|Year : 2021 | Volume
| Issue : 1 | Page : 46-57
Design and methodology of a randomized crossover trial to test the effect of low and high dAGE diets on metabolic risk factors and inflammatory markers among overweight and centrally obese Asian Indian adults
Mookambika Ramya Bai1, Srinivasan Vedantham2, Shanmugam Shobana3, Lakshmi Priya Nagarajan3, Gayathri Rajagopal3, Geetha Gunasekaran3, Gayathri Nagamuthu3, Anitha Chandrashekaran3, Kuppan Gokulakrishnan4, Narasimhan Sandhya3, Bhaskaran Sarojam Regin5, Ramajeevan Ganeshjeevan3, Balasubramanyam Muthuswamy5, Ranjit Mohan Anjana6, Ranjit Unnikrishnan6, Kamala Krishnaswamy3, Viswanathan Mohan6, Vasudevan Sudha3
1 Department of Food Nutrition and Dietetics Research, Madras Diabetes Research Foundation (MDRF), Dr. Mohan’s Diabetes Specialities Centre, WHO Collaborating Centre for Non-Communicable Diseases, Chennai, Tamil Nadu, India; Department of Biotechnology, Sastra University, Tanjavore, Tamil Nadu, India
2 Operations, MedGenome Labs Ltd, Bengaluru, Karnataka, India
3 Department of Food Nutrition and Dietetics Research, Madras Diabetes Research Foundation (MDRF), Dr. Mohan’s Diabetes Specialities Centre, WHO Collaborating Centre for Non-Communicable Diseases, Chennai, Tamil Nadu, India
4 Department of Neurochemistry, National Institute of Mental Health and Neurosciences (NIMHANS), Bengaluru, Karnataka, India; Department of Research Biochemistry, Madras Diabetes Research Foundation (MDRF), Dr. Mohan’s Diabetes Specialities Centre, WHO Collaborating Centre for Non-Communicable Diseases, Chennai, Tamil Nadu, India
5 Department of Cell and Molecular Biology, Madras Diabetes Research Foundation (MDRF), Dr. Mohan’s Diabetes Specialities Centre, WHO Collaborating Centre for Non-Communicable Diseases, Chennai, Tamil Nadu, India
6 Department of Diabetology, Madras Diabetes Research Foundation (MDRF), Dr. Mohan’s Diabetes Specialities Centre, WHO Collaborating Centre for Non-Communicable Diseases, Chennai, Tamil Nadu, India
|Date of Submission||23-Apr-2020|
|Date of Decision||19-May-2020|
|Date of Acceptance||08-Jul-2020|
|Date of Web Publication||25-Dec-2020|
Ms. Vasudevan Sudha
Department of Foods, Nutrition and Dietetics Research, Madras Diabetes Research Foundation & Dr. Mohan’s Diabetes Specialities Centre, WHO Collaborating Centre for Non-Communicable Diseases, ICMR Centre for Advanced Research on Diabetes, International Diabetes Federation (IDF) Centre of Excellence in Diabetes, 4, Conran Smith Road, Gopalapuram, Chennai 600086, Tamil Nadu.
Source of Support: None, Conflict of Interest: None
Background: Heat processing of foods accelerates the formation of advanced glycation end products (AGEs). Dietary AGEs (dAGEs) could exacerbate the risk for diabetes, by adversely affecting glucose metabolism. Asian Indian diets have not been evaluated for AGEs and their effect on metabolic risk factors. Objective: As a proof of concept, we report the dAGE content of Indian foods to further plan the design and methodology of a study that would evaluate the effect of high and low dAGE diets on metabolic risk factors such as insulin resistance, glycemia, lipid profile, and inflammatory markers in overweight and centrally obese Indian adults without diabetes. Materials and Methods: This randomized crossover trial includes 50 overweight and centrally obese adults aged 25–45 years with body mass index (BMI) ≥23 kg/m2 and waist circumference (WC) ≥90cm in men and ≥80cm in women. Participants will be provided 12 weeks each of low and high dAGE diets (with the dAGE content being measured by enzyme-linked immunosorbent assay), matched for calories and macronutrients with a 2-week washout period in between the two diets. Low dAGE diets use steaming, boiling, and pressure cooking compared to deep frying, stir frying, and roasting in high dAGE diets. Biochemical measures will be assessed both at baseline and the end of each diet using standard protocols. The difference in outcome measures will be evaluated (analysis of variance and paired t test) using SAS (version 9.2). Results: The dAGE content was found to be 49709 ± 5239 vs. 26178 ± 4327 mg/day (mean ± standard deviation [SD]) in high and low dAGE diets, respectively (P < 0.001). Baseline demographic and biochemical characteristics did not differ between low and high dAGE diet interventions. Conclusion: The study trial will throw light on the effect of high and low dAGE diets on metabolic risk factors in overweight and centrally obese Indian adults, potentially leading to a novel dietary strategy to prevent diabetes in this population.
