Modulation of GLP-1 Levels by a Genetic Variant That Regulates the Cardiovascular Effects of Intensive Glycemic Control in ACCORD

New insights on genetic background of major diabetic vascular complications

BACKGROUND

By 2045, it is expected that 693 million individuals worldwide will have diabetes and with greater risk of morbidity, mortality, loss of vision, renal failure, and a decreased quality of life due to the devastating effects of macro- and microvascular complications. As such, clinical variables and glycemic control alone cannot predict the onset of vascular problems. An increasing body of research points to the importance of genetic predisposition in the onset of both diabetes and diabetic vascular complications.

OBJECTIVES

Purpose of this article is to review these approaches and narrow down genetic findings for Diabetic Mellitus and its consequences, highlighting the gaps in the literature necessary to further genomic discovery.

MATERIAL AND METHODS

In the past, studies looking for genetic risk factors for diabetes complications relied on methods such as candidate gene studies, which were rife with false positives, and underpowered genome-wide association studies, which were constrained by small sample sizes.

RESULTS

The number of genetic findings for diabetes and diabetic complications has over doubled due to the discovery of novel genomics data, including bioinformatics and the aggregation of global cohort studies. Using genetic analysis to determine whether diabetes individuals are at the most risk for developing diabetic vascular complications (DVC) might lead to the development of more accurate early diagnostic biomarkers and the customization of care plans.

CONCLUSIONS

A newer method that uses extensive evaluation of single nucleotide polymorphisms (SNP) in big datasets is Genome-Wide Association Studies (GWAS).

Exploring the design of clinical research studies on the efficacy mechanisms in type 2 diabetes mellitus

This review examines the complexities of Type 2 Diabetes Mellitus (T2DM), focusing on the critical role of integrating omics technologies with traditional experimental methods. It underscores the advancements in understanding the genetic diversity of T2DM and emphasizes the evolution towards personalized treatment modalities. The paper analyzes a variety of omics approaches, including genomics, methylation, transcriptomics, proteomics, metabolomics, and intestinal microbiomics, delineating their substantial contributions to deciphering the multifaceted mechanisms underlying T2DM. Furthermore, the review highlights the indispensable role of non-omics experimental techniques in comprehending and managing T2DM, advocating for their integration in the development of tailored medicine and precision treatment strategies. By identifying existing research gaps and suggesting future research trajectories, the review underscores the necessity for a comprehensive, multidisciplinary approach. This approach synergistically combines clinical insights with cutting-edge biotechnologies, aiming to refine the management and therapeutic interventions of T2DM, and ultimately enhancing patient outcomes. This synthesis of knowledge and methodologies paves the way for innovative advancements in T2DM research, fostering a deeper understanding and more effective treatment of this complex condition.

Precision Medicine in Type 2 Diabetes Mellitus: Utility and Limitations

Type 2 diabetes mellitus (T2DM) is one of the most widespread diseases in Western countries, and its incidence is constantly increasing. Epidemiological studies have shown that in the next 20 years. The number of subjects affected by T2DM will double. In recent years, owing to the development and improvement in methods for studying the genome, several authors have evaluated the association between monogenic or polygenic genetic alterations and the development of metabolic diseases and complications. In addition, sedentary lifestyle and socio-economic and pandemic factors have a great impact on the habits of the population and have significantly contributed to the increase in the incidence of metabolic disorders, obesity, T2DM, metabolic syndrome, and liver steatosis. Moreover, patients with type 2 diabetes appear to respond to antihyperglycemic drugs. Only a minority of patients could be considered true non-responders. Thus, it appears clear that the main aim of precision medicine in T2DM is to identify patients who can benefit most from a specific drug class more than from the others. Precision medicine is a discipline that evaluates the applicability of genetic, lifestyle, and environmental factors to disease development. In particular, it evaluated whether these factors could affect the development of diseases and their complications, response to diet, lifestyle, and use of drugs. Thus, the objective is to find prevention models aimed at reducing the incidence of pathology and mortality and therapeutic personalized approaches, to obtain a greater probability of response and efficacy. This review aims to evaluate the applicability of precision medicine for T2DM, a healthcare burden in many countries.

