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Table of Contents
Year : 2022  |  Volume : 8  |  Issue : 4  |  Page : 539-547

Metabolic characterization of the Badagan constitution in mongolian medicine by ultrahigh-performance liquid chromatography/quadrupole time-of-flight mass spectrometry/MS

1 College of Mongolian Medicine, Inner Mongolia University for Nationalities; Editorial Department of Journal, Inner Mongolia Research Institute of Traditional Mongolian Medicine Engineering Technology, Tongliao, China
2 College of Mongolian Medicine, Inner Mongolia University for Nationalities, Tongliao, China
3 Editorial Department of Journal, Inner Mongolia University for Nationalities, Tongliao, China
4 State owned Assets Management Department, Inner Mongolia University for Nationalities, Tongliao, China

Date of Submission19-May-2021
Date of Acceptance20-Aug-2021
Date of Web Publication21-Jul-2022

Correspondence Address:
Dr. Li-Ming Bao
College of Mongolian Medicine, Inner Mongolia University for Nationalities, Tongliao, 028000
Dr. Xiao-Hua Bao
College of Mongolian Medicine, Inner Mongolia University for Nationalities, Tongliao, 028000
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/2311-8571.351507

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This study aimed to identify the potential metabolic biomarkers of the Badagan constitution (BC) in Mongolian medicine. Serum samples from the participants with BCs (n = 32) and aggregative constitutions (n = 30) were analyzed by using ultrahigh-performance liquid chromatography/mass spectrometry. Meanwhile, principal component analysis and orthogonal partial least squares discriminant analysis were used to characterize the endogenous metabolites and potential biomarkers, respectively. Fifteen of the 18 biomarkers in six metabolic pathways were significantly upregulated, including phosphatidylserine, sphingolipids, tryptophan, riboflavin and glutathione, and three biomarkers were significantly downregulated, including lysophosphatidylcholine (LysoPC) (18:1), LysoPC (16:1), and lysophosphatidylethanolamine (LysoPE) (22:2). This study also implied that sphingolipid metabolism, glycerophospholipid metabolism, and tryptophan metabolism played important roles in the BC. Therefore, metabolomics may improve the diagnostic efficacy of the BC in terms of the accuracy and comprehensiveness of a diagnosis based on this constitution. This result further reveals the mechanism of the constitution type in Mongolian medicine and provides a reference for the treatment of related diseases.

Keywords: Mongolian Medicine, Badagan Constitution, Metabolic Characterization, UPLC-ESI-QTOF-MS

How to cite this article:
Bao XH, Bao LM, Xiang C, Gerile S, Qiqige S, Xie YL. Metabolic characterization of the Badagan constitution in mongolian medicine by ultrahigh-performance liquid chromatography/quadrupole time-of-flight mass spectrometry/MS. World J Tradit Chin Med 2022;8:539-47

How to cite this URL:
Bao XH, Bao LM, Xiang C, Gerile S, Qiqige S, Xie YL. Metabolic characterization of the Badagan constitution in mongolian medicine by ultrahigh-performance liquid chromatography/quadrupole time-of-flight mass spectrometry/MS. World J Tradit Chin Med [serial online] 2022 [cited 2023 Dec 8];8:539-47. Available from: https://www.wjtcm.net/text.asp?2022/8/4/539/351507

  Introduction Top

In accordance with Mongolian medical theory, the human body consists of Heyi, Xila, and Badagan.[1] In Mongolian medical science, the associations between Badagan,Xila, and Heyi explain the physiology- and pathology-related phenomena of the human body.[2] Heyi is considered the moving energy of the body, directing language, thinking, and outer and inner physical activity. Xila expresses hotness and determines the spirit or heat of the organs and body temperature. Badagan refers to a sticky material inside humans characterized by coldness. Heyi, Xila, and Badagan are the main material bases for the human body and an important energy and power source of human life activities.[3]

Mongolian medicine holds that the human body's Heyi, Xila, and Badagan have their own characteristics and functions and that they can interact via interdependence, mutual restraint, closeness, and harmonization.

The ternary structure of Heyi, Xila, and Badagan is derived from the gametes of the parents and is influenced by a person's diet, living conditions, season and other factors. The body's physiological function is dominated by these ternary functions. For example, metabolism is the basis of the body's physiological characteristics, that is, digestion and defecation.[1]

Because each person encounters different conditions during growth and development, a stable relative equilibrium state is associated with different proportions of the Heyi, Xila, and Badagan constitutions (BCs). These individual differences are the physiological bases of people's physical and personality characteristics.

