Serum Protein KNG1, APOC3, and PON1 as Potential Biomarkers for Yin-Deficiency-Heat Syndrome

Yin-deficiency-heat (YDH) syndrome is a concept in Traditional Chinese Medicine (TCM) for describing subhealth status. However, there are few efficient diagnostic methods available for confirming YDH syndrome. To explore the novel method for diagnosing YDH syndrome, we applied iTRAQ to observe the serum protein profiles in YDH syndrome rats and confirmed protein levels by ELISA. A total of 92 differentially expressed proteins (63 upregulated proteins and 29 downregulated proteins), which were mainly involved in complement and coagulation cascades and glucose metabolism pathway, were identified by the proteomic experiments. Kininogen 1 (KNG1) was significantly increased (p < 0.0001), while apolipoprotein C-III (APOC3, p < 0.005) and paraoxonase 1 (PON1, p < 0.001) were significantly decreased in the serum of YDH syndrome rats. The combination of KNG1, APOC3, and PON1 constituted a diagnostic model with 100.0% sensitivity and 85.0% specificity. The results indicated that KNG1, APOC3, and PON1 may act as potential biomarkers for diagnosing YDH syndrome. KNG1 may regulate cytokines and chemokines release in YDH syndrome, and the low levels of PON1 and APOC3 may increase oxidative stress and lipolysis in YDH syndrome, respectively. Our work provides a novel method for YDH syndrome diagnosis and also provides valuable experimental basis to understand the molecular mechanism of YDH syndrome.


Introduction
Yin-deficiency-heat (YDH) syndrome, also known as the pathological condition "internal heat due to Yin deficiency," is a common subhealth status in Traditional Chinese Medicine (TCM). YDH syndrome occurs frequently in individuals with Yin deficiency constitution, which is the fourth most common pathological constitution in general population [1]. Nowadays, YDH syndrome presents a great challenge in China, prevailing especially among white collar workers and college students [2]. YDH syndrome among individuals aged between 15 and 34 years has been shown to be more common than among other age groups [1]. Individuals with YDH syndrome present with deterioration in physical function, fatigue, weakness, emaciation, five-center (the palms, soles, and chest) heat, and tidal fever, which negatively affect the quality of life and the work productivity.
YDH syndrome could be relieved by Chinese herbal compound, and if diagnosed and treated promptly, it can be prevented from developing into disease. However, as a subhealth status without any obvious manifestations, the diagnosis of YDH syndrome has always been a tough problem. Currently, the traditional clinical diagnosis of YDH syndrome is based on subjective observation, which depends heavily on the clinical experience or knowledge of practitioner in TCM. In addition, questionnaires are commonly used to identify YDH syndrome, whereas the questions which are ambiguous or difficult-to-distinguish may lead to the bias in the test. The current methods for the diagnosis of YDH syndrome are lack of scientific basis. Therefore, novel methods suitable for YDH syndrome diagnosis are urgently needed.
Given the noninvasiveness and easy accessibility, serum is frequently used to screen diagnostic biomarkers for many diseases. Furthermore, serum contains approximately 10,000 proteins from cells and tissues [3], and the alteration of protein level sensitively reflects different diseases or pathological conditions. Former studies have successfully identified serum biomarkers for the diagnosis of breast carcinoma [4], colorectal cancer hepatic metastasis [5], and pathological characteristics of pulmonary TB with TCM syndromes [6]. In this study, we applied iTRAQ labeling coupled with twodimensional liquid chromatography-tandem mass spectrometry (2D LCMS/MS) to investigate differentially expressed proteins in the serum of YDH syndrome rats. Further bioinformatics analysis revealed that differentially expressed proteins KNG1, APOC3, and PON1 were closely related to YDH syndrome and may act as potential biomarkers for diagnosis of YDH syndrome. Our results suggest the potential role of KNG1, APOC3, and PON1 in the diagnosis of YDH syndrome and provide important insights to understand the molecular mechanism of YDH syndrome.

Experimental Design.
The schematic of the experimental workflow is shown in Figure 1. Serum samples from YDH syndrome rats and normal rats were subjected to iTRAQcoupled 2D LC-MS/MS analysis. Bioinformatics approaches were used to explore the function of differentially expressed proteins. The expression levels of proteins were measured by ELISA.

