Factors Associated With Serum Albumin in Diabetes Mellitus Type 2 With Microalbuminuria Using Non-Normal Mixed Models: A Prospective Cohort Study

In silico prediction and validation of potential therapeutic genes in pancreatic β-cells associated with type 2 diabetes

Diabetes mellitus is becoming a major health burden worldwide. Pancreatic β-cell death is a characteristic of type 2 diabetes (T2D), but the underlying mechanisms of pancreatic β-cell death remain unknown. Therefore, the aim of the present study was to identify potential targets in the pancreatic islet of T2D. The GSE20966 dataset was obtained from the Gene Expression Omnibus (GEO) database, and differentially expressed genes (DEGs) were identified by using the GEO2R tool. The Gene Ontology terms and Kyoto Encyclopedia of Genes and Genomes Pathway enrichment analysis of DEGs were further assessed using the Database for Annotation, Visualization and Integrated Discovery. Furthermore, protein-protein interaction (PPI) networks were constructed for the up- and downregulated genes using STRING databases and were then visualized with Cytoscape. The body weight, fasting blood glucose (FBG), pancreatic index and biochemistry parameters were measured in db/db mice. Moreover, the morphology of the pancreas was detected by hematoxylin and eosin staining, and hub genes were assessed using reverse transcription-quantitative PCR (RT-qPCR) and western blot analysis. In total, 570 DEGs were screened, including 376 upregulated and 194 downregulated genes, which were associated with 'complement activation, classical pathway', 'proteolysis', 'complement activation' and 'pancreatic secretion pathway'. It was found that the body weight, FBG, alanine aminotransferase, aspartate aminotransferase, total cholesterol, triglycerides, blood urea nitrogen, creatinine, fasting serum insulin, glucagon and low-density lipoprotein cholesterol levels were significantly higher in db/db mice, while high-density lipoprotein cholesterol levels and the pancreatic index were significantly decreased. Furthermore, albumin, interleukin-8, CD44, C-C motif chemokine ligand 2, hepatocyte growth factor, cystic fibrosis transmembrane conductance regulator, histone cluster 1 H2B family member n, mitogen-activated protein kinase 11 and neurotrophic receptor tyrosine kinase 2 were identified as hub genes in PPI network. RT-qPCR and western blotting results demonstrated the same expression trend in hub genes as found by the bioinformatics analysis. Therefore, the present study identified a series of hub genes involved in the progression of pancreatic β-cell, which may help to develop effective therapeutic strategy for T2D.

Higher serum albumin was related with diabetes incidence and the impact of BMI changes: Based on cohort study of 18,384 Chinese male elderly

AIMS

Albumin (ALB) was a useful marker of nutrition and general health status. However, the conclusion about the association between ALB and diabetes was inconsistent, and little information was known about the elderly.

METHODS

A cohort study based on 18,384 army cadres was conducted Beijing, from 2009 to 2013.

RESULTS

The mean age of the total 18,384 participants was 71±14years, and the mean ALB concentration was 44.33±3.94g/L at baseline. Diabetes incident showed an increasing trend according to the four ALB concentration groups, from 2.054% to 2.811% for incident. Cox regression showed that participants with higher ALB concentration were at increased HRs for diabetes incident. The HRs of ALB (per SD) and ALB concentration for diabetes were 1.125 (95% CI: 1.024-1.231) and 1.029 (95% CI: 1.007-1.051) respectively in the adjusted model. Also the HRs were closely related with BMI changes. For those who had a BMI changes<-1.00kg/m², the HRs were lower and not statistically significant, and for those with increasing BMI during an average of 4years' follow-up, the HRs were higher.

CONCLUSION

There was a positive and independent association between baseline ALB concentrations with diabetes incident among Chinese male elderly, and this association was closely related with BMI changes.