CRCM Journal

Abbreviations: HDL: High Density Lipoproteins; T2DM:Type 2 Diabetes mellitus; BSP: Broccoli Sprout Powder; WHO: World Health Organisation; CDC: Centre for Disease Control and Prevention; FBG: Fasting Blood Glucose; PPBG: Post Prandial Blood Glucose; HbA1c: Glycosylated haemoglobin; TC: Total Cholesterol; LDL: Low Density Lipoprotein; VLDL: Very Low Density Lipoprotein; HDL: High Density Lipoprotein; PCS: Physical Component Summary; MCS: Mental Component Summary; BMI: Body Mass Index; SGOT: Serum Glutamic Oxaloacetic Transaminase; SGPT: Serum Glutamic Pyruvic Transaminase; ARE: Antioxidant Responsive Element; CVD: Cardiovascular Disease; SFN: Sulforaphane

Introduction

Lifestyle disorders such as metabolic syndrome refer to a cluster of conditions such as high blood pressure, high blood sugar, high triglyceride levels, excess body fat around the waist and low HDL, that increase the chances of Type 2 Diabetes Mellitus (T2DM), cardiovascular disease and stroke [1,2]. Risk of long term complications associated with T2DM increases with prevalence of hypertension and obesity which are common comorbidities in adults with T2DM [3]. Chronic hyperglycaemia is also associated with atherosclerosis, and cardiovascular diseases are the leading cause of mortality worldwide [4,5]. The comorbidity burden is further impacted by poor nutritional status as observed in a cohort study with obese Asian population [6]. With an increase in diet and lifestyle related disorders, the concept of functional foods has emerged with inclusion of phytochemicals in the daily diet [7]. Functional foods provide additional physiological benefits in addition to their nutritional profile [8].Various in vitro, in vivo, and clinical studies have been conducted to understand the role and significance of functional foods with respect to micronutrient as well as bioactive composition. In addition to whole grains, legumes and nuts, vegetables and fruits rich in phytochemicals and antioxidants have also been explored [9].

Cruciferous vegetables, such as broccoli, cabbage, kale etc have been shown to be powerhouses of chemoprotective agents and other micronutrients [10]. Broccoli contains glucosinolates, the precursors of bioactive isothiocyanates. One of the wellstudied isothiocyanates, sulforaphane is formed from a precursor glucosinolate molecule, glucoraphanin via enzymatic reaction in the presence of myrosinase. In broccoli plant cells glucoraphanin and myrosinase are in two different compartments and in presence of water or by chewing both come in contact leading to formation of sulforaphane [11,12]. Sprouts of broccoli contain 20-50 times higher glucosinolates than mature broccoli [13-15]. The beneficial antioxidant effect of broccoli sprout consumption is well elucidated. In a study involving administration of sulforaphane, up-regulation of glutathione system by phase 2 enzyme inducers in in aortic smooth muscle cells from spontaneously hypertensive rats was observed [16]. Similarly, administration of 200mg per day of dried broccoli sprouts to rats, showed significant improvement in oxidative stress markers in cardiovascular and kidney tissues [17].

Human clinical studies demonstrate some of the health benefits of broccoli sprouts, sprout powders and extracts. In a study evaluating the effect of consumption of 100 grams of broccoli sprouts in 12 subjects for a duration of one week, an improvement in cholesterol biomarkers was observed [18]. A study with 63 diabetic subjects observed significant reduction of oxidative stress markers upon consumption of 5-10g of broccoli sprout powder for four weeks [19].Similarly, effect of 5-10g of broccoli sprout powder in 72 diabetic adults was evaluated and favourable changes in lipid profile markers within the study groups were observed [20]. Overall, from several short term studies, health benefits of broccoli sprout consumption are evident. These studies have largely been conducted in smaller study groups for shorter duration of time. Here, we aimed to evaluate efficacy of long term consumption (12 weeks) of broccoli sprout powder (BSP) on blood glucose and lipid biomarkers in target population at risk of metabolic disorder.

