Diabetes precision medicine: plenty of potential, pitfalls and perils but not yet ready for prime time

MULTITARGETED POLYPHARMACOTHERAPY for CANCER TREATMENT. THEORETICAL CONCEPTS and PROPOSALS

INTRODUCTION

. The pharmacological treatment of cancer has evolved from cytotoxic to molecular targeted therapy. The median survival gains of 124 drugs approved by the FDA from 2003 to 2021 is 2.8 months. Targeted therapy is based on the somatic mutation theory, which has some paradoxes and limitations. While efforts of targeted therapy must continue, we must study newer approaches that could advance therapy and affordability for patients.

AREAS COVERED

This work briefly overviews how cancer therapy has evolved from cytotoxic chemotherapy to current molecular-targeted therapy. The limitations of the one-target, one-drug approach considering cancer as a robust system and the basis for multitargeting approach with polypharmacotherapy using repurposing drugs.

EXPERT OPINION

Multitargeted polypharmacotherapy for cancer with repurposed drugs should be systematically investigated in preclinical and clinical studies. Remarkably, most of these proposed drugs already have a long history in the clinical setting, and their safety is known. In principle, the risk of their simultaneous administration should not be greater than that of a first-in-human phase I study as long as the protocol is developed with strict vigilance to detect early possible side effects from their potential interactions. Research on cancer therapy should go beyond the prevailing paradigm targeted therapy.

Interaction effect between low birthweight and resistin gene rs1862513 variant on insulin resistance and type 2 diabetes mellitus in adulthood: Toon Genome Study

AIMS/INTRODUCTION

Gene-environment interactions are considered to critically influence type 2 diabetes mellitus development; however, the underlying mechanisms and specific interactions remain unclear. Given the increasing prevalence of low birthweight (LBW) influenced by the intrauterine environment, we sought to investigate genetic factors related to type 2 diabetes development in individuals with LBW.

MATERIALS AND METHODS

The interaction between 20 reported type 2 diabetes susceptibility genes and the development of type 2 diabetes in LBW (<2,500 g) individuals in a population-based Japanese cohort (n = 1,021) was examined by logistic regression and stratified analyses.

RESULTS

Logistic regression analyses showed that only the G/G genotype at the rs1862513 locus of the resistin gene (RETN), an established initiator of insulin resistance, was closely related to the prevalence of type 2 diabetes in individuals with LBW. Age, sex and current body mass index-adjusted stratified analyses showed a significant interaction effect of LBW and the RETN G/G genotype on fasting insulin, homeostatic model assessment 2-insulin resistance, Matsuda index and the prevalence of type 2 diabetes (all P-values for interaction <0.05). The adjusted odds ratio for type 2 diabetes in the LBW + G/G genotype group was 7.33 (95% confidence interval 2.43-22.11; P = 0.002) compared with the non-LBW + non-G/G genotype group. Similar results were obtained after excluding the influence of malnutrition due to World War II.

CONCLUSIONS

Simultaneous assessment of LBW and the RETN G/G genotype can more accurately predict the risk of future type 2 diabetes than assessing each of these factors alone, and provide management strategies, including early lifestyle intervention in LBW population.

Taking the risk. A systematic review of ethical reasons and moral arguments in the clinical use of polygenic risk scores

Debates about the prospective clinical use of polygenic risk scores (PRS) have grown considerably in the last years. The potential benefits of PRS to improve patient care at individual and population levels have been extensively underlined. Nonetheless, the use of PRS in clinical contexts presents a number of unresolved ethical challenges and consequent normative gaps that hinder their optimal implementation. Here, we conducted a systematic review of reasons of the normative literature discussing ethical issues and moral arguments related to the use of PRS for the prevention and treatment of common complex diseases. In total, we have included and analyzed 34 records, spanning from 2013 to 2023. The findings have been organized in three major themes: in the first theme, we consider the potential harms of PRS to individuals and their kin. In the theme "Threats to health equity," we consider ethical concerns of social relevance, with a focus on justice issues. Finally, the theme "Towards best practices" collects a series of research priorities and provisional recommendations to be considered for an optimal clinical translation of PRS. We conclude that the use of PRS in clinical care reinvigorates old debates in matters of health justice; however, open questions, regarding best practices in clinical counseling, suggest that the ethical considerations applicable in monogenic settings will not be sufficient to face PRS emerging challenges.