Traditional Mongolian medicine recognizes seven body constitutions, namely the Heyi, Xila, Badagan, Heyi-Xila, Heyi-Badagan, Xila-Badagan, and aggregate Heyi, Xila, Badagan (aggregation constitution [AC]) constitution types.[4]

The constitution of the body, a long-standing basic tenet of conventional Mongolian medical science, has been extensively adopted on a day-to-day basis by Mongolian medical science trailblazers. Traditional Mongolian medicine asserts that as a result of genetic and acquired influences, we all have a number of structural, physical, and psychological peculiarities.

Together, these characteristics shape our lives and behavior as well as our sensitivity to pathogens and diseases. The constitution of the body is critical to the clinical diagnosis and treatment of disease and underpins the promotion of health and prevention of disease; however, standardized measurements for determining body constitution are lacking.

Metabolomics, an omic science in systems biology, has been extensively adopted to diagnose various diseases (e.g., diabetes, lung cancer, liver fibrosis, and neuropsychiatric disorders).[5],[6]

Ultra-performance liquid chromatography/mass spectrometry (UPLC/MS), with its efficient separation process, high resolution and sensitivity, has been frequently employed for metabolomics studies.[7],[8],[9] Blood and urine are integrated biological fluids that contain the functions and phenotypes of various body parts in different samples, representing the metabolic footprint of tissue metabolism.[10]

In this study, UPLC/MS-based serum metabolomics was employed to investigate metabolic profiles and underlying biomarkers of the BC.

  Materials and Methods Top


Chemicals such as LC-MS grade acetonitrile and formic acid were purchased from Thermo Fisher Scientific (Shanghai, China), and pure water was purchased from Watsons (Inner Mongolia, China).

Sample collection and preparation

Participants were 18- to 25-year-old healthy volunteers from Inner Mongolia University. Thirty BC and 32 AC participants were recruited.

We carried out the analysis in line with the procedures of the declaration of Helsinki. The Ethics Committee of Inner Mongolia University for Nationalities gave approval for this study. Participants provided written informed consent. All the samples were processed within 6 h of collection and frozen at −80°C until the time of analysis.

Preparation of samples for mass spectrometry analysis

The preparation of the serum samples was to mix 50 μL serum with 200 μL methanol. Then, the serum sample was swirled for 3 min. Later, it was centrifuged for 15 min at 12000 RPM to precipitate the proteins. Later, 5 μL supernatant was taken to carry out the LC-MS analysis.

The preparation of the quality control (QC) samples for serum content was to mix 20 μL aliquots per research sample. Then, the QC samples were injected at an interval of 8 research samples to assess both the stability and suitability of the analytical system before the commencement of the order.

Ultrahigh-performance liquid chromatography/mass spectrometry measurement of the serum samples

The serum samples were separated by a Waters Acquity™ UPLC system (Waters Corp, Milford, MA, USA) on a Waters Acquity BEH C18 column (with a size of 100 mm × 2.1 mm, 1.7 μm). To guarantee the sample quality and stability, during the analysis process, the temperature of the automatic sampler was kept at 4°C, while the column temperature was kept at 40°C±0.5°C. The mobile phase was composed of aqueous 0.1% formic acid (A) and acetonitrile (B). Then, the gradient elution program below was used, including 0–4 min, 10%–85% B; 4–10 min, 85% B; 10–10.1 min, 85%–10% B; and 10.1–12 min, 10% B. The injection volume of 2 μL was analyzed by using ultra-performance liquid chromatography-electrospray ionization-quadrupole time-of-flight mass spectrometry (UPLC-ESI-QTOF-MSE). Before analysis, the samples were dissolved in the mobile phase and then filtered through a 0.22 μm filter film.

The UPLC system was connected to the Xevo™ G2S instrument (Waters MS Technologies, Manchester, UK), and it contained an electrospray ionization source and operated in both positive and negative ionization modes. In addition, its scanning range was between m/z 100 and 1100. The capillary voltage in the positive mode was 3.0 kV, that in the negative mode was 2.5 kV, and the sampling cone voltage was 40 V. The low impact energy scanning was set to 6 eV, and the high impact energy scanning was set to 15–45 eV, with a desolvation flow rate of 800 L/h and an atomization temperature of 400°C. Meanwhile, the source temperature was 100°C, and leucine enkephalin (leu-enk) was used as the lock mass. The acquisition of all data and the analyses or quantification was controlled by MassLynx version 4.1 software (Waters Corporation, Milford, MA, USA).