Animals and Treatment
. SPF female Sprague-Dawley rats, weighing 180-220 g, were purchased from the Experimental Animal Center of Zhejiang Province (China). All rats were housed at a constant temperature of 23 ± 1 ∘ C and a 12 h light/dark cycle with free access to water and standard rat diet. All experimental procedures were approved by the Zhejiang University Institutional Animal Care and Use Committee. The pungent and hot Chinese herbs, Fuzi (Radix Aconiti Praeparata), Ganjiang (Rhizoma Zingiberis), and Rougui (Cinnamomum cassia) were purchased from the Hangzhou Hu Qingyu Drugstore (China). These herbs with warm nature consume Yin fluid, which is commonly used in TCM to induce YDH syndrome animal models [7]. Equal amounts of Fuzi, Ganjiang, and Rougui were mixed, decocted, and concentrated to a final concentration of 4 g/mL according to the previously described method [8]. After acclimation for 7 days, rats were randomly divided into the model group (herbal decoction, 2 mL/100 g/d, by gastrogavage) and the control group (sterile saline solution, 2 mL/100 g/d, by gastrogavage). All rats were sacrificed after 3 weeks of treatment, and serum samples were collected and stored at −80 ∘ C. Thymus, spleen, and adrenal gland were immediately removed and weighed. The anesthetized rats were euthanized by cervical dislocation.

iTRAQ-2D LC-MS/MS.
Sample pooling is commonly used in proteomic studies to increase the precision and accuracy of the results [9]. Serum samples from the model group ( = 16) and the control group ( = 16) were subjected to iTRAQ labeling according to the manufacturer's instructions (Applied Biosystems, Foster city, CA, USA), and 16 samples in each group were randomly separated into two subgroups to establish two biological replicates, so 4 pooling samples were generated. To enrich the low abundant protein, Agilent MARS-14 column (Agilent Technologies, Santa Clara, CA, USA) was used to remove 14 highly abundant proteins, including albumin, IgG, antitrypsin, IgA, transferring, haptoglobin, fibrinogen, alpha 2-macroglobulin, alpha 1-acid glycoprotein, IgM, apolipoprotein AI, apolipoprotein AII, complement C3, and transthyretin, and the eluent of protein samples were quantified by the Bradford method. The protein samples (100 g) of each group were reduced, alkylated, and digested with trypsin (Sigma, St. Louis, MO, USA) overnight at 37 ∘ C. Then, protein samples from the control group were labeled with reporter tags 114 and 116 and protein samples from the YDH model group were labeled with reporter tags 113 and 115. The labeled peptides were pooled and desalted and then dried by a rotation vacuum concentrator (Christ RVC 2-25, Christ, Osterode, Germany).
The iTRAQ-labeled peptides were fractionated by strong cation exchange (SCX) liquid chromatography using a polysulfoethyl column (2.1 × 100 mm, 5 m, 200 >; Nest Group, Inc., Southborough, MA, USA). A gradient of buffer A (10 mM KH 2 PO 4 , 25% ACN, pH 2.6) and buffer B (350 mM KCl, 10 mM KH 2 PO 4 , 25% ACN, pH 2.6) was used to elute the peptides adsorbed on the column. The concentrations of the eluted peptides were monitored by measuring the absorbance at 214 nm [10]. A total of ten SCX fractions were collected and concentrated. Each fraction was dissolved and subjected to Reverse-phase LC fractionation. The LC elution was subsequently analyzed on a Triple TOF 5600 system (Applied Biosystems) in duplicate as two technical replicates. In an information-dependent acquisition mode (IDA), the survey scans were acquired from 400 to 1500 m/z with up to 20 most intense multiply charged ions selected for MS/MS analysis [11]. The product ion spectra were accumulated in the 100-2000 m/z to enhance the intensities of the iTRAQ reporter ions (113, 114, 115, and 116 m/z) for quantification. The relative abundance of the peptides and proteins was reflected by the ratio of the peak area of the iTRAQ reporter ions intensities [12].
The data of MS/MS spectra were searched against the IPI rat database (IPI.rat.v3.69, 39 578 entries) with ProteinPilot6 2.0.1 software (Applied Biosystems) [13]. ProteinPilot was searched with a fragment ion mass tolerance of 0.050 Da and a parent ion tolerance of 10.0 ppm. Scaffold (version Scaffold 4.6.2, Proteome Software Inc., Portland, OR) was used to validate MS/MS based peptide and protein identifications. Peptide identifications were accepted if they could establish an FDR less than 1.0% by the Scaffold Local FDR algorithm and contained at least 2 identified peptides. Proteins that contained similar peptides and could not be differentiated based on MS/MS analysis alone were grouped to satisfy the principles of parsimony. Scaffold Q+ (version Scaffold 4.6.2, Proteome Software Inc., Portland, OR) was used to quantitate Label Based Quantitation (iTRAQ, TMT, SILAC, etc.) peptide and protein identifications. Normalization was performed iteratively (across samples and spectra) on intensities, as described in Statistical Analysis of Relative Labeled Mass Spectrometry Data from Complex Samples Using ANOVA [14]. Medians were used for averaging. Spectra data were log-transformed, pruned of those matched to multiple proteins, and weighted by an adaptive intensity weighting algorithm. values less than 0.05 in each independent iTRAQ experiment and the fold-changes ratio lower than 0.8 or higher than 1.25 were considered as significant [15,16].