Keywords: Cooking methods, diabetes, dietary AGEs, disposition index, inflammation
|How to cite this article:|
Ramya Bai M, Vedantham S, Shobana S, Nagarajan LP, Rajagopal G, Gunasekaran G, Nagamuthu G, Chandrashekaran A, Gokulakrishnan K, Sandhya N, Regin BS, Ganeshjeevan R, Muthuswamy B, Anjana RM, Unnikrishnan R, Krishnaswamy K, Mohan V, Sudha V. Design and methodology of a randomized crossover trial to test the effect of low and high dAGE diets on metabolic risk factors and inflammatory markers among overweight and centrally obese Asian Indian adults. J Diabetol 2021;12:46-57
|How to cite this URL:|
Ramya Bai M, Vedantham S, Shobana S, Nagarajan LP, Rajagopal G, Gunasekaran G, Nagamuthu G, Chandrashekaran A, Gokulakrishnan K, Sandhya N, Regin BS, Ganeshjeevan R, Muthuswamy B, Anjana RM, Unnikrishnan R, Krishnaswamy K, Mohan V, Sudha V. Design and methodology of a randomized crossover trial to test the effect of low and high dAGE diets on metabolic risk factors and inflammatory markers among overweight and centrally obese Asian Indian adults. J Diabetol [serial online] 2021 [cited 2021 Jan 25];12:46-57. Available from: https://www.journalofdiabetology.org/text.asp?2021/12/1/46/304349
| Introduction|| |
Glycotoxins are a diverse group of highly oxidant compounds, which have been shown in vivo to increase the risk of many chronic diseases, including diabetes and cardiovascular disease (CVD)., This is of particular relevance to India, which is currently battling a growing epidemic of obesity-related chronic diseases such as diabetes.,
Advanced glycation end products (AGEs) are a group of glycotoxins formed when foods are heated by Maillard reactions where aldehydes bind with amines or amides. Though all free amino acids can form AGEs, lysine and arginine are the predominant amino acids involved in AGE formation within proteins. Dietary AGEs (dAGEs) are similar in structure, and function almost identically, to endogenous AGEs, and are therefore important contributors to the body’s AGE pool.
During food preparation, nutrients such as carbohydrate, protein, and fat could interact and react to form AGEs. Many studies have reported that restriction of dAGEs prevents vascular and kidney dysfunction,, diabetes (type 1 or type 2), improves insulin sensitivity, and also reduces markers of oxidative stress and inflammation in healthy and overweight individuals. Many western studies have been conducted with the representative AGE compound Ne-carboxymethyl lysine (CML), a low molecular weight AGE that might be absorbed from the gut and contribute to the endogenous pool of AGEs in the body.
Asian Indian cuisine varies considerably by region. There are various cooking methods used in the preparation of Indian foods, which include steaming, boiling, frying (deep-frying, and shallow frying), and baking, many of which could result in amplified levels of AGEs., The factors that could influence AGE formation as reported in various studies are as follows: composition of food availability of pro- and antioxidants, cooking period, cooking temperature, reactant concentration, presence of moisture, and pH.
A meta-analysis of 17 randomized controlled trials by Baye et al. has shown that low AGE diets can reduce cardiometabolic risk factors such as insulin resistance, adverse lipid profile, and markers of inflammation and oxidative stress. Ever as Uribarri et al. launched dAGE database describing the AGE content of 549 foods, several investigators worldwide have been continuously using and expanding this database, and very recent studies do attest that consumption of diets with low AGEs improve cardiometabolic health.,,
There exists a paucity of information on the AGE content of Indian foods. Although Asian Indians are highly prone to insulin resistance, diabetes, and CVD, there is a complete paucity of research as well as intervention trials on dAGEs in relation to Indian diets. It is therefore important to understand the levels of AGEs in Indian diets and to evaluate the effect of low and high dAGE diets on metabolic risk factors so that nutrition-based strategies incorporating AGE levels could be suggested for effective prevention of diabetes and other obesity-related disorders. Therefore, we made an attempt to evaluate the AGE content of commonly consumed Indian foods and proposed conducting a structured randomized crossover trial with low and high dAGE diets in overweight and centrally obese Indian adults to assess the metabolic markers such as insulin resistance, glycemia, lipid profile, and inflammatory markers.
Here, we describe the design and methodology of our study to plan low and high dAGE diets in a randomized crossover trial as a proof-of-concept, and present the results of the assessment of the dAGE content of commonly consumed Indian foods.
| Materials and Methods|| |
The study is a isocaloric, macronutrient matched 3-month randomized cross over single-blinded design to compare the effects of low vs. high AGE diets for three meals a day for 6 days per week with a 2-week washout period in between diets [Figure 1]. The meal planning for this study has been considered keeping in mind the local cultural preferences and the frequently consumed foods of a typical Indian diet. The foods included in the meal plan have been assessed for AGE content and further ranked to devise low and high dAGE diets with specified serving sizes. Participants have been enrolled and randomized to a low vs. high AGEs regimen with an equal treatment allocation ratio. A stratification factor for gender has been considered for randomization to avoid differences in the percentage of men and women between the orders of intervention administration. However, more male (62%) participants consented to participate in the study than women (38%) perhaps due to the protocol needing regular visits to the centre’s test facility for breakfast, lunch, and dinner. All the participants recruited in this study have been given full details about the purpose of the study, the complications and benefits of the trial, and their full cooperation sought. Written informed consent has been obtained prior to study initiation. A 1-week run-in phase will be conducted prior to the start of the trial to evaluate the compliance of the participant in the study and also to observe any probable adverse effects.
|Figure 1: Study design on low and high dAGE randomized controlled feeding trial among overweight adults––RCT|
Click here to view
Overweight/obese adult men and women (as per Asia Pacific guidelines) at high risk for developing type 2 diabetes (n = 50) have been identified from the nongovernment sectors, as well as staff of a large tertiary care center for diabetes in Chennai, South India, and their relatives. Age range between 25 and 65, body mass index (BMI) ≥ 23 kg/m2, waist circumference (WC) of ≥90cm for men and ≥80cm for women, and prediabetes have been considered as inclusion criteria [Figure 1].
