Deciphering the Metabolomics-Based Intervention of Yanghe Decoction on Hashimoto’s Thyroiditis

Zhang, Xing; Chen, Dexuan; Xu, Kun; Ma, Zhaoqun

doi:https://doi.org/10.1155/2022/6215573

Evidence-Based Complementary and Alternative Medicine

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Abstract Introduction Methods Results Discussion Conclusion Data Availability Conflicts of Interest References Copyright Related Articles

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Medicinal Plants and Natural Products in Health Promotion and Disease Prevention

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Research Article | Open Access

Volume 2022 | Article ID 6215573 | https://doi.org/10.1155/2022/6215573

Deciphering the Metabolomics-Based Intervention of Yanghe Decoction on Hashimoto’s Thyroiditis

Xing Zhang,¹Dexuan Chen,¹Kun Xu,¹and Zhaoqun Ma¹

Academic Editor: Ruchika Garg

Received17 Feb 2022

Revised05 May 2022

Accepted07 May 2022

Published15 Jul 2022

Abstract

Background. Yanghe decoction is a famous formula consisting of Rehmannia, deer horn gum, cinnamon, rue, Ephedra, ginger charcoal, and licorice. However, few studies have explored the role of the potential mechanism of Yanghe decoction in the treatment of Hashimoto’s thyroiditis by metabolomics. Methods. Nine mice were randomly divided into three groups: control group (group C), model group (group M), and drug administration group (group T), with three mice in each group. Mice in groups M and T were established as models of Hashimoto’s thyroiditis, and group T was treated with Yanghe decoction. The metabolome of plasma samples from each group of mice was determined using mass spectrometry coupled with high-performance liquid and gas phases, and nuclear magnetic resonance. Based on the three assays, principal component analysis was performed on all samples, as well as orthogonal partial least squares-discriminant analysis and differential metabolite molecules for groups M and T. Subsequently, pathway enrichment analysis was performed, and the intersection was taken for the differential metabolites screened in the M and T groups. The levels of inflammatory factors IL-35 and IL-6 within the serum of each group of mice were detected. Results. The difference analysis showed that a total of 38 differential metabolites were screened based on mass spectrometry coupled with the high-performance liquid phase, 120 differential metabolites were screened based on mass spectrometry coupled with gas phase, and a total of α-glucose and β-glucose were the differential metabolites analyzed based on NMR test results. The pathways enriched by the differential metabolites in the M and T groups were intersected, and a total of 5 common pathways were obtained (amino acid tRNA biosynthesis, D-glutamine and D-glutamate metabolism, tryptophan metabolism, nitrogen metabolism, and arginine and proline metabolism). The results also showed a significant decrease in the serum inflammatory factor IL-35 and a significant increase in IL-6 in mice from group M compared with group C, while a significant increase in the serum inflammatory factor IL-35 and a significant decrease in IL-6 in mice from group T compared with group M. Conclusion. Our study reveals the metabolites as well as a metabolic network that can be altered by Yanghe decoction treatment of Hashimoto’s thyroiditis and shows that Yanghe decoction can effectively reduce the level of inflammatory factors in Hashimoto’s thyroid.

1. Introduction

Hashimoto’s thyroiditis, also known as chronic lymphocytic or autoimmune thyroiditis, is an autoimmune thyroid disease that causes the immune system to attack and destroy the thyroid gland [1]. It is characterized by an enlarged thyroid gland, parenchymal lymphocytic infiltration, and the presence of thyroid antigen-specific antibodies [2]. Hashimoto’s thyroiditis causes chronic inflammation of the thyroid tissue and may result in hypothyroidism in 20–30% of patients [3]. The incidence is approximately 3 to 6 cases per 10,000 people per year, with a prevalence of at least 2% in women. The glands involved in thyroiditis often lose the ability to store iodine, produce and secrete rod proteins that circulate in the plasma, and fail to make hormones efficiently [4,5]. At present, methylprednisolone is often used in clinical practice for Hashimoto’s thyroiditis treatment, which could inhibit the synthesis of the thyroid gland and alleviate the patient’s clinical symptoms. However, research has shown that the use of methimazole alone in patients with Hashimoto’s thyroiditis for long term often have poor prognosis.

