Discrimination of Traditional Chinese Medicine Syndromes in Type 2 Diabetic Patients Based on Metabolomics-Proteomics Profiles

Materials and Methods The metabolomics-proteomics of sixty patients with T2DM were acquired by high-performance liquid chromatography (HPLC). In addition, some clinical features, containing total cholesterol (TC), triglycerides (TG), hemoglobin A1c (HbA1c), body mass index (BMI), and low-density lipoprotein (LDL) together with high-density lipoprotein (HDL), were determined via clinical detection strategies. Abundant metabolites and proteins, respectively, were identified with the analysis of liquid chromatography tandem mass spectrometry (LC-MS/MS). Results 22 differentially abundant metabolites and 15 differentially abundant proteins were determined. The analysis of bioinformatics suggested that the differentially abundant proteins were commonly associated with the renin-angiotensin system, vitamin digestion and absorption, hypertrophic cardiomyopathy, and so on. Furthermore, differentially abundant metabolites were amino acids and were associated with the biosynthesis of CoA and pantothenate, together with the metabolisms of phenylalanine, beta-alanine, proline, and arginine. Combination analysis revealed that the vitamin metabolism pathway was predominantly affected. Conclusions DHS syndrome can be separated by certain metabolic-proteomic differences, and metabolism is particularly prominent, especially in vitamin digestion and absorption. From the molecular level, we provide preliminary data for the extensive application of TCM in the study of T2DM, and at the same time benefited in a sense diagnosis and treatment of T2DM.


Introduction
Diabetes is a serious health problem in the world, and the management costs of the national health system and patients are high. Te latent efect of diabetes on health care systems, health, and life expectancy along with fnancial costs will increase over the next few years [1]. Te pathogenesis of T2DM is not entirely clear. It is the most common type of diabetes characterized through impaired β-cell function, insulin resistance (IR), chronic hyperglycemia, as well as comorbidities for instance cardiovascular disease and obesity [2]. Treatment of T2DM needs the sequence of latent measures to manage hyperlipidemia, hyperglycemia, and risk factors for a series of complications related to diabetes, as well as specifc biomarkers.
Owing to the diversity of T2DM diseases, identifying biomarkers of T2DM has become a huge problem. Tey are employed to assess chemical characteristics, target validation, disease status, and the response of treatment [3]. With the progress of metabolic technology and proteomics, serum biomarkers of T2DM have existed. In addition, integrating various profles for instance transcriptomics, proteomics, and metabolomics will better present the biological process and gene expression regulation of T2DM so as to formulate prevention strategies and reduce complications [4].
TCM is a medical system centered on medical care. It has more than 3000 years of continuous experience of practice and is improved via the treatment observation [5]. As a result, it has its own features and advantages in personalized treatment and early intervention. In the theory of TCM, syndrome diferentiation (also known as pattern classifcation or Zheng diferentiation) is the essence and basis [6]. Diagnosis is principally decided by the overall human symptoms observation, involving observation, touching, smelling, listening, and background research [7] instead of the test at the "micro" level. For the same disease, sometimes diferent treatment approaches are applied for the treatment of various pathological states. Te relationship between these syndromes and the relevant treatment comes from practical experience and is improved through the investigations of long-term treatment. Nevertheless, due to the lack of technological and scientifc means, TCM is facing serious challenges and lack of modern research [8]. Terefore, it is essential to explore the changes of compounds (containing fatty acids, proteins, metabolites, and so on) in several symptoms of a same disease in order to confrm these experiences and subsequently expand the disease understanding.
In accordance with the theory of TCM, T2DM is considered as Xiaokezheng having symptomatic polydipsia [8]. TCM in-depth classifes Xiaokezheng into distinct syndromes and has relevant clinical manifestations, containing damp-heat syndrome (DHS), Qi Yin defciency, and Qi defciency [9]. Based on diferent syndromes of TCM, TCM can provide more efective personalized treatment according to its pathological features. So far, more and more randomized clinical trials have focused on the advantages of TCM in the treatment of diabetes. In this research, we employed metabolomics-proteomics analysis to identify non-DHS and DHS syndromes of T2DM.

