Journal of Genetics, Vol. 97, No. 4, September 2018, pp. 1047–1071 © Indian Academy of Sciences https://doi.org/10.1007/s12041-018-0987-8 REVIEW ARTICLE Genetics of obesity and its measures in India SIMMI SAINI1, GAGANDEEP KAUR WALIA2, MOHINDER PAL SACHDEVA1 and VIPIN GUPTA1∗ 1Department of Anthropology, University of Delhi, Delhi 110 007, India 2Public Health Foundation of India, Gurugram 122 002, India *For correspondence. E-mail: [email protected]. Received 14 September 2017; accepted 27 February 2018; published online 14 September 2018 Abstract. Obesity is one of the largest global health problems associated with increased morbidity and mortality mediated by its association with several other metabolic disorders. The interaction between the genes and environment plays an important role in the manifestation of obesity. Despite a high heritability (40–70%) of obesity, the search for genetic variants associated with obesity susceptibility has been a challenging task. To date, limited studies have been conducted in India, restricted to the validation of few genetic variants identified by genomewide association studies. In this critical review, we sought to examine the current knowledge of genetic basis of obesity and its measures in the Indian population. A comprehensive literature search was performed using ‘PubMed’, ‘Medline’ and ‘IndMed’ databases to search for citations published until 31st May 2017, using the key terms as ‘Genetics’ AND ‘obesity’ AND ‘India’. We identified 48 potential studies which fulfilled the eligibility criteria. The findings indicated that FTO, MC4R, TNF-α, PPAR-γ , UCP1, UCP2, LPL, LEPR, AMD1, IL6, APOE, ADIPOQ, DOK5, INSIG2, PBEF1, IL6R, Myostatin, CXCR4, HHEX, IRX3, POMC, NGN3, FOXA2, MTR, TCN and CHDH are some of the important genes studied among the Indian population. Importantly, the role of sexual dimorphism in the genetic regulation of obesity and body fat distribution was also reported in a few studies. Further, seven biological pathways have been identified that contribute to obesity pathogenesis in India. In conclusion, further exploration of pathway-based research on genetics of obesity can be useful for better understanding the pathophysiology of obesity in India. Keywords. obesity; body fat distribution; genetics; genomewide association study; India. Introduction school-aged children worldwide, between 5 and 17 years, are either overweight or obese (Kalra and Unnikrishnan Obesity is one of the common public-health conditions 2012). A recent systematic review has reported a combined that has a huge epidemiological burden across low-, prevalence of 19.3% of childhood overweight and obesity middle-income and high-income countries. The global in India which is a significant increase from the earlier burden of overweight/obesity increased to 36.9% in men prevalence of 16.3% reported in 2001–2005 (Ranjani et al. and 38% in women in 2013 (Ng et al. 2014). Rising preva- 2016). lence of overweight and obesity is the major driving factor Obesity is broadly measured through body mass index of noncommunicable chronic diseases (NCDs), account- (BMI), which is a composite parameter of weight–height ing for 44% of diabetes, 23% of ischaemic heart disease and that indicates the amount of body fat and also used to between 7 and 41% of certain cancer burden (WHO 2013). classify overweight and obesity in adults (Chris 2004). In The prevalence of overweight/obesity range from 1.50 comparison with Western countries, a lower cut-off for to 45.6% among the Indian population (Kshatriya and BMI (≥23 kg/m2 instead of ≥25 kg/m2) has been proposed Acharya 2016; NFHS-4 2016, http://rchiips.org/NFHS/ to define overweight/obesity in South Asians including factsheet_NFHS-4.shtml). Indians (Misra and Khurana 2011). The risks for type- Childhood obesity is another rapidly growing public 2 diabetes (T2D) and cardiovascular diseases (CVDs) are health concern worldwide (Lobstein et al. 2004) and is one associated with a lower BMI among South Asians as they of the major determinants of onset of NCDs in adulthood have a higher total and central adiposity for a given body (Biro and Wien 2010). It has been estimated that 10% of weight when compared with matched white populations 1047 1048 Simmi Saini et al. (Sniderman et al. 2007; Misra and Khurana 2011). Fur- of relevant search terms such as: ‘genetics’ OR ‘genetic ther, higher rate of metabolic syndrome in South Asians association studies’ OR ‘single-nucleotide polymorphisms’ is mostly attributed to the increased prevalence of central AND ‘obesity’ OR ‘adiposity’ OR ‘body fat’ OR ‘seg- adiposity (Ramachandran and Snehalatha 2010). Waist mental body fat’ OR ‘central obesity’ AND ‘measures’ circumference (WC), hip circumference (HC) and waist– OR ‘body mass index’ OR ‘waist circumference’ OR ‘hip hip ratio (WHR) are the other indicators which measure circumference’ OR ‘waist hip ratio’ OR ‘skinfolds’ AND regional fat distribution (Avenell et al. 2004). A higher ‘risk’ AND ‘India’. We included all the studies that were prevalence of T2D