Multimodal digital phenotyping of diet, physical activity, and glycemia in Hispanic/Latino adults with or at risk of type 2 diabetes

Digital phenotyping refers to characterizing human bio-behavior through wearables, personal devices, and digital health technologies. Digital phenotyping in populations facing a disproportionate burden of type 2 diabetes (T2D) and health disparities continues to lag compared to other populations. Here, we report our study demonstrating the application of multimodal digital phenotyping, i.e., the simultaneous use of CGM, physical activity monitors, and meal tracking in Hispanic/Latino individuals with or at risk of T2D. For 14 days, 36 Hispanic/Latino adults (28 female, 14 with non-insulin treated T2D) wore a continuous glucose monitor (CGM) and a physical activity monitor (Actigraph) while simultaneously logging meals using the MyFitnessPal app. We model meal events and daily digital biomarkers representing diet, physical activity choices, and corresponding glycemic response. We develop a digital biomarker for meal events that differentiates meal events into normal and elevated categories. We examine the contribution of daily digital biomarkers of elevated meal event count and step count on daily time-in-range 54-140 mg/dL (TIR54-140) and average glucose. After adjusting for step count, a change in elevated meal event count from zero to two decreases TIR54-140 by 4.0% (p = 0.003). An increase in 1000 steps in post-meal step count also reduces the meal event glucose response by 641 min mg/dL (p = 0.0006) and reduces the odds of an elevated meal event by 55% (p < 0.0001). The proposed meal event digital biomarkers may provide an opportunity for non-pharmacologic interventions for Hispanic/Latino adults facing a disproportionate burden of T2D.

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.

The case for precision medicine in the prevention, diagnosis, and treatment of cardiometabolic diseases in low-income and middle-income countries

Cardiometabolic diseases are the leading preventable causes of death in most geographies. The causes, clinical presentations, and pathogenesis of cardiometabolic diseases vary greatly worldwide, as do the resources and strategies needed to prevent and treat them. Therefore, there is no single solution and health care should be optimised, if not to the individual (ie, personalised health care), then at least to population subgroups (ie, precision medicine). This optimisation should involve tailoring health care to individual disease characteristics according to ethnicity, biology, behaviour, environment, and subjective person-level characteristics. The capacity and availability of local resources and infrastructures should also be considered. Evidence needed for equitable precision medicine cannot be generated without adequate data from all target populations, and the idea that research done in high-income countries will transfer adequately to low-income and middle-income countries (LMICs) is problematic, as many migration studies and transethnic comparisons have shown. However, most data for precision medicine research are derived from people of European ancestry living in high-income countries. In this Series paper, we discuss the case for precision medicine for cardiometabolic diseases in LMICs, the barriers and enablers, and key considerations for implementation. We focus on three propositions: first, failure to explore and implement precision medicine for cardiometabolic disease in LMICs will enhance global health disparities. Second, some LMICs might already be placed to implement cardiometabolic precision medicine under appropriate circumstances, owing to progress made in treating infectious diseases. Third, improvements in population health from precision medicine are most probably asymptotic; the greatest gains are more likely to be obtained in countries where health-care systems are less developed. We outline key recommendations for implementation of precision medicine approaches in LMICs.

A scoping review of artificial intelligence-based methods for diabetes risk prediction

The increasing prevalence of type 2 diabetes mellitus (T2DM) and its associated health complications highlight the need to develop predictive models for early diagnosis and intervention. While many artificial intelligence (AI) models for T2DM risk prediction have emerged, a comprehensive review of their advancements and challenges is currently lacking. This scoping review maps out the existing literature on AI-based models for T2DM prediction, adhering to the PRISMA extension for Scoping Reviews guidelines. A systematic search of longitudinal studies was conducted across four databases, including PubMed, Scopus, IEEE-Xplore, and Google Scholar. Forty studies that met our inclusion criteria were reviewed. Classical machine learning (ML) models dominated these studies, with electronic health records (EHR) being the predominant data modality, followed by multi-omics, while medical imaging was the least utilized. Most studies employed unimodal AI models, with only ten adopting multimodal approaches. Both unimodal and multimodal models showed promising results, with the latter being superior. Almost all studies performed internal validation, but only five conducted external validation. Most studies utilized the area under the curve (AUC) for discrimination measures. Notably, only five studies provided insights into the calibration of their models. Half of the studies used interpretability methods to identify key risk predictors revealed by their models. Although a minority highlighted novel risk predictors, the majority reported commonly known ones. Our review provides valuable insights into the current state and limitations of AI-based models for T2DM prediction and highlights the challenges associated with their development and clinical integration.

The heterogeneity of metabolic syndrome presentation and challenges this causes in its pharmacological management: a narrative review focusing on principal risk modifiers

INTRODUCTION

Metabolic syndrome (MetS), i.e. the cluster of cardiometabolic risk factors comprising visceral obesity, impaired glucose metabolism, arterial hypertension and atherogenic dyslipidemia, is prevalent globally and exacts a heavy toll on health care expenditures.

AREAS COVERED

The pathophenotypes of individual traits of the MetS in adults are discussed first, with strong emphasis on nonalcoholic fatty liver disease (NAFLD) and sex differences. Next, I discuss recent studies on phenotypic and outcome heterogeneity of the MetS, highlighting the role of NAFLD, sex, reproductive status, and depressive disorders. In the second half of the article, the therapeutic implications of the variable MetS types and features are analyzed, focusing on the most recent developments, and guidelines.

