Predictive factors associated with glycaemic response to exenatide in Chinese patients with type 2 diabetes mellitus

Predictive factors of response to liraglutide in patients with type 2 diabetes mellitus and metabolic syndrome

Background

Although liraglutide has established advantages in treating patients with type 2 diabetes mellitus (T2DM) and metabolic syndrome (MS), there are still some patients with lower responsiveness to liraglutide. The objective of the study was to identify the predictors of response to liraglutide in patients with T2DM and MS.

Methods

This retrospective cohort study included patients diagnosed with T2DM and MS who received liraglutide treatment as a part of their diabetes management for a minimum of six months. The participants were stratified into two groups: responders (HbA1c reduction≥1.0% and weight loss≥3%) and non-responders. The discrepancies in baseline data between the two groups were analyzed, containing comedications, test parameters, and basic profiles. The affecting factors of response to liraglutide by Logistic regression analysis were performed, and the predictive ability of the identified factors was evaluated by plotting a receiver operating characteristic (ROC) curve.

Results

A total of 417 patients with T2DM and MS were examined and followed up according to the inclusion criteria, and 206 patients completed the follow-up; 105 (50.97%) were responders and 101 (49.03%) were non-responders to liraglutide. The binary logistic regression analysis identified baseline HbA1c, baseline BMI, and the duration of T2DM as significant predictors of glycemic and weight responses to liraglutide (P <0.05). The area under the curve of the ROC for the three predictors of liraglutide response after 6 months of treatment was 0.851 (95% confidence interval: 0.793 - 0.910).

Conclusion

The baseline HbA1c, baseline BMI, and duration of T2DM were shown to be predictive factors of glycemic and weight improvements in patients with T2DM and MS treated with liraglutide, and had good predictive power.

Treatment effect heterogeneity following type 2 diabetes treatment with GLP1-receptor agonists and SGLT2-inhibitors: a systematic review

BACKGROUND

A precision medicine approach in type 2 diabetes requires the identification of clinical and biological features that are reproducibly associated with differences in clinical outcomes with specific anti-hyperglycaemic therapies. Robust evidence of such treatment effect heterogeneity could support more individualized clinical decisions on optimal type 2 diabetes therapy.

METHODS

We performed a pre-registered systematic review of meta-analysis studies, randomized control trials, and observational studies evaluating clinical and biological features associated with heterogenous treatment effects for SGLT2-inhibitor and GLP1-receptor agonist therapies, considering glycaemic, cardiovascular, and renal outcomes. After screening 5,686 studies, we included 101 studies of SGLT2-inhibitors and 75 studies of GLP1-receptor agonists in the final systematic review.

RESULTS

Here we show that the majority of included papers have methodological limitations precluding robust assessment of treatment effect heterogeneity. For SGLT2-inhibitors, multiple observational studies suggest lower renal function as a predictor of lesser glycaemic response, while markers of reduced insulin secretion predict lesser glycaemic response with GLP1-receptor agonists. For both therapies, multiple post-hoc analyses of randomized control trials (including trial meta-analysis) identify minimal clinically relevant treatment effect heterogeneity for cardiovascular and renal outcomes.

CONCLUSIONS

Current evidence on treatment effect heterogeneity for SGLT2-inhibitor and GLP1-receptor agonist therapies is limited, likely reflecting the methodological limitations of published studies. Robust and appropriately powered studies are required to understand type 2 diabetes treatment effect heterogeneity and evaluate the potential for precision medicine to inform future clinical care.

Precision medicine in type 2 diabetes: A systematic review of treatment effect heterogeneity for GLP1-receptor agonists and SGLT2-inhibitors

Background

A precision medicine approach in type 2 diabetes requires identification of clinical and biological features that are reproducibly associated with differences in clinical outcomes with specific anti-hyperglycaemic therapies. Robust evidence of such treatment effect heterogeneity could support more individualized clinical decisions on optimal type 2 diabetes therapy.