Bioinformatics Analysis.
We annotated function or feature of proteins from several different categories, including Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, and Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) software. The molecular function, cellular component, and biological process were analyzed by searching GO database (http://geneontology .org/). The signal pathways of proteins were annotated by KEGG pathway database (http://www.genome.jp/kegg/mapper.html). The interaction networks of the identified proteins were analyzed by STRING software (http://string-db.org/).

Enzyme-Linked Immunosorbent Assay (ELISA).
Kininogen 1 (KNG1) Rat ELISA Kit (Abcam, detection limit 4.97 ng/mL), Apoc3 (Rat/Mouse) ELISA Kit (Abnova, detection limit 0.3 g/mL), and rat paraoxonase 1 (PON1) ELISA Kit (Cusabio Biotech, Wuhan, Hubei, China; detection limit 15.6 U/mL) were used to measure the expression levels of proteins. Briefly, serum samples were incubated in microtiter wells with appropriate dilution according to the manufacturer's instructions. After discarding the solution and washing, biotinylated antibody, HRP-streptavidin, substrate reagent, and stop solution were sequentially added to the wells. Finally, absorbance was read at wavelength of 450 nm immediately. The expression levels of the proteins were calculated by a four-parameter logistic curve (Microplate manager 6 software, Bio-Rad).

Statistical Analysis.
Experimental data were presented as mean ± standard deviation (SD). Statistical analyses were performed with SPSS software, version 18.0 (SPSS, Chicago, IL, USA) and value of less than 0.05 was considered statistically significant. Nonparametric analyses were performed using the Mann-Whitney test. Receiver operating characteristic (ROC) curves and logistic regression models were performed using MedCalc Software (Version 12.4.2.0, Belgium).

Characteristics of YDH Syndrome Rats.
Compared with the normal group, rats in the model group showed obvious YDH symptoms, including dry hair, restlessness, dry stool, and weight loss. The rate of weight gain in the YDH syndrome rats was consistently lower than that of the control group (Figure 2(a)). At the end of the third week, rats in the YDH model group appeared much smaller than the normal rats (Figure 2(b)), and the relative thymus weight decreased significantly in the model group compared with the normal group ( < 0.001, Figure 3(b)). However, the relative weights of the spleen, adrenal gland, and liver showed no remarkable changes (Figures 3(a), 3(c), and 3(d)).  Table 1) and 29 downregulated proteins (<0.8-fold, < 0.05, Table 2). GO annotation was used to analyze the cellular component, molecular function, and participation in biological processes of these 92 distinct proteins. In the biological processes analysis, we found that a majority of differentially expressed proteins were associated with metabolic process (48, 36%; Figure 4(a)), indicating that metabolic abnormalities were closely related to the YDH syndrome. Cellular component analysis revealed that the differentially expressed proteins were mainly localized to the organelle (66, 26%), macromolecular complex (64, 25%), organelle part (54, 21%), and extracellular region part (42, 16%; Figure 4(b)). Functionbased enrichment analysis indicated that most of these proteins played important roles in catalyzing (48, 50%) and enzyme regulating (20, 21%; Figure 4(c)). KEGG pathway annotation revealed a greater relative abundance of proteins involved in immune system (especially in complement and coagulation cascades, Table 3) and carbohydrate metabolism (especially in glycolysis and gluconeogenesis, Table 4), indicating that the YDH syndrome was closely related to the abnormality of immunoreaction and glycometabolism. Furthermore, STRING analysis showed that most of the differentially expressed proteins interacted with each other (Figure 4(d)).