Fasting glucose values of ≥126 mg/dL, postprandial glucose ≥ 200 mg/dL, use of any special diets for therapeutic or other purposes, chronic illnesses such as diabetes, cancer patient, or person who has received radiotherapy or chemotherapy during the past 5 years, alcohol or drug abuse, cardiovascular or cerebrovascular disease, psychological disorders, diarrhea and gastrointestinal ulcer, liver disease, renal disease, AIDS, jaundice, tuberculosis, hypo or hyperthyroidism, physical disability, pregnancy and lactation, and history of food allergy are considered as exclusion criteria.
The study protocol has been approved by the institutional review board of the Madras Diabetes Research Foundation (MDRF) and registered with Clinical Trial Registry of India, ctri.nic.in (CTRI/2018/04/012983). The study details have been explained to the study participants and informed consent obtained.
Effect and sample size calculation
The effective size of 0.58 (medium effective) has been calculated with the primary outcome measure of oral disposition index (DIo) with the mean difference of 22.0 (change in DIo of intervention vs. control) and SD as previously published by Singhal et al. The sample size was calculated to be 50 after accounting for a dropout rate of 20%.
Participants were identified and recruited using a face-to-face interviewer-administered questionnaire with a checklist of inclusion and exclusion criteria. The screening questionnaire elicited details of demographic and lifestyle factors, medical history, alcohol consumption, and smoking status and dietary recall by well-trained interviewers. The participants thus shortlisted and identified from this questionnaire were taken up for further randomization.
Randomization to either a high dAGE diet or a low dAGE diet was performed by computer-generated random numbers after recording screening and baseline measurements. This process was conducted by an investigator who is not involved in the study either during data recording, analysis, or report generation to avoid biasing. The low dAGE diet was coded as Diet 1 and high dAGE diet as Diet 2 by the study investigators to keep the participants blinded. The lab technicians involved in this study were also blinded for diet allocation.
For this study, the most commonly consumed/reported foods have been selected using a validated semi-quantitative Food Frequency Questionnaire (FFQ) based on the Chennai Urban Rural Epidemiology Study. The foods selected have diverse modes of cooking, such as stir frying, deep frying, steaming, boiling, pressure cooking, and baking. The low and high dAGE diets have been planned so as to resemble the culture-specific food habits of south Indian adults and matched for calories and macronutrient composition, but differ in cooking methods, for example, foods prepared by roasting, deep frying, and shallow frying have been mainly considered for high dAGE diet plan, whereas those prepared by boiling and steaming have been considered for low dAGE diet plan. Forty-six foods used in the low and high dAGE diet have been assessed for their AGE content. Based on the dAGE content, the low dAGE and high dAGE menu items with specified serving sizes have been developed as test diets [Table 1a] and [Table b].
|Table 1a: dAGE content of the foods provided in the low dAGE isocaloric diet|
Click here to view
|Table 1b: dAGE content of the foods provided in the high dAGE isocaloric diet|
Click here to view
Assessment of dietary advanced glycation end-product content of food samples
The food samples were homogenized, reconstituted, and extracted in phosphate buffer saline, centrifuged and the supernatants tested for AGE content using enzyme-linked immunosorbent assay (ELISA), Cell Biolabs, San Diego, CA, USA.
The principle of this assay is that, first, an AGE conjugate is coated on the ELISA plate. The unknown AGE samples or AGE-BSA standards are then added to the AGE conjugate pre-absorbed ELISA plate. After a brief incubation, an anti-AGE polyclonal antibody is added, followed by an HRP conjugated secondary antibody and the color developed measured at 450 nm. The AGE content of each food item has been calculated based on the mean value of at least two measurements per sample and expressed as AGE mg/100 g food [Figure 2].
The foods were categorized in quartiles of AGE content with the first two quartiles considered low dAGE-based foods and the third and fourth quartiles as high dAGE- based foods.
An inter-laboratory assessment was conducted to assess the agreement of dAGE content using the same ELISA based kit for a selected common food––onion oothapam. Only a small acceptable difference of 2% was found with the collaborating lab (Department of Biotechnology, Sastra University, Thanjavur, Tamil Nadu, India).
