第1页
Clinical efficacy of Yiqi Yangxue
formula on knee osteoarthritis and
unraveling therapeutic
mechanism through plasma
metabolites in rats
Ting Zhao1†
, Shiqi Wang1†
, Wenbin Liu2†
, Jiayan Shen1
,
Youwu Dai 3
, Mingqin Shi 3
, Xiaoyi Huang3
, Yuanyuan Wei 3
, Tao Li 4
,
Xiaoyu Zhang1
, Zhaohu Xie 3
, Na Wang5
*, Dongdong Qin3
* and
Zhaofu Li 3
*
1
The First School of Clinical Medicine, Yunnan University of Chinese Medicine, Kunming, China, 2
The
Central Hospital of Enshi Tujia and Miao Autonomous Prefecture, Enshi, China, 3
School of Basic Medical
Sciences, Yunnan University of Chinese Medicine, Kunming, China, 4
Qujing Hospital Affiliated to Yunnan
University of Traditional Chinese Medicine, Qujing, China, 5
Institutes of Integrative Medicine, Fudan
University, Shanghai, China
Objective: To observe the clinical efficacy and safety of Yiqi Yangxue formula
(YQYXF) on knee osteoarthritis (KOA), and to explore the underlying therapeutic
mechanism of YQYXF through endogenous differential metabolites and their
related metabolic pathways.
Methods: A total of 61 KOA patients were recruited and divided into the treatment
group (YQYXF, 30 cases) and the control group (celecoxib, Cxb, 31 cases). Effects
of these two drugs on joint pain, swelling, erythrocyte sedimentation rate (ESR)
and c-reactive protein (CRP) were observed, and their safety and adverse reactions
were investigated. In animal experiments, 63 SD rats were randomly divided into
normal control (NC) group, sham operation (sham) group, model (KOA) group,
Cxb group, as well as low-dose (YL), medium-dose (YM), and high-dose groups of
YQYXF (YH). The KOA rat model was established using a modified Hulth method.
Ultra-high-performance liquid chromatography/Q Exactive HF-X Hybrid
Quadrupole-Orbitrap Mass (UHPLC-QE-MS)-based metabolomics technology
was used to analyze the changes of metabolites in plasma samples of rats.
Comprehensive (VIP) >1 and t-test p < 0.05 conditions were used to screen
the disease biomarkers of KOA, and the underlying mechanisms of YQYXF were
explored through metabolic pathway enrichment analysis. The related markers of
YQYXF were further verified by ELISA (enzyme-linked immunosorbent assay).
Results: YQYXF can improve joint pain, swelling, range of motion, joint function,
Michel Lequesen index of severity for osteoarthritis (ISOA) score, Western Ontario
and McMaster Universities Osteoarthritis Index (WOMAC) score, ESR, and CRP. No
apparent adverse reactions were reported. In addition, YQYXF can improve
cartilage damage in KOA rats, reverse the abnormal changes of 16 different
metabolites, and exert an anti-KOA effect mainly through five metabolic
pathways. The levels of reactive oxygen species (ROS) and glutathione (GSH)
were significantly decreased after the treatment of YQYXF.
OPEN ACCESS
EDITED BY
Xiao-Ling Xu,
Zhejiang Shuren University, China
REVIEWED BY
Venketesh Sivaramakrishnan,
Sri Sathya Sai Institute of Higher Learning
(SSSIHL), India
Heather Walker,
The University of Sheffield,
United Kingdom
Elizabeth R. Lusczek,
University of Minnesota Twin Cities,
United States
*CORRESPONDENCE
Zhaofu Li,
lzf0817@126.com
Na Wang,
18203638814@163.com
Dongdong Qin,
qindong108@163.com
†
These authors have contributed equally
to this work.
SPECIALTY SECTION
This article was submitted
to Human and Medical Genomics, a
section of the journal
Frontiers in Genetics
RECEIVED 12 November 2022
ACCEPTED 23 March 2023
PUBLISHED 05 April 2023
CITATION
Zhao T, Wang S, Liu W, Shen J, Dai Y,
Shi M, Huang X, Wei Y, Li T, Zhang X, Xie Z,
Wang N, Qin D and Li Z (2023), Clinical
efficacy of Yiqi Yangxue formula on knee
osteoarthritis and unraveling therapeutic
mechanism through plasma metabolites
in rats.
Front. Genet. 14:1096616.
doi: 10.3389/fgene.2023.1096616
COPYRIGHT
© 2023 Zhao, Wang, Liu, Shen, Dai, Shi,
Huang, Wei, Li, Zhang, Xie, Wang, Qin and
Li. This is an open-access article
distributed under the terms of the
Creative Commons Attribution License
(CC BY). The use, distribution or
reproduction in other forums is
permitted, provided the original author(s)
and the copyright owner(s) are credited
and that the original publication in this
journal is cited, in accordance with
accepted academic practice. No use,
distribution or reproduction is permitted
which does not comply with these terms.
Frontiers in Genetics 01 frontiersin.org
TYPE Original Research
PUBLISHED 05 April 2023
DOI 10.3389/fgene.2023.1096616
第2页
Conclusion: YQYXF can significantly improve the clinical symptoms of KOA
patients without obvious adverse reactions. It mainly improved KOA through
modulating lipid metabolism-related biomarkers, reducing lipid peroxidation and
oxidative stress.
KEYWORDS
knee osteoarthritis, YQYXF, clinical efficacy, metabolome, biomarkers
Introduction
Knee osteoarthritis (KOA) is the most prevalent form of arthritis
characterized by a degeneration of articular cartilage resulting in the
development of osteophytes, or bone spurs (Horecka et al., 2022).
The global prevalence of KOA is around 3.8% (Kao et al., 2022).
KOA is closely associated with age, as radiographic evidence of KOA
occurs in most people over the age of 65 years (Lespasio et al., 2017).
Furthermore, the incidence of KOA increases with a higher average
weight of the population, particularly in obese women (Zhang and
Jordan, 2010). Strenuous physical activity, especially activities
requiring kneeling, knee-bending, squatting, and prolonged
standing, as well as knee trauma and injury have also been
linked to a high prevalence of KOA (Heidari, 2011).
Although the mechanisms of degenerative changes are betterunderstood thanks to numerous biochemical and genetic studies,
drugs that can stop the degenerative cascade remain unknown. So
far, arthritis have been managed pharmacologically and nonpharmacologically, including common pharmacotherapies,
surgery, and lifestyle changes. All available forms of KOA
therapy are based on symptomatic treatment, such as pain relief
and joint function improvement (Nowaczyk et al., 2022). Pain
medications, including the most popular non-steroidal antiinflammatory drugs (NSAIDs), are the first-line treatment
(Gnylorybov et al., 2020). Surgery should be considered only in
the case of no improvement and the presence of advanced lesions
visible in imaging tests. Currently, an increasing number of studies
are being published suggesting that traditional Chinese medicine
may be as effective or even more effective than NSAIDs and result in
fewer systemic adverse effects (Glyn-Jones et al., 2015; Wang et al.,
2020). Yiqi Yangxue formula (YQYXF) is a prescribed Chinese
herbal formula for treating KOA based on the traditional Chinese
medicine theory. The YQYXF consists of astragalus, codonopsis,
tangerine peel, cohosh, bupleurum, angelica, atractylodes, cassia
twig, white peony, licorice, divaricate saposhniovia root, ligusticum
wallichii, rhizoma drynariae, epimedium, a total of 14 herbs. In our
previous study, YQYXF could inhibit the levels of matrix
metalloproteases 1 (MMP-1) and MMP-13, promoting
chondrocyte proliferation (Duan R. et al., 2020). However, the
potential mechanism of YQYXF in treating KOA is still unclear.