Traditional Chinese medicine is remarkably effective in the adjuvant treatment of the disease, especially in improving clinical symptoms, prolonging patient survival, and modulating immune function. As an effective method for preventing and treating diseases, TCM has been increasingly used worldwide in the past decades [6]. Yanghe decoction is a famous formula consisting of Rehmannia, deer horn gum, cinnamon, rue, Ephedra, ginger charcoal, and licorice [7]. It has the effect of warming yang and nourishing blood and dispersing cold and moving stagnation. For centuries, Yang He Tang has been proven to be used to treat a variety of noninfectious inflammatory conditions [8].

Yanghe decoction can be combined with modern therapies, which have a combination of “multicomponent, multitarget, and multipathway” regulatory mechanisms and have fewer toxic side effects [9]. In one study, Yang He Tang was shown to have a high mean cure rate (defined as complete regression or significant improvement of lumps and pain for at least two months) in patients with chronic breast fibrosis and palpable lumps [10]. Fewer studies have clinically investigated the effect of Yanghe decoction in the treatment of Hashimoto’s thyroiditis. Therefore, the present study was conducted to investigate the potential mechanism of Yanghe decoction in the treatment of Hashimoto’s thyroiditis through a metabolomic approach.

2. Material and Methods

2.1. Animal Grouping and Model Construction

Nine NOD mice (4 weeks old) were purchased from the Nanjing Biomedical Research Institute of Nanjing University. NOD mice were randomly divided into three groups: control group (group C), model group (group M), and drug administration group (group T), with three mice in each group. The mice in the model group and the drug administration group were treated with porcine thyroglobulin and high iodine water to establish the mouse model of autoimmune thyroiditis. After successful modeling, Yanghe decoction formula granule (Xuyang Pharmaceutical Co., LTD., China) was prepared into 0.5 g/mL liquid medicine; the drug-administered group was given 0.5 g/ml Yanghe decoction formula 1 ml/100 g by gavage for 1 h, and the model group and normal group were given the same amount of saline by gavage once a day for 10 weeks. The serum and plasma samples were collected and stored at −20°C for serum and −80°C for plasma. The study protocols were approved by the Institutional Animal Care and Use Committee of Nanjing University of Chinese Medicine Affiliated Yancheng.

2.2. Enzyme-Linked Immunosorbent Assay

The serum collected was assayed for IL-35 (interleukin-35) and IL-6 (interleukin-6) inflammatory factors using enzyme-linked immunosorbent assay (ELISA) kits. The experiment was performed according to the instructions.

2.3. Mass Spectrometry Coupled with Ultra-High Performance Liquid-Phase Detection

Metabolite extraction was performed in strict accordance with the operating instructions, followed by onboard detection.

On-Board Detection. The target compounds were chromatographed on a Waters ACQUITY UPLCBEH Amide (2.1 mm × 100 mm, 1.7 μm) column using a Vanquish (Thermo Fisher Scientific) ultra-performance liquid chromatography. The A phase of the liquid chromatography was aqueous containing 25 mmol/L ammonium acetate and 25 mmol/L ammonia, and the B phase was acetonitrile. The sample tray temperature is 4°C, and injection volume is 2 μL.

The Thermo Q Exactive HFX mass spectrometer was capable of primary and secondary mass spectrometry data acquisition under the control of the control software Xcalibur (Thermo). Detailed parameters were as follows: sheath gas flow rate, 30 Arb; Aux gas flow rate, 25 Arb; capillary temperature: 350°C; full ms resolution, 60000; MS/MS resolution, 7500; collision energy, 10/30/60 in NCE mode; and spray voltage: 3.6 kV (positive) or −3.2 kV (negative).

