Case Control Study
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World J Diabetes. Mar 15, 2022; 13(3): 224-239
Published online Mar 15, 2022. doi: 10.4239/wjd.v13.i3.224
Functional annotation and enrichment analysis of differentially expressed serum proteins in patients with type 2 diabetes after dapagliflozin
Yan-Xue Zhao, Sarul Borjigin, Zhao-Li Yan
Yan-Xue Zhao, Basic Building Laboratory, The Affiliated Hospital of Inner Mongolia Medical University, Hohhot 010000, Inner Mongolia, China
Sarul Borjigin, Zhao-Li Yan, Department of Endocrinology, The Affiliated Hospital of Inner Mongolia Medical University, Hohhot 010000, Inner Mongolia, China
Author contributions: Zhao YX contributed to methodology, software, formal analysis, investigation, resources, data curation, writing original draft preparation, writing review and editing; Borjigin S contributed to experimental operation. Yan ZL contributed to conceptualization, methodology, validation, formal analysis, investigation, resources, writing original draft preparation, writing review and editing, supervision, funding acquisition; all authors have read and agreed to the published version of the manuscript.
Supported by Major Scientific Research Program of The Affiliated Hospital of Inner Mongolia Medical University, No. NYFY ZD 001.
Institutional review board statement: The present study was approved by the Ethics Committee of Affiliated Hospital of Inner Mongolia Medical University, No. WZ.
Informed consent statement: Written informed consent was obtained from the patients.
Conflict-of-interest statement: The authors declare that they have no competing interests.
Data sharing statement: The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.
STROBE statement: The authors have read the STROBE Statement-checklist of items, and the manuscript was prepared and revised according to the STROBE Statement-checklist of items.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Zhao-Li Yan, MD, Professor, Department of Endocrinology, The Affiliated Hospital of Inner Mongolia Medical University, No. 1 Tongdao North Road, Huimin District, Hohhot 010000, Inner Mongolia, China. aliceyzl@126.com
Received: October 30, 2021
Peer-review started: October 30, 2021
First decision: December 27, 2021
Revised: January 29, 2022
Accepted: February 23, 2022
Article in press: February 23, 2022
Published online: March 15, 2022
Processing time: 135 Days and 23.8 Hours
Abstract
BACKGROUND

Only 50% of patients with type 2 diabetes mellitus (T2DM) can control their blood glucose levels. Dapagliflozin is a selective inhibitor of sodium-glucose co-transporter 2 (SGLT-2) that improves the insulin sensitivity of the liver and peripheral tissues. Many studies confirmed that SGLT2 inhibitors reduce blood glucose and have multiple beneficial effects such as weight loss, lipid regulation, and kidney protection. Nevertheless, the mechanisms of the renal and cardiovascular protective effects of dapagliflozin from the perspective of differentially expressed proteins in the serum of T2DM patients have not been intensively explored so far.

AIM

To identify differentially expressed proteins associated with dapagliflozin treatment in patients with T2DM.

METHODS

Twenty T2DM patients [hemoglobin A1c (HbA1c) 7.0%-10.0%] were enrolled at The Affiliated Hospital of Inner Mongolia Medical University between January 1, 2017 and December 1, 2018. They received dapagliflozin (10 mg/d) for 3 mo, and the HbA1c < 7.0% target was achieved. The changes in clinical indexes were compared before and after treatments. Label-free quantitative proteomics was used to identify differentially expressed proteins using the serum samples of five patients. The identified differentially expressed proteins were analyzed using various bioinformatics tools.

RESULTS

Dapagliflozin significantly improved the clinical manifestation of the patients. There were 18 downregulated proteins and one upregulated protein in the serum samples of patients after dapagliflozin administration. Bioinformatics analyses, including subcellular localization, EuKaryotic Orthologous Groups, Gene Ontology, and Kyoto Encyclopedia of Genes and Genomes annotations, were used to profile the biological characteristics of the 19 differentially expressed proteins. Based on the literature and function enrichment analysis, two downregulated proteins, myeloperoxidase (MPO) and alpha II B integrin (ITGA2B), and one upregulated protein, podocalyxin (PCX), were selected for enzyme linked immunosorbent assay validation. These validated differentially expressed proteins had multiple correlations with clinical indexes, including HbAc1 and fasting C-peptide.

CONCLUSION

Dapagliflozin has hypoglycemic effects and regulates the serum expressions of MPO, ITGA2B, and PCX, possibly contributing to the effects of dapagliflozin on oxidative stress, insulin resistance, and lipid metabolism.

Keywords: Type 2 diabetes mellitus; Dapagliflozin; Non-standard quantitative proteomics; Myeloperoxidase; Alpha II B integrin; Podocalyxin

Core Tip: This study aimed to identify differentially expressed proteins associated with dapagliflozin treatment in patients with type 2 diabetes mellitus. Changes in blood indexes were examined in 20 patients treated with dapagliflozin for 3 mo. Quantitative proteomics was used to identify differentially expressed proteins using the serum samples of five patients. Dapagliflozin has hypoglycemic effects and regulates the serum expressions of myeloperoxidase, alpha II B integrin, and podocalyxin, possibly contributing to the effects of dapagliflozin on oxidative stress, insulin resistance, and lipid metabolism.