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Emerging Diabetes Research: Prevention, Risk and Management

      Globally, research on type 2 diabetes continues to expand at a whirlwind pace, generating volumes of new science that addresses all levels of the condition. This month, Clinical Therapeutics is profiling 5 examples of emerging diabetes research, including diabetes prevention, evaluation of risk, and disease management. We chose to address these timely topics because of noteworthy presentations that explored them at the 74th Scientific Sessions of the American Diabetes Association in 2014, and the 75th Scientific Sessions are taking place this month.
      A symposium session at the 74th Scientific Sessions, titled “More Than a Gut Feeling—The Role of Gut Bacteria in Diabetes and Obesity,” explored the function of the gut in health and disease, generating significant interest among the audience of diabetes investigators and providers. As this field emerges, we felt it was crucial to have this research thread represented among the journal’s diabetes and endocrinology articles. The 2015 Clinical Therapeutics update of emerging diabetes research features a recent review by van Olden et al
      • van Olden C.
      • Groen A.K.
      • Niewdorp M.
      Role of intestinal microbiome in lipid and glucose metabolism in diabetes mellitus.
      of the current literature examining the contribution of intestinal bacterial strains to human metabolism and obesity, which offers a perspective on the clinical utility of modifying the gut microbiota. This perspective provides a tool for learning about novel mechanisms for preventing diabetes and developing new therapeutic approaches for managing type 2 diabetes from this remarkably rich and independent ecosystem. This team continues to actively push the frontier of our understanding of the interactions between the intestinal microbiota and host metabolism. The communication included in this issue provides a rich context for how the microbiome may reveal therapeutic potential.
      • Nieuwdorp M.
      • Gilijamse P.W.
      • Pai N.
      • Kaplan L.M.
      Role of the microbiome in energy regulation and metabolism.
      The relationship between conditions that produce an inflammatory response and diabetes is often complex and equivocal, complicating the primary and secondary prevention of type 2 diabetes. Alzheimer disease (AD) and gout are 2 important conditions on which to focus in this regard. AD influences patient cognition, which has an essential role in diabetes self-management. A building body of evidence suggests that hyperglycemia contributes to diabetes-like end-organ damage to the brain and that impaired insulin signaling may be a contributing factor in AD.
      • Gispen W.H.
      • Biessels G.J.
      Cognition and synaptic plasticity in diabetes mellitus.
      It has been suggested that AD should be considered “type 3 diabetes”
      • Biessels G.J.
      • Kappelle L.J.
      Increased risk of Alzheimer’s disease in Type II diabetes: insulin resistance of the brain or insulin-induced amyloid pathology?.
      Similarly confounding, gout has been identified for many years as a risk factor for type 2 diabetes, yet patients with type 2 diabetes have a lower risk for gout.
      • Liu Q.
      • Gamble G.
      • Pickering K.
      • et al.
      Prevalence and clinical factors associated with gout in patients with diabetes and prediabetes.
      Gout limits physical activity and creates dietary complexity by considering foods that are high in purine. Furthermore, the management of gout-related arthritis with a corticosteroid may contribute to metabolic-related adverse effects. Colchicine, an oral anti-inflammatory alkaloid agent commonly used for alleviating arthritis-related pain from hyperuricemia—a gout-associated excess of uric acid in the blood—is thought to reduce the risk for type 2 diabetes.
      For inclusion in this month’s Diabetes Update, we selected 2 recently submitted research articles that address AD and gout in relation to type 2 diabetes. These articles are important because they propagate the field for further inquiry. In the first, Ascher-Svanum et al
      • Ascher-Svanum H.
      • Chen Y.-F.
      • Hake A.
      • et al.
      Cognitive and Functional Decline Among Mild Alzheimer’s Disease Dementia Patients With and Without Comorbid Diabetes.
      sought to better understand whether patients with type 2 diabetes experience different rates of cognitive and functional decline compared with patients without diabetes. In a post hoc analysis over an 18-month period, the authors suggest that there is evidence to support the hypothesis that patients with AD and diabetes experience increased rates of cognitive and functional decline compared with patients with AD but without diabetes. Although their data did not produce statistically significant differences between the 2 groups, their effort suggests that there is merit in continuing to pursue a better understanding of end-organ damage to the brain from uncontrolled diabetes and AD. In the second article, which addresses the relationship between diabetes and hyperuricemia, Wang et al
      • Wang L.
      • Sawhney M.
