| Literature DB >> 36013384 |
Krisztina Kupai1,2, Tamás Várkonyi2, Szilvia Török1, Viktória Gáti3, Zsolt Czimmerer3,4, László G Puskás3,5, Gábor J Szebeni1,3,6.
Abstract
Type 2 diabetes mellitus (T2DM) is one of the world's leading causes of death and life-threatening conditions. Therefore, we review the complex vicious circle of causes responsible for T2DM and risk factors such as the western diet, obesity, genetic predisposition, environmental factors, and SARS-CoV-2 infection. The prevalence and economic burden of T2DM on societal and healthcare systems are dissected. Recent progress on the diagnosis and clinical management of T2DM, including both non-pharmacological and latest pharmacological treatment regimens, are summarized. The treatment of T2DM is becoming more complex as new medications are approved. This review is focused on the non-insulin treatments of T2DM to reach optimal therapy beyond glycemic management. We review experimental and clinical findings of SARS-CoV-2 risks that are attributable to T2DM patients. Finally, we shed light on the recent single-cell-based technologies and multi-omics approaches that have reached breakthroughs in the understanding of the pathomechanism of T2DM.Entities:
Keywords: COVID-19; CVD risk; inflammation; insulin resistance; obesity; type 2 diabetes mellitus
Year: 2022 PMID: 36013384 PMCID: PMC9409806 DOI: 10.3390/life12081205
Source DB: PubMed Journal: Life (Basel) ISSN: 2075-1729
Classification of main types of diabetes mellitus [2,3,4,5,7].
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Type 1 diabetes mellitus Type 2 diabetes mellitus Hybrid forms of diabetes Slowly evolving immune-mediated diabetes of adults Ketosis prone type 2 diabetes |
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Monogenic defects of β-cell function Monogenic defects in insulin action Diseases of the exocrine pancreas Endocrine disorders Drug- or chemical-induced Infection-related diabetes Uncommon specific forms of immune-mediated diabetes Other genetic syndromes sometimes associated with diabetes |
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Hyperglycemia first detected during pregnancy Diabetes mellitus in pregnancy Gestational diabetes mellitus |
The following criteria are used to establish a diagnosis of diabetes (Reference: [7]).
| Fasting plasma glucose (8 h no food intake) level ≥126 mg/dL (7.0 mmol/L) |
| 75 g OGTT 2 h value ≥ 200 mg/dL (11.1 mmol/L); OGTT: glucose load containing the equivalent of 75 g anhydrous glucose dissolved in water. |
| Hemoglobin A1c ≥ 6.5% |
| Random plasma glucose ≥200 mg/dL (11.1 mmol/L), sometimes appears as a hyperglycemic crisis |
| Clinical symptoms of diabetes (e.g., thirst, polydipsia, polyuria, weight loss, and dry mouth) |
Oral hypoglycemic medications approved by FDA indications [65,66].
| Pharmacological Group | Drug | Biochemical Key Factor for Mechanism of Action | Mechanism of Action |
|---|---|---|---|
| Sulfonylureas (SU) | glipizide | K-ATP channels of beta cells | Close ATP-dependent potassium channels that depolarize the beta cells, opening calcium channels and causing insulin release |
| Meglitinides | repaglinide nateglinide | K-ATP channels of beta cells | Same as SU |
| Biguanides | metformin | Increase hepatic AMP-activated protein kinase activity | Reduce hepatic gluconeogenesis and lipogenesis, stimulate fatty acid oxidation, and increase insulin-mediated uptake of glucose in muscles |
| Thiazolidinediones (TZD) | rosiglitazone pioglitazone | Activate peroxisome proliferator-activated receptor gamma (PPAR-γ) | Increase insulin sensitivity and stimulate fatty acid oxidation |
| α-Glucosidase inhibitors | acarbose | Inhibit alpha-glucosidase enzymes in the intestinal brush border cells | Inhibit polysaccharide reabsorption |
| GLP-1 Receptor Agonists | exenatide BID | Stimulate GLP-1 receptors | Lead to the increase in insulin secretion |
| DPP-4 inhibitors | sitagliptin | Inhibit the enzyme dipeptidyl peptidase 4 (DPP-4) | Decrease glucagon release, thus increasing glucose-dependent insulin release |
| SGLT2 inhibitors | dapagliflozin canagliflozin | Inhibit sodium–glucose cotransporter 2 (SGLT-2) in the proximal tubules of renal glomerulus | Inhibition of glucose reabsorption, resulting in glycosuria |
| Cycloset | bromocriptine | Dopamine (D2) receptor agonist | Resets the hypothalamic circadian rhythm and improves insulin resistance |
Figure 1Summary of glucose-lowering medication in T2DM: monotherapy and combination of drugs. Adapted from the 2022 ADA Professional Practice Committee (PPC) based on the work of Davis and Busa et al. [75,76,77]. This strategy suggests a selection of therapy rather than sequential add-on, which may require the adjustment of ongoing therapies. Treatment should be individualized to comorbidities (such as heart failure, atherosclerotic cardiovascular disease, chronic kidney disease, and cardiovascular disease), patient-centered treatment factors, and management needs. DPP-4i, dipeptidyl peptidase 4 inhibitor; GLP-1 agonist, glucagon-like peptide 1 receptor agonist; SGLT2i, sodium–glucose cotransporter 2 inhibitor; SU, sulfonylurea; TZD, thiazolidinedione. * A treatment with DPP-4 inhibitors should be stopped when GLP-1 receptor agonists are used [78].
