Pharmacogenetics of type 2 diabetes mellitus, the route toward tailored medicine

KCNQ1 rs2237895 gene polymorphism increases susceptibility to type 2 diabetes mellitus in Asian populations

BACKGROUND

The association of single nucleotide polymorphism of KCNQ1 gene rs2237895 with type 2 diabetes mellitus (T2DM) is currently controversial. It is unknown whether this association can be gene realized across different populations.

AIM

To determine the association of KCNQ1 rs2237895 with T2DM and provide reliable evidence for genetic susceptibility to T2DM.

METHODS

We searched PubMed, Embase, Web of Science, Cochrane Library, Medline, Baidu Academic, China National Knowledge Infrastructure, China Biomedical Liter-ature Database, and Wanfang to investigate the association between KCNQ1 gene rs2237895 and the risk of T2DM up to January 12, 2022. Review Manager 5.4 was used to analyze the association of the KCNQ1 gene rs2237895 polymorphism with T2DM and to evaluate the publication bias of the selected literature.

RESULTS

Twelve case-control studies (including 11273 cases and 11654 controls) met our inclusion criteria. In the full population, allelic model [odds ratio (OR): 1.19; 95% confidence interval (95%CI): 1.09-1.29; P < 0.0001], recessive model (OR: 1.20; 95%CI: 1.11-1.29; P < 0.0001), dominant model (OR: 1.27. 95%CI: 1.14-1.42; P < 0.0001), and codominant model (OR: 1.36; 95%CI: 1.15-1.60; P = 0.0003) (OR: 1.22; 95%CI: 1.10-1.36; P = 0.0002) indicated that the KCNQ1 gene rs2237895 polymorphism was significantly correlated with susceptibility to T2DM. In stratified analysis, this association was confirmed in Asian populations: allelic model (OR: 1.25; 95%CI: 1.13-1.37; P < 0.0001), recessive model (OR: 1.29; 95%CI: 1.11-1.49; P = 0.0007), dominant model (OR: 1.35; 95%CI: 1.20-1.52; P < 0.0001), codominant model (OR: 1.49; 95%CI: 1.22-1.81; P < 0.0001) (OR: 1.26; 95%CI: 1.16-1.36; P < 0.0001). In non-Asian populations, this association was not significant: Allelic model (OR: 1.06, 95%CI: 0.98-1.14; P = 0.12), recessive model (OR: 1.04; 95%CI: 0.75-1.42; P = 0.83), dominant model (OR: 1.06; 95%CI: 0.98-1.15; P = 0.15), codominant model (OR: 1.08; 95%CI: 0.82-1.42; P = 0.60. OR: 1.15; 95%CI: 0.95-1.39; P = 0.14).

CONCLUSION

KCNQ1 gene rs2237895 was significantly associated with susceptibility to T2DM in an Asian population. Carriers of the C allele had a higher risk of T2DM. This association was not significant in non-Asian populations.

Landscape of pharmacogenetic variants associated with non-insulin antidiabetic drugs in the Indian population

INTRODUCTION

Genetic variants contribute to differential responses to non-insulin antidiabetic drugs (NIADs), and consequently to variable plasma glucose control. Optimal control of plasma glucose is paramount to minimizing type 2 diabetes-related long-term complications. India's distinct genetic architecture and its exploding burden of type 2 diabetes warrants a population-specific survey of NIAD-associated pharmacogenetic (PGx) variants. The recent availability of large-scale whole genomes from the Indian population provides a unique opportunity to generate a population-specific map of NIAD-associated PGx variants.

RESEARCH DESIGN AND METHODS

We mined 1029 Indian whole genomes for PGx variants, drug-drug interaction (DDI) and drug-drug-gene interactions (DDGI) associated with 44 NIADs. Population-wise allele frequencies were estimated and compared using Fisher's exact test.

RESULTS

Overall, we found 76 known and 52 predicted deleterious common PGx variants associated with response to type 2 diabetes therapy among Indians. We report remarkable interethnic differences in the relative cumulative counts of decreased and increased response-associated alleles across NIAD classes. Indians and South Asians showed a significant excess of decreased metformin response-associated alleles compared with other global populations. Network analysis of shared PGx genes predicts high DDI risk during coadministration of NIADs with other metabolic disease drugs. We also predict an increased CYP2C19-mediated DDGI risk for CYP3A4/3A5-metabolized NIADs, saxagliptin, linagliptin and glyburide when coadministered with proton-pump inhibitors (PPIs).

CONCLUSIONS

Indians and South Asians have a distinct PGx profile for antidiabetes drugs, marked by an excess of poor treatment response-associated alleles for various NIAD classes. This suggests the possibility of a population-specific reduced drug response in atleast some NIADs. In addition, our findings provide an actionable resource for accelerating future diabetes PGx studies in Indians and South Asians and reconsidering NIAD dosing guidelines to ensure maximum efficacy and safety in the population.

Diabetes and artificial intelligence beyond the closed loop: a review of the landscape, promise and challenges

The discourse amongst diabetes specialists and academics regarding technology and artificial intelligence (AI) typically centres around the 10% of people with diabetes who have type 1 diabetes, focusing on glucose sensors, insulin pumps and, increasingly, closed-loop systems. This focus is reflected in conference topics, strategy documents, technology appraisals and funding streams. What is often overlooked is the wider application of data and AI, as demonstrated through published literature and emerging marketplace products, that offers promising avenues for enhanced clinical care, health-service efficiency and cost-effectiveness. This review provides an overview of AI techniques and explores the use and potential of AI and data-driven systems in a broad context, covering all diabetes types, encompassing: (1) patient education and self-management; (2) clinical decision support systems and predictive analytics, including diagnostic support, treatment and screening advice, complications prediction; and (3) the use of multimodal data, such as imaging or genetic data. The review provides a perspective on how data- and AI-driven systems could transform diabetes care in the coming years and how they could be integrated into daily clinical practice. We discuss evidence for benefits and potential harms, and consider existing barriers to scalable adoption, including challenges related to data availability and exchange, health inequality, clinician hesitancy and regulation. Stakeholders, including clinicians, academics, commissioners, policymakers and those with lived experience, must proactively collaborate to realise the potential benefits that AI-supported diabetes care could bring, whilst mitigating risk and navigating the challenges along the way.

Predictors of efficacy of Sodium-GLucose Transporter-2 inhibitors and Glucagon-Like Peptide 1 receptor agonists: A retrospective cohort study

AIMS

The aim of the present study was to verify predictors of HbA1c reduction with Sodium-GLucose Transporter-2 (SGLT2) inhibitors and Glucagon-Like Peptide 1 (GLP1) receptor agonists in routine clinical practice.

MATERIALS AND METHODS

A retrospective cohort study was performed, enrolling patients with type 2 diabetes aged ≥18 years who received a prescription of an SGLT2 inhibitor or a long-acting GLP1 receptor agonist with at least 6 months of persistence in therapy. Therapeutic success was defined as HbA1c reduction >10 mmol/mol or attainment of the recommended HbA1c target.

RESULTS

Out of 236 patients receiving SGLT2 inhibitors, 148 were categorised as successes: successes had a mean lower age and higher estimated Glomerular Filtration Rate than failures, but only age retained statistical significance at multivariate analysis (Odds Ratio with 95% confidence interval: 0.94 [0.91-0.98], p = 0.006). In the GLP1 receptor agonists cohort (N = 214) there were 146 successes, showing a significantly shorter duration of diabetes even after adjusting for age, and baseline HbA1c (HR 0.96 [0.91-0.99], p = 0.02).

CONCLUSIONS

The present study is a preliminary exploration of factors associated with HbA1c response to SGLT2 inhibitors and GLP1 receptor agonists. Differences in predictors of HbA1c changes across different classes of drugs could be useful in identifying the most suitable drug in individual patients. SGLT2 inhibitors seem to be associated with a greater reduction of HbA1c in younger subjects, and GLP1 agonists in those with a shorter duration of diabetes.

Effects of vitamin D supplementation on glucose and lipid metabolism in patients with type 2 diabetes mellitus and risk factors for insulin resistance

BACKGROUND

Type 2 diabetes mellitus (T2DM) is a chronic metabolic disease featured by insulin resistance (IR) and decreased insulin secretion. Currently, vitamin D deficiency is found in most patients with T2DM, but the relationship between vitamin D and IR in T2DM patients requires further investigation.

AIM

To explore the risk factors of IR and the effects of vitamin D supplementation on glucose and lipid metabolism in patients with T2DM.

METHODS

Clinical data of 162 T2DM patients treated in First Affiliated Hospital of Harbin Medical University between January 2019 and February 2022 were retrospectively analyzed. Based on the diagnostic criteria of IR, the patients were divided into a resistance group (n = 100) and a non-resistance group (n = 62). Subsequently, patients in the resistance group were subdivided to a conventional group (n = 44) or a joint group (n = 56) according to the treatment regimens. Logistic regression was carried out to analyze the risk factors of IR in T2DM patients. The changes in glucose and lipid metabolism indexes in T2DM patients with vitamin D deficiency were evaluated after the treatment.

