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The ongoing epidemic of diabetes mellitus in India: genetics or lifestyle?

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Abstract

India is estimated to have the second highest number of cases of diabetes mellitus in the world after China. Recent epidemiological evidence indicates that people of lower socioeconomic group in India are equally or even more susceptible to diabetes. Family history is a very strong risk factor for developing type 2 diabetes mellitus; the lifetime risk is nearly 40% for individuals who have one parent affected and approaches 70% if both parents are affected. Genome-wide association studies identified more than 50 genetic variants associated with type 2 diabetes mellitus, but these risk alleles identified to date could only explain less than 10% of the observed heritability. Acquisition of the same unhealthy lifestyle from the parents could be the major reason for the observed heritability that genetics could not explain. The global age-standardised prevalence of diabetes has nearly doubled since 1980, rising from 4.7 to 8.5% in the adult population. If genes are responsible for this doubling of prevalence, the responsible gene pool should also amplify to the same extent in the population. The Hardy–Weinberg law states that allele and genotype frequencies in a population will remain constant from generation to generation in the absence of other evolutionary influences, making genetics as the etiology for this ongoing epidemic less likely. Indians have a tendency to become metabolically obese and develop type 2 diabetes mellitus with normal weight; thus, body mass index cut-off for overweight and obesity is kept lower in Indians. Primary and secondary prevention strategies should be more emphasised at the community level. Physical activity recommended is at least 150 min/week. All adults should decrease the amount of time spent in daily sedentary behaviour. Dietary modifications by reducing carbohydrate intake and increasing the intake of proteins, green leafy vegetables, fruits, and nuts should be promoted.

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References

  1. International Diabetes Federation. IDF Diabetes Atlas 7th Edition, International Diabetes Federation; 2015. [E-book] Available: www.diabetesatlas.org. [Internet].

  2. Misra P, Upadhyay RP, Misra A, Anand K. A review of the epidemiology of diabetes in rural India. Diabetes Res Clin Pract. 2011;92(3):303–11.

    Article  CAS  PubMed  Google Scholar 

  3. Pierce M, Keen H, Bradley C. Risk of diabetes in offspring of parents with non-insulin-dependent diabetes. Diabetic Med. 1995;12:6–13.

    Article  CAS  PubMed  Google Scholar 

  4. Kobberling J, Tillil H. Empirical risk figures for first-degree relatives of non-insulin-dependent diabetics. In: Kobberling J, editor. Genetics of diabetes mellitus. London: Academic; 1982. p. 201–9.

    Google Scholar 

  5. Groop L, Forsblom C, Lehtovirta M, Tuomi T, Karanko S, Nissen M, et al. Metabolic consequences of a family history of NIDDM (the Botnia study): evidence for sex-specific parental effects. Diabetes. 1996;45(11):1585–93.

    Article  CAS  PubMed  Google Scholar 

  6. Kaprio J, Tuomilehto J, Koskenvuo M, Romanov K, Reunanen A, Eriksson J, et al. Concordance for type 1 (insulin-dependent) and type 2 (non-insulin-dependent) diabetes mellitus in a population-based cohort of twins in Finland. Diabetologia. 1992;35(11):1060–7.

    Article  CAS  PubMed  Google Scholar 

  7. Lyssenko V, Jonsson A, Almgren P, Pulizzi N, Isomaa B, Tuomi T, et al. Clinical risk factors, DNA variants, and the development of type 2 diabetes. N Engl J Med. 2008;359:2220–32.

    Article  CAS  PubMed  Google Scholar 

  8. Lyssenko V, Almgren P, Anevski D, Perfekt R, Lahti K, Nissén M, et al. Botnia study group. Predictors of and longitudinal changes in insulin sensitivity and secretion preceding onset of type 2 diabetes. Diabetes. 2005;54:166–74.

    Article  CAS  PubMed  Google Scholar 

  9. International Human Genome Sequencing Consortium. Initial sequencing and analysis of the human genome. Nature. 2001;409:860–921.

    Article  Google Scholar 

  10. Venter JC, Adams MD, Myers EW, Li PW, Mural RJ, Sutton GG, et al. The sequence of the human genome. Science. 2001;291:1304–51.

