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1.  Contribution of Common Genetic Variants to Obesity and Obesity-Related Traits in Mexican Children and Adults 
PLoS ONE  2013;8(8):e70640.
Several studies have identified multiple obesity-associated loci mainly in European populations. However, their contribution to obesity in other ethnicities such as Mexicans is largely unknown. The aim of this study was to examine 26 obesity-associated single-nucleotide polymorphisms (SNP) in a sample of Mexican mestizos.
9 SNPs in biological candidate genes showing replications (PPARG, ADRB3, ADRB2, LEPR, GNB3, UCP3, ADIPOQ, UCP2, and NR3C1), and 17 SNPs in or near genes associated with obesity in first, second and third wave GWAS (INSIG2, FTO, MC4R, TMEM18, FAIM2/BCDIN3, BDNF, SH2B1, GNPDA2, NEGR1, KCTD15, SEC16B/RASAL2, NPC1, SFRF10/ETV5, MAF, PRL, MTCH2, and PTER) were genotyped in 1,156 unrelated Mexican-Mestizos including 683 cases (441 obese class I/II and 242 obese class III) and 473 normal-weight controls. In a second stage we selected 12 of the SNPs showing nominal associations with obesity, to seek associations with quantitative obesity-related traits in 3 cohorts including 1,218 Mexican Mestizo children, 945 Mexican Mestizo adults, and 543 Indigenous Mexican adults.
After adjusting for age, sex and admixture, significant associations with obesity were found for 6 genes in the case-control study (ADIPOQ, FTO, TMEM18, INSIG2, FAIM2/BCDIN3 and BDNF). In addition, SH2B1 was associated only with class I/II obesity and MC4R only with class III obesity. SNPs located at or near FAIM2/BCDIN3, TMEM18, INSIG2, GNPDA2 and SEC16B/RASAL2 were significantly associated with BMI and/or WC in the combined analysis of Mexican-mestizo children and adults, and FTO locus was significantly associated with increased BMI in Indigenous Mexican populations.
Our findings replicate the association of 8 obesity-related SNPs with obesity risk in Mexican adults, and confirm the role of some of these SNPs in BMI in Mexican adults and children.
PMCID: PMC3738539  PMID: 23950976
2.  Genetic Markers of Adult Obesity Risk Are Associated with Greater Early Infancy Weight Gain and Growth 
PLoS Medicine  2010;7(5):e1000284.
Ken Ong and colleagues genotyped children from the ALSPAC birth cohort and showed an association between greater early infancy gains in weight and length and genetic markers for adult obesity risk.
Genome-wide studies have identified several common genetic variants that are robustly associated with adult obesity risk. Exploration of these genotype associations in children may provide insights into the timing of weight changes leading to adult obesity.
Methods and Findings
Children from the Avon Longitudinal Study of Parents and Children (ALSPAC) birth cohort were genotyped for ten genetic variants previously associated with adult BMI. Eight variants that showed individual associations with childhood BMI (in/near: FTO, MC4R, TMEM18, GNPDA2, KCTD15, NEGR1, BDNF, and ETV5) were used to derive an “obesity-risk-allele score” comprising the total number of risk alleles (range: 2–15 alleles) in each child with complete genotype data (n = 7,146). Repeated measurements of weight, length/height, and body mass index from birth to age 11 years were expressed as standard deviation scores (SDS). Early infancy was defined as birth to age 6 weeks, and early infancy failure to thrive was defined as weight gain between below the 5th centile, adjusted for birth weight. The obesity-risk-allele score showed little association with birth weight (regression coefficient: 0.01 SDS per allele; 95% CI 0.00–0.02), but had an apparently much larger positive effect on early infancy weight gain (0.119 SDS/allele/year; 0.023–0.216) than on subsequent childhood weight gain (0.004 SDS/allele/year; 0.004–0.005). The obesity-risk-allele score was also positively associated with early infancy length gain (0.158 SDS/allele/year; 0.032–0.284) and with reduced risk of early infancy failure to thrive (odds ratio  = 0.92 per allele; 0.86–0.98; p = 0.009).
The use of robust genetic markers identified greater early infancy gains in weight and length as being on the pathway to adult obesity risk in a contemporary birth cohort.
Please see later in the article for the Editors' Summary
Editors' Summary
The proportion of overweight and obese children is increasing across the globe. In the US, the Surgeon General estimates that, compared with 1980, twice as many children and three times the number of adolescents are now overweight. Worldwide, 22 million children under five years old are considered by the World Health Organization to be overweight.
Being overweight or obese in childhood is associated with poor physical and mental health. In addition, childhood obesity is considered a major risk factor for adult obesity, which is itself a major risk factor for cancer, heart disease, diabetes, osteoarthritis, and other chronic conditions.
The most commonly used measure of whether an adult is a healthy weight is body mass index (BMI), defined as weight in kilograms/(height in metres)2. However, adult categories of obese (>30) and overweight (>25) BMI are not directly applicable to children, whose BMI naturally varies as they grow. BMI can be used to screen children for being overweight and or obese but a diagnosis requires further information.
Why Was This Study Done?
As the numbers of obese and overweight children increase, a corresponding rise in future numbers of overweight and obese adults is also expected. This in turn is expected to lead to an increasing incidence of poor health. As a result, there is great interest among health professionals in possible pathways between childhood and adult obesity. It has been proposed that certain periods in childhood may be critical for the development of obesity.
In the last few years, ten genetic variants have been found to be more common in overweight or obese adults. Eight of these have also been linked to childhood BMI and/or obesity. The authors wanted to identify the timing of childhood weight changes that may be associated with adult obesity. Knowledge of obesity risk genetic variants gave them an opportunity to do so now, without following a set of children to adulthood.
