DPP-4 inhibitors for the treatment of type 2 diabetes: a methodology overview of systematic reviews

Machine learning-based prediction of risk factors for abnormal glycemic control in diabetic cancer patients receiving nutrition support: a case-control study

PURPOSE

To date, risk factors affecting abnormal glycemic control have not been investigated. This study aimed to analyze risk factors for hypoglycemia or hyperglycemia in diabetic cancer patients receiving nutritional support by using machine learning methods.

METHODS

This retrospective two-center study was performed using medical records. Odds ratios and adjusted odds ratios were estimated from univariate and multivariate analyses, respectively. Machine learning algorithms, including five-fold cross-validated multivariate logistic regression, elastic net, and random forest, were developed to predict risk factors for hypoglycemia and hyperglycemia.

RESULTS

Data from 127 patients were analyzed. The use of sulfonylurea (SU) and blood urea nitrogen (BUN) level > 20 mg/dL increased hypoglycemia by 6.3-fold (95% CI 1.30-30.47) and 5.0-fold (95% CI 1.06-23.46), respectively. In contrast, patients who received an actual energy intake/total energy expenditure (TEE) ≥ 120% and used dipeptidyl peptidase-4 (DPP-4) inhibitors had a higher risk of hyperglycemia by 19.3- (95% CI 1.46-254.78) and 3.3-fold (95% CI 1.23-8.61), respectively. An initial blood glucose level ≥ 182.5 mg/dL also increased the risk of hyperglycemia by 15.3-fold. AUROC values for all machine learning methods indicated acceptable and excellent performance for hypoglycemia and hyperglycemia.

CONCLUSION

The use of SU and BUN level > 20 mg/dL increased the risk of hypoglycemia, whereas an initial blood glucose level ≥ 182.5 mg/dL, a supplied actual energy intake/ TEE ≥ 120%, and the use of DPP-4 inhibitors increased the risk of hyperglycemia.

Diabetes and Its Complications: Therapies Available, Anticipated and Aspired

Worldwide, diabetes ranks among the ten leading causes of mortality. Prevalence of diabetes is growing rapidly in low and middle income countries. It is a progressive disease leading to serious co-morbidities, which results in increased cost of treatment and over-all health system of the country. Pathophysiological alterations in Type 2 Diabetes (T2D) progressed from a simple disturbance in the functioning of the pancreas to triumvirate to ominous octet to egregious eleven to dirty dozen model. Due to complex interplay of multiple hormones in T2D, there may be multifaceted approach in its management. The 'long-term secondary complications' in uncontrolled diabetes may affect almost every organ of the body, and finally may lead to multi-organ dysfunction. Available therapies are inconsistent in maintaining long term glycemic control and their long term use may be associated with adverse effects. There is need for newer drugs, not only for glycemic control but also for prevention or mitigation of secondary microvascular and macrovascular complications. Increased knowledge of the pathophysiology of diabetes has contributed to the development of novel treatments. Several new agents like Glucagon Like Peptide - 1 (GLP-1) agonists, Dipeptidyl Peptidase IV (DPP-4) inhibitors, amylin analogues, Sodium-Glucose transport -2 (SGLT- 2) inhibitors and dual Peroxisome Proliferator-Activated Receptor (PPAR) agonists are available or will be available soon, thus extending the range of therapy for T2D, thereby preventing its long term complications. The article discusses the pathophysiology of diabetes along with its comorbidities, with a focus on existing and novel upcoming antidiabetic drugs which are under investigation. It also dives deep to deliberate upon the novel therapies that are in various stages of development. Adding new options with new mechanisms of action to the treatment armamentarium of diabetes may eventually help improve outcomes and reduce its economic burden.

Dipeptidyl peptidase-4 (DPP4) inhibition in COVID-19

AIMS

SARS-CoV-2 causes severe respiratory syndrome (COVID-19) with high mortality due to a direct cytotoxic viral effect and a severe systemic inflammation. We are herein discussing a possible novel therapeutic tool for COVID-19.

METHODS

Virus binds to the cell surface receptor ACE2; indeed, recent evidences suggested that SARS-CoV-2 may be using as co-receptor, when entering the cells, the same one used by MERS-Co-V, namely the DPP4/CD26 receptor. The aforementioned observation underlined that mechanism of cell entry is supposedly similar among different coronavirus, that the co-expression of ACE2 and DPP4/CD26 could identify those cells targeted by different human coronaviruses and that clinical complications may be similar.