Materials and methods

Subjects and Study Design

The study was randomised, double blind and placebo controlled. The study was approved by independent ethics committees and registered with Clinical Trials Registry India (CTRI/2016/05/006977). Both males and females in the age group 18-60 years were included as subjects in the study. Subjects with history of thyroid diseases, HIV, cancer, smoking and alcohol consumption were excluded from the study. All subjects provided written informed consent to participate in the study prior to being screened. A total of 288 subjects from India, were enrolled in the study. Subjects were distributed across three groups to include metabolic syndrome risk factors of elevated glucose, obesity and elevated triglycerides, since most previous studies have focused on either healthy or diabetic subjects. Cut off levels as defined by WHO and CDC were used. Group A comprised of hyperglycaemic subjects with elevated fasting and post prandial blood glucose levels i.e. ≥ 130mg/dl and ≥200mg/dl respectively. Group B comprised of overweight and obese subjects with BMI in the range of 25 – 35 kg/m2 and Group C com-prised of dyslipidaemic subjects with elevated fasting triglyceride levels i.e. ≥ 150mg/dl. A total of 96 subjects were recruited into each study group and further sub grouped into test and placebo arms. The study duration was 12 weeks. All laboratory assessments were carried out at baseline and end of treatment.

Intervention

Each test capsule contained 200mg of commercially procured broccoli sprout powder and placebo capsule comprised of equivalent quantity of maltodextrin. Each arm received either test or placebo capsules to be consumed as two capsules at a time before meal.

Laboratory assessments

All laboratory assessments were carried out at baseline and end of treatment visits. Subjects were tested for fasting and post prandial blood glucose (FBG and PPBG respectively), glycosylated haemoglobin (HbA1c), lipid profile (triglycerides, total cholesterol TC, Low density lipoprotein LDL, Very low density lipoprotein VLDL, High density lipoprotein HDL) Physical and Mental Component Summary (PCS and MCS respectively as measured by Quality of life questionnaire SF-36), Anthropometry (Body Mass Index BMI, waist and hip circumference, body weight), Renal Function Test (Creatinine, urea, blood urea nitrogen, Sodium, Potassium and Chloride), Liver Function Test (Alkaline Phosphatase ALP, Bilirubin, Albumin, serum glutamic oxaloacetic transaminase SGOT, serum glutamic pyruvic transaminase SGPT) and Vitals (pulse rate, respiratory rate, blood pressure, temperature).

Statistical analyses

SAS software version 9.1 was used for the statistical analysis. The sample size considered 5% significance level and 80 % power. The difference within the group was assessed using paired t-test. The difference between the groups was assessed using independent t-test.

Results

The details on study participation are shown in (Figure 1). Of the 96 subjects enrolled in each group, 84 subjects completed the study in Group A (42 each in test and placebo), 92 subjects completed the study in Group B (46 each in test and placebo) and 89 subjects completed the study in Group C (45 in test and 44 in placebo arms). (Table 1) shows the demographic details of study subjects. The average age of subjects across groups was similar, ranging from 47 - 48 years in Group A, 44 - 46 years in Group B and 47 - 48 years in Group C. The average weight of subjects in group B test arm was 75.7 kgs and in placebo arm was 73.9 kgs which was slightly higher than groups A and C where average weight of subjects in test arm was 72.6 and 70.1 kgs respectively and average weight of subjects in placebo arms was 72.9 and 71.1 kgs respectively. Similarly, the BMI of subjects across groups was in overweight range. The BMI of subjects in group B test arm was 29.8 kg/m2 and in placebo arm was 29.7 kg/m2 which was slightly higher than groups A and C where average BMI of subjects in test arm was 27.8 and 28.1 kg/m2 respectively and average weight of subjects in placebo arms was 28.6 and 28.2 kg/m2 respectively. Waist circumference and hip circumference were in similar range for subjects across all groups.

Figure 1: shows the flow chart of study participation

Table 1: Demographic details of subjects in Groups A, B and C Table 2 shows the values of assessment parameters at the baseline and end of treatment in test and placebo arms of Group A comprising of hyperglycaemic subjects. A significant reduction in PPBG was observed between test and placebo arms (p=0.0327). Additionally, LDL and PCS also showed a significant improvement in test arm compared to placebo arm (p=0.0232, 0.0051 respectively). Other parameters such as HbA1c, TG, TC, HDL and VLDL showed improvement in the test arm when compared to placebo arm, however, these changes were not statistically significant. Table 2 shows the change in outcome measures from baseline to end of treatment (EoT) in Group A study subjects.