What Did the Researchers Do and Find?
The authors analysed data gathered from a subset of 7,146 singleton white European children enrolled in the Avon Longitudinal Study of Parents and Children (ALSPAC) study, which is investigating associations between genetics, lifestyle, and health outcomes for a group of children in Bristol whose due date of birth fell between April 1991 and December 1992. They used knowledge of the children's genetic makeup to find associations between an obesity risk allele score—a measure of how many of the obesity risk genetic variants a child possessed—and the children's weight, height, BMI, levels of body fat (at nine years old), and rate of weight gain, up to age 11 years.
They found that, at birth, children with a higher obesity risk allele score were not any heavier, but in the immediate postnatal period they were less likely to be in the bottom 5% of the population for weight gain (adjusted for birthweight), often termed “failure to thrive.” At six weeks of age, children with a higher obesity risk allele score tended to be longer and heavier, even allowing for weight at birth.
After six weeks of age, the obesity risk allele score was not associated with any further increase in length/height, but it was associated with a more rapid weight gain between birth and age 11 years. BMI is derived from height and weight measurements, and the association between the obesity risk allele score and BMI was weak between birth and age three-and-a-half years, but after that age the association with BMI increased rapidly. By age nine, children with a higher obesity risk allele score tended to be heavier and taller, with more fat on their bodies.
What Do These Findings Mean?
The combined obesity allele risk score is associated with higher rates of weight gain and adult obesity, and so the authors conclude that weight gain and growth even in the first few weeks after birth may be the beginning of a pathway of greater adult obesity risk.
A study that tracks a population over time can find associations but it cannot show cause and effect. In addition, only a relatively small proportion (1.7%) of the variation in BMI at nine years of age is explained by the obesity risk allele score.
The authors' method of finding associations between childhood events and adult outcomes via genetic markers of risk of disease as an adult has a significant advantage: the authors did not have to follow the children themselves to adulthood, so their findings are more likely to be relevant to current populations. Despite this, this research does not yield advice for parents how to reduce their children's obesity risk. It does suggest that “failure to thrive” in the first six weeks of life is not simply due to a lack of provision of food by the baby's caregiver but that genetic factors also contribute to early weight gain and growth.
The study looked at the combined obesity risk allele score and the authors did not attempt to identify which individual alleles have greater or weaker associations with weight gain and overweight or obesity. This would require further research based on far larger numbers of babies and children. The findings may also not be relevant to children in other types of setting because of the effects of different nutrition and lifestyles.
Additional Information
Please access these Web sites via the online version of this summary at
Further information is available on the ALSPAC study
The UK National Health Service and other partners provide guidance on establishing a healthy lifestyle for children and families in their Change4Life programme
The International Obesity Taskforce is a global network of expertise and the advocacy arm of the International Association for the Study of Obesity. It works with the World Health Organization, other NGOs, and stakeholders and provides information on overweight and obesity
The Centers for Disease Control and Prevention (CDC) in the US provide guidance and tips on maintaining a healthy weight, including BMI calculators in both metric and Imperial measurements for both adults and children. They also provide BMI growth charts for boys and girls showing how healthy ranges vary for each sex at with age
The Royal College of Paediatrics and Child Health provides growth charts for weight and length/height from birth to age 4 years that are based on WHO 2006 growth standards and have been adapted for use in the UK
The CDC Web site provides information on overweight and obesity in adults and children, including definitions, causes, and data
The CDC also provide information on the role of genes in causing obesity.
The World Health Organization publishes a fact sheet on obesity, overweight and weight management, including links to childhood overweight and obesity
Wikipedia includes an article on childhood obesity (note that Wikipedia is a free online encyclopedia that anyone can edit; available in several languages)
PMCID: PMC2876048  PMID: 20520848
3.  Replication and extension of genome-wide association study results for obesity in 4923 adults from northern Sweden 
Human Molecular Genetics  2009;18(8):1489-1496.
Recent genome-wide association studies (GWAS) have identified multiple risk loci for common obesity (FTO, MC4R, TMEM18, GNPDA2, SH2B1, KCTD15, MTCH2, NEGR1 and PCSK1). Here we extend those studies by examining associations with adiposity and type 2 diabetes in Swedish adults. The nine single nucleotide polymorphisms (SNPs) were genotyped in 3885 non-diabetic and 1038 diabetic individuals with available measures of height, weight and body mass index (BMI). Adipose mass and distribution were objectively assessed using dual-energy X-ray absorptiometry in a sub-group of non-diabetics (n = 2206). In models with adipose mass traits, BMI or obesity as outcomes, the most strongly associated SNP was FTO rs1121980 (P < 0.001). Five other SNPs (SH2B1 rs7498665, MTCH2 rs4752856, MC4R rs17782313, NEGR1 rs2815752 and GNPDA2 rs10938397) were significantly associated with obesity. To summarize the overall genetic burden, a weighted risk score comprising a subset of SNPs was constructed; those in the top quintile of the score were heavier (+2.6 kg) and had more total (+2.4 kg), gynoid (+191 g) and abdominal (+136 g) adipose tissue than those in the lowest quintile (all P < 0.001). The genetic burden score significantly increased diabetes risk, with those in the highest quintile (n = 193/594 cases/controls) being at 1.55-fold (95% CI 1.21–1.99; P < 0.0001) greater risk of type 2 diabetes than those in the lowest quintile (n = 130/655 cases/controls). In summary, we have statistically replicated six of the previously associated obese-risk loci and our results suggest that the weight-inducing effects of these variants are explained largely by increased adipose accumulation.
