Evolving to Personalized Medicine for Type 2 Diabetes

Precision Nutrition to Improve Risk Factors of Obesity and Type 2 Diabetes

PURPOSE OF REVIEW

Existing dietary and lifestyle interventions and recommendations, to improve the risk factors of obesity and type 2 diabetes with the target to mitigate this double global epidemic, have produced inconsistent results due to interpersonal variabilities in response to these conventional approaches, and inaccuracies in dietary assessment methods. Precision nutrition, an emerging strategy, tailors an individual's key characteristics such as diet, phenotype, genotype, metabolic biomarkers, and gut microbiome for personalized dietary recommendations to optimize dietary response and health. Precision nutrition is suggested to be an alternative and potentially more effective strategy to improve dietary intake and prevention of obesity and chronic diseases. The purpose of this narrative review is to synthesize the current research and examine the state of the science regarding the effect of precision nutrition in improving the risk factors of obesity and type 2 diabetes.

RECENT FINDINGS

The results of the research review indicate to a large extent significant evidence supporting the effectiveness of precision nutrition in improving the risk factors of obesity and type 2 diabetes. Deeper insights and further rigorous research into the diet-phenotype-genotype and interactions of other components of precision nutrition may enable this innovative approach to be adapted in health care and public health to the special needs of individuals. Precision nutrition provides the strategy to make individualized dietary recommendations by integrating genetic, phenotypic, nutritional, lifestyle, medical, social, and other pertinent characteristics about individuals, as a means to address the challenges of generalized dietary recommendations. The evidence presented in this review shows that precision nutrition markedly improves risk factors of obesity and type 2 diabetes, particularly behavior change.

New Paradigm of Personalized Glycemic Control Using Glucose Temporal Density Histograms

BACKGROUND

Current methods used to assess glycemic control use averaged measures and provide little information on the glycemic pathology of the patients. In this article we propose visual tools and their related mathematical formulas that allow for improved characterization of the glycemic behavior and achieve better glycemic control.

METHODS

We present a reanalysis of published data, based on SMBG measurements from clinical trials of both men and women older than 18 years who were either healthy volunteers, prediabetes, or type 1 or type 2 diabetes. New graphic visualizations of glycemia as well as mathematical formulas that describe the glycemic behavior are presented and described, as well as suggested methods for their use to improve glycemic control.

RESULTS

Patients with different problems in their glycemic control had different histogram shapes. In addition, patients who had the same HbA1c level at the time of the trial revealed significantly different glucose histograms with different shapes, variability and glycemic burden. The derived graphic visualizations provided information about the temporal evolution of the glycemic control.

CONCLUSIONS

A paradigm change of the existing model of diabetes control is proposed, shifting from standardized treatment algorithms based on HbA1c follow-up to a new controlling approach that is based on the personal glucose density histogram. The histogram is an informative, detailed tool for the current patient glycemic behavior, and a future histogram can be targeted for a successful treatment. In addition, the glucose burden and the glucose severity index are proposed as informative markers for successful treatment. This is applicable to any glycemic data, by means of invasive and noninvasive glucometers.

Precision nutrition for prevention and management of type 2 diabetes

Precision nutrition aims to prevent and manage chronic diseases by tailoring dietary interventions or recommendations to one or a combination of an individual's genetic background, metabolic profile, and environmental exposures. Recent advances in genomics, metabolomics, and gut microbiome technologies have offered opportunities as well as challenges in the use of precision nutrition to prevent and manage type 2 diabetes. Nutrigenomics studies have identified genetic variants that influence intake and metabolism of specific nutrients and predict individuals' variability in response to dietary interventions. Metabolomics has revealed metabolomic fingerprints of food and nutrient consumption and uncovered new metabolic pathways that are potentially modified by diet. Dietary interventions have been successful in altering abundance, composition, and activity of gut microbiota that are relevant for food metabolism and glycaemic control. In addition, mobile apps and wearable devices facilitate real-time assessment of dietary intake and provide feedback which can improve glycaemic control and diabetes management. By integrating these technologies with big data analytics, precision nutrition has the potential to provide personalised nutrition guidance for more effective prevention and management of type 2 diabetes. Despite these technological advances, much research is needed before precision nutrition can be widely used in clinical and public health settings. Currently, the field of precision nutrition faces challenges including a lack of robust and reproducible results, the high cost of omics technologies, and methodological issues in study design as well as high-dimensional data analyses and interpretation. Evidence is needed to support the efficacy, cost-effectiveness, and additional benefits of precision nutrition beyond traditional nutrition intervention approaches. Therefore, we should manage unrealistically high expectations and balance the emerging field of precision nutrition with public health nutrition strategies to improve diet quality and prevent type 2 diabetes and its complications.

