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Regin BS, Sowmiya B, Shiny A, Shanthi Rani CS, Gokulakrishnan K, Mohan V, Balasubramanyam M. Association of POC-based Measurement of Skin AGEs with Serum AGEs as well as AGE Biomarkers in Individuals with and without Glucose Intolerance. J Assoc Physicians India 2023; 71:11-12. [PMID: 37355787 DOI: 10.5005/japi-11001-0188] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/26/2023]
Abstract
Accumulation of advanced glycation end products (AGEs) occurs with aging and in various disease states. There are no reliable screening techniques to measure AGEs in clinical settings. In this study, a point-of-care (POC) device was used to validate skin AGE measurements with serum AGE levels and to assess its usefulness to identify individuals with abnormal glucose tolerance (AGT). MATERIALS AND METHODS The study group comprised individuals with normal glucose tolerance (NGT: n = 47) and with AGT, that is, either diabetes or prediabetes (n = 68). Intrinsic AGE fluorescence was measured spectrofluorimetrically using multimode plate reader in the serum by exciting the samples at 370 nm and emission readouts at 440 nm. Skin AGEs were acquired using a CE-marked Scout DS commercial device. Serum levels of biomarkers carboxymethyl lysine (CML), carboxyethyl lysine (CEL), and pentosidine were analyzed by enzyme-linked immunosorbent assay (ELISA). RESULTS In subjects with AGT, the skin AGEs [61.3 vs 53.7 arbitrary units (AU), p<0.0001] and serum AGEs (3.5 vs 2.8 AU, p<0.0001) were significantly higher than in individuals with NGT. The levels of CML, CEL, and pentosidine were also significantly higher in the subjects with AGT when compared with NGT (138 vs 89 pg/mL; 2.4 vs 1.4 nmol/mL, and 64 vs 48 pmol/mL, p<0.0001), respectively. Pearson correlation analysis showed a significant positive association of skin AGEs with serum AGEs (r = 0.344) (p<0.001), CML (r = 0.323) (p<0.001), CEL (r = 0.308) (p<0.001), and pentosidine (r = 0.251) (p<0.001). In addition, it also showed a positive correlation with fasting plasma glucose (FPG) (p<0.001), 2-hour post-glucose (p<0.001), glycated hemoglobin (HbA1c) (p<0.001), and body mass index (BMI) (p<0.05). Multiple logistic regression analysis using AGT as a dependent variable showed that skin AGE scores were significantly (p<0.001) associated with AGT (odds ratio: 1.133, confidence intervals: 1.067-1.203). CONCLUSION This study shows that the measurement of skin AGEs using a POC device may be suitable for mass screening of AGT even in low-resource settings.
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Affiliation(s)
| | | | | | | | - Kuppan Gokulakrishnan
- Associate Professor, DBT/Wellcome Trust India Alliance-Intermediate Fellow, Department of Neurochemistry, National Institute of Mental Health and NeuroSciences (NIMHANS), Bengaluru, Karnataka
| | - Viswanathan Mohan
- Director and Chief of Diabetology, Department of Diabetology, Madras Diabetes Research;Corresponding Author
| | - Muthuswamy Balasubramanyam
- Emeritus Scientist, Department of Cell and Molecular Biology, Madras Diabetes Research Foundation, Chennai, Tamil Nadu, India
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Mohan V, Uma Sankari G, Amutha A, Anjana RM, Jeba Rani S, Unnikrishnan R, Venkatesan U, Shanthi Rani CS. Clinical and biochemical profile of childhood-adolescent-onset type 1 diabetes and adult-onset type 1 diabetes among Asian Indians. Acta Diabetol 2023; 60:579-586. [PMID: 36700996 DOI: 10.1007/s00592-023-02034-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/11/2022] [Accepted: 01/09/2023] [Indexed: 01/27/2023]
Abstract
AIM To compare the clinical and biochemical profile and prevalence of complications among childhood/adolescent-onset (CAO; onset of diabetes< 20 years of age) and adult-onset (AO; onset of diabetes- ≥ 20 years of age) type 1 diabetes (T1D), seen at a tertiary care diabetes center in south India. METHOD Data of 5578 individuals with T1D, diagnosed based on a history of diabetic ketoacidosis or ketonuria, fasting C-peptide < 0.3 pmol/mL and stimulated C-peptide values < 0.6 pmol/mL, and requirement of insulin right from the time of diagnosis, presenting to our center between 1991 and 2021, were retrieved from our electronic medical records. Retinopathy was assessed by retinal photography, chronic kidney disease (CKD) by urinary albumin excretion ≥ 30 µg/mg of creatinine and/or eGFR < 60 mL/min, and neuropathy by vibration perception threshold >= 20v on biothesiometry. RESULTS Overall, 3559 (63.8%) of individuals with T1D, belonged to CAO group and 2019 (36.2%) to AO category. AO had higher prevalence of all microvascular complications compared to CAO at every diabetes duration interval, even after adjusting for A1c. Among the AO group, prevalence of retinopathy, CKD, and neuropathy was higher in the GAD negative group. Among CAO there were no differences between the GAD negative and GAD positive groups with respect to prevalence of complications of diabetes. CONCLUSION AO with T1D had higher prevalence of microvascular complications compared to CAO. Among AO, GAD negative individuals had higher percentage of retinopathy and CKD compared to GAD positive group.
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Affiliation(s)
- Viswanathan Mohan
- Madras Diabetes Research Foundation (ICMR Centre for Advanced Research On Diabetes) & Dr. Mohan's Diabetes Specialities Centre (IDF Centre of Excellence in Diabetes Care), No 4, Conran Smith Road, Gopalapuram, Chennai, 600 086, India.
| | - Ganesan Uma Sankari
- Madras Diabetes Research Foundation (ICMR Centre for Advanced Research On Diabetes) & Dr. Mohan's Diabetes Specialities Centre (IDF Centre of Excellence in Diabetes Care), No 4, Conran Smith Road, Gopalapuram, Chennai, 600 086, India
| | - Anandakumar Amutha
- Madras Diabetes Research Foundation (ICMR Centre for Advanced Research On Diabetes) & Dr. Mohan's Diabetes Specialities Centre (IDF Centre of Excellence in Diabetes Care), No 4, Conran Smith Road, Gopalapuram, Chennai, 600 086, India
| | - Ranjit Mohan Anjana
- Madras Diabetes Research Foundation (ICMR Centre for Advanced Research On Diabetes) & Dr. Mohan's Diabetes Specialities Centre (IDF Centre of Excellence in Diabetes Care), No 4, Conran Smith Road, Gopalapuram, Chennai, 600 086, India
| | - Saravanan Jeba Rani
- Madras Diabetes Research Foundation (ICMR Centre for Advanced Research On Diabetes) & Dr. Mohan's Diabetes Specialities Centre (IDF Centre of Excellence in Diabetes Care), No 4, Conran Smith Road, Gopalapuram, Chennai, 600 086, India
| | - Ranjit Unnikrishnan
- Madras Diabetes Research Foundation (ICMR Centre for Advanced Research On Diabetes) & Dr. Mohan's Diabetes Specialities Centre (IDF Centre of Excellence in Diabetes Care), No 4, Conran Smith Road, Gopalapuram, Chennai, 600 086, India
| | - Ulagamathesan Venkatesan
- Madras Diabetes Research Foundation (ICMR Centre for Advanced Research On Diabetes) & Dr. Mohan's Diabetes Specialities Centre (IDF Centre of Excellence in Diabetes Care), No 4, Conran Smith Road, Gopalapuram, Chennai, 600 086, India
| | - Coimbatore Subramanian Shanthi Rani
- Madras Diabetes Research Foundation (ICMR Centre for Advanced Research On Diabetes) & Dr. Mohan's Diabetes Specialities Centre (IDF Centre of Excellence in Diabetes Care), No 4, Conran Smith Road, Gopalapuram, Chennai, 600 086, India
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Mohan V, Shanthi Rani CS, Saboo B, Mukhopadhyay S, Chatterjee S, Dharmarajan P, Gupta S, Pendsey S, Chandrakanta J, Umasankari G, Amutha A, Salis S, Datta S, Gupta PK, Routray P, Jebarani S, Sastry NG, Venkatesan U, Anjana RM, Unnikrishnan R. Clinical Profile of Long-Term Survivors and Nonsurvivors with Type 1 Diabetes in India. Diabetes Technol Ther 2022; 24:120-129. [PMID: 34569820 DOI: 10.1089/dia.2021.0284] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
Objective: To compare the clinical profile of long-term survivors and nonsurvivors with type 1 diabetes (T1D) in India. Research Design and Methods: This is a retrospective study of 76 individuals with T1D who had survived for at least 40 years ("survivors") and 51 individuals with T1D who had died with shorter duration of diabetes ("non-survivors"), from diabetes clinics in different cities of India. Prevalence of complications in both groups and causes of death of the nonsurvivors were analyzed. Retinopathy was diagnosed by retinal photography; chronic kidney disease (CKD) by urinary albumin excretion (micro-or macroalbuminuria) and estimated glomerular filtration rate; peripheral vascular disease (PVD) by doppler measurement of ankle-brachial pressure index; coronary artery disease (CAD) based on history of myocardial infarction or coronary revascularization, and neuropathy by biothesiometry. Results: Mean glycated hemoglobin (8.4% ± 1.5% vs. 10.7% ± 2.2%, P < 0.001), serum low-density lipoprotein cholesterol (91 ± 29 mg/dL vs. 107 ± 22 mg/dL, P = 0.004), and systolic blood pressure (135 ± 16 mmHg vs. 153 ± 37 mmHg, P = 0.003) were lower, and high-density lipoprotein cholesterol (51 ± 11 mg/dL vs. 43 ± 15 mg/dL, P = 0.002) higher, among survivors compared to nonsurvivors. Diabetic retinopathy, CKD, neuropathy, PVD, and CAD were more frequent among nonsurvivors. CAD [25.5%] and renal failure [23.5%] were the most frequent causes of death. Conclusions: In this first report of long-term survivors with T1D from India, we report that survivors had better glycemic and blood pressure control, more favorable lipid profiles and lower prevalence of complications compared to nonsurvivors. However, there could be other protective factors as well, which merit further studies.