Low and high dAGE diets cyclic menu plan
A 6-day cyclic menu will be considered to plan low and high dAGE diets based on typical meal choices of south India. Diets by design are planned to reflect a significant difference in the total daily dAGE content and otherwise matched for total daily calories and macronutrients [Table 2].
|Table 2: dAGE, macronutrient composition, and calorie content of high and low dAGE diets used in 6 days feeding trial for a crossover RCT|
Click here to view
Most of the test meals will be prepared and served to the study participants in the test kitchen facility of the Madras Diabetes Research Foundation (MDRF). However, some of the animal food preparations such as chicken biriyani and plain parotta will be purchased from popular commercial eateries and served to the participants. Certain foods will be included in both the diet arms irrespective of their presumed AGE content as they are commonly consumed as the main meal or accompaniments in the diet. However, the serving size will be adjusted for these common foods so as to distinguish significantly between diets for the total dAGE content. Weekly breakfast, lunch, and dinner choices usually consumed will be considered for assessing low dAGE and high dAGE foods. The list of main meal choices with accompaniments is given in [Supplementary Table 1].
|Supplementary Table 1: List of foods selected based using a validated semi quantitative Food frequency questionnaire as part of the Chennai Urban Rural Epidemiology study for assessment of low dAGE and high dAGE food choices|
Click here to view
Data collection and analyses
As part of the anthropometry measurements, body weight (kg), height (cm), and WC are measured as per the standardized procedures detailed previously and BMI is calculated as weight (kg)/by height (m2). As per the Asia Pacific Classification, overweight has been defined with a BMI of ≥ 23 kg/m2.
We plan to perform biochemical measurements in blood samples that will be obtained after an overnight fast (10–12h), ensuring avoidance of vigorous physical exercise and preferably during the follicular phase of the menstrual cycle in women participants. Serum will be separated from 15mL of the fasting blood sample and stored at –70oC until the assays are performed. Biochemical analyses will be performed on Hitachi-912 Autoanalyzer (Hitachi, Mannheim, Germany) using kits supplied by Roche Diagnostics (Mannheim, Germany).
Oral glucose tolerance test
At the time of screening, diabetes was ruled out by performing an oral glucose tolerance test (OGTT), with blood samples that are obtained by collecting finger-prick capillary blood samples from the participants in the fasting stage and 2h after administration of an oral glucose load of 82.5 g (equivalent to 75 g of anhydrous glucose). The measurement of capillary blood glucose was done using an Hemocue 201+ Glucose analyzer (Hemocue Ltd, Angelholm, Sweden) to rule out any newly diagnosed diabetes at the time of screening. Individuals with fasting capillary blood glucose ≥ 126 mg/dL or 2-h postcapillary blood glucose ≥200 mg/dL at the time of screening were not considered further for the study. Fasting plasma glucose was measured using GOD-POD method at baseline, and will be repeated at the end of each diet arm over 12 weeks.
Glycated hemoglobin (HbA1C) was estimated by high-pressure liquid chromatography using the Varian machine (Bio-Rad, Hercules, California) at baseline and will be repeated at the end of each diet intervention.
Insulin sensitivity and insulin resistance
Plasma insulin was measured at baseline with a two-site chemiluminescent enzyme immunometric assay and will be repeated at the end of each dietary intervention. The β cell function is being evaluated using DIo, which is the ratio of difference in fasting to 30-min insulin (I) to glucose (G) values = (δI0–30/δG0–30),,, and insulin resistance calculated by the Homeostasis Model Assessment (HOMA-IR) using the formula: fasting insulin (uIU/mL)×fasting glucose (mmol/L)/22.5, [Table 3].
|Table 3: Baseline characteristics of study participants in both low dAGE and high dAGE groups for periods 1 and 2 for a crossover RCT (per protocol)|
Click here to view
Blood pressure (resting systolic and diastolic blood pressure) was recorded in the right arm with a mercury sphygmomanometer (Diamond Deluxe Blood pressure apparatus, Pune, India) with the participant seated. The mean of two readings taken 5 minutes apart was taken as the blood pressure.
At baseline, serum cholesterol (CHOD-PAP method), serum triglycerides (GPO-PAP method), and high-density lipoprotein (HDL) cholesterol (Direct method–polyethylene glycol-pretreated enzymes) were measured, and low-density lipoprotein (LDL) cholesterol calculated using the Friedewald formula. The lipid profile will be repeated at the end of each diet arm.
Assessment of inflammation
Established enzyme-linked immunosorbent assays (ELISAs) are being used to assess the AGE content in serum. The anti-inflammatory marker adiponectin has been measured in serum samples of the study participants at baseline using ELISA kit specific for human adiponectin (R&D Systems, Minneapolis, MN, USA) and Perkin Elmer Multimode reader. Both these will be repeated at the end of the study.
Assessment of oxidative stress
Oxidative stress marker thiobarbituric acid reactive substances (TBARS) in serum will be measured using CAYMAN’s TBARS assay kit (Cayman Chemical Company, Ann Arbor, Michigan) the malondialdehyde (MDA)-thiobarbituric acid (TBA) adduct formed as a result of reaction between MDA and TBA under acidic conditions and at higher temperature ranging between 90 and 100 is measured colorimetrically at 530–540 nm.
An interviewer-administered validated semi-quantitative FFQ was administered to all the volunteers at baseline. In addition, 24-h recall was also administered at baseline, and will be repeated during and at the end of the intervention period (total of 6 times) for compliance in the study. Satiety of the intervention meals will be recorded monthly.
Madras diabetes research foundation––physical activity questionnaire (MPAQ)
The validated MPAQ was used to measure the type of physical activity involved in the day-to-day activities of the study participants at baseline of each diet arm. The MPAQ is the most preferred, suitable, and reproducible tool that records physical activity data for 1 year.