Validation of Proteins by ELISA.
According to the results of the bioinformatics analysis, several abnormally expressed proteins (KNG1, APOC3, and PON1) were validated by ELISA. The results showed that the serum levels of KNG1 in YDH syndrome rats (1271.80 ± 413.65 g/mL) were significantly higher ( < 0.0001) than that in normal rats (702.89 ± 296.43 g/mL) ( Figure 5(a)). The serum levels of APOC3 in YDH syndrome rats and normal rats were 36.60 ± 26.43 g/mL and 61.04 ± 28.32 g/mL, respectively ( Figure 5(b)), and the serum levels of PON1 in YDH syndrome rats and normal rats were 274.76 ± 69.23 mU/mL and 465.73±254.91 mU/mL, respectively ( Figure 5(c)). These data indicated that the levels of APOC3 ( < 0.005) and PON1 ( < 0.001) were significantly decreased in YDH syndrome rats. The results were in line with the iTRAQ data.         respectively. The sensitivity and specificity of the diagnostic model (KNG1, APOC3, and PON1 combination) were 100.0% and 85.0%. In addition, the positive values and the negative predictive values for YDH syndrome diagnosis were also improved by the combination of KNG1, APOC3, and PON1 (Table 5).

Discussion
YDH syndrome is common in TCM practice and has been widely studied in recent decades. Many former studies have observed the abnormalities of immune function in YDH syndrome individuals. Wang found decline in immune function with a decrease of immunological substances in YDH constitution [17]. In addition, TNF-, IL-1 , and IL-6 levels have been found to be elevated, while IL-2 levels have been found to be decreased in YDH syndrome individuals [18,19]. Liu demonstrated decreased CD3+ and CD4+ levels in the peripheral blood of YDH syndrome individuals [20], indicating that the immune function is declined in YDH syndrome. Notably, we found that the weight of the thymus, one of the most important immune organs, was significantly decreased in YDH syndrome rats, suggesting reduced immune function in YDH syndrome. In iTRAQ-2DLC-MS/MS experiment, it was interesting to find that a majority of differentially expressed proteins were involved in immune response and metabolic processes. KEGG pathway analysis revealed that the immune response-associated proteins were mainly clustered at complement and coagulation cascades. To our knowledge, the deficiency of complement significantly reduces IL-1 levels [21,22], and TNF-contributes to coagulation and complement activation in virus-induced fulminant hepatitis [23], accounting for the upregulation of IL-1 and TNF-levels in YDH syndrome individuals. Based on these findings, we speculated that the abnormally expressed proteins involved in complement and coagulation cascades disrupted the signaling pathways related to immune response. Accordingly, immune function in YDH syndrome was disturbed.
Previous studies have revealed that the activities of energy-yielding and energy-consuming reactions were enhanced in YDH syndrome rats [24], which was in line with our results of proteomic experiment. By comparing the differentially expressed serum proteins between YDH syndrome rats and normal rats, we found that approximately Table 3: KEGG pathways analysis of the differentially expressed proteins categorized by organismal systems.