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Affiliation(s)
- Viswanathan Mohan
- Dr. Mohan's Diabetes Specialities Centre & Madras Diabetes Research Foundation, Chennai, India
| | | | - Banshi Saboo
- Diabetes Care & Hormone Clinic, Ahmedabad, India
| | | | | | | | - Sunil Gupta
- Sunil's Diabetes Care n' Research Pvt Ltd., Nagpur, India
| | | | - Jha Chandrakanta
- Dr. Mohan's Diabetes Specialities Centre & Madras Diabetes Research Foundation, Chennai, India
| | - Ganesan Umasankari
- Dr. Mohan's Diabetes Specialities Centre & Madras Diabetes Research Foundation, Chennai, India
| | - Anandakumar Amutha
- Dr. Mohan's Diabetes Specialities Centre & Madras Diabetes Research Foundation, Chennai, India
| | | | - Supriya Datta
- Dr. Mohan's Diabetes Specialities Centre & Madras Diabetes Research Foundation, Chennai, India
| | - Prasanna Kumar Gupta
- Dr. Mohan's Diabetes Specialities Centre & Madras Diabetes Research Foundation, Chennai, India
| | - Philips Routray
- Dr. Mohan's Diabetes Specialities Centre & Madras Diabetes Research Foundation, Chennai, India
| | - Saravanan Jebarani
- Dr. Mohan's Diabetes Specialities Centre & Madras Diabetes Research Foundation, Chennai, India
| | | | | | - Ranjit Mohan Anjana
- Dr. Mohan's Diabetes Specialities Centre & Madras Diabetes Research Foundation, Chennai, India
| | - Ranjit Unnikrishnan
- Dr. Mohan's Diabetes Specialities Centre & Madras Diabetes Research Foundation, Chennai, India
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Alsulami S, Bodhini D, Sudha V, Shanthi Rani CS, Pradeepa R, Anjana RM, Radha V, Lovegrove JA, Gayathri R, Mohan V, Vimaleswaran KS. Lower Dietary Intake of Plant Protein Is Associated with Genetic Risk of Diabetes-Related Traits in Urban Asian Indian Adults. Nutrients 2021; 13:3064. [PMID: 34578944 PMCID: PMC8466015 DOI: 10.3390/nu13093064] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2021] [Revised: 08/26/2021] [Accepted: 08/27/2021] [Indexed: 01/19/2023] Open
Abstract
The increasing prevalence of type 2 diabetes among South Asians is caused by a complex interplay between environmental and genetic factors. We aimed to examine the impact of dietary and genetic factors on metabolic traits in 1062 Asian Indians. Dietary assessment was performed using a validated semi-quantitative food frequency questionnaire. Seven single nucleotide polymorphisms (SNPs) from the Transcription factor 7-like 2 and fat mass and obesity-associated genes were used to construct two metabolic genetic risk scores (GRS): 7-SNP and 3-SNP GRSs. Both 7-SNP GRS and 3-SNP GRS were associated with a higher risk of T2D (p = 0.0000134 and 0.008, respectively). The 3-SNP GRS was associated with higher waist circumference (p = 0.010), fasting plasma glucose (FPG) (p = 0.002) and glycated haemoglobin (HbA1c) (p = 0.000066). There were significant interactions between 3-SNP GRS and protein intake (% of total energy intake) on FPG (Pinteraction = 0.011) and HbA1c (Pinteraction = 0.007), where among individuals with lower plant protein intake (<39 g/day) and those with >1 risk allele had higher FPG (p = 0.001) and HbA1c (p = 0.00006) than individuals with ≤1 risk allele. Our findings suggest that lower plant protein intake may be a contributor to the increased ethnic susceptibility to diabetes described in Asian Indians. Randomised clinical trials with increased plant protein in the diets of this population are needed to see whether the reduction of diabetes risk occurs in individuals with prediabetes.
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Affiliation(s)
- Sooad Alsulami
- Hugh Sinclair Unit of Human Nutrition, Department of Food and Nutritional Sciences, University of Reading, Reading RG6 6DZ, UK; (S.A.); (J.A.L.)
- Department of Clinical Nutrition, Faculty of Applied Medical Sciences, King Abdulaziz University, Jeddah 21589, Saudi Arabia
| | - Dhanasekaran Bodhini
- Department of Molecular Genetics, Madras Diabetes Research Foundation, Chennai 603103, India; (D.B.); (V.R.)
| | - Vasudevan Sudha
- Department of Foods, Nutrition and Dietetics Research, Madras Diabetes Research Foundation, Chennai 600086, India; (V.S.); (R.G.)
| | | | - Rajendra Pradeepa
- Department of Diabetology, Madras Diabetes Research Foundation & Dr. Mohan’s Diabetes Specialities Centre, WHO Collaborating Centre for Non-Communicable Diseases Prevention and Control, ICMR Centre for Advanced Research on Diabetes, Gopalapuram, Chennai 600086, India; (R.P.); (R.M.A.); (V.M.)
| | - Ranjit Mohan Anjana
- Department of Diabetology, Madras Diabetes Research Foundation & Dr. Mohan’s Diabetes Specialities Centre, WHO Collaborating Centre for Non-Communicable Diseases Prevention and Control, ICMR Centre for Advanced Research on Diabetes, Gopalapuram, Chennai 600086, India; (R.P.); (R.M.A.); (V.M.)
| | - Venkatesan Radha
- Department of Molecular Genetics, Madras Diabetes Research Foundation, Chennai 603103, India; (D.B.); (V.R.)
| | - Julie A. Lovegrove
- Hugh Sinclair Unit of Human Nutrition, Department of Food and Nutritional Sciences, University of Reading, Reading RG6 6DZ, UK; (S.A.); (J.A.L.)
| | - Rajagopal Gayathri
- Department of Foods, Nutrition and Dietetics Research, Madras Diabetes Research Foundation, Chennai 600086, India; (V.S.); (R.G.)
| | - Viswanathan Mohan
- Department of Diabetology, Madras Diabetes Research Foundation & Dr. Mohan’s Diabetes Specialities Centre, WHO Collaborating Centre for Non-Communicable Diseases Prevention and Control, ICMR Centre for Advanced Research on Diabetes, Gopalapuram, Chennai 600086, India; (R.P.); (R.M.A.); (V.M.)
| | - Karani Santhanakrishnan Vimaleswaran
- Hugh Sinclair Unit of Human Nutrition, Department of Food and Nutritional Sciences, University of Reading, Reading RG6 6DZ, UK; (S.A.); (J.A.L.)
- The Institute for Food, Nutrition, and Health (IFNH), University of Reading, Reading RG6 6AP, UK
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Natarajan H, Shanthi Rani CS, Krishna Kumar D, Anjana RM, Ranjit U, Venkatesan U, Uma Sankari G, Pradeepa R, Mohan V, Deepa M. Future risk of diabetes among Indians with metabolic and phenotypic obesity: Results from the 10-year follow-up of the Chennai Urban Rural Epidemiology Study (CURES-158). Acta Diabetol 2021; 58:1051-1058. [PMID: 33759049 DOI: 10.1007/s00592-021-01698-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/15/2020] [Accepted: 02/27/2021] [Indexed: 12/19/2022]
Abstract
AIM To investigate the risk of type 2 diabetes (T2DM) among the combinations of BMI categories and metabolic syndrome in Asian Indians. MATERIALS AND METHODS Individuals from the Chennai Urban Rural Epidemiology Study cohort (n = 1,368), free of diabetes at baseline were stratified by BMI and metabolic health as metabolically healthy non-obese (MHNO), metabolically healthy obese (MHO), metabolically obese non-obese (MONO) and metabolically obese obese (MOO). Phenotypic obesity was defined as BMI ≥ 25 kg/m2 and metabolic obesity as presence of any two of the metabolic abnormalities: hyperglycemia, high blood pressure, high triglyceridemia or low HDL cholesterol. Hazard ratios for progression to diabetes were estimated using Cox proportional hazard regression. RESULTS During median 9.1 years of follow-up, incident cases of diabetes were highest among MOO-45.1%, followed by MONO-41.3%, MHO-27.1% and MHNO-15.9%. Incidence rates of diabetes among MOO, MONO, MHO and MHNO were 57.8, 50.9, 30.4 and 18.1 per 1000 person years, respectively. Hazard ratio for diabetes development were 1.71 in MHO, 2.87 in MONO, and 3.39 in MOO compared with MHNO. CONCLUSIONS Increased BMI and metabolic risk factor clustering independently contribute to the increased risk of T2DM in obese individuals. Screening for metabolic abnormalities should be performed routinely in clinic to identify high-risk individuals and institute appropriate preventive measures.
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Affiliation(s)
- Hariharasudan Natarajan
- Madras Diabetes Research Foundation and Dr. Mohan's Diabetes Specialities Centre, ICMR Center for Advanced Research on Diabetes, No 4, Conran Smith Road, Gopalapuram, Chennai, 600086, India
| | - Coimbatore Subramanian Shanthi Rani
- Madras Diabetes Research Foundation and Dr. Mohan's Diabetes Specialities Centre, ICMR Center for Advanced Research on Diabetes, No 4, Conran Smith Road, Gopalapuram, Chennai, 600086, India
| | - Dharman Krishna Kumar
- Madras Diabetes Research Foundation and Dr. Mohan's Diabetes Specialities Centre, ICMR Center for Advanced Research on Diabetes, No 4, Conran Smith Road, Gopalapuram, Chennai, 600086, India
| | - Ranjit Mohan Anjana
- Madras Diabetes Research Foundation and Dr. Mohan's Diabetes Specialities Centre, ICMR Center for Advanced Research on Diabetes, No 4, Conran Smith Road, Gopalapuram, Chennai, 600086, India
| | - Unnikrishnan Ranjit
- Madras Diabetes Research Foundation and Dr. Mohan's Diabetes Specialities Centre, ICMR Center for Advanced Research on Diabetes, No 4, Conran Smith Road, Gopalapuram, Chennai, 600086, India
| | - Ulagamathesan Venkatesan
- Madras Diabetes Research Foundation and Dr. Mohan's Diabetes Specialities Centre, ICMR Center for Advanced Research on Diabetes, No 4, Conran Smith Road, Gopalapuram, Chennai, 600086, India
| | - Ganesan Uma Sankari
- Madras Diabetes Research Foundation and Dr. Mohan's Diabetes Specialities Centre, ICMR Center for Advanced Research on Diabetes, No 4, Conran Smith Road, Gopalapuram, Chennai, 600086, India
| | - Rajendra Pradeepa
- Madras Diabetes Research Foundation and Dr. Mohan's Diabetes Specialities Centre, ICMR Center for Advanced Research on Diabetes, No 4, Conran Smith Road, Gopalapuram, Chennai, 600086, India
| | - Viswanathan Mohan
- Madras Diabetes Research Foundation and Dr. Mohan's Diabetes Specialities Centre, ICMR Center for Advanced Research on Diabetes, No 4, Conran Smith Road, Gopalapuram, Chennai, 600086, India.
| | - Mohan Deepa
- Madras Diabetes Research Foundation and Dr. Mohan's Diabetes Specialities Centre, ICMR Center for Advanced Research on Diabetes, No 4, Conran Smith Road, Gopalapuram, Chennai, 600086, India
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Vimaleswaran KS, Bodhini D, Jiang J, Ramya K, Mohan D, Shanthi Rani CS, Lakshmipriya N, Sudha V, Pradeepa R, Anjana RM, Mohan V, Radha V. Circulating adiponectin mediates the association between omentin gene polymorphism and cardiometabolic health in Asian Indians. PLoS One 2021; 16:e0238555. [PMID: 33979354 PMCID: PMC8115825 DOI: 10.1371/journal.pone.0238555] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2020] [Accepted: 03/15/2021] [Indexed: 12/17/2022] Open
Abstract
BACKGROUND Plasma omentin levels have been shown to be associated with circulating adiponectin concentrations and cardiometabolic disease-related outcomes. In this study, we aim to examine the association of omentin gene polymorphism with serum adiponectin levels and cardiometabolic health status using a genetic approach, and investigate whether these associations are modified by lifestyle factors. METHODS The study included 945 normal glucose tolerant and 941 unrelated individuals with type 2 diabetes randomly selected from the Chennai Urban Rural Epidemiology Study (CURES), in southern India. Study participants were classified into cardiometabolically healthy and unhealthy, where cardiometabolically healthy were those without hypertension, diabetes, and dyslipidemia. Fasting serum adiponectin levels were measured by radioimmunoassay. The omentin A326T (rs2274907) single nucleotide polymorphism (SNP) was screened by polymerase chain reaction-restriction fragment length polymorphism and direct sequencing. RESULTS The 'A' allele of the omentin SNP was significantly associated with lower adiponectin concentrations after adjusting for age, sex, body mass index (BMI), waist circumference (WC) and cardiometabolic health status (p = 1.90 x 10-47). There was also a significant association between circulating adiponectin concentrations and cardiometabolic health status after adjusting for age, sex, BMI, WC and Omentin SNP (p = 7.47x10-10). However, after adjusting for age, sex, BMI, WC and adiponectin levels, the association of 'A' allele with cardiometabolic health status disappeared (p = 0.79) suggesting that adiponectin serves as a mediator of the association between omentin SNP and cardiometabolic health status. There were no significant interactions between the SNP and dietary factors on adiponectin levels and cardiometabolic health status (p>0.25, for all comparisons). CONCLUSIONS Our findings show that adiponectin might function as a mechanistic link between omentin SNP and increased risk of cardiometabolic diseases independent of common and central obesity in Asian Indians. Before strategies to promote adiponectin modulation could be implemented, further studies are required to confirm the molecular mechanisms involved in this triangular relationship between omentin gene, adiponectin and cardiometabolic diseases.