The data recorded throughout the study period are being electronically stored using in-house software EpiNu that maintains an organized data record of anthropometric, dietary and biochemical parameters and will be used to estimate the nutrient content of the dietary records of the participants at baseline, mid-study and at the end of the study. Participant confidentiality will be secured using a computer-based data coding system before analyzing the data. The study parameters and timeline of the assessments are shown in [Table 4], where all biochemical parameters being measured at baseline and end of each diet intervention. The dietary assessments are carried out with multiple 24-h diet recalls collected at baseline and monthly recalls (each month 1 week day and 1 week end) to monitor the compliance of the study. Similarly, the details of physical activity including the nature of work, domestic chores, and other recreational activities are collected using MPAQ.
|Table 4: Schedule of assessments for the study participants in both low dAGE and high dAGE groups during the study periods 1 and 2 for a crossover RCT|
Click here to view
Assessment of compliance and monitoring
There will be direct interaction with the study participants by the research dietitians on a daily basis when they visit the test kitchen facility for their meals. Reasons for discontinuing the study, if any, will be recorded by contacting the participant in person or by telephone. Compliance will be assessed by the research dietitians as to whether the participants had their 12 weeks of low dAGE and high dAGE meals for 6 days in week (except Sunday) by direct observation at the dining facility of the test kitchen. In addition to this, the compliance will be assessed using 24h dietary recalls (one weekday and one weekend).
Any serious side effects such as any medical condition or anomaly in the health of the participant identified as a result of the intervention during screening, baseline, and follow-up procedures, will be discussed and treated immediately by a qualified medical practitioner involved in the study. The participant will further be withdrawn from the study if the side effects recurred. The study participants are advised to review their blood reports with a qualified medical practitioner at the end of the study so to improve their diabetes risk profile.
The main outcome from the 12-week crossover feeding trial from the low and high dAGE diets will be the changes in biochemical parameters –glycemia (fasting glucose) and beta cell function (insulin disposition index––DIo). The secondary outcomes are anthropometric measurements such as BMI, waist and waist to hip ratio, HbA1c, clinical parameters (resting systolic and diastolic blood pressure), markers of anti-inflammation such as adiponectin, serum AGE and an oxidative stress marker TBARS.
The significance between 6-day cyclic menu of low vs. high dAGE diet will be assessed using independent t test and P < 0.01. In this study, the independent t test will be used to test the sensitivity of differences in baseline characteristics between low and high dAGE intervention groups. All analyses will be performed using SAS version 9.2, SAS Institute Inc. Statistical difference will be determined post follow-up over 12 weeks between the high and low dAGE groups both at baseline and end of study for biomarkers, BMI, WC, weight, and dietary intake using repeated measurements with robust variance. This would further require various sensitivity analysis including the analysis for change by adjusting other covariates (confounders) such as physical activity, blood pressure, and testing for any carry-over effects by creating an interaction between the period of study and the two diet groups.
| Results|| |
Low and high dAGE foods included a total of 46 foods [Figure 1]. The mean ± SD of dAGE of 6 days’ low and high dAGE diets was 26179 ± 4327 mg/100 g and 49710 ± 5239 mg/100 g (P < 0.001). [Table 5] provides the description of low and high dAGE diets comprising typical culture specific meal choices with accompaniments. Low dAGE diets included foods prepared by processing /cooking methods such as steaming (e.g., idly) and boiling (e.g., rasam), whereas high dAGE diets had foods predominantly prepared by dry heat methods such as stir frying (e.g., vegetable fried rice), roasting (e.g., chicken) and deep frying (e.g., fish fry). In this study, AGE content of low dAGE foods ranged from 117 to 2433 mg/100 g, whereas that of high dAGE diets from 2467 to 7712 mg/100 g.
[Table 3] shows the baseline characteristics of the participants. A total of 100 participants were screened [Figure 2], of whom 75 expressed their initial interest to participate. These participants were scheduled for an OGTT and a total of 60 participants were willing to participate further. Five people who had initially shown their willingness to participate could not continue because of a work relocation. Out of these 55 volunteers, 5 were newly diagnosed with diabetes by OGTT (during screening) and were excluded from the study. Hence, the study commenced with only 50 participants matching with inclusion and exclusion criteria. Participants have been randomized to start with either the low dAGE diet arm or high dAGE diet arms (Baseline––Period 1). Participants were aged 25–62 years and 38% were female. By design, the mean ± SD for BMI was 28 ± 3 kg/m2 and 27 ± 3 kg/m2 in high and low dAGE diet arms, and average WC was 93 ± 8cm and 92 ± 7cm in high and low dAGE diet arms, fasting blood glucose was 94 ± 12 mg/dL and 93 ± 13 mg/dL for high and low dAGE diet arms, fasting insulin was 15 ± 8 and 14 ± 8 for high and low dAGE diet arms, insulin disposition index (DIo) was 4 ± 5 and 3 ± 3 for high and low dAGE diet arms, Serum AGE was 3 ± 1 for both high and low dAGE diet arms and serum Adiponectin was 1 ± 0.7 and 1 ± 0.6 for high and low dAGE diets arms, respectively. There were no statistically significant differences in clinical and the biochemical characteristics between those randomized to the low or high dAGE diets at the start of study.
| Discussion|| |
To the best of our knowledge, this is the first study in India attempting to assess the dAGE content of Indian foods to develop low and high dAGE test diets for a randomized control trial among overweight and centrally obese participants. The effect of low vs. high dAGE diets on various metabolic risk factors such as blood glucose, HBA1c, insulin sensitivity, HOMA-IR, blood lipid profile, and selected markers of inflammation (Serum AGE, Adiponectin) and oxidative stress will be evaluated as primary and secondary outcomes. This study describes only the design and methodological aspects of this randomized trial.