    Article  CAS  PubMed  Google Scholar 

  11. The International HapMap Consortium. The International HapMap Project. Nature. 2003;426:789–96.

    Article  CAS  Google Scholar 

  12. International HapMap Consortium. A second generation human haplotype map of over 3.1 million SNPs. Nature. 2007;449:851–61.

    Article  CAS  Google Scholar 

  13. Billings LK, Florez JC. The genetics of type 2 diabetes: what have we learned from GWAS? Ann N Y Acad Sci. 2010;1212:59–77.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Worldwide trends in diabetes since 1980: a pooled analysis of 751 population-based studies with 4·4 million participants. The Lancet 2016;387:1513–30.

  15. Sohani ZN, Deng WQ, Pare G, Meyre D, Gerstein HC, Anand SS. Genetic studies of type 2 diabetes in South Asians: a systematic overview. Curr Diabetes Rev. 2014;10(4):258–74.

    Article  CAS  Google Scholar 

  16. Maher B. Personal genomes: the case of the missing heritability. Nature. 2008;456:18–21.

    Article  CAS  PubMed  Google Scholar 

  17. Chambers JC, Loh M, Lehne B, Drong A, Kriebel J, Motta V, et al. Epigenome-wide association of DNA methylation markers in peripheral blood from Indian Asians and Europeans with incident type 2 diabetes: a nested case-control study. Lancet Diabetes Endocrinol. 2015;3(7):526–34.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Razak F, Anand SS, Shannon H, Vuksan V, Davis B, Jacobs R, et al. Defining obesity cut points in a multiethnic population. Circulation. 2007;115:2111–8.

    Article  PubMed  Google Scholar 

  19. McKeigue PM, Shah B, Marmot MG. Relation of central obesity and insulin resistance with high diabetes prevalence and cardiovascular risk in South Asians. Lancet. 1991;337:382–6.

    Article  CAS  PubMed  Google Scholar 

  20. Raji A, Seely EW, Arky RA, Simonson DC. Body fat distribution and insulin resistance in healthy Asian Indians and Caucasians. J Clin Endocrinol Metab. 2001;86:5366–71.

    Article  CAS  PubMed  Google Scholar 

  21. Das S, Samal SC, Baliarsinha AK, Tripathy BB. Lean (underweight) NIDDM—peculiarities and differences in metabolic and hormonal status—a pilot study. J Assoc Physicians India. 1995;43:339–42.

    CAS  PubMed  Google Scholar 

  22. Sinharoy K, Mandal L, Chakrabarti S, Paul UK, Bandyopadhyay R, Basu AKA. Study on clinical and biochemical profile of low body weight type 2 diabetes mellitus. J Indian Med Assoc. 2008;106:747–50.

    PubMed  Google Scholar 

  23. Davey G, Ramachandran A, Snehalatha C, Hitman GA, McKeigue PM. Familial aggregation of central obesity in Southern Indians. Int J Obes Relat Metab Disord. 2000;24:1523–7.

    Article  CAS  PubMed  Google Scholar 

  24. Zabaneh D, Chambers JC, Elliott P, Scott J, Balding DJ, Kooner JS. Heritability and genetic correlations of insulin resistance and component phenotypes in Asian Indian families using a multivariate analysis. Diabetologia. 2009;52:2585–9.

    Article  CAS  PubMed  Google Scholar 

  25. Scott WR, Zhang W, Loh M, Tan ST, Lehne B, Afzal U, et al. Investigation of genetic variation underlying central obesity amongst South Asians. PLoS One. 2016;11(5):e0155478.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Sniderman AD, Bhopal R, Prabhakaran D, Sarrafzadegan N, Tchernof A. Why might South Asians be so susceptible to central obesity and its atherogenic consequences? The adipose tissue overflow hypothesis. Int J Epidemiol. 2007;36(1):220–5.

    Article  PubMed  Google Scholar 

  27. Gealekman O, Guseva N, Hartigan C, Apotheker S, Gorgoglione M, Gurav K, et al. Depot-specific differences and insufficient subcutaneous adipose tissue angiogenesis in human obesity. Circulation. 2011;123(2):186–94.

    Article  PubMed  PubMed Central  Google Scholar 

  28. WHO Expert Consultation. Appropriate body-mass index for Asian populations and its implications for policy and intervention strategies. Lancet. 2004;363:157–63.