      • Zhao Y.
      • et al.
      The association between colchicine use and risk of diabetes among Veterans Affairs population with gout.
      examine the possible treatment duration and dose-related association between colchicine use and the risk for diabetes in adults with gout. As mentioned earlier, colchicine is an alkaloid agent conventionally used for the treatment of pain associated with arthritis. The authors used propensity scores to match 1046 colchicine-treated US veterans with control patients selected from among 27,876 adults. The authors concluded that although the differences between the 2 groups were not statistically significant, the risk for incident diabetes was reduced with increased duration of colchicine use.
      This year at the 75th Scientific Sessions of the American Diabetes Association, the results from a clinical trial that included >14,700 people aged ≥50 years with type 2 diabetes, heart and circulatory disease, and poorly managed blood glucose will be released. The Trial to Evaluate Cardiovascular Outcomes After Treatment With Sitagliptin (TECOS) was meant to determine whether sitagliptin reduces the risks for myocardial infarction and stroke among people with type 2 diabetes. Sitagliptin is an oral antihyperglycemic agent of the dipeptidyl peptidase (DPP)-4 inhibitor class. Several large-scale drug-specific trials, such as TECOS, were initiated following the US Food and Drug Administration’s 2008 Endocrinologic and Metabolic Drugs Advisory Committee guideline to address the role of cardiovascular assessment in the pre- and postmarketing settings. Previously, trials such as UKPDS (United Kingdom Prospective Diabetes Study), ACCORD (Action to Control Cardiovascular Risk in Diabetes), and ADVANCE (Action in Diabetes and Vascular Disease: Preterax and Diamicron MR Controlled Evaluation) had been powered on glycemic control. TECOS follows several years during which new classes of antidiabetic drugs were introduced, including DPP-4 inhibitors, glucagon-like peptide (GLP)-1 agonists, and sodium-glucose transport protein (SGLT)-2 inhibitors, based on glycemic outcomes.
      The most authoritative diabetes treatment guideline, developed from 2006 and 2009 by the American Diabetes Association and the European Association for the Study of Diabetes, was last updated in 2012 to include DPP-4 inhibitors, GLP-1 inhibitors, and SGLT-2 inhibitors.
      • Patrick A.R.
      • Fischer M.A.
      • Choudhry N.K.
      • et al.
      Trends in insulin initiation and treatment intensification among patients with type 2 diabetes.
      However, this guideline was not informed by the more recent studies generated for examining the cardiovascular-related outcomes associated with these 3 recently introduced treatments. SAVOR-TIMI 53 (Saxagliptin Assessment of Vascular Outcomes Recorded in Patients With Diabetes Mellitus–Thrombolysis in Myocardial Infarction 53) was a Phase IV, multicenter, randomized, double-blind, placebo-controlled trial that evaluated the tolerability and efficacy of the DPP-4 inhibitor saxagliptin in patients with diabetes at risk for cardiovascular events. The findings suggested that saxagliptin contributed to a 27% increase in hospitalization for heart failure, but without an increase in overall cardiovascular impact or total mortality.
      • Scirica B.M.
      • Bhatt D.L.
      • Braunwald E.
      • et al.
      Saxagliptin and cardiovascular outcomes in patients with type 2 diabetes mellitus.
      In a recent systematic review that examined data from published studies and from insurance and hospital databases, Clifton
      • Clifton P.
      Do dipeptidyl peptidase IV (DPP-IV) inhibitors cause heart failure.
      argued that there was evidence to suggest that use of the DPP-4 inhibitors sitagliptin, saxagliptin, and alogliptin may be involved in an increased risk for hospitalization for heart failure, although the author mentions a caveat that more data were required for a more definitive conclusion.
      In this month’s issue of Clinical Therapeutics, Desouza et al
      • Desouza C.V.
      • Gupta N.
      • Patel A.
      Cardiometabolic effects of new class of anti-diabetic agents.
      weigh in on this topic in a review of the effects of recently introduced antidiabetic agents on the prevalence of major adverse cardiac events (MACE), defined as death, Q-wave myocardial infarction, and/or the need for repeat revascularization by repeat coronary artery bypass grafting or repeat percutaneous coronary intervention. In “Cardio-Metabolic Effects of New Classes of Anti-Diabetic Agents,” the author suggests that an examination of published results demonstrates only neutral effects of saxagliptin on heart failure–related hospitalizations, and that the recently introduced antidiabetic agents have potentially beneficial effects on weight, blood pressure, and lipids.