Cultural primer for cardiometabolic health: health disparities, structural factors, community, pathways to improvement, and clinical applications

The quest to optimize cardiometabolic health has created great interest in nonmedical health variables in the population, community-based research and coordination, and addressing social, ethnic, and cultural barriers. All of these may be of equal or even greater importance than classical health care delivery in achieving individual well-being. One dominant issue is health disparity - causes, methods of reduction, and community versus other levels of solutions. This communication summarizes some major views regarding social structures, followed by amplification and synthesis of central ideas in the literature. The role of community involvement, tools, and partnerships is also presented in this Primer. Recent views of how these approaches could be incorporated into cardiometabolic initiatives and strategies follow, with implications for research. Two examples comparing selected aspects of community leverage and interventions in relation to individual approaches to health care equity are examined in depth: overall performance in reducing cardiovascular risk and mortality, and the recent National Diabetes Prevention Program, both touching upon healthy diets and adherence. Finally, the potential that precision medicine offers, and possible effects on disparities are also discussed.

Digital health technology and diabetes management

Diabetes care is largely dependent on patient self-management and empowerment, given that patients with diabetes must make numerous daily decisions as to what to eat, when to exercise, and determine their insulin dose and timing if required. In addition, patients and providers are generating vast amounts of data from many sources, including electronic medical records, insulin pumps, sensors, glucometers, and other wearables, as well as evolving genomic, proteomic, metabolomics, and microbiomic data. Multiple digital tools and apps have been developed to assist patients to choose wisely, and to enhance their compliance by using motivational tools and incorporating incentives from social media and gaming techniques. Healthcare teams (HCTs) and health administrators benefit from digital developments that sift through the enormous amounts of patient-generated data. Data are acquired, integrated, analyzed, and presented in a self-explanatory manner, highlighting important trends and items that require attention. The use of decision support systems may propose data-driven actions that, for the most, require final approval by the patient or physician before execution and, once implemented, may improve patient outcomes. The digital diabetes clinic aims to incorporate all digital patient data and provide individually tailored virtual or face-to-face visits to those persons who need them most. Digital diabetes care has demonstrated only modest HbA1c reduction in multiple studies and borderline cost-effectiveness, although patient satisfaction appears to be increased. Better understanding of the barriers to digital diabetes care and identification of unmet needs may yield improved utilization of this evolving technology in a safe, effective, and cost-saving manner.

Genetic and epigenetic modifications in the pathogenesis of diabetic retinopathy: a molecular link to regulate gene expression

Intensification in the frequency of diabetes and the associated vascular complications has been a root cause of blindness and visual impairment worldwide. One such vascular complication which has been the prominent cause of blindness; retinal vasculature, neuronal and glial abnormalities is diabetic retinopathy (DR), a chronic complicated outcome of Type 1 and Type 2 diabetes. It has also become clear that "genetic" variations in population alone can't explain the development and progression of diabetes and its complications including DR. DR experiences engagement of foremost mediators of diabetes such as hyperglycemia, oxidant stress, and inflammatory factors that lead to the dysregulation of "epigenetic" mechanisms involving histone acetylation and histone and DNA methylation, chromatin remodeling and expression of a complex set of stress-regulated and disease-associated genes. In addition, both elevated glucose concentration and insulin resistance leave a robust effect on epigenetic reprogramming of the endothelial cells too, since endothelium associated with the eye aids in maintaining the vascular homeostasis. Furthermore, several studies conducted on the disease suggest that the modifications of the epigenome might be the fundamental mechanism(s) for the proposed metabolic memory' resulting into prolonged gene expression for inflammation and cellular dysfunction even after attaining the glycemic control in diabetics. Henceforth, the present review focuses on the aspects of genetic and epigenetic alterations in genes such as vascular endothelial growth factor and aldose reductase considered being associated with DR. In addition, we discuss briefly the role of the thioredoxin-interacting protein TXNIP, which is strongly induced by high glucose and diabetes, in cellular oxidative stress and mitochondrial dysfunction potentially leading to chromatin remodeling and ocular complications of diabetes. The identification of disease-associated genes and their epigenetic regulations will lead to potential new drugs and gene therapies as well as personalized medicine to prevent or slow down the progression of DR.