Plasma Sample Collection.
Te experiment was authorized through the ethics committee of the institute and complied with the principles of the Helsinki declaration. Moreover, from the patients, the informed consent to research protocol could be acquired. Te plasma samples were harvested from the T2DM patients with and without the DHS syndrome (thirty in each group). In both experimental groups, all of the chose patients were diagnosed through syndrome diferentiation of western medicine and TCM. Tey were ofered via Nanjing Hospital of Traditional Chinese Medicine and adhered to the guidance of the Hospital Human Subjects Committee. Te values of fasting blood glucose (FPG) were more than 7.0 mmol/L, and some blood lipid parameters, for instance, TG, TC, LDL, and HDL, were acquired via clinical detection approaches. It was classifed via two authentic TCM doctors on the basis of "Diabetes TCM Diagnostic Criteria" [9]. Table 1 shows the clinical features of TCM syndromes of T2DM.
After fasting at night, venous blood was harvested as mentioned above. Te bufy coat, plasma, and serum were isolated from whole blood and kept at a temperature of −80°C within four hours after collection. In order to repeat freeze-thaw cycles and maximize the longevity, serum and plasma samples were widely divided and placed at −80°C prior to the subsequent use. Levels of clinical features were determined by automated clinical laboratory methods using a diagnostic analyzer.

Data Processing and Metabolite
Identifcation. Te integrated and centroided data of UPLC-TOFMS were pretreated with XCMS software according to the manufacturer's recommendation [10], which was then normalized to the ionic strength of their respective internal standards in metabolomics analysis experiments [11]. Te remarkably altered metabolites were identifed via multivariate analysis. Te Madison Metabolomics Consortium Database (MMCD) [12] as well as the Human Metabolome Database (HMDB) [13] were employed to determine the metabolites through accurate search based on mass. Te identifcation of metabolite was demonstrated through the comparison of the retention time under identical chromatographic conditions and through the match of the cleavage mode of parent ions in biological samples with that of standard metabolites via applying tandem mass spectrometry (UPLC-TOFMS/MS).

TMT Proteomic Analysis.
Te UHPLC separation was carried out using a 1290 Infnity series UHPLC System (Agilent Technologies), equipped with a UPLC BEH Amide column (2.1 * 100 mm, 1.7 μm, Waters). Te mobile phase consisted of 25 mmol/L of ammonium acetate and 25 mmol/L of ammonia hydroxide in water (pH � 9.75) (A) and acetonitrile (B). Te analysis was carried out with elution gradient as follows: 0∼0.5 min, 95%B; 0.5∼7.0 min, 95%∼65% B; 7.0∼8.0 min, 65%∼40% B; 8.0∼9.0 min, 40%B; 9.0∼9.1 min, 40%∼95%B; and 9.1∼12.0 min, 95%B. Te column temperature was25°C. Te auto-sampler temperature was 4°C, and the injection volume was 2 μL (pos) or 2 μL (neg), respectively. Te TripleTOF 6600 mass spectrometry (AB Sciex) was used for its ability to acquire MS/ MS spectra on an information-dependent basis (IDA) during an LC/MS experiment. In this mode, the acquisition software (Analyst TF 1.7, AB Sciex) continuously evaluates the full scan survey MS data as it collects and triggers the acquisition of MS/MS spectra depending on preselected criteria. In each cycle, the most intensive 12 precursor ions with intensity above 100 were chosen for MS/MS at collision energy (CE) of 30 eV. Te cycle time was 0.56 s. ESI source conditions were set as following: gas 1 as 60 psi, gas 2 as 60 psi, curtain gas as 35 psi, source temperature as 600°C, declustering potential as 60 V, ion spray voltage foating (ISVF) as 5000 V or −4000 V in positive or negative modes, respectively. One QC is inserted for every 8 samples, for a total of 7 QCs. Protein Pilot software 3.0 (ABSCIEX) was used to quantify relative abundance and identify protein and peptide. MMTS was utilized as the fxed modifcation of the cysteine to analyze the data, and the database could be searched with the interval rate of confdence (95%) to identify the protein. For the target proteins, their high confdence peptides revealing abundant production spectrum were chose for the assay of multiple reaction monitoring (MRM). TargetLynx 2.0 was used to treat the data of MRM, and the Graph Pad Prism program v 5.0 was employed to conduct the statistical analysis and for the generation of the receiver operating features. Each peptide was compared with the Wilcoxon test.