In this study, 46 commonly consumed Indian meal choices with accompaniments were evaluated for their AGE content and further ranked to devise low and high dAGE diets (<median and >median) with appropriate serving size thereby producing a significant difference in AGE content between diets. These diets will be prepared and fed to 50 overweight and centrally obese adults without diabetes for a 12-week crossover feeding trial. The diets do not significantly differ in terms of calories and macronutrients, as they have been matched for these nutrients by default study design.
Foods prepared by common cooking methods such as boiling (e.g., rasam, spicy soup accompaniments to go with main meal such as rice) and steaming (e.g., idly-fermented steamed rice cake) showed lower AGE content compared to foods cooked with dry heat methods such pan roasting (e.g., unripe plantainpan roast) and deep frying (e.g., chicken fry). However, the exception to this is the low AGE content of poori (deep fried wheat flour item similar to preparation to Taco in oil) (130 g contains 485 kU dAGE). This is probably because of its shorter cooking time (less than a minute) despite being a deep-fried food at higher temperature. The low dAGE content of rasam (75 g contain 88kU dAGE) might be due to higher moisture content, lower carbohydrate and protein in the preparation, lower pH (tamarind juice rich in tartaric acid), presence of ground spices with better bioavailability of active principles (antioxidant) and method of preparation (boiling), whereas the high dAGE content of plantain pan roast was possibly due to the dry heat method of shallow frying in oil with mild spices for a longer time.
Similar explanations could hold good for other foods included in the low and high dAGE diets in the trial. For example, despite being a seafood, fish gravy (150 g contains 3232kU dAGE) was a low dAGE dietary choice as this was cooked mostly by boiling fish with ground Indian spices and Tamarind; the inclusion of chicken fry (75 g contains 1888 kU dAGE) as a high dAGE food might be a consequence of it being deep fried in oil at higher temperature with a longer cooking time.
On the other hand, pongal showed higher dAGE content (250 g contains 19280kU dAGE). This might be due to the cooking method of pressure cooking with refined cereal and dhal (decorticated and split green gram with lower antioxidant phytochemical contents compared to whole-grain counterparts) for a longer duration, thereby suggesting the role of extrinsic factors such as prolonged cooking time in the formation of dAGEs. Also, the higher temperature involved in the seasoning of whole spices (which have restricted bioavailability of antioxidants compared to the ground spices) with clarified butter could have led to thermal degradation of fat leading to lipoxidation products (precursors for AGEs).
Data on the AGE content of such Indian foods is almost nonexistent and using the corresponding western foods for comparison may not be appropriate owing to the differences in the ingredients and cooking styles. In this study, the differences in dAGE content between low and high dAGE diets were not only due to the cooking methods but also due to ingredient composition and variation in the serving sizes. This was necessary keeping in mind the cultural dietary habits of the Asian Indians in general.
There are very limited or no data on effect of dAGE content on insulin resistance among Indians, but studies in the west that assessed the AGE content in diet among 20 overweight adults without diabetes reported improvement in insulin sensitivity with low dAGE diets. A recent study from Iran has shown that the intake of AGE could increase the risk for abdominal obesity. Asian Indians are characterized by unique clinical and biochemical incongruities which have been termed the “Asian Indian phenotype,” characterized by higher insulin resistance, abdominal obesity (higher WC though low in BMI), low adiponectin and high C-reactive protein levels. This study represents an attempt to evaluate the effect of dAGE on such metabolic risks in overweight and centrally obese Asian Indians.
The major strength of this study is that it attempts to assess the AGE content in culture-specific Indian foods for the first time using protocols similar to those reported elsewhere. This assessment could initiate the preparation of a database for pro-inflammatory foods in India. Such a database could bring awareness among the population about the deleterious effects of AGEs which are generally thought to occur only within the body and through consumption of animal foods, and not through any cooked foods. The study design accounts for confounding due to calorie and macronutrient contents by matching for these variables. The crossover design is another major strength of the study as it controls individual variation between participants, as well as measurement of confounders which include dietary macronutrients, energy intake, and physical activity. The measurement of cardiac (which includes blood pressure, lipid profile) and metabolic profile (OGTT, fasting glucose, insulin sensitivity, insulin resistance, HbA1C) follows a validated protocol. We also plan to correlate dAGEs consumed during the study period with AGE levels in blood.