Data Processing. The raw data were converted to mzXML format by ProteoWizard software, and then the peak identification, peak extraction, peak alignment, and integration were performed using the R package (kernel XCMS) written by ourselves and then matched with the BiotreeDB (V2.1) self-built secondary mass spectrometry database for substance annotation.

2.4. Mass Spectrometry Coupled with Gas Chromatography Detection

Metabolite extraction was performed strictly according to the operating instructions, and then all samples were analyzed by gas chromatography and time-of-flight mass spectrometry.

On-Board Detection. GC-TOF-MS analysis was performed using an Agilent 7890 gas chromatograph and a time-of-flight mass spectrometer. The system used a DB-5MS capillary column. 1 μL aliquots were injected in a nonsplit mode. Helium was used as the carrier gas with a front inlet purge flow rate of 3 mL min⁻¹ and a gas flow rate through the column of 1 ml min⁻¹. The initial temperature was held at 50°C for 1 min, then increased to 310°C at a rate of 20°C, and then held at 310°C for 6 min. The injection, transmission line, and ion source temperatures were 280, 280, and 250°C, respectively. The energy in electron collision mode was −70 eV. After a solvent delay of 4.83 min, mass spectral data were acquired in full-scan mode in the m/z range of 50–500 at a rate of 12.5 spectra per second.

Data Processing. The mass spectral data were analyzed for peak extraction, baseline correction, deconvolution, peak integration, and peak alignment using ChromaTOF software (V 4.3x, LECO). For the substance characterization work, the LECO-Fiehn Rtx5 database was used, including mass spectrometry matching and retention time index matching.

2.5. Nuclear Magnetic Resonance Detection

The experimental testing equipment was Varian Inova 600M Agilent.

Description of the Spectral Processing. The integration interval of the serum NMR spectra was 0.5–8.5 ppm with an integration spacing of 0.002 ppm, and a section of 4.60–4.80 ppm containing the residual water peak and the urea peak at 5.20–5.25 ppm and the region of its influence was removed. Among them, the demonstration of mouse serum spectra for groups C, M, and T were chosen: 1, 9, and 17, respectively.

2.6. Principal Component Analysis (PCA)

Data were formatted for logarithmic (LOG) transformation plus centralization (CTR) using SIMCA software (V16.0.2; Sartorius Stedim Data Analytics AB, Umea, Sweden), followed by automated modeling analysis.

2.7. Orthogonal Partial Least Squares-Discriminant Analysis (OPLS-DA)

The data were UV-formatted using SIMCA software (V14.1; MKS Data Analytics Solutions, Umea, Sweden), and OPLS-DA modeling analysis was first performed on the first principal component, and the quality of the model was tested with 7-fold cross-validation (7-fold cross-validation). Then, R2Y (interpretability of the model for the categorical variable Y) and Q2 (predictability of the model) were used to judge the validity of the model; finally, the validity of the model was further tested by a permutation test, which randomly changed the order of the categorical variable Y several times to obtain different random Q2 values.

2.8. Pathway Enrichment Analysis

The metabolic pathways of differentially expressed metabolites were analyzed by searching the relevant metabolic pathways of differentially expressed metabolites using authoritative metabolite databases such as Kyoto Encyclopedia of Genes and Genomes (KEGG) and PubChem.

3. Results

3.1. Principal Component Analysis

First, we performed PCA on the results of the three assays to observe the overall metabolic levels and species differences between the groups. The results of principal component analysis (positive ions) of the mass spectrometry coupled with gas and high-performance liquid phases showed that the samples of groups M and T were more closely distributed and both groups were distant from the samples of group C. The results of the NMR principal component analysis showed that the samples of groups M and T were distributed more into and partitioned from the samples of group C. This can all indicate that the more similar the type and content of metabolites in groups M and T, the more different the overall metabolic levels in groups M and T from group C. The samples were all in the 95% confidence interval. See Figure 1.