In the present study, we aimed to evaluate the clinical efficacy
and safety of YQYXF in patients with KOA. We observed the effects
of YQYXF and celecoxib (Cxb) on visual analogue scale (VAS) score,
swelling, range of motion (ROM) and joint function, Michel
Lequesen index of severity for osteoarthritis (ISOA) score, the
Western Ontario and McMaster Universities Osteoarthritis Index
(WOMAC), Kellgren-Lawrence score, erythrocyte sedimentation
rate (ESR) and c-reactive protein (CRP) index of KOA patients
(Kellgren and Lawrence, 1957; Brosseau et al., 2003; Zhang et al.,
2009; Anil et al., 2021). The safety and adverse reactions were
investigated by blood cell analysis (white blood cell, red blood
cell, hemoglobin, and platelet), liver function (alanine
transaminase, aspartate aminotransferase), and kidney function
(blood urea nitrogen, creatinine) (Wu et al., 2021). In addition,
we used the KOA rat model to further analyze the changes of
metabolites in rat plasma samples using metabonomics technologies
based on ultra-high-performance liquid chromatography/Q
Exactive HF-X Hybrid Quadrupole-Orbitrap Mass (UHPLC-QEMS) (Xiao et al., 2012; Wang et al., 2014). The potential mechanism
of YQYXF on endogenous differential metabolites and related
metabolic pathways was also discussed, providing evidence for
the treatment of KOA.
Materials and methods
Clinical study design
Sample source and grouping
Sixty-one KOA patients (Kellgren-Lawrence score I-III) were
recruited from Yunnan Provincial Hospital of Traditional
Chinese Medicine. The patients were divided into a treatment
group with 30 patients (YQYXF) and a control group with
31 patients (celecoxib, Cxb). All patients fulfilled the
American College of Rheumatology criteria for primary KOA,
and the subjects agreed to sign the informed clinical consent. The
age was between 38 and 70 years old—patients who discontinued
NSAIDs for 7 days or more. The exclusion criteria included
patients with other rheumatic diseases, such as rheumatoid
arthritis, Sjögren’s syndrome, and gouty arthritis. In addition,
patients with allergies or severe other systemic diseases will not
participate in this study. The design scheme of this project has
been approved by the Medical Ethics Committee of Yunnan
University of Traditional Chinese Medicine (ethics number:
2019YXLL005).
Experimental drugs and treatments
YQYXF granules, provided by Jiangyin Tianjiang
Pharmaceutical Co., Ltd. YQYXF granules consist of astragalus
30 g, codonopsis 15 g, tangerine peel 10 g, cohosh 10 g,
bupleurum 10 g, angelica 20 g, cassia twig 15 g, white peony 15 g,
atractylodes 15 g, licorice 5 g, divaricate saposhniovia root 15 g,
ligusticum wallichii 15 g, rhizoma drynariae 15 g, epimedium
15 g. The Cxb capsules, provided by Ruihui Pharmaceutical Co.,
Ltd., are approved by Chinese medicine J20080059. In this study, the
treatment group was given YQYXF, one bag/time, three times a day.
The control group was given 200 mg/day of Cxb capsules once times
a day.
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Observation indicators and methods
All patients were evaluated using the VAS score and ISOA
score, WOMAC, Kellgren-Lawrence score, range of motion
(ROM), and joint function grades before the treatment and at
4 weeks after treatment (Kellgren and Lawrence, 1957; Brosseau
et al., 2003; Zhang et al., 2009; Anil et al., 2021). ESR and CRP
were detected before treatment and on the fourth weekend of
treatment, respectively. ESR was detected by the ESR analyzer.
C-reactive protein (CRP) was detected by immunoturbidimetry.
The Kellgren-Lawrence grading system for KOA is the most
widely used method and has become a widely accepted
method for the diagnosis of KOA, which is a grading method
for the severity of KOA. According to X-ray findings of the knee
joint, grading of the severity of KOA can be divided into grade 0
(normal knee joint), grade I, grade II, grade III, and grade IV (the
most severe KOA) (Kellgren and Lawrence, 1957; Zeng et al.,
2017; Di Martino et al., 2022). Grading of joint function can be
divided into four grades. Grade I refers to various activities that
can be done. Grade II refers to moderate limitation. Although one
or more joints are uncomfortable or have limited movement, they
can still engage in normal activities. Grade III refers to limited
actions and can only take care of themselves but cannot engage in
general activities. Grade IV refers to lying in bed or sitting in bed
and you cannot take care of yourself (Zheng, 2002). Joint pain
(VAS of patient and physician) was scored using a 10-cm visual
analog scale (VAS), and the patients were instructed to mark the
corresponding position on the VAS that represented their pain
(Abbott et al., 2013; Su et al., 2018). 0 cm: no pain; 1–3 cm: mild
pain, but still able to engage in normal activities; 4–6 cm:
moderate pain, affecting work, but able to take care of
themselves; 7–9 cm: severe pain, unable to take care of
themselves; 10 cm: extreme pain. The efficacy evaluation, joint
function, swelling, and range of motion in this study are
determined according to the guiding principles for clinical
research of new drugs of traditional Chinese medicine (Zheng,
2002). Highly effective: pain and swelling disappear, joint activity
is normal, and the score decreases by ≥ 95%. Moderately effective:
pain and swelling disappear, joint activity is not limited, and
score decreases ≥70% and <95%. Lowly effective: pain and
swelling symptoms are basically eliminated, joint activity is
slightly limited, and the score decreased by ≥ 30% and <70%.
Ineffective: pain, swelling, and joint range of motion did not
improve significantly, and the score decreased by < 30%.
Animal experimental design
Preparation of experimental drugs
The 14 herbs in YQYXF are provided by the Chinese Pharmacy
of the First Affiliated Hospital of Yunnan University of Traditional
Chinese Medicine, and their composition and dosage are the same as
those of YQYXF granules. The high dose group of YQYXF was
administered by gavage with an aqueous solution containing 18.4 g
of crude drug/kg, the medium dose group was administered with
9.2 g of crude drug/kg, and the low dose group was administered
with 4.6 g of crude drug/kg of rats (respectively equivalent to 0.25,
0.5, and 1 time of the human clinical equivalent dose according to
the body surface area dose conversion method of humans and rats
Meeh-Rubner formula). In the positive drug group, 18 mg Cxb/kg
aqueous solution was administered by gavage. Cxb capsules,
provided by Ruihui Pharmaceutical Co., Ltd., approved by
Chinese medicine J20080059.
Identification of the compounds in YQYXF by
UHPLC-QE-MS
Compounds in YQYXF were analyzed using a UHPLC system
(Vanquish, Thermo Fisher Scientific) equipped with a waters
UPLC BEH C18 column (1.7 μm 2.1 100 mm), and the flow rate
was set to 0.5 mL/min, and an injection volume was set to 5 μL.
Mobile phase A consisted of 0.1% formic acid solution, and
mobile phase B was 0.1% formic acid in acetonitrile. The
multi-step linear elution gradient program was as follows:
0–11 min, 85%–25% A; 11–12 min, 25%–2% A; 12–14 min,
2%–2% A; 14–14.1 min, 2%–85% A. During each acquisition
cycle, the mass range was from 100 to 1,500, the top four of
every process were screened, and the corresponding MS/MS data
were further acquired. Sheath gas flow rate: 35 Arb, Aux gas flow
rate: 15 Arb, Ion Transfer Tube Temp: 350°
C, Vaporizer Temp:
350°
C, Full ms resolution: 60,000, MS/MS resolution: 15,000,
Collision energy: 16/32/48 in NCE mode, Spray Voltage: 5.5 kV
(positive) or −4 kV (negative). An Orbitrap Exploris 120 mass
spectrometer coupled with Xcalibur software was employed to
obtain the MS and MS/MS data information of YQYXF based on
the IDA acquisition mode. The raw data of mass spectra were
imported into XCMS software for processing, such as retention
time correction, peak identification, peak extraction, peak
integration, and peak alignment. The peak information of
compounds was searched through the in-house secondary
mass spectrometry database provided by Shanghai BIOTREE
Biotech Co., Ltd.