Data acquisition

To check the original status of the device, 10 QC samples underwent continuous studies prior to the experimental process. We tested one QC sample per seven samples to ascertain the device's stability. In addition, to ensure that no samples remained on the column, a blank sample (acetonitrile) was analyzed per three samples.

Data processing and statistical analysis

Using Waters MassLynx v4.1 software, the original data were obtained, and to achieve peak extraction, peak alignment and normalization, we comprehensively substituted the raw data in MarkerLynx software (Waters Corp., Milford, MA, USA). For the implementation of orthogonal partial least squares discriminant analysis (OPLS-DA) as well as principal component analysis (PCA), we substituted such data with Simca-P 16.0 software. For the observation of samples separated from a range of groups, PCA was employed; to ascertain the separated metabolites significantly different in content between the AC and BC groups, we adopted OPLS-DA. The noted metabolites acted as underlying biomarkers displaying variance importance for projection (VIP) values over 1.0 and P < 0.05. By using SPSS Statistics 17.0, we carried out the statistical studies, with a P < 0.05 identified to be of statistical significance. We found the underlying biomarkers using HMDB and ChemSpider. Pathway studies were performed by using a molecular pathway level synthesis analysis (IMPaLA) on the basis of the potential biomarkers.

  Results Top

Body constitution judgment

Body constitution classification mainly determines the type of constitution according to the parameters in the “Ershi Mongolian Medical Physique Judgment Table,” as shown below [Table 1].
Table 1: Ershi Mongolian medical judgment table

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Body weight indexes and serum biochemical parameters

Body mass index (BMI) is the number of kilograms of body weight divided by the square of meters of height. It is a standard body weight commonly used in clinical practice to measure whether the body is healthy. The index is also directly related to some diseases. The normal BMI of adults is between 18.5 and 24; a BMI below 18.5 is considered underweight, a BMI between 24 and 27 is overweight, a BMI above 27 is obese, and a BMI above 32 is very obese.[11] If BMI exceeds the standard, it will greatly increase the occurrence of hypertension, hyperlipidemia, and diabetes and have a direct relationship with the occurrence of cardiovascular and cerebrovascular diseases.[12],[13],[14]

As shown in [Table 2], the BMI of the AC group was between 18.5 and 24 and in the normal range. The BC group's BMI was between 24 and 27 and was overweight, and these results agree well with the findings of Wu et al.[15] Compared with the triglyceride, total cholesterol (TC) and low-density lipoprotein levels in the AC group, those in the BC group were greatly increased, but the level of serum high-density lipoprotein cholesterol (HDL-C) was greatly reduced.
Table 2: General characteristics of participants and serum parameters

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There seems to be a serious disorder of lipid metabolism in the BC group; therefore, people with BC seem to be prone to obesity, high insulin levels and insulin resistance compared to those with AC.[16]

Metabolomics analysis

Optimization of the liquid chromatography-quadrupole time-of-flight mass spectrometry conditions

According to the serum sample characteristics, the chromatographic conditions, including column selection and mobile phase pH, were improved.

Acetonitrile, as an organic component of the mobile phase, has high responsiveness and low background noise. In addition, the ACQUITY BEH C18 column (100 mm × 2.1 mm diameter, 1.7 m diameter) was superior to the ACQUITY UPLCTM HSS C18 column (100 mm × 2.1 mm diameter) in peak symmetry and retention performance. The chromatographic chart of base peak intensity of serum samples in the BC and AC groups is shown in [Figure 1].
Figure 1: The base peak chromatograms of serum samples from the Badagan constitution (a) and aggregation constitution (b) groups

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Analysis of the serum samples by liquid chromatography-mass spectrometry

To monitor the analysis efficacy of the instrument, QC samples were also employed for the detection of the system's stability. After the preprocessing of original data, all samples, covering QC samples, were tested by the PCA model. In addition, the score plot in [Figure 2]a suggests a high aggregation extent of the QC samples. Thus, analyzing the efficacy of the device was demonstrated to exhibit stability and reproducibility.
Figure 2: Principal component analysis score scatter plots for serum samples from the Badagan constitution and aggregation constitution groups in the positive (a) electrospray ionization mode. Orthogonal partial least squares discriminant analysis score scatter plots and S plots for the Badagan constitution and aggregation constitution groups in the positive (b and c) electrospray ionization mode. Metabolic pathway analysis with MetaboAnalyst (D. a: sphingolipid metabolism; b: glycerol phospholipid metabolism; c: riboflavin metabolism; d: amino acid metabolism)

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In our study, the PCA model was first employed to observe the analyzed sample distributions. In the score plot in PCA [Figure 2]a, the samples in the BC group (in green) spread obviously in a confined zone and were noticeably isolated from those in the AC group (in blue). Most of the samples followed the confidence interval, suggesting data rationality.