Methods

We performed a pre-registered systematic review of meta-analysis studies, randomized control trials, and observational studies evaluating clinical and biological features associated with heterogenous treatment effects for SGLT2-inhibitor and GLP1-receptor agonist therapies, considering glycaemic, cardiovascular, and renal outcomes.

Results

After screening 5,686 studies, we included 101 studies of SGLT2-inhibitors and 75 studies of GLP1-receptor agonists in the final systematic review. The majority of papers had methodological limitations precluding robust assessment of treatment effect heterogeneity. For glycaemic outcomes, most cohorts were observational, with multiple analyses identifying lower renal function as a predictor of lesser glycaemic response with SGLT2-inhibitors and markers of reduced insulin secretion as predictors of lesser response with GLP1-receptor agonists. For cardiovascular and renal outcomes, the majority of included studies were post-hoc analyses of randomized control trials (including meta-analysis studies) which identified limited clinically relevant treatment effect heterogeneity.

Conclusions

Current evidence on treatment effect heterogeneity for SGLT2-inhibitor and GLP1-receptor agonist therapies is limited, likely reflecting the methodological limitations of published studies. Robust and appropriately powered studies are required to understand type 2 diabetes treatment effect heterogeneity and evaluate the potential for precision medicine to inform future clinical care.

Plain language summary

This review identifies research that helps understand which clinical and biological factors that are associated with different outcomes for specific type 2 diabetes treatments. This information could help clinical providers and patients make better informed personalized decisions about type 2 diabetes treatments. We focused on two common type 2 diabetes treatments: SGLT2-inhibitors and GLP1-receptor agonists, and three outcomes: blood glucose control, heart disease, and kidney disease. We identified some potential factors that are likely to lessen blood glucose control including lower kidney function for SGLT2-inhibitors and lower insulin secretion for GLP1-receptor agonists. We did not identify clear factors that alter heart and renal disease outcomes for either treatment. Most of the studies had limitations, meaning more research is needed to fully understand the factors that influence treatment outcomes in type 2 diabetes.

Allergic diseases in children in the age of the COVID-19 pandemic

COVID-19 coronavirus infection caused by the SARS-CoV-2 virus has become a real disaster for all of humanity. Today, issues related to diagnostics, clinical presentations, treatment of the complications, preventive measures, including vaccination for a new coronavirus infection, are relevant. It is also important to identify risk factors for a severe course of the disease, features of the development of infection against the background of comorbid conditions and different immunological reactivity of the human body. The comorbidity of allergic and infectious diseases is based on the common humoral and cellular mechanisms of the immune response. The trigger for the development of allergic diseases is often the viruses of measles and chickenpox, influenza, parainfluenza, rhinoviruses, enteroviruses, respiratory syncytial viruses, coronaviruses, and others. Most allergic patients are predisposed to acute respiratory viral infections. COVID-19 occurs in 0.39–12.3% of children. Children tend to have milder disease than adults and have low mortality rates. At the same time, one should not forget about the adequate support for patients with chronic diseases, especially children with allergic diseases. Viruses and preventive hygiene measures associated with a pandemic are triggers of an exacerbation of bronchial asthma and atopic dermatitis. Early diagnosis, adequate treatment of allergic diseases in children, and provision of doctors with information are also problematic. It is important to understand which patients with bronchial asthma are at particular risk and how inhaled glucocorticosteroids may influence the course and outcome of COVID-19. International associations and societies have developed guidelines for the management of children with allergies during the COVID-19 pandemic. Inhaled glucocorticosteroids for bronchial asthma reduce the expression of genes of the main target receptors for the SARS-CoV-2 virus. Anti-inflammatory therapy for asthma, primarily inhaled glucocorticosteroids, should be continued until asthma control is achieved, which will help reduce the risk of an unfavorable course of COVID-19.