Administration of the KOA rat model
Sixty-three SPF-grade female SD rats (180 ± 20 g) were
purchased from Hunan Slike Jingda Laboratory Animal Co.,
Ltd., license number: SCXK (Xiang) 2019–0004. The
experiments were conducted under full authorization from the
Ethics Committee of Yunnan University of Chinese Medicine
(ethical code no. R-062019065). The rats were randomly divided
into seven groups, including normal control (NC), shamoperated (sham), model (KOA), Cxb (18 mg/kg), YQYXF low-,
middle-, and high-dose groups (18.4, 9.2, and 4.6 g of crude
drug/kg, respectively). Each group had nine rats. The KOA
models were established by the modified Hulth method
(Rogart et al., 1999). The anterior ligament was severed, and
the medial meniscus was removed with the tibial joint reduction
(Gu et al., 2021). The knee in the sham group was only treated
with joint capsule opening and suturing. The operation was
conducted in an aseptic environment. After the successful
modeling, the NC group and the sham group were provided
with normal drinking water and diet. The rest were given the
corresponding drug suspension by gavage once a day for eight
consecutive weeks. The plasma was collected by centrifugation,
and the right knee joint was taken. The knee joints were fixed
with 10% neutral formaldehyde solution and decalcified with
10% EDTA for 56 days. The tissue was embedded in paraffin and
sliced with a thickness of 5 μm.
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Hematoxylin-eosin (HE) staining
Routine dewaxing, rinsed with tap water, stained with
hematoxylin solution for 5 min, dehydrated in acid water and
ammonia, rinsed with tap water, dehydrated and stained with
eosin for 3 min. Dehydrated from low to high concentrations of
alcohol, clear, sealed with neutral glue.
Metabolites extraction and UHPLC-QE-MS analysis
Add 400 μL of extract (methanol: acetonitrile = 1:1 (V/V),
containing isotope-labeled internal standard mixture) to 100 μL
of plasma and vortex to mix for 30 s. Sonicate for 10 min and let
stand at −40°
C for 1 h, centrifuge at 12,000 rpm for 15 min at 4°
C,
and collect the supernatant for assay. The quality control (QC)
sample was prepared by mixing an equal aliquot of the supernatants
from all plasma samples. UHPLC-QE-MS analyses were performed
using a UHPLC system (Vanquish, Thermo Fisher Scientific) with a
UPLC BEH Amide column (2.1 mm × 100 mm, 1.7 μm) coupled to
Q Exactive HFX mass spectrometer (Orbitrap MS, Thermo). The
mobile phase consisted of 25 mmol/L ammonium acetate and
25 mmol/L ammonia hydroxide in water (A) and acetonitrile (B).
The auto-sampler temperature was 4°
C, and the injection volume
was 2 μL. The QE HFX mass spectrometer was used for its ability to
acquire MS/MS spectra in information-dependent acquisition mode
in the control of the acquisition software (Xcalibur, Thermo). In this
mode, the acquisition software continuously evaluated the full scan
MS spectrum. The ESI source conditions were set as follows: sheath
gas flow rate as 30 Arb, Aux gas flow rate as 25 Arb, capillary
temperature as 350°
C, full MS resolution as 60,000, MS/MS
resolution as 7,500, collision energy as 10/30/60 in NCE mode,
spray Voltage as 3.6 kV (positive) or −3.2 kV (negative),
respectively. The raw data were converted to the mzXML format
using ProteoWizard and processed with an in-house program,
which was developed using R and based on XCMS, for peak
detection, extraction, alignment, and integration. Then an inhouse MS2 database (BiotreeDB) was applied in metabolite
annotation. The cutoff for annotation was set at 0.3. The Thermo
Q Exactive HFX mass spectrometer is capable of primary and
secondary mass spectral data acquisition under the control of the
acquisition software (Xcalibur, Thermo).
Principal components analysis (PCA) and orthogonal
correction partial least squares discriminant analysis (OPLSDA) were conducted using the SIMCA16.0.2 software package
(Sartorius Stedim Data Analytics AB, Umea, Sweden). PCA, an
unsupervised analysis that reduces the dimension of the data, was
carried out to visualize the distribution and the grouping of the
samples. A 95% confidence interval in the PCA score plot was
used as the threshold to identify potential outliers in the dataset.
In order to visualize group separation and find significantly
changed metabolites, supervised orthogonal projections to
latent structures-discriminate analysis (OPLS-DA) were
applied. Then, 7-fold cross-validation was performed to
examine the quality of the model. Permutation tests were used
to test the validity of the model. The first principal component of
variable importance in the projection (VIP) and Student’s t-test
were obtained to refine the analysis. Suppose VIP>1 and p < 0.05,
the variable was defined as a significantly different metabolite
between the two groups. The significantly different metabolites
were used for plotting hierarchical clustering based on the
Euclidean distance formula and drawn heat maps using the
Pheatmap package in R studio. The volcano plots were used to
filter the metabolites of interest based on Log 2 (fold change)
and–Log 10 (p-value). The Kyoto Encyclopedia of Genes and
Genomes (KEGG, http://www.genome.jp/kegg/) and
MetaboAnalyst (http://www.metaboanalyst.ca/) databases were
used for pathway enrichment analysis.
The determination of the content of lipid
peroxidation-related indexes
The plasma of the rats was collected, and the levels of lipid
peroxidation-related indexes, such as reactive oxygen species (ROS)
and glutathione (GSH), were tested by enzyme-linked
immunosorbent assay (ELISA). The ELISA kit (Jiangsu Jingmei
Biological Technology Co., Ltd., China) was used according to the
manufacturer’s instructions.
Statistical method
The data were processed and analyzed by using SPSS
26.0 software. If the data followed the normal distribution, they
were presented as mean ± SD (standard deviation). Data were
compared for differences using two independent samples t-tests
or one-way ANOVA. If the data were not normally distributed, they
were presented as median (IQR, interquartile range), and a nonparametric test was adopted, and p < 0.05 was considered
statistically significant.
Results
Clinical experiments
Participant’s characteristics
As illustrated in Table 1, the ages of the treatment group and
control group were 57.30 ± 7.82 years and 56.94 ± 7.95 years,
respectively. There was no significant difference in age between
the two groups (p = 0.97). Among the treatment group, 4 males
(13.33%) and 26 females (86.67%). While in the control group,
5 were males (16.13%) and 26 were females (83.87%). There was
no significant difference in gender between the two groups (p =
0.76). The disease duration of the treatment and control groups
were 46.33 ± 21.34 months and 45.29 ± 20.92 months,
respectively. There was no significant difference in disease
duration between the two groups (p = 0.84). In grading of
severity of KOA assessed by Kellgren-Lawrence score grading,
6 cases were grade I, 20 were grade II, and 4 were grade III among
the treatment group. While, in the control group, 7 cases were
grade I, 19 were grade II, and 5 were grade III. There was no
significant difference in severity of KOA between the two groups
(p = 0.99). The joint function grades in the treatment group
included 10 cases of grade I, 18 cases of grade II, and 2 cases of
grade III. In comparison, the control group had 11 cases of grade
I, 18 cases of grade II, and 2 cases of grade III. There was also no
significant difference in joint function between the two groups
(p = 0.87). Therefore, the age, gender, disease duration, severity of
arthritis, and joint function of the two groups of patients are
comparable, and follow-up research can be carried out.
