Verapamil and beta cell function in adults with recent-onset type 1 diabetes

Fernando Ovalle, Tiffany Grimes, Guanlan Xu, Anish J Patel, Truman B Grayson, Lance A Thielen, Peng Li, Anath Shalev, Fernando Ovalle, Tiffany Grimes, Guanlan Xu, Anish J Patel, Truman B Grayson, Lance A Thielen, Peng Li, Anath Shalev

Abstract

Pancreatic beta cell loss is a key factor in the pathogenesis of type 1 diabetes (T1D), but therapies to halt this process are lacking. We previously reported that the approved antihypertensive calcium-channel blocker verapamil, by decreasing the expression of thioredoxin-interacting protein, promotes the survival of insulin-producing beta cells and reverses diabetes in mouse models1. To translate these findings into humans, we conducted a randomized double-blind placebo-controlled phase 2 clinical trial ( NCT02372253 ) to assess the efficacy and safety of oral verapamil added for 12 months to a standard insulin regimen in adult subjects with recent-onset T1D. Verapamil treatment, compared with placebo was well tolerated and associated with an improved mixed-meal-stimulated C-peptide area under the curve, a measure of endogenous beta cell function, at 3 and 12 months (prespecified primary endpoint), as well as with a lower increase in insulin requirements, fewer hypoglycemic events and on-target glycemic control (secondary endpoints). Thus, addition of once-daily oral verapamil may be a safe and effective novel approach to promote endogenous beta cell function and reduce insulin requirements and hypoglycemic episodes in adult individuals with recent-onset T1D.

Conflict of interest statement

COMPETING FINANCIAL INTERESTS STATEMENT

None of the authors have any interests to declare.

Figures

Figure 1
Figure 1
Screening, Randomization and Treatment. A schematic diagram illustrating the selection procedure for the enrolled individuals in the study. All participants had been diagnosed with T1D within the last 3 months and continued their standard insulin infusion therapy throughout the trial.
Figure 2
Figure 2
Verapamil Effects on Endogenous Beta cell Function. (a,b) Absolute values (a) and changes from individual baseline values (b) of the mixed meal-stimulated C-peptide area under the curve (AUC) at 0, 3 and 12 months of the trial in all subjects of the verapamil (n = 11) and placebo (n = 13) groups. Means and SE error bars of are shown. For a repeated measures ANOVA: F1,48=4.92, P = 0.0313; 3 months: two-sided Student’s t-test: t22 = −2.37, *P = 0.0270; (ANCOVA F1,23=5.19, P = 0.0334); 12 months: treatment difference 0.28 nmol/L, 95% CI 0.05 to 0.51, two-sided Student’s t-test: t22 =−2.54, *P = 0.0186; (ANCOVA F1,23=4.92, P = 0.0377). For b repeated measures ANOVA: F1,48=4.86, P = 0.0323; 3 months: two-sided Student’s t-test: t22=−2.08, *P = 0.0491; 12 months: treatment difference 35.4%, 95% CI 0.8 to 69.9, two-sided Student’s t-test: t22=−2.12, *P = 0.0451.
Figure 3
Figure 3
Verapamil Effects on Glycemic Control and Insulin Requirements. (a) Mean percent change in total daily dose of insulin (TDDI) during the trial in the verapamil (n = 10) and placebo (n = 13) groups. Error bars show SE. Repeated measures ANOVA: F1,89=4.37, P = 0.0395; 9 months: two-sided Student’s t-test: t16=2.41, *P = 0.0281; 12 months: treatment difference −43%, 95% CI −84 to −1, two-sided Student’s t -test: t17=2.34, *P = 0.0312. (b) Mean values for %HbA1c as measured at 0, 3, 6, 9, and 12 months in the verapamil (n = 11) and placebo (n = 13) groups. (c) Average number of hypoglycemic episodes of blood glucose ≤ 2.2 mmol/L per month in the verapamil (n = 11) as compared to the placebo (n = 11) group. Bars represent means, error bars show SE, dots indicate individual data points. Treatment difference −2.2 events/month, 95% CI −4.2 to −0.1, two-sided Student’s t-test: t20=−2.21, *P = 0.0387. (d) Percent time spent at the target blood glucose range of 3.9–10 mmol/L (grey), above 10 mmol/L (black) or below 3.9 mmol/L (red) as assessed by continuous glucose monitoring in the verapamil (n = 10) and the placebo (n = 11) groups.
Figure 4
Figure 4
Blood Pressure and Heart Rate throughout the Trial. (a-e) Mean values for systolic (a) and diastolic (b) blood pressure (BP), heart rate (c) and EKG-measured QT (d) and PR (e) intervals observed in the verapamil (n = 11) and placebo (n = 13) groups during the 12 month trial. Error bars represent SE.