RESULTS

Notable differences were observed in age and body mass index (BMI) between the resistance group and the non-resistance group (both P < 0.05). The resistance group exhibited a lower 25-hydroxyvitamin D3 (25(OH)D3) level, as well as notably higher levels of 2-h postprandial blood glucose (2hPG), fasting blood glucose (FBG), and glycosylated hemoglobin (HbA1c) than the non-resistance group (all P < 0.0001). Additionally, the resistance group demonstrated a higher triglyceride (TG) level but a lower high-density lipoprotein-cholesterol (HDL-C) level than the non-resistance group (all P < 0.0001). The BMI, TG, HDL-C, 25(OH)D3, 2hPG, and HbA1c were found to be risk factors of IR. Moreover, the post-treatment changes in levels of 25(OH)D3, 2hPG, FBG and HbA1c, as well as TG, total cholesterol, and HDL-C in the joint group were more significant than those in the conventional group (all P < 0.05).

CONCLUSION

Patients with IR exhibit significant abnormalities in glucose and lipid metabolism parameters compared to the non-insulin resistant group. Logistic regression analysis revealed that 25(OH)D3 is an independent risk factor influencing IR. Supplementation of vitamin D has been shown to improve glucose and lipid metabolism in patients with IR and T2DM.

Examining the Genetic Role of rs8192675 Variant in Saudi Women Diagnosed with Polycystic Ovary Syndrome

Polycystic ovary syndrome is a complex disorder defined by the Rotterdam criteria. Insulin resistance is a common factor for the development of type 2 diabetes mellitus among women with PCOS. The SLC2A2 gene has been identified as a T2DM gene by genome-wide association studies in the rs8192675 SNP. This study aimed to investigate the rs8192675 SNP in women diagnosed with PCOS on a molecular level and further for T2DM development in the Saudi women. In this case-control study, 100 PCOS women and 100 healthy controls were selected. Among 100 PCOS women, 28 women showed T2DM development. Genotyping for rs8192675 SNP was performed by PCR-RFLP analysis. Additionally, Sanger sequencing was performed to validate the RFLP analysis. The obtained data were used for a statistical analysis for the genotype and allele frequencies, logistic regression, and ANOVA analysis. The clinical data confirmed the positive association between FBG, FI, FSH, TT, TC, HDLc, LDLc, and family histories (p < 0.05). HWE analysis was associated in both the PCOS cases and the control individuals. Genotype and allele frequencies were associated in PCOS women and strongly associated with women with PCOS who developed T2DM (p < 0.05). No association was found in the logistic regression model or ANOVA analysis studied in women with PCOS (p > 0.05). A strong association was observed between the rs8192675 SNP and women with PCOS who developed T2DM using ANOVA analysis (p < 0.05). This study confirms that the rs8192675 SNP is associated with women with PCOS and strongly associated with women with PCOS with developed T2DM in Saudi Arabia.

Profiling of patients with type 2 diabetes based on medication adherence data

Introduction

Type 2 diabetes mellitus (T2DM) is a complex, chronic disease affecting multiple organs with varying symptoms and comorbidities. Profiling patients helps identify those with unfavorable disease progression, allowing for tailored therapy and addressing special needs. This study aims to uncover different T2DM profiles based on medication intake records and laboratory measurements, with a focus on how individuals with diabetes move through disease phases.

Methods

We use medical records from databases of the last 20 years from the Department of Endocrinology and Diabetology of the University Medical Center in Maribor. Using the standard ATC medication classification system, we created a patient-specific drug profile, created using advanced natural language processing methods combined with data mining and hierarchical clustering.

Results

Our results show a well-structured profile distribution characterizing different age groups of individuals with diabetes. Interestingly, only two main profiles characterize the early 40-50 age group, and the same is true for the last 80+ age group. One of these profiles includes individuals with diabetes with very low use of various medications, while the other profile includes individuals with diabetes with much higher use. The number in both groups is reciprocal. Conversely, the middle-aged groups are characterized by several distinct profiles with a wide range of medications that are associated with the distinct concomitant complications of T2DM. It is intuitive that the number of profiles increases in the later age groups, but it is not obvious why it is reduced later in the 80+ age group. In this context, further studies are needed to evaluate the contributions of a range of factors, such as drug development, drug adoption, and the impact of mortality associated with all T2DM-related diseases, which characterize these middle-aged groups, particularly those aged 55-75.

Conclusion

Our approach aligns with existing studies and can be widely implemented without complex or expensive analyses. Treatment and drug use data are readily available in healthcare facilities worldwide, allowing for profiling insights into individuals with diabetes. Integrating data from other departments, such as cardiology and renal disease, may provide a more sophisticated understanding of T2DM patient profiles.

Correlation between PPARG Pro12Ala Polymorphism and Therapeutic Responses to Thiazolidinediones in Patients with Type 2 Diabetes: A Meta-Analysis

Background: Thiazolidinediones (TZDs) are a type of oral drug that are utilized for the treatment of type 2 diabetes mellitus (T2DM). They function by acting as agonists for a nuclear transcription factor known as peroxisome proliferator-activated receptor-gamma (PPAR-γ). TZDs, such as pioglitazone and rosiglitazone, help enhance the regulation of metabolism in individuals with T2DM by improving their sensitivity to insulin. Previous studies have suggested a relationship between the therapeutic efficacy of TZDs and the PPARG Pro12Ala polymorphism (C > G, rs1801282). However, the small sample sizes of these studies may limit their applicability in clinical settings. To address this limitation, we conducted a meta-analysis assessing the influence of the PPARG Pro12Ala polymorphism on the responsiveness of TZDs. Method: We registered our study protocol with PROSPERO, number CRD42022354577. We conducted a comprehensive search of the PubMed, Web of Science, and Embase databases, including studies published up to August 2022. We examined studies investigating the association between the PPARG Pro12Ala polymorphism and metabolic parameters such as hemoglobin A_1C (HbA_1C), fasting plasma glucose (FPG), triglyceride (TG), low-density lipoprotein cholesterol (LDL), high-density lipoprotein cholesterol (HDL), and total cholesterol (TC). The mean difference (MD) and 95% confidence intervals (CIs) between pre- and post-drug administration were evaluated. The quality of the studies included in the meta-analysis was assessed by using the Newcastle-Ottawa Scale (NOS) tool for cohort studies. Heterogeneity across studies was assessed by using the I² value. An I² value greater than 50% indicated substantial heterogeneity, and a random-effects model was used for meta-analysis. If the I² value was below 50%, a fixed-effects model was employed instead. Both Begg's rank correlation test and Egger's regression test were performed to detect publication bias, using R Studio software. Results: Our meta-analysis incorporated 6 studies with 777 patients for blood glucose levels and 5 studies with 747 patients for lipid levels. The included studies were published between 2003 and 2016, with the majority involving Asian populations. Five of the six studies utilized pioglitazone, while the remaining study employed rosiglitazone. The quality scores, as assessed with the NOS, ranged from 8 to 9. Patients carrying the G allele exhibited a significantly greater reduction in HbA_1C (MD = -0.3; 95% CI = -0.55 to -0.05; p = 0.02) and FPG (MD = -10.91; 95% CI = -19.82 to -2.01; p = 0.02) levels compared to those with the CC genotype. Furthermore, individuals with the G allele experienced a significantly larger decrease in TG levels than those with the CC genotype (MD = -26.88; 95% CI = -41.30 to -12.46; p = 0.0003). No statistically significant differences were observed in LDL (MD = 6.69; 95% CI = -0.90 to 14.29; p = 0.08), HDL (MD = 0.31; 95% CI = -1.62 to 2.23; p = 0.75), and TC (MD = 6.4; 95% CI = -0.05 to 12.84; p = 0.05) levels. No evidence of publication bias was detected based on Begg's test and Egger's test results. Conclusions: This meta-analysis reveals that patients with the Ala12 variant in the PPARG Pro12Ala polymorphism are more likely to exhibit positive responses to TZD treatment in terms of HbA_1C, FPG, and TG levels compared to those with the Pro12/Pro12 genotype. These findings suggest that genotyping the PPARG Pro12Ala in diabetic patients may be advantageous for devising personalized treatment strategies, particularly for identifying individuals who are likely to respond favorably to TZDs.

Pharmacogenetic interactions of medications administered for weight loss in adults: a systematic review and meta-analysis

Aim: To analyze roles of single nucleotide variants (SNVs) on weight loss with US FDA-approved medications. Materials & methods: We searched the literature up until November 2022. Preferred Reporting Items for Systematic reviews and Meta-Analyses guidelines were followed. Results: 14 studies were included in qualitative analysis and seven in meta-analysis. SNVs in CNR1, GLP-1R, MC4R, TCF7L2, CTRB1/2, ADIPOQ, SORCS1 and ANKK1 were evaluated relative to weight loss with glucagon-like peptide-1 agonists (13 studies) or naltrexone-bupropion (one study). CNR1 gene (rs1049353), GLP-1R gene (rs6923761, rs10305420), TCF7L2 gene (rs7903146) were associated with weight loss in at least one study involving glucagon-like peptide-1 agonist(s). The meta-analysis did not identify any consistent effect of SNVs. Conclusion: Pharmacogenetic interactions for exenatide, liraglutide, naltrexone-bupropion and weight loss were identified, but the directionality was inconsistent.