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Efficacy evaluation
The clinical observation results showed that 3 (10%) cases were
highly effective, 17 (56.67%) cases were moderately effective, 9
(30%) cases were lowly effective, and 1 (3.33%) case was
ineffective, with a total effective rate of 96.67% in the treatment
group. In the control group, 2 (6.45%) cases were highly effective, 15
(48.39%) cases were moderately effective, 12 (38.71%) cases were
lowly effective, and 2 (6.45%) cases were ineffective, and the total
effective rate was 93.55% (all p > 0.05) (Figure 1A). The VAS score of
patients in the treatment group was 4.23 ± 1.19 before
administration and 1.46 ± 0.93 after 4 weeks of administration
(p = 2.81 × 10−14). The VAS score of patients in the control
group was 4.35 ± 1.20 before administration and 1.86 ±
0.83 after 4 weeks of administration (p = 1.14 × 10−13). In the
treatment group, the VAS score of physician was 4.20 ±
0.92 before administration and 1.73 ± 0.79 after 4 weeks of
administration (Figure 1B, p = 5.44 × 10−16). In the control
group, the VAS score of physician was 4.10 ± 1.25 before
administration, and the VAS score of physician was 1.97 ±
0.66 after 4 weeks of administration (Figure 1B, p = 1.07 × 10−11).
In the treatment group, the medium of swelling score was
2.00 before administration and 0.00 after 4 weeks of
administration (Figure 1C, p = 1.80 × 10−5
). The swelling score
of the control group was 2.00 before administration and 0 after
4 weeks of administration (Figure 1C, p = 1.10 × 10−5
). In the
treatment group, the joint range of motion (ROM) was 2.00 before
administration and 0.00 after 4 weeks of administration (Figure 1D,
p = 9.40 × 10−7
). The ROM in the control group was 2.00 before
administration and 0.00 after 4 weeks of administration (Figure 1D,
p = 0.002). In the treatment group, ISOA score was 9.00 ±
1.80 before administration and 3.07 ± 1.36 after 4 weeks of
administration (Figure 1E, p = 8.49 × 10−21). The ISOA in the
control group was 8.74 ± 1.63 before administration and 4.10 ±
1.33 after 4 weeks of administration (Figure 1E, p = 4.78 × 10−18). In
the treatment group, the WOMAC score was 52.27 ± 6.74 before
administration and 16.13 ± 3.85 after 4 weeks of administration
(Figure 1F, p = 3.24 × 10−33). The WOMAC score of the control
group was 53.13 ± 6.38 before administration and 19.52 ± 3.71 after
4 weeks of administration (Figure 1F, p = 9.10 × 10−34). In the
treatment group, the ESR was 20.67 ± 8.21 (mm/h) before
administration and 10.03 ± 4.80 (mm/h) after 4 weeks of
administration (Figure 1G, p = 7.21 × 10−18). The ESR of the
control group was 20.90 ± 8.94 (mm/h) before administration
and 10.61 ± 3.07 (mm/h) after 4 weeks of administration
(Figure 1G, p = 1.90 × 10−7
). In the treatment group, the CRP
was 8.56 ± 3.05 (mg/L) before administration and 2.06 ± 1.15 (mg/L)
after 4 weeks of administration (Figure 1H, p = 3.12 × 10−15). The
CRP of the control group was 8.80 ± 2.81 (mg/L) before
administration and 2.09 ± 1.06 (mg/L) after 4 weeks of
administration (Figure 1H, p = 2.71 × 10−17). After drug
intervention, the joint function grades in the treatment group
included 22 cases of grade I, 8 cases of grade II, and 0 cases of
grade III, while the control group had 19 cases of grade I, 12 cases of
grade II, and 0 cases of grade III and no significant difference was
observed (p = 0.97).
Safety evaluation
Compared with before treatment, there was no significant
difference in safety indicators such as blood cell analysis (white
blood cell, red blood cell, hemoglobin, platelet), liver function
(alanine transaminase, aspartate aminotransferase), renal function
(blood urea nitrogen, creatinine), and electrocardiogram after
4 weeks of treatment (all p > 0.05) (Table 2). Our research has
proved that YQYXF is safe for KOA patients.
Animal experiment
Screening active components of YQYXF with
UHPLC-QE-MS
The compounds in YQYXF were identified by the UHPLC-QEMS method. A total of 447 compounds were characterized in
TABLE 1 Comparison of baseline characteristics between treatment group and control group.
Treatment group (n = 30) Control group (n = 31) p-value
Age, yrs, mean ± SD 57.30 ± 7.82 56.94 ± 7.95 0.97
Female sex, n (%) 26 (86.67) 26 (83.87) 0.76
Disease duration, months, mean ± SD 46.33 ± 21.34 45.29 ± 20.92 0.84
Grading of severity of KOA
Ⅰ, n (%) 6 (20.00) 7 (22.58) 0.99
Ⅱ, n (%) 20 (66.67) 19 (61.29)
Ⅲ, n (%) 4 (13.33) 5 (16.13)
Grading of joint function
Ⅰ, n (%) 10 (33.33) 11 (35.48) 0.87
Ⅱ, n (%) 18 (60.00) 18 (58.06)
Ⅲ, n (%) 2 (0.07) 2 (6.45)
Note: there were no significant differences in baseline characteristics between therapy group and control group.
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YQYXF (Figure 2A: positive ion modes; Figure 2B, negative ion
modes). Among these, 17 kinds of components were detected,
including flavonoids, phenols, terpenoids, amino acid derivatives,
phenylpropanoids, alkaloids, aromaticity aliphatic acyl, xanthones,
jasmonic acid, organic acids and derivatives, fatty acids, prenol
lipids, lipoic acids and derivatives, carboxylic acids and
derivatives, carbohydrates and derivatives, alkaloids, and
quinones. The peak area represents the relative abundance of the
substance, and ppm is the deviation between the measured mz value
of the substance and the theoretical mz value. ppm = (measured mz
value - theoretical mz value) × 1,000,000 ÷ theoretical mz value. The
leading substances were defined as the top 10 substances identified
by UHPLC-QE-MS analysis. As in Table 3, the top ten substances
were ranked from highest to lowest according to their respective
peak area. The larger the peak area, the higher the ranking.
Effects of YQYXF in KOA rats
The time flow chart of the experiment is shown in Figure 3A.
The body weight of the rats in each group showed a steadily
increasing trend (Figure 3B). The overall growth trend of the
body weight of the KOA group was lower than that of the NC
group. The weight gain trend of Cxb and YQYXF groups with
FIGURE 1
Clinical efficacy assessment. (A) Disease effectiveness comparison. (B) Joint pain VAS score. (C) Joint swelling score. (D) Joint range of motion
(ROM) score. (E) Michel Lequesen index of severity for osteoarthritis (ISOA) score. (F) WOMAC score. (G) Erythrocyte sedimentation rate (ESR). (H)
C-reactive protein (CRP). *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001.
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different doses was higher than that of KOA group, but there was no
significant difference in the body weight (p > 0.05). The point
indicated by the arrow was the cartilage surface (Figure 3C). The
NC and sham operation groups’ cartilage surfaces were smooth and
flat, without cracks and defects. Chondrocytes were orderly
arranged, clearly stratified, and evenly distributed, without
obvious cell clusters. In the model group, the cartilage surface
ulcer became thinner, and the local cartilage calcification layer
was ruptured and disappeared. Chondrocytes were disordered.
The stratification was not easy to recognize, and regional cell
clusters were apparent. The Cxb group’s cartilage surface was
smooth, without obvious cracks and defects, and the
chondrocytes were arranged in order with a regular hierarchical
structure. The cartilage surface was rough in the YQYXF low-dose
(YL) group, and some cartilage tissues were defective. The cartilage
surface was not smooth in the YQYXF medium (YM) dose
group. Some cartilages were defective or cracked, and the
chondrocytes were complex and disordered. The hierarchical
structure was obvious, and local cell clusters appeared. The
staining matrix was uniform. The cartilage surface in the YQYXF
high-dose (YH) group was smooth, without apparent defects
and tear.
