Chapter 2: The problem with South Asians (a seed in the soil hypothesis)
Lessons for South Asians at Risk for Diabetes and Heart Disease
Have you ever observed at a family gathering, how some people carry their excess fat tightly around their abdominal region whereas others are generally fat all over their legs, arms, face, and hips? These two types of excess fat carriage are referred to as “Apple-Shaped” versus “Pear Shaped” fat distribution.
Figure 1a: Examples of Fat distribution types
Well, in short South Asians are far more prone to carry excess fat tissue in an Apple-shaped distribution. Look around you – you may observe this beach ball with skinny arms and legs shape around you, or you may notice subtle trends towards this, when YOU gain weight, where the first place you notice this extra weight is with an out pouching of your tummy, and tight-fitting pants at the waist.
I have always been struck by this observation - especially when visiting India, observing low body weight men (in particular) who also have a small pot belly. These individuals are not overweight by conventional western definitions (e.g. using body mass index), and therefore typically told “they are just fine”. So, is this apple shaped fat distribution of a normal weight man or women cause for concern? And if so, why is it that excess fat at all be stored around the abdomen? And why do South Asians have this more commonly than other groups?
South Asian studies have shown that a persistent multigenerational unique predilection to central adiposity and high adipose tissue to non-adipose tissue mass at birth that persists into adulthood when compared to white Europeans (Yajnik et al., 2002, 2003). We have shown this pattern exists in adults and in newborns (Anand et al., 2000; Anand, Vasudevan, et al., 2013). Another component of the South Asian phenotype is small birthweight babies with relatively more adipose tissue compared to white European babies (Anand et al., 2016). These observations provide support for a unique genetic and gene expression signature that likely exists in South Asians– reflecting ancestry and prior pregnancy and early life exposures (Anand, Vasudevan, et al., 2013).
Figure 1b: South Asian Body Type
As a researcher in this field, there are many hypotheses that have been put forth to explain this phenomenon in South Asians. Here are a few of them and the associated observations.
The Thrifty Gene hypothesis put forth by James Neel in 1962 suggested that populations exposed to feast times followed by famine times, had a genetic adaptation to enable survival famine by storing fat centrally so that it could be called upon to be utilized as fatty acids and generate glucose when glycogen supplies were depleted (Neel, 1962). However modern-day genetic studies have not confirmed this to be true (Ayub et al., 2014; Gosling et al., 2015; Steinthorsdottir et al., 2014).
Genetic Predisposition: The early case series published by Malhotra from India in the 1950 also concluded that without a doubt there was a genetic reason for the early onset coronary heart disease hereafter referred to as heart disease, the first clues provided by the strong family histories reported (Malhotra & Pathania, 1958). Genetic variants can be present in each one of the known risk factors for heart disease such as high cholesterol, diabetes, high blood pressure and abdominal obesity. South Asian studies have shown that a persistent multigenerational unique predilection to central adiposity and high adipose tissue to non-adipose tissue mass at birth that persists into adulthood when compared to white Europeans (Yajnik et al., 2002, 2003). This also raises support for a unique genetic and gene expression signature that likely exists in South Asians– reflecting ancestry and prior exposures (Anand, Vasudevan, et al., 2013). To date more than 40 genetic variants have been significantly linked to development of central fat providing solid backing to a genetic component of this common characteristic, which is not exclusive to but more common in South Asians (Herrera et al., 2011).
South Asians Genetic Propensity to risk factors for cardiovascular disease
Previous investigations have shown that South Asians have a greater frequency of genetic variants associated with gestational diabetes and type 2 diabetes (Anand, Meyre, et al., 2013; Lamri et al., 2022). When counting genetic variants for diabetes between South Asian, white Europeans and Latinos, South Asians have the higher score, and because each variants in the gene score is a predictor of future development of type 2 diabetes, South Asians are therefore at higher risk of developing type 2 diabetes due to genetic factors compared to the other two ethnic groups (Anand, Meyre, et al., 2013; Mahajan et al., 2022). Specific gene variants related to insulin resistance and beta-cell function have been identified and there are complex interactions between genetic and environmental factors, such as dietary habits and physical activity levels. Many of the genetic variants associated with type 2 diabetes are also related to traits of body fat and muscle mass and cardiovascular disease (Mahajan et al., 2022).