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Affiliation(s)
- Karani Santhanakrishnan Vimaleswaran
- Department of Food and Nutritional Sciences, Hugh Sinclair Unit of Human Nutrition, University of Reading, Reading, United Kingdom
- Institute for Food, Nutrition, and Health, University of Reading, Reading, United Kingdom
| | - Dhanasekaran Bodhini
- Department of Molecular Genetics, Madras Diabetes Research Foundation, Chennai, India
| | - Juanjie Jiang
- Department of Food and Nutritional Sciences, Hugh Sinclair Unit of Human Nutrition, University of Reading, Reading, United Kingdom
| | - Kandaswamy Ramya
- Department of Molecular Genetics, Madras Diabetes Research Foundation, Chennai, India
| | - Deepa Mohan
- Department of Epidemiology, Madras Diabetes Research Foundation, Chennai, India
| | | | - Nagarajan Lakshmipriya
- Department of Foods, Nutrition and Dietetics Research, Madras Diabetes Research Foundation, Chennai, India
| | - Vasudevan Sudha
- Department of Foods, Nutrition and Dietetics Research, Madras Diabetes Research Foundation, Chennai, India
| | - Rajendra Pradeepa
- Department of Diabetology, Madras Diabetes Research Foundation & Dr. Mohan’s Diabetes Specialities Centre, IDF Centre of Excellence in Diabetes Care, & ICMR Centre for Advanced Research on Diabetes, Gopalapuram, Chennai, India
| | - Ranjit Mohan Anjana
- Department of Diabetology, Madras Diabetes Research Foundation & Dr. Mohan’s Diabetes Specialities Centre, IDF Centre of Excellence in Diabetes Care, & ICMR Centre for Advanced Research on Diabetes, Gopalapuram, Chennai, India
| | - Viswanathan Mohan
- Department of Diabetology, Madras Diabetes Research Foundation & Dr. Mohan’s Diabetes Specialities Centre, IDF Centre of Excellence in Diabetes Care, & ICMR Centre for Advanced Research on Diabetes, Gopalapuram, Chennai, India
| | - Venkatesan Radha
- Department of Molecular Genetics, Madras Diabetes Research Foundation, Chennai, India
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7
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Alvarez-Silva C, Kashani A, Hansen TH, Pinna NK, Anjana RM, Dutta A, Saxena S, Støy J, Kampmann U, Nielsen T, Jørgensen T, Gnanaprakash V, Gnanavadivel R, Sukumaran A, Rani CSS, Færch K, Radha V, Balasubramanyam M, Nair GB, Das B, Vestergaard H, Hansen T, Mande SS, Mohan V, Arumugam M, Pedersen O. Trans-ethnic gut microbiota signatures of type 2 diabetes in Denmark and India. Genome Med 2021; 13:37. [PMID: 33658058 PMCID: PMC7931542 DOI: 10.1186/s13073-021-00856-4] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2020] [Accepted: 02/12/2021] [Indexed: 12/15/2022] Open
Abstract
Background Type 2 diabetes (T2D), a multifactorial disease influenced by host genetics and environmental factors, is the most common endocrine disease. Several studies have shown that the gut microbiota as a close-up environmental mediator influences host physiology including metabolism. The aim of the present study is to examine the compositional and functional potential of the gut microbiota across individuals from Denmark and South India with a focus on T2D. Many earlier studies have investigated the microbiome aspects of T2D, and it has also been anticipated that such microbial associations would be dependent on diet and ethnic origin. However, there has been no large scale trans-ethnic microbiome study earlier in this direction aimed at evaluating any “universal” microbiome signature of T2D. Methods 16S ribosomal RNA gene amplicon sequencing was performed on stool samples from 279 Danish and 294 Indian study participants. Any differences between the gut microbiota of both populations were explored using diversity measures and negative binomial Wald tests. Study samples were stratified to discover global and country-specific microbial signatures for T2D and treatment with the anti-hyperglycemic drug, metformin. To identify taxonomical and functional signatures of the gut microbiota for T2D and metformin treatment, we used alpha and beta diversity measures and differential abundances analysis, comparing metformin-naive T2D patients, metformin-treated T2D patients, and normoglycemic individuals. Results Overall, the gut microbial communities of Danes and Indians are compositionally very different. By analyzing the combined study materials, we identify microbial taxonomic and functional signatures for T2D and metformin treatment. T2D patients have an increased relative abundance of two operational taxonomic units (OTUs) from the Lachnospiraceae family, and a decreased abundance of Subdoligranulum and Butyricicoccus. Studying each population per se, we identified T2D-related microbial changes at the taxonomic level within the Danish population only. Alpha diversity indices show that there is no significant difference between normoglycemic individuals and metformin-naive T2D patients, whereas microbial richness is significantly decreased in metformin-treated T2D patients compared to metformin-naive T2D patients and normoglycemic individuals. Enrichment of two OTUs from Bacteroides and depletion of Faecalibacterium constitute a trans-ethnic signature of metformin treatment. Conclusions We demonstrate major compositional differences of the gut microbiota between Danish and South Indian individuals, some of which may relate to differences in ethnicity, lifestyle, and demography. By comparing metformin-naive T2D patients and normoglycemic individuals, we identify T2D-related microbiota changes in the Danish and Indian study samples. In the present trans-ethnic study, we confirm that metformin changes the taxonomic profile and functional potential of the gut microbiota. Supplementary Information The online version contains supplementary material available at 10.1186/s13073-021-00856-4.
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Affiliation(s)
- Camila Alvarez-Silva
- Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Blegdamsvej 3B, DK-2200, Copenhagen N, Denmark
| | - Alireza Kashani
- Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Blegdamsvej 3B, DK-2200, Copenhagen N, Denmark.,Danish Academy of Diabetes, Odense University Hospital, DK-5000 Odense C, Kløvervænget 6, Odense, Denmark
| | - Tue Haldor Hansen
- Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Blegdamsvej 3B, DK-2200, Copenhagen N, Denmark.,Department of Cardiology and Endocrinology, Slagelse Hospital, Slagelse, Denmark
| | - Nishal Kumar Pinna
- TCS Research, Tata Consultancy Services Limited, 54B Hadapsar Industrial Estate, Pune, 411013, India
| | - Ranjit Mohan Anjana
- Madras Diabetes Research Foundation, No. 4, Conran Smith Road, Gopalapuram, Chennai, 600 086, India
| | - Anirban Dutta
- TCS Research, Tata Consultancy Services Limited, 54B Hadapsar Industrial Estate, Pune, 411013, India
| | - Shruti Saxena
- Molecular Genetics Laboratory, Infections and Immunology, Translational Health Science and Technology Institute, NCR Biotech Science Cluster, Faridabad, 121001, India
| | - Julie Støy
- Steno Diabetes Center Aarhus, Aarhus Universitetshospital, Hedeager 3, 2. sal, Aarhus, 8200, Denmark
| | - Ulla Kampmann
- Steno Diabetes Center Aarhus, Aarhus Universitetshospital, Hedeager 3, 2. sal, Aarhus, 8200, Denmark
| | - Trine Nielsen
- Danish Academy of Diabetes, Odense University Hospital, DK-5000 Odense C, Kløvervænget 6, Odense, Denmark
| | - Torben Jørgensen
- Center for Clinical Research and Prevention, Bispebjerg and Frederiksberg Hospitals, University of Copenhagen, Copenhagen, Denmark
| | - Visvanathan Gnanaprakash
- Madras Diabetes Research Foundation, No. 4, Conran Smith Road, Gopalapuram, Chennai, 600 086, India
| | - Rameshkumar Gnanavadivel
- Madras Diabetes Research Foundation, No. 4, Conran Smith Road, Gopalapuram, Chennai, 600 086, India
| | - Aswath Sukumaran
- Madras Diabetes Research Foundation, No. 4, Conran Smith Road, Gopalapuram, Chennai, 600 086, India
| | | | - Kristine Færch
- Steno Diabetes Center Aarhus, Aarhus Universitetshospital, Hedeager 3, 2. sal, Aarhus, 8200, Denmark
| | - Venkatesan Radha
- Madras Diabetes Research Foundation, No. 4, Conran Smith Road, Gopalapuram, Chennai, 600 086, India
| | | | - Gopinath Balakrish Nair
- Molecular Genetics Laboratory, Infections and Immunology, Translational Health Science and Technology Institute, NCR Biotech Science Cluster, Faridabad, 121001, India
| | - Bhabatosh Das
- Molecular Genetics Laboratory, Infections and Immunology, Translational Health Science and Technology Institute, NCR Biotech Science Cluster, Faridabad, 121001, India
| | - Henrik Vestergaard
- Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Blegdamsvej 3B, DK-2200, Copenhagen N, Denmark
| | - Torben Hansen
- Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Blegdamsvej 3B, DK-2200, Copenhagen N, Denmark
| | - Sharmila Shekhar Mande
- TCS Research, Tata Consultancy Services Limited, 54B Hadapsar Industrial Estate, Pune, 411013, India.
| | - Viswanathan Mohan
- Madras Diabetes Research Foundation, No. 4, Conran Smith Road, Gopalapuram, Chennai, 600 086, India.
| | - Manimozhiyan Arumugam
- Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Blegdamsvej 3B, DK-2200, Copenhagen N, Denmark. .,Faculty of Health Sciences, University of Southern Denmark, Odense, Denmark.
| | - Oluf Pedersen
- Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Blegdamsvej 3B, DK-2200, Copenhagen N, Denmark.