Effects of YQYXF on potential biomarkers in KOA
rats
To further explore the effect of YQYXF on the endogenous
differential metabolites and their related metabolic pathways of
KOA, we used the plasma of rats in the NC group, KOA group,
and YH group for metabolomic analysis. We included QC samples
throughout the experimental process to ensure the stability and
reliability of the data and the system. The QC samples (yellow dots)
were closely clustered together, indicating that the UHPLC-QE-MS
system had good stability and was reliable for metabolomic analysis
of the samples. LC-MS data obtained from the plasma samples were
analyzed using PCA for metabolic changes between the NC, KOA,
YH, and QC samples (Figure 4A: positive ion modes; Figure 4B,
negative ion modes). In both the positive and negative ion modes, we
found a large deviation in 1 rat in the NC group, and no meaningful
results could be drawn. Therefore, we excluded it from further
analysis. The contribution ratio of principal component 1 (PC1) was
39.4%, and that of PC2 was 15.4% (Figure 4A: positive ion modes).
The contribution ratio of principal component 1 (PC1) was 22.2%,
and that of PC2 was 11.2% (Figure 4B, negative ion modes). In the
positive ion mode, the separation of KOA and NC samples was
insignificant. It is worth noting that the KOA samples were
significantly separated from the NC samples in the negative
mode plot, indicating significant metabolic differences between
the two groups. Meanwhile, YH and OA samples were separated,
but the separations were not significant in both positive and negative
ion modes. Due to the complex multidimensional characteristics of
metabolic data, unsupervised PCA model analysis alone could not
well distinguish group differences among samples. The OPLS-DA
model was employed to characterize the differential metabolites
among NC, KOA, and YH groups to further identify the differences
in the composition of the metabolites. R2 indicated how well the
variation of a variable was explained, and Q2 meant how well a
variable could be predicted. The replacement test established the
corresponding OPLS-DA model to obtain the R2 and Q2 values of the
random model by randomly changing the order of the classification
variable Y and repeating it for several times (n = 200), which played
TABLE 2 Safety index evaluation.
Project Group Before treatment After 4 weeks of treatment p-value
WBC (×109
/L) Treatment group 6.03 ± 1.17 5.58 ± 1.04 0.12
Control group 5.10 ± 0.63 5.14 ± 0.51 0.77
RBC (×109
/L) Treatment group 4.65 ± 0.28 4.70 ± 0.43 0.59
Control group 4.63 ± 0.52 4.84 ± 0.51 0.88
Hb (g/L) Treatment group 141.17 ± 7.30 141.47 ± 8.51 0.88
Control group 139.23 ± 10.70 143.94 ± 7.75 0.12
PLT (×109
/L) Treatment group 225.00 ± 41.55 217.40 ± 57.96 0.56
Control group 216.06 ± 43.89 228.45 ± 54.87 0.34
ALT (U/L) Treatment group 18.80 ± 7.83 16.87 ± 6.97 0.32
Control group 16.71 ± 7.92 19.26 ± 6.40 0.17
AST (U/L) Treatment group 21.57 ± 5.34 19.17 ± 5.36 0.09
Control group 18.71 ± 5.81 19.97 ± 4.18 0.33
BUN (mmol/L) Treatment group 4.80 ± 1.46 4.72 ± 1.22 0.82
Control group 5.00 ± 1.54 4.47 ± 1.02 0.12
Cr (umol/L) Treatment group 67.20 ± 11.74 69.10 ± 14.08 0.57
Control group 67.00 ± 12.84 67.58 ± 11.10 0.85
WBC, white blood cell; RBC, red blood cell; Hb, hemoglobin; PLT, platelet; ALT, alanine transaminase; AST, aspartate aminotransferase; BUN, blood urea nitrogen; Cr, creatinine, all p > 0.05.
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FIGURE 2
The total ion chromatograms (TIC) of YQYXF that were obtained in positive ion mode and negative ion mode. (A) UHPLC-QE-MS analysis base peak
intensity chromatograms of YQYXF in positive ion mode. (B) UHPLC-QE-MS analysis base peak intensity chromatograms of YQYXF in negative ion mode.
TABLE 3 Identification of components of YQYXF by UHPLC-QE-MS analysis (top 10).
Name Composite score Rtmed (s) Mzmed ppm Formula Peak area
3,5,7,8-tetramethoxy-2-(3,4,5-trimethoxyphenyl)chromen-4-one 0.78 399.66 433.15 1.04 C22H24O9 3.17×109
2″-O-beta-L-galactopyranosylorientin 0.63 88.34 609.15 2.69 C27H30O16 1.66×109
Herbacetin 1.00 132.90 303.05 1.25 C15H10O7 1.40×109
Isoliquiritigenin 0.99 101.62 257.08 3.29 C15H12O4 1.32×109
Biochanin-7-O-glucoside 0.90 98.83 447.13 0.00 C22H22O10 1.25×109
Liquiritin 0.72 102.92 417.12 3.15 C21H22O9 1.06×109
4-Methoxysalicylic acid 0.93 63.18 167.04 0.40 C8H8O4 9.81×108
Formononetin-7-O-glucoside 0.87 190.81 431.13 0.96 C22H22O9 9.71×108
Licoricesaponin H2 0.90 352.46 823.41 2.05 C42H62O16 8.85×108
Naringin 0.61 130.20 581.18 4.13 C27H32O14 8.51×108
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an essential role in avoiding the over-fitting of the test model and
evaluating the robustness of the model.
The OPLS-DA score plots showed an obvious separation
between the KOA and NC group in the positive and negative ion
mode from the metabolic profiles (Figure 5, A1: positive ion, A2:
negative ion). The permutation test results R2
Y and Q2 between the
KOA and NC groups were respectively 0.98 and 0.40 in the positive
ion mode and 0.99 and 0.58 in negative ion mode (Figure 5, B1:
positive ion, B2: negative ion). The YH and KOA groups OPLS-DA
scores plots were also well separated in the positive and negative ion
mode (Figure 5, C1: positive ion, C2: negative ion); R2
Y and Q2 were
respectively, 0.99 and 0.72 in the positive ion mode and 0.99 and
0.68 in the negative ion mode (Figure 5, D1: positive ion, D2:
negative ion). All R2
Y were very close to 1, indicating that the
established model conformed to the real situation of the sample data.
The intercept between the regression line of Q2 and the longitudinal
axis was less than zero. Meanwhile, with the gradual reduction of
displacement retention, the proportion of the Y variable of
displacement increased, and the Q2 of random model gradually
decreased. It showed that the model in this study had good
robustness, and there was no over-fitting phenomenon.
Therefore, the OPLS-DA results further confirmed the successful
establishment of our OA rat model and that YH administration
could regulate the metabolic profile of the rat.
FIGURE 3
Effects of YQYXF in OA rats. (A) Time flow chart. (B) Effects of YQYXF on body weight. (C) Cartilage tissue HE staining. NC: normal control group,
sham: sham operation group, OA: model group, Cxb: celecoxib, YL: low-dose groups of YQYXF, YM: medium-dose groups of YQYXF, YH: high-dose
groups of YQYXF.
FIGURE 4
PCA score plots of the QC, NC, KOA, and YH groups. (A) Positive ion modes. (B) Negative ion modes. NC group (n = 5), KOA group (n = 6), YH group
(n = 6).
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To investigate the contribution of potential biomarkers between
the two groups, a volcano plot was drawn, followed by Student’s
t-test. Volcano plot of comparison groups: KOA vs. NC (Figure 6,
A1: positive ion; A2: negative ion); YH vs. KOA (Figure 6, B1:
positive ion; B2: negative ion). It summarized the contribution of
each variable to the model. The metabolites with VIP>1 and p <
0.05 were considered as significantly changed metabolites. In total,
66 metabolites were identified in the heatmap of hierarchical
clustering analysis between the KOA and NC groups, including
29 and 37 metabolites in the positive and negative ion modes,
respectively. Between the YH and KOA groups, 81 metabolites
were identified, including 57 and 24 metabolites in the positive
and negative ion modes, respectively. Heatmap of comparison
groups: KOA vs. NC (Figure 6, C1: positive ion, C2: negative
ion); YH vs. KOA (Figure 6, D1: positive ion, D2: negative ion).