The Caste System leads to non-random mating: Another ancestral predilection that could explain a genetic predisposition to diabetes – which we learn from ancient DNA studies. Priya Moorjani and David Reich reconstructed the Indian subcontinent populations using ancient DNA as well as information from historical social structures such as the Caste system to help us understand the history of admixture in the Indian subcontinent (Moorjani et al., 2013). They identified that there are some distinct DNA markers separating North Indians from South Indians and from those who originate from the Andaman Islands (Moorjani et al., 2013). Using ancient DNA, they reconstructed the history of migration and admixing on the Indian subcontinent, and elegantly showed how the Caste system – a social construct which prevented random mating – led to an increase in recessive alleles or so-called bottle neck populations within South Asian subpopulations (Moorjani et al., 2013). This increase in recessive alleles is associated with some health conditions like type 2 diabetes, and added to this is the cultural expectation of interfamily marriage which can increase this even (Moorjani et al., 2013). Furthermore, in some countries far from the Indian subcontinent where South Asian migrated, they may face a double jeopardy through intermarriage within castes, as well as a closed mating population due to the remoteness of communities (e.g. Trinidad and Guyana). The increased frequency of atherosclerosis and diabetes causing genetic variants may help explain the higher burden of heart disease in parts of the South Asian diaspora.
Figure 2: A map showing the sampling locations for Indian groups used in the study conducted by Moorjani et al. (2013).
The Thrifty Phenotype hypothesis argues that the effects of poor nutrition in early life, produces permanent changes in glucose-insulin metabolism, and places the individual at increased risk of future type 2 diabetes (Hales & Barker, 2001; A. C. J. Ravelli et al., 1998). Evidence for this hypothesis comes from populations who have faced starvation in the last century, as offspring often show evidence of the long-term effect of the stressor of famine, on their ability to store fat and their predisposition to pre-diabetes and diabetes. For example, in the Dutch Hunger Winter of World War 2, in which the Nazis closed off the food supply to the Dutch, Dutch women who were pregnant and starving had offspring who were not only smaller than expected at birth, but who were considered to have abdominal obesity and pre-diabetes were observed by the first 2 decades of their lives (Lumey et al., 2011; A. C. J. Ravelli et al., 1998; Roseboom et al., 2011) Why would this occur? The developing fetus could be thought of as a scavenger trying to compete for any calories and nutrients, such as amino acids, from the mother. They used any energy and nutrients as judiciously as possible – and these mechanisms of storing energy were hard wired into them after birth. This would stand them well if they faced nutrient shortages again, but in the scenario of energy excess (which is common in high income countries and urban areas of low-income countries), this excess energy and nutrients would result in excess abdominal adipose tissue, diabetes, and early heart disease (G. P. Ravelli et al., 1976). This supports the idea that the fetal environment can have long-lasting effects on health and highlights the importance of maternal nutrition and health during pregnancy. The insulin like growth factor 1 (IGF-1) genetic polymorphism has been implicated as being subject to epigenetic modification (Kyle & Pichard, 2006).
Epigenetics refers to marks such as methylation CPG or histone modification of genes that affect how genes are expressed, meaning how they create proteins. Environmental influences during pregnancy can mark fetal DNA and influence the “expression” of DNA as the newborns develop. These can include influences from exposure to cigarette smoking to vitamin deficiencies as part of dietary intake during pregnancy. An interesting analysis of South Asian women born in the United Kingdom, in which the birth weight of these second-generation South Asians offspring was compared to white European original citizens of UK, showed that South Asian offspring remain lower birthweight by approximately 200 grams (Leon & Moser, 2012).
The persistent lower birthweight of South Asian babies comparing India to the UK could be explained by a different seed (genetics) in a different soil (environment), but within the UK the comparison is a different seed in similar soil for the 1st generation, and in the same soil for 2nd generation offspring. To keep this analogy going, a persistent difference in how tall the plant grows in two generations is similar in identical soil and does point to a seed difference - either genetic or persistent epigenetic difference.
Thus, there are multiple theories as to why South Asians develop type 2 diabetes at higher rates than other ethnic populations – from an excess of recessive alleles as a reflection of distant migration and admixture patterns, and/or epigenetic marks reflecting past in utero exposures that influence gene expression, all of which can have different manifestations in the presence of particular health behaviors such as dietary intake and physical activity- and there are also likely other factors at play.
What about biomarkers of risk - adipokines adiponectin and leptin?
