Metalloproteins and apolipoprotein C: candidate plasma biomarkers of T2DM screened by comparative proteomics and lipidomics in ZDF rats

Wang, Shuai; Lu, Zhiyuan; Wang, Yuxin; Zhang, Tianran; He, Xiaodong

doi:10.21203/rs.3.rs-28040/v1

Cited by 1 publication

(1 citation statement)

References 45 publications

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“…Proteins that are negatively associated with T2DM include: lipoprotein lipase, 26,28 IGF‐binding protein 2 26,29 and paraoxonase 3 26,29 . Markers such as ceruloplasmin, apolipoprotein C‐I, apolipoprotein C‐II and apolipoprotein C‐IV have also been found and can be used as candidate biomarkers for the prediction and treatment of T2DM 30 . These results are comparable with findings of the present study, suggesting that these proteins may play a role even in the early stage of T2DM pathogenesis.…”

Section: Discussionmentioning

confidence: 99%

Analysis of protein expression changes in patients with prediabetes using proteomics approaches

Xie

Liu

et al. 2022

Rapid Comm Mass Spectrometry

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Rationale Proteomics and metabolomics are widely used in the study of diabetes, but rarely in prediabetes research. This study aimed to explore the mechanisms of early‐onset type 2 diabetes mellitus (T2DM) by analyzing proteomic changes at different stages of glucose metabolism. Methods A total of 40 individuals undergoing routine physical health examinations between December 2016 and April 2017 were enrolled. Subjects were divided into four groups based on fasting blood glucose (FPG) levels: FPG < 5.6 mmol/L (group A); FPG ≥ 5.6 mmol/L and <6.1 mmol/L (group B); FPG ≥ 6.1 mmol/L and <7.0 mmol/L (group C); and FPG ≥ 7.0 mmol/L (group D). Each group had 10 cases. Sera from these 40 subjects were analyzed by label‐free quantitative liquid chromatography coupled with tandem mass spectrometry (LC/MS/MS). LC/MS/MS with selected reaction monitoring mode was also performed for qualitative and quantitative metabolomics analysis. Differentially expressed proteins were identified. Partial least squares discriminant analysis (PLS‐DA) and orthogonal partial least squares discriminant analysis (OPLS‐DA) were used to analyze the differentially expressed metabolites. Results A total of 202 differentially expressed proteins were screened and were identified as mainly secreted proteins. Comparing group A with group B, 32 proteins were up‐regulated and 18 proteins were down‐regulated. Comparing group A with group C, 24 proteins were up‐regulated and 24 proteins were down‐regulated. Comparing group A with group D, 19 proteins were up‐regulated and 17 proteins were down‐regulated. The fold change for up‐regulated proteins was >1.2, p < 0.05, while the fold change for down‐regulated proteins was <−1.2, p < 0.05. PLS‐DA and OPLS‐DA revealed 113 differentially expressed metabolites. Correlation analysis of differentially expressed metabolites of group A versus group B revealed that among the down‐regulated differential proteins, transforming growth factor β‐induced protein ig‐h3 correlated negatively with metabolite L‐saccharin, while among the up‐regulated differential proteins, apolipoprotein C‐IV correlated negatively with metabolite 3‐methyloxindole. Among all differentially expressed proteins, 19 proteins were associated with early initiation of chronic inflammation, including CD14 and CSF‐1R, which were newly identified in the early onset of T2DM. Conclusions Many proteins are differentially expressed between prediabetes and after T2DM diagnosis, although the specific mechanism remains unclear. The expression level of CD14 was significantly up‐regulated and that of CSF‐1R was significantly down‐regulated when FPG was ≥5.6 mmol/L, suggesting that CD14 and CSF‐1R may be important markers for early‐onset T2DM and may serve as new targets for T2DM treatment.

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