    Article  Google Scholar 

  29. Misra A, Chowbey P, Makkar BM, Vikram NK, Wasir JS, Chadha D, et al. Consensus statement for diagnosis of obesity, abdominal obesity and the metabolic syndrome for Asian Indians and recommendations for physical activity, medical and surgical management. J Assoc Physicians India. 2009;57:163–70.

    CAS  PubMed  Google Scholar 

  30. Waist circumference and waist–hip ratio [Internet]. WHO. World Health Organization; [cited 2017Aug29]. Available from: http://www.who.int/nutrition/publications/obesity/WHO_report_waistcircumference_and_waisthip_ratio/en/

  31. Premanath M, Basavanagowdappa H, Mahesh M, Suresh M. Correlation of abdominal adiposity with components of metabolic syndrome, anthropometric parameters and insulin resistance, in obese and non obese, diabetics and non diabetics: a cross sectional observational study. (Mysore visceral adiposity in diabetes study). Indian J Endocrinol Metab. 2014;18(5):676–82.

    CAS  PubMed  PubMed Central  Google Scholar 

  32. Mørkedal B, Romundstad PR, Vatten LJ. Informativeness of indices of blood pressure, obesity and serum lipids in relation to ischaemic heart disease mortality: the HUNT-II study. Eur J Epidemiol. 2011;26(6):457–61.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Mohan V, Vijayaprabha R, Rema M, Premalatha G, Poongothai S, Deepa R, et al. Clinical profile of lean NIDDM in South India. Diabetes Res Clin Pract. 1997;38(2):101–8.

    Article  CAS  PubMed  Google Scholar 

  34. Coleman NJ, Miernik J, Philipson L, Fogelfeld L. Lean versus obese diabetes mellitus patients in the United States minority population. J Diabetes Complicat. 2014;28:500–5.

    Article  PubMed  Google Scholar 

  35. González-Chávez A, Simental-Mendía LE, Elizondo-Argueta S. Elevated triglycerides/HDL-cholesterol ratio associated with insulin resistance. Cir Cir. 2011;79:126–31.

    PubMed  Google Scholar 

  36. Boizel R, Benhamou PY, Lardy B, Laporte F, Foulon T, Halimi S. Ratio of triglycerides to HDL cholesterol is an indicator of LDL particle size in patients with type 2 diabetes and normal HDL cholesterol levels. Diabetes Care. 2000;23:1679–85.

    Article  CAS  PubMed  Google Scholar 

  37. Giannini C, Santoro N, Caprio S, Kim G, Lartaud D, Shaw M, et al. The triglyceride-to-HDL cholesterol ratio: association with insulin resistance in obese youths of different ethnic backgrounds. Diabetes Care. 2011;34:1869–74.

    Article  PubMed  PubMed Central  Google Scholar 

  38. Evangelou E, Ntritsos G, Chondrogiorgi M, Kavvoura FK, Hernández AF, Ntzani EE, et al. Exposure to pesticides and diabetes: a systematic review and meta-analysis. Environ Int. 2016;91:60–8.

    Article  CAS  PubMed  Google Scholar 

  39. Velmurugan G, Ramprasath T, Swaminathan K, Mithieux G, Rajendhran J, Dhivakar, et al. Gut microbial degradation of organophosphate insecticides-induces glucose intolerance viagluconeogenesis. Genome Biol. 2017;18:1134–6.

    Article  CAS  Google Scholar 

  40. Shah B, Mathur P. Surveillance of cardiovascular disease risk factors in India: the need & scope. Indian J Med Res. 2010;132:634–42.

    PubMed  PubMed Central  Google Scholar 

  41. Thankappan KR, Shah B, Mathur P, Sarma PS, Srinivas G, Mini GK, et al. Risk factor profile for chronic non-communicable diseases: results of a community-based study in Kerala, India. Indian J Med Res. 2010;131:53–63.

    CAS  PubMed  Google Scholar 

  42. Revival of Public Distribution System in Kerala [Internet]. Economic and Political Weekly; 2017 [cited 2017Aug23]. Available from: http://www.epw.in/journal/2017/25-26/notes/revival-public-distribution-system-kerala.html

  43. Food & Civil Supplies Page [Internet]. Food & Civil Supplies - Government of Kerala, India. [cited 2017Aug23]. Available from: https://kerala.gov.in/food-civil-supplies

  44. Unnikrishnan R, Anjana RM, Mohan V. Diabetes mellitus and its complications in India. Nat Rev Endocrinol. 2016;12:357–70.