Pharmacogenetic impact of SLC22A1 gene variant rs628031 (G/A) in newly diagnosed Indian type 2 diabetes patients undergoing metformin monotherapy

OBJECTIVES

Type 2 diabetes (T2D) imposes an enormous burden all over the world in both developed and developing countries. Inter-individual differences are attributed to polymorphisms in candidate genes resulting in altered absorption, transportation, distribution, and metabolism of oral antidiabetic drugs (OADs). Hence, the present study was undertaken to evaluate the pharmacogenetic impact of SLC22A1 gene variant rs628031 (G/A) on metformin monotherapy in newly diagnosed untreated T2D patients.

METHODS

Newly diagnosed T2D patients ( n  = 500) were enrolled according to inclusion/exclusion criteria. Initially, enrolled subjects were prescribed metformin monotherapy and followed up for at least 12 weeks. Response to metformin was evaluated in 478 patients who revisited for follow-up by measuring HbA1c.

RESULT

Out of 478 patients, 373 were responders to metformin monotherapy while 105 were non-responders. The pharmacogenetic impact was evaluated by genotype, haplotype, and pharmacogenetic analyses. 'GG' genotype and 'G' allele of SLC22A1 rs628031 G/A were observed in 48.8% and 67.7% of Met responders, respectively, while 20.9% and 49.1 % were in non-responders. Therefore, there was a 2.18-fold increase in the success rate of Met therapeutics.

CONCLUSION

Individuals carrying the 'GG' genotype or 'G' allele for SLC22A1 gene variant rs628031 G/A are better responders for Metformin monotherapy.

Effect of ertugliflozin on renal function and cardiovascular outcomes in patients with type 2 diabetes mellitus: A systematic review and meta-analysis

BACKGROUND

The global prevalence of type 2 diabetes mellitus (T2DM) is growing yearly. The efficacy of ertugliflozin (ERT), a recently licensed anti-diabetic drug, has been widely reported. However, additional evidence-based data is required to ensure its safety. In particular, convincing evidence on the effects of ERT on renal function and cardiovascular outcomes is needed.

METHODS

We searched PubMed, Cochrane Library, Embase, and Web of Science for randomized placebo-controlled trials of ERT for T2DM published up to August 11, 2022. Cardiovascular events here mainly refer to acute myocardial infarction and angina pectoris (AP) (including stable AP and unstable AP). The estimated glomerular filtration rate (eGFR) was used to measure renal function. The pooled results are risk ratios (RRs) and 95% confidence intervals (CIs). Two participants worked independently to extract data.

RESULTS

We searched 1516 documents and filtered the titles, abstracts, and full text, 45 papers were left. Seven trials met the inclusion criteria and were ultimately included in the meta-analysis. The meta-analysis found that ERT reduced eGFR by 0.60 mL·min-1·1.733 m-2 (95% CI: -1.02--0.17, P = .006) in patients with T2DM when used for no more than 52 weeks and these differences were statistically significant. Compared with placebo, ERT did not increase the risk of acute myocardial infarction (RR 1.00, 95% CI: 0.83-1.20, P = .333) and AP (RR 0.85, 95% CI: 0.69-1.05, P = .497). However, the fact that these differences were not statistically significant.

CONCLUSION

This meta-analysis shows that ERT reduces eGFR over time in people with T2DM but is safe in the incidence of specific cardiovascular events.

Genetic predictors of lifelong medication-use patterns in cardiometabolic diseases

Little is known about the genetic determinants of medication use in preventing cardiometabolic diseases. Using the Finnish nationwide drug purchase registry with follow-up since 1995, we performed genome-wide association analyses of longitudinal patterns of medication use in hyperlipidemia, hypertension and type 2 diabetes in up to 193,933 individuals (55% women) in the FinnGen study. In meta-analyses of up to 567,671 individuals combining FinnGen with the Estonian Biobank and the UK Biobank, we discovered 333 independent loci (P < 5 × 10-9) associated with medication use. Fine-mapping revealed 494 95% credible sets associated with the total number of medication purchases, changes in medication combinations or treatment discontinuation, including 46 credible sets in 40 loci not associated with the underlying treatment targets. The polygenic risk scores (PRS) for cardiometabolic risk factors were strongly associated with the medication-use behavior. A medication-use enhanced multitrait PRS for coronary artery disease matched the performance of a risk factor-based multitrait coronary artery disease PRS in an independent sample (UK Biobank, n = 343,676). In summary, we demonstrate medication-based strategies for identifying cardiometabolic risk loci and provide genome-wide tools for preventing cardiovascular diseases.

Pharmacological Treatment of Type-2-Diabetes and Cardiovascular Comorbidities: Differences between Undocumented Migrants and Natives in Italy

Diabetes prevalence is growing worldwide, especially in some populations. Though migrations seem to contribute to the presence in host countries of a significant number of patients with diabetes and its comorbidities, very little is known about the health conditions of undocumented migrants. We retrospectively studied 838 patients with type 2 diabetes mellitus (T2DM), 425 Italians followed by the diabetes clinic of a university hospital, and 413 undocumented migrants receiving assistance from a non-governmental organization. We analyzed their demographic and clinical data together with the medications they were on. The prevalence of the use of specific classes of drugs was compared between undocumented migrants and Italians by fitting a Poisson regression model, and the results were reported as prevalence rate ratios (PRRs) with a 95% confidence interval. Undocumented migrants with T2DM received fewer medications for cardiovascular (CV) conditions (PRR: 0.68, 0.60 to 0.76) than Italians, after correcting for confounding factors. Only sulfonylureas were more frequently used in undocumented migrants. The causes of these differences are not completely clear, but social, cultural, and economic factors can have an important role. More efforts are needed to provide appropriate treatment of diabetes and its CV comorbidities to undocumented migrants.

Pharmacotherapy of type 2 diabetes: An update and future directions

Type 2 diabetes (T2D) is a widely prevalent disease with substantial economic and social impact for which multiple conventional and novel pharmacotherapies are currently available; however, the landscape of T2D treatment is constantly changing as new therapies emerge and the understanding of currently available agents deepens. This review aims to provide an updated summary of the pharmacotherapeutic approach to T2D. Each class of agents is presented by mechanism of action, details of administration, side effect profile, cost, and use in certain populations including heart failure, non-alcoholic fatty liver disease, obesity, chronic kidney disease, and older individuals. We also review targets of novel therapeutic T2D agent development. Finally, we outline an up-to-date treatment approach that starts with identification of an individualized goal for glycemic control then selection, initiation, and further intensification of a personalized therapeutic plan for T2D.

Efficacy and safety of dorzagliatin for type 2 diabetes mellitus: A meta-analysis and trial sequential analysis

Objective

To evaluate the efficacy and safety of dorzagliatin in the treatment of type 2 diabetes mellitus (T2DM) by using meta-analysis and trial sequential analysis (TSA).

Method

Search for clinical trials of dorzagliatin for T2DM in eight databases, with a time limit of build to July 2022. The included studies that met the requirements were carried out for meta-analysis and TSA.

Results

In terms of efficacy endpoints, meta-analysis showed that dorzagliatin decreased glycated hemoglobin A1c(HbA1c) [mean difference (MD) -0.65%, 95% confidence interval (CI) -0.76 ~ -0.54, P < 0.00001], fasting plasma glucose (FPG) (MD -9.22 mg/dL, 95% CI -9.99 ~ -8.44, P < 0.00001), 2 h postprandial glucose (2h-PPG) (MD -48.70 mg/dL, 95% CI -55.45 ~ -41.96, P < 0.00001), homeostasis model assessment 2 of insulin resistance (HOMA2-IR) (MD -0.07, 95% CI -0.14 ~ -0.01, P = 0.03) and increased homeostasis model assessment 2 of ß-cells function (HOMA2-β) (MD 2.69, 95% CI 1.06 ~ 4.31, P = 0.001) compared with placebo. And TSA revealed that the benefits observed for the current information set were conclusive, except for HOMA2-IR. In comparison with placebo, dorzagliatin increased triglyceride(TG) (MD 0.43 mmol/L, 95% CI 0.30 ~ 0.56, P < 0.00001), total cholesterol (TC) (MD 0.13 mmol/L, 95% CI 0.05 ~ 0.21, P = 0.001), body weight (MD 0.38 kg, 95% CI 0.12-0.63, P = 0.004) and body mass index (BMI) (MD 0.14 kg/m², 95% CI 0.05-0.24, P = 0.003), while low density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), systolic blood pressure (SBP) and diastolic blood pressure (DBP) were comparable. And TSA demonstrated that TG, TC, body weight, and BMI were conclusive. In terms of safety endpoints, dorzagliatin increased total adverse events (AEs) [risk ratio (RR) 1.56, 95% CI 1.06 ~ 2.30, P = 0.03], while serious AEs, hyperlipidemia, and hypoglycaemia were all comparable. And TSA indicated that the results need to be confirmed by additional studies. Harbord regression showed no publication bias.