Bioinformatics Analysis.
Te analysis of pathway enrichment and Gene Ontology (GO) was performed for the protein functional enrichment. In accordance with the presenting report, with the InterProScan database (v.5.14-53.0 https://www.ebi.ac.uk/interpro/), GO was annotated (containing the cellular component (CC), molecular function (MF), and the biological process (BP)). Te exploration of pathway enrichment was implemented with the Kyoto Encyclopedia of Genes and Genomes (KEGG) Database [14]. Te KEGG mapper (v.2.5, https://www.kegg.jp/ kegg/mapper.html) along with KAAS (v.2.0, https://www. genome.jp/kaas-bin/kaas_main) were the major tools employed by the database of KEGG. Te WoLF PSORT software (v.0.2, https://www.genscript.com/psort/wolf_ psort.html) was applied to predict the subcellular localization. Te heat map obtained via the function heatmap in R language package is applied to visualize the cluster members. For each annotation, the comparison of enrichment degree between all the identifed proteins and diferentially abundant proteins was performed with Fisher's exact test, and P less than 0.05 was regarded as signifcant.

Statistical Analyses.
Te biochemical and clinical data were presented with mean ± SD. Te SPSS program for Windows (version 21 statistical software: Texas instruments, IL, USA) was employed for all of the statistical analyses. Te Mann-Whitney/Wilcoxon and Student's t-test were exploited to carry out the diferences between both TCM syndrome groups of T2DM when proper. Te two-tailed p value is signifcant when FDR-adjustedp < 0.05.

Clinical Data of the Study Subjects.
Te biochemical and clinical data of the study subjects are refected in Table 2. Te DHS group had signifcantly higher values for TG (P < 0.001), TC (P < 0.05), fasting insulin (FINS, P < 0.05), fasting c-peptide (FCP, P < 0.05), and insulin resistance index (HOMA-IR, P < 0.05). Furthermore, the DHS group showed a lower mean level of HDL and a higher level of LDL than the non-DHS group, although there was no statistical diference.

Identifcation and Functional Enrichment Analysis of Diferentially Abundant Proteins.
Using the abovementioned analytical conditions, proteomic profles from 30 T2DM patients with TCM syndrome with DHS and 30 without DHS were obtained by LC-MS/MS. Tere were 654 proteins available. After data management and normalization, there were 621 quantifable proteins ( Figure 1). In the end, ffteen proteins revealed obvious diferences (P < 0.05; FCa0< 0.83 or >1.2), of which 3 proteins were increased and 12 proteins were decreased (Figures 1(a) and 1(b)). With the aim of determining the features of diferentially abundant proteins, the analysis of KEGG and GO of proteins were annotated.
BP classifcation of the proteins suggested that various abnormal biological processes appeared in the syndrome of DHS, for instance positive regulation or regulation of the cholesterol esterifcation, sterol or steroid esterifcation, positive regulation of the steroid metabolism, and proteinlipid complex remodeling (Figure 1(c)). Remarkably, representative diferentially abundant proteins including AGT and APOA4 participated in all the above process.
Te classifcation of protein via CC indicated that most diferentially expressed proteins are located in the extracellular regions, even in the extracellular organelles or vesicles. Te classifcation of protein via MF indicated that more proteins were associated with iron binding, followed by cation binding, aminopeptidase activity, antioxidant activity, exopeptidase activity, and so on (Figure 1(c)). Te following analysis of KEGG suggested that the most remarkable change pathways involved the renin-angiotensin system, vitamin digestion and absorption, hypertrophic cardiomyopathy, dilated cardiomyopathy, protein digestion and absorption, adrenergic signaling in cardiomyocytes, and metabolic pathways. In conclusion, extensive and comprehensive proteomic data revealed that many metabolic pathways of T2DM were abnormal in the syndrome of DHS.

Changes in Serum Metabolites Detected by Untargeted
Metabolomics. Relative standard deviation denoising was conducted (individual peaks were fltered to remove noise, and the deviation value was fltered based on the relative standard deviation). 1895 peaks were determined. In addition,    International Journal of Analytical Chemistry the approach of internal standard normalization was employed in analyzing the data. Te data were scaled and then transformed logarithmically to minimize the infuence of variable high variance and noise. After above transformations, the grouping and distribution of samples was visualized with principal component analysis (PCA). Te confdence interval (95%) in the PCA score graph was employed as a threshold to determine latent outliers in the data set. Te outcomes indicated that our present metabolomics data set has outstanding reproducibility and stability (Figure 2(a)).
Orthogonal projection with latent structures discriminate analysis (OPLS-DA) was performed to choose remarkably changed metabolites between non-DHS and DHS groups (Figure 2(b)). Subsequently, the calculation of the Q 2 and R 2 values was carried out with a 7-fold cross-validation, respectively, suggesting how well the variables were predicted and the changes in variables were explained. In order to test the prediction ability and robustness of the OPLS-DA model, 200 permutations were carried out in-depth, and subsequently, the intercept values of Q 2 and R 2 were acquired.
Here, the Q 2 intercept value was the model reliability, the risk of over ftting, and the model robustness; the smaller the better (Figure 2(c)). In addition, the frst principal component, the variable importance in the projection (VIP) value in the analysis of OPLS-DA, was acquired (Figure 2(d)). Metabolites with P < 0.05, FC > 1, and VIP >1 (Student's t-test) were regarded to be remarkably changed metabolites. In the end, 22 metabolites which revealed signifcant diferences in DHS (FC > 1.2 and P < 0.05) were determined. As shown in Figure 2(e), imidazole, L-pipecolic acid, L-citrulline, Lcarnitine, and 3′-O-methylguanosine were decreased, while pantothenate, sphingomyelin, and thioetheramide-PC were increased. Furthermore, the subsequent metabolic pathways had signifcantly changed: the biosynthesis of CoA and pantothenate, the metabolisms of phenylalanine, betaalanine, proline, and arginine ( Figure 2(f)). Tese outcomes exhibited that vitamin and amino acid metabolism were changed in T2DM patients with the syndrome of DHS. Tese analyses were performed by using SIMCA (16.0.2) software.

