General characteristic
As shown in Table 1, the proportion of hypertension group of AG, RG and AHU was more than the group of CTL. Comparative analysis suggested that the variables of BUN, TC, TG, ALT, AST and LDL-C had no statistical difference, while variables of UA, SCr, HDL-C were significantly different among these four groups (p < 0.05).
Table 1
Baseline characteristics of identified subjects.
Items | Control (N = 8) | Acute Gout (N = 8) | Gout Remission (N = 7) | Asymptomatic Hyperuricemia (N = 7) |
Male(n) | 2 | 8 | 6 | 6 |
Age(year) | 28.38 ± 1.97 | 50.13 ± 3.92* | 44.57 ± 7.19 | 38.57 ± 6.34 |
Serum UA (µmol/L) | 273.0 ± 19.90 | 550.3 ± 45.17*** | 498.1 ± 55.78*** | 509.2 ± 19.53*** |
SCr (µmol/L) | 59.86 ± 5.60 | 86.44 ± 6.92 | 106.8 ± 19.84* | 107.5 ± 12.09* |
BUN (mmol/L) | 4.49 ± 0.24 | 4.80 ± 0.41 | 5.40 ± 1.14 | 5.93 ± 0.53 |
TC (mmol/L) | 4.81 ± 0.13 | 4.21 ± 0.31 | 4.00 ± 0.21 | 4.64 ± 0.39 |
TG (mmol/L) | 0.74 ± 0.05 | 1.84 ± 0.37 | 1.80 ± 0.22 | 2.33 ± 0.67* |
HDL-C (mmol/L) | 1.80 ± 0.10 | 0.95 ± 0.075*** | 0.98 ± 0.08*** | 1.18 ± 0.14*** |
LDL-C (mmol/L) | 2.42 ± 0.08 | 2.42 ± 0.25 | 2.28 ± 0.26 | 2.64 ± 0.38 |
Hypertension(n) | 0 | 3 | 3 | 2 |
Data present mean ± SD (minimum–maximum); UA uric acid, SCr the serum level of creatinine, BUN blood urea nitrogen, TC total cholesterol, TG total glycerides, HDL-C high-density lipoprotein cholesterol, LDL-C low-density lipoprotein cholesterol; P values were calculated by using χ2 test for gender, hypertension and one-way ANOVA test for others (*, p < 0.05; **, p < 0.01; ***, p < 0.001) |
Proteomic differences detected by iTRAQ
Identify differentially expressed proteins (DEPs)
By iTRAQ proteomic analysis, a total of 9,876 with unique peptides or polypeptide segments corresponding to 947 proteins were identified among AG, RG, AHU patients, and healthy controls (Table S1). Compared with CTL, we totally found 84 DEPs in the AG group, of which 63 proteins were up-regulated and 21 proteins were down-regulated. Compared with the CTL, we totally found 94 DEPs in the RG group, of which 32 proteins were up -regulated and 62 proteins were down-regulated. Compared with the CTL, in AHU group, we totally found 92 DEPs, of which 52 proteins were up-regulated and 40 proteins were down-regulated. Compared with the AG, in the AHU, we totally found 69 DEPs, of which 21 proteins were up-regulated and 48 proteins were down-regulated. The differential proteins in the clustering heat map were shown in Fig. 1.
Gene Ontology (GO) functional annotation analysis
To analyze the associated functions of the proteomics profiles in four groups, the DEPs underwent GO functional annotation based on Blast2GO software. Using Fisher’s exact test method, result of GO functional enrichment analysis could reveal the main biological processes (BP), cellular components (CC), and molecular function (MF) involved in DEPs in different groups (Fig. 2.). According to the GO analysis, we found that in terms of biological processes, these proteins were mainly involved in lipid metabolism, endocytosis, vesicle-mediated transport, receptor-mediated endocytosis, anion transport, negative regulation of proteolysis, negative regulation of cell metabolic process, and negative regulation of catalytic activity. In terms of cell localization, these proteins were mainly located in extracellular space, blood microparticles, high-density lipoprotein particles, triglyceride-rich lipoprotein particles, and low-density lipoprotein particles. Significant changes occurred in some molecular functions like binding of lipid substances, lipid transport activity and peroxidase activity.