Conclusion

Dorzagliatin was effective in lowering glycemia, reducing insulin resistance and improving islet ß-cells function without affecting blood pressure, LDL-C, and HDL-C. Although dorzagliatin caused a mild increase in TG and TC, it did not increase the incidence of hyperlipidemia, and the small increases in body weight and BMI were not clinically significant enough. In terms of safety, the total AEs caused by dorzagliatin may be a cumulative effect of single AEs, with no drug-related adverse event being reported at a higher incidence than placebo alone. Dorzagliatin's serious AEs, hyperlipidemia, and hypoglycemia are comparable to that of placebo, and dorzagliatin has a good safety profile.

Systematic review registration

https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=371802 identifier: CRD42022371802.

Analysis of missense SNPs in the SLC47A1 and SLC47A2 genes affecting the pharmacokinetics of metformin: Computational approach

Background

Metformin as an anti-hyperglycaemic drug is commonly used for the treatment of type 2 diabetes mellitus (T2DM). The metformin response is variable due to the interindividual variation of pharmacokinetics which is based on strong genetic background. MATE1 and MATE2 proteins are significantly implicated in the pharmacokinetics of metformin. Missense SNPs with high risk of pathogenicity are expected to affect response to metformin via pharmacokinetics. Therefore, the aim of the current study is to determine the effects of missense SNPs in the SLC47A1 and SLC47A2 genes. The structural and functional consequences of all known SLC47A1 and SLC47A2 missense SNPs of the human MATE1 and MATE2 proteins were identified by various bioinformatics methods (SIFT, PhD-SNP, PolyPhen-2, PROVEAN, PMut, MUpro, I-Mutant 3.0, COACH, RaptorX Binding, ConSurf, STRING).

Results

The SLC47A1 variants P186T, L116P and the SLC47A2 variants I158N, L112P, V118G exhibited ΔΔG values less than − 1 kcal/mol, and these variants are considered to disrupt the structure and function of MATE1 and MATE2 proteins. SLC47A1 R118Q and SLC47A2 Y273C, V118G may significantly disturb protein function and transporting activities according to the analysis of ligand-binding regions.

Conclusion

It is suggested that high-risk deleterious missense SNPs may mediate the pharmacokinetics of metformin and may be associated with altered tissue distribution, renal clearance and metformin toxicity. We suppose that our results might serve as potential targets for the studies composed of the development of potential diagnostic and therapeutic strategies based on the relationship between mutations and metformin response.

KCNQ1 variant rs163184 is a potential biomarker of glycemic response to exenatide

Aim: To examine the association between variant rs163184 in the type 2 diabetes mellitus (T2DM) susceptibility gene KCNQ1 and exenatide glycemic response in the Chinese population. Patients & methods: We included 100 T2DM patients from the CONFIDENCE study and investigated the association between rs163184 and glycemic response to exenatide, by using a multivariate linear model with adjustment for baseline glucose status and other covariates. Results: The G allele of rs163184 was associated with a 0.34% (p = 0.016) lower glycosylated hemoglobin reduction after 48 weeks of exenatide treatment. Similar significant associations were observed when glycemic response to exenatide was evaluated with fasting blood glucose or postprandial blood glucose reduction. Conclusion: We found that rs163184 in the gene KCNQ1 was associated with reduced glycemic response to exenatide in T2DM patients. The effect size observed in this study was large enough to be considered clinically relevant in stratified medicine.

The management of diabetes mellitus by mangiferin: advances and prospects

Diabetes mellitus has become one of the most challenging public health problems today. There are still various deficiencies that remain in existing therapeutic drugs. With increasing prevalence and mortality rates, more effective therapeutic agents are required for treatment clinically. As a kind of polyphenol and as a natural product, mangiferin has numerous pharmacological and excellent effects. In this review, the underlying mechanisms of mangiferin on diabetes mellitus and complications will be summarized. Moreover, mangiferin belongs to the BSC IV class and the clinical application and development of mangiferin are limited due to its poor aqueous solubility and fat solubility as well as low bioavailability. Our review also elaborated on improving the solubility of mangiferin by changing the dosage form and introduced the existing results, which hope to provide useful reference for mangiferin for further treating diabetes. In conclusion, mangiferin might be a potential adjuvant therapy for the treatment of diabetes mellitus and complications in the future.

Effects of the TCF7L2 and KCNQ1 common variant on sulfonylurea response in type 2 diabetes mellitus patients: a preliminary pharmacogenetic study

Background

Type 2 diabetes mellitus (T2DM) is a common chronic condition characterized by high blood glucose levels which is caused by genetic and environmental factors. Currently, pharmacogenomics (PGx) is anticipated to enable the development of personalized treatment in a wide range of health issues. Sulfonylureas (SFUs) are among the oral anti-diabetic drugs that are very popular due to their low cost. Genetic variants in transcription factor 7 like 2 (TCF7L2) and potassium voltage-gated channel subfamily Q member 1 (KCNQ1) have been reported for altered therapeutic response to sulfonylurea. The aim of the present study is to evaluate any association between common genetic variant of the TCF7L2 and KCNQ1 (rs7903146 and rs2237892, respectively) and the response to sulfonylurea in a group of Iranian patients for the first time.

Methods

Genotyping was carried out in 30 T2DM patients who received sulfonylurea treatment for more than two months in addition to previous medication using the Sanger sequencing method.

Results

In 30 T2DM patients who received SFUs treatment, 60%, 33.3% and 6.7% had CC, CT and TT genotypes, respectively. After treatment, adjusted fasting blood sugar (FBS) mean reduction level in CT and TT carriers was lower than CC carriers. Adjusted hemoglobin A1c (HbA1c) mean reduction level was also lower in CT and TT compared with CC carriers, but, none of these differences were statistically significant. Genotype frequencies of TT, CT and CC genotypes of rs2237892 variant of KCNQ1 gene were 0 (0%), 3 (10%) and 27 (90%) respectively. Patients with CT and CC genotypes of rs2237892 variant had also similar changes in FBS (P=0.200) and HbA1c (P=0.436) after treatment with SFUs.

Conclusions

Genotypes of TCF7L2 and KCNQ1 common variant did not show any impact on the treatment response among T2DM patients receiving SFUs.

In vivo and in vitro studies of Danzhi Jiangtang capsules against diabetic cardiomyopathy via TLR4/MyD88/NF-κB signaling pathway

Objectives

Danzhi Jiangtang capsule (DJC) is widely used for preventing and treating diabetic cardiomyopathy (DCM). However, the underlying mechanisms of the anti-inflammatory and antiapoptotic activities are unclear.

Methods

In the in vivo diabetic cardiomyopathy rat model, cardiac function was measured through echocardiography, histological changes in the myocardium were visualized using HE staining, and cardiomyocyte apoptosis was detected using TUNEL. The serum levels of anti-inflammatory cytokines were detected using ELISA. Finally, TLR4, MyD88, and NF-κB mRNA expressions were analyzed using RT-qPCR. In the in vitro experiments, the apoptosis rate of the H9c2 cells was detected using FCM; moreover, TLR4, MyD88 and NF-κB mRNA expressions were measured using RT-qPCR and related protein levels were investigated using Western blotting.

Results

In vivo, DJC effectively improved cardiac function, alleviated the pathological changes, and reduced the apoptosis rate. Moreover, DJC reduced TNF-α, IL-1β, and IL-6 activities, with significant inhibition of the TLR4, MyD88 and NF-κB p65 mRNA expression. Moreover, in vitro, DJC effectively inhibited high-glucose-induced H9c2 apoptosis-an effect similar to that for TAK242. Finally, both the DJC and TAK242 considerably reduced TLR4, MyD88, NF-κB, Bax, and caspase-3 protein expression but increased that of BCL-2.

Conclusions

DJC prevented the overactivation of the TLR4/MyD88/NF-κB signaling pathway and regulate cardiomyocyte apoptosis against DCM.

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).

A pharmacogenetic pilot study of CYP2C9 common genetic variant and sulfonylureas therapeutic response in type 2 diabetes mellitus patients

Background

Type 2 diabetes mellitus (T2DM) is a chronic metabolic disease that is associated with elevated blood glucose levels. Sulfonylureas (SFUs) are the most widely used among the oral antidiabetic drugs that are highly metabolized by cytochrome P450 family 2 subfamily C member 9 (CYP2C9). The CYP2C9 has been shown to be associated with a better glycemic response to SFUs and a lower treatment failure rate. The aim of the present study was to assess the influence of the CYP2C9 rs1067910 gene variant on the SFUs response in a group of Iranian patients for the first time.

Methods

Blood samples were taken from 30 patients with T2DM under sulfonylurea treatment. DNA extraction was performed using Salting out method, and then genotyping was performed by polymerase chain reaction (PCR) followed by Sanger sequencing.

Results

There was no significant difference in the fasting blood sugar (FBS) between T2DM patients with different genotypes before and after the treatment with SFUs (P = 0.073 and P = 0.893, respectively). Although HbA1c was significantly different among AA, CA and CC carriers before (P = 0.001) and after (P = 0.018) treatment, no significant change was observed after treatment in all three groups.

