Endocrinol Metab.  2021 Jun;36(3):637-646. 10.3803/EnM.2021.962.

Association of Protein Z with Prediabetes and Type 2 Diabetes

• Bae YU
• You JH
• Cho NH
• Kim LE
• Shim HM
• Park JH
• Cho HC

• KMID: 2517654
• DOI: http://doi.org/10.3803/EnM.2021.962

Abstract

Background
Type 2 diabetes mellitus (T2DM) is a progressive metabolic disease. Early detection of prediabetes is important to reduce the risk of T2DM. Some cytokines are known to be associated with T2DM. Therefore, we aimed to identify cytokines as novel biomarkers of glucose dysmetabolism.
Methods
The first stage of the study included 43 subjects (13 subjects with newly diagnosed T2DM, 13 with prediabetes, and 16 with normoglycemia) for cytokine microarray analysis. Blood samples of the subjects were assessed for 310 cytokines to identify potential indicators of prediabetes. The second stage included 142 subjects (36 subjects with T2DM, 35 with prediabetes, and 71 with normoglycemia) to validate the potential cytokines associated with prediabetes.
Results
We identified 41 cytokines that differed by 1.5-fold or more in at least one out of the three comparisons (normoglycemia vs. prediabetes, normoglycemia vs. T2DM, and prediabetes vs. T2DM) among 310 cytokines. Finally, we selected protein Z (PROZ) and validated this finding to determine its association with prediabetes. Plasma PROZ levels were found to be decreased in patients with prediabetes (1,490.32±367.19 pg/mL) and T2DM (1,583.34±465.43 pg/mL) compared to those in subjects with normoglycemia (1,864.07±450.83 pg/mL) (P<0.001). There were significantly negative correlations between PROZ and fasting plasma glucose (P=0.001) and hemoglobin A1c (P=0.010).
Conclusion
PROZ levels were associated with prediabetes and T2DM. We suggest that PROZ may be a promising biomarker for the early detection of prediabetes. Further large-scale studies are needed to evaluate the relationship and mechanism between PROZ and prediabetes and T2DM.

Keyword

Protein Z; Prediabetic state; Diabetes mellitus; type 2; Biomarkers; Cytokines

Figure

• 

  Fig. 1 Identification of cytokines associated with glucose dysmetabolism using antibody array profiling. The columns and rows in the heatmap represent samples and gene symbol, respectively. In each row, the intensities were divided by the standard deviation after subtracting the mean intensity from them. Red and blue represent the increase and decrease in abundance, respectively. The color bar represents the gradient of the auto scaled log2 intensities. T2DM, type 2 diabetes mellitus; IL, interleukin; ARTN, artemin; CXCL, C-X-C motif chemokine ligand; IGFBP, insulin like growth factor-binding protein; CCL, C-C motif chemokine ligand; DEFB1, defensin beta 1; TIMP1, TIMP metallopepetidase inhibitor 1; BLK, BLK proto-oncogene; ADIPOQ, adiponectin, C1Q and collagen domain containing; TNFRSF1B, tumor necrosis factor receptor superfamily 1B; LTA, lymphotoxin alpha; CDH1, cadherin 1; NTF4, neurotrophin 4; CRP, C-reactive protein; CTNNA1, catenin alpha 1; MMP2, matrix metallopeptidase 2; PROZ, protein Z; FSHB, follicle stimulating hormone subunit beta; STAT6, signal transducer and activator of transcription 6; IL13RA1, interleukin 13 receptor subunit alpha 1; AFP, alpha-fetoprotein; PSG2, pregnancy specific beta-1-glycoprotein 2; IGF2, insulin-like growth factor 2; IFNL2, interferon lambda 2; TG, thyroglobulin; ADAM2, ADAM metallopeptidase domain 2; TNF, tumor necrosis factor; NGF, nerve growth factor; SELL, selectin L.

• 

  Fig. 2 Functional network analysis showing at least 1.5-fold change between normoglycemia and prediabetes. Proteins with well-defined relevant functions have been grouped (orange circle=immune response; red circle=regulation of cell proliferation; purple circle=inflammatory response). Green line=text mining (listing the proteins that are frequently mentioned together), black line=co-expression of proteins, blue line=pathway database, light purple line=protein homology. The network was generated using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database in Cytoscape. ADAM2, ADAM metallopeptidase domain 2; ADIPOQ, adiponectin, C1Q and collagen domain containing; AFP, alpha-fetoprotein; ARTN, artemin; BLK, BLK proto-oncogene; CCL, C-C motif chemokine ligand; CDH1, cadherin 1; CRP, C-reactive protein; CXCL, C-X-C motif chemokine ligand; DEFB1, defensin beta 1; FSHB, follicle stimulating hormone subunit beta; IFNL2, interferon lambda 2; IGF2, insulin-like growth factor 2; IGFBP7, insulin like growth factor-binding protein 7; IL, interleukin; IL13RA1, interleukin 13 receptor subunit alpha 1; TIMP1, TIMP metallopepetidase inhibitor 1; NGF, nerve growth factor; PROZ, protein Z; PSG2, pregnancy specific beta-1-glycoprotein 2; SELL, selectin L; STAT6, signal transducer and activator of transcription 6; TG, thyroglobulin; TNF, tumor necrosis factor.

• 

  Fig. 3 The association of protein Z (PROZ) with normoglycemia, prediabetes, and type 2 diabetes mellitus (T2DM). (A) Fold changes of PROZ levels in subjects with normoglycemia, prediabetes, and T2DM. (B) Plasma levels of PROZ in subjects with normoglycemia, prediabetes, and T2DM. Values are presented as mean±standard error of the mean. Figures are representative of duplicate experiments. aP<0.01; bP<0.001.

• 

  Fig. 4 Receiver operating characteristic (ROC) curves of protein Z (PROZ). (A) The ROC curves of PROZ levels for prediabetes and type 2 diabetes mellitus (T2DM) compared with those in normoglycemia. (B) The area under the curve, sensitivity, specificity and cutoff value of PROZ for prediabetes and T2DM compared with those in normoglycemia. AUC, area under the curve; CI, confidence interval.

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