Kyoto Encyclopedia of Genes and Genomes (KEGG) Analysis of DEPs
In order to classify the functional annotations of the identified proteins, pathway analysis of DEPs was mainly conducted by KEGG analysis (Table S2, S3, S4 and S5 ). The top significant pathways in each comparison groups were displayed in Fig. 3. Although the KEGG analysis provides a large number of pathway information from each comparison groups, the most representative pathway was peroxisome proliferator activated receptor (PPAR) signaling pathways and alcoholism pathway, because these two pathways occurred frequently among four comparison groups. Moreover, interestingly, histone H2A and histone H2B proteins were seen to be involved in alcoholism pathways and these two proteins were significantly increased in AG, RG and AHU compared with CTL, but were significantly decreased in AHU compared with AG (Table 2). This result revealed that histone H2A and histone H2B proteins may be involved in the core mechanism of gout onset through alcoholism pathway.
Table 2
List of histone H2A and histone H2B in four comparison groups.
Accession | Description | AG/CTL | P-value | AHU/CTL | P-value | RG/CTL | P-value | AG/AHU | P-value |
A0A0U1RRH7 | Histone H2A | 4.132 | 0.005 | 1.553 | 0.030 | 1.437 | 0.003 | 0.348 | 0.009 |
B4DR52 | Histone H2B | 4.206 | ༜0.001 | 1.951 | 0.025 | 1.913 | 0.022 | 0.455 | 0.004 |
The Table 1 shows the fold-change and its P-value of histone H2A and histone H2B in four comparison groups. Accession refers to protein numbers in the FASTA Database. Description refers to the name of protein. |
Following this DEPs level trends, more proteins would be further validated by PRM analysis. Firstly, A venn diagram including the total DEPs from four comparison was generated to find the level trends we want. The detailed information of all proteins obtained from four comparison groups was presented in Fig. 4. In the venn diagram, 92 DEPs were shared in four comparison groups, which were significantly increased in AG, RG and AHU compared with CTL, but were significantly decreased in AHU compared with AG. Similarly, 53 DEPs were also shared in four comparison groups if the protein level trends become down-regulated in AG/CTL, RG/CTL, AHU/CTL, but up-regulated in AHU/AG. Then, a total of 145 DEPs were further screened by a combination of VIP score based on PCA analysis and protein sequence database searching based on DDA method. Finally, a list of 40 peptides was prepared for PRM validation (Table 3). Unfortunately, histone A and histone B was difficult to identified because its peptide spectrum matches (PSM) is lower from DDA database. (only the best scoring peptide to spectrum match for each LC/MS spectrum is considered as the potential peptide identification and is taken to the subsequent statistical validation)
Table 3
Selected 40 proteins to be verified by PRM. The table shows the fold-change and its P-value of 40 selected proteins from iTRAQ data in four comparison groups. Accession refers to protein numbers in the FASTA Database. Coverage refers to the percentage of the protein sequence covered by identified peptides. Unique Peptides refers to the number of peptide sequences unique to a protein group.
