Ficoll was purchased from Shanghai Chemical Company (Shanghai, China). MG, phytohemagglutinin (PHA), and S-p-bromobenzylglutathione cyclopentyl diester (BrBzGCp2) were from Sigma-Aldrich (St. Louis, MO, USA). TRIzol was purchased from Invitrogen (Carlsbad, CA, USA). MG-H1 antibody was obtained from Novus Biologicals (Littleton, CO, USA). The BeyoRT™ III First Strand cDNA Synthesis Kit; BeyoFast™ SYBR Green qPCR Mix; anti-mouse IgG horseradish peroxidase (HRP)-linked secondary antibody; and enzyme-linked immunosorbent assay (ELISA) kits for pro-inflammatory cytokines IL-1$\beta$, TNF-$\alpha$, and IFN-$\gamma$ were purchased from Beyotime Biotech Ltd. (Beijing, China). Fetal bovine serum (FBS) was obtained from Sijiqing Co. (Hubei, China). RPMI 1640 medium was purchased from Genom Biotech Pvt. Ltd. (Shanghai, China).

The study was approved by the Affiliated Hospital of Gansu Medical College (Lanzhou, Gansu province, China) and conducted in accordance with the principles of the Declaration of Helsinki. Diabetic patients were recruited from the Affiliated Hospital of Gansu Medical College. Informed consent was obtained from the patients. A total of 12 males and 7 females between the ages of 9 and 45 years old with newly diagnosed T1DM (1 year) according to the criteria of the American Diabetes Association, were recruited to this study. Patients were excluded from the study if they had an active infection, acute diabetic complications, or autoimmune disease. Control subjects were 35 volunteers without diabetes or other autoimmune diseases. No infectious diseases were detected during the 1-month period prior to the study.

Fasting human venous blood was collected in sterile heparinized tubes between 08:00 and 10:30 am. PBMCs were isolated using Ficoll gradients within 4 h after the blood was drawn, and then washed with 1$\times$ phosphate-buffered saline (PBS).

Isolated PBMCs from control subjects were added to RPMI 1640 containing 10% FBS. Cells (2 $\times$ 10${}^5$/mL) were seeded in 96-well plates and treated with different concentrations of MG and a GLO1 inhibitor. After 24 h of incubation, cells were resuspended and trypan blue dye was added. Cell viability was calculated based on the ratio of stained cells and total cells.

The measurement of GLO1 activity followed the protocol described by Qian et al. [10]. Cellular lysate from PBMCs was added to a hemithioacetal solution, which was prepared by pre-incubation with methylglyoxal and glutathione. The production of S-lactoylglutathione mediated by GLO1 was determined at an absorbance of 235 nm. GLO1 activity was calculated by the change in S-lactoylglutathione concentration.

Isolated PBMCs (2 $\times$ 10${}^5$/mL) were cultured in RPMI 1640 medium supplemented with 10% FBS, and treated with 10 µg/mL PHA for 24 h [18]. The supernatant was collected for the measurement of pro-inflammatory cytokines.

The concentrations of IL-1$\beta$, TNF-$\alpha$, and IFN-$\gamma$ in the supernatant were measured by the protocol described by the commercial supplier. In brief, 25 µL supernatant and 75 µL dilution buffer were added to individual wells and incubated at room temperature for 2 h, washed with 1X Wash Buffer, and then incubated with capture antibodies and substrate. The results were obtained using absorbance at 450 nm by a microplate reader.

Indirect ELISAs with anti-MG-H1 antibody were carried out following the protocol described by Moraru et al. [19]. In brief, cell lysate (20 µL) in ammonium bicarbonate 100 mM pH 9.6 into a 96-well plate. The plate was incubated at room temperature for 2 h and the wells were washed with PBS. Then the wells were blocked in 5% (w/v) bovine serum albumin and incubated at room temperature for 2 h. The wells were incubated overnight with an anti-MG-H1 antibody, followed by washing and then incubation with anti-rabbit IgG, HRP-linked secondary antibody at room temperature for 1 h. The absorbance at 450 nm was measured by a microplate reader.

RNA from PBMCs was isolated by TRIzol according to the manufacturer’s instructions. RNA concentration was measured following cDNA synthesis using the BeyoRT™ III First Strand cDNA Synthesis Kit. The PCR reactions contained 10 pM sense and 10 pM antisense oligonucleotides with BeyoFast™ SYBR Green qPCR Mix. The human GLO1 forward primer was 5${}^{\prime }$-AGC AGA CCA TGC TAC GAG TG-3${}^{\prime }$, and the reverse primer was 5${}^{\prime }$-GAG AGC GCC CAG GCT ATT T-3${}^{\prime }$; the human $\beta$ actin forward primer was 5${}^{\prime }$-GGT GGC TTT TAG GAT GGC AAG-3${}^{\prime }$, and the reverse primer was 5${}^{\prime }$-ACT GGA ACG GTG AAG GTG ACA G-3${}^{\prime }$.