Table 1: Biomarker roles and cardiovascular implications
Our studies indicate that South Asians have the least favourable adipokine profile and, display a greater increase in insulin resistance with decreasing levels of adiponectin. Further we have shown that South Asians in whom the metabolic syndrome is highly prevalent have higher levels of inflammatory proteins called C- Reactive protein (Mente et al., 2010).
How can I change my genetic risk?
Healthy active living is recommended to “turn off” certain genetic factors and has been shown robustly in other populations for example. We showed in a previous analysis that individuals who were born with a genetic risk of myocardial infarction or heart attack could negate this risk by consuming a diet high in fruit and vegetables (Do et al., 2011). You cannot change your genetic code, but you have some influence over minimizing the genetic risk from being transmitted to your offspring- for example, not marrying blood relatives, nor promoting only marrying strictly within a caste, are some considerations.
Anything else? This field of research is accelerating, especially as the technological advances including the ability to sequence the entire human genome with robotic technology in a short time at relatively lower cost, means we will learn a lot regarding genetic and epigenetic differences in the coming decade. In the meantime, the typical South Asian risk pattern can be summarized as such:
Knowing all this, and knowing that researchers are racing to understand why, and not being able to wait for two more decades, what can you do now to prevent you from becoming another South Asian statistic? As it is often stated, “Genetics loads the gun, and your environment pulls the trigger”. That means you have the chance to prevent heart disease and diabetes by being aware and beginning your journey to health.
REFERENCES
Anand, S. S., Gupta, M. K., Schulze, K. M., Desai, D., Abdalla, N., Wahi, G., Wade, C., Scheufler, P., McDonald, S. D., Morrison, K. M., Vasudevan, A., Dwarakanath, P., Srinivasan, K., Kurpad, A., Gerstein, H. C., & Teo, K. K. (2016). What accounts for ethnic differences in newborn skinfold thickness comparing South Asians and White Caucasians? Findings from the START and FAMILY Birth Cohorts. International Journal of Obesity, 40(2), Article 2. https://doi.org/10.1038/ijo.2015.171
Anand, S. S., Meyre, D., Pare, G., Bailey, S. D., Xie, C., Zhang, X., Montpetit, A., Desai, D., Bosch, J., Mohan, V., Diaz, R., McQueen, M. J., Cordell, H. J., Keavney, B., Yusuf, S., Gaudet, D., Gerstein, H., Engert, J. C., & on behalf of the EpiDREAM Genetics Investigators. (2013). Genetic Information and the Prediction of Incident Type 2 Diabetes in a High-Risk Multiethnic Population: The EpiDREAM genetic study. Diabetes Care, 36(9), 2836–2842. https://doi.org/10.2337/dc12-2553
Anand, S. S., Vasudevan, A., Gupta, M., Morrison, K., Kurpad, A., Teo, K. K., Srinivasan, K., & The START Cohort Study Investigators. (2013). Rationale and design of South Asian Birth Cohort (START): A Canada-India collaborative study. BMC Public Health, 13(1), 79. https://doi.org/10.1186/1471-2458-13-79
Anand, S. S., Yusuf, S., Vuksan, V., Devanesen, S., Teo, K. K., Montague, P. A., Kelemen, L., Yi, C., Lonn, E., Gerstein, H., Hegele, R. A., & McQueen, M. (2000). Differences in risk factors, atherosclerosis, and cardiovascular disease between ethnic groups in Canada: The Study of Health Assessment and Risk in Ethnic groups (SHARE). Lancet (London, England), 356(9226), 279–284. https://doi.org/10.1016/s0140-6736(00)02502-2
Ayub, Q., Moutsianas, L., Chen, Y., Panoutsopoulou, K., Colonna, V., Pagani, L., Prokopenko, I., Ritchie, G. R. S., Tyler-Smith, C., McCarthy, M. I., Zeggini, E., & Xue, Y. (2014). Revisiting the thrifty gene hypothesis via 65 loci associated with susceptibility to type 2 diabetes. American Journal of Human Genetics, 94(2), 176–185. https://doi.org/10.1016/j.ajhg.2013.12.010