References

    1. Xu G, Chen J, Jing G & Shalev A Preventing beta-Cell Loss and Diabetes With Calcium Channel Blockers. Diabetes 61, 848–856 (2012).
    1. Davis AK, et al. Prevalence of detectable C-Peptide according to age at diagnosis and duration of type 1 diabetes. Diabetes Care 38, 476–481 (2015).
    1. Liu EH, et al. Pancreatic beta cell function persists in many patients with chronic type 1 diabetes, but is not dramatically improved by prolonged immunosuppression and euglycaemia from a beta cell allograft. Diabetologia 52, 1369–1380 (2009).
    1. Effect of intensive therapy on residual beta-cell function in patients with type 1 diabetes in the diabetes control and complications trial. A randomized, controlled trial. The Diabetes Control and Complications Trial Research Group. Ann Intern Med 128, 517–523 (1998).
    1. Shalev A, et al. Oligonucleotide microarray analysis of intact human pancreatic islets: identification of glucose-responsive genes and a highly regulated TGFbeta signaling pathway. Endocrinology 143, 3695–3698 (2002).
    1. Chen J, et al. Thioredoxin-Interacting Protein Deficiency Induces Akt/Bcl-xL Signaling and Pancreatic Beta Cell Mass and Protects Against Diabetes. FASEB J 22, 3581–3594 (2008).
    1. Chen J, Saxena G, Mungrue IN, Lusis AJ & Shalev A Thioredoxin-Interacting Protein: A Critical Link between Glucose Toxicity and Beta Cell Apoptosis. Diabetes 57, 938–944 (2008).
    1. Minn AH, Hafele C & Shalev A Thioredoxin-interacting protein is stimulated by glucose through a carbohydrate response element and induces beta-cell apoptosis. Endocrinology 146, 2397–2405 (2005).
    1. Minn AH, et al. Gene expression profiling in INS-1 cells overexpressing thioredoxin-interacting protein. Biochem Biophys Res Commun 336, 770–778 (2005).
    1. Chen J, Cha-Molstad H, Szabo A & Shalev A Diabetes Induces and Calcium Channel Blockers Prevent Cardiac Expression of Pro-Apoptotic Thioredoxin-Interacting Protein. Am J Physiol Endocrinol Metab 296, 1133–1139 (2009).
    1. Afzal N, et al. Beneficial effects of verapamil in diabetic cardiomyopathy. Diabetes 37, 936–942 (1988).
    1. Cohn RD, et al. Prevention of cardiomyopathy in mouse models lacking the smooth muscle sarcoglycan-sarcospan complex. J Clin Invest 107, R1–7 (2001).
    1. Xu G, Chen J, Jing G & Shalev A Thioredoxin-interacting protein regulates insulin transcription through microRNA-204. Nat Med (2013).
    1. Jo S, et al. miR-204 Controls Glucagon-Like Peptide 1 Receptor Expression and Agonist Function. Diabetes 67, 256–264 (2018).
    1. Zhou R, Tardivel A, Thorens B, Choi I & Tschopp J Thioredoxin-interacting protein links oxidative stress to inflammasome activation. Nat Immunol 11, 136–140 (2010).
    1. Yin T, Kuo SC, Chang YY, Chen YT & Wang KK Verapamil Use Is Associated With Reduction of Newly Diagnosed Diabetes Mellitus. J Clin Endocrinol Metab 102, 2604–2610 (2017).
    1. Cooper-Dehoff R, et al. Predictors of development of diabetes mellitus in patients with coronary artery disease taking antihypertensive medications (findings from the INternational VErapamil SR-Trandolapril STudy [INVEST]). Am J Cardiol 98, 890–894 (2006).