Pharmacogenetics of Cardiovascular Prevention in Diabetes: From Precision Medicine to Identification of Novel Targets

Pharmacogenetics—a branch of precision medicine—holds the promise of becoming a novel tool to reduce the social and healthcare burdens of cardiovascular disease (CVD) and coronary artery disease (CAD) in diabetes. The improvement in cardiovascular risk stratification resulting from adding genetic characteristics to clinical data has moved from the modest results obtained with genetic risk scores based on few genetic variants, to the progressively better performances of polygenic risk scores based on hundreds to millions of variants (CAD-PGRS). Similarly, over the past few years, the number of studies investigating the use of CAD-PGRS to identify different responses to cardio-preventive treatment has progressively increased, yielding striking results for lipid-lowering drugs such as proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitors and statins. The use of CAD-PGRS to stratify patients based on their likely response to diabetes-specific interventions has been less successful, but promising results have been obtained with regard to specific genetic variants modulating the effects of interventions such as intensive glycemic control and fenofibrate. The finding of diabetes-specific CAD-loci, such as GLUL, has also led to the identification of promising new targets that might hopefully result in the development of specific therapies to reduce CVD burden in patients with diabetes. As reported in consensus statements from international diabetes societies, some of these pharmacogenetic approaches are expected to be introduced in clinical practice over the next decade. For this to happen, in addition to continuing to improve and validate these tools, it will be necessary to educate physicians and patients about the opportunities and limits of pharmacogenetics, as summarized in this review.

Current trends in epidemiology of cardiovascular disease and cardiovascular risk management in type 2 diabetes

With the advances in diabetes care, the trend of incident cardiovascular disease (CVD) in patients with type 2 diabetes mellitus (T2DM) has been decreasing over past decades. However, given that CVD is still a major cause of death in patients with diabetes and that the risk of CVD in patients with T2DM is more than twice that in those without DM, there are still considerable challenges to the prevention of CVD in diabetes. Accordingly, there have been several research efforts to decrease cardiovascular (CV) risk in T2DM. Large-scale genome-wide association studies (GWAS) and clinical cohort studies have investigated the effects of factors, such as genetic determinants, hypoglycaemia, and insulin resistance, on CVD and can account for the unexplained CV risk in T2DM. Lifestyle modification is a widely accepted cornerstone method to prevent CVD as the first-line strategy in T2DM. Recent reports from large CV outcome trials have proven the positive CV effects of sodium-glucose cotransporter-2 (SGLT-2) inhibitors and glucagon-like peptide-1 receptor agonists (GLP-1RAs) in patients with high CVD risk. Overall, current practice guidelines for the management of CVD in T2DM are moving from a glucocentric strategy to a more individualised patient-centred approach. This review will discuss the current epidemiologic trends of CVD in T2DM and the risk factors linking T2DM to CVD, including genetic contribution, hypoglycaemia, and insulin resistance, and proper care strategies, including lifestyle and therapeutic approaches.

Cardiovascular disease in diabetes, beyond glucose

Despite the decades-old knowledge that diabetes mellitus is a major risk factor for cardiovascular disease, the reasons for this association are only partially understood. While this association is true for both type 1 and type 2 diabetes, different pathophysiological processes may be responsible. Lipids and other risk factors are indeed important, whereas the role of glucose is less clear. This lack of clarity stems from clinical trials that do not unambiguously show that intensive glycemic control reduces cardiovascular events. Animal models have provided mechanisms that link diabetes to increased atherosclerosis, and evidence consistent with the importance of factors beyond hyperglycemia has emerged. We review clinical, pathological, and animal studies exploring the pathogenesis of atherosclerosis in humans living with diabetes and in mouse models of diabetes. An increased effort to identify risk factors beyond glucose is now needed to prevent the increased cardiovascular disease risk associated with diabetes.