Conclusions

In the present study based on only 30 samples in pilot survey, it is shown that the therapeutic response to SFUs was not related to rs1057910 CYP2C9 variant.

PPARD rs2016520 (T/C) and NOS1AP rs12742393 (A/C) polymorphisms affect therapeutic efficacy of nateglinide in Chinese patients with type 2 diabetes mellitus

Background

Genetic polymorphisms in the PPARD and NOS1AP is associated with type 2 diabetes mellitus (T2DM); however, there is no evidence about its impact on the therapeutic efficacy of nateglinide. This study was designed to investigate a potential association of PPARD rs2016520 (T/C) and NOS1AP rs12742393 (A/C) polymorphisms with efficacy of nateglinide in newly diagnosed Chinese patients with type 2 diabetes mellitus (T2DM).

Methods

Sixty patients with newly diagnosed T2DM were enrolled to identify PPARD rs2016520 and NOS1AP rs12742393 genotypes using the polymerase chain reaction-restriction fragment length polymorphism assay (PCR–RFLP). All subjects were treated with nateglinide (360 mg/day) for 8 weeks. Anthropometric measurements, clinical laboratory tests were obtained at baseline and after 8 weeks of nateglinide treatment.

Results

After nateglinide treatment for 8 consecutive weeks, patients with at least one C allele of PPARD rs2016520 showed a smaller decrease in post plasma glucose (PPG), homeostasis model assessment for beta cell function (HOMA-B) than those with the TT genotype did (P < 0.05). In patients with the AA genotype of NOS1AP rs12742393, the drug showed better efficacy with respect to levels of fasting plasma glucose (FPG), fasting serum insulin (FINS), HOMA-B and homeostasis model assessment for insulin resistance (HOMA-IR) than in patients with the AC + CC genotype (P < 0.05). NOS1AP rs12742393 genotype distribution and allele frequency were associated with responsiveness of nateglinide treatment (P < 0.05).

Conclusions

The PPARD rs2016520 and NOS1AP rs12742393 polymorphisms were associated with nateglinide monotherapy efficacy in Chinese patients with newly diagnosed T2DM.

Trial registration

Chinese Clinical Trial Register ChiCTR13003536, date of registration: May 14, 2013.

Prognostic factors for the carbohydrate metabolism normalization in patients with type 2 diabetes mellitus and obesity using liraglutide 3.0 mg per day

Background. Glucagon-like peptide-1 receptor agonists (GLP-1 RA) are innovative drugs that effectively reduce glycemic levels and overweight in patients with type 2 diabetes mellitus (T2DM). However, the criteria for predicting the hypoglycemic effect of this group of drugs have not been practically defined. Aim. To assess the factors contributing to the achievement the glycemia normalization in patients with diabetes mellitus and obesity by adding to antihyperglycemic therapy (AT) a drug from the GLP-1 RA group liraglutide 3.0 mg per day. Materials and methods. A single-center, prospective, non-randomized study was provided. The objects of the study were patients with T2DM and obesity (n=22). Liraglutide 3.0 mg per day was added to the current AT of patients. Initially, the parameters of carbohydrate metabolism, hormones of the incretin system on an empty stomach and during the mixed-meal test, insulin resistance using the euglycemic hyperinsulinemic clamp test, and body composition were studied. After 9 months of therapy, all studies were repeated and a search for possible predictors of the carbohydrate metabolism normalization was made. Results. The body mass index of patients decreased from 42.4 [37.7; 45.0] to 35.9 [33.0; 40.9] kg/m2. Fasting blood glucose and glycated hemoglobin levels decreased from 9.02 [7.40; 11.37] mmol/L and 7.85 [7.43; 8.65]% up to 5.90 [5.12; 6.18] mmol/L and 6.40 [5.90; 6.60]%, respectively. 14 (63.6%) patients reached normoglycemia. Insulin resistance according to the clamp test did not change over the study. Basal concentrations of oxyntomodulin, glycentin and the area under the GLP-1, oxyntomodulin, glycentin curve significantly decreased 9 months after liraglutide administration. The prognostic marker of the achievement of normoglycemia during therapy with liraglutide 3.0 mg/day is the level of endogenous GLP-15.5 pmol/L before the appointment of arGPP-1 therapy. Conclusion. The concentration of endogenous GLP-1 before the appointment of liraglutide therapy at a dose of 3.0 mg per day can be used for prediction the drug hypoglycemic effect and achieving normoglycemia possibility.

Diabetes: discovery of insulin, genetic, epigenetic and viral infection mediated regulation

Diabetes mellitus, commonly referred to as diabetes, is a combination of many metabolic diseases. Insulin deficiency in our body is the main cause of diabetes. Insulin is one of the most well studied proteins, yet the genesis of its discovery was not getting much attention so far. Nevertheless, the history of the discovery of insulin is an exemplary of solving observational and scientific riddles, drudgery, patience and even professional turmoil. It is an inspiration for all medical personnel and scientists who are practising in the field of molecular medicine. Additionally, the genetic and epigenetic regulation of different types of diabetes needs to be addressed because of the widespread nature of the disease. Diabetes not only involves genetic predisposition but environmental factors, lifestyle etc. can be the major contributor for its inception. Nonetheless, viral infections at an early age are also found to trigger the onset of type I diabetes. In this review article, the history of the discovery of insulin is detailed along with the justification for the genetic and epigenetic regulatory mechanisms of diabetes and explained how viral infections can also trigger the onset of diabetes.

The Link between Type 2 Diabetes Mellitus and the Polymorphisms of Glutathione-Metabolizing Genes Suggests a New Hypothesis Explaining Disease Initiation and Progression

The present study investigated whether type 2 diabetes (T2D) is associated with polymorphisms of genes encoding glutathione-metabolizing enzymes such as glutathione synthetase (GSS) and gamma-glutamyl transferase 7 (GGT7). A total of 3198 unrelated Russian subjects including 1572 T2D patients and 1626 healthy subjects were enrolled. Single nucleotide polymorphisms (SNPs) of the GSS and GGT7 genes were genotyped using the MassArray-4 system. We found that the GSS and GGT7 gene polymorphisms alone and in combinations are associated with T2D risk regardless of sex, age, and body mass index, as well as correlated with plasma glutathione, hydrogen peroxide, and fasting blood glucose levels. Polymorphisms of GSS (rs13041792) and GGT7 (rs6119534 and rs11546155) genes were associated with the tissue-specific expression of genes involved in unfolded protein response and the regulation of proteostasis. Transcriptome-wide association analysis has shown that the pancreatic expression of some of these genes such as EDEM2, MYH7B, MAP1LC3A, and CPNE1 is linked to the genetic risk of T2D. A comprehensive analysis of the data allowed proposing a new hypothesis for the etiology of type 2 diabetes that endogenous glutathione deficiency might be a key condition responsible for the impaired folding of proinsulin which triggered an unfolded protein response, ultimately leading to beta-cell apoptosis and disease development.

Personalized approach for type 2 diabetes pharmacotherapy: where are we and where do we need to be?

INTRODUCTION

Cluster analysis has identified distinct groups of type 2 diabetes (T2D) subjects with distinct metabolic characteristics. Thus, personalizing pharmacologic therapy to individual phenotypic and pathophysiologic characteristics has potential to improve metabolic control and reduce risk of microvascular and macrovascular complications.

AREAS COVERED

The authors review the classification of T2D, genetic markers, pathophysiology and natural history of T2D, the ABCDE approach to therapy, the ADA/EASD stepwise approach to therapy, available antidiabetic agents, and provide a more rational therapeutic approach based upon pathophysiology and cardiovascular and renal outcome trials.

EXPERT OPINION

Although insulin resistance is the earliest detectable abnormality, overt T2D does not occur in the absence of progressive beta cell failure. Because of the complex etiology of T2D (Ominous Octet), initiation of therapy with combined agents that (i) target both insulin resistance and beta cell dysfunction and (ii) prevent macrovascular, as well as microvascular, complications will be required. The ratio of C-peptide at 120 minutes (OGTT) to baseline C-peptide predicts with high sensitivity who will respond to metformin, the response to glucose-lowering agents and provides a useful tool to guide optimal glucose lowering therapy.

Multi-omics profiling: the way towards precision medicine in metabolic diseases

Metabolic diseases including type 2 diabetes mellitus (T2DM), non-alcoholic fatty liver disease (NAFLD), and metabolic syndrome (MetS) are alarming health burdens around the world, while therapies for these diseases are far from satisfying as their etiologies are not completely clear yet. T2DM, NAFLD, and MetS are all complex and multifactorial metabolic disorders based on the interactions between genetics and environment. Omics studies such as genetics, transcriptomics, epigenetics, proteomics, and metabolomics are all promising approaches in accurately characterizing these diseases. And the most effective treatments for individuals can be achieved via omics pathways, which is the theme of precision medicine. In this review, we summarized the multi-omics studies of T2DM, NAFLD, and MetS in recent years, provided a theoretical basis for their pathogenesis and the effective prevention and treatment, and highlighted the biomarkers and future strategies for precision medicine.

