Joint effects of diabetic-related genomic loci on the therapeutic efficacy of oral anti-diabetic drugs in Chinese type 2 diabetes patients

Diabetes in China: epidemiology, pathophysiology and multi-omics

Although diabetes is now a global epidemic, China has the highest number of affected people, presenting profound public health and socioeconomic challenges. In China, rapid ecological and lifestyle shifts have dramatically altered diabetes epidemiology and risk factors. In this Review, we summarize the epidemiological trends and the impact of traditional and emerging risk factors on Chinese diabetes prevalence. We also explore recent genetic, metagenomic and metabolomic studies of diabetes in Chinese, highlighting their role in pathogenesis and clinical management. Although heterogeneity across these multidimensional areas poses major analytic challenges in classifying patterns or features, they have also provided an opportunity to increase the accuracy and specificity of diagnosis for personalized treatment and prevention. National strategies and ongoing research are essential for improving diabetes detection, prevention and control, and for personalizing care to alleviate societal impacts and maintain quality of life.

Diabetes and Its Cardiovascular Complications: Comprehensive Network and Systematic Analyses

Diabetes mellitus is a worldwide health problem that usually comes with severe complications. There is no cure for diabetes yet and the threat of these complications is what keeps researchers investigating mechanisms and treatments for diabetes mellitus. Due to advancements in genomics, epigenomics, proteomics, and single-cell multiomics research, considerable progress has been made toward understanding the mechanisms of diabetes mellitus. In addition, investigation of the association between diabetes and other physiological systems revealed potentially novel pathways and targets involved in the initiation and progress of diabetes. This review focuses on current advancements in studying the mechanisms of diabetes by using genomic, epigenomic, proteomic, and single-cell multiomic analysis methods. It will also focus on recent findings pertaining to the relationship between diabetes and other biological processes, and new findings on the contribution of diabetes to several pathological conditions.

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.

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.

Clinical and genetic predictors of diabetes drug's response

Diabetes is a major health problem worldwide. Glycemic control is the main goal in the management of type 2 diabetes. While many anti-diabetic drugs and guidelines are available, almost half of diabetic patients do not reach their treatment goal and develop complications. The glucose-lowering response to anti-diabetic drug differs significantly between individuals. Relatively little is known about the factors that might underlie this response. The identification of predictors of response to anti-diabetic drugs is essential for treatment personalization. Unfortunately, the evidence on predictors of drugs response in type 2 diabetes is scarce. Only a few trials were designed for specific groups of patients (e.g. patients with renal impairment or older patients), while subgroup analyses of larger trials are frequently unreported. Physicians need help in picking the drug which provides the maximal benefit, with minimal side effects, in the right dose, for a specific patient, using an omics-based approach besides the phenotypic characteristics.

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

Type 2 diabetes mellitus (T2DM) is a chronic disease that has reached the levels of a global epidemic. In order to achieve optimal glucose control, it is often necessary to rely on combination therapy of multiple drugs or insulin because uncontrolled glucose levels result in T2DM progression and enhanced risk of complications and mortality. Several antihyperglycemic agents have been developed over time, and T2DM pharmacotherapy should be prescribed based on suitability for the individual patient's characteristics. Pharmacogenetics is the branch of genetics that investigates how our genome influences individual responses to drugs, therapeutic outcomes, and incidence of adverse effects. In this review, we evaluated the pharmacogenetic evidences currently available in the literature, and we identified the top informative genetic variants associated with response to the most common anti-diabetic drugs: metformin, DPP-4 inhibitors/GLP1R agonists, thiazolidinediones, and sulfonylureas/meglitinides. Overall, we found 40 polymorphisms for each drug class in a total of 71 loci, and we examined the possibility of encouraging genetic screening of these variants/loci in order to critically implement decision-making about the therapeutic approach through precision medicine strategies. It is possible then to anticipate that when the clinical practice will take advantage of the genetic information of the diabetic patients, this will provide a useful resource for the prevention of T2DM progression, enabling the identification of the precise drug that is most likely to be effective and safe for each patient and the reduction of the economic impact on a global scale.