Diabetes Metab J.  2023 Jul;47(4):559-570. 10.4093/dmj.2022.0226.

Change Profiles and Functional Targets of MicroRNAs in Type 2 Diabetes Mellitus Patients with Obesity

• Lu G
• Gao H
• Dong Z
• Jiang S
• Hu R
• Wang C

• KMID: 2544734
• DOI: http://doi.org/10.4093/dmj.2022.0226

Abstract

Background
MicroRNAs (miRNAs) exert an essential contribution to obesity and type 2 diabetes mellitus (T2DM). This study aimed to investigate the differences of miRNAs in the presence and absence of T2DM in patients with obesity, as well as before and after bariatric surgery in T2DM patients with obesity. Characterization of the common changes in both was further analyzed.
Methods
We enrolled 15 patients with obesity but without T2DM and 15 patients with both obesity and T2DM. Their preoperative clinical data and serum samples were collected, as well as 1 month after bariatric surgery. The serum samples were analyzed by miRNA sequencing, and the miRNAs profiles and target genes characteristics were compared.
Results
Patients with T2DM had 16 up-regulated and 32 down-regulated miRNAs compared to patients without T2DM. Improvement in metabolic metrics after bariatric surgery of T2DM patients with obesity was correlated with changes in miRNAs, as evidenced by the upregulation of 20 miRNAs and the downregulation of 30 miRNAs. Analysis of the two miRNAs profiles identified seven intersecting miRNAs that showed opposite changes. The target genes of these seven miRNAs were substantially enriched in terms or pathways associated with T2DM.
Conclusion
We determined the expression profiles of miRNAs in the obese population, with and without diabetes, before and after bariatric surgery. The miRNAs that intersected in the two comparisons were discovered. Both the miRNAs discovered and their target genes were closely associated with T2DM, demonstrating that they might be potential targets for the regulation of T2DM.

Keyword

Bariatric surgery; Diabetes mellitus, type 2; Metabolism; MicroRNAs; Obesity

Figure

• 

  Fig. 1. Volcano plots and heatmaps analysis of differentially expressed microRNAs (DEMs). Volcano plot (A) and heatmap cluster (C) analysis of DEMs between the absence and presence of type 2 diabetes mellitus (T2DM) in patients with obesity. Volcano plot (B) and heatmap cluster (D) analysis of DEMs before and after bariatric surgery in T2DM patients with obesity. The red dots of the volcano plots indicated DEMs, which meant that |log2 fold change (FC)| >1 and P<0.05. NS, no significant.

• 

  Fig. 2. The intersection of up- and down-regulated differentially expressed microRNAs (DEMs) from different groups and correlation analysis. (A) Venn diagram showed the intersection. (B) The specific DEMs that were produced by the intersection. (C) Pearson correlations of the seven microRNAs (miRNAs) from 30 patients preoperatively. (D) Pearson correlations of seven preoperative miRNAs at the intersection with preoperative clinical characteristics. The color bar on the right represented the correlation coefficient, with red for positive correlation and blue for negative correlation. The expression of preoperative miRNAs was all represented by log counts per million. T2DM, type 2 diabetes mellitus; FC, fold change; BMI, body mass index; WHR, waist to hip ratio; TG, triglyceride; TCHOL, total cholesterol; HDL, high density lipoprotein; LDL, low density lipoprotein; GSP, glycated serum protein; HbA1c, glycosylated hemoglobin; GLU, fasting glucose; HOMA-IR, homeostasis model assessment of insulin resistance; ∆BMI, changes in BMI; %TWL, percentage total weight loss. aP<0.05.

• 

  Fig. 3. Target genes analysis predicted by the screened seven microRNAs (miRNAs). (A) Gene Ontology (GO) terms analysis of target genes. (B) Interaction network of GO terms and target genes. (C) Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis of target genes. (D) Interaction network of KEGG pathway and target genes. Gene ratio indicated the ratio of the number of genes associated with the term or pathway to the total number of the entire gene. All P values were less than 0.05.

• 

  Fig. 4. Analysis of the hub genes. The left showed the relationship of the top 15 hub genes. On the right was the ranking of the 15 hub genes and the score of the degree model algorithm by cytoHubba. HNF4A, hepatocyte nuclear factor 4 alpha; SREBF1, sterol regulatory element binding transcription factor 1; SHH, sonic hedgehog signaling molecule; AXIN1, axis inhibition protein 1; RBX1, ring-box 1; TPI1, triosephate isomerase 1; PIK3R1, phosphoinositide-3-kinase regulatory subunit 1; PPP2R1A, protein phosphatase 2 scaffold subunit aalpha; NDUFS8, NADH: ubiquinone oxidoreductase core subunit S8; FGR, FGR proto-oncogene, Src family tyrosine kinase; ALDH18A1, aldehyde dehydrogenase 18 family member A1; RAB11A, member RAS oncogene family; MAG, myelin associated glycoprotein; GRB2, growth factor receptor bound protein 2; STX1A, syntaxin 1A.

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