Effect of metformin on blood pressure in patients with hypertension: a randomized clinical trial

Metformin Monotherapy With and Without Lifestyle Changes Affects Anthropometric Parameters, Blood Pressure, Blood Glucose, and Lipid Profile in Indian Patients With Newly Diagnosed Type 2 Diabetes

INTRODUCTION

Type 2 diabetes mellitus (T2DM) is a consequence of insulin resistance, insulin deficiency, or both. It is usually seen in adults and is a consequence of genetic (polygenic inheritance), endogenous (obesity and or hormonal factors), and environmental factors (e.g., obesogenic environment, endocrine disrupting chemicals, stress, and medicines). The prevalence of T2DM has increased over the past few decades. South Asians, including Indians, are more prone to central adiposity and develop lifestyle diseases like T2DM at body mass index values lower than those considered normal for the Western population. Generally, the first line of treatment is metformin monotherapy with lifestyle changes in patients with T2DM. Most of the research conducted on this drug is on Western subjects. Since the Indian population has genetic differences in the site of deposition of adipose and is more prone to develop lifestyle diseases, the effect of metformin may be different in Indians.

METHODS

Seventy-one (34 female, non-pregnant, non-lactating) adults with newly diagnosed T2DM were recruited in this short-duration pilot study after obtaining written informed consent. Patients regularly taking any drug were excluded, as were patients with chronic comorbidities. Treatment was initiated with metformin 500 mg OD. Lifestyle changes were recommended according to the age and physical condition of the patients. Anthropometric parameters (age, weight, height, BMI, waist-to-hip ratio (WHR), and waist-to-height ratio (WHtR)), blood pressure, glycemic status (fasting and 2 h PP glucose and HbA1c), and lipid profile of the subjects were recorded before initiating and six months after initiating metformin monotherapy with lifestyle changes.

RESULTS

Small but statistically significant improvements were observed in the WHR,WHtR, blood pressure, blood glucose, and glycated hemoglobin. Although improvement was also observed in weight and lipid profile, these changes were not statistically significant.

CONCLUSION

This study shows that metformin monotherapy with lifestyle changes is suitable for patients of Indian origin and results in improvement in the WHR, WHtR, blood pressure, plasma glucose, and glycated hemoglobin.

Metformin reduces insulin resistance and attenuates progressive renal injury in prepubertal obese Dahl salt-sensitive rats

Prepubertal obesity is currently an epidemic and is considered as a major risk factor for renal injury. Previous studies have demonstrated that insulin resistance contributes to renal injury in obesity, independent of diabetes. However, studies examining the relationship between insulin resistance and renal injury in obese children are lacking. Recently, we reported that progressive renal injury in Dahl salt-sensitive (SS) leptin receptor mutant (SSLepRmutant) rats was associated with insulin resistance before puberty. Therefore, the aim of the present study was to examine whether decreasing insulin resistance with metformin will reduce renal injury in SSLepRmutant rats. Four-wk-old SS and SSLepRmutant rats were separated into the following two groups: 1) vehicle and 2) metformin (300 mg/kg/day) via chow diet for 4 wk. Chronic administration of metformin markedly reduced insulin resistance and dyslipidemia in SSLepRmutant rats. We did not detect any differences in mean arterial pressure between vehicle and metformin-treated SS and SSLepRmutant rats. Proteinuria was significantly greater in SSLepRmutant rats versus SS rats throughout the study, and metformin administration significantly reduced proteinuria in SSLepRmutant rats. At the end of the protocol, metformin prevented the renal hyperfiltration observed in SSLepRmutant rats versus SS rats. Glomerular and tubular injury and renal inflammation and fibrosis were significantly higher in vehicle-treated SSLepRmutant rats versus SS rats, and metformin reduced these parameters in SSLepRmutant rats. These data suggest that reducing insulin resistance with metformin prevents renal hyperfiltration and progressive renal injury in SSLepRmutant rats before puberty and may be therapeutically useful in managing renal injury during prepubertal obesity.NEW & NOTEWORTHY Childhood/prepubertal obesity is a public health concern that is associated with early signs of proteinuria. Insulin resistance has been described in obese children. However, studies investigating the role of insulin resistance during childhood obesity-associated renal injury are limited. This study provides evidence of an early relationship between insulin resistance and renal injury in a rat model of prepubertal obesity. These data also suggest that reducing insulin resistance with metformin may be renoprotective in obese children.

Prestroke Metformin Use on the 1-Year Prognosis of Intracerebral Hemorrhage Patients with Type 2 Diabetes

Background

Although recent studies have focused on the use of metformin in treating ischemic stroke, there is little literature to support whether it can treat intracerebral hemorrhage (ICH). Therefore, this study is aimed at evaluating the possible effects of prestroke metformin (MET) on ICH patients with type 2 diabetes.