Pathophysiology, phenotypes and management of type 2 diabetes mellitus in Indian and Chinese populations

Nearly half of all adults with type 2 diabetes mellitus (T2DM) live in India and China. These populations have an underlying predisposition to deficient insulin secretion, which has a key role in the pathogenesis of T2DM. Indian and Chinese people might be more susceptible to hepatic or skeletal muscle insulin resistance, respectively, than other populations, resulting in specific forms of insulin deficiency. Cluster-based phenotypic analyses demonstrate a higher frequency of severe insulin-deficient diabetes mellitus and younger ages at diagnosis, lower β-cell function, lower insulin resistance and lower BMI among Indian and Chinese people compared with European people. Individuals diagnosed earliest in life have the most aggressive course of disease and the highest risk of complications. These characteristics might contribute to distinctive responses to glucose-lowering medications. Incretin-based agents are particularly effective for lowering glucose levels in these populations; they enhance incretin-augmented insulin secretion and suppress glucagon secretion. Sodium-glucose cotransporter 2 inhibitors might also lower blood levels of glucose especially effectively among Asian people, while α-glucosidase inhibitors are better tolerated in east Asian populations versus other populations. Further research is needed to better characterize and address the pathophysiology and phenotypes of T2DM in Indian and Chinese populations, and to further develop individualized treatment strategies.

Effects of PPARD gene variants on the therapeutic responses to exenatide in chinese patients with type 2 diabetes mellitus

BACKGROUND

Exenatide is a GLP-1R agonist that often exhibits considerable interindividual variability in therapeutic efficacy. However, there is no evidence about the impact of genetic variants in the PPARD on the therapeutic efficacy of exenatide. This research was aimed to explore the influence of PPARD gene polymorphism on the therapeutic effect of exenatide, and to identify the potential mechanism futher.

METHODS

A total of 300 patients with T2DM and 200 control subjects were enrolled to identify PPARD rs2016520 and rs3777744 genotypes. A prospective clinical study was used to collect clinical indicators and peripheral blood of T2DM patients treated with exenatide monotherapy for 6 months. The SNaPshot method was used to identify PPARD rs2016520 and rs3777744 genotypes, and then we performed correlation analysis between PPARD gene variants and the efficacy of exenatide, and conducted multiple linear regression analysis of factors affecting the therapeutic effect of exenatide. HepG2 cells were incubated with exenatide in the absence or presence of a PPARδ agonist or the siPPARδ plasmid, after which the levels of GLP-1R and the ratio of glucose uptake were determined.

RESULTS

After 6 months exenatide monotherapy, we observed that homeostasis model assessment for insulin resistance (HOMA-IR) levels of the subjects with at least one C allele of the PPARD rs2016520 were significantly lower than those with the TT genotype, which suggested that the PPARD rs2016520 TT genotype conferred the poor exenatide response through a reduction of insulin resistance, as measured by HOMA-IR. The carriers of G alleles at rs3777744 exhibited higher levels of in waist to hip ratio (WHR), fasting plasma glucose (FPG), hemoglobin A1c (HbA1c) and HOMA-IR compared to individuals with the AA genotype following 6 months of exenatide treatment, potentially accounting for the lower failure rate of exenatide therapy among the AA homozygotes. In an insulin resistant HepG2 cell model, the PPARδ agonists enhanced exenatide efficacy on insulin resistance, with the expression of GLP-1R being up-regulated markedly.

CONCLUSION

These data suggest that the PPARD rs2016520 and rs3777744 polymorphisms are associated with exenatide monotherapy efficacy, due to the pivotal role of PPARδ in regulating insulin resistance through affecting the expression of GLP-1R. This study was registered in the Chinese Clinical Trial Register (No. ChiCTR-CCC13003536).

Application of machine learning methods for the development of antidiabetic drugs

Diabetes is a chronic non-communicable disease caused by several different routes, which has attracted increasing attention. In order to speed up the development of new selective drugs, machine learning (ML) technology has been applied in the process of diabetes drug development, which opens up a new blueprint for drug design. This review provides a comprehensive portrayal of the application of ML in antidiabetic drug use.