Next-generation epidemiology: the role of high-resolution molecular phenotyping in diabetes research

Diabetes and obesity: leveraging heterogeneity for precision medicine

The increasing prevalence of diabetes, obesity, and their cardiometabolic sequelae present major global health challenges and highlight shortfalls of current approaches to the prevention and treatment of these conditions. Representing the largest global burden of morbidity and mortality, the pathobiological processes underlying cardiometabolic diseases are in principle preventable and, even when disease is manifest, sometimes reversable. Nevertheless, with current clinical and public health strategies, goals of widespread prevention and remission remain largely aspirational. Application of precision medicine approaches that reduce errors and improve accuracy in medical and health recommendations has potential to accelerate progress towards these goals. Precision medicine must also maintain safety and ideally be cost-effective, as well as being compatible with an individual's preferences, capabilities, and needs. Initial progress in precision medicine was made in the context of rare diseases, with much focus on pharmacogenetic studies, owing to the cause of these diseases often being attributable to highly penetrant single gene mutations. By contrast, most obesity and type 2 diabetes are heterogeneous in aetiology and clinical presentation, underpinned by complex interactions between genetic and non-genetic factors. The heterogeneity of these conditions can be leveraged for development of approaches for precision therapies. Adequate characterization of the heterogeneity in cardiometabolic disease necessitates diversity of and synthesis across data types and research methods, ideally culminating in precision trials and real-world application of precision medicine approaches. This State-of-the-Art Review provides an overview of the current state of the science of precision medicine, as well as outlining a roadmap for study designs that maximise opportunities and address challenges to clinical implementation of precision medicine approaches in obesity and diabetes.

Do gene-environment interactions have implications for the precision prevention of type 2 diabetes?

The past decades have seen a rapid global rise in the incidence of type 2 diabetes. This surge has been driven by diabetogenic environmental changes that may act together with a genetic predisposition to type 2 diabetes. It is possible that there is a synergistic gene-environment interaction, where the effects of the diabetogenic environment depend on the genetic predisposition to type 2 diabetes. Randomised trials have shown that it is possible to delay, or even prevent the development of type 2 diabetes in individuals at elevated risk through behavioural modification, focusing on weight loss, physical activity and diet. There is wide heterogeneity between individuals regarding the effectiveness of these interventions, which could, in part, be due to genetic differences. However, the studies of gene-environment interactions performed thus far suggest that behavioural modifications appear equally effective in reducing the incidence of type 2 diabetes from the stage of impaired glucose tolerance, regardless of the known underlying genetic predisposition. Recent studies suggest that there may be several subtypes of type 2 diabetes, which give new opportunities for gaining insight into gene-environment interactions. At present, the role of gene-environment interactions in the development of type 2 diabetes remains unclear. With many puzzle pieces missing in the general picture of type 2 diabetes development, the available evidence of gene-environment interactions is not ready for translation to individualised type 2 diabetes prevention based on genetic profiling.

'Omics in environmental epidemiological studies of chemical exposures: A systematic evidence map

BACKGROUND

Systematic evidence maps are increasingly used to develop chemical risk assessments. These maps can provide an overview of available studies and relevant study information to be used for various research objectives and applications. Environmental epidemiological studies that examine the impact of chemical exposures on various 'omic profiles in human populations provide relevant mechanistic information and can be used for benchmark dose modeling to derive potential human health reference values.

OBJECTIVES

To create a systematic evidence map of environmental epidemiological studies examining environmental contaminant exposures with 'omics in order to characterize the extent of available studies for future research needs.

METHODS

Systematic review methods were used to search and screen the literature and included the use of machine learning methods to facilitate screening studies. The Populations, Exposures, Comparators and Outcomes (PECO) criteria were developed to identify and screen relevant studies. Studies that met the PECO criteria after full-text review were summarized with information such as study population, study design, sample size, exposure measurement, and 'omics analysis.

RESULTS

Over 10,000 studies were identified from scientific databases. Screening processes were used to identify 84 studies considered PECO-relevant after full-text review. Various contaminants (e.g. phthalate, benzene, arsenic, etc.) were investigated in epidemiological studies that used one or more of the four 'omics of interest: epigenomics, transcriptomics, proteomics, and metabolomics . The epidemiological study designs that were used to explore single or integrated 'omic research questions with contaminant exposures were cohort studies, controlled trials, cross-sectional, and case-control studies. An interactive web-based systematic evidence map was created to display more study-related information.