RESULTS

The DPP4 family/system was implicated in various physiological processes and diseases of the immune system, and DPP4/CD26 is variously expressed on epithelia and endothelia of the systemic vasculature, lung, kidney, small intestine and heart. In particular, DPP4 distribution in the human respiratory tract may facilitate the entrance of the virus into the airway tract itself and could contribute to the development of cytokine storm and immunopathology in causing fatal COVID-19 pneumonia.

CONCLUSIONS

The use of DPP4 inhibitors, such as gliptins, in patients with COVID-19 with, or even without, type 2 diabetes, may offer a simple way to reduce the virus entry and replication into the airways and to hamper the sustained cytokine storm and inflammation within the lung in patients diagnosed with COVID-19 infection.

1-Phenyl-N-(benzothiazol-2-yl)methanimine derivatives as Middle East respiratory syndrome coronavirus inhibitors

A series of novel 1-phenyl-N-(benzothiazol-2-yl)methanimine derivatives were synthesized and their in vitro inhibitory potencies were evaluated on MERS-S pseudovirus.

Ten years of experience with DPP-4 inhibitors for the treatment of type 2 diabetes mellitus

Achieving and maintaining recommended glycemic targets without causing adverse e ffects, including hypoglycemia, is challenging, especially in older patients with type 2 diabetes mellitus (T2DM). The introduction of dipeptidyl peptidase-4 (DPP-4) inhibitors, more than 10 years ago, has provided an alternative to conventional medications for the intensification of glucose-lowering treatment after failure of metformin monotherapy, and therefore, marked an important advance in the management of T2DM. By prolonging the activity of incretin hormones, DPP-4 inhibitors induce insulin release and decrease glucagon secretion in a glucose-dependent manner. This results in a more physiologic glycemic control as compared to that ensured by insulin secretagogues (sulfonylureas and glinides). Overall, DPP-4 inhibitors have a favorable safety profile and can be used without dose adjustments in older adults and in patients with mild renal impairment; they have a neutral effect on body weight and do not cause hypoglycemia by themselves. Safety issues, reported mainly in post-marketing surveillance programs and including cardiovascular outcomes and the risk of acute pancreatitis, are being extensively investigated. The aim of this review is to discuss the impact of DPP-4 inhibitors on the treatment of T2DM, after 10 years of experience, with an emphasis on diabetes care in Italy. We will first describe T2DM treatment in Italy and then provide an overview of the main findings from randomized controlled trials, real-world studies and post-marketing surveillance programs with DPP-4 inhibitors.

A Network Pharmacology Approach to Uncover the Molecular Mechanisms of Herbal Formula Ban-Xia-Xie-Xin-Tang

Ban-Xia-Xie-Xin-Tang (BXXXT) is a classical formula from Shang-Han-Lun which is one of the earliest books of TCM clinical practice. In this work, we investigated the therapeutic mechanisms of BXXXT for the treatment of multiple diseases using a network pharmacology approach. Here three BXXXT representative diseases (colitis, diabetes mellitus, and gastric cancer) were discussed, and we focus on in silico methods that integrate drug-likeness screening, target prioritizing, and multilayer network extending. A total of 140 core targets and 72 representative compounds were finally identified to elucidate the pharmacology of BXXXT formula. After constructing multilayer networks, a good overlap between BXXXT nodes and disease nodes was observed at each level, and the network-based proximity analysis shows that the relevance between the formula targets and disease genes was significant according to the shortest path distance (SPD) and a random walk with restart (RWR) based scores for each disease. We found that there were 22 key pathways significantly associated with BXXXT, and the therapeutic effects of BXXXT were likely addressed by regulating a combination of targets in a modular pattern. Furthermore, the synergistic effects among BXXXT herbs were highlighted by elucidating the molecular mechanisms of individual herbs, and the traditional theory of "Jun-Chen-Zuo-Shi" of TCM formula was effectively interpreted from a network perspective. The proposed approach provides an effective strategy to uncover the mechanisms of action and combinatorial rules of BXXXT formula in a holistic manner.