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8
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Pinna NK, Anjana RM, Saxena S, Dutta A, Gnanaprakash V, Rameshkumar G, Aswath S, Raghavan S, Rani CSS, Radha V, Balasubramanyam M, Pant A, Nielsen T, Jørgensen T, Færch K, Kashani A, Silva MCA, Vestergaard H, Hansen TH, Hansen T, Arumugam M, Nair GB, Das B, Pedersen O, Mohan V, Mande SS. Trans-ethnic gut microbial signatures of prediabetic subjects from India and Denmark. Genome Med 2021; 13:36. [PMID: 33658065 PMCID: PMC7931552 DOI: 10.1186/s13073-021-00851-9] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2020] [Accepted: 02/11/2021] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND Recent studies have indicated an association of gut microbiota and microbial metabolites with type 2 diabetes mellitus (T2D). However, large-scale investigation of the gut microbiota of "prediabetic" (PD) subjects has not been reported. Identifying robust gut microbiome signatures of prediabetes and characterizing early prediabetic stages is important for the understanding of disease development and could be crucial in early diagnosis and prevention. METHODS The current study performed amplification and sequencing on the variable regions (V1-V5) of the 16S rRNA genes to profile and compare gut microbiota of prediabetic individuals (N = 262) with normoglycemic individuals (N = 275) from two cohorts in India and Denmark. Similarly, fasting serum inflammatory biomarkers were profiled from the study participants. RESULTS After correcting for strong country-specific cohort effect, 16 operational taxonomic units (OTUs) including members from the genera Prevotella9, Phascolarctobacterium, Barnesiella, Flavonifractor, Tyzzerella_4, Bacteroides, Faecalibacterium, and Agathobacter were identified as enriched in normoglycaemic subjects with respect to the subjects with prediabetes using a negative binomial Wald test. We also identified 144 OTUs enriched in the prediabetic subjects, which included members from the genera Megasphaera, Streptococcus, Prevotella9, Alistipes, Mitsuokella, Escherichia/Shigella, Prevotella2, Vibrio, Lactobacillus, Alloprevotella, Rhodococcus, and Klebsiella. Comparative analyses of relative abundance of bacterial taxa revealed that the Streptococcus, Escherichia/Shigella, Prevotella2, Vibrio, and Alloprevotella OTUs exhibited more than fourfold enrichment in the gut microbiota of prediabetic subjects. When considering subjects from the two geographies separately, we were able to identify additional gut microbiome signatures of prediabetes. The study reports a probable association of Megasphaera OTU(s) with impaired glucose tolerance, which is significantly pronounced in Indian subjects. While the overall results confirm a state of proinflammation as early as in prediabetes, the Indian cohort exhibited a characteristic pattern of abundance of inflammatory markers indicating low-grade intestinal inflammation at an overall population level, irrespective of glycemic status. CONCLUSIONS The results present trans-ethnic gut microbiome and inflammation signatures associated with prediabetes, in Indian and Danish populations. The identified associations may be explored further as potential early indicators for individuals at risk of dysglycemia.
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Affiliation(s)
- Nishal Kumar Pinna
- TCS Research, Tata Consultancy Services Limited, 54B Hadapsar Industrial Estate, Pune, 411013, India
| | - Ranjit Mohan Anjana
- Madras Diabetes Research Foundation, No. 4, Conran Smith Road, Gopalapuram, Chennai, 600 086, India
| | - Shruti Saxena
- Molecular Genetics Laboratory, Infections and Immunology, Translational Health Science and Technology Institute, NCR Biotech Science Cluster, 3rd Milestone, Faridabad - Gurgaon Expressway, PO box #04, Faridabad, 121001, India
| | - Anirban Dutta
- TCS Research, Tata Consultancy Services Limited, 54B Hadapsar Industrial Estate, Pune, 411013, India
| | - Visvanathan Gnanaprakash
- Madras Diabetes Research Foundation, No. 4, Conran Smith Road, Gopalapuram, Chennai, 600 086, India
| | - Gnanavadivel Rameshkumar
- Madras Diabetes Research Foundation, No. 4, Conran Smith Road, Gopalapuram, Chennai, 600 086, India
| | - Sukumaran Aswath
- Madras Diabetes Research Foundation, No. 4, Conran Smith Road, Gopalapuram, Chennai, 600 086, India
| | - Srividhya Raghavan
- Madras Diabetes Research Foundation, No. 4, Conran Smith Road, Gopalapuram, Chennai, 600 086, India
| | | | - Venkatesan Radha
- Madras Diabetes Research Foundation, No. 4, Conran Smith Road, Gopalapuram, Chennai, 600 086, India
| | - Muthuswamy Balasubramanyam
- Madras Diabetes Research Foundation, No. 4, Conran Smith Road, Gopalapuram, Chennai, 600 086, India.,Present address: SRM Medical College Hospital & Research Centre, SRM Institute of Science & Technology (SRMIST), Kattankulathur, Chennai, India
| | - Archana Pant
- Molecular Genetics Laboratory, Infections and Immunology, Translational Health Science and Technology Institute, NCR Biotech Science Cluster, 3rd Milestone, Faridabad - Gurgaon Expressway, PO box #04, Faridabad, 121001, India
| | - Trine Nielsen
- Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Blegdamsvej 3B, Maersk Tower, Building: 07-8-55, DK-2200, Copenhagen N, Denmark
| | - Torben Jørgensen
- Center for Clinical Research and Prevention, Bispebjerg and Frederiksberg Hospitals, University of Copenhagen, Copenhagen, Denmark
| | | | - Alireza Kashani
- Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Blegdamsvej 3B, Maersk Tower, Building: 07-8-55, DK-2200, Copenhagen N, Denmark.,Current affiliation: Qbiom, Microbiome Consultancy Service, Copenhagen, Denmark
| | - Maria Camila Alvarez Silva
- Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Blegdamsvej 3B, Maersk Tower, Building: 07-8-55, DK-2200, Copenhagen N, Denmark
| | - Henrik Vestergaard
- Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Blegdamsvej 3B, Maersk Tower, Building: 07-8-55, DK-2200, Copenhagen N, Denmark
| | - Tue Haldor Hansen
- Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Blegdamsvej 3B, Maersk Tower, Building: 07-8-55, DK-2200, Copenhagen N, Denmark.,Department of Cardiology and Endocrinology, Slagelse Hospital, Slagelse, Denmark
| | - Torben Hansen
- Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Blegdamsvej 3B, Maersk Tower, Building: 07-8-55, DK-2200, Copenhagen N, Denmark
| | - Manimozhiyan Arumugam
- Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Blegdamsvej 3B, Maersk Tower, Building: 07-8-55, DK-2200, Copenhagen N, Denmark
| | - Gopinath Balakrish Nair
- Molecular Genetics Laboratory, Infections and Immunology, Translational Health Science and Technology Institute, NCR Biotech Science Cluster, 3rd Milestone, Faridabad - Gurgaon Expressway, PO box #04, Faridabad, 121001, India
| | - Bhabatosh Das
- Molecular Genetics Laboratory, Infections and Immunology, Translational Health Science and Technology Institute, NCR Biotech Science Cluster, 3rd Milestone, Faridabad - Gurgaon Expressway, PO box #04, Faridabad, 121001, India.
| | - Oluf Pedersen
- Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Blegdamsvej 3B, Maersk Tower, Building: 07-8-55, DK-2200, Copenhagen N, Denmark.
| | - Viswanathan Mohan
- Madras Diabetes Research Foundation, No. 4, Conran Smith Road, Gopalapuram, Chennai, 600 086, India.
| | - Sharmila Shekhar Mande
- TCS Research, Tata Consultancy Services Limited, 54B Hadapsar Industrial Estate, Pune, 411013, India.
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9
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Ghosh A, Anjana RM, Shanthi Rani CS, Jeba Rani S, Gupta R, Jha A, Gupta V, Kuchay MS, Luthra A, Durrani S, Dutta K, Tyagi K, Unnikrishnan R, Srivastava BK, Ramu M, Sastry NG, Gupta PK, Umasankari G, Jayashri R, Mohan V, Misra A. Glycemic parameters in patients with new-onset diabetes during COVID-19 pandemic are more severe than in patients with new-onset diabetes before the pandemic: NOD COVID India Study. Diabetes Metab Syndr 2021; 15:215-220. [PMID: 33450530 PMCID: PMC7771314 DOI: 10.1016/j.dsx.2020.12.033] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/14/2020] [Revised: 12/18/2020] [Accepted: 12/18/2020] [Indexed: 12/12/2022]
Abstract
BACKGROUND AND AIMS It is not known if new onset diabetes during Coronavirus-19 disease (COVID-19; NOD COVID) is phenotypically or biochemically different than new onset diabetes before COVID-19 (NOD). METHODS All adults diagnosed with new onset diabetes from during the time of COVID-19 were compared with new onset diabetes prior to COVID-19 from two tertiary care hospitals in Chennai and Delhi. RTPCR test for SARS-CoV-2 virus was done as appropriate, and COVID-19 antibody test was done in all other NOD COVID patients. RESULT A total of 555 patients with new onset diabetes were included in the study (282 NOD and 273 NOD COVID patients). Patients with NOD COVID had higher fasting and post prandial blood glucose and glycated hemoglobin levels vs. NOD patients. Both the groups had high average body mass index; ∼28 kg/m2. Interestingly, fasting C-peptide levels were significantly higher in the NOD COVID group vs. NOD group. There was no difference in C-peptide levels or glycemic parameters between the COVID-19 antibody positive and negative NOD COVID cases. CONCLUSION Individuals who were diagnosed with diabetes during COVID-19 epidemic (NOD COVID) do not significantly differ from those diagnosed before COVID-19 in symptomatology, phenotype, and C-peptide levels but they had more severe glycemia.
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Affiliation(s)
- Amerta Ghosh
- Fortis CDOC Centre for Diabetes and Allied Sciences, New Delhi, India
| | - Ranjit Mohan Anjana
- Madras Diabetes Research Foundation & Dr. Mohan's Diabetes Specialities Centre, Chennai, India
| | | | - Saravanan Jeba Rani
- Madras Diabetes Research Foundation & Dr. Mohan's Diabetes Specialities Centre, Chennai, India
| | - Ritesh Gupta
- Fortis CDOC Centre for Diabetes and Allied Sciences, New Delhi, India
| | - Alka Jha
- Fortis CDOC Centre for Diabetes and Allied Sciences, New Delhi, India
| | - Vimal Gupta
- Fortis CDOC Centre for Diabetes and Allied Sciences, New Delhi, India
| | | | - Atul Luthra
- Fortis CDOC Center for Diabetes, Fortis Memorial Institute, Gurgaon, India
| | - Suhail Durrani
- Fortis CDOC Centre for Diabetes and Allied Sciences, New Delhi, India
| | - Koel Dutta
- Fortis CDOC Centre for Diabetes and Allied Sciences, New Delhi, India
| | - Kanika Tyagi
- Fortis CDOC Centre for Diabetes and Allied Sciences, New Delhi, India
| | - Ranjit Unnikrishnan
- Madras Diabetes Research Foundation & Dr. Mohan's Diabetes Specialities Centre, Chennai, India
| | | | - Muthu Ramu
- Madras Diabetes Research Foundation & Dr. Mohan's Diabetes Specialities Centre, Chennai, India
| | | | - Prasanna Kumar Gupta
- Madras Diabetes Research Foundation & Dr. Mohan's Diabetes Specialities Centre, Chennai, India
| | - Ganesan Umasankari
- Madras Diabetes Research Foundation & Dr. Mohan's Diabetes Specialities Centre, Chennai, India
| | - Ramamoorthy Jayashri
- Madras Diabetes Research Foundation & Dr. Mohan's Diabetes Specialities Centre, Chennai, India
| | - Viswanathan Mohan
- Madras Diabetes Research Foundation & Dr. Mohan's Diabetes Specialities Centre, Chennai, India.
| | - Anoop Misra
- Fortis CDOC Centre for Diabetes and Allied Sciences, New Delhi, India; National Diabetes, Obesity and Cholesterol Foundation, New Delhi, India; Diabetes Foundation (India), New Delhi, India.