The National Center for Biotechnology Information (NCBI) Gene Expression Omnibus (GEO) database (http://www.ncbi.nlm.nih.gov/geo/) was used to explore the expression profiles in microarray datasets. The keywords ‘type 1 diabetes’, ‘autoimmune diabetes’, ‘mononuclear’, and ‘PBMC’ were applied for this search. The inclusion criteria were: (1) gene expression profiling of circulating PBMCs; (2) patients with newly diagnosed T1DM and suitable control subjects; and (3) clear microarray platforms. In summary, the current study identified three GEO datasets (GSE55098, GSE29142, and GSE9006). The study included a total of 64 newly diagnosed patients with T1DM and 44 control subjects. The microarray platforms were Affymetrix Human Genome U133 Plus 2.0 Array, Phalanx Human OneArray, and Affymetrix Human Genome U133A Array.

All microarray datasets were downloaded from the NCBI GEO datasets using the R package GEOquery. Individual datasets were re-analyzed using the R package limma version 3.42.2 (Parkville, Victoria, Australia). The results of log fold change (logFC), p values, and the left and right limits of the confidence interval for logFC from individual datasets were exported for further meta-analysis. Meta-analysis was performed with the MetaVolcanoR package [20] by combining the P values using the random method. Differentially expressed genes (DEGs) from random analysis between patients with T1DM and control subjects were used for the functional analysis. For the enrichment analysis, the R package, clusterProfiler (Guangzhou, China) was used for the analysis of Gene Ontology (GO) biological process [21].

Statistical analyses were performed with GraphPad Prism 8 (Dotmatics, Boston, MA, USA). Due to the limitation of patients, the significant analysis was conducted with the Mann–Whitney U Test. Correlation analysis was performed by simple linear regression analysis. p 0.05 was considered statistically significant.

Three studies were recruited for this meta-analysis study. GSE55098 [22] included 12 patients with newly diagnosed T1DM (defined as treatment with insulin for 12 weeks) and 10 control subjects. GSE29142 [23] included 9 patients newly diagnosed T1DM (considered patients with positive glutamic acid decarboxylase 65-kilodalton isoform, islet antigen-2, and insulin autoantibodies) and 10 control subjects. GSE9006 [24] had 43 patients with newly diagnosed T1DM and 24 control subjects. Those studies were conducted in China, the Czech Republic, and the United States. As shown in Fig. 1A, the upregulated DEGs in PBMCs from patients with T1DM compared with control were 715 (GSE55098), 969 (GSE29142), and 642 (GSE9006); and the down-regulated DGEs were 783 (GSE55098), 1008 (GSE29142), and 701 (GSE9006).

Fig. 1.

Activation of the immune response in peripheral blood mononuclear cells (PBMCs) from patients with type 1 diabetes mellitus (T1DM). (A) Differentially expressed genes (DEGs) of published microarray datasets. Red: upregulated DEGs; blue: downregulated DEGs; grey: no significant difference genes. (B) Forest plot of top 1% DEGs in PBMCs between patients with T1DM and control subjects using meta-analysis random effect analysis. (C) Gene Ontology (GO) term biological process analysis of upregulated DEGs of PBMCs from T1DM patients compared with control subjects. (D) GO term biological process analysis of downregulated DEGs of PBMCs from T1DM patients compared with control subjects.

Then we performed random analysis based on the results of limma analysis from individual studies. Fig. 1B shows the top 1% of both up- and downregulated DEGs of PBMCs from patients with T1DM. To identify DEGs related to the functional biological group, using GO biological process analysis, the results from upregulated DEGs in T1DM further confirmed that the development of T1DM was related to the immune response (Fig. 1C). The top pathways of downregulated DEGs in T1DM showed the inhibition of mitochondrial electron transport chain activity (Fig. 1D).

As shown in Table 1, patients with T1DM had significantly higher levels of fasting blood glucose and hemoglobin A1C compared with control subjects. The correlation between fasting blood glucose and glycated hemoglobin was positive (r = 0.7081, p 0.05). The results of Fig. 2A also demonstrated that patients with T1DM had significantly increased MG-H1 (MG-derived AGEs) in PBMC lysate, compared to control subjects. Both results indicated that there was significant accumulation of systemic AGEs, including circulating PBMCs in patients with T1DM. The increase in AGE accumulation is also related to the detoxification of MG by the ubiquitous cellular enzyme, GLO1. Fig. 2B shows that the expression of GLO1 was markedly lower (p = 0.001096) in patients with T1DM based on the results of random analysis. In the current study, we also confirmed the previous microarray data. Fig. 2C,D show that GLO1 expression and activity were significantly reduced in the PBMCs of patients with T1DM compared to those of control subjects.

Fig. 2.

Accumulation of cellular Advanced glycation end products (AGEs) in peripheral blood mononuclear cells (PBMCs) from patients with type 1 diabetes mellitus (T1DM). (A) Cellular levels of methylglyoxal (MG)-derived AGEs were measured by indirect enzyme-linked immunosorbent assay (ELISA), as described in Materials and Methods. * indicates the comparison with control subjects, as determined by Mann–Whitney U Test. p 0.05. (B) The expression of Glyoxalase I (GLO1) in PBMCs from published Gene Expression Omnibus (GEO) datasets were analyzed based on random effect analysis. (C) GLO1 transcript in PBMCs was determined by qPCR. * indicates the comparison with control subjects, as determined by Mann–Whitney U Test. (D) GLO1 activity was measured in PBMCs from patient with T1DM and control subjects. * indicates the comparison with control subjects, as determined by Mann–Whitney U Test.