PMCID: PMC2664142  PMID: 19164386
4.  Modelling BMI Trajectories in Children for Genetic Association Studies 
PLoS ONE  2013;8(1):e53897.
The timing of associations between common genetic variants and changes in growth patterns over childhood may provide insight into the development of obesity in later life. To address this question, it is important to define appropriate statistical models to allow for the detection of genetic effects influencing longitudinal childhood growth.
Methods and Results
Children from The Western Australian Pregnancy Cohort (Raine; n = 1,506) Study were genotyped at 17 genetic loci shown to be associated with childhood obesity (FTO, MC4R, TMEM18, GNPDA2, KCTD15, NEGR1, BDNF, ETV5, SEC16B, LYPLAL1, TFAP2B, MTCH2, BCDIN3D, NRXN3, SH2B1, MRSA) and an obesity-risk-allele-score was calculated as the total number of ‘risk alleles’ possessed by each individual. To determine the statistical method that fits these data and has the ability to detect genetic differences in BMI growth profile, four methods were investigated: linear mixed effects model, linear mixed effects model with skew-t random errors, semi-parametric linear mixed models and a non-linear mixed effects model. Of the four methods, the semi-parametric linear mixed model method was the most efficient for modelling childhood growth to detect modest genetic effects in this cohort. Using this method, three of the 17 loci were significantly associated with BMI intercept or trajectory in females and four in males. Additionally, the obesity-risk-allele score was associated with increased average BMI (female: β = 0.0049, P = 0.0181; male: β = 0.0071, P = 0.0001) and rate of growth (female: β = 0.0012, P = 0.0006; male: β = 0.0008, P = 0.0068) throughout childhood.
Using statistical models appropriate to detect genetic variants, variations in adult obesity genes were associated with childhood growth. There were also differences between males and females. This study provides evidence of genetic effects that may identify individuals early in life that are more likely to rapidly increase their BMI through childhood, which provides some insight into the biology of childhood growth.
PMCID: PMC3547961  PMID: 23349760
5.  Studies of Metabolic Phenotypic Correlates of 15 Obesity Associated Gene Variants 
PLoS ONE  2011;6(9):e23531.
Genome-wide association studies have identified novel BMI/obesity associated susceptibility loci. The purpose of this study is to determine associations with overweight, obesity, morbid obesity and/or general adiposity in a Danish population. Moreover, we want to investigate if these loci associate with type 2 diabetes and to elucidate potential underlying metabolic mechanisms.
15 gene variants in 14 loci including TMEM18 (rs7561317), SH2B1 (rs7498665), KCTD15 (rs29941), NEGR1 (rs2568958), ETV5 (rs7647305), BDNF (rs4923461, rs925946), SEC16B (rs10913469), FAIM2 (rs7138803), GNPDA2 (rs10938397), MTCH2 (rs10838738), BAT2 (rs2260000), NPC1 (rs1805081), MAF (rs1424233), and PTER (rs10508503) were genotyped in 18,014 middle-aged Danes.
Five of the 15 gene variants associated with overweight, obesity and/or morbid obesity. Per allele ORs ranged from 1.15–1.20 for overweight, 1.10–1.25 for obesity, and 1.41–1.46 for morbid obesity. Five of the 15 variants moreover associated with increased measures of adiposity. BDNF rs4923461 displayed a borderline BMI-dependent protective effect on type 2 diabetes (0.87 (0.78–0.96, p = 0.008)), whereas SH2B1 rs7498665 associated with nominally BMI-independent increased risk of type 2 diabetes (1.16 (1.07–1.27, p = 7.8×10−4)).
Associations with overweight and/or obesity and measures of obesity were confirmed for seven out of the 15 gene variants. The obesity risk allele of BDNF rs4923461 protected against type 2 diabetes, which could suggest neuronal and peripheral distinctive ways of actions for the protein. SH2B1 rs7498665 associated with type 2 diabetes independently of BMI.
PMCID: PMC3166286  PMID: 21912638
6.  BMI-Associated Alleles Do Not Constitute Risk Alleles for Polycystic Ovary Syndrome Independently of BMI: A Case-Control Study 
PLoS ONE  2014;9(1):e87335.
Polycystic Ovary Syndrome (PCOS) has a strong genetic background and the majority of patients with PCOS have elevated BMI levels. The aim of this study was to determine to which extent BMI-increasing alleles contribute to risk of PCOS when contemporaneous BMI is taken into consideration.
Patients with PCOS and controls were recruited from the United Kingdom (563 cases and 791 controls) and The Netherlands (510 cases and 2720 controls). Cases and controls were of similar BMI. SNPs mapping to 12 BMI-associated loci which have been extensively replicated across different ethnicities, i.e., BDNF, FAIM2, ETV5, FTO, GNPDA2, KCTD15, MC4R, MTCH2, NEGR1, SEC16B, SH2B1, and TMEM18, were studied in association with PCOS within each cohort using the additive genetic model followed by a combined analysis. A genetic allelic count risk score model was used to determine the risk of PCOS for individuals carrying increasing numbers of BMI-increasing alleles.
None of the genetic variants, including FTO and MC4R, was associated with PCOS independently of BMI in the meta-analysis. Moreover, no differences were observed between cases and controls in the number of BMI-risk alleles present and no overall trend across the risk score groups was observed.
In this combined analysis of over 4,000 BMI-matched individuals from the United Kingdom and the Netherlands, we observed no association of BMI risk alleles with PCOS independent of BMI.