(a)

(b)

(c)

3.2. Orthogonal Partial Least Squares-Discriminant Analysis (OPLS-DA) and Differential Metabolite Analysis

We then modeled OPLS-DA for the M and T groups and screened for differential metabolites. The scatter plots of OPLS-DA model scores for the three assays showed that the horizontal distance between samples was farther for group M versus group T, which could indicate the greater the difference between the two groups, and the samples were very clearly differentiated. The samples were all in the 95% confidence interval. The results of the differential metabolite analysis showed that a total of 38 differential metabolites were screened for the mass spectrometry coupled with high-performance liquid phase (Table 1); a total of 120 differential metabolites were screened for the mass spectrometry coupled with gas phase (Table 2), and the conditions for this metabolite screening were VIP value (the projected importance of the variable obtained from the OPLS-DA model for the comparison of the substance in this group) > 1 and . NMR analysis showed that α-glucose and β-glucose were significant differentiating metabolites (see Figure 2).

(a)

(b)

(c)

(d)

Figure 2

OPLS-DA model score scatter plot and differential metabolite analysis. (a) Scatter plot of OPLS-DA model score and volcano plot of differential metabolites for group M versus group T detected by mass spectrometry coupled with the high-performance liquid phase. (b) Scatter plot of OPLS-DA model score and volcano plot of differential metabolites for group M versus group T detected by mass spectrometry coupled with gas phase. The size of scattering in the volcano plot represents the VIP value of OPLS-DA model, the larger the scatter the larger the VIP value. Significantly upregulated metabolites are shown in red, significantly down-regulated metabolites are shown in blue, and nonsignificantly different metabolites are shown in gray. (c) Scatter plot of OPLS-DA model scores for group M versus group T detected by NMR. (d) OPLS-DA loadings plot for group M versus group (T). The horizontal coordinates in the plot indicate the magnitude of chemical shifts, from right to left, with increasing values of chemical shifts; the vertical coordinates indicate the magnitude of loadings after back conversion, where the shades of color indicate the magnitude of correlation coefficients, red indicates a positive correlation, and blue indicates negative correlation. The marked substances in the figure are the differential metabolites that passed the critical value test of the correlation coefficient.

3.3. Enrichment Analysis of Metabolic Pathways of Differential Metabolites

We further analyzed the effect of differential metabolites on their pathways. The analysis based on the mass spectrometry combined with high-performance liquid phase detection results showed that the differential metabolites in the M and T groups were enriched to 11 pathways (Table 3), among which the pathways with higher enrichment were histidine metabolism, amino acid tRNA biosynthesis, phenylalanine, tyrosine and tryptophan biosynthesis, tryptophan metabolism, phenylalanine metabolism, cysteine, and methionine metabolism. The analysis based on the results of mass spectrometry combined with gas-phase detection showed that the differential metabolites of the M and T groups were enriched to 28 pathways (Table 4), among which the pathways with higher enrichment were pyrimidine metabolism, biosynthesis of pantothenic acid and CoA, metabolism of β-alanine, sulfur metabolism, glycerolipid metabolism, and metabolism of glycine, serine, and threonine. Subsequently, we took the intersection of the pathways enriched by the differential metabolites in the M and T groups for both high-performance liquid- and gas-phase methods coupled to mass spectrometry and obtained a total of five common pathways (biosynthesis of amino acid tRNA, metabolism of D-glutamine and D-glutamate, metabolism of tryptophan, metabolism of nitrogen, and metabolism of arginine and proline). See Figure 3

(a)

(b)

(c)

Figure 3

Metabolic pathway enrichment analysis of differential metabolites. (a) Pathway analysis of group M versus group T based on mass spectrometry combined with high-performance liquid chromatography. (b) Pathway analysis of group M versus group T based on mass spectrometry combined with gas chromatography. Each bubble represents a metabolic pathway; the bubble size represents the influence factor, the larger the size, the larger the influence factor; the vertical coordinate of the bubble and the color of the bubble indicate the value of the enrichment analysis; the darker the color, the smaller the value, the more significant the enrichment.