Combination Analysis of Proteomics and Metabolomics
Data. Te outcomes of LC-MS/MS were analyzed with Paintomics3 (v.0.4.5, http://www.paintomics.org). We calculated the content information of all diferentially expressed proteins and metabolites, compared the correlation between them, and used Spearman rank and rank correlation to analyze the diferent metabolites and proteins. We took the correlation coefcient Q-value <0.05 as the condition of signifcant correlation. Te heatmap of proteomic-metabolomic correlation analysis for group DHS vs. non-DHS revealed that SLC8A3 and SERPINA10 had a positive relationship with pantothenate and negative with Tr-Tyr, and lysosomal pro-X carboxypeptidase (PRCP) had positive correlation with 3′-O-methylguanosine and Tr-Tyr and negative with pantothenate. DL-Norvaline was negatively related to oncoprotein-induced transcript 3 (OIT3), interferon-induced very large GTPase 1 (GVINP1), glutathione reductase (GSR), and endoplasmic reticulum aminopeptidase 1 (ERAP1). L-Pipecolic acid was negatively related to CBFA2T2, carbonic anhydrase 3 (CA3), and APOA4. Tioetheramide-PC was positively related with Akinase anchor protein 12 (AKAP12) and negatively with biotinidase (BTD) (Figure 3(a)). Trough the visual analysis of the KEGG diagram, it can be concluded that metabolites and protein were jointly regulated. Te vitamin digestion and absorption pathway exhibited downregulation of APOA4 (P < 0.05, FC � 0.60), BTD (P < 0.05, FC � 0.76) and upregulation of pantothenate (P < 0.05, FC � 1.20) (Figure 3(b)). Te integrated analysis outcomes indicated the potential mechanism of vitamin metabolism in T2DM patients with DHS syndrome.