and CVDs in Asian populations, espe- published until 31st May 2017. Bibliographies and cita- cially in women could be attributed to the higher WC tion sections of the retrieved articles were also reviewed (Sniderman et al. 2007; Kaur et al. 2012). for additional related studies. Obesity is an outcome of complex, heritable and mul- tifactorial interactions of multiple genes, environmental factors and behavioural traits that make the management Selection strategy and prevention challenging in human populations (Rao et al. 2014). Globally, the changing patterns of food intake, The inclusion criteria followed were: (i) studies published both in quality and quantity (nutrition transition), an in English language journals, (ii) studies related to humans, increase in physical inactivity due to increasing sedentary (iii) original research studies and (iv) studies conducted lifestyle, changing modes of transportation and increasing exclusively in India. Studies were excluded if they were (i) urbanization (WHO 2013) are contributing to the ris- duplicated studies, (ii) reviews (iii) based on gene expres- ing burden of obesity. Biologically, obesity is an adverse sion, (iv) methylation and (v) case only studies (in the case consequence of energy imbalance between the calories of other metabolic phenotypes such as T2D, insulin resis- consumed and calories expended. Family studies includ- tance and hyperinsulinaemia). ing twin and adoption studies indicated that adiposity is As a result of the initial search, we identified 919 poten- highly heritable with the estimated genetic contribution tial articles for inclusion. After excluding articles not ranging from 65 to 80% for body weight (Stunkard et al. related to humans, 628 papers were left for examination. 1986; Malis et al. 2005), 40–77% for BMI (Maes et al. 1997; Further, screening for duplicates left a total of 133 studies. Atwood et al. 2002; Schousboe et al. 2003; Wardle et al. Preliminary assessment of titles and abstracts was carried 2008) and 31–76% for WC and WHR (Selby et al. 1990; out to determine the objectives and relevance of studies, Nelson et al. 1999; Souren et al. 2007) even after account- which resulted in the exclusion of 70 articles. The full ing for the BMI (Rose et al. 1998; Nelson et al. 2002). texts of 63 articles were read to extract information on Genomewide association studies (GWASs) have the topic of interest, of which 15 articles were excluded. changed the genetic landscape of common traits which The excluded articles did not fit the inclusion criteria. The were earlier restricted to the linkage and candidate gene- remaining 48 articles fulfilled eligibility criteria. based association studies. More than 80 genomewide linkage studies have been carried out so far, identifying Data extraction more than 300 chromosomal loci showing some evidence of linkage with obesity (Loos 2012). On the other hand, After the final inclusion, identifying information (such as since 2007, several waves of GWASs have been conducted research setting, study design, phenotype, gene, genetic in Western countries, and have discovered more than 100 variant and effect size) was extracted from each article and loci associated with obesity and related traits (Frayling is presented in tables 1–4. et al. 2007; Scuteri et al. 2007; Chambers et al. 2008; Heid et al. 2010; Speliotes et al. 2010; Locke et al. 2015; Shun- gin et al. 2015). Indian-specific GWASs related to obesity Genetic associations with obesity and its measures are absent and to date no published find- ings are available. To address the clinical and public health Of the 25 genetic studies exclusively on obesity in the implications of the alarming obesity epidemic in India, a Indian population only 15 had observed significant asso- comprehensive understanding of the genetic architecture ciations of genetic variants with obesity in pooled sample of obesity and related traits is demanded. Therefore, the size of 22,383 participants (table 2). Similar to the studies purpose of this review is to assess the current knowledge on Western populations (Frayling et al. 2007; Loos et al. and understanding of genetics of obesity and its measures 2008; Lindgren et al. 2009), FTO and MC4R loci have been in the Indian population. widely studied in India (table 2) as they are the major obe- sity determining genes even in younger age groups (Zhao Search strategy et al. 2011; Melka et al. 2012). Both the genes are highly expressed in the central nervous system that has shown to A comprehensive search was conducted using ‘PubMed’, play a significant role in control of the well-known regula- ‘Medline’ and ‘IndMed’ databases using a combination tory pathways of energy homeostasis (Beckers et al. 2009). Table 1. Study designs adopted for studying obesity and its measures in India. Study design No. of studies (n = 48) Areas covered References Population-based cross-sectional 2 Chennai Cassell et al. (1999); Vasan et al. (2012) 1 Delhi and Trivandrum Moore et al. (2012) 2 Lucknow, Nagpur, Hyderabad Taylor et al.