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10
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Mohan V, Anjana RM, Unnikrishnan R, Venkatesan U, Uma Sankari G, Rahulashankiruthiyayan T, Samhita SK, Subramanian Shanthi Rani C. Incidence of hypertension among Asian Indians: 10 year follow up of the Chennai Urban Rural Epidemiology Study (CURES-153). J Diabetes Complications 2020; 34:107652. [PMID: 32595016 DOI: 10.1016/j.jdiacomp.2020.107652] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/06/2020] [Revised: 06/01/2020] [Accepted: 06/06/2020] [Indexed: 10/24/2022]
Abstract
AIMS There are very few studies on incidence of hypertension from developing countries. We report on the incidence of hypertension and its risk factors in Chennai city in southern India. METHODS Participants were 1691 individuals from the Chennai Urban Rural Epidemiology Study (CURES) cohorts who did not have hypertension (normotensive n = 878, prehypertension n = 813) at baseline and who were followed for a median of 9.0 years. During the follow-up, 41 with missing blood pressure values were excluded, leaving 1650 individuals for the present analysis. Incidence rates of hypertension and predictors of progression to prehypertension and/or hypertension were estimated using Cox proportional hazards model. RESULTS During the follow-up period, 426 out of 1650 individuals developed hypertension, giving an overall incidence of hypertension of 28.7(95%CI 26.1-31.5) per 1000 person-years. Individuals with dysglycemia at baseline had higher incident rates of hypertension. Collectively, four modifiable risk factors [pre-hypertension, dysglycemia, central obesity and physical inactivity] accounted for 87.2% of the population attributable risk of incident hypertension. CONCLUSIONS Higher body weight, BMI, age and dysglycemia were associated with an increased risk of incident hypertension. Prehypertension, dysglycemia, central obesity and physical inactivity accounted for 87% of incident hypertension.
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Affiliation(s)
- Viswanathan Mohan
- Madras Diabetes Research Foundation & Dr. Mohan's Diabetes Specialities Centre, WHO Collaborating Centre for Non-communicable Diseases Prevention and Control & ICMR Center for Advanced Research on Diabetes, Chennai, India.
| | - Ranjit Mohan Anjana
- Madras Diabetes Research Foundation & Dr. Mohan's Diabetes Specialities Centre, WHO Collaborating Centre for Non-communicable Diseases Prevention and Control & ICMR Center for Advanced Research on Diabetes, Chennai, India
| | - Ranjit Unnikrishnan
- Madras Diabetes Research Foundation & Dr. Mohan's Diabetes Specialities Centre, WHO Collaborating Centre for Non-communicable Diseases Prevention and Control & ICMR Center for Advanced Research on Diabetes, Chennai, India
| | - Ulagamathesan Venkatesan
- Madras Diabetes Research Foundation & Dr. Mohan's Diabetes Specialities Centre, WHO Collaborating Centre for Non-communicable Diseases Prevention and Control & ICMR Center for Advanced Research on Diabetes, Chennai, India
| | - Ganesan Uma Sankari
- Madras Diabetes Research Foundation & Dr. Mohan's Diabetes Specialities Centre, WHO Collaborating Centre for Non-communicable Diseases Prevention and Control & ICMR Center for Advanced Research on Diabetes, Chennai, India
| | - Thangarajan Rahulashankiruthiyayan
- Madras Diabetes Research Foundation & Dr. Mohan's Diabetes Specialities Centre, WHO Collaborating Centre for Non-communicable Diseases Prevention and Control & ICMR Center for Advanced Research on Diabetes, Chennai, India
| | - Sharat Kumar Samhita
- Madras Diabetes Research Foundation & Dr. Mohan's Diabetes Specialities Centre, WHO Collaborating Centre for Non-communicable Diseases Prevention and Control & ICMR Center for Advanced Research on Diabetes, Chennai, India
| | - Coimbatore Subramanian Shanthi Rani
- Madras Diabetes Research Foundation & Dr. Mohan's Diabetes Specialities Centre, WHO Collaborating Centre for Non-communicable Diseases Prevention and Control & ICMR Center for Advanced Research on Diabetes, Chennai, India
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11
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Anjana RM, Pradeepa R, Deepa M, Jebarani S, Venkatesan U, Parvathi SJ, Balasubramanyam M, Radha V, Poongothai S, Sudha V, Shanthi Rani CS, Ranjani H, Amutha A, Manickam N, Unnikrishnan R, Mohan V. Acceptability and Utilization of Newer Technologies and Effects on Glycemic Control in Type 2 Diabetes: Lessons Learned from Lockdown. Diabetes Technol Ther 2020; 22:527-534. [PMID: 32522031 DOI: 10.1089/dia.2020.0240] [Citation(s) in RCA: 34] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
Aim: To evaluate the effects of a prolonged lockdown due to Coronavirus (COVID-19) on the adoption of newer technologies and changes in glycemic control on patients with type 2 diabetes (T2D) in India. Methods: The study population included a random list of 3000 individuals with T2D derived from 30,748 individuals who had visited a large tertiary diabetes center during the past year. The survey was carried out through a telephonic interview. A structured questionnaire was used to collect information on changes in lifestyle, access and challenges to diabetes care and use of technologies such as telemedicine facilities and use of self-monitoring of blood glucose (SMBG), etc. Results: Of the 2510 individuals successfully interviewed (83.7% response rate), 382 (15.2%) reported having attempted to consult their health care providers during the lockdown, of whom only 30.6% utilized the telemedicine facility. However, 96 (82%) of those who utilized the telemedicine facility (n = 117) were happy with their experience and 68 (58.1%) were willing to continue to use the facility in the future. Only 11.4% of participants utilized online support for management of diabetes. Use of SMBG increased significantly from 15.5% to 51.3% during the lockdown. There was an improvement in glycemic control during the lockdown (HbA1c:before vs. during lockdown: 8.2% ± 1.9% vs. 7.7% ± 1.7%, P < 0.001) in a nonrandomly selected subset of subjects (n = 205). Conclusions: Acceptance of telemedicine facilities remains suboptimal in this Asian Indian population, in spite of high levels of satisfaction among those who utilized it. The COVID-19 pandemic and the subsequent lockdown have not adversely affected metabolic control in our patients, and indeed there appears to be an improvement in HbA1c levels. Greater accessibility and acceptance of technology could help individuals with diabetes to maintain better contact with their physicians and ensure better metabolic control in the future.
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Affiliation(s)
- Ranjit Mohan Anjana
- Madras Diabetes Research Foundation and Dr. Mohan's Diabetes Specialities Centre, Chennai, India
| | - Rajendra Pradeepa
- Madras Diabetes Research Foundation and Dr. Mohan's Diabetes Specialities Centre, Chennai, India
| | - Mohan Deepa
- Madras Diabetes Research Foundation and Dr. Mohan's Diabetes Specialities Centre, Chennai, India
| | - Saravanan Jebarani
- Madras Diabetes Research Foundation and Dr. Mohan's Diabetes Specialities Centre, Chennai, India
| | - Ulagamathesan Venkatesan
- Madras Diabetes Research Foundation and Dr. Mohan's Diabetes Specialities Centre, Chennai, India
| | | | | | - Venkatesan Radha
- Madras Diabetes Research Foundation and Dr. Mohan's Diabetes Specialities Centre, Chennai, India
| | - Subramani Poongothai
- Madras Diabetes Research Foundation and Dr. Mohan's Diabetes Specialities Centre, Chennai, India
| | - Vasudevan Sudha
- Madras Diabetes Research Foundation and Dr. Mohan's Diabetes Specialities Centre, Chennai, India
| | | | - Harish Ranjani
- Madras Diabetes Research Foundation and Dr. Mohan's Diabetes Specialities Centre, Chennai, India
| | - Anandakumar Amutha
- Madras Diabetes Research Foundation and Dr. Mohan's Diabetes Specialities Centre, Chennai, India
| | - Nagaraj Manickam
- Madras Diabetes Research Foundation and Dr. Mohan's Diabetes Specialities Centre, Chennai, India
| | - Ranjit Unnikrishnan
- Madras Diabetes Research Foundation and Dr. Mohan's Diabetes Specialities Centre, Chennai, India
| | - Viswanathan Mohan
- Madras Diabetes Research Foundation and Dr. Mohan's Diabetes Specialities Centre, Chennai, India
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12
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Alathari BE, Bodhini D, Jayashri R, Lakshmipriya N, Shanthi Rani CS, Sudha V, Lovegrove JA, Anjana RM, Mohan V, Radha V, Pradeepa R, Vimaleswaran KS. A Nutrigenetic Approach to Investigate the Relationship between Metabolic Traits and Vitamin D Status in an Asian Indian Population. Nutrients 2020; 12:E1357. [PMID: 32397403 PMCID: PMC7285077 DOI: 10.3390/nu12051357] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2020] [Revised: 04/27/2020] [Accepted: 05/06/2020] [Indexed: 12/11/2022] Open
Abstract
Studies in Asian Indians have examined the association of metabolic traits with vitamin D status. However, findings have been quite inconsistent. Hence, we aimed to explore the relationship between metabolic traits and 25-hydroxyvitamin D [25(OH)D] concentrations. We investigate whether this relationship was modified by lifestyle factors using a nutrigenetic approach in 545 Asian Indians randomly selected from the Chennai Urban Rural Epidemiology Study (219 normal glucose tolerant individuals, 151 with pre-diabetes and 175 individuals with type 2 diabetes). A metabolic genetic risk score (GRS) was developed using five common metabolic disease-related genetic variants. There was a significant interaction between metabolic GRS and carbohydrate intake (energy%) on 25(OH)D (Pinteraction = 0.047). Individuals consuming a low carbohydrate diet (≤62%) and those having lesser number of metabolic risk alleles (GRS ≤ 1) had significantly higher levels of 25(OH)D (p = 0.033). Conversely, individuals consuming a high carbohydrate diet despite having lesser number of risk alleles did not show a significant increase in 25(OH)D (p = 0.662). In summary, our findings show that individuals carrying a smaller number of metabolic risk alleles are likely to have higher 25(OH)D levels if they consume a low carbohydrate diet. These data support the current dietary carbohydrate recommendations of 50%-60% energy suggesting that reduced metabolic genetic risk increases 25(OH)D.
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Affiliation(s)
- Buthaina E. Alathari
- Hugh Sinclair Unit of Human Nutrition, Department of Food and Nutritional Sciences, University of Reading, Reading RG6 6AP, UK; (B.E.A.); (J.A.L.)