      Finally, an emerging mechanism for managing type 2 diabetes is remote monitoring, typically using the Internet. This month we feature a research report from Katalenich et al,
      • Katalenich B.
      • Shi L.
      • Liu S.
      • et al.
      Evaluation of a Remote Monitoring System for Diabetes Control.
      “Evaluation of a Remote Monitoring System for Diabetes Control.” The authors evaluated a system that employs text messaging or phone calls to remind patients to test blood glucose levels and that reports results using an automated system. Their analyses suggest that glycosylated hemoglobin levels decreased more rapidly over 3 months among patients assigned to the intervention group, although both groups experienced similar decreases at 6 months. From an evaluation of an intervention relying on a Web-based suite of tools to support diabetes self-management, our group found improvements in clinical and health-related quality of life at 12 months, with greater improvements among those patients who engaged with the intervention more frequently than did other patients.
      • Ryan J.G.
      • Schwartz R.
      • Jennings T.
      • et al.
      Feasibility of an Internet-Based Intervention for Improving Diabetes Outcomes among Low-Income Patients with a High Risk for Poor Diabetes Outcomes Followed in a Community Clinic.
      As in the other research we are highlighting this month, this study deserves attention because of the promise of a new model for managing diabetes that it offers clinicians and patients and the variability in results that we are observing in the published literature that explore this research thread.

      References

        • van Olden C.
        • Groen A.K.
        • Niewdorp M.
        Role of intestinal microbiome in lipid and glucose metabolism in diabetes mellitus.
        Clin Ther. 2015; 37: 1172-1177
        • Nieuwdorp M.
        • Gilijamse P.W.
        • Pai N.
        • Kaplan L.M.
        Role of the microbiome in energy regulation and metabolism.
        Gastroenterology. 2014; 146: 1525-1533
        • Gispen W.H.
        • Biessels G.J.
        Cognition and synaptic plasticity in diabetes mellitus.
        Trends Neurosci. 2000; 23: 542-549
        • Biessels G.J.
        • Kappelle L.J.
        Increased risk of Alzheimer’s disease in Type II diabetes: insulin resistance of the brain or insulin-induced amyloid pathology?.
        Biochem Soc Trans. 2005; 33: 1041-1044
        • Liu Q.
        • Gamble G.
        • Pickering K.
        • et al.
        Prevalence and clinical factors associated with gout in patients with diabetes and prediabetes.
        Rheumatology. 2012; 51d: 757-759
        • Ascher-Svanum H.
        • Chen Y.-F.
        • Hake A.
        • et al.
        Cognitive and Functional Decline Among Mild Alzheimer’s Disease Dementia Patients With and Without Comorbid Diabetes.
        Clin Ther. 2015; 37: 1195-1205
        • Wang L.
        • Sawhney M.
        • Zhao Y.
        • et al.
        The association between colchicine use and risk of diabetes among Veterans Affairs population with gout.
        Clin Ther. 2015; 37: 1206-1215
        • Patrick A.R.
        • Fischer M.A.
        • Choudhry N.K.
        • et al.
        Trends in insulin initiation and treatment intensification among patients with type 2 diabetes.
        J Gen Intern Med. 2012; 29: 320-327
        • Scirica B.M.
        • Bhatt D.L.
        • Braunwald E.
        • et al.
        Saxagliptin and cardiovascular outcomes in patients with type 2 diabetes mellitus.
        N Engl J Med. 2013; 369: 1317-1326
        • Clifton P.
        Do dipeptidyl peptidase IV (DPP-IV) inhibitors cause heart failure.
        Clin Ther. 2014; 36: 2072-2079
        • Desouza C.V.
        • Gupta N.
        • Patel A.
        Cardiometabolic effects of new class of anti-diabetic agents.
        Clin Ther. 2015; 37: 1178-1194
        • Katalenich B.
        • Shi L.
        • Liu S.
        • et al.
        Evaluation of a Remote Monitoring System for Diabetes Control.
        Clin Ther. 2015; 37: 1216-1225
        • Ryan J.G.
        • Schwartz R.
        • Jennings T.
        • et al.
        Feasibility of an Internet-Based Intervention for Improving Diabetes Outcomes among Low-Income Patients with a High Risk for Poor Diabetes Outcomes Followed in a Community Clinic.
        Diab Educ. 2013; 39: 365-375