The limitation of this study with regard to participant’s recruitment did not have specific exclusion criteria for inflammatory bowel disease (IBD), irritable bowel syndrome (IBS), and menopausal women. The AGE content of all the Indian foods could not be evaluated and the number of foods analyzed was comparatively low (limited to the diets of study design) and their complete characterization could not be done due to budgetary constraints. In this study the dAGE content of foods was estimated with AGE competitive ELISA kit (Oxiselect, Cell Biolabs) with anti-AGE antibody to assess the broad range of AGEs in foods, whereas most of the studies published had used antibody specific to carboxymethyl lysine (CML), carboxyethyl lysine (CEL) or methylglyoxal (MG) and hence the dAGE content of foods in this study are not comparable to such published values. Longitudinal follow-up studies are needed to evaluate the modification of metabolic risk factors with low dAGE diets.
| Conclusion|| |
The concept of modifying dAGE content in the Indian diets is a novel step in the prevention of noncommunicable diseases such as diabetes. This study can be considered as a prototype to conduct such clinical intervention trials in India. The findings of the trial if positive could aid in helping policymakers to understand the importance of dAGE content of foods and this could help in making healthier food choices available. The study findings could further inform the need to include details on dAGE and inflammation in medical nutrition therapy (MNT) with focus on glycemic control. Our findings if encouraging are expected to have important public health implications, such as for programs that promote sustainable low AGE consumption and influence guidelines for food preparation and processing This, in the long run, may pave way for an adjuvant nutritional guide for patients at risk for type 2 diabetes mellitus and CVDs.
Financial support and sponsorship
This work was funded by the Department of Biotechnology, Ministry of Science and Technology, India
Conflicts of interest
There are no conflicts of interest.
| References|| |
Uribarri J, Woodruff S, Goodman S, Cai W, Chen X, Pyzik R, et al
. Advanced glycation end products in foods and a practical guide to their reduction in the diet. J Am Diet Assoc 2010;110:911-16.e12.
Šebeková K, Somoza V Dietary advanced glycation endproducts (AGEs) and their health effects––PRO. Mole Nutr Food Res 2007;51:1079-84.
World Health Organization. Global status report on noncommunicable diseases 2014. Geneva, Switzerland: World Health Organization; 2014. Available from: http://www.who.int/nmh/publications/ncd-status-report-2014/en/. [Last accessed on 2020 Apr 9].
Mohan V Why are Indians more prone to diabetes? J Assoc Physicians India 2004;52:468-74.
Poulsen MW, Hedegaard RV, Andersen JM, de Courten B, Bügel S, Nielsen J, et al
. Advanced glycation endproducts in food and their effects on health. Food Chem Toxicol 2013;60:10-37.
Cai W, He JC, Zhu L, Chen X, Zheng F, Striker GE, et al
. Oral glycotoxins determine the effects of calorie restriction on oxidant stress, age-related diseases, and lifespan. Am J Pathol 2008;173:327-36.
Goldberg T, Cai W, Peppa M, Dardaine V, Baliga BS, Uribarri J, et al
. Advanced glycoxidation end products in commonly consumed foods. J Am Diet Assoc 2004;104:1287-91.
Clarke RE, Dordevic AL, Tan SM, Ryan L, Coughlan MT Dietary advanced glycation end products and risk factors for chronic disease: A systematic review of randomised controlled trials. Nutrients 2016;8:125.
Koschinsky T, He CJ, Mitsuhashi T, Bucala R, Liu C, Buenting C, et al
. Orally absorbed reactive glycation products (glycotoxins): An environmental risk factor in diabetic nephropathy. Proc Natl Acad Sci U S A 1997;94:6474-9.
He C, Sabol J, Mitsuhashi T, Vlassara H Dietary glycotoxins: Inhibition of reactive products by aminoguanidine facilitates renal clearance and reduces tissue sequestration. Diabetes 1999;48:1308-15.
de Courten B, de Courten MP, Soldatos G, Dougherty SL, Straznicky N, Schlaich M, et al
. Diet low in advanced glycation end products increases insulin sensitivity in healthy overweight individuals: A double-blind, randomized, crossover trial. Am J Clin Nutr 2016;103:1426-33.
Vlassara H, Cai W, Goodman S, Pyzik R, Yong A, Chen X, et al
. Protection against loss of innate defenses in adulthood by low advanced glycation end products (AGE) intake: Role of the antiinflammatory AGE receptor-1. J Clin Endocrinol Metab 2009;94:4483-91.
O’Brien J, Morrissey PA Nutritional and toxicological aspects of the maillard browning reaction in foods. Crit Rev Food Sci Nutr 1989;28:211-48.
Nagai R, Unno Y, Hayashi MC, Masuda S, Hayase F, Kinae N, et al
. Peroxynitrite induces formation of N(epsilon)-(carboxymethyl) lysine by the cleavage of amadori product and generation of glucosone and glyoxal from glucose: Novel pathways for protein modification by peroxynitrite. Diabetes 2002;51:2833-9.
Sharma C, Kaur A, Thind SS, Singh B, Raina S Advanced glycation end-products (ages): An emerging concern for processed food industries. J Food Sci Technol 2015;52:7561-76.
Busch M, Franke S, Rüster C, Wolf G Advanced glycation end-products and the kidney. Eur J Clin Invest 2010;40:742-55.
Baye E, Kiriakova V, Uribarri J, Moran LJ, de Courten B Consumption of diets with low advanced glycation end products improves cardiometabolic parameters: Meta-analysis of randomised controlled trials. Sci Rep 2017;7:2266.