- Department of Food Science and Nutrition, Faculty of Health Sciences, The Public Authority for Applied Education and Training, PO Box 14281, AlFaiha 72853, Kuwait
| | - Dhanasekaran Bodhini
- Department of Molecular Genetics, Madras Diabetes Research Foundation, Chennai 603103, India; (D.B.); (V.R.)
| | - Ramamoorthy Jayashri
- Department of Biochemistry, Madras Diabetes Research Foundation, Chennai 600086, India;
| | - Nagarajan Lakshmipriya
- Department of Foods, Nutrition and Dietetics Research, Madras Diabetes Research Foundation, Chennai 600086, India; (N.L.); (V.S.)
| | | | - Vasudevan Sudha
- Department of Foods, Nutrition and Dietetics Research, Madras Diabetes Research Foundation, Chennai 600086, India; (N.L.); (V.S.)
| | - Julie A. Lovegrove
- Hugh Sinclair Unit of Human Nutrition, Department of Food and Nutritional Sciences, University of Reading, Reading RG6 6AP, UK; (B.E.A.); (J.A.L.)
| | - Ranjit Mohan Anjana
- Department of Diabetology, Madras Diabetes Research Foundation & Dr. Mohan′s Diabetes Specialities Centre, WHO Collaborating Centre for Non-communicable Diseases Prevention and Control, ICMR Centre for Advanced Research on Diabetes, Gopalapuram, Chennai 600086, India; (R.M.A.); (V.M.); (R.P.)
| | - Viswanathan Mohan
- Department of Diabetology, Madras Diabetes Research Foundation & Dr. Mohan′s Diabetes Specialities Centre, WHO Collaborating Centre for Non-communicable Diseases Prevention and Control, ICMR Centre for Advanced Research on Diabetes, Gopalapuram, Chennai 600086, India; (R.M.A.); (V.M.); (R.P.)
| | - Venkatesan Radha
- Department of Molecular Genetics, Madras Diabetes Research Foundation, Chennai 603103, India; (D.B.); (V.R.)
| | - Rajendra Pradeepa
- Department of Diabetology, Madras Diabetes Research Foundation & Dr. Mohan′s Diabetes Specialities Centre, WHO Collaborating Centre for Non-communicable Diseases Prevention and Control, ICMR Centre for Advanced Research on Diabetes, Gopalapuram, Chennai 600086, India; (R.M.A.); (V.M.); (R.P.)
| | - Karani S. Vimaleswaran
- Hugh Sinclair Unit of Human Nutrition, Department of Food and Nutritional Sciences, University of Reading, Reading RG6 6AP, UK; (B.E.A.); (J.A.L.)
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Rajalakshmi R, Shanthi Rani CS, Venkatesan U, Unnikrishnan R, Anjana RM, Jeba Rani S, UmaSankari G, Sivaprasad S, Raman R, Mohan V. Correlation between markers of renal function and sight-threatening diabetic retinopathy in type 2 diabetes: a longitudinal study in an Indian clinic population. BMJ Open Diabetes Res Care 2020; 8:8/1/e001325. [PMID: 32475840 PMCID: PMC7265015 DOI: 10.1136/bmjdrc-2020-001325] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/29/2020] [Revised: 04/11/2020] [Accepted: 04/28/2020] [Indexed: 01/10/2023] Open
Abstract
INTRODUCTION Previous epidemiological studies have reported on the prevalence of diabetic kidney disease (DKD) and diabetic retinopathy (DR) from India. The aim of this study is to evaluate the effect of DKD on the development of new-onset DR and sight-threatening diabetic retinopathy (STDR) in Asian Indians with type 2 diabetes (T2D). RESEARCH DESIGN AND METHODS The study was done on anonymized electronic medical record data of people with T2D who had undergone screening for DR and renal work-up as part of routine follow-up at a tertiary care diabetes center in Chennai, South India. The baseline data retrieved included clinical and biochemical parameters including renal profiles (serum creatinine, estimated glomerular filtration rate (eGFR) and albuminuria). Grading of DR was performed using the modified Early Treatment Diabetic Retinopathy Study grading system. STDR was defined as the presence of proliferative diabetic retinopathy (PDR) and/or diabetic macular edema. DKD was defined by the presence of albuminuria (≥30 µg/mg) and/or reduction in eGFR (<60 mL/min/1.73 m2). Cox regression analysis was used to evaluate the hazard ratio (HR) for DR and STDR. RESULTS Data of 19 909 individuals with T2D (mean age 59.6±10.2 years, mean duration of diabetes 11.1±12.1 years, 66.1% male) were analyzed. At baseline, DR was present in 7818 individuals (39.3%), of whom 2249 (11.3%) had STDR. During the mean follow-up period of 3.9±1.9 years, 2140 (17.7%) developed new-onset DR and 980 individuals with non-proliferative DR (NPDR) at baseline progressed to STDR. Higher serum creatinine (HR 1.5, 95% CI 1.3 to 1.7; p<0.0001), eGFR <30 mL/min/1.73 m2 (HR 4.9, 95% CI 2.9 to 8.2; p<0.0001) and presence of macroalbuminuria >300 µg/mg (HR 3.0, 95% CI 2.4 to 3.8; p<0.0001) at baseline were associated with increased risk of progression to STDR. CONCLUSIONS DKD at baseline is a risk factor for progression to STDR. Physicians should promptly refer their patients with DKD to ophthalmologists for timely detection and management of STDR.
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Affiliation(s)
- Ramachandran Rajalakshmi
- Ophthalmology, Madras Diabetes Research Foundation and Dr. Mohan's Diabetes Specialities Centre, Chennai, Tamil Nadu, India
| | | | | | - Ranjit Unnikrishnan
- Diabetology, Madras Diabetes Research Foundation and Dr. Mohan's Diabetes Specialities Centre, Chennai, Tamil Nadu, India
| | - Ranjit Mohan Anjana
- Diabetology, Madras Diabetes Research Foundation and Dr. Mohan's Diabetes Specialities Centre, Chennai, Tamil Nadu, India
| | - Saravanan Jeba Rani
- Data Management, Madras Diabetes Research Foundation, Chennai, Tamil Nadu, India
| | - Ganesan UmaSankari
- Epidemiology, Madras Diabetes Research Foundation, Chennai, Tamil Nadu, India
| | - Sobha Sivaprasad
- University College London, London, UK
- NIHR Moorfields Biomedical Research Centre, Moorfields Eye Hospital NHS Foundation Trust, London, UK
| | - Rajiv Raman
- Vitreo-Retina Services, Vision Research Foundation, Chennai, Tamil Nadu, India
| | - Viswanathan Mohan
- Diabetology, Madras Diabetes Research Foundation and Dr. Mohan's Diabetes Specialities Centre, Chennai, Tamil Nadu, India
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Surendran S, Jayashri R, Drysdale L, Bodhini D, Lakshmipriya N, Shanthi Rani CS, Sudha V, Lovegrove JA, Anjana RM, Mohan V, Radha V, Pradeepa R, Vimaleswaran KS. Evidence for the association between FTO gene variants and vitamin B12 concentrations in an Asian Indian population. Genes Nutr 2019; 14:26. [PMID: 31516636 PMCID: PMC6728975 DOI: 10.1186/s12263-019-0649-3] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/09/2019] [Accepted: 07/30/2019] [Indexed: 12/15/2022]
Abstract
BACKGROUND Low vitamin B12 concentrations have been associated with major clinical outcomes, including adiposity, in Indian populations. The Fat mass and obesity-associated gene (FTO) is an established obesity-susceptibility locus; however, it remains unknown whether it influences vitamin B12 status. Hence, we investigated the association of two previously studied FTO polymorphisms with vitamin B12 concentrations and metabolic disease-related outcomes and examined whether these associations were modified by dietary factors and physical activity. METHODS A total of 176 individuals with type 2 diabetes, 152 with pre-diabetes, and 220 normal glucose-tolerant individuals were randomly selected from the Chennai Urban Rural Epidemiology Study. Anthropometric, clinical, and biochemical investigations, which included body mass index (BMI), waist circumference, vitamin B12, homocysteine, and folic acid were measured. A validated food frequency questionnaire was used for dietary assessment and self-reported physical activity measures were collected. An unweighted genetic risk score (GRS) was calculated for two FTO single-nucleotide polymorphisms (rs8050136 and rs2388405) by summation of the number of risk alleles for obesity. Interaction analyses were performed by including the interaction terms in the regression model. RESULTS The GRS was significantly associated with increased BMI (P = 0.009) and risk of obesity (P = 0.023). Individuals carrying more than one risk allele for the GRS had 13.13% lower vitamin B12 concentrations, compared to individuals carrying zero risk alleles (P = 0.018). No associations between the GRS and folic acid and homocysteine concentrations were observed. Furthermore, no statistically significant GRS-diet or GRS-physical activity interactions with vitamin B12, folic acid, homocysteine or metabolic-disease outcomes were observed. CONCLUSION The study shows for the first time that a genetic risk score using two FTO SNPs is associated with lower vitamin B12 concentrations; however, we did not identify any evidence for the influence of lifestyle factors on this association. Further replication studies in larger cohorts are warranted to investigate the association between the GRS and vitamin B12 concentrations.