    1. Cooper-DeHoff RM, et al. Blood pressure control and cardiovascular outcomes in high-risk Hispanic patients--findings from the International Verapamil SR/Trandolapril Study (INVEST). Am Heart J 151, 1072–1079 (2006).
    1. Busch Sorensen M, et al. Influence of short term verapamil treatment on glucose metabolism in patients with non-insulin dependent diabetes mellitus. European journal of clinical pharmacology 41, 401–404 (1991).
    1. Khodneva Y, Shalev A, Frank SJ, Carson AP & Safford MM Calcium channel blocker use is associated with lower fasting serum glucose among adults with diabetes from the REGARDS study. Diabetes Res Clin Pract 115, 115–121 (2016).
    1. Nambam B, Bratina N & Schatz D Immune Interventions for Type 1 Diabetes Mellitus. Diabetes technology & therapeutics 19, S74–S81 (2017).
    1. Alhadj Ali M, et al. Metabolic and immune effects of immunotherapy with proinsulin peptide in human new-onset type 1 diabetes. Science translational medicine 9(2017).
    1. Herold KC, et al. Anti-CD3 monoclonal antibody in new-onset type 1 diabetes mellitus. The New England journal of medicine 346, 1692–1698 (2002).
    1. Aronson R, et al. Low-dose otelixizumab anti-CD3 monoclonal antibody DEFEND-1 study: results of the randomized phase III study in recent-onset human type 1 diabetes. Diabetes Care 37, 2746–2754 (2014).
    1. Pescovitz MD, et al. Rituximab, B-lymphocyte depletion, and preservation of beta-cell function. The New England journal of medicine 361, 2143–2152 (2009).
    1. Pozzilli P, Maddaloni E & Buzzetti R Combination immunotherapies for type 1 diabetes mellitus. Nature reviews. Endocrinology 11, 289–297 (2015).
    1. Greenbaum CJ, et al. Fall in C-peptide during first 2 years from diagnosis: evidence of at least two distinct phases from composite Type 1 Diabetes TrialNet data. Diabetes 61, 2066–2073 (2012).
    1. Hao W, et al. Fall in C-Peptide During First 4 Years From Diagnosis of Type 1 Diabetes: Variable Relation to Age, HbA1c, and Insulin Dose. Diabetes Care 39, 1664–1670 (2016).
METHODS-ONLY REFERENCES
    1. Greenbaum CJ, et al. Mixed-meal tolerance test versus glucagon stimulation test for the assessment of beta-cell function in therapeutic trials in type 1 diabetes. Diabetes Care 31, 1966–1971 (2008).
    1. Palmer JP, et al. C-peptide is the appropriate outcome measure for type 1 diabetes clinical trials to preserve beta-cell function: report of an ADA workshop, 21–22 October 2001. Diabetes 53, 250–264 (2004).
    1. Lachin JM, et al. Sample size requirements for studies of treatment effects on beta-cell function in newly diagnosed type 1 diabetes. PLoS One 6, e26471 (2011).
    1. Moore CG, Carter RE, Nietert PJ & Stewart PW Recommendations for planning pilot studies in clinical and translational research. Clinical and translational science 4, 332–337 (2011).
    1. Li P, Stuart EA & Allison DB Multiple Imputation: A Flexible Tool for Handling Missing Data. JAMA 314, 1966–1967 (2015).

Source: PubMed

3
Subskrybuj