Methods

From January 2010 to December 2019, all first-ever ICH patients with type 2 diabetes from our hospitals were included. All discharged patients would receive a one-time follow-up at 1 year after admission. Death, disability, and recurrence events were recorded.

Results

We included 730 patients for analysis (the median age: 65 [IQR, 56-72] years and 57.7% was men). Of those patients, 281 (38.5%) had received MET before ICH (MET+), whereas 449 (61.5%) had not (MET−). MET (+) patients had a lower median baseline hematoma volume than did MET (-) patients (9.6 ml [IQR, 5.3-22.4 ml] vs. 14.7 ml [IQR, 7.9-28.6 ml]; P < 0.001). The inhospital mortality events were not significantly reduced in the MET (+) group compared with the MET (-) group (6.4% vs 8.9%, respectively; absolute difference, −2.5% [95% CI, −3.9% to −0.7%]; OR, 0.70 [95% CI, 0.39 to 1.27]; P = 0.22). The 1-year mortality events were not significantly reduced in the MET (+) group compared with the MET (-) group (14.1% vs 17.4%, respectively; absolute difference, −3.3% [95% CI, −5.1% to −1.8%]; OR, 0.73 [95% CI, 0.47 to 1.14]; P = 0.16). The 1-year disability events were not significantly reduced in the MET (+) group compared with the MET (-) group (28.4% vs 34.1%, respectively; absolute difference, −5.7% [95% CI, −8.2% to −3.3%]; OR, 0.77 [95% CI, 0.52 to 1.13]; P = 0.18). Finally, the recurrence rates in those two groups were not significantly different (MET [+] vs. MET [-]: 6.4% vs. 5.9%; absolute difference, 0.5% [95% CI, 0.2% to 1.3%]; OR, 1.08 [95% CI, 0.51 to 2.28]; P = 0.84).

Conclusions

Pre-ICH metformin use was not associated with inhospital mortality and 1-year prognosis in diabetic ICH patients.

Pharmacokinetic Interaction between Metformin and Verapamil in Rats: Inhibition of the OCT2-Mediated Renal Excretion of Metformin by Verapamil

The incidence of hypertension in diabetic patients has been increasing and contributing to the high mortality of diabetic patients. Recently, verapamil use was found to lower fasting blood glucose levels in diabetic patients, which led to a new indication of verapamil as combination treatment with anti-diabetic agents such as metformin. As pharmacokinetic (PK) interaction can affect drug efficacy and safety in drug combination, their PK-based interaction is recommended to be evaluated in preclinical levels as well as clinical levels. In case of metformin and verapamil, organic cation transporter (OCT) 1 and 2 primarily mediate metformin distribution to the liver and its elimination into urine, whereas cytochrome P450 is responsible for the hepatic metabolism of verapamil. Verapamil is also known as a potential OCT2 inhibitor. Thus, PK interaction between metformin (30 mg/kg) and verapamil (20 mg/kg) were investigated after their simultaneous administration to rats. In our results, verapamil inhibited the OCT2-mediated renal excretion of metformin, subsequently leading to increase of the systemic exposure of metformin. In contrast, metformin did not influence the pharmacokinetic pattern of verapamil. Although the further clinical investigation is required, our finding suggests a possibility of OCT2-mediated interaction of metformin and verapamil.

Endothelial dysfunction and inflammatory biomarkers as a response factor of concurrent coenzyme Q10 add-on metformin in patients with type 2 diabetes mellitus

OBJECTIVES

The objective of the study was to evaluate the effect of metformin alone or in combination with coenzyme Q10 (CoQ10) on inflammatory changes and endothelial dysfunction in patients with type 2 diabetes mellitus (T2DM).

MATERIALS AND METHODS

A total numbers of 54 patients with T2DM compared to 30 healthy subjects were divided into three groups: Group A (n = 30): healthy subjects without any medications; Group B (n = 24): T2DM patients treated with metformin 1 g/day; and Group C (n = 30): T2DM patients treated with metformin 1 g/day plus CoQ10, 300 mg/day. The duration of the study was 8 weeks. Fasting blood glucose, glycated hemoglobin, lipid profile, blood pressure variables, fasting insulin, insulin resistance, homeostatic model assessment of insulin resistance, vascular cell adhesion molecule 1 (VCAM-1), and E-selectin were measured before and after therapy.

RESULTS

Metformin and/or CoQ10 therapy illustrated an insignificant effect on the fody mass index. This combination produced a significant improvement of metabolic changes in patients with T2DM (P < 0.01). sVCAM-1 serum level was decreased significantly after the initiation of metformin and/or CoQ10 therapy compared to the baseline P < 0.05. E-selectin was declined significantly following metformin monotherapy and after metformin plus CoQ10 therapy (P = 0.0001).