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Affiliation(s)
- Shelini Surendran
- Hugh Sinclair Unit of Human Nutrition and Institute for Cardiovascular and Metabolic Research (ICMR), Department of Food and Nutritional Sciences, University of Reading, Whiteknights, PO Box 226, Reading, RG6 6AP UK
| | - Ramamoorthy Jayashri
- Department of Diabetology, Madras Diabetes Research Foundation and Dr. Mohan’s Diabetes Specialities Centre, WHO Collaborating Centre for Non-communicable Diseases Prevention and Control, ICMR Centre for Advanced Research on Diabetes, Gopalapuram, Chennai, 600086 India
| | - Lauren Drysdale
- School of Psychology and Clinical Language Sciences, University of Reading, Reading, UK
| | - Dhanasekaran Bodhini
- Department of Molecular Genetics, Madras Diabetes Research Foundation, Chennai, India
| | - Nagarajan Lakshmipriya
- Department of Foods, Nutrition and Dietetics Research, Madras Diabetes Research Foundation, Chennai, India
| | | | - Vasudevan Sudha
- Department of Foods, Nutrition and Dietetics Research, Madras Diabetes Research Foundation, Chennai, India
| | - Julie A. Lovegrove
- Hugh Sinclair Unit of Human Nutrition and Institute for Cardiovascular and Metabolic Research (ICMR), Department of Food and Nutritional Sciences, University of Reading, Whiteknights, PO Box 226, Reading, RG6 6AP UK
| | - Ranjit M. Anjana
- Department of Diabetology, Madras Diabetes Research Foundation and Dr. Mohan’s Diabetes Specialities Centre, WHO Collaborating Centre for Non-communicable Diseases Prevention and Control, ICMR Centre for Advanced Research on Diabetes, Gopalapuram, Chennai, 600086 India
| | - Viswanathan Mohan
- Department of Diabetology, Madras Diabetes Research Foundation and Dr. Mohan’s Diabetes Specialities Centre, WHO Collaborating Centre for Non-communicable Diseases Prevention and Control, ICMR Centre for Advanced Research on Diabetes, Gopalapuram, Chennai, 600086 India
| | - Venkatesan Radha
- Department of Molecular Genetics, Madras Diabetes Research Foundation, Chennai, India
| | - Rajendra Pradeepa
- Department of Diabetology, Madras Diabetes Research Foundation and Dr. Mohan’s Diabetes Specialities Centre, WHO Collaborating Centre for Non-communicable Diseases Prevention and Control, ICMR Centre for Advanced Research on Diabetes, Gopalapuram, Chennai, 600086 India
| | - Karani S. Vimaleswaran
- Hugh Sinclair Unit of Human Nutrition and Institute for Cardiovascular and Metabolic Research (ICMR), Department of Food and Nutritional Sciences, University of Reading, Whiteknights, PO Box 226, Reading, RG6 6AP UK
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Jayashri R, Venkatesan U, Rohan M, Gokulakrishnan K, Shanthi Rani CS, Deepa M, Anjana RM, Mohan V, Pradeepa R. Prevalence of vitamin B 12 deficiency in South Indians with different grades of glucose tolerance. Acta Diabetol 2018; 55:1283-1293. [PMID: 30317438 DOI: 10.1007/s00592-018-1240-x] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/17/2018] [Accepted: 10/03/2018] [Indexed: 01/12/2023]
Abstract
AIMS To determine the prevalence of vitamin B12 deficiency in an urban south Indian population in individuals with different grades of glucose tolerance. METHODS A total of 1500 individuals [900 normal glucose tolerance (NGT), 300 prediabetes and 300 type 2 diabetes (T2DM)] who were not on vitamin B12 supplementation were randomly selected from the Chennai Urban Rural Epidemiological Study (CURES) follow-up study. Anthropometric, clinical and biochemical investigations, which included vitamin B12, insulin, homocysteine, HbA1c and serum lipids, were measured. Vitamin B12 ≤ 191 pg/ml was defined as absolute vitamin B12 deficiency and vitamin B12 > 191 pg/ml and ≤ 350 pg/ml as borderline deficiency. RESULTS The mean levels of vitamin B12 significantly decreased with increasing degrees of glucose tolerance (NGT 444 ± 368; prediabetes 409 ± 246; T2DM 389 ± 211 pg/ml, p = 0.021). The prevalence of absolute vitamin B12 deficiency was 14.9% while 37.6% had borderline deficiency. The prevalence of absolute vitamin B12 deficiency was significantly higher among individuals with T2DM (18.7%) followed by prediabetes (15%) and NGT(13.7%) [p for trend = 0.05]. The prevalence of vitamin B12 significantly increased with age (p < 0.05) and in those with abdominal obesity (p < 0.001). Men and vegetarians had twice the risk of vitamin B12 deficiency compared to women and non-vegetarians, respectively. Among individuals with NGT, prediabetes and T2DM, vitamin B12 negatively correlated with homocysteine. CONCLUSION This study reports that the levels of vitamin B12 decreased with increasing severity of glucose tolerance.
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Affiliation(s)
- Ramamoorthy Jayashri
- Madras Diabetes Research Foundation, Dr. Mohan's Diabetes Specialities Centre, WHO Collaborating Centre for Non-communicable Diseases Prevention and Control, ICMR Centre for Advanced Research on Diabetes, No:6B, Conran Smith Road, Gopalapuram, Chennai, 600086, India
| | - Ulagamathesan Venkatesan
- Madras Diabetes Research Foundation, Dr. Mohan's Diabetes Specialities Centre, WHO Collaborating Centre for Non-communicable Diseases Prevention and Control, ICMR Centre for Advanced Research on Diabetes, No:6B, Conran Smith Road, Gopalapuram, Chennai, 600086, India
| | - Menon Rohan
- Madras Diabetes Research Foundation, Dr. Mohan's Diabetes Specialities Centre, WHO Collaborating Centre for Non-communicable Diseases Prevention and Control, ICMR Centre for Advanced Research on Diabetes, No:6B, Conran Smith Road, Gopalapuram, Chennai, 600086, India
| | - Kuppan Gokulakrishnan
- Madras Diabetes Research Foundation, Dr. Mohan's Diabetes Specialities Centre, WHO Collaborating Centre for Non-communicable Diseases Prevention and Control, ICMR Centre for Advanced Research on Diabetes, No:6B, Conran Smith Road, Gopalapuram, Chennai, 600086, India
| | - Coimbatore Subramanian Shanthi Rani
- Madras Diabetes Research Foundation, Dr. Mohan's Diabetes Specialities Centre, WHO Collaborating Centre for Non-communicable Diseases Prevention and Control, ICMR Centre for Advanced Research on Diabetes, No:6B, Conran Smith Road, Gopalapuram, Chennai, 600086, India
| | - Mohan Deepa
- Madras Diabetes Research Foundation, Dr. Mohan's Diabetes Specialities Centre, WHO Collaborating Centre for Non-communicable Diseases Prevention and Control, ICMR Centre for Advanced Research on Diabetes, No:6B, Conran Smith Road, Gopalapuram, Chennai, 600086, India
| | - Ranjit Mohan Anjana
- Madras Diabetes Research Foundation, Dr. Mohan's Diabetes Specialities Centre, WHO Collaborating Centre for Non-communicable Diseases Prevention and Control, ICMR Centre for Advanced Research on Diabetes, No:6B, Conran Smith Road, Gopalapuram, Chennai, 600086, India
| | - Viswanathan Mohan
- Madras Diabetes Research Foundation, Dr. Mohan's Diabetes Specialities Centre, WHO Collaborating Centre for Non-communicable Diseases Prevention and Control, ICMR Centre for Advanced Research on Diabetes, No:6B, Conran Smith Road, Gopalapuram, Chennai, 600086, India
| | - Rajendra Pradeepa
- Madras Diabetes Research Foundation, Dr. Mohan's Diabetes Specialities Centre, WHO Collaborating Centre for Non-communicable Diseases Prevention and Control, ICMR Centre for Advanced Research on Diabetes, No:6B, Conran Smith Road, Gopalapuram, Chennai, 600086, India.
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Anjana RM, Unnikrishnan R, Mugilan P, Jagdish PS, Parthasarathy B, Deepa M, Loganathan G, Kumar RA, Rahulashankiruthiyayan T, Uma Sankari G, Venkatesan U, Mohan V, Shanthi Rani CS. Causes and predictors of mortality in Asian Indians with and without diabetes-10 year follow-up of the Chennai Urban Rural Epidemiology Study (CURES - 150). PLoS One 2018; 13:e0197376. [PMID: 29985959 PMCID: PMC6037346 DOI: 10.1371/journal.pone.0197376] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2017] [Accepted: 05/01/2018] [Indexed: 02/06/2023] Open
Abstract
Background The incidence and prevalence of diabetes is increasing worldwide and it is the fifth leading cause of mortality accounting for over 3.8 million deaths annually. Despite the enormity of the diabetes-related health burdens, very few studies have evaluated the factors associated with mortality among people with diabetes in India. We sought to study the causes and predictors of mortality among urban Asian Indians with and without diabetes. Methods and findings Of 2273 adults (27,850 person-years of follow-up) from the 10-year follow-up of the Chennai Urban Rural Epidemiology Study (CURES), the cause of death could be ascertained in 552 individuals out of the 671 who had died (response rate 82.3%). Verbal autopsy was obtained from the family members of the deceased and this was adjudicated by trained physicians. The age-standardized mortality rate was 28.2 (95%CI 25.9–30.6) per 100,000 population. Mortality rates were significantly higher in individuals with diabetes compared to those without [27.9(95% CI 25.5–30.6) vs. 8.0 (6.6–9.9) per 1000 person years]. Compared to individuals of normal body mass index, underweight individuals had higher risk of mortality (Hazard ratio 1.49; 95% CI 1.11–2.0), whereas overweight and obese individuals did not show a higher risk. The population-attributable risk for all-cause mortality in the entire study cohort was highest for ischemic heart disease and diabetes. The excess mortality attributable to diabetes was highest in the age group of 51 to 70 years, and was mostly accounted for by renal disease (Rate ratio 5.68, 95%CI 2.43–6.23), ischemic heart disease (4.23,2.78–6.67), and cerebrovascular disease (4.00,1.87–9.81). Conclusion Underweight (but not overweight or obesity) was strongly associated with mortality in this Asian Indian population. Ischemic heart disease and diabetes contributed the most to risk for all cause mortality. Excess mortality due to diabetes was higher in relatively younger individuals and was mostly accounted for by renal disease.
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Affiliation(s)
- Ranjit Mohan Anjana
- Madras Diabetes Research Foundation & Dr. Mohan’s Diabetes Specialities Centre, WHO Collaborating Centre for Non-communicable Diseases Prevention and Control &ICMR Center for Advanced Research on Diabetes, Chennai, India
- * E-mail:
| | - Ranjit Unnikrishnan
- Madras Diabetes Research Foundation & Dr. Mohan’s Diabetes Specialities Centre, WHO Collaborating Centre for Non-communicable Diseases Prevention and Control &ICMR Center for Advanced Research on Diabetes, Chennai, India
| | - Poongkunran Mugilan
- Madras Diabetes Research Foundation & Dr. Mohan’s Diabetes Specialities Centre, WHO Collaborating Centre for Non-communicable Diseases Prevention and Control &ICMR Center for Advanced Research on Diabetes, Chennai, India
| | - Padoor Sethuraman Jagdish
- Madras Diabetes Research Foundation & Dr. Mohan’s Diabetes Specialities Centre, WHO Collaborating Centre for Non-communicable Diseases Prevention and Control &ICMR Center for Advanced Research on Diabetes, Chennai, India
| | - Balasubramanian Parthasarathy
- Madras Diabetes Research Foundation & Dr. Mohan’s Diabetes Specialities Centre, WHO Collaborating Centre for Non-communicable Diseases Prevention and Control &ICMR Center for Advanced Research on Diabetes, Chennai, India
| | - Mohan Deepa
- Madras Diabetes Research Foundation & Dr. Mohan’s Diabetes Specialities Centre, WHO Collaborating Centre for Non-communicable Diseases Prevention and Control &ICMR Center for Advanced Research on Diabetes, Chennai, India
| | - Geetha Loganathan
- Madras Diabetes Research Foundation & Dr. Mohan’s Diabetes Specialities Centre, WHO Collaborating Centre for Non-communicable Diseases Prevention and Control &ICMR Center for Advanced Research on Diabetes, Chennai, India
| | - Rajendran Ashok Kumar
- Madras Diabetes Research Foundation & Dr. Mohan’s Diabetes Specialities Centre, WHO Collaborating Centre for Non-communicable Diseases Prevention and Control &ICMR Center for Advanced Research on Diabetes, Chennai, India
| | - Thangarajan Rahulashankiruthiyayan
- Madras Diabetes Research Foundation & Dr. Mohan’s Diabetes Specialities Centre, WHO Collaborating Centre for Non-communicable Diseases Prevention and Control &ICMR Center for Advanced Research on Diabetes, Chennai, India
| | - Ganesan Uma Sankari
- Madras Diabetes Research Foundation & Dr. Mohan’s Diabetes Specialities Centre, WHO Collaborating Centre for Non-communicable Diseases Prevention and Control &ICMR Center for Advanced Research on Diabetes, Chennai, India
| | - Ulagamathesan Venkatesan
- Madras Diabetes Research Foundation & Dr. Mohan’s Diabetes Specialities Centre, WHO Collaborating Centre for Non-communicable Diseases Prevention and Control &ICMR Center for Advanced Research on Diabetes, Chennai, India
| | - Viswanathan Mohan
- Madras Diabetes Research Foundation & Dr. Mohan’s Diabetes Specialities Centre, WHO Collaborating Centre for Non-communicable Diseases Prevention and Control &ICMR Center for Advanced Research on Diabetes, Chennai, India
| | - Coimbatore Subramanian Shanthi Rani
- Madras Diabetes Research Foundation & Dr. Mohan’s Diabetes Specialities Centre, WHO Collaborating Centre for Non-communicable Diseases Prevention and Control &ICMR Center for Advanced Research on Diabetes, Chennai, India
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Unnikrishnan R, Shanthi Rani CS, Anjana RM, Uthra SC, Vidya J, Sankari GU, Venkatesan U, Rani SJ, Mohan V. Postpartum development of type 1 diabetes in Asian Indian women with gestational diabetes. Indian J Endocrinol Metab 2016; 20:702-706. [PMID: 27730084 PMCID: PMC5040054 DOI: 10.4103/2230-8210.190562] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
AIM To study the postpartum conversion of gestational diabetes mellitus (GDM) to different types of diabetes among Asian Indian women. MATERIALS AND METHODS Using data from electronic medical records, 418 women with GDM seen at a tertiary diabetes care center for diabetes in Chennai in South India between 1991 and 2014 were evaluated for development of diabetes postpartum. RESULTS Of the 418 GDM women followed up postpartum, 388 progressed to diabetes. Of these 359 (92.5%) developed type 2 diabetes (T2DM) and 29 women (7.5%) developed type 1 diabetes (T1DM). The median time to development of T1DM was 2 years (interquartile range 2 [IQR]) while for T2DM it was 5 years (IQR 6). Women who developed T1DM had significantly lower mean body mass index (BMI) (20.4 ± 2.8 vs. 27.5 ± 4.4 kg/m2, P = 0.001), and higher fasting plasma glucose (222 ± 105 vs. 165 ± 62 mg/dl P = 0.008) and glycated hemoglobin levels (10.2 ± 2.7 vs. 8.5 ± 2.1% P < 0.001) compared to those who developed T2DM. Glutamic acid decarboxylase (GAD) autoantibodies were present in 24/29 (82.7%) of women who developed T1DM. CONCLUSION A small but significant proportion of women with GDM progress to T1DM postpartum. Measurement of GAD antibodies in leaner women with more severe diabetes could help to identify women who are likely to develop T1DM and thus prevent their presentation with acute hyperglycemic emergencies after delivery.