Then, for the observation of the diversification of the two groups, OPLS-DA was further employed. As seen from the OPLS-DA score diagram in [Figure 2]b, there was a great difference between the BC group and AC group, and there were differences in metabolites between the BC group and AC group. In the OPLS-DA scoring graph, parameters such as R2Y (cum) and Q2 (cum) were adopted to evaluate these models. Meanwhile, R2Y (cum) refers to fitness, while Q2 (cum) suggests prediction capability. Here, the parameters contained in the OPLS-DA model in the positive ionization model were R2Y (cum) = 0.937 and Q2 (cum) = 0.476, indicating that the OPLS-DA scoring chart had a good fitting and prediction capability.

Differentially expressed metabolites for the Badagan constitution group

In general, the candidate metabolites with a VIP of <1.0 and P < 0.05 were regarded as potential biomarkers [Table 3]. Eighteen serum metabolites, including PS, sphingolipids, tryptophan, riboflavin and glutathione, were found to be significantly higher in the BC group than in the AC group, while LysoPC (18:1), LysoPC (16:1) and LysoPE (22:2) showed the opposite trend in the BC group [Figure 2]c. The trends in these potential biomarkers were visualized in heatmaps [Figure 3]. These metabolites were screened for potential markers in the BC group.
Table 3: Identification of significantly differential metabolites in serum of Badagan constitution group

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Figure 3: Heatmap of identified differential metabolites

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By introducing the potential biomarkers into MetaboAnalyst 4.0, the relative metabolic pathways of the BC group were determined, and the pathways of P < 0.05, false discovery rate was smaller than 0.05 and impact was larger than 0 were selected. Therefore, the results indicated that the main metabolic pathways involved were glycerol phospholipid metabolism, sphingolipid metabolism, and amino acid and riboflavin metabolism in the BC group group [Table 3] and [Figure 1]b and [Figure 2]d.

Phospholipids are the main component of biofilms and are divided into glycerol phospholipids and sphingomyelin. Glycerol phospholipids are one of the most abundant phospholipids in the human body. In addition to forming biofilms, these phospholipids are essential components of bile as well as membrane surface active substances, and they participate in protein identification and signal transduction through the cell membrane.[17]

The basic structure of glycerophospholipids is phosphatidic acid, and the substituent group is connected with phosphoric acid; glycerophospholipids can be divided into many categories because of their different substituent groups. The important ones are phosphatidylcholine, also known as lecithin, phosphatidylethanolamine, also known as cephain, phosphatidylserine (PS), phosphatidylglycerol, and phosphatidylinositol.

Lysophospholipids (lysolecithins), also known as hydrolyzed phospholipids, are phospholipids that are hydrolyzed by phospholipase A1, phospholipase A2, and phospholipase B.[18]

In the present study, the main identified lysophospholipids were LysoPC and LysoPE.

Research shows that LysoPCs are associated with obesity.[19],[20] The plasma levels of LysoPC (18:2) and LysoPC (20:1) were significantly decreased in obese mice induced by a high-fat diet.[21] In a study by Kim et al., LysoPC (18:1) was decreased in the plasma of overweight/obese subjects.[22] The BC group was associated with a high BMI and is an obesity-prone constitution, which may be related to the decrease in LysoPC content.

Glycerol 3-phosphate is a key precursor for the synthesis of glycerophospholipids and is considered to be a characteristic metabolic marker of glycerophospholipid metabolism.[23]

PS, a class of ubiquitous phospholipids, is a component of the cell membrane and is usually located in the inner layer of the cell membrane.[24]

As one of the brain membrane's important components,[25] it has an essential function in the regulation of the brain's functions, such as memory and emotional stability of the brain.[26]

PS can also help the cell wall remain flexible, enhance the efficiency of neurotransmitters that transmit brain signals, help brain function efficiently, and stimulate brain activation.

Several studies have also shown that phosphatidyl serine can significantly reduce the level of excessive stress hormones, reduce stress and relieve brain fatigue in people with work stress.[27] PS can also act on the level of neurotransmitters that affect mood in the brain, can promote attention concentration, improve alertness and memory, and help relieve bad emotions, such as depression and depression.