Genetics of macrovascular complications in type 2 diabetes

Type 2 diabetes mellitus (T2DM) is a metabolic disorder that currently affects more than 400 million worldwide and is projected to cause 552 million cases by the year 2030. Long-term vascular complications, such as coronary artery disease, myocardial infarction, stroke, are the leading causes of morbidity and mortality among diabetic patients. The recent advances in genome-wide technologies have given a powerful impetus to the study of risk markers for multifactorial diseases. To date, the role of genetic and epigenetic factors in modulating susceptibility to T2DM and its vascular complications is being successfully studied that provides the accumulation of genomic knowledge. In the future, this will provide an opportunity to reveal the pathogenetic pathways in the development of the disease and allow to predict the macrovascular complications in T2DM patients. This review is focused on the evidence of the role of genetic variants and epigenetic changes in the development of macrovascular pathology in diabetic patients.

Treatment of type 2 diabetes: challenges, hopes, and anticipated successes

Despite the successful development of new therapies for the treatment of type 2 diabetes, such as glucagon-like peptide-1 (GLP-1) receptor agonists and sodium-glucose cotransporter-2 inhibitors, the search for novel treatment options that can provide better glycaemic control and at reduce complications is a continuous effort. The present Review aims to present an overview of novel targets and mechanisms and focuses on glucose-lowering effects guiding this search and developments. We discuss not only novel developments of insulin therapy (eg, so-called smart insulin preparation with a glucose-dependent mode of action), but also a group of drug classes for which extensive research efforts have not been rewarded with obvious clinical impact. We discuss the potential clinical use of the salutary adipokine adiponectin and the hepatokine fibroblast growth factor (FGF) 21, among others. A GLP-1 peptide receptor agonist (semaglutide) is now available for oral absorption, and small molecules activating GLP-1 receptors appear on the horizon. Bariatric surgery and its accompanying changes in the gut hormonal milieu offer a background for unimolecular peptides interacting with two or more receptors (for GLP-1, glucose-dependent insulinotropic polypeptide, glucagon, and peptide YY) and provide more substantial glycaemic control and bodyweight reduction compared with selective GLP-1 receptor agonists. These and additional approaches will help expand the toolbox of effective medications needed for optimising the treatment of well delineated subgroups of type 2 diabetes or help develop personalised approaches for glucose-lowering drugs based on individual characteristics of our patients.

Canagliflozin for Prevention of Cardiovascular and Renal Outcomes in type2 Diabetes: A Systematic Review and Meta-analysis of Randomized Controlled Trials

Objective: We aimed to evaluate the efficacy of canagliflozin for the treatment of specific cardiovascular and renal outcomes in Type 2 diabetes mellitus (T2DM) patients by means of a systematic review and meta-analysis.

Methods: We performed comprehensive searches of PubMed, the Cochrane Library, and Embase for randomized, placebo-controlled trials of the treatment of T2DM with canagliflozin that were published to 28 September 2020. The cardiovascular outcomes recorded were cardiovascular mortality, heart failure, myocardial infarction, and stroke. The renal composite outcomes recorded were end-stage renal disease (ESRD), renal death. The data for the principal cardiovascular outcomes, ESRD, and renal death were pooled and expressed as Hazard ratios (HRs) with 95% confidence intervals (CIs). Two reviewers independently selected the trials and extracted the data.

Results: We identified a total of 1,741 publications, leaving 96 for their titles, abstracts and full-text review. Of these, 10 trials met the inclusion criteria and were finally included in our meta-analysis. The meta-analysis showed that canagliflozin significantly reduced the risk of heart failure in T2DM by 36% (HR 0.64, 95% CI 0.53 to 0.77, p = 0.000). The effects of canagliflozin on non-fatal myocardial infarction or non-fatal stroke (HR 0.84, 95% CI: 0.76 to 0.93, p = 0.001), cardiovascular mortality (HR 0.84, 95% CI 0.72 to 0.97, p = 0.021), and myocardial infarction (HR 0.84, 95% CI 0.70 to 1.00, p = 0.045) in patients with T2DM were relatively small, reducing the risks by 16%. In addition, canagliflozin reduced the risk of stroke in T2DM patients by 13% (HR 0.87, 95% CI 0.71 to 1.06, p = 0.166). Moreover, canagliflozin significantly reduced the risk of the composite renal event of ESRD or renal death by 36% (HR 0.64, 95% CI 0.54 to 0.75, p = 0.000).

Conclusion: This meta-analysis suggests that canagliflozin protects against cardiovascular and renal outcomes in patients with T2DM.

Systematic Review Registration: [https://www.crd.york.ac.uk/prospero], identifier [CRD42020210315]

Transporters, TBC1D4, and ARID5B Variants to Explain Glycated Hemoglobin Variability in Patients with Type 2 Diabetes

INTRODUCTION

Genetic variants could aid in predicting antidiabetic drug response by associating them with markers of glucose control, such as glycated hemoglobin (HbA1c). However, pharmacogenetic implementation for antidiabetics is still under development, as the list of actionable markers is being populated and validated. This study explores potential associations between genetic variants and plasma levels of HbA1c in 100 patients under treatment with metformin.

METHODS

HbA1c was measured in a clinical chemistry analyzer (Roche), genotyping was performed in an Illumina-GSA array and data were analyzed using PLINK. Association and prediction models were developed using R and a 10-fold cross-validation approach.

RESULTS

We identified genetic variants on SLC47A1, SLC28A1, ABCG2, TBC1D4, and ARID5B that can explain up to 55% of the interindividual variability of HbA1c plasma levels in diabetic patients under treatment. Variants on SLC47A1, SLC28A1, and ABCG2 likely impact the pharmacokinetics (PK) of metformin, while the role of the two latter can be related to insulin resistance and regulation of adipogenesis.

CONCLUSIONS

Our results confirm previous genetic associations and point to previously unassociated gene variants for metformin PK and glucose control.

Precision Health Care Elements, Definitions, and Strategies for Patients with Diabetes: A Literature Review

Diabetes is a prevalent disease with a high risk of complications. The number of people with diabetes worldwide was reported to increase every year. However, new integrated individualized health care related to diabetes is insufficiently developed. Purpose: The objective of this study was to conduct a literature review and discover precision health care elements, definitions, and strategies. Methods: This study involved a 2-stage process. The first stage comprised a systematic literature search, evidence evaluation, and article extraction. The second stage involved discovering precision health care elements and defining and developing strategies for the management of patients with diabetes. Results: Of 1337 articles, we selected 35 relevant articles for identifying elements and definitions of precision health care for diabetes, including personalized genetic or lifestyle factors, biodata- or evidence-based practice, glycemic target, patient preferences, glycemic control, interdisciplinary collaboration practice, self-management, and patient priority direct care. Moreover, strategies were developed to apply precision health care for diabetes treatment based on eight elements. Conclusions: We discovered precision health care elements and defined and developed strategies of precision health care for patients with diabetes. precision health care is based on team foundation, personalized glycemic target, and control as well as patient preferences and priority, thus providing references for future research and clinical practice.

Therapeutic Dilemma in personalized medicine

The practice of medicine depends over a long time on identifying therapies that target an entire population. The increase in scientific knowledge over the years has led to the gradual change towards individualization and personalization of drug therapy. The hope of this change is to achieve a better clinical response to given medications and reduction of their adverse effects. Tailoring of medicine on the road of personalized medicine considers molecular and genetic mapping of the individual. However, many factors still impede the smooth application of personalized medicine and represent challenges or limitations in its achievement. In this article, we put some clinical examples that show dilemmas in the application of personalized medicine such as opioids in pain control, fluoropyrimidines in malignancy, clopidogrel as antiplatelet therapy and oral hypoglycemic drugs in Type2 diabetes in adults. Shaping the future of medicine through the application of personalized medicine for a particular patient needs to put into consideration many factors such as patient's genetic makeup and life style, pathology of the disease and dynamic changes in its course as well as interactions between administered drugs and their effects on metabolizing enzymes. We hope in the coming years, the personalized medicine will foster changes in health care system in the way not only to treat patients but also to prevent diseases.

The Pro12Ala polymorphism of PPARγ2 modulates beta cell function and failure to oral glucose-lowering drugs in patients with type 2 diabetes

BACKGROUND

We evaluate whether the Pro12Ala polymorphism of peroxisome proliferator-activated receptor γ2 (PPARγ2) has a role in the progression of diabetes by modulating the occurrence of treatment failure to glucose-lowering drugs.

METHODS

We studied 215 patients with type 2 diabetes participating in the Thiazolidinediones Or Sulphonylureas and Cardiovascular Accidents Intervention Trial study. All participants were insufficiently controlled (glycated haemoglobin [HbA_1c ] 7.0%-9.0%) with metformin 2 g/day and were randomly allocated to add-on pioglitazone or a sulfonylurea. Treatment failure was defined as HbA_1c ≥8% on two consecutive visits, 3 months apart.