Scheijen JLJM, Hanssen NMJ, van Greevenbroek MM, Van der Kallen CJ, Feskens EJM, Stehouwer CDA, et al
. Dietary intake of advanced glycation endproducts is associated with higher levels of advanced glycation endproducts in plasma and urine: The CODAM study. Clin Nutr 2018;37:919-25.
Sukino S, Nirengi S, Kawaguchi Y, Kotani K, Tsuzaki K, Okada H, et al
. Effects of a low advanced glycation end products diet on insulin levels: The feasibility of a crossover comparison test. J Clin Med Res 2018;10:405-10.
Cordova R, Knaze V, Viallon V, Rust P, Schalkwijk CG, Weiderpass E, et al
. Dietary intake of advanced glycation end products (AGEs) and changes in body weight in European adults. Eur J Nutr 2019; 7:1-2.
World Health Organization. International Association for the Study of Obesity & International Obesity Task Force. The Asia-Pacific perspective: Redefining obesity and its treatment. Sydney, Australia: Health Communications; 2000.
Erlinger TP, Brancati FL Postchallenge hyperglycemia in a national sample of US adults with type 2 diabetes. Diab Care 2001;24:1734-8.
Singhal N, Misra A, Shah P, Gulati S, Bhatt S, Sharma S, et al
. Impact of intensive school-based nutrition education and lifestyle interventions on insulin resistance, β-cell function, disposition index, and subclinical inflammation among asian indian adolescents: A controlled intervention study. Metab Syndr Relat Disord 2011;9:143-50.
Sudha V, Radhika G, Sathya RM, Ganesan A, Mohan V Reproducibility and validity of an interviewer-administered semi-quantitative food frequency questionnaire to assess dietary intake of urban adults in Southern India. Int J Food Sci Nutr 2006;57:481-93.
Radhika G, Sathya RM, Ganesan A, Saroja R, Vijayalakshmi P, Sudha V, et al
. Dietary profile of urban adult population in South India in the context of chronic disease epidemiology (CURES–68). Pub Health Nutr 2011;14:591-8.
Deepa M, Pradeepa R, Rema M, Mohan A, Deepa R, Shanthirani S, et al
. The chennai urban rural epidemiology study (CURES)–study design and methodology (urban component) (CURES-I). J Assoc Physicians India 2003;51:863-70.
Stork AD, Kemperman H, Erkelens DW, Veneman TF Comparison of the accuracy of the hemocue glucose analyzer with the yellow springs instrument glucose oxidase analyzer, particularly in hypoglycemia. Eur J Endocrinol 2005;153:275-81.
Deepa M, Farooq S, Deepa R, Manjula D, Mohan V Prevalence and significance of generalized and central body obesity in an Urban Asian Indian population in Chennai, India (CURES: 47). Eur J Clin Nutr 2009;63:259-67.
Bi Y, Zhu D, Jing Y, Hu Y, Feng W, Shen S, et al
. Decreased beta cell function and insulin sensitivity contributed to increasing fasting glucose in Chinese. Acta Diabetol 2012;49:S51-8.
Wang H, Hu B, Feng B Decreased beta cell function and insulin sensitivity contributed to coronary artery disease in patients with normal glucose tolerance. J Atheroscler Thromb 2012;19:806-13.
Retnakaran R, Shen S, Hanley AJ, Vuksan V, Hamilton JK, Zinman B Hyperbolic relationship between insulin secretion and sensitivity on oral glucose tolerance test. Obesity (Silver Spring) 2008;16:1901-7.
Matthews DR, Hosker JP, Rudenski AS, Naylor BA, Treacher DF, Turner RC Homeostasis model assessment: Insulin resistance and β-cell function from fasting plasma glucose and insulin concentrations in man. Diabetol 1985;28:412-9.
DeFronzo RA, Matsuda M Reduced time points to calculate the composite index. Diabetes Care 2010;33:e93.
Anjana RM, Sudha V, Lakshmipriya N, Subhashini S, Pradeepa R, Geetha L, et al
. Reliability and validity of a new physical activity questionnaire for India. Int J Behav Nutr Phys Act 2015;12:40.
Fitzmaurice GM, Laird NM, Ware JH Applied longitudinal analysis. Hoboken, NJ: John Wiley & Sons; 2004.
Inan-Eroglu E, Ayaz A, Buyuktuncer Z Formation of advanced glycation endproducts in foods during cooking process and underlying mechanisms: A comprehensive review of experimental studies. Nutr Res Rev2020;33:77-89.
Srinivasan K Antioxidant potential of spices and their active constituents. Crit Rev Food Sci Nutr 2014;54:352-72.
Mirmiran P, Hadavi H, Mottaghi A, Azizi F Advanced glycation end products and risk of general and abdominal obesity in Iranian adults: Tehran lipid and glucose study. Med J Islam Repub Iran 2019;33:21.
Deepa R, Sandeep S, Mohan V Abdominal obesity, visceral fat and type 2 diabetes- “Asian Indian phenotype. In: Mohan V, Rao GHR, editors. Type 2 diabetes in South Asians: Epidemiology, risk factors and prevention. New Delhi, India: Jaypee Brothers Medical Publishers (P) Ltd. 2006; 138-52.
[Figure 1], [Figure 2]
[Table 1], [Table 2], [Table 3], [Table 4], [Table 5], [Table 6], [Table 7]