Accession | Coverage | Unique peptide | AG/CTL | P value | HUA/CTL | P value | RG/CTL | P value | AG/HUA | P value |
Q14520 | 38 | 18 | 1.17 | 0.02 | 1.00 | 0.94 | 1.00 | 0.93 | 0.86 | 0.04 |
O95445 | 62 | 10 | 1.30 | ༜0.01 | 1.15 | 0.01 | 1.29 | 0.10 | 0.99 | 0.91 |
P0DJI9 | 50 | 4 | 2.61 | 0.13 | 1.02 | 0.91 | 1.15 | 0.36 | 0.44 | 0.15 |
P23528 | 45 | 8 | 1.52 | ༜0.01 | 1.37 | 0.17 | 1.42 | 0.17 | 0.93 | 0.70 |
P14780 | 23 | 14 | 1.50 | ༜0.01 | 1.04 | 0.69 | 1.25 | 0.02 | 0.84 | ༜0.01 |
P55056 | 30 | 5 | 2.17 | ༜0.01 | 1.76 | ༜0.01 | 1.90 | ༜0.01 | 0.88 | 0.20 |
P02768 | 84 | 61 | 0.51 | ༜0.01 | 0.43 | ༜0.01 | 0.51 | ༜0.01 | 0.99 | 0.84 |
P00734 | 56 | 35 | 1.04 | 0.13 | 1.00 | 0.96 | 0.97 | 0.29 | 0.93 | 0.02 |
P43652 | 45 | 25 | 0.90 | ༜0.01 | 0.98 | 0.12 | 1.04 | 0.08 | 1.16 | ༜0.01 |
P05160 | 49 | 29 | 1.15 | 0.01 | 1.02 | 0.49 | 1.00 | 0.96 | 0.87 | ༜0.01 |
P05546 | 44 | 20 | 0.97 | 0.49 | 1.03 | 0.65 | 0.84 | 0.03 | 0.87 | 0.01 |
P06681 | 38 | 22 | 1.17 | 0.05 | 0.89 | 0.12 | 0.98 | 0.83 | 0.84 | 0.02 |
P02763 | 51 | 11 | 1.21 | 0.19 | 0.76 | 0.29 | 0.72 | 0.22 | 0.60 | 0.12 |
P19652 | 44 | 10 | 0.99 | 0.88 | 0.59 | 0.01 | 0.51 | 0.01 | 0.51 | 0.01 |
P05164 | 34 | 20 | 2.15 | ༜0.01 | 0.95 | 0.63 | 1.18 | 0.30 | 0.55 | 0.01 |
P29401 | 32 | 17 | 0.91 | 0.10 | 0.72 | 0.02 | 0.96 | 0.28 | 1.06 | 0.34 |
Q9UHG3 | 34 | 14 | 1.22 | 0.07 | 1.08 | 0.35 | 1.14 | 0.42 | 0.93 | 0.61 |
P14625 | 22 | 16 | 1.00 | 0.98 | 0.83 | 0.02 | 0.79 | ༜0.01 | 0.79 | 0.01 |
P02790 | 72 | 33 | 0.91 | ༜0.01 | 0.98 | 0.15 | 0.92 | 0.22 | 1.01 | 0.92 |
P08697 | 49 | 22 | 0.93 | 0.30 | 0.95 | 0.33 | 0.94 | 0.27 | 1.01 | 0.82 |
Q96PD5 | 44 | 17 | 0.87 | 0.05 | 0.90 | 0.03 | 0.99 | 0.93 | 1.14 | 0.12 |
P04278 | 50 | 13 | 0.60 | ༜0.01 | 0.70 | 0.01 | 0.72 | 0.03 | 1.20 | 0.23 |
P51884 | 38 | 10 | 0.79 | ༜0.01 | 0.94 | 0.04 | 0.87 | 0.03 | 1.10 | 0.14 |
P35908 | 42 | 15 | 0.76 | 0.32 | 0.87 | 0.58 | 0.88 | 0.70 | 1.17 | 0.56 |
Q03591 | 28 | 1 | 0.97 | 0.73 | 0.99 | 0.87 | 0.99 | 0.81 | 1.01 | 0.86 |
P22352 | 29 | 6 | 0.83 | 0.02 | 0.88 | 0.02 | 0.87 | 0.07 | 1.05 | 0.43 |
Q14624 | 49 | 38 | 1.19 | 0.22 | 1.37 | 0.20 | 1.15 | 0.39 | 0.96 | 0.80 |
P05155 | 31 | 19 | 1.01 | 0.63 | 1.04 | 0.60 | 0.84 | 0.01 | 0.83 | 0.01 |
P07358 | 41 | 18 | 1.01 | 0.81 | 1.00 | 0.90 | 1.01 | 0.78 | 1.00 | 0.98 |
P07996 | 29 | 29 | 1.59 | 0.03 | 1.78 | 0.01 | 1.52 | 0.02 | 0.96 | 0.76 |
P02760 | 42 | 11 | 1.06 | 0.50 | 1.10 | 0.24 | 1.06 | 0.50 | 1.00 | 0.98 |
P02671 | 35 | 21 | 1.34 | 0.04 | 0.81 | 0.02 | 0.92 | 0.16 | 0.68 | 0.02 |
Q92954 | 20 | 23 | 1.33 | 0.02 | 1.18 | 0.01 | 1.13 | 0.04 | 0.85 | 0.10 |
O43866 | 47 | 17 | 1.66 | 0.02 | 0.92 | 0.47 | 1.12 | 0.09 | 0.68 | 0.05 |
P00915 | 57 | 10 | 1.06 | 0.63 | 1.42 | 0.22 | 2.19 | 0.02 | 2.06 | 0.03 |
Q04756 | 22 | 12 | 1.08 | 0.09 | 1.03 | 0.65 | 1.01 | 0.78 | 0.94 | 0.17 |
P00558 | 47 | 13 | 1.15 | 0.33 | 0.91 | 0.48 | 1.09 | 0.38 | 0.95 | 0.67 |
Q13201 | 16 | 14 | 1.20 | 0.08 | 1.10 | 0.34 | 1.17 | 0.19 | 0.97 | 0.76 |
