsule (HQC).
Herb Name
|
Mol ID
|
Molecule Name
|
OB
|
DL
|
Scutellariae
Radix
|
MOL001689
|
acacetin
|
34.97
|
0.24
|
MOL000173
|
wogonin
|
30.68
|
0.23
|
MOL000228
|
(2R)-7-hydroxy-5-methoxy-2-phenylchroman-4-one
|
55.23
|
0.2
|
MOL002714
|
baicalein
|
33.52
|
0.21
|
MOL002909
|
5,7,2,5-tetrahydroxy-8,6-dimethoxyflavone
|
33.82
|
0.45
|
Gardeniae Fructus
|
MOL001406
|
crocetin
|
35.3
|
0.26
|
MOL001941
|
Ammidin
|
34.55
|
0.22
|
MOL004561
|
Sudan III
|
84.07
|
0.59
|
MOL000098
|
quercetin
|
46.43
|
0.28
|
MOL000358
|
beta-sitosterol
|
36.91
|
0.75
|
Radix Clematidis
|
MOL005235
|
Embelin
|
37.72
|
0.18
|
MOL000449
|
Stigmasterol
|
43.83
|
0.76
|
MOL005603
|
Heptyl phthalate
|
42.26
|
0.31
|
MOL000263
|
oleanolic acid
|
29.02
|
0.76
|
MOL005592
|
Clematisprosapogenin,Cp7a_qt
|
12.62
|
0.76
|
Coicis Semen
|
MOL001323
|
Sitosterol alpha1
|
43.28
|
0.78
|
MOL001494
|
Mandenol
|
42
|
0.19
|
MOL002372
|
(6Z,10E,14E,18E)-2,6,10,15,19,23-hexamethyltetracosa-2,6,10,14,18,22-hexaene
|
33.55
|
0.42
|
MOL002882
|
[(2R)-2,3-dihydroxypropyl] (Z)-octadec-9-enoate
|
34.13
|
0.3
|
MOL000359
|
sitosterol
|
36.91
|
0.75
|
Persicae Semen
|
MOL001323
|
Sitosterol alpha1
|
43.28
|
0.78
|
MOL001328
|
2,3-didehydro GA70
|
63.29
|
0.5
|
MOL001329
|
2,3-didehydro GA77
|
88.08
|
0.53
|
MOL001340
|
GA120
|
84.85
|
0.45
|
MOL001342
|
GA121-isolactone
|
72.7
|
0.54
|
Prediction of Drug Ingredients and Disease-associated Targets
A total of 1,312 target genes were acquired by searching the targets corresponding to HQC active components in TCMSP. Finally, 179 target genes were obtained by removing the duplicate targets and standardized names using UniProt. The larger node reflected the greater degree value of a node (Figure 2). With "ankylosing spondylitis" as the keyword, the disease-associated targets were screened based on the GeneCards, OMIM, Drugbank, PharmGkb, and TTD databases, and 1,979 genes were finally obtained by deleting the duplicate values after summarizing.
Analysis of PPI Network Topology and Screening of Core Targets
First, the Venn analysis of 179 common action targets corresponding to HQC active components and 1,979 AS-related targets showed that 47 intersection genes were obtained, which are the potential action targets of HQC in AS therapy (Figure 3). Then, input the cross target into the String database and import it into the Cytoscape 3.9.1 software for analysis. It could be observed that VEGFA, CXCL8, PTGS2, PPARG, Intercellular cell adhesion molecule-1(ICAM1), Myeloperoxidase(MPO) and FOS may be the most important key targets (Figure 4).
Pathway Enrichment Results
From the findings of the GO functional enrichment analysis, we observed that there were 107 GO annotation items. Biological processes (BP) mainly involve aging, cellular response to hypoxia, negative modulation of the apoptotic process, as well as positive regulation of transcription from RNA polymerase II promoter and phosphatidylinositol 3-kinase signaling. Cellular component (CC) mainly involves the extracellular region, extracellular space, intracellular membrane-bounded organelle, and chromatin. Molecular function (MF) mainly involves transcription factor activity, growth factor activity, sequence-specific DNA binding, enzyme binding, chromatin binding, RNA polymerase II sequence-specific DNA binding, and transcription factor binding (Figure 5).
The enrichment analysis of KEGG pathway showed that HQC may play an anti inflammatory role by regulating IL-17, Th1 and Th2 cell differentiation, NF kappa B, TNF, T-cell receptor, c-type lectin receptor, toll like receptor, pathogenic E. coli infection, human T-cell leukemia virus 1 infection and Th17 cell differentiation (Figure 6).
Component-Target-Pathway Network Diagram
Through network analysis, it was found that the top 5 targets were PTGS2, FOS, RELA, PPARG, and VEGFA based on the order of degree value. Following the degree values of active ingredients, the top 5 active ingredients were beta-sitosterol, Stigmasterol, quercetin, Baicalein, and wogonin. It is suggested that these components and targets may be important components and targets for HQC in the treatment of AS (Figure 7).
Molecular Docking results
The binding energy of the components, the targets, and the number of hydrogen bonds formed are important indicators to evaluate the binding ability. The increase in the number of hydrogen bonds reflects a more stable binding. According to the data, 70% of the binding energy was under -4.25 kcal/mol, and 53% of the binding energy was -5.0 kcal/mol below, of which the binding energy of stigmasterol with PPARG, CXCL8, and CAT were under -7.50 kcal/mol. This indicated that the chemical active ingredients in HQC formula had high binding activity with inflammatory targets(Figure 8-9).
Experimental Validation Results
The experimental results revealed that increased serum PTGS2 levels and reduced serum levels of PPARG and CAT were witnessed in AS patients before treatment compared with healthy individuals (P < 0.01). HQC can make PTGS2 low expression and PPARG and CAT high expression(P < 0.01; Figure 10).