Prevalence and Risk Factors of Type 2 Diabetes and Prediabetes Among 53,288 Middle-Aged and Elderly Adults in China: A Cross-Sectional Study

BACKGROUND

Diabetes is a metabolic disorder that causes a heavy burden on healthcare systems worldwide. The aim of this study was to determine the prevalence of type 2 diabetes and prediabetes and its associated factors among eight communities in Nanchong, China.

METHODS

This was an observational cross-sectional study conducted throughout eight communities in Nanchong, China. The participants were 53,288 individuals aged 45 years or older. The participants' characteristics, comorbidities, health behaviors, family history, and dietary intake were assessed. Multinomial logistic regression models were fitted to identify factors associated with type 2 diabetes and prediabetes.

RESULTS

The prevalence of diabetes and prediabetes was 13.9% (95% confidence interval [CI], 13.6-14.2) and 3.1% (95% CI, 2.9-3.2) of the population, respectively. After adjusting for other risk factors, advanced age, overweight, obesity, abdominal obesity, comorbidities, smoking, a family history of diabetes, and Chinese cooking vegetable intake were associated with an increased risk of type 2 diabetes and prediabetes.

CONCLUSION

The prevalence of type 2 diabetes in the Chinese population is rising compared with data from the past. The risk factors of type 2 diabetes and prediabetes identified in this study will aid the identification of individuals at a high-risk of diabetes and the implementation of effective health promotion programs and campaigns.

CLINICAL TRIAL REGISTRY NUMBER

ChiCTR-HOC-17013200.

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.

Genetics of diabetes mellitus and diabetes complications

Diabetes is one of the fastest growing diseases worldwide, projected to affect 693 million adults by 2045. Devastating macrovascular complications (cardiovascular disease) and microvascular complications (such as diabetic kidney disease, diabetic retinopathy and neuropathy) lead to increased mortality, blindness, kidney failure and an overall decreased quality of life in individuals with diabetes. Clinical risk factors and glycaemic control alone cannot predict the development of vascular complications; numerous genetic studies have demonstrated a clear genetic component to both diabetes and its complications. Early research aimed at identifying genetic determinants of diabetes complications relied on familial linkage analysis suited to strong-effect loci, candidate gene studies prone to false positives, and underpowered genome-wide association studies limited by sample size. The explosion of new genomic datasets, both in terms of biobanks and aggregation of worldwide cohorts, has more than doubled the number of genetic discoveries for both diabetes and diabetes complications. We focus herein on genetic discoveries for diabetes and diabetes complications, empowered primarily through genome-wide association studies, and emphasize the gaps in research for taking genomic discovery to the next level.

PPARA Polymorphism Influences the Cardiovascular Benefit of Fenofibrate in Type 2 Diabetes: Findings From ACCORD-Lipid

The cardiovascular benefits of fibrates have been shown to be heterogeneous and to depend on the presence of atherogenic dyslipidemia. We investigated whether genetic variability in the PPARA gene, coding for the pharmacological target of fibrates (PPAR-α), could be used to improve the selection of patients with type 2 diabetes who may derive cardiovascular benefit from addition of this treatment to statins. We identified a common variant at the PPARA locus (rs6008845, C/T) displaying a study-wide significant influence on the effect of fenofibrate on major cardiovascular events (MACE) among 3,065 self-reported white subjects treated with simvastatin and randomized to fenofibrate or placebo in the ACCORD-Lipid trial. T/T homozygotes (36% of participants) experienced a 51% MACE reduction in response to fenofibrate (hazard ratio 0.49; 95% CI 0.34-0.72), whereas no benefit was observed for other genotypes (P interaction = 3.7 × 10-4). The rs6008845-by-fenofibrate interaction on MACE was replicated in African Americans from ACCORD (N = 585, P = 0.02) and in external cohorts (ACCORD-BP, ORIGIN, and TRIUMPH, total N = 3059, P = 0.005). Remarkably, rs6008845 T/T homozygotes experienced a cardiovascular benefit from fibrate even in the absence of atherogenic dyslipidemia. Among these individuals, but not among carriers of other genotypes, fenofibrate treatment was associated with lower circulating levels of CCL11-a proinflammatory and atherogenic chemokine also known as eotaxin (P for rs6008845-by-fenofibrate interaction = 0.003). The GTEx data set revealed regulatory functions of rs6008845 on PPARA expression in many tissues. In summary, we have found a common PPARA regulatory variant that influences the cardiovascular effects of fenofibrate and that could be used to identify patients with type 2 diabetes who would derive benefit from fenofibrate treatment, in addition to those with atherogenic dyslipidemia.