    Article  PubMed  Google Scholar 

  45. Rayappa PH, Raju KN, Kapur A, Bjork S, Sylvest C, Kumar KM. The impact of socio-economic factors on diabetes care. Int J Diab Dev Coun. 1999;19:8–16.

    Google Scholar 

  46. Shobhana R, Begum R, Snehalatha C, Vijay V, Ramachandran A. Patients’ adherence to diabetes treatment. J Assoc Phys India. 1999;47:1173–5.

    CAS  Google Scholar 

  47. King P, Peacock I, Donnelly R. The UK Prospective Diabetes Study (UKPDS): clinical and therapeutic implications for type 2 diabetes. Br J Clin Pharmacol. 1999;48(5):643–8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Nathan DM, DCCT/EDIC Research Group. The diabetes control and complications trial/epidemiology of diabetes interventions and complications study at 30 years: overview. Diabetes Care. 2014;37(1):9–16.

    Article  CAS  PubMed  Google Scholar 

  49. Nagpal J, Bhartia A. Quality of diabetes care in the middle- and high-income group populace—the Delhi Diabetes Community (DEDICOM) survey. Diabetes Care. 2006;29:2341–8.

    Article  PubMed  Google Scholar 

  50. Funnell MM, Bootle S, Stuckey HL. The diabetes attitudes, wishes and needs second study. Clin Diabetes : A Publ Am Diabetes Assoc. 2015;33(1):32–6.

    Article  Google Scholar 

  51. Pai S, Ghugre PS, Udipi SA. Satiety from rice-based, wheat-based and rice-pulse combination preparations. Appetite. 2005;44(3):263–71.

    Article  PubMed  Google Scholar 

  52. Shobana S, Kumari SR, Malleshi NG, Ali SZ. Glycemic response of rice, wheat and finger millet based diabetic food formulations in normoglycemic subjects. Int J Food Sci Nutr. 2007;58(5):363–72.

    Article  CAS  PubMed  Google Scholar 

  53. Colberg SR. Key points from the updated guidelines on exercise and diabetes. Front Endocrinol (Lausanne). 2017;8:33.

    Article  Google Scholar 

  54. Mohan D, Raj D, Shanthirani CS, Datta M, Unwin NC, Kapur A, et al. Awareness and knowledge of diabetes in Chennai—the Chennai Urban Rural Epidemiology Study [CURES-9]. J Assoc Physicians India. 2005;53:283–7.

    PubMed  Google Scholar 

  55. Deepa M, Bhansali A, Anjana RM, Pradeepa R, Joshi SR, Joshi PP, et al. Knowledge and awareness of diabetes in urban and rural India: the Indian Council of Medical Research India Diabetes Study (phase I): Indian Council of Medical Research India Diabetes 4. Indian J Endocrinol Metab. 2014;18(3):379–85.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Florez JC. Leveraging genetics to advance type 2 diabetes prevention. PLoS Med. 2016;13(7):e1002102.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. Jablonski KA, McAteer JB, de Bakker PI, Franks PW, Pollin TI, Hanson RL, et al. Common variants in 40 genes assessed for diabetes incidence and response to metformin and lifestyle intervention in the Diabetes Prevention Program. Diabetes. 2010;59(10):2672–81.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. Evaluation of Genomic Applications in Practice and Prevention (EGAPP) Working Group; Evaluation of Genomic Applications in Practice and Prevention (EGAPP) Working Group. Recommendations from the EGAPP Working Group: does genomic profiling to assess type 2 diabetes risk improve health outcomes? Genet Med. 2013;15(8):612–7.

    Article  CAS  Google Scholar 

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Authors and Affiliations

  1. Thiruvananthapuram, Kerala, India

    E. T. Arun Thomas & Bhagya Shaji

  2. Indian Institute of Diabetes, Thiruvananthapuram, Kerala, India

    Noble Gracious

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  1. E. T. Arun Thomas
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Arun Thomas, E.T., Shaji, B. & Gracious, N. The ongoing epidemic of diabetes mellitus in India: genetics or lifestyle?. Int J Diabetes Dev Ctries 39, 8–14 (2019). https://doi.org/10.1007/s13410-018-0630-5

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