Do, R., Xie, C., Zhang, X., Männistö, S., Harald, K., Islam, S., Bailey, S. D., Rangarajan, S., McQueen, M. J., Diaz, R., Lisheng, L., Wang, X., Silander, K., Peltonen, L., Yusuf, S., Salomaa, V., Engert, J. C., Anand, S. S., & Investigators, on behalf of the I. (2011). The Effect of Chromosome 9p21 Variants on Cardiovascular Disease May Be Modified by Dietary Intake: Evidence from a Case/Control and a Prospective Study. PLOS Medicine, 8(10), e1001106. https://doi.org/10.1371/journal.pmed.1001106
Gosling, A. L., Buckley, H. R., Matisoo-Smith, E., & Merriman, T. R. (2015). Pacific Populations, Metabolic Disease and ‘Just-So Stories’: A Critique of the ‘Thrifty Genotype’ Hypothesis in Oceania. Annals of Human Genetics, 79(6), 470–480. https://doi.org/10.1111/ahg.12132
Graff, M., Scott, R. A., Justice, A. E., Young, K. L., Feitosa, M. F., Barata, L., Winkler, T. W., Chu, A. Y., Mahajan, A., Hadley, D., Xue, L., Workalemahu, T., Heard-Costa, N. L., Hoed, M. den, Ahluwalia, T. S., Qi, Q., Ngwa, J. S., Renström, F., Quaye, L., … Kilpeläinen, T. O. (2017). Genome-wide physical activity interactions in adiposity ― A meta-analysis of 200,452 adults. PLOS Genetics, 13(4), e1006528. https://doi.org/10.1371/journal.pgen.1006528
Hales, C. N., & Barker, D. J. P. (2001). The thrifty phenotype hypothesis: Type 2 diabetes. British Medical Bulletin, 60(1), 5–20. https://doi.org/10.1093/bmb/60.1.5
Herrera, B. M., Keildson, S., & Lindgren, C. M. (2011). Genetics and epigenetics of obesity. Maturitas, 69(1), 41–49. https://doi.org/10.1016/j.maturitas.2011.02.018
Kyle, U. G., & Pichard, C. (2006). The Dutch Famine of 1944-1945: A pathophysiological model of long-term consequences of wasting disease. Current Opinion in Clinical Nutrition and Metabolic Care, 9(4), 388–394. https://doi.org/10.1097/01.mco.0000232898.74415.42
Lamri, A., Limbachia, J., Schulze, K. M., Desai, D., Kelly, B., de Souza, R. J., Paré, G., Lawlor, D. A., Wright, J., & Anand, S. S. (2022). The genetic risk of gestational diabetes in South Asian women. eLife, 11, e81498. https://doi.org/10.7554/eLife.81498
Leon, D. A., & Moser, K. A. (2012). Low birth weight persists in South Asian babies born in England and Wales regardless of maternal country of birth. Slow pace of acculturation, physiological constraint or both? Analysis of routine data. J Epidemiol Community Health, 66(6), 544–551. https://doi.org/10.1136/jech.2010.112516
Lumey, L. H., Stein, A. D., & Susser, E. (2011). Prenatal Famine and Adult Health. Annual Review of Public Health, 32, 10.1146/annurev-publhealth-031210–101230. https://doi.org/10.1146/annurev-publhealth-031210-101230
Mahajan, A., Spracklen, C. N., Zhang, W., Ng, M. C. Y., Petty, L. E., Kitajima, H., Yu, G. Z., Rüeger, S., Speidel, L., Kim, Y. J., Horikoshi, M., Mercader, J. M., Taliun, D., Moon, S., Kwak, S.-H., Robertson, N. R., Rayner, N. W., Loh, M., Kim, B.-J., … Morris, A. P. (2022). Multi-ancestry genetic study of type 2 diabetes highlights the power of diverse populations for discovery and translation. Nature Genetics, 54(5), Article 5. https://doi.org/10.1038/s41588-022-01058-3
Malhotra, R. P., & Pathania, N. S. (1958). Some aetiological aspects of coronary heart disease; an Indian point of view based on a study of 867 cases seen during 1948-55. British Medical Journal, 2(5095), 528–531. https://doi.org/10.1136/bmj.2.5095.528
Mente, A., Razak, F., Blankenberg, S., Vuksan, V., Davis, A. D., Miller, R., Teo, K., Gerstein, H., Sharma, A. M., Yusuf, S., Anand, S. S., & for the Study of Health Assessment and Risk Evaluation (SHARE) and SHARE in Aboriginal Peoples (SHARE-AP) Investigators. (2010). Ethnic Variation in Adiponectin and Leptin Levels and Their Association With Adiposity and Insulin Resistance. Diabetes Care, 33(7), 1629–1634. https://doi.org/10.2337/dc09-1392
Moorjani, P., Thangaraj, K., Patterson, N., Lipson, M., Loh, P.-R., Govindaraj, P., Berger, B., Reich, D., & Singh, L. (2013). Genetic Evidence for Recent Population Mixture in India. The American Journal of Human Genetics, 93(3), 422–438. https://doi.org/10.1016/j.ajhg.2013.07.006
Neel, J. V. (1962). Diabetes Mellitus: A “Thrifty” Genotype Rendered Detrimental by “Progress”? American Journal of Human Genetics, 14(4), 353–362.