Taking the intersection of differential metabolites between the KOA
vs. NC group and the YH vs. KOA group, there were 16 potential
biomarkers, including 8 lipids and lipid-like molecules, 2 organic
acids and derivatives, 2 phenylpropanoids and polyketides,
2 oganoheterocyclic compounds, 2 oganic acids and derivatives
(Table 4).
In order to more intuitively express the intervention effect of
YQYXF components on the screened metabolites, PCA analysis was
performed on the 16 screened potential biomarkers (Figure 7A). The
intra-group aggregation and inter-group dispersion were obvious in
the NC and the KOA group, indicating that the plasma metabolites
in the KOA rats were distinguished from the NC. The KOA group
was significantly separated from the NC group and YH group, while
the NC group and YH group were significantly aggregated,
indicating that YH can regulate KOA-related metabolites.
Further, we mapped the differential metabolites to authoritative
metabolite databases. After obtaining the matching information of
the differential metabolites, we searched and analyzed the metabolic
pathway of the pathway database of Rattus norvegicus (rat). The
metabolic pathway enrichment analysis of differential metabolites
showed that YQYXF mainly exerted its anti-inflammatory effect by
regulating five pathways: linoleic acid metabolism, α-linolenic acid
metabolism, sphingolipid metabolism, arachidonic acid metabolism,
FIGURE 5
OPLS-DA analysis of serum of mice. OPLS-DA scores plots: KOA vs. NC (A1: positive ion, A2: negative ion), YH vs. KOA (C1: positive ion, C2: negative
ion). Permutation test of OPLS-DA model: KOA vs. NC (B1: positive ion, B2: negative ion); YH vs. KOA (D1: positive ion, D2: negative ion).
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and glycerophospholipid metabolism (Figure 7B). In addition, we
performed correlation analysis on 16 biomarkers. Internal
interaction and crosstalk networks are established between
phenylpropanoic acids and organoheterocyclic compounds, fatty
acyls and organic sulfonic acids, carboxylic acids and diazinanes,
fatty acyls and organonitrogen compounds (Figure 7C).
YQYXF modulates oxidative stress and lipid
peroxidation capacity in KOA rats
The results of metabonomics experiments showed that YQYXF
mainly regulated the signal pathway related to lipid metabolism.
Therefore, it may play the role of anti-KOA cartilage destruction by
repairing lipid metabolism disorder. We further explored the
changes of oxidative stress and lipid peroxidation-related factors
in KOA rats. The GSH of NC, sham, OA, YL, YM, YH, and Cxb
group was 235.69 ± 33.23, 250.43 ± 24.85, 467.97 ± 29.25, 397.37 ±
22.89, 374.49 ± 29.29, 319.31 ± 18.88, 284.02 ± 28.56 mmol/L,
respectively. The ROS of NC, sham, OA, YL, YM, YH, and Cxb
group was 290.41 ± 50.77, 318.59 ± 31.99, 681.62 ± 25.38, 540.76 ±
48.31, 495.07 ± 47.84, 433.13 ± 51.34, 359.10 ± 30.95 pg/mL,
respectively. Compared with the NC and sham group, the
expression of GSH (p = 1.59 × 10−19 for the KOA group vs. the
NC group, p = 1.67 × 10−18 for the KOA group vs. the sham group)
and ROS (p = 9.23 × 10−21 for the KOA vs. the NC group, p = 1.43 ×
FIGURE 6
Multivariate statistical analysis of metabolite profiles in plasma. Volcano plot of comparison groups: KOA vs. NC (A1: positive ion, A2: negative ion);
YH vs. KOA (C1: positive ion, C2: negative ion). Heatmap of comparison groups: KOA vs. NC (C1: positive ion, C2: negative ion); YH vs. KOA (D1: positive
ion, D2: negative ion). Screening of differential metabolites by metabolomic analysis. Significantly upregulated metabolites are shown in red, significantly
downregulated metabolites in blue, and non-significantly different metabolites in grey.
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TABLE 4 Identified Potential Biomarkers Regulated by Yiqi Yangxue formula (YQYXF).
Name MS2 score Rt
(s)
Mz VIP
(KOA
vs. NC)
p-value
(KOA
vs. NC)
Fold
change
(KOA
vs. NC)
VIP
(YH
vs.
KOA)
p-value
(YH
vs. KOA
Fold
change
(YH
vs. KOA)
AUC
(KOA
vs. NC)
AUC
(YH
vs.
KOA)
CV
(%)
Ion
mode
KOA
vs. NC
YH
vs.
KOA
1,3-Dihydro-(2H)-indol-2-one 0.99 28.61 134.06 1.61 0.002 0.32 1.30 0.03 2.16 0.83 0.86 63.53 + ↓ ↑
Oleamide 0.98 82.95 282.28 2.38 0.01 3.60 1.72 0.02 0.50 1.00 0.92 71.07 + ↑ ↓
Sphingosine 0.97 82.95 300.29 2.40 0.01 3.71 1.71 0.02 0.48 1.00 0.92 73.62 + ↑ ↓
DL-2-Aminooctanoic acid 0.96 243.66 160.13 2.39 0.001 3.20 2.17 0.01 0.32 1.00 1.00 66.90 + ↑ ↓
LysoPE (18:1 (9Z)/0:0) 0.93 220.69 480.31 1.74 0.03 0.67 1.53 0.03 1.41 0.75 0.92 29.06 + ↓ ↑
7-Ketocholesterol 0.90 31.98 401.34 2.44 0.03 0.19 2.23 0.01 4.62 1.00 1.00 88.44 + ↓ ↑
PC(22:6
(4Z,7Z,10Z,13Z,16Z,19Z)/20:3
(5Z8Z11Z))
0.78 152.05 856.58 1.91 0.01 0.65 1.52 0.04 1.33 0.89 0.83 49.78 + ↓ ↑
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(5Z,8Z,11Z))
PC(22:4 (7Z,10Z,13Z,16Z)/14:0) 0.68 159.91 782.57 1.74 0.04 0.76 1.4 0.04 1.23 0.92 0.86 58.83 + ↓ ↑
L-Cyclo (alanylglycyl) 0.62 379.50 129.07 2.02 0.004 0.50 1.76 0.01 2.03 0.97 0.89 60.36 + ↓ ↑
PC(16:0/14:0) 0.61 169.58 706.54 1.86 0.02 0.64 1.59 0.02 1.37 0.89 0.89 27.85 + ↓ ↑
PC(22:6
(4Z,7Z,10Z,13Z,16Z,19Z)/22:6
(4Z,7Z,10Z,13Z,16Z,19Z))
0.56 148.69 878.57 2.07 0.01 0.41 1.63 0.04 1.62 0.94 0.81 48.93 + ↓ ↑
2-Hydroxyethanesulfonate 0.98 160.46 124.99 1.82 0.05 2.29 1.74 0.04 0.40 0.81 0.92 64.01 - ↑ ↓
Phenyllactic acid 0.97 125.42 165.05 2.40 0.03 0.13 2.27 0.003 3.57 0.86 1.00 95.37 - ↓ ↑
Citraconic acid 0.96 453.31 129.02 1.79 0.03 0.70 1.54 0.04 1.41 0.81 0.83 28.08 - ↓ ↑
(9xi,10xi,12xi)-9,10-Dihydroxy12-octadecenoic acid 0.93 178.74 313.24 1.87 0.02 0.39 1.87 0.04 7.68 0.78 0.94 125.36 - ↓ ↑
4-Hydroxycinnamic acid 0.68 58.39 163.04 2.00 0.01 0.66 1.87 0.005 1.41 0.89 0.92 22.82 - ↓ ↑
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FIGURE 7
Metabolic profiling of 16 potential biomarkers. (A) Principal components analysis score plot of 16 differential metabolites. (B) Metabolic pathway
bubble plot of 16 differential metabolites. (C) Heatmap of correlation analysis. The horizontal and vertical coordinates in the figure represent the
contrasting differential metabolites. Red represents a positive correlation, blue represents a negative correlation, and the darker the color, the stronger
the correlation. Significant correlations are marked with an asterisk (*).