Recent multi-omics approaches that revealed T2DM-associated factors.
| Omics/Field | Measures | Results | Assay | References |
|---|---|---|---|---|
| Genomics | 16S rRNA on microbiome analysis | Smoking and/or HIV lowers microbiome diversity in T2DM | NGS | [ |
| Genomics | 16S rRNA on microbiome analysis | Metformin helps to normalize microbiome with the support of | NGS | [ |
| Genomics | Analysis of SNPs | SNPs in the CAT, FTO and UCP1 genes associated with retinopathy and nephropathy | Sequenom platform | [ |
| Genomics | Genome sequencing | Heritability of T2DM is approximately 10–15% | GWAS | [ |
| Epigenomics | CpGs methylation pattern | CpG methylation of ABCG1, LOXL2, TXNIP, SLC1A5 and SREBF1 is associated with T2DM | EWAS, Illumina 450K methylation array | [ |
| Epigenomics | Alpha or beta cell-specific open chromatin landscape | Alpha cell-specific ATAC-seq peaks: ISL1 and MAFB; beta cell-specific: SMAD2 | ATAC-seq | [ |
| Epigenomics | Open chromatin regions/SNPs | Thousands of pancreatic islet-specific enhancer–target gene pairs | Hi-C, ATAC-seq, ChIP-seq | [ |
| Transcriptomics | Gene expression | T2DM-specific gene expression signatures in alpha, beta and delta cells | scRNA-seq | [ |
| Transcriptomics | Gene expression, regulatory networks | Increased OTUD7B, PPRC1, ARRB2, C17orf96, NME2, and E2F1 or four markers with decreased PageRank centrality (FBXW7, CXCL8, FHL1, and CELF4) | scRNA-seq | [ |
| Epigenomics | scRNA-seq and deep learning approaches | T2DM-associated SNPs were significantly enriched in beta cell-specific and common islet-specific open chromatin | scRNA-seq and deep learning approaches | [ |
| Transcriptomics | Gene expression, pathway analysis | T2DM-associated genes responsible for energy metabolism, immune homeostasis, and autophagy | Meta-analysis of scRNA-seq data | [ |
| Transcriptomics |
Whole transcriptome | Top DEGs in peripheral fat of Asian Indians associated with T2DM: | Affymetrix GeneChip PrimeView Human Gene Expression Array | [ |
| Transcriptomics |
Whole transcriptome | Altered lipid, glucose, and protein metabolism; adipogenesis defect; and inflammation in peripheral fat of Asian Indians associated with T2DM | Bulk RNAseq | [ |
| Genomics | Analysis of SNPs | s2241766-G (ADIPOQ), rs6494730-T (FEM1B), rs1799817-A, rs2059806-T (INSR), rs11745088-C (FST), rs9939609-A, and rs9940128-A (FTO) were associated with T2DM in southern Asian Indians | AGENA | [ |
| Proteomics | Protein concentrations | Osteopontin and osteoprotegerin are elevated in T2DM | Milliplex Luminex assay | [ |
| Proteomics | Protein concentrations | High KIM-1 and β2-B2M are associated with renal failure | Luminex Multiplex ELISA Luminex assay | [ |
| Proteomics | Protein concentration | High KIM-1 is associated with low GFR | Multiplex Luminex Panel | [ |
| Proteomics | Immune cell infiltration | High HLA-DR+ macrophages and HLA-DR+ CD8+ T-cells in the islets of pancreata of T2DM patients | Single-cell imaging mass cytometry | [ |
| Lipidomics | Lipid composition | High TAGs, DAGs, PEs: high risk for T2DM | Mass spectrometry (MS) | [ |
| Lipidomics | Lipid composition | High TAGs, DAGs and Low PC–PLs: high risk for T2DM | Ultra-performance liquid chromatography and MS | [ |