PMCID: PMC3909077  PMID: 24498077
7.  Susceptibility variants for obesity and colorectal cancer risk: the Multiethnic Cohort and PAGE Studies 
Obesity is a leading contributor to colorectal cancer risk. We investigated whether the risk variants identified in genome-wide association studies of body mass index (BMI) and waist size are associated with colorectal cancer risk, independently of the effect of obesity phenotype due to a shared etiology. Twenty four SNPs in 15 loci (BDNF, FAIM2, FTO, GNPDA2, KCTD15, LYPLAL1, MC4R, MSRA, MTCH2, NEGR1, NRXN3, SEC16B, SH2B1, TFAP2B, and TMEM18) were genotyped in a case-control study of 2,033 colorectal cancer cases and 9,640 controls nested within the Multiethnic Cohort Study, as part of the Population Architecture using Genomics and Epidemiology (PAGE) consortium. Risk alleles for two obesity SNPs were associated with colorectal cancer risk – KCTD15 rs29941 [odds ratio (OR) for C allele = 0.90, 95% confidence interval (CI) 0.83–0.98; p = 0.01] and MC4R rs17782313 (OR for C allele = 1.12, 95% CI 1.02–1.22; p = 0.02). These associations were independent of the effect of BMI. However, none of the results remained significant after adjustment for multiple comparisons. No heterogeneity was observed across race/ethnic groups. Our findings suggest that the obesity risk variants are not likely to affect the risk of colorectal cancer substantially.
PMCID: PMC3402643  PMID: 22511254
genotype-phenotype interactions; obesity; pleiotropy; prospective nested case-control studies; race/ethnicity
8.  Adult obesity susceptibility variants are associated with greater childhood weight gain and a faster tempo of growth: the 1946 British Birth Cohort Study123 
Background: Longitudinal growth associations with genetic variants identified for adult BMI may provide insights into the timing of obesity susceptibility.
Objective: The objective was to explore associations of known BMI loci with measures of body size from birth to adulthood.
Design: A total of 2537 individuals from a longitudinal British birth cohort were genotyped for 11 genetic variants robustly associated with adult BMI (in/near FTO, MC4R, TMEM18, GNPDA2, KCTD15, NEGR1, BDNF, ETV5, SEC16B, SH2B1, and MTCH2). We derived an obesity-risk-allele score, comprising the sum of BMI-increasing alleles in each individual, and examined this for an association with birth weight and repeated measures of weight, height, and BMI SD scores (SDS) at 11 time points between ages 2 and 53 y.
Results: The obesity-risk-allele score showed borderline significant association with birth weight (0.019 SDS/allele; P = 0.05) and was more clearly associated with higher weight and BMI at all time points between ages 2 and 53 y; the strongest associations with weight occurred at ages 11 and 20 y (both 0.056 SDS/allele). In longitudinal analyses, the score was positively associated with weight gain only between birth and 11 y (0.003 SDS/allele per year; 95% CI: 0.001, 0.004; P = 0.001). The risk-allele score was associated with taller height at 7 y (0.031 SDS/allele; P = 0.002) and greater height gains between 2 and 7 y (0.007 SDS/allele per year; P < 0.001), but not with adult height (P = 0.5).
Conclusions: The combined effect of adult obesity susceptibility variants on weight gain was confined to childhood. These variants conferred a faster tempo of height growth that was evident before the pubertal years.
PMCID: PMC3325838  PMID: 22456663
9.  Mendelian Randomisation Study of Childhood BMI and Early Menarche 
Journal of Obesity  2011;2011:180729.
To infer the causal association between childhood BMI and age at menarche, we performed a mendelian randomisation analysis using twelve established “BMI-increasing” genetic variants as an instrumental variable (IV) for higher BMI. In 8,156 women of European descent from the EPIC-Norfolk cohort, height was measured at age 39–77 years; age at menarche was self-recalled, as was body weight at age 20 years, and BMI at 20 was calculated as a proxy for childhood BMI. DNA was genotyped for twelve BMI-associated common variants (in/near FTO, MC4R, TMEM18, GNPDA2, KCTD15, NEGR1, BDNF, ETV5, MTCH2, SEC16B, FAIM2 and SH2B1), and for each individual a “BMI-increasing-allele-score” was calculated by summing the number of BMI-increasing alleles across all 12 loci. Using this BMI-increasing-allele-score as an instrumental variable for BMI, each 1 kg/m2 increase in childhood BMI was predicted to result in a 6.5% (95% CI: 4.6–8.5%) higher absolute risk of early menarche (before age 12 years). While mendelian randomisation analysis is dependent on a number of assumptions, our findings support a causal effect of BMI on early menarche and suggests that increasing prevalence of childhood obesity will lead to similar trends in the prevalence of early menarche.