EXPERT OPINION

I have identified physiological, pathological, social and medical sources of phenotypical heterogeneity in the MetS and its constitutive traits. Improved understanding of these variables may be utilized in the setting of future precision medicine approaches in the field of metabolic disorders and target organ damage.

Using Continuous Glucose Monitoring to Prescribe a Time to Exercise for Individuals with Type 2 Diabetes

This study examines the potential utility of using continuous glucose monitoring (CGM) to prescribe an exercise time to target peak hyperglycaemia in people with type 2 diabetes (T2D). The main aim is to test the feasibility of prescribing an individualised daily exercise time, based on the time of CGM-derived peak glucose, for people with T2D. Thirty-five individuals with T2D (HbA1c: 7.2 ± 0.8%; age: 64 ± 7 y; BMI: 29.2 ± 5.2 kg/m²) were recruited and randomised to one of two 14 d exercise interventions: i) ExPeak (daily exercise starting 30 min before peak hyperglycaemia) or placebo active control NonPeak (daily exercise starting 90 min after peak hyperglycaemia). The time of peak hyperglycaemia was determined via a two-week baseline CGM. A CGM, accelerometer, and heart rate monitor were worn during the free-living interventions to objectively measure glycaemic control outcomes, moderate-to-vigorous intensity physical activity (MVPA), and exercise adherence for future translation in a clinical trial. Participation in MVPA increased 26% when an exercise time was prescribed compared to habitual baseline (p < 0.01), with no difference between intervention groups (p > 0.26). The total MVPA increased by 10 min/day during the intervention compared to the baseline (baseline: 23 ± 14 min/d vs. intervention: 33 ± 16 min/d, main effect of time p = 0.03, no interaction). The change in peak blood glucose (mmol/L) was similar between the ExPeak (-0.44 ± 1.6 mmol/L, d = 0.21) and the NonPeak (-0.39 ± 1.5 mmol/L, d = 0.16) intervention groups (p = 0.92). Prescribing an exercise time based on CGM may increase daily participation in physical activity in people with type 2 diabetes; however, further studies are needed to test the long-term impact of this approach.

Precision Medicine in Type 1 Diabetes

Type 1 diabetes is a complex, chronic disease in which the insulin-producing beta cells in the pancreas are sufficiently altered or impaired to result in requirement of exogenous insulin for survival. The development of type 1 diabetes is thought to be an autoimmune process, in which an environmental (unknown) trigger initiates a T cell-mediated immune response in genetically susceptible individuals. The presence of islet autoantibodies in the blood are signs of type 1 diabetes development, and risk of progressing to clinical type 1 diabetes is correlated with the presence of multiple islet autoantibodies. Currently, a "staging" model of type 1 diabetes proposes discrete components consisting of normal blood glucose but at least two islet autoantibodies (Stage 1), abnormal blood glucose with at least two islet autoantibodies (Stage 2), and clinical diagnosis (Stage 3). While these stages may, in fact, not be discrete and vary by individual, the format suggests important applications of precision medicine to diagnosis, prevention, prognosis, treatment and monitoring. In this paper, applications of precision medicine in type 1 diabetes are discussed, with both opportunities and barriers to global implementation highlighted. Several groups have implemented components of precision medicine, yet the integration of the necessary steps to achieve both short- and long-term solutions will need to involve researchers, patients, families, and healthcare providers to fully impact and reduce the burden of type 1 diabetes.

Clinical pharmacology of antidiabetic drugs: What can be expected of their use?

The pharmacotherapy of type 2 diabetes mellitus (T2DM) has markedly evolved in the last two decades. Classical antidiabetic agents (sulphonylureas, metformin, insulin) are now in competition with new glucose-lowering medications. Alpha-glucosidase inhibitors and thiazolidinediones (glitazones) were not able to replace older agents, because of insufficient efficacy and/or poor tolerability/safety. In contrast, incretin-based therapies, both dipeptidyl peptidase-4 inhibitors (DPP-4is or gliptins, oral agents) and glucagon-like peptide-1 receptor agonists (GLP-1RAs, subcutaneous injections) are a major breakthrough in the management of T2DM. Because they are not associated with hypoglycaemia and weight gain, DPP-4is tend to replace sulphonylureas as add-on to metformin while GLP-1RAs tend to replace basal insulin therapy after failure of oral therapies. Furthermore, placebo-controlled cardiovascular outcome trials demonstrated neutrality for DPP-4is, but cardiovascular protection for GLP-1RAs in patients with T2DM at high cardiovascular risk. More recently sodium-glucose cotransporter 2 inhibitors (SGLT2is or gliflozins, oral agents) also showed cardiovascular protection, especially a reduction in hospitalization for heart failure, as well as a renal protection in patients with and without T2DM, at high cardiovascular risk, with established heart failure and/or with chronic kidney disease. Thus, GLP-1RAs and SGLT2is are now considered as preferred drugs in T2DM patients with or at high risk of atherosclerotic cardiovascular disease whereas SGLT2is are more specifically recommended in patients with or at risk of heart failure and renal (albuminuric) disease. The management of T2DM is moving from a glucocentric approach to a broader strategy focusing on all risk factors, including overweight/obesity, and to an organ-disease targeted personalized approach.