Table 2: Efficacy outcome measures of subjects in group A

Table 3 shows the values of assessment parameters at the baseline and end of treatment in test and placebo arms of Group B comprising of overweight subjects. While placebo arm showed an increase in BMI between baseline and end of treatment, test arm showed a significant reduction within test arm between baseline and end of treatment (p=0.0029). However, this reduction was not significant when compared to placebo arm. A significant reduction in FBG, TG and LDL was observed in test arm compared to placebo arm. Significant improvement in HDL was also observed in test arm compared to placebo arm. Other parameters such as PPBG, HbA1c, TC, VLDL also showed reduction in test arm compared to placebo arm, however, these changes were not statistically significant. Table 3 shows the change in outcome measures from baseline to end of treatment (EoT) in Group B study subjects.

Table 3: Efficacy outcome measures of subjects in group B

Table 4 shows the values of assessment parameters at the baseline and end of treatment in test and placebo arms of Group C comprising of dyslipidaemic subjects. A significant reduction in TC between test and placebo arms was observed (p=0.0206). Additionally, FBG, PPBG and HbA1c also showed significant reduction in test arm compared to placebo arm. Significant improvement in PCS was also observed in test arm compared to placebo arm. Other parameters such as TG, LDL, and VLDL also showed reduction in test arm compared to placebo arm, however, these changes were not statistically significant. Table 4 shows the change in outcome measures from baseline to end of treatment (EoT) in Group C study subjects.

Table 4: Efficacy outcome measures of subjects in group C 

BSP showed no significant change in safety parameters between test and placebo arms across groups, as shown in (Table 5).

Table 5: Renal function and liver parameters of groups A, B and C

Discussion

Metabolic disorders such as dyslipidemia, diabetes mellitus, obesity and hypertension tend to co-exist and are most often associated with one another thus implying that one condition may act as a potential risk factor for emergence of another condition [21-24]. This was also observed in a prospective observational study which showed that long term exposure to glycaemia impacted cardiovascular complications in T2DM patients. For every 1% reduction in HbA1c, a 14% reduction in risk of myocardial infarction and 37% reduction in risk of microvascular complications was observed [25]. Similarly, diabetes and hypertension were found to be associated with a significant increase in risk of cardiovascular diseases [26]. Additionally, effect of obesity on cardiovascular disease was also elaborated in a Mendelian randomisation analysis study which indicates the significance of obesity reduction in reducing risk of CVD through management of downstream metabolic disorders such as diabetes and hypertension [27]. A prospective cohort study showed that obesity is the central feature of metabolic syndrome wherein, BMI was identified as a common risk factor in both men and women [28]. These studies elucidate the co-existential nature of health conditions associated with metabolic disorders. Similar observations were made in our study wherein subjects with elevated triglycerides or fasting blood glucose also had higher BMI.

Management of health conditions such as diabetes has been addressed through multiple routes including nutrition and dietary interventions, lifestyle modifications and medication among others. Nutraceuticals as described by DeFelice refer to a food or part of a food, which can be of vegetal or animal origin that has a beneficial pharmaceutical activity beyond its nutritional value [29]. In addition to efficacy, safety of nutraceutical compositions is of utmost importance and most regulations ensure that rigorous safety and toxicity studies are met before a product reaches the consumer. For instance, nutraceuticals such as berberine, cocoa flavonoids, coenzyme Q etc are commonly used as co-adjuvants in management of diabetes and hypertension conditions and have well established safety data [30]. Similarly, ingredient such as cinnamon at recommended dosages is implicated in beneficial effects of weight management and diabetes and only at higher levels, presence of coumarin in spices such as cassia and cinnamon can be a safety concern [31-34]. In previous short term studies involving consumption for 1 – 4 weeks, BSP has been shown to be safe and efficacious. In a study with 12 healthy volunteers, the authors studied safety and metabolism of an equivalent of 12.6 – 50.4 grams of broccoli sprouts for a duration of 7 days and found no significant subjective or objective toxicities associated with its consumption [35]. Our study extends this finding wherein long term consumption of BSP for 12 weeks did not have any significant effects of safety parameters.