PMCID: PMC3136158  PMID: 21773002
10.  Six new loci associated with body mass index highlight a neuronal influence on body weight regulation 
Willer, Cristen J | Speliotes, Elizabeth K | Loos, Ruth J F | Li, Shengxu | Lindgren, Cecilia M | Heid, Iris M | Berndt, Sonja I | Elliott, Amanda L | Jackson, Anne U | Lamina, Claudia | Lettre, Guillaume | Lim, Noha | Lyon, Helen N | McCarroll, Steven A | Papadakis, Konstantinos | Qi, Lu | Randall, Joshua C | Roccasecca, Rosa Maria | Sanna, Serena | Scheet, Paul | Weedon, Michael N | Wheeler, Eleanor | Zhao, Jing Hua | Jacobs, Leonie C | Prokopenko, Inga | Soranzo, Nicole | Tanaka, Toshiko | Timpson, Nicholas J | Almgren, Peter | Bennett, Amanda | Bergman, Richard N | Bingham, Sheila A | Bonnycastle, Lori L | Brown, Morris | Burtt, Noël P | Chines, Peter | Coin, Lachlan | Collins, Francis S | Connell, John M | Cooper, Cyrus | Smith, George Davey | Dennison, Elaine M | Deodhar, Parimal | Elliott, Paul | Erdos, Michael R | Estrada, Karol | Evans, David M | Gianniny, Lauren | Gieger, Christian | Gillson, Christopher J | Guiducci, Candace | Hackett, Rachel | Hadley, David | Hall, Alistair S | Havulinna, Aki S | Hebebrand, Johannes | Hofman, Albert | Isomaa, Bo | Jacobs, Kevin B | Johnson, Toby | Jousilahti, Pekka | Jovanovic, Zorica | Khaw, Kay-Tee | Kraft, Peter | Kuokkanen, Mikko | Kuusisto, Johanna | Laitinen, Jaana | Lakatta, Edward G | Luan, Jian'an | Luben, Robert N | Mangino, Massimo | McArdle, Wendy L | Meitinger, Thomas | Mulas, Antonella | Munroe, Patricia B | Narisu, Narisu | Ness, Andrew R | Northstone, Kate | O'Rahilly, Stephen | Purmann, Carolin | Rees, Matthew G | Ridderstråle, Martin | Ring, Susan M | Rivadeneira, Fernando | Ruokonen, Aimo | Sandhu, Manjinder S | Saramies, Jouko | Scott, Laura J | Scuteri, Angelo | Silander, Kaisa | Sims, Matthew A | Song, Kijoung | Stephens, Jonathan | Stevens, Suzanne | Stringham, Heather M | Tung, Y C Loraine | Valle, Timo T | Van Duijn, Cornelia M | Vimaleswaran, Karani S | Vollenweider, Peter | Waeber, Gerard | Wallace, Chris | Watanabe, Richard M | Waterworth, Dawn M | Watkins, Nicholas | Witteman, Jacqueline C M | Zeggini, Eleftheria | Zhai, Guangju | Zillikens, M Carola | Altshuler, David | Caulfield, Mark J | Chanock, Stephen J | Farooqi, I Sadaf | Ferrucci, Luigi | Guralnik, Jack M | Hattersley, Andrew T | Hu, Frank B | Jarvelin, Marjo-Riitta | Laakso, Markku | Mooser, Vincent | Ong, Ken K | Ouwehand, Willem H | Salomaa, Veikko | Samani, Nilesh J | Spector, Timothy D | Tuomi, Tiinamaija | Tuomilehto, Jaakko | Uda, Manuela | Uitterlinden, André G | Wareham, Nicholas J | Deloukas, Panagiotis | Frayling, Timothy M | Groop, Leif C | Hayes, Richard B | Hunter, David J | Mohlke, Karen L | Peltonen, Leena | Schlessinger, David | Strachan, David P | Wichmann, H-Erich | McCarthy, Mark I | Boehnke, Michael | Barroso, Inês | Abecasis, Gonçalo R | Hirschhorn, Joel N
Nature genetics  2008;41(1):25-34.
Common variants at only two loci, FTO and MC4R, have been reproducibly associated with body mass index (BMI) in humans. To identify additional loci, we conducted meta-analysis of 15 genome-wide association studies for BMI (n > 32,000) and followed up top signals in 14 additional cohorts (n > 59,000). We strongly confirm FTO and MC4R and identify six additional loci (P < 5 × 10−8): TMEM18, KCTD15, GNPDA2, SH2B1, MTCH2 and NEGR1 (where a 45-kb deletion polymorphism is a candidate causal variant). Several of the likely causal genes are highly expressed or known to act in the central nervous system (CNS), emphasizing, as in rare monogenic forms of obesity, the role of the CNS in predisposition to obesity.
PMCID: PMC2695662  PMID: 19079261
11.  Genes and lifestyle factors in obesity: results from 12 462 subjects from MONICA/KORA 
Data from meta-analyses of genome-wide association studies provided evidence for an association of polymorphisms with body mass index (BMI), and gene expression results indicated a role of these variants in the hypothalamus. It was consecutively hypothesized that these associations might be evoked by a modulation of nutritional intake or energy expenditure.
It was our aim to investigate the association of these genetic factors with BMI in a large homogenous population-based sample to explore the association of these polymorphisms with lifestyle factors related to nutritional intake or energy expenditure, and whether such lifestyle factors could be mediators of the detected single-nucleotide polymorphism (SNP)-association with BMI. It was a further aim to compare the proportion of BMI explained by genetic factors with the one explained by lifestyle factors.
The association of seven polymorphisms in or near the genes NEGR1, TMEM18, MTCH2, FTO, MC4R, SH2B1and KCTD15 was analyzed in 12 462 subjects from the population-based MONICA/KORA Augsburg study. Information on lifestyle factors was based on standardized questionnaires. For statistical analysis, regression-based models were used.
The minor allele of polymorphism rs6548238 C>T (TMEM18) was associated with lower BMI (−0.418 kg/m2, p=1.22×10−8), and of polymorphisms rs9935401 G>A (FTO) and rs7498665 A>G (SH2B1) with increased BMI (0.290 kg/m2, p=2.85×10−7 and 0.145 kg/m2, p=9.83×10−3). The other polymorphisms were not significantly associated. Lifestyle factors were correlated with BMI and explained 0.037 % of the BMI variance as compared to 0.006 % of explained variance by the associated genetic factors. The genetic variants associated with BMI were not significantly associated with lifestyle factors and there was no evidence of lifestyle factors mediating the SNP-BMI association.