T1DM is considered an autoimmune disease. Therefore, the pro-inflammatory cytokines were determined in the serum of patients with T1DM. As shown in Fig. 3A, there was no significant difference in circulating levels of IL-1$\beta$, TNF-$\alpha$, IFN-$\gamma$, and IL-6 between patients with T1DM and control subjects. To further explore immune dysfunction in T1DM, PHA, a nonspecific T cell activator, was used to enhance the immune reaction. Fig. 3B shows that IFN-$\gamma$ and TNF-$\alpha$ levels were markedly higher in PHA-stimulated PBMCs from T1DM compared with those from control subjects. However, there was no significant difference in the levels of IL-1$\beta$ and IL-6 in PHA-stimulated PBMCs from patients with T1DM and control subjects.

Fig. 3.

The activation of immune response in PBMCs from patients with T1DM. (A) Serum cytokine levels from patients with T1DM and control subjects were determined by commercial ELISA kits. (B) Supernatant cytokine levels were measured in phytohemagglutinin (PHA)-treated PBMCs from patients with T1DM and control subjects by commercial ELISA kits. * indicates the comparison with control subjects, as determined by Mann–Whitney U Test. The correlation of secreted cytokines induced by PHA in PBMCs from T1DM and cellular MG-derived AGEs (C), GLO1 activity (D) were analyzed. * indicates the comparison with control subjects, as determined by simple linear regression analysis.

To explore whether cellular AGEs aggravate the immune response in T1DM, correlation analysis was performed between pro-inflammatory cytokines such as IFN-$\gamma$ and TNF-$\alpha$ and MG-derived AGEs in patients with T1DM. Fig. 3C shows that PHA-induced TNF-$\alpha$ and IFN-$\gamma$ secretion were positively correlated with an increase of MG-H1 level in PBMCs from T1DM. However, cytokine secretion showed a negative correlation with GLO1 activity (Fig. 3D). In summary, our results indicated that the accumulation of AGEs in T1DM also contributes to exacerbating immune dysfunction in immune cells.

To further evaluate the role of MG-derived AGEs on pro-inflammatory secretion, MG and a GLO1 inhibitor, BrBzGCp2, was applied in the current study. Fig. 4A shows that treatment of PBMCs with 20 µM MG significantly reduced cell viability compared with vehicle. To further explore the effect of MG on the accumulation of cellular AGEs, the results showed that 10 µM MG markedly enhanced the accumulation of MG-derived AGEs (Fig. 4B). The effect of BrBzGCp2 on GLO1 activity was also determined in PBMCs from control subjects. The results of Fig. 4C showed that 1.5 µM BrBzGCp2 led to a significant reduction of PBMC viability compared with that of vehicle. However, we did not observe a significant difference in cell viability between 0.5 and 1 µM BrBzGCp2. To determine whether BrBzGCp2 induces cellular AGE accumulation, PBMCs were treated with the vehicle, 0.5 and 1 µM BrBzGCp2 for 24 h. The 0.5 µM BrBzGCp2 effectively increased cellular MG-derived AGE accumulation (Fig. 4D). Therefore, in the current study, 10 µM MG and 0.5 µM BrBzGCp2 were applied to PBMCs.

Fig. 4.

Accumulation of cellular AGEs by MG and GLO1 inhibitor enhanced immune response in mononuclear cells. (A) Cell viability of MG-treated mononuclear cells from control subjects (n = 10) was determined. * indicates the comparison with control subjects, as determined by the Mann–Whitney U Test. (B) Cellular MG-derived AGEs in MG-treated PBMCs were determined by indirect ELISA. * indicates the comparison with control subjects, as determined by Mann–Whitney U Test. (C) Cell viability of GLO1 inhibitor – S-4-Bromobenzylglutathione cyclopentyl diester (BrBzGCp2) treated mononuclear cells from control subjects (n = 10) was determined. * indicates the comparison with control subjects, as determined by the Mann–Whitney U Test. (D) Cellular MG-derived AGEs in BrBzGCp2-treated PBMCs were determined by indirect ELISA. * indicates the comparison with control subjects, as determined by Mann–Whitney U Test. (E) TNF-$\alpha$ and IFN-$\gamma$ levels in supernatant from MG or BrBzGCp2 PBMCs were determined by commercial ELISA kits. * indicates the comparison with the vehicle, # indicates the comparison with MG treatment, as determined Mann–Whitney U Test.

Finally, we examined the effects of MG and BrBzGCp2 on the regulation of the immune response in PBMCs from control subjects. Fig. 4E shows that treatment of PBMCs with 10 µM MG or 0.5 µM BrBzGCp2 led to an increase in TNF-$\alpha$ and IFN-$\gamma$ secretion compared to vehicle. In conclusion, the results showed that the accumulation of AGEs in PBMCs contributed to an immune response in PBMCs.