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Affiliation(s)
- Ranjit Unnikrishnan
- Madras Diabetes Research Foundation and Dr. Mohan's Diabetes Specialities Centre, Chennai, Tamil Nadu, India
| | | | - Ranjit Mohan Anjana
- Madras Diabetes Research Foundation and Dr. Mohan's Diabetes Specialities Centre, Chennai, Tamil Nadu, India
| | - Subash Chandrabose Uthra
- Madras Diabetes Research Foundation and Dr. Mohan's Diabetes Specialities Centre, Chennai, Tamil Nadu, India
| | - Jaydeep Vidya
- Madras Diabetes Research Foundation and Dr. Mohan's Diabetes Specialities Centre, Chennai, Tamil Nadu, India
| | - Ganesan Uma Sankari
- Madras Diabetes Research Foundation and Dr. Mohan's Diabetes Specialities Centre, Chennai, Tamil Nadu, India
| | - Ulagamathesan Venkatesan
- Madras Diabetes Research Foundation and Dr. Mohan's Diabetes Specialities Centre, Chennai, Tamil Nadu, India
| | - Saravanan Jeba Rani
- Madras Diabetes Research Foundation and Dr. Mohan's Diabetes Specialities Centre, Chennai, Tamil Nadu, India
| | - Viswanathan Mohan
- Madras Diabetes Research Foundation and Dr. Mohan's Diabetes Specialities Centre, Chennai, Tamil Nadu, India
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Anjana RM, Shanthi Rani CS, Deepa M, Pradeepa R, Sudha V, Divya Nair H, Lakshmipriya N, Subhashini S, Binu VS, Unnikrishnan R, Mohan V. Incidence of Diabetes and Prediabetes and Predictors of Progression Among Asian Indians: 10-Year Follow-up of the Chennai Urban Rural Epidemiology Study (CURES). Diabetes Care 2015; 38:1441-8. [PMID: 25906786 DOI: 10.2337/dc14-2814] [Citation(s) in RCA: 160] [Impact Index Per Article: 17.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/27/2014] [Accepted: 03/30/2015] [Indexed: 02/03/2023]
Abstract
OBJECTIVE There are few data on the incidence rates of diabetes and prediabetes (dysglycemia) in Asian Indians. This article presents the incidence of diabetes and prediabetes and the predictors of progression in a population-based Asian Indian cohort. RESEARCH DESIGN AND METHODS Data on progression to diabetes and prediabetes from 1,376 individuals, a subset of 2,207 of the Chennai Urban Rural Epidemiology Study (CURES) cohort (phase 3) with normal glucose tolerance (NGT) or prediabetes at baseline, who were followed for a median of 9.1 years (11,629 person-years), are presented. During follow-up, 534 died and 1,077 with NGT and 299 with prediabetes at baseline were reinvestigated in a 10-year follow-up study. Diabetes and prediabetes were diagnosed based on the American Diabetes Association criteria. Incidence rates were calculated and predictors of progression to prediabetes and/or diabetes were estimated using the Cox proportional hazards model. RESULTS The incidence rates of diabetes, prediabetes, and "any dysglycemia" were 22.2, 29.5, and 51.7 per 1,000 person-years, respectively. Among those with NGT, 19.4% converted to diabetes and 25.7% to prediabetes, giving an overall conversion rate to dysglycemia of 45.1%. Among those with prediabetes, 58.9% converted to diabetes. Predictors of progression to dysglycemia were advancing age, family history of diabetes, 2-h plasma glucose, glycated hemoglobin (HbA1c), low HDL cholesterol, and physical inactivity. CONCLUSIONS Asian Indians have one of the highest incidence rates of diabetes, with rapid conversion from normoglycemia to dysglycemia. Public health interventions should target modifiable risk factors to slow down the diabetes epidemic in this population.
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Affiliation(s)
- Ranjit Mohan Anjana
- Madras Diabetes Research Foundation and Dr. Mohan's Diabetes Specialities Centre, WHO Collaborating Centre for Noncommunicable Diseases Prevention and Control and International Diabetes Federation Centre of Education, Chennai, India
| | - Coimbatore Subramanian Shanthi Rani
- Madras Diabetes Research Foundation and Dr. Mohan's Diabetes Specialities Centre, WHO Collaborating Centre for Noncommunicable Diseases Prevention and Control and International Diabetes Federation Centre of Education, Chennai, India
| | - Mohan Deepa
- Madras Diabetes Research Foundation and Dr. Mohan's Diabetes Specialities Centre, WHO Collaborating Centre for Noncommunicable Diseases Prevention and Control and International Diabetes Federation Centre of Education, Chennai, India
| | - Rajendra Pradeepa
- Madras Diabetes Research Foundation and Dr. Mohan's Diabetes Specialities Centre, WHO Collaborating Centre for Noncommunicable Diseases Prevention and Control and International Diabetes Federation Centre of Education, Chennai, India
| | - Vasudevan Sudha
- Madras Diabetes Research Foundation and Dr. Mohan's Diabetes Specialities Centre, WHO Collaborating Centre for Noncommunicable Diseases Prevention and Control and International Diabetes Federation Centre of Education, Chennai, India
| | - Haridas Divya Nair
- Madras Diabetes Research Foundation and Dr. Mohan's Diabetes Specialities Centre, WHO Collaborating Centre for Noncommunicable Diseases Prevention and Control and International Diabetes Federation Centre of Education, Chennai, India
| | - Nagarajan Lakshmipriya
- Madras Diabetes Research Foundation and Dr. Mohan's Diabetes Specialities Centre, WHO Collaborating Centre for Noncommunicable Diseases Prevention and Control and International Diabetes Federation Centre of Education, Chennai, India
| | - Sivasankaran Subhashini
- Madras Diabetes Research Foundation and Dr. Mohan's Diabetes Specialities Centre, WHO Collaborating Centre for Noncommunicable Diseases Prevention and Control and International Diabetes Federation Centre of Education, Chennai, India
| | | | - Ranjit Unnikrishnan
- Madras Diabetes Research Foundation and Dr. Mohan's Diabetes Specialities Centre, WHO Collaborating Centre for Noncommunicable Diseases Prevention and Control and International Diabetes Federation Centre of Education, Chennai, India
| | - Viswanathan Mohan
- Madras Diabetes Research Foundation and Dr. Mohan's Diabetes Specialities Centre, WHO Collaborating Centre for Noncommunicable Diseases Prevention and Control and International Diabetes Federation Centre of Education, Chennai, India
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Mohan V, Shanthi Rani CS, Amutha A, Dhulipala S, Anjana RM, Parathasarathy B, Unnikrishnan R. Clinical profile of long-term survivors and nonsurvivors with type 2 diabetes. Diabetes Care 2013; 36:2190-7. [PMID: 23564913 PMCID: PMC3714469 DOI: 10.2337/dc12-1193] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Abstract
OBJECTIVE To compare clinical profile of long-term survivors and nonsurvivors with type 2 diabetes (T2DM). RESEARCH DESIGN AND METHODS After conducting a retrospective survey of >200,000 case records, we identified T2DM survivors (>40 years of duration) and age at diagnosis and sex-matched T2DM nonsurvivors. Prevalence of complications and causes of death were analyzed. Retinopathy was diagnosed by retinal photography. Microalbuminuria and macroalbuminuria, peripheral vascular disease based on ankle-brachial index <0.9, coronary artery disease based on history of myocardial infarction or coronary revascularization, and neuropathy based on vibration perception threshold >20 V were compared in both groups. RESULTS The mean duration of diabetes of survivors (n = 238) was 43.7 ± 3.9 years, and that of the nonsurvivors (n = 307), at time of death, was 22.4 ± 11.0 years (P < 0.001). Nonsurvivors had significantly higher systolic and diastolic blood pressures, plasma glucose, HbA1c, serum cholesterol, LDL cholesterol, and triglycerides and lower HDL cholesterol compared with long-term survivors (P < 0.001 for all parameters except systolic blood pressure, which was P = 0.027). Myocardial infarction (46.4%) and renal failure (16.6%) were the most common causes of death. Prevalence of most complications was higher among survivors because of longer duration and older age, as follows, for survivors versus nonsurvivors: retinopathy, 76 vs. 62%; microalbuminuria, 39.1 vs. 27.3%; macroalbuminuria, 8.4 vs. 23.7%; neuropathy, 86.5 vs. 63.5%; peripheral vascular disease, 23.1 vs. 11.4%; and coronary artery disease, 44.5 vs. 40.7%. CONCLUSIONS Long-term survivors with T2DM had better glycemic and blood pressure control and more favorable lipid profiles.
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