Our data first confirm the findings for TMEM18 with BMI in a single study on adults and also confirm the findings for FTO and SH2B1. There was no evidence for a direct SNP-lifestyle association.
PMCID: PMC3251754  PMID: 20386550
TMEM18; FTO; SH2B1; lifestyle; obesity
12.  Genome-Wide Population-Based Association Study of Extremely Overweight Young Adults – The GOYA Study 
PLoS ONE  2011;6(9):e24303.
Thirty-two common variants associated with body mass index (BMI) have been identified in genome-wide association studies, explaining ∼1.45% of BMI variation in general population cohorts. We performed a genome-wide association study in a sample of young adults enriched for extremely overweight individuals. We aimed to identify new loci associated with BMI and to ascertain whether using an extreme sampling design would identify the variants known to be associated with BMI in general populations.
Methodology/Principal Findings
From two large Danish cohorts we selected all extremely overweight young men and women (n = 2,633), and equal numbers of population-based controls (n = 2,740, drawn randomly from the same populations as the extremes, representing ∼212,000 individuals). We followed up novel (at the time of the study) association signals (p<0.001) from the discovery cohort in a genome-wide study of 5,846 Europeans, before attempting to replicate the most strongly associated 28 SNPs in an independent sample of Danish individuals (n = 20,917) and a population-based cohort of 15-year-old British adolescents (n = 2,418). Our discovery analysis identified SNPs at three loci known to be associated with BMI with genome-wide confidence (P<5×10−8; FTO, MC4R and FAIM2). We also found strong evidence of association at the known TMEM18, GNPDA2, SEC16B, TFAP2B, SH2B1 and KCTD15 loci (p<0.001), and nominal association (p<0.05) at a further 8 loci known to be associated with BMI. However, meta-analyses of our discovery and replication cohorts identified no novel associations.
Our results indicate that the detectable genetic variation associated with extreme overweight is very similar to that previously found for general BMI. This suggests that population-based study designs with enriched sampling of individuals with the extreme phenotype may be an efficient method for identifying common variants that influence quantitative traits and a valid alternative to genotyping all individuals in large population-based studies, which may require tens of thousands of subjects to achieve similar power.
PMCID: PMC3174168  PMID: 21935397
13.  EMR-linked GWAS study: investigation of variation landscape of loci for body mass index in children 
Frontiers in Genetics  2013;4:268.
Common variations at the loci harboring the fat mass and obesity gene (FTO), MC4R, and TMEM18 are consistently reported as being associated with obesity and body mass index (BMI) especially in adult population. In order to confirm this effect in pediatric population five European ancestry cohorts from pediatric eMERGE-II network (CCHMC-BCH) were evaluated.
Method: Data on 5049 samples of European ancestry were obtained from the Electronic Medical Records (EMRs) of two large academic centers in five different genotyped cohorts. For all available samples, gender, age, height, and weight were collected and BMI was calculated. To account for age and sex differences in BMI, BMI z-scores were generated using 2000 Centers of Disease Control and Prevention (CDC) growth charts. A Genome-wide association study (GWAS) was performed with BMI z-score. After removing missing data and outliers based on principal components (PC) analyses, 2860 samples were used for the GWAS study. The association between each single nucleotide polymorphism (SNP) and BMI was tested using linear regression adjusting for age, gender, and PC by cohort. The effects of SNPs were modeled assuming additive, recessive, and dominant effects of the minor allele. Meta-analysis was conducted using a weighted z-score approach.
Results: The mean age of subjects was 9.8 years (range 2–19). The proportion of male subjects was 56%. In these cohorts, 14% of samples had a BMI ≥95 and 28 ≥ 85%. Meta analyses produced a signal at 16q12 genomic region with the best result of p = 1.43 × 10-7 [p(rec) = 7.34 × 10-8) for the SNP rs8050136 at the first intron of FTO gene (z = 5.26) and with no heterogeneity between cohorts (p = 0.77). Under a recessive model, another published SNP at this locus, rs1421085, generates the best result [z = 5.782, p(rec) = 8.21 × 10-9]. Imputation in this region using dense 1000-Genome and Hapmap CEU samples revealed 71 SNPs with p < 10-6, all at the first intron of FTO locus. When hetero-geneity was permitted between cohorts, signals were also obtained in other previously identified loci, including MC4R (rs12964056, p = 6.87 × 10-7, z = -4.98), cholecystokinin CCK (rs8192472, p = 1.33 × 10-6, z = -4.85), Interleukin 15 (rs2099884, p = 1.27 × 10-5, z = 4.34), low density lipoprotein receptor-related protein 1B [LRP1B (rs7583748, p = 0.00013, z = -3.81)] and near transmembrane protein 18 (TMEM18) (rs7561317, p = 0.001, z = -3.17). We also detected a novel locus at chromosome 3 at COL6A5 [best SNP = rs1542829, minor allele frequency (MAF) of 5% p = 4.35 × 10-9, z = 5.89].
Conclusion: An EMR linked cohort study demonstrates that the BMI-Z measurements can be successfully extracted and linked to genomic data with meaningful confirmatory results. We verified the high prevalence of childhood rate of overweight and obesity in our cohort (28%). In addition, our data indicate that genetic variants in the first intron of FTO, a known adult genetic risk factor for BMI, are also robustly associated with BMI in pediatric population.