FIGURE 8
The effect of YQYXF on anti-oxidative stress and lipid peroxidation in OA rats. (A) Levels of ROS in plasma. (B) Levels of GSH in plasma. All data were
expressed as mean ± SD. *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001.
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10−19 for the KOA group vs. the sham group) were significantly
increased (Figures 8A, B). The GSH of drug-treated groups was
lower than that of the KOA group (p = 1.60 × 10−5 for the lowYQYXF-dose group, p = 8.6826 × 10−8 for the middle-YQYXF-dose
group, p = 5.00 × 10−13 for the high-YQYXF-dose group, and p =
5.50 × 10−16 for the Cxb group) and the ROS of drug-treated groups
was lower than that of the KOA group (p = 1.76 × 10−7 for the lowYQYXF-dose group, p = 2.34 × 10−10 for the middle-YQYXF-dose
group, p = 5.74 × 10−14 for the high-YQYXF-dose group, and p =
9.69 × 10−18 for the Cxb group), suggesting that the YQYXF could
regulate the plasma lipid metabolism disorder in the KOA rats.
Hence, YQYXF may exert anti-KOA cartilage degeneration by
regulating lipid peroxidation.
Discuss
Clinical research results showed that YQYXF could improve the
clinical symptoms of KOA patients without noticeable adverse
reactions. In animal experiments, the 66 potential disease
biomarkers of KOA and 81 related metabolites of YQYXF were
screened out. After comparative analysis, there were 16 potential
biomarkers in the intervention of YQYXF in KOA rats, and exert
anti-KOA through five metabolic pathways, including sphingolipid
metabolism, glycerophospholipid metabolism, linoleic acid
metabolism, α-linolenic acid metabolism, and arachidonic acid
metabolism.
Sphingolipids display important functions in various
pathologies such as obesity, diabetes, and OA (El Jamal et al.,
2020). Sphingosine 1-phosphate (S1P) is a metabolite of cell
membrane sphingolipids enriched in circulating fluid. It binds to
G protein-coupled S1P receptors to regulate embryonic
development and organ function. S1P binding triggers multiple
cellular and physiological events, including the localization of
immune cells to sites of inflammation and regulation of T-cell
differentiation (Th17 and Treg cells) (Robinson et al., 2022). The
balance between the levels of S1P and sphingosine has been
considered as a switch that could determine whether a cell
proliferates or dies (El Jamal et al., 2020). Masuko found that
S1P may play a unique role in the pathophysiology of KOA by
regulating VEGF expression in chondrocytes (Masuko et al., 2012).
A study found that the activity of sphingosine kinase 1 increased
with osteoclast differentiation, and its expression was enhanced in
the subchondral bone of mice with KOA (Cherifi et al., 2021). The
lipid mediator S1P was identified as a therapeutic target for KOA
(Stradner et al., 2013; Ustyol et al., 2017). In this study, potential
biomarkers were significantly enriched in the sphingolipid
metabolism pathway, suggesting that YQYXF may reduce KOA
cartilage damage and improve lipid metabolism mainly by
regulating sphingolipid metabolism changes.
Glycerophospholipids form the essential lipid bilayer of all
biological membranes and are intimately involved in signal
transduction, regulation of membrane trafficking, and many
other membrane-related phenomena (Farooqui et al., 2000). The
alterations in phospholipid composition and concentrations are
associated with the development of KOA (Kosinska et al., 2014;
Zhang W. et al., 2014). A study found activation of
glycerophospholipid metabolism and oxidative stress pathways in
synovial fluid metabolism in patients with KOA (Carlson et al.,
2019). In this study, YQYXF may improve lipid metabolism by
affecting the level of glycerophospholipids, alleviating the
progression of KOA.
In addition, linoleic acid, α-linolenic acid, and arachidonic acid
all belong to polyunsaturated fatty acids (PUFAs). While all PUFAs
reduced markers of oxidative stress, omega-3 PUFAs additionally
decreased prostaglandin production (Loef et al., 2019). The omega-3
PUFAs have been shown to decrease markers of inflammation and
cartilage degradation. Oxidative stress can be directly assessed by
measuring ROS. Known ROS include superoxide, hydrogen
peroxide, peroxyl radicals, and reactive nitrogen species
(including nitric oxide and peroxynitrite derived from the nitric
oxide) (Duan L. et al., 2020). Previous studies have found that
excessive ROS generated by lipid metabolism disorders can induce
chondrocyte apoptosis (Poulet and Staines, 2016). Excessive
accumulation of ROS can cause chondrocyte damage and
cartilage matrix degradation, promoting the occurrence of KOA
(Bolduc et al., 2019). ROS can also destroy proteoglycans and type II
collagen in the cartilage matrix by activating matrix
metalloproteinases, inhibiting matrix synthesis, and leading to
loss of cartilage integrity (Mehana et al., 2019). GSH can exert a
destructive effect on ROS through an enzymatic mechanism,
reducing the level of ROS or inhibiting its activity. Imbalanced
ROS/GSH may result from a direct increase of ROS, consumption of
GSH, intracellular oxidoreductase interference, or thioredoxin
activity reduction (Liu et al., 2022). GSH and ROS in the model
group were significantly increased, suggesting an imbalance between
ROS production and elimination. Furthermore, the intervention of
different doses of YQYXF may activate the feedback regulation
mechanism, promote the reduction of ROS level, and then lead to
the corresponding decrease of GSH, which can alleviate the
imbalance. Thus, YQYXF may reduce ROS production by
balancing lipid metabolism disorders and inhibiting KOA
TABLE 5 The relevance of metabolic pathways to symptoms and pathology.
Pathway Symptoms and pathology
Linoleic acid metabolism Regulate inflammatory reactions and pain, and maintain the stability of blood glucose and blood fat levels
Alpha-Linolenic acid metabolism Regulate lipid metabolism and inflammatory reactions
Sphingolipid metabolism Regulate inflammatory reactions and pain
Arachidonic acid metabolism Participate in immune and inflammatory reactions
Glycerophospholipid metabolism Regulate lipid metabolism
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cartilage destruction. However, further experimental verification is
still needed.
A study used liquid chromatography/mass spectrometry (LC/
MS)-based metabolomics to explore the serum metabolomics in rats
with KOA. The six biomarkers were identified, which were
metabolized through tryptophan metabolism, glutamate
metabolism, nitrogen metabolism, spermidine metabolism, and
fatty acid metabolism pathways (Zhao et al., 2021). Another
study used ultra-high performance liquid chromatography-triple
quadrupole mass spectrometry (UPLC-TQ-MS), followed by
multivariate statistical analysis, to determine the serum amino
acid profiles of KOA patients and healthy controls. The
metabolic pathways with the most significant effects were
involved in the metabolism of alanine, aspartate, glutamate,
arginine, and proline (Chen et al., 2018). In our study, the
plasma metabolites of KOA and control group participated in
alanine, aspartate and glucose metabolism, pyrimidine
metabolism, and biosynthesis of unsaturated fatty acids. The
results are consistent with the findings of the above studies. In
addition, the fasting serum of KOA patients and healthy controls
was assessed by metabolomic analysis (Tootsi et al., 2020). The
changes in the serum levels of amino acids, sphingomyelins,
phoshatidylcholines and lysophosphatidylcholines of the KOA
patients compared with healthy controls suggest systemic
inflammation in severe KOA patients. In our study, YQYXF is
mainly involved in lipid metabolism pathways, such as sphingolipids
metabolism and glycerol phospholipids metabolism, which indicates
that YQYXF may play a role in treating systemic inflammation
in KOA.