Mongolian medicine asserts that Badagan is a kind of mucilage. BC is associated with physical strength, full endurance, magnanimity, strong memory, flexible joint movement, and delicate skin lubrication, which may be related to the high serum PS content in the body.

Based on the MetaboAnalyst pathway, glycerophospholipid metabolism influences BC. According to Fig., when compared with the AC group, the PS and glycerin 3-phosphate were elevated and LysoPC (18:1), LysoPC (16:1) and LysoPE (22:2) were reduced in the BC group.

Sphingolipids are essential components of biofilm structure, and sphingolipids and their metabolites are a category of necessary active molecules participating in a number of important signal transduction processes; for example, they can regulate cell growth, differentiation, senescence, and programmed cell death. It has been reported that a significant increase in sphingolipid synthesis can reduce the reverse transport of cholesterol during lipid metabolism,[28] which may lead to lipoprotein aggregation and accumulation.[29]

In this study, sphingosine 1-phosphate was upregulated in the BC group. Recently, researchers have shown that elevated sphingolipids may be a marker of obesity and cardiovascular risk.[30] Therefore, the upregulation of sphingolipids confirmed the impairment of the reverse cholesterol pathway in the BC group.

As an important metabolite for health care, riboflavin can be transformed into flavin mononucleotides and flavin adenine dinucleotides through riboflavin kinase, thus minimizing cardiovascular risk as well as oxidative stresses.[31],[32] Therefore, there is evidence that continuously consuming a high-fat diet can downregulate urinary riboflavin.[9]

Tryptophan is an essential amino acid in the human body and plays an important role in regulating cell activation and proliferation, and the kynuramine metabolic pathway is one of its main metabolic pathways.[33] The kynuramine metabolic pathway is present in the liver, kidney and brain of mammals in humans and is closely related to physiological functions such as neural regulation, immune system regulation and energy metabolism [Figure 4].
Figure 4: Potential metabolic pathways disturbed in the Badagan constitution groups. The metabolites colored blue, red, and gray show a significant decrease and increase not detected in the Badagan constitution groups, respectively

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Glutathione is a tripeptide composed of three amino acids, L-glutamate, cysteine and glycine, in human cells that can help maintain normal immune system function. It has physiological activities such as antifree radicals, antioxidative stress,[34] and integrated detoxification activities and has effects such as delaying aging[35] and enhancing immunity.[36]

  Discussion Top

Mongolian medicine asserts that people with different physiques have different susceptibilities to disease. According to the physical characteristics and symptoms of the patients, different diagnosis and treatment schemes are given for the same diseases. Different treatments are determined according to the patient's personal situation in terms of increasing the positive effect of the treatment and reducing the adverse effects.

Metabolomics is becoming a useful tool to investigate metabolic processes, recognize potential biomarkers that are in charge of metabolic characteristics, and then reveal the metabolic mechanism. The UPLC technique has been extensively used in metabolite identification in vitro or in vivo,[37],[38] and Q-TOF/MS has been researched and developed to identify lipids. The benefits of MS in metabolite identification have been reported in previous publications.[39]

In this study, a comparative study was carried out via UPLC-QTOF-MS of BC and AC group metabolites.

The results showed that the contents of PS, sphingolipids, tryptophan, riboflavin and glutathione were increased in the BC group, but that LysoPE and LysoPC were decreased. Metabolic pathway [Figure 5]. analysis showed that the main pathways in the BC group were glycerophospholipid metabolism, sphingolipid metabolism, amino acid metabolism and riboflavin metabolism pathways. These metabolites may be potential biomarkers for BC. This study is not only helpful for explaining the scientific connotation of Mongolian medicine's “three roots” theory but also provides an objective basis for modern research on Mongolian medicine's physique theory. It also lays a foundation for the treatment and early prevention and treatment of clinical diseases in Mongolian medicine.
Figure 5: The receiver operating characteristic curve for discriminating metabolites

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Financial support and sponsorship

This work was supported by the National Natural Science Foundation of China (grant number 81660828); the Open Fund Project of Engineering Technology Research Center of Mongolian Medicine of Inner Mongolia (grant numbers MDK2018070, MDK2019034); MDK2019036; National and local Joint Engineering Research Center for Mongolian Medicine Research Open Fund Projects (MDK2021035) and the Natural Science Foundation of Inner Mongolia of China (grant number 2019MS08040).

Conflicts of interest

There are no conflicts of interest.

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  [Figure 1], [Figure 2], [Figure 3], [Figure 4], [Figure 5]

  [Table 1], [Table 2], [Table 3]


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