PMCID: PMC3847941  PMID: 24348519
BMI; obesity; polymorphism; GWAS
14.  Expression of fourteen novel obesity-related genes in zucker diabetic fatty rats 
Genome-wide association studies (GWAS) are useful to reveal an association between single nucleotide polymorphisms and different measures of obesity. A multitude of new loci has recently been reported, but the exact function of most of the according genes is not known. The aim of our study was to start elucidating the function of some of these genes.
We performed an expression analysis of fourteen genes, namely BDNF, ETV5, FAIM2, FTO, GNPDA2, KCTD15, LYPLAL1, MCR4, MTCH2, NEGR1, NRXN3, TMEM18, SEC16B and TFAP2B, via real-time RT-PCR in adipose tissue of the kidney capsule, the mesenterium and subcutaneum as well as the hypothalamus of obese Zucker diabetic fatty (ZDF) and Zucker lean (ZL) rats at an age of 22 weeks.
All of our target genes except for SEC16B showed the highest expression in the hypothalamus. This suggests a critical role of these obesity-related genes in the central regulation of energy balance. Interestingly, the expression pattern in the hypothalamus showed no differences between obese ZDF and lean ZL rats. However, LYPLAL1, TFAP2B, SEC16B and FAIM2 were significantly lower expressed in the kidney fat of ZDF than ZL rats. NEGR1 was even lower expressed in subcutaneous and mesenterial fat, while MTCH2 was higher expressed in the subcutaneous and mesenterial fat of ZDF rats.
The expression pattern of the investigated obesity genes implies for most of them a role in the central regulation of energy balance, but for some also a role in the adipose tissue itself. For the development of the ZDF phenotype peripheral rather than central mechanisms of the investigated genes seem to be relevant.
PMCID: PMC3398851  PMID: 22553958
15.  Longitudinal Replication Studies of GWAS Risk SNPs Influencing Body Mass Index over the Course of Childhood and Adulthood 
PLoS ONE  2012;7(2):e31470.
Genome-wide association studies (GWAS) have identified multiple common variants associated with body mass index (BMI). In this study, we tested 23 genotyped GWAS-significant SNPs (p-value<5*10-8) for longitudinal associations with BMI during childhood (3–17 years) and adulthood (18–45 years) for 658 subjects. We also proposed a heuristic forward search for the best joint effect model to explain the longitudinal BMI variation. After using false discovery rate (FDR) to adjust for multiple tests, childhood and adulthood BMI were found to be significantly associated with six SNPs each (q-value<0.05), with one SNP associated with both BMI measurements: KCTD15 rs29941 (q-value<7.6*10-4). These 12 SNPs are located at or near genes either expressed in the brain (BDNF, KCTD15, TMEM18, MTCH2, and FTO) or implicated in cell apoptosis and proliferation (FAIM2, MAP2K5, and TFAP2B). The longitudinal effects of FAIM2 rs7138803 on childhood BMI and MAP2K5 rs2241423 on adulthood BMI decreased as age increased (q-value<0.05). The FTO candidate SNPs, rs6499640 at the 5 ′-end and rs1121980 and rs8050136 downstream, were associated with childhood and adulthood BMI, respectively, and the risk effects of rs6499640 and rs1121980 increased as birth weight decreased. The best joint effect model for childhood and adulthood BMI contained 14 and 15 SNPs each, with 11 in common, and the percentage of explained variance increased from 0.17% and 9.0*10−6% to 2.22% and 2.71%, respectively. In summary, this study evidenced the presence of long-term major effects of genes on obesity development, implicated in pathways related to neural development and cell metabolism, and different sets of genes associated with childhood and adulthood BMI, respectively. The gene effects can vary with age and be modified by prenatal development. The best joint effect model indicated that multiple variants with effects that are weak or absent alone can nevertheless jointly exert a large longitudinal effect on BMI.
PMCID: PMC3280302  PMID: 22355368
16.  The Influence of Obesity-Related Single Nucleotide Polymorphisms on BMI Across the Life Course 
Diabetes  2013;62(5):1763-1767.
Evidence is limited as to whether heritable risk of obesity varies throughout adulthood. Among >34,000 European Americans, aged 18–100 years, from multiple U.S. studies in the Population Architecture using Genomics and Epidemiology (PAGE) Consortium, we examined evidence for heterogeneity in the associations of five established obesity risk variants (near FTO, GNPDA2, MTCH2, TMEM18, and NEGR1) with BMI across four distinct epochs of adulthood: 1) young adulthood (ages 18–25 years), adulthood (ages 26–49 years), middle-age adulthood (ages 50–69 years), and older adulthood (ages ≥70 years); or 2) by menopausal status in women and stratification by age 50 years in men. Summary-effect estimates from each meta-analysis were compared for heterogeneity across the life epochs. We found heterogeneity in the association of the FTO (rs8050136) variant with BMI across the four adulthood epochs (P = 0.0006), with larger effects in young adults relative to older adults (β [SE] = 1.17 [0.45] vs. 0.09 [0.09] kg/m2, respectively, per A allele) and smaller intermediate effects. We found no evidence for heterogeneity in the association of GNPDA2, MTCH2, TMEM18, and NEGR1 with BMI across adulthood. Genetic predisposition to obesity may have greater effects on body weight in young compared with older adulthood for FTO, suggesting changes by age, generation, or secular trends. Future research should compare and contrast our findings with results using longitudinal data.
PMCID: PMC3636619  PMID: 23300277
17.  Obesity-susceptibility loci and the tails of the pediatric BMI distribution 
Obesity (Silver Spring, Md.)  2013;21(6):1256-1260.
