Abstract

The convergence of advances in medical science, human biology, data science, and technology has enabled the generation of new insights into the phenotype known as “diabetes.” Increased knowledge of this condition has emerged from populations around the world, illuminating the differences in how diabetes presents, its variable prevalence, and how best practice in treatment varies between populations. In parallel, focus has been placed on the development of tools for the application of precision medicine to numerous conditions.

This Consensus Report presents the American Diabetes Association (ADA) Precision Medicine in Diabetes Initiative in partnership with the European Association for the Study of Diabetes (EASD), including its mission, the current state of the field, and prospects for the future. Expert opinions are presented on areas of precision diagnostics and precision therapeutics (including prevention and treatment), and key barriers to and opportunities for implementation of precision diabetes medicine, with better care and outcomes around the globe, are highlighted. Cases where precision diagnosis is already feasible and effective (i.e., monogenic forms of diabetes) are presented, while the major hurdles to the global implementation of precision diagnosis of complex forms of diabetes are discussed. The situation is similar for precision therapeutics, in which the appropriate therapy will often change over time owing to the manner in which diabetes evolves within individual patients.

This Consensus Report describes a foundation for precision diabetes medicine, while highlighting what remains to be done to realize its potential. This, combined with a subsequent, detailed evidence-based review (due 2022), will provide a roadmap for precision medicine in diabetes that helps improve the quality of life for all those with diabetes

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Rationale for Precision Medicine in Diabetes

The practice of medicine centers on the individual. From the beginning, the physician has examined the patient suffering from illness, ascertained his/her signs and symptoms, related them to the medical knowledge available at the time, recognized patterns that fit a certain category and, based on the practical wisdom accumulated via empirical trial and error, applied a given remedy that is best suited to the situation at hand. Thus, the concept of precision medicine, often defined as providing the right therapy for the right patient at the right time, is not novel. What has changed radically is our ability to characterize and understand human biological variation through 1) assessment of the genetic and metabolic state, 2) leveraging data to inform disease categories, and 3) science-guided preventive and treatment decisions tailored to specific pathological conditions. Coupling these with detailed information about lifestyle and environment, available through digital devices and technologies that collect those measures, as well as data abstracted from electronic medical records, present unparalleled opportunities to optimize diabetes medicine.

Diabetes mellitus is diagnosed by the presence of hyperglycemia that is higher than a threshold blood glucose concentration which predisposes to microvascular end-organ complications. However, hyperglycemia is the end product of numerous pathophysiological processes that often emerge over many years and converge on the inability of the pancreatic β-cells to secrete enough insulin to meet the demands of target tissues. In clinical practice, absolute insulin deficiency can be detected from the autoimmune destruction of β-cells in type 1 diabetes (T1D), which represents ∼10% of all diabetes cases. Making the diagnosis of T1D is critical for survival, given the therapeutic requirement of exogenous administration of insulin. However, less commonly, hyperglycemia might derive from an inherited or de novo loss of function in a single gene (e.g., monogenic diabetes, comprising 2–3% of all diabetes diagnosed in children or young adults). Diabetes can also appear after pancreatitis or organ transplantation, during pregnancy, or as a result of cystic fibrosis. Most individuals with diabetes, however, are likely to be diagnosed with type 2 diabetes (T2D), which includes defects in one or (more often) multiple physiological pathways (e.g., β-cell insufficiency, fat accumulation or miscompartmentalization, inflammation, incretin resistance, dysfunctional insulin signaling).

Our modern capacity to comprehensively interrogate diverse axes of biology has facilitated the approach of studying an individual to infer general principles, from which a discrete treatment plan is selected. These axes include developmental/metabolic context, genomic variation, chromatin signals that mark genes as active or repressed in tissues, expressed transcripts, biomarkers of disease, and increased knowledge of lifestyle/environmental risk factors. Parallel advances in computational power and analytical methods required to appropriately interrogate “big data” are driving insights that may radically transform the practice of medicine. Yet, at this time, the individual physician often lacks the time and training needed to incorporate these insights into medical decision making. Thus, the translation of the rapidly accumulating new knowledge into practice requires careful evaluation and translational strategies involving specialist training, education, and policy considerations.

The failure to adequately understand the diverse molecular and environmental processes that underlie diabetes and our inability to identify the pathophysiological mechanisms that trigger diabetes in individual patients limit our ability to prevent and treat the disease. Public health strategies have struggled to slow the epidemic, even in countries with the greatest financial and scientific resources. Pharmacological therapies, comprising 12 different drug classes currently approved by the U.S. Food and Drug Administration (FDA), may, at best, control blood glucose and modify disease course but do not provide a cure or result in the remission of disease. Moreover, these agents are sometimes prescribed based on nonmedical considerations (cost, side effects, patient preference, or comorbidities), which may overlook the biological mechanism. Thus, more people are developing diabetes worldwide and have disease progressing to complications, incurring a significant health care burden and cost.

There are, however, several reasons for hope. First, diabetes caused by single gene defects can be characterized and targeted therapies are particularly effective (1,2). Second, islet autoantibody biomarkers and genomic risk have clarified autoimmune diabetes from other forms of the disease (3,4), thereby facilitating immune intervention trials and preonset monitoring to reduce risk of severe complications and aiding in detection of environmental triggers (5). Third, multiple biomarkers and genetic variants have been shown to alter risk of T2D, revealing previously unsuspected biological pathways and providing new targets. Fourth, T2D has been shown to be a complex combination of multiple conditions and processes, defined by process-specific subgroups in which individuals with extreme burdens of risk in particular pathways reside and for whom a specific therapeutic approach may be optimal (6). Finally, the tools, resources, and data now exist to determine the biological and lifestyle/environmental predictors of drug response, as measured by a variety of clinical outcomes (7).