The Evolution of Diabetes Treatment Through the Ages: From Starvation Diets to Insulin, Incretins, SGLT2-Inhibitors and Beyond

Diabetes is an ancient disease and for centuries extreme diets and herbal remedies were used to treat diabetes symptoms. The discovery of insulin in 1921 transformed the landscape of diabetes treatment and was followed by the discovery of several new therapies which improved glycemia and increased patient life span. However, as patients with diabetes lived longer, they developed classic microvascular and macrovascular diabetes complications. In the 1990s, the DCCT and the UKPDS trials demonstrated that tight glucose control reduced the microvascular complications of diabetes, but had marginal effects on cardiovascular disease, the leading cause of death in patients with diabetes. In 2008, the FDA directed that all new diabetes medications demonstrate cardiovascular safety. From this recommendation emerged novel therapeutic classes, the GLP-1 receptor agonists and SGLT2-Inhibitors, which not only improve glycemia, but also provide robust cardio-renal protection. In parallel, developments in diabetes technology like continuous glucose monitoring systems, insulin pumps, telemedicine and precision medicine have advanced diabetes management. Remarkably, a century later, insulin remains a cornerstone of diabetes treatment. Also, diet and physical activity remain important components of any diabetes treatment. Today type 2 diabetes is preventable and long-term remission of diabetes is possible. Finally, progress continues in the field of islet transplantation, perhaps the ultimate frontier in diabetes management.

Toward better diabetes care: Exploration and implementation

Approximately 40 years ago, I was fortunate enough to step into the field of diabetes. When I had my fellowship training in the USA, I learned how to ask a good scientific question and conduct clinical research. With collaboration with my mentors, Prof. Gerald R Reaven and Prof. Ida Chen, we participated in many clinical trials. We established the Taiwan Diabetes Registry (TDR) to track long-term changes in diabetes profiles. The ultimate purpose of medical research is to provide benefits to patients. Using electronic medical records and point-of-care glucometers, we reduced inpatients' hyperglycemia and hypoglycemia greatly, which was also reflected by the reduction in hospital stays and readmission rates. With the advent of new technology and medications, we have to ponder where we are on the journey toward better diabetes care. We rigorously advocate diabetes care, hold many symposia and publish updated guidelines. We successfully hosted the congress of the 11th International Diabetes Federation Western Pacific Region & 8th Asian Association for the Study of Diabetes Scientific Meeting 2016 at Taipei, Taiwan. As the era of precision medicine is coming, Taiwan could be considered as one of the best places to run precision medicine. The Taiwan Precision Medicine Initiative has enrolled more than half a million residents, and is currently conducting genotyping and data analysis. In conclusion. I witnessed the early days of simple and few choices for diabetes management to the current various modalities in diabetes care. As these new technologies have become available, patients will always remain at the center of the care model with warmth and humility.

Konjac Glucomannan: An Emerging Specialty Medical Food to Aid in the Treatment of Type 2 Diabetes Mellitus

There are many factors causing T2DM; thus, it is difficult to prevent and cure it with conventional treatment. In order to realize the continuous intervention of T2DM, the treatment strategy of combining diet therapy and traditional medication came into being. As a natural product with the concept of being healthy, konjac flour and its derivatives are popular with the public. Its main component, Konjac glucomannan (KGM), can not only be applied as a food additive, which greatly improves the taste and flavor of food and extends the shelf life of food but also occupies an important role in T2DM. KGM can extend gastric emptying time, increase satiety, and promote liver glycogen synthesis, and also has the potential to improve intestinal flora and the metabolic system through a variety of molecular pathways in order to positively regulate oxidative stress and immune inflammation, and protect the liver and kidneys. In order to establish the theoretical justification for the adjunctive treatment of T2DM, we have outlined the physicochemical features of KGM in this article, emphasizing the advantages of KGM as a meal for special medical purposes of T2DM.

Genomic discoveries unveil mechanistic insights in diabetes

Two diabetes-related papers are featured in this issue of Cell Genomics. Gardner et al.¹ focus on type 2 diabetes through exome sequencing, and Benaglio et al.² employ a functional genomics approach to advance understanding in type 1 diabetes. In this preview, Jose Florez highlights their contribution toward clinical translation of genomics discoveries.