O00187 | 17 | 9 | 1.18 | 0.06 | 0.97 | 0.70 | 1.09 | 0.23 | 0.93 | 0.01 |
P02741 | 23 | 5 | 1.73 | 0.11 | 0.71 | 0.32 | 1.35 | 0.41 | 0.78 | 0.41 |
PRM result
The PRM verified data were imported into skyline to check the peak shape of the target peptide segment and judge the spectral effect. The peak shape of some peptide segments was intact and the peak time was within the set retention time range, indicating the data quality was reliable (Supplementary Figure S1). 40 proteins related to gout process were found for PRM further analysis.
PRM analysis revealed that 14 proteins were identified to predict gout process significantly. The results, as shown in Fig. 5, the level of four proteins (Hyaluronan-binding protein 2, Myeloperoxidase (MPO), Carbonic anhydrase 1 (CA1), C-reactive protein) were significantly increased in AG, RG and AHU compared with the healthy group. Interestingly, these four proteins were also expressed higher in AG than in RG and AHU. Similarly, the expression levels of Apolipoprotein M, Serum albumin (ALB) and Hepatocyte growth factor activator exhibited a significant reduction in AG, RG and AHU compared with the healthy group. And these three proteins were also expressed lower in AG than in RG and AHU. Alpha-1-acid glycoprotein 1 (ORM1), Inter-alpha-trypsin inhibitor heavy chain H4 (ITIH4) and Complement C2 presented no significant difference among healthy group, RG patients and AHU patients. However, in AG patients, the level of these two proteins were significantly lower than in the rest of three group. The levels of Complement component C8 beta chain (C8B) in AUR and AG patients were significantly lower than those of controls, which resulted in a significantly higher level in AG patients oppositely. More interestingly, the changes of Apolipoprotein C-IV and Thrombospondin-1 (THBS1) in RG and AHU patients were observed to increase compared with the healthy group but these two proteins displayed a significant reduction in AG patients compared with the healthy group. Finally, the level of Multimerin-1 (MMRN1) in AG patients was expressed lowest compared with the group of healthy control, RG and AHU.
In order to reveal the function of proteins, 40 differential proteins related to gout process were selected for protein–protein interaction (PPI) network analysis. By comparing proteins to STRING, the results showed that known proteins, such as THBS1, F2, FGA, SERPINF2, ORM2, ITIH4, ORM1 and MMRN1, account for a large weight in the network (Fig. 6). However, combined with the PRM results, THBS1, ITIH4, ORM1, MMRN1, MPO, CA1, ALB, C8B and Complement C2 were significantly related to gout process. Of all proteins, THBS1 exhibited the strongest regulatory ability above all others and complement and coagulation cascades performed the strongest regulatory ability above all pathways due to its higher interconnectedness in the network. The THBS1 might be the key biomarker to maintain the balance and stability of the gout process.