Pathway
Number of matched proteins Organismal systems Pathway map Complement and coagulation cascades 9 Immune system rno04610 Antigen processing and presentation 7 Immune system rno04612 Leukocyte transendothelial migration 5 Immune system rno04670 Fc gamma R-mediated phagocytosis 4 Immune system rno04666 NOD-like receptor signaling pathway 2 Immune system rno04621 B cell receptor signaling pathway 1 Immune system rno04662 Natural killer cell mediated cytotoxicity 1 Immune system rno04650 Intestinal immune network for IgA production 1 Immune system rno04672 Chemokine signaling pathway  half of these proteins were associated with the metabolic processes. KEGG pathway analysis demonstrated that proteins participating in carbohydrate metabolism pathway, especially glycolysis and gluconeogenesis, accounted for a great proportion of the metabolism-associated proteins, which was consistent with previous studies revealing the lower levels of glycogen in YDH syndrome rats [24] and the hyperactivity of glycolysis in epithelial tissue with YDH syndrome [25]. Our results revealed that the enhanced energy metabolism in YDH syndrome attributed mostly to glucose metabolism, which might account for the weight loss in YDH syndrome individuals and animal models.
In the present study, we found that the level of KNG1 was significantly increased in the serum of YDH rats ( < 0.0001). KNG1, a precursor protein of vasoactive kinin [26], is known to participate in inflammation, coagulation, and innate immunity [27]. KNG1 has been found to be significantly elevated in uterine proliferative lesions rats [28] and the mRNA expression of the KNG1 gene has been shown to be upregulated in mouse lung tumors [29]. High-molecularweight kininogen (HK) is cleaved by kallikrein to release bradykinin (BK) and HKa. HKa induces mononuclear cells to release cytokines (TNF-, IL-1, and IL-6) and chemokines (IL-8 and MCP-1) [30]. Interestingly, it has been demonstrated previously that the levels of TNF-, IL-1 , and IL-6 were higher in YDH syndrome individuals, suggesting that Valine, leucine, and isoleucine biosynthesis 1 Amino acid metabolism rno00290 KNG1 is highly associated with the immune abnormalities in YDH syndrome. PON1 is an important antioxidant enzyme against oxidative stress [31], which protects low-density lipoprotein (LDL) against oxidative processes [32] and prevents the formation of oxidized-(Ox-) LDL [33]. Ox-LDL facilitates the proliferation of endothelial cells and the accumulation of macrophages in arterial wall [34] and has been shown to be associated with high oxidative stress [35,36]. So, PON1 may reduce the oxidative stress in the body. In this study, we found that the serum level of PON1 declined considerably in YDH syndrome rats ( = 0.0052), which was consistent with the PON1 alterations in cardiovascular disorders, cancer, and acute influenza infection [37,38]. YDH syndrome, induced by emotional stress or long-term intake of spicy and hot food, is characterized by mucosal lesions. Meanwhile, oxidative stress plays an important role in the pathogenesis of mucosal lesions [39]. Therefore, the low levels of PON1 may indirectly increase oxidative stress in YDH individuals, subsequently contributing to the mucosal lesions.
APOC3 is closely correlated to lipid metabolism. It is an inhibitor of hepatic lipase and lipoprotein lipase [40], which interferes with lipolysis. Maeda et al. found that the plasma triglyceride levels in mice lacking gene APOC3 reduced to approximately 70% of normal level [41]. Another study indicated that the overexpression of APOC3 can lead to hypertriglyceridemia in vivo [42]. In the present study, obvious weight loss was observed in YDH syndrome rats, and the rate of weight gain was consistently lower than normal rats. Serum APOC3 levels in YDH syndrome rats decreased significantly ( = 0.0046). So, we suggested that rats with lower APOC3 have higher activities of hepatic lipase and lipoprotein lipase and undergo more adipose tissue lipolysis compared with normal rats.

Conclusion
In this study, we found that YDH syndrome is highly associated with the disturbance in immune response and metabolic processes. Further proteomic analysis revealed that YDH syndrome was mainly attributed to the disruption in complement and coagulation pathway and the glucose metabolism pathway. Besides, we revealed that the increased serum KNG1 levels and the decreased serum APOC3 and PON1 levels were closely related to YDH syndrome. KNG1 may regulate cytokines and chemokines release during the abnormal immune responses in YDH syndrome, while the low levels of PON1 and APOC3 may increase oxidative stress and lipolysis in YDH syndrome, respectively. The results indicated that KNG1, APOC3, and PON1 may act as potential biomarkers for the diagnosis of YDH syndrome. To accelerate the process of applying our findings in clinical practice, further study to evaluate the effectiveness in a relatively large sample size in YDH syndrome patients is needed. This study provides a novel method to diagnose YDH syndrome and may have significant implications for revealing the molecular mechanism of YDH syndrome.