We aimed to determine if previously identified adult obesity susceptibility loci were associated uniformly with childhood BMI across the BMI distribution.
Design and Methods
Children were recruited through the Children's Hospital of Philadelphia (n=7225). Associations between the following loci and BMI were assessed using quantile regression: FTO (rs3751812), MC4R (rs12970134), TMEM18 (rs2867125), BDNF (rs6265), TNNI3K (rs1514175), NRXN3 (rs10146997), SEC16B (rs10913469), and GNPDA2 (rs13130484). BMI z-score (age and gender adjusted) was modeled as the dependent variable, and genotype risk score (sum of risk alleles carried at the 8 loci) was modeled as the independent variable.
Each additional increase in genotype risk score was associated with an increase in BMI z-score at the 5th, 15th, 25th, 50th, 75th, 85th and 95th BMI z-score percentiles by 0.04 (±0.02, p=0.08), 0.07 (±0.01, p=9.58 × 10-7), 0.07 (±0.01, p=1.10 × 10-8), 0.09 (±0.01, p=3.13 × 10-22), 0.11 (±0.01, p=1.35 × 10-25), 0.11 (±0.01, p=1.98 × 10-20), and 0.06 (±0.01, p=2.44 × 10-6), respectively. Each additional increase in genotype risk score was associated with an increase in mean BMI z-score by 0.08 (±0.01, p=4.27 × 10-20).
Obesity risk alleles were more strongly associated with increases in BMI z-score at the upper tail compared to the lower tail of the distribution.
PMCID: PMC3661695  PMID: 23408508
18.  Study of 11 BMI-Associated Loci Identified in GWAS for Associations with Central Obesity in the Chinese Children 
PLoS ONE  2013;8(2):e56472.
Recent genome-wide association studies have identified many single nucleotide polymorphisms (SNPs) associated with body mass index (BMI)/generalized obesity. In this study, we aimed to examine the associations of identified SNPs with risk of central obesity in a child population from China.
We genotyped 11 SNPs (FTO rs9939609, MC4R rs17782313, GNPDA2 rs10938397, BDNF rs6265, FAIM2 rs7138803, NPC1 rs1805081, SEC16B rs10913469, SH2B1 rs4788102, PCSK1rs6235, KCTD15 rs29941, BAT2 rs2844479) in the Chinese children (N = 3502, age range 6–18 years) from the Beijing Child and Adolescent Metabolic Syndrome (BCAMS). Based on the age- and sex- specific waist circumference (WC) standards generated in the BCAMS study, 1196 central obese cases and 2306 controls were identified.
Of 11 studied SNPs, four SNPs and genetic risk score (GRS) based on them were statistically significantly associated with central obesity by WC criteria (FTO rs9939609: OR = 1.29, 95%CI = 1.10–1.50, p = 0.001; MC4R rs17782313: OR = 1.27, 95%CI = 1.12–1.44, p = 1.32×10−4; GNPDA2 rs10938397: OR = 1.22, 95%CI = 1.09–1.37, p = 4.09×10−4; BDNF rs6265: OR = 1.20, 95%CI = 1.08–1.34, p = 8.86×10−4; GRS: OR = 1.25, 95%CI 1.16–1.34, p = 2.58×10−9) after adjustment for sex, age, pubertal stage, physical activity and family history of obesity. Similar observations were made using weight-to-height ratio (WHtR) criterion. However, other SNPs were not associated with central obesity by WC as well as WHtR criterion.
Our study replicates the statistically significant association of four SNPs (FTO rs9939609, MC4R rs17782313, GNPDA2 rs10938397, BDNF rs6265) with risk of central obesity in the Chinese children.
PMCID: PMC3570414  PMID: 23424664
19.  Replication of Established Common Genetic Variants for Adult BMI and Childhood Obesity in Greek Adolescents: The TEENAGE Study 
Annals of Human Genetics  2013;77(3):268-274.
Multiple genetic loci have been associated with body mass index (BMI) and obesity. The aim of this study was to investigate the effects of established adult BMI and childhood obesity loci in a Greek adolescent cohort. For this purpose, 34 variants were selected for investigation in 707 (55.9% females) adolescents of Greek origin aged 13.42 ± 0.88 years. Cumulative effects of variants were assessed by calculating a genetic risk score (GRS-34) for each subject. Variants at the FTO, TMEM18, FAIM2, RBJ, ZNF608 and QPCTL loci yielded nominal evidence for association with BMI and/or overweight risk (p < 0.05). Variants at TFAP2B and NEGR1 loci showed nominal association (p < 0.05) with BMI and/or overweight risk in males and females respectively. Even though we did not detect any genome-wide significant associations, 27 out of 34 variants yielded directionally consistent effects with those reported by large-scale meta-analyses (binomial sign p = 0.0008). The GRS-34 was associated with both BMI (beta = 0.17 kg/m2/allele; p < 0.001) and overweight risk (OR = 1.09/allele; 95% CI: 1.04–1.16; p = 0.001). In conclusion, we replicate associations of established BMI and childhood obesity variants in a Greek adolescent cohort and confirm directionally consistent effects for most of them.
PMCID: PMC3652032  PMID: 23347264
Obesity; BMI; common genetic variants; adolescents
20.  Analyses of shared genetic factors between asthma and obesity in children 
Epidemiological studies consistently show associations between asthma and obesity. Shared genetics may account for this association.
To identify genetic variants associated with both asthma and obesity.
Based on a literature search, we identified genes from: 1) Genome-wide association studies (GWAS) of Body Mass Index (BMI) (n=17 genes), 2) GWAS of asthma (n=