Leveraging Genetics to Improve Cardiovascular Health in Diabetes: The 2018 Edwin Bierman Award Lecture

The past decade has witnessed an exponential increase in our ability to search the genome for genetic factors predisposing to cardiovascular disease (CVD) and in particular coronary heart disease (CHD). Identifying these genes could lead to the development of innovative strategies to prevent the cardiovascular complications of diabetes by allowing us to 1) create predictive algorithms for the identification of patients at especially high risk of CVD so that these individuals can undergo preventive interventions early in the natural history of the disease; 2) discover as yet unknown disease pathways linking diabetes to atherosclerosis, which can be used as targets for the development of new CVD-preventing drugs specifically directed at subjects with diabetes; and 3) devise personalized programs increasing the cost-effectiveness of preventive interventions by tailoring them to the genetic background of each patient. Substantial progress has been made in each of these three areas as exemplified by the recent development of a CHD genetic risk score improving CHD prediction among subjects with type 2 diabetes, the discovery of a diabetes-specific CHD locus on 1q25 pointing to glutamine synthase (GLUL) and the γ-glutamyl cycle as key regulators of CHD risk in diabetes, and the identification of two genetic loci allowing the selection of patients with type 2 diabetes who may especially benefit from intensive glycemic control. Translating these discoveries into clinical practice will not be without challenges, but the potential rewards, from the perspective of public health as well as that of persons with diabetes, make this goal worth pursuing.

Precision medicine in the management of type 2 diabetes

The study of type 2 diabetes has been driven by advances in human genetics, epigenetics, biomarkers, mechanistic studies, and large clinical trials, enabling new insights into disease susceptibility, pathophysiology, progression, and development of complications. Simultaneously, several new drug classes with different mechanisms of action have been introduced over the past two decades, accompanied by data about cardiovascular safety and non-glycaemic outcomes. In this Review, we critically examine the progress and integration of this new science into clinical practice, and review opportunities for enabling the use of precision medicine in the diagnosis and treatment of type 2 diabetes. We contrast the success in delivering personalised medicine for monogenic diabetes with the greater challenge of providing a precision medicine approach for type 2 diabetes, highlighting gaps, limitations, and areas requiring further study.

Mechanisms of Action and Therapeutic Application of Glucagon-like Peptide-1

Glucagon-like peptide-1 (GLP-1) released from gut enteroendocrine cells controls meal-related glycemic excursions through augmentation of insulin and inhibition of glucagon secretion. GLP-1 also inhibits gastric emptying and food intake, actions maximizing nutrient absorption while limiting weight gain. Here I review the circuits engaged by endogenous versus pharmacological GLP-1 action, highlighting key GLP-1 receptor (GLP-1R)-positive cell types and pathways transducing metabolic and non-glycemic GLP-1 signals. The role(s) of GLP-1 in the benefits and side effects associated with bariatric surgery are discussed and actions of GLP-1 controlling islet function, appetite, inflammation, and cardiovascular pathophysiology are highlighted. Refinement of the risk-versus-benefit profile of GLP-1-based therapies for the treatment of diabetes and obesity has stimulated development of orally bioavailable agonists, allosteric modulators, and unimolecular multi-agonists, all targeting the GLP-1R. This review highlights established and emerging concepts, unanswered questions, and future challenges for development and optimization of GLP-1R agonists in the treatment of metabolic disease.