Ravelli, A. C. J., Meulen, J. van der, Michels, R. P. J., Osmond, C., Barker, D. J. P., Hales, C. N., & Bleker, O. P. (1998). Glucose tolerance in adults after prenatal exposure to famine. The Lancet, 351(9097), 173–177. https://doi.org/10.1016/S0140-6736(97)07244-9
Ravelli, G. P., Stein, Z. A., & Susser, M. W. (1976). Obesity in young men after famine exposure in utero and early infancy. The New England Journal of Medicine, 295(7), 349–353. https://doi.org/10.1056/NEJM197608122950701
Roseboom, T. J., Painter, R. C., van Abeelen, A. F. M., Veenendaal, M. V. E., & de Rooij, S. R. (2011). Hungry in the womb: What are the consequences? Lessons from the Dutch famine. Maturitas, 70(2), 141–145. https://doi.org/10.1016/j.maturitas.2011.06.017
Shungin, D., Winkler, T. W., Croteau-Chonka, D. C., Ferreira, T., Locke, A. E., Mägi, R., Strawbridge, R. J., Pers, T. H., Fischer, K., Justice, A. E., Workalemahu, T., Wu, J. M. W., Buchkovich, M. L., Heard-Costa, N. L., Roman, T. S., Drong, A. W., Song, C., Gustafsson, S., Day, F. R., … Mohlke, K. L. (2015). New genetic loci link adipose and insulin biology to body fat distribution. Nature, 518(7538), Article 7538. https://doi.org/10.1038/nature14132
Steinthorsdottir, V., Thorleifsson, G., Sulem, P., Helgason, H., Grarup, N., Sigurdsson, A., Helgadottir, H. T., Johannsdottir, H., Magnusson, O. T., Gudjonsson, S. A., Justesen, J. M., Harder, M. N., Jørgensen, M. E., Christensen, C., Brandslund, I., Sandbæk, A., Lauritzen, T., Vestergaard, H., Linneberg, A., … Stefansson, K. (2014). Identification of low-frequency and rare sequence variants associated with elevated or reduced risk of type 2 diabetes. Nature Genetics, 46(3), 294–298. https://doi.org/10.1038/ng.2882
Vujkovic, M., Keaton, J. M., Lynch, J. A., Miller, D. R., Zhou, J., Tcheandjieu, C., Huffman, J. E., Assimes, T. L., Lorenz, K., Zhu, X., Hilliard, A. T., Judy, R. L., Huang, J., Lee, K. M., Klarin, D., Pyarajan, S., Danesh, J., Melander, O., Rasheed, A., … Saleheen, D. (2020). Discovery of 318 new risk loci for type 2 diabetes and related vascular outcomes among 1.4 million participants in a multi-ancestry meta-analysis. Nature Genetics, 52(7), Article 7. https://doi.org/10.1038/s41588-020-0637-y
Yajnik, C. S., Fall, C. H. D., Coyaji, K. J., Hirve, S. S., Rao, S., Barker, D. J. P., Joglekar, C., & Kellingray, S. (2003). Neonatal anthropometry: The thin–fat Indian baby. The Pune Maternal Nutrition Study. International Journal of Obesity, 27(2), Article 2. https://doi.org/10.1038/sj.ijo.802219
Yajnik, C. S., Lubree, H. G., Rege, S. S., Naik, S. S., Deshpande, J. A., Deshpande, S. S., Joglekar, C. V., & Yudkin, J. S. (2002). Adiposity and Hyperinsulinemia in Indians Are Present at Birth. The Journal of Clinical Endocrinology & Metabolism, 87(12), 5575–5580. https://doi.org/10.1210/jc.2002-020434