RESULTS

Carriers or non-carriers of the polymorphism had similar age, body mass index, and diabetes duration. Ala carriers had lower fasting plasma insulin, better insulin sensitivity (Homeostasis Model Assessment [HOMA]2-%S), and worse beta cell secretion (HOMA2-%B) than non-carriers. During 24 months of follow-up, 32.5% among the Ala carriers and 8.6% among non-carriers (P < 0.001) developed treatment failure with a cumulative incidence of 18.6 vs 4.6/100 person-years. Those patients who developed treatment failure were older, had a younger age at diabetes diagnosis (48 ± 10 vs 52 ± 7 years; P = 0.032), higher HbA_1c (8.1 ± 0.5 vs 7.7 ± 0.5%; P < 0.001), and lower HOMA2-%B (30 ± 12 vs 46 ± 29; P = 0.015) at study entry, as compared to those who did not develop treatment failure. At multivariate analysis, the Pro12Ala polymorphism was significantly associated with treatment failure (hazard ratio [HR] 4.45; 95% confidence interval [CI] 1.79-11.1; P < 0.001); HbA_1c at study entry was the other independent predictor of failure in this study population.

CONCLUSION

The Pro12Ala polymorphism is associated with a greater insulin sensitivity, reduced beta cell function and a substantially increased risk of treatment failure.

Silencing of the tRNA Modification Enzyme Cdkal1 Effects Functional Insulin Synthesis in NIT-1 Cells: tRNALys3 Lacking ms2- (ms2t6A37) is Unable to Establish Sufficient Anticodon:Codon Interactions to Decode the Wobble Codon AAG

Human Genome Wide Association Studies found a significant risk of Type 2 Diabetes Mellitus (T2DM) in single nucleotide polymorphisms in the cdkal1 gene. The cdkal1 gene is remote from the insulin gene and with the surprising function of a specific tRNA modification. Population studies and case control studies acquired evidences of the connection between Cdkal1 protein and insulin production over the years. To obtain biochemical proofs directly linking potential SNPs to their roles in insulin production and availability is challenging, but the development of Cdkal1 knock out mice and knock out cell lines made it possible to extend our knowledge towards therapeutic field of diabetic research. Supporting the evidences, here we show that knock down of the cdkal1 gene using small interfering and short hairpin RNA in the NIT-1 cell line, a β-cell line inducible for insulin resulted in reduced levels of cdkal1 and mature insulin mRNAs, increased the level of precursor insulin mRNA, decreased Cdkal1 and insulin proteins, and diminished modification of tRNA^Lys3 from t⁶A₃₇ to ms²t⁶A₃₇, the specified function of Cdkal1. tRNA^Lys3 lacking ms²- is incapable of establishing sufficient hydrogen bonding energy and hydrophobic stabilization to decode the wobble codon AAG.

Incretin Hormones in Obesity and Related Cardiometabolic Disorders: The Clinical Perspective

The prevalence of obesity continues to grow rapidly worldwide, posing many public health challenges of the 21st century. Obese subjects are at major risk for serious diet-related noncommunicable diseases, including type 2 diabetes mellitus, cardiovascular disease, and non-alcoholic fatty liver disease. Understanding the mechanisms underlying obesity pathogenesis is needed for the development of effective treatment strategies. Dysregulation of incretin secretion and actions has been observed in obesity and related metabolic disorders; therefore, incretin-based therapies have been developed to provide new therapeutic options. Incretin mimetics present glucose-lowering properties, together with a reduction of appetite and food intake, resulting in weight loss. In this review, we describe the physiology of two known incretins—glucose-dependent insulinotropic polypeptide (GIP) and glucagon-like peptide-1 (GLP-1), and their role in obesity and related cardiometabolic disorders. We also focus on the available and incoming incretin-based medications that can be used in the treatment of the above-mentioned conditions.

Plant Extracts for Type 2 Diabetes: From Traditional Medicine to Modern Drug Discovery

Type 2 diabetes mellitus (T2DM) is one of the largest public health problems worldwide. Insulin resistance-related metabolic dysfunction and chronic hyperglycemia result in devastating complications and poor prognosis. Even though there are many conventional drugs such as metformin (MET), Thiazolidinediones (TZDs), sulfonylureas (SUF), dipeptidyl peptidase 4 (DPP-4) inhibitors, glucagon like peptide 1 (GLP-1) and sodium-glucose cotransporter-2 (SGLT-2) inhibitors, side effects still exist. As numerous plant extracts with antidiabetic effects have been widely reported, they have the potential to be a great therapeutic agent for type 2 diabetes with less side effects. In this study, sixty-five recent studies regarding plant extracts that alleviate type 2 diabetes were reviewed. Plant extracts regulated blood glucose through the phosphoinositide 3-kinase (PI3K)/protein kinase B (Akt) pathway. The anti-inflammatory and antioxidant properties of plant extracts suppressed c-Jun amino terminal kinase (JNK) and nuclear factor kappa B (NF-κB) pathways, which induce insulin resistance. Lipogenesis and fatty acid oxidation, which are also associated with insulin resistance, are regulated by AMP-activated protein kinase (AMPK) activation. This review focuses on discovering plant extracts that alleviate type 2 diabetes and exploring its therapeutic mechanisms.

Evaluating the Evidence behind the Novel Strategy of Early Combination from Vision to Implementation

Type 2 diabetes mellitus (T2DM) is a complex and progressive chronic disease characterised by elevating hyperglycaemia and associated need to gradually intensify therapy in order to achieve and maintain glycaemic control. Treating hyperglycaemia with sequential therapy is proposed to allow holistic assessment of the efficacy and risk-to-benefit ratio of each added component. However, there is an array of evidence supporting the scientific rationale for using synergistic, earlier, modern drug combinations to achieve glycaemic goals, delay the deterioration of glycaemic control, and, therefore, potentially preserve or slow down the declining β-cell function. Additionally, implementation of early combination(s) may lead to opportunities to combat clinical inertia and other hurdles to optimised disease management outcomes. This review aims to discuss the latest empirical evidence for long-term clinical benefits of this novel strategy of early combination in people with newly diagnosed T2DM versus the current widely-implemented treatment paradigm, which focuses on control of hyperglycaemia using lifestyle interventions followed by sequentially intensified (mostly metformin-based) monotherapy. The recent reported Vildagliptin Efficacy in combination with metfoRmin For earlY treatment of T2DM (VERIFY) study results have provided significant new evidence confirming long-term glycaemic durability and tolerability of a specific early combination in the management of newly diagnosed, treatment-naïve patients worldwide. These results have also contributed to changes in clinical treatment guidelines and standards of care while clinical implementation and individualised treatment decisions based on VERIFY results might face barriers beyond the existing scientific evidence.

[The pharmacogenetics of hypoglycemia and the glycemic variability at the patients ith type 2 diabetes mellitus]

AIM

To investigate the link between the hypoglycemia (registrated accurately by the professional Continuous Glucose Monitoring CGM; severe hypoglycemia at home) and the hetero-/homozygote carriage of single nucleotide polymorphisms (SNP) of cytochrome systems geneCYP2C9(rs1799853CYP2C9*2 иrs1057910CYP2C9*3) at the patients with Type 2 Diabetes Mellitus (T2DM) used sulphonylurea (SU).

MATERIALS AND METHODS

In Study Case-Control 120 T2DM-SU-patients genotyped by SNPs of geneCYP2C9(using PCR-RT) had been done the professional CGM (System iPro2, Medtronic) recorded Time in Range of Hypoglycemia (TIR-HYPO), level of Minimal CGM-hypoglycemia (MinGl) and standard CGM-parameters of Glycemic Variability. Severe hypoglycemia at home was recorded from visit to visit. The odds ratio (OR) of metabolic disturbances had been assessed for carriage SNPs in comparison with wide alleles.

RESULTS

The Study established that carriage of SNPsrs1799853andrs1057910geneCYP2C9at T2DM-SU-patients associated with rising of Glycemic Variability and frequency of CGM-hypoglycemia (MinGl decreasing, increasing of TIR-HYPO and number of Glycemia Excursion 4 mmol/L/h), as well as increasing severe hypoglycemia at home (p0.05). Thus, OR at the carriage ofrs1799853andrs1057910respectively equaled: for CGM-hypoglycemia 7.78 (3.0220.01) and 5.80 (0.23145.87); number of Glycemia Excursion 4 mmol/L/h 5.76 (2.2914.43) and 4.44 (1.4313.76); MinGl3.9 mmol/L 4.39 (1.7910.75) and 6.26 (1.8421.30); CV40% (vs30%) 3.63 (1.0412.62) and 15.22 (0.59393.94);p0.05.

CONCLUSION

At the real clinical practice the assessment of carriage of SNPs of geneCYP2C9before inclusion of SU to glucose-lowering scheme of T2DM-therapy it necessary to carry out for the detecting patients with a higher risk of hypoglycemia and rising of Glycemic Variability.