For note, the flavocoxid is a medical food consisting of plantderived flavonoids which have anti-inflammatory activity and are
used to treat chronic KOA. Studies have shown that flavocoxid was
as effective as naproxen in managing the signs and symptoms of
KOA (Levy et al., 2010). In our study, 99 flavonoids in YQYXF were
identified, including naringin, baicalin, icariin, and quercetin.
Naringin, a natural flavanone found in citrus fruits, and its
aglycone have been demonstrated to ameliorate obesity and
dyslipidemia. The principal mechanisms by which these
flavonoids exert their action involve upregulation of peroxisome
proliferator activated receptor α and adenosine 5′-monophosphateactivated protein kinase, and the downregulation of genes involved
in lipid metabolism (Massaro et al., 2022). Naringin is an effective
therapeutic drug for the treatment of KOA and KOA-related
symptoms, which can support the recovery of hind-limb weightbearing (Xu et al., 2017). Naringin can prevent cartilage destruction
in KOA by inhibiting the nuclear factor kappa-B (NF-κB) signaling
pathway, which reduces Tumor necrosis factor-α (TNF-α)-mediated
chondrocyte inflammation and cartilage matrix degradation (Zhao
et al., 2016). Baicalein can ameliorate inflammatory-related
apoptotic and catabolic phenotypes in human chondrocytes
(Zhang X. et al., 2014). In addition, the anti-inflammatory and
anti-apoptotic effects of baicalein are mediated by inhibiting the
translocation of phosphorylated p65 to the nucleus (Li et al., 2017).
Icariin has been shown to stimulate osteogenic differentiation and
bone formation and to increase the synthesis of the cartilage
extracellular matrix (Zhao et al., 2019). A study has
demonstrated that the IKBKB, NFKBIA, MAPK8, MAPK9, and
MAPK10 may be the hub genes affected by icariin when providing
its beneficial effects on KOA. In addition, icariin can alleviate KOA
by inhibiting NOD-like receptor thermal protein domain associated
protein 3-mediated pyroptosis (Zu et al., 2019). Quercetin may be
related to the inhibition of interleukin-1β (IL-1β) and TNF-α
production via the Toll-like receptor 4/NF-κB pathway in KOA
rats (Zhang et al., 2020). The use of quercetin partially abrogated
intestinal flora disorder and reversed fecal metabolite abnormalities
(Lan et al., 2021). In addition, 32 phenolic compounds were found in
YQYXF, such as paeonol, 4-methylatechol, and thymol. Paeonol, as
an essential component in traditional Chinese medicine, has antiinflammatory activity and can offer therapy for a multitude of
inflammatory-related diseases. Studies have shown that applying
paeonol can attenuate the secretion of cartilage extracellular matrix
and cartilage degrading enzymes induced by IL-1β in chondrocytes
(Liu et al., 2017). Besides, paeonol can also alleviate destabilization of
the medial meniscus-induced articular cartilage degeneration in vivo
(Liu et al., 2017). There are few studies on phenolic compounds in
OA, which need further research and verification.
For note, the metabolic pathways likely contribute to symptoms
and pathology in KOA. Some studies demonstrated that metabolites
in the synovial fluid and blood could be used as biomarkers for KOA
incidence, prognosis, and response to therapy (Rockel and Kapoor,
2018). Various metabolites can directly influence the perception of
pain. Secreted phospholipase A2 catalyzes the conversion of
phosphatidylcholine (PC) analogues to lysoPC analogues.
Subsequent metabolism of lysoPCs via autotaxin generates
lysophosphatidic acid, an inflammatory and pain-producing
signal. Endocannabinoids, endogenously produced lipid-derived
compounds, could be beneficial for individuals with KOA to
reduce pain symptoms. In turn, the endocannabinoids may result
in the production of lysoPCs, which could promote joint pain due to
metabolism of lysophosphatidic acid (Muccioli, 2010). In addition,
the oxidized linoleic acid metabolite and partial TRPV1 agonist 9-
hydroxyoctadecandienoic acid was shown to be involved in chronic
inflammatory pain (Wedel et al., 2022). The linoleic acid can
attenuate inflammatory responses and reduce LPS-induced
phosphorylation of proteins associated with NF-κB signaling
(Kim et al., 2020). In addition, the dysregulation of sphingolipid
metabolism contributes to neuropathic pain (Stockstill et al., 2018)
(Table 5).
The limitation of this study is that the components of traditional
Chinese medicine are complex, with the characteristics of multiple
targets and pathways. Although the components of YQYXF were
identified, the analysis of members entering the blood and the study
of pharmacokinetics still need to be clarified.
In conclusion, YQYXF could be an effective and promising
agent for treating KOA, which might exert its action by regulating
multiple lipid metabolism-related pathways. Our study provides
new insights into studying the underlying molecular mechanism of
YQYXF against oxidative stress in the KOA model. However,
further research exploration is needed.
Data availability statement
The original contributions presented in the study are publicly
available. This data can be found here: https://www.ebi.ac.uk/
metabolights/. Accession number: MTBLS5667.
Frontiers in Genetics 15 frontiersin.org
Zhao et al. 10.3389/fgene.2023.1096616
第17页
Ethics statement
The studies involving human participants were reviewed and
approved by the Medical Ethics Committee of Yunnan University of
Traditional Chinese Medicine (ethics number: 2019YXLL005).
Written informed consent to participate in this study was
provided by the participants’legal guardian/next of kin. The
animal study was reviewed and approved by the Ethics
Committee of Yunnan University of Chinese Medicine (ethical
code no. R-062019065). Written informed consent was obtained
from the individual(s) for the publication of any potentially
identifiable images or data included in this article.
Author contributions
All authors listed have made a substantial, direct, and intellectual
contribution to the work and approved it for publication.
Funding
National Natural Science Foundation of China grant Nos.
(81960870, 31960178, 82160923, 81560781, and 81760822);
Yunnan Provincial Ten Thousands Program Famous Doctor
Special; Yunnan Province Qingguo Wang Expert Workstation
Construction Project (202005AF150017); Yunnan Applied Basic
Research Projects-Yunnan University of Chinese Medicine Union
Foundation (202101AZ070001-247); Yunnan Applied Basic
Research Projects-Union Foundation [2019FF002(-031)]; Applied
Basic Research Programs of Science and Technology Commission
Foundation of Yunnan Province (2019FA007); Key Laboratory of
Traditional Chinese Medicine for Prevention and Treatment of
Neuropsychiatric Diseases, Yunnan Provincial Department of
Education; Scientific Research Projects for High-level Talents of
Yunnan University of Chinese Medicine (2019YZG01); Young TopNotch Talent in 10,000 Talent Program of Yunnan Province
(YNWR-QNBJ-2019-235); National Science and Technology
Innovation 2030 Major Program (2021ZD0200900); Yunnan Key
Research and Development Program (202103AC100005); Yunnan
Province Fabao Gao Expert Workstation Construction Project
(202105AF150037); Yunnan Engineering Research Center of
Drug Development for Bone Diseases. Scientific Research Fund
Project of Yunnan Provincial Department of Education
(2021Y461 and 2022Y348).
Acknowledgments
We would like to thank Shanghai Biotree Biomedical
Biotechnology Co., Ltd., for assistance in UHPLC-QE-MS analysis.
Conflict of interest
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.
Publisher’s note
All claims expressed in this article are solely those of the authors
and do not necessarily represent those of their affiliated
organizations, or those of the publisher, the editors and the
reviewers. Any product that may be evaluated in this article, or
claim that may be made by its manufacturer, is not guaranteed or
endorsed by the publisher.
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