CONCLUSION

CoQ10 add-on metformin therapy improves endothelial dysfunction and inflammatory changes in patients with T2DM alongside with amelioration of metabolic profile.

Head-to-head comparison of inorganic nitrate and metformin in a mouse model of cardiometabolic disease

BACKGROUND/PURPOSE

Unhealthy dietary habits contribute to the increasing incidence of metabolic syndrome and type 2 diabetes (T2D), which is accompanied by oxidative stress, compromised nitric oxide (NO) bioavailability and increased cardiovascular risk. Apart from lifestyle changes, biguanides such as metformin are the first-line pharmacological treatment for T2D. Favourable cardiometabolic effects have been demonstrated following dietary nitrate supplementation to boost the nitrate-nitrite-NO pathway. Here we aim to compare the therapeutic value of inorganic nitrate and metformin alone and their combination in a model of cardiometabolic disease.

EXPERIMENTAL APPROACH

Mice were fed control or high fat diet (HFD) for 7 weeks in combination with the NO synthase (NOS) inhibitor l-NAME to induce metabolic syndrome. Simultaneously, the mice were treated with vehicle, inorganic nitrate, metformin or a combination of nitrate and metformin in (drinking water). Cardiometabolic functions were assessed in vivo and tissues were collected/processed for analyses.

KEY RESULTS

HFD + L-NAME was associated with cardiometabolic dysfunction, compared with controls, as evident from elevated blood pressure, endothelial dysfunction, impaired insulin sensitivity and compromised glucose clearance as well as liver steatosis. Both nitrate and metformin improved insulin/glucose homeostasis, whereas only nitrate had favourable effects on cardiovascular function and steatosis. Mechanistically, metformin and nitrate improved AMPK signalling, whereas only nitrate attenuated oxidative stress. Combination of nitrate and metformin reduced HbA1c and trended to further increase AMPK activation.

CONCLUSION/IMPLICATIONS

Nitrate and metformin had equipotent metabolic effects, while nitrate was superior regarding protection against cardiovascular dysfunction and liver steatosis. If reproduced in future clinical trials, these findings may have implications for novel nutrition-based strategies against metabolic syndrome, T2D and associated complications.

Achieving Rapid Blood Pressure Control With Digital Therapeutics: Retrospective Cohort and Machine Learning Study

BACKGROUND

Behavioral therapies, such as electronic counseling and self-monitoring dispensed through mobile apps, have been shown to improve blood pressure, but the results vary and long-term engagement is a challenge. Machine learning is a rapidly advancing discipline that can be used to generate predictive and responsive models for the management and treatment of chronic conditions and shows potential for meaningfully improving outcomes.

OBJECTIVE

The objectives of this retrospective analysis were to examine the effect of a novel digital therapeutic on blood pressure in adults with hypertension and to explore the ability of machine learning to predict participant completion of the intervention.

METHODS

Participants with hypertension, who engaged with the digital intervention for at least 2 weeks and had paired blood pressure values, were identified from the intervention database. Participants were required to be ≥18 years old, reside in the United States, and own a smartphone. The digital intervention offers personalized behavior therapy, including goal setting, skill building, and self-monitoring. Participants reported blood pressure values at will, and changes were calculated using averages of baseline and final values for each participant. Machine learning was used to generate a model of participants who would complete the intervention. Random forest models were trained at days 1, 3, and 7 of the intervention, and the generalizability of the models was assessed using leave-one-out cross-validation.

RESULTS

The primary cohort comprised 172 participants with hypertension, having paired blood pressure values, who were engaged with the intervention. Of the total, 86.1% participants were women, the mean age was 55.0 years (95% CI 53.7-56.2), baseline systolic blood pressure was 138.9 mmHg (95% CI 136.6-141.3), and diastolic was 86.2 mmHg (95% CI 84.8-87.7). Mean change was -11.5 mmHg for systolic blood pressure and -5.9 mmHg for diastolic blood pressure over a mean of 62.6 days (P<.001). Among participants with stage 2 hypertension, mean change was -17.6 mmHg for systolic blood pressure and -8.8 mmHg for diastolic blood pressure. Changes in blood pressure remained significant in a mixed-effects model accounting for the baseline systolic blood pressure, age, gender, and body mass index (P<.001). A total of 43% of the participants tracking their blood pressure at 12 weeks achieved the 2017 American College of Cardiology/American Heart Association definition of blood pressure control. The 7-day predictive model for intervention completion was trained on 427 participants, and the area under the receiver operating characteristic curve was .78.

CONCLUSIONS

Reductions in blood pressure were observed in adults with hypertension who used the digital therapeutic. The degree of blood pressure reduction was clinically meaningful and achieved rapidly by a majority of the studied participants. Greater improvement was observed in participants with more severe hypertension at baseline. A successful proof of concept for using machine learning to predict intervention completion was presented.