Discussion
Omics are generally employed to elucidate the diabetes pathogenesis and screen latent phenotypic markers of T2DM. In comparison with single omics, integrated analysis of multiomics (the integrated analysis of metabolomics and proteomics [15] or metabolomics and transcriptomics [16], etc.) can more deeply reveal the molecular characteristics and physiological mechanism of this disease. In our work, DHS produced a lot of data on the proteomic analysis of T2DM patients' serum, refecting the mechanisms of diabetes occurrence and development, for example the reninangiotensin system, vitamin digestion and absorption, hypertrophic cardiomyopathy, dilated cardiomyopathy, protein digestion and absorption, adrenergic signaling in cardiomyocytes, and metabolic pathways. Serum metabolites can exhibit the body metabolic changes, which is helpful to the monitor of metabolic process in the state of disease [17]. With the aim of understanding the whole metabolic status of T2DM patients with DHS, we implemented a metabolomic analysis on the serum samples and acquired the metabolic profles. Besides, we implemented an integrated metabolomic and proteomic analysis. Long-term exposure to high blood glucose could enhance the risk of amputation, heart attacks, diabetic retinopathy as well as strokes. Intuitively, T2DM could be classifed into several cases without or with the complications. Nevertheless, so far, T2DM has not been classifed in accordance with the clinical parameters. Interestingly, various syndromes of T2DM can be decided via the theory of TCM, despite they are on the basis of long-term experience of practical. More signifcantly, special treatment is generally carried out under the guidance of various syndrome types. As a result, with the aim of further understanding T2DM, it is essential to prove various syndromes through biological approaches, especially the analysis of omics with big data. In this study, two syndromes were explored applying the method of metabolomics-proteomics analysis, together with the clinical data including glucose measurements and four lipid parameters (TG, TC, and HDL together with LDL). PCA and OPLS-DA were carried out to, respectively, construct the discriminant models for the T2DM patients with two syndromes of TCM and next explore the correlation between syndromes and proteomics-metabolites. OPLS-DA 6 International Journal of Analytical Chemistry  is a complex and generally applied supervised clustering approach, which is employed to construct the best discriminant surface in order to isolate the best classifcation. Te diference between the two groups was signifcant, and with Hotelling's T-square ellipse, the samples were basically within the confdence interval of 95%. Tus, the statistical analysis results indicated that the plasma metabolic profles could exhibit some perturbations between DHS and non-DHS syndromes in TCM.
According to Table 2, it is understandable why DHS patients with lower APOA4 exhibit signifcantly elevated TC and TG. Te upregulated FCP, FINS, and HOMA-IR also refect the worsening process of T2DM. It is an efective and innovative method to divide the disease into distinct stages in accordance with a variety of symptoms and then carry out the symptom-specifc treatment. In addition, the observation of syndrome-related biomarkers is especially signifcant for the personalized treatment. Biomarkers related to syndrome of TCM can assist the clinical diagnosis, promote the modernization of TCM, and ofer a reference for exhibiting the diabetes pathogenesis.
Te proteomics analysis revealed that diferentially abundant proteins were related to the vitamin digestion and absorption. After integrated study of the metabolomics and proteomics outcomes, it can be observed that both proteins (APOA4 and BTD) in the DHS group were downregulated as well as one amino acid metabolite (pantothenate) was upregulated in the serum, thus afecting the vitamin metabolism pathway. It has been reported that the levels of plasma vitamin C in patients with T2DM were relatively low, which made people pay growing attention to the preventive efect of vitamin C on T2DM and its related complications. Te prospective cohort survey in seven countries exhibited that the glucose intolerance was negatively correlated with the intake of dietary vitamin C, refecting that antioxidants, for example vitamin C, may possess a protective efect in the occurrence of T2DM and impaired glucose tolerance [18]. In addition, some clinical researches have confrmed that the supplementation of vitamin D can improve the principal metabolic parameters linked to the insulin resistance, containing HbA1c, TC, LDL, triglycerides, as well as HOMA-IR. Te supplementation of vitamin D for three months in the elderly with the metabolic disorders can evidently increase the level of HDL and decrease the ratio of TG/HDL and HOMA-IR [19], which is also supported by our results. Similarly, the percentage of HbA1c in T2DM patients decreased by approximately 0.5% after the supplementation of vitamin D [20]. Pantetheine, also called vitamin B5, plays a crucial role in the CoA biosynthetic pathway. It presents good opportunity for drug discovery moving forward [21]. Since B vitamins are the cornerstone of all the cell repair, during the frst two years of the supplementation of vitamin D, the increase of repair and the improvement of sleep ultimately leaded to the consumption of B5 reserves. Owing to the lack of B5, the generation of coenzyme A in the brain was reduced, which may lead to the reduction of acetylcholine generation, resulting in sleep disorders. Te decrease in CoA in the adrenal gland may lead to the reduction of the cortisol level (adrenal fatigue), resulting in the increase in arthritis, allergy, and infammation [22]. As the DHS group showed lower APOA4 and higher pantothenic, it is understandable that non-DHS patients feature sleep hyperhidrosis, fatigue, as well as joint disorders. In the light of lots of articles [23][24][25] connecting vitamin D with the normal immune system function and the fact that B5 is essential for cortisol production, it can be speculated that the continuous defciency of B5 and vitamin D may lead to the proinfammatory and abnormal state in patients with T2DM.
As the metabolomics was "untargeted" and the number of signifcant features in both the proteins and the metabolomics was not very many, further work and large follow-up studies are required to remedy the defect of this research.

Conclusion
To sum up, via implementing metabolomics and proteomics analysis of the serum of T2DM patients with or without DHS, we gave an initial understanding of the features of diabetes with two diferent TCM syndromes from a molecular perspective. Furthermore, we found that, in the DHS patients, the metabolic abnormalities were especially prominent, particularly vitamins metabolism. Tese results provided a fundamental data for the extensive application of TCM in the study of T2DM and at the same time benefted in a sense diagnosis and treatment of T2DM.

Data Availability
Te quality control and omics data used to support the fndings of this study are available from the corresponding author upon request.

Conflicts of Interest
Te authors declare that there are no conficts of interest.