CONCLUSIONS

This systematic evidence map is a novel tool to visually characterize the available environmental epidemiological studies investigating contaminants and biological effects using 'omics technology and serves as a resource for investigators and allows for a range of applications in chemical research and risk assessment needs.

Angiopoietin-like protein 8 (betatrophin) inhibits hepatic gluconeogenesis through PI3K/Akt signaling pathway in diabetic mice

BACKGROUND & AIMS

Angiopoietin-like protein 8 (ANGPTL8) is a 198 amino-acid long, novel secreted protein that is mainly expressed in the liver and brown adipose tissues. At present, evidence supporting the involvement of ANGPTL8 in the regulation of glucose metabolism is inconclusive, along with its function in the liver. Previous studies mainly focused on the effect of ANGPTL8 on glucose metabolism in non-diabetic mice, and few relevant studies in diabetic mice exist. Therefore, this study aimed to investigate the role of ANGPTL8 on glucose homeostasis and elucidate the underlying mechanisms in diabetic mice.

METHODS

db/db diabetic and high-fat diet/streptozotocin-induced diabetic mice were injected with adenovirus expressing ANGPTL8 through the tail vein. Blood glucose levels were measured and glucose, insulin, and pyruvate tolerance tests were performed. To explore the molecular mechanism by which ANGPTL8 regulates hepatic glucose metabolism and manipulate mouse ANGPTL8 expression levels both in vivo and in vitro based on adenoviral transduction, gain- and loss-of-function strategies were adopted.

RESULTS

Adenovirus-mediated overexpression of ANGPTL8 decreased fasting blood glucose levels and improved glucose tolerance and insulin sensitivity in db/db and high-fat diet/streptozotocin-induced diabetic mice. ANGPTL8 knockdown yielded the opposite effects. ANGPTL8 was upregulated in the cAMP/Dex-induced hepatocyte gluconeogenesis model. Moreover, ANGPTL8 overexpression in primary hepatocytes and diabetic mouse livers inhibited the expression of gluconeogenesis-related genes, including PEPCK and G6PC, by activating the AKT signaling pathway and, thereby, reducing glucose production. Therefore, the results demonstrated that ANGPTL8 improved glucose metabolism via inhibition of hepatic gluconeogenesis in diabetic mice.

CONCLUSIONS

Current findings highlight a critical role of hepatic ANGPTL8 in glucose homeostasis, suggesting that increased ANGPTL8 expression could be an underlying factor for the inhibition of hepatic gluconeogenesis, which could be targeted for the prevention and treatment of type 2 diabetes.

Diagnosis and treatment of type 1 diabetes at the dawn of the personalized medicine era

Type 1 diabetes affects millions of people globally and requires careful management to avoid serious long-term complications, including heart and kidney disease, stroke, and loss of sight. The type 1 diabetes patient cohort is highly heterogeneous, with individuals presenting with disease at different stages and severities, arising from distinct etiologies, and overlaying varied genetic backgrounds. At present, the “one-size-fits-all” treatment for type 1 diabetes is exogenic insulin substitution therapy, but this approach fails to achieve optimal blood glucose control in many individuals. With advances in our understanding of early-stage diabetes development, diabetes stratification, and the role of genetics, type 1 diabetes is a promising candidate for a personalized medicine approach, which aims to apply “the right therapy at the right time, to the right patient”. In the case of type 1 diabetes, great efforts are now being focused on risk stratification for diabetes development to enable pre-clinical detection, and the application of treatments such as gene therapy, to prevent pancreatic destruction in a sub-set of patients. Alongside this, breakthroughs in stem cell therapies hold great promise for the regeneration of pancreatic tissues in some individuals. Here we review the recent initiatives in the field of personalized medicine for type 1 diabetes, including the latest discoveries in stem cell and gene therapy for the disease, and current obstacles that must be overcome before the dream of personalized medicine for all type 1 diabetes patients can be realized.