The Need for Precision Medicine to be Applied to Diabetes

Precision medicine refers to the tailoring of medical treatment for an individual based on large amounts of biologic and extrinsic data. The fast advancing fields of molecular biology, gene sequencing, machine learning, and other technologies enable precision medicine to utilize this detailed information to enhance clinical management decision-making for an individual in the real time of the disease course. Traditional clinical decision making is based on reacting to a relatively limited number of phenotypes that are determined by history, physical examination, and conventional lab tests. Precision medicine depends on highly detailed profiling of the patient's genetic, morphologic, and metabolic makeup. The precision medicine approach can be applied to individuals with diabetes to select treatments most likely to offer benefit and least likely to cause side effects, offering prospects of improved clinical outcomes and economic costs savings over current empiric practices. As genetic, metabolomic, immunologic, and other sophisticated testing becomes less expensive and more widespread in the medical record, it is expected that precision medicine will become increasingly applied to diabetes care.

Metformin and Chemoprevention: Potential for Heart-Healthy Targeting of Biologically Aggressive Breast Cancer

Currently, tamoxifen is the only drug approved for reduction of breast cancer risk in premenopausal women. The significant cardiovascular side effects of tamoxifen, coupled with lack of a survival benefit, potential for genotoxicity, and failure to provide a significant risk-reduction for estrogen receptor-negative breast cancer, all contribute to the low acceptance of tamoxifen chemoprevention in premenopausal women at high-risk for breast cancer. While other prevention options exist for postmenopausal women, there is a search for well-tolerated prevention agents that can simultaneously reduce risk of breast cancers, cardiovascular disease, and type-2 diabetes. Metformin is a well-tolerated oral biguanide hypoglycemic agent that is prescribed worldwide to over 120 million individuals with type-2 diabetes. Metformin is inexpensive, safe during pregnancy, and the combination of metformin, healthy lifestyle, and exercise has been shown to be effective in preventing diabetes. There is a growing awareness that prevention drugs and interventions should make the “whole woman healthy.” To this end, current efforts have focused on finding low toxicity alternatives, particularly repurposed drugs for chemoprevention of breast cancer, including metformin. Metformin's mechanisms of actions are complex but clearly involve secondary lowering of circulating insulin. Signaling pathways activated by insulin also drive biologically aggressive breast cancer and predict poor survival in women with breast cancer. The mechanistic rationale for metformin chemoprevention is well-supported by the scientific literature. Metformin is cheap, safe during pregnancy, and has the potential to provide heart-healthy breast cancer prevention. On-going primary and secondary prevention trials will provide evidence whether metformin is effective in preventing breast cancer.

Precision Medicine in Type 2 Diabetes: Using Individualized Prediction Models to Optimize Selection of Treatment

Despite the known heterogeneity of type 2 diabetes and variable response to glucose lowering medications, current evidence on optimal treatment is predominantly based on average effects in clinical trials rather than individual-level characteristics. A precision medicine approach based on treatment response would aim to improve on this by identifying predictors of differential drug response for people based on their characteristics and then using this information to select optimal treatment. Recent research has demonstrated robust and clinically relevant differential drug response with all noninsulin treatments after metformin (sulfonylureas, thiazolidinediones, dipeptidyl peptidase 4 [DPP-4] inhibitors, glucagon-like peptide 1 [GLP-1] receptor agonists, and sodium-glucose cotransporter 2 [SGLT2] inhibitors) using routinely available clinical features. This Perspective reviews this current evidence and discusses how differences in drug response could inform selection of optimal type 2 diabetes treatment in the near future. It presents a novel framework for developing and testing precision medicine-based strategies to optimize treatment, harnessing existing routine clinical and trial data sources. This framework was recently applied to demonstrate that "subtype" approaches, in which people are classified into subgroups based on features reflecting underlying pathophysiology, are likely to have less clinical utility compared with approaches that combine the same features as continuous measures in probabilistic "individualized prediction" models.

Pharmacogenetics of Type 2 Diabetes-Progress and Prospects

Type 2 diabetes mellitus (T2D) is a chronic metabolic disease resulting from insulin resistance and progressively reduced insulin secretion, which leads to impaired glucose utilization, dyslipidemia and hyperinsulinemia and progressive pancreatic beta cell dysfunction. The incidence of type 2 diabetes mellitus is increasing worldwide and nowadays T2D already became a global epidemic. The well-known interindividual variability of T2D drug actions such as biguanides, sulfonylureas/meglitinides, DPP-4 inhibitors/GLP1R agonists and SGLT-2 inhibitors may be caused, among other things, by genetic factors. Pharmacogenetic findings may aid in identifying new drug targets and obtaining in-depth knowledge of the causes of disease and its physiological processes, thereby, providing an opportunity to elaborate an algorithm for tailor or precision treatment. The aim of this article is to summarize recent progress and discoveries for T2D pharmacogenetics and to discuss the factors which limit the furthering accumulation of genetic variability knowledge in patient response to therapy that will allow improvement the personalized treatment of T2D.

Role of Genetic Variations in the Hepatic Handling of Drugs

The liver plays a pivotal role in drug handling due to its contribution to the processes of detoxification (phases 0 to 3). In addition, the liver is also an essential organ for the mechanism of action of many families of drugs, such as cholesterol-lowering, antidiabetic, antiviral, anticoagulant, and anticancer agents. Accordingly, the presence of genetic variants affecting a high number of genes expressed in hepatocytes has a critical clinical impact. The present review is not an exhaustive list but a general overview of the most relevant variants of genes involved in detoxification phases. The available information highlights the importance of defining the genomic profile responsible for the hepatic handling of drugs in many ways, such as (i) impaired uptake, (ii) enhanced export, (iii) altered metabolism due to decreased activation of prodrugs or enhanced inactivation of active compounds, and (iv) altered molecular targets located in the liver due to genetic changes or activation/downregulation of alternative/compensatory pathways. In conclusion, the advance in this field of modern pharmacology, which allows one to predict the outcome of the treatments and to develop more effective and selective agents able to overcome the lack of effect associated with the existence of some genetic variants, is required to step forward toward a more personalized medicine.

Beyond the CNS: The many peripheral roles of APOE

Apolipoprotein E (APOE) is a multifunctional protein synthesized and secreted by multiple mammalian tissues. Although hepatocytes contribute about 75% of the peripheral pool, APOE can also be expressed in adipose tissue, the kidney, and the adrenal glands, among other tissues. High levels of APOE production also occur in the brain, where it is primarily synthesized by glia, and peripheral and brain APOE pools are thought to be distinct. In humans, APOE is polymorphic, with three major alleles (ε2, ε3, and ε4). These allelic forms dramatically alter APOE structure and function. Historically, the vast majority of research on APOE has centered on the important role it plays in modulating risk for cardiovascular disease and Alzheimer's disease. However, the established effects of this pleiotropic protein extend well beyond these two critical health challenges, with demonstrated roles across a wide spectrum of biological conditions, including adipose tissue function and obesity, metabolic syndrome and diabetes, fertility and longevity, and immune function. While the spectrum of biological systems in which APOE plays a role seems implausibly wide at first glance, there are some potential unifying mechanisms that could tie these seemingly disparate disorders together. In the current review, we aim to concisely summarize a wide breadth of APOE-associated pathologies and to analyze the influence of APOE in the development of several distinct disorders in order to provide insight into potential shared mechanisms implied in these various pathophysiological processes.

Can Precision Medicine Reduce the Burden of Diabetes?

Precision medicine is a new health care concept intended to hasten progress toward individualized treatment and, in so doing, to improve everyone's opportunity to enjoy good health. Yet, this concept pays scant attention to opportunities for change in the social determinants that are the major drivers of health. Precision medicine research is likely to generate improvements in medical care but may have the unintended consequence of worsening existing disparities in health care access. For prevention, precision medicine emphasizes comprehensive risk prediction and individual efforts to accomplish risk reduction. The application of the precision medicine vision to type 2 diabetes, a growing threat to population health, fails to acknowledge collective responsibility for a health-promoting society.

MTNR1B Gene Polymorphisms Are Associated With the Therapeutic Responses to Repaglinide in Chinese Patients With Type 2 Diabetes Mellitus

The objective of this study was to investigate whether MTNR1B gene variants influence repaglinide response in Chinese patients with newly diagnosed type 2 diabetes mellitus (T2DM). A total of 300 patients with T2DM and 200 control subjects were enrolled to identify MTNR1B rs10830963 and rs1387153 genotypes by real-time polymerase chain reaction (PCR), with subsequent high-resolution melting (HRM) analysis. Ninety-five patients with newly diagnosed T2DM were randomly selected to undergo 8 weeks of repaglinide treatment (3 mg/day). After 8-week repaglinide monotherapy, patients with at least one G allele of MTNR1B rs10830963 showed a smaller decrease in fasting plasma glucose (FPG) (P = 0.031) and a smaller increase in homeostasis model assessment for beta cell function (HOMA-B) (P = 0.002) levels than those with the CC genotype did. The T allele carriers at rs1387153 exhibited a smaller decrease in FPG (P = 0.007) and smaller increases in postprandial serum insulin (PINS) (P = 0.016) and HOMA-B (P < 0.001) levels compared to individuals with the CC genotype. These data suggest that the MTNR1B rs10830963 and rs1387153 polymorphisms are associated with repaglinide monotherapy efficacy in Chinese patients with T2DM.