3.4. Comparison of Serum Inflammatory Factor Levels in Three Groups of Mice

Finally, we observed the serum inflammatory factor levels in the three groups of mice to determine the effect of Yanghe decoction on inflammatory factors in mice with Hashimoto’s thyroiditis. The results showed that the serum inflammatory factor IL-35 was significantly lower and IL-6 was significantly higher in mice of group M than group C, while the serum inflammatory factor IL-35 was significantly higher and IL-6 was significantly lower in mice of group T than group M. The results showed that the serum inflammatory factor IL-35 was significantly lower and IL-6 was significantly lower in mice of group T than group C. See Figure 4.

4. Discussion

Metabolism plays a central role as a signaling molecule, immunomodulator, endogenous toxin, and environmental sensor in all areas of biology, from ecology to bioengineering to cancer. Each of these fields is now increasingly being studied from a metabolic perspective. And these studies are valuable from a big picture perspective [11]. The metabolome is a collection of small-molecule chemical entities involved in metabolism and has traditionally been studied to identify biomarkers for the diagnosis and prediction of disease. Nowadays, the value of metabolomic analysis has been redefined from a simple biomarker identification tool to a technique for discovering active drivers of biological processes [12]. Metabolomics is the high-throughput characterization of metabolites from cells, organs, tissues, or biofluids using advanced analytical chemistry techniques [13]. NMR and mass spectrometry are commonly used in metabolomics; NMR is highly reproducible and quantitative, has a simple sample preparation protocol, and is capable of measuring analytes in a variety of solvent conditions, but it has low sensitivity. In contrast, the high sensitivity and low detection limits of mass spectrometry enable the detection of subtle metabolic changes that are not visible with NMR [14]. In this experiment, a total of 38 differential metabolites were screened based on mass spectrometry coupled with the high-performance liquid phase, 120 differential metabolites were screened based on mass spectrometry coupled with gas phase, and a total of α-glucose and β-glucose were analyzed based on NMR test results.

Measuring metabolite concentrations by metabolomics only tells half the story. Equally important is to understand pathway activity, which can be quantified as the flow of material per unit time, i.e., metabolic flux. In this experiment, we took intersections of pathways enriched by differential metabolites in the M and T groups for both mass spectrometry coupled with high-performance liquid and gas phases, yielding a total of five common pathways, namely, amino acid tRNA biosynthesis, D-glutamine and D-glutamate metabolism, tryptophan metabolism, nitrogen metabolism, and arginine and proline metabolism.

Amino tRNA is a substrate for translation and plays a key role in determining how the genetic code is interpreted into amino acids. The function of aminyl-tRNA synthesis is to precisely match amino acids to tRNAs containing the corresponding anticodons [15]. Aminyl-tRNA synthetase is essential for the physical interpretation of the genetic code [16], and in addition to its function in protein synthesis, it is involved in various cellular processes such as immune and inflammatory responses, angiogenesis, and apoptosis [17,18]. Just one study showed that the pentose phosphate pathway, amyl-tRNA biosynthesis, and pyrimidine metabolism are the main pathways altered in hypothyroidism [19]. Glutamate is a key excitatory neurotransmitter responsible for maintaining cognitive function and neuronal plasticity [20], while metabolites associated with glutamate metabolism, 2-ketoglutarate, L-aspartate, and fumarate are associated with the gut microbiota, and their alterations may affect human health [21]. Some studies have indicated that glycerophospholipid, glutamine, and glutamate metabolism, and related metabolites are potential key targets for common molecular mechanisms linking HIV to NCDs through inflammation and oxidative stress [22]. Tryptophan is an essential aromatic amino acid consisting of a β-carbon attached to the 3-position of the indole group. Although tryptophan is the least abundant amino acid in proteins and cells, it is a biosynthetic precursor for a large number of microbial and host metabolites [23,24]. Tryptophan metabolism in the intestine is the direct conversion of tryptophan by intestinal microorganisms into several molecules, such as indoles and their derivatives. And many of these indole derivatives, in turn, are ligands for aryl hydrocarbon receptors [25]. Aryl hydrocarbon receptor signaling is thought to be a key component of the immune response at the barrier site and thus can maintain intestinal homeostasis by acting on epithelial renewal, barrier integrity, and many immune cell types [26]. Arginine is a nonessential or semiessential amino acid that plays an important role in a variety of biological functions including cell proliferation, survival, and protein synthesis. It is also a precursor for the production of nitric oxide, polyamines, proline, creatinine, and glutamate. As a multifunctional amino acid, arginine plays an important role in physical health by being involved in tissue damage and chronic metabolic diseases [27]. Arginine has also been associated with endothelial function, inflammation, and airway hyperresponsiveness [28]. Just one study indicated that arginine and proline metabolic pathways are related to asthma pathogenesis [29]. The above combined with the results of the present experiment could suggest that Yanghe decoction may maintain homeostasis by altering the relevant metabolic pathways and thus improving the disease. In addition, the above pathways have shown relevance to inflammation as well as immune cells. For this reason, we also investigated the effect of Yanghe decoction.

Inflammation is a comprehensive physiological response to tissue damage, which is caused by physical injury, infection, exposure to toxins, or other types of trauma [30]. There is growing evidence that inflammation is a major factor in the progression of many diseases, including autoimmune thyroiditis [31]. The results of the present study showed that serum inflammatory factor IL-35 was significantly lower and IL-6 was significantly higher in mice in the model group compared with the normal control group, whereas serum inflammatory factor IL-35 was significantly higher and IL-6 was significantly lower in mice treated based on Yanghe decoction compared with the model group. This may be due to the effect of one or a combination of herbs in the composition of Yanghe decoction. Deer antler tablets have antifatigue, anti-inflammatory, and analgesic effects, while deer antler peptides are the main active ingredients obtained by isolation from deer antler tablets [32]. It has been shown that in osteoblasts, antler peptides block TNF-α-mediated inhibition of osteoblastogenesis and inhibit osteoclastogenesis through the nuclear factor-κB (NF-κB)/p65 pathway. In addition, deer antler peptides reduce levels of interleukin 1β and interleukin 6, as well as oxidative responses induced by increased catalase activity and reduced malondialdehyde levels [33]. Previous studies have also indicated that Yanghe decoction may improve the symptoms of Hashimoto’s thyroiditis and reduce inflammation [34]. This could suggest that Yanghe decoction can effectively reduce the inflammatory response in Hashimoto’s thyroiditis, but whether the specific mechanism is related to metabolic pathways remains to be explored.

5. Conclusion

In summary, we detected multiple metabolites that can be altered by Yanghe decoction by NMR and mass spectrometry coupled with gas or liquid chromatography, and most of them were related to aminyl-tRNA biosynthesis, D-glutamine and D-glutamine metabolism, tryptophan metabolism, nitrogen metabolism, and arginine and proline metabolic pathways. In addition, Yanghe decoction can effectively reduce serum inflammatory factor levels in mice with Hashimoto’s thyroiditis.

Although we identified the metabolites that can be altered by Yanghe decoction and the pathways that are highly affected, there are still shortcomings in this study. We only observed the metabolomic profile of plasma, and further studies should evaluate serum, urine, cerebrospinal fluid, and brain samples to accurately reflect the pathological changes in Hashimoto’s thyroiditis and the therapeutic mechanisms of Yanghe decoction.

Data Availability

All data generated or analyzed during this study are included in this article.

Conflicts of Interest

The authors declare that they have no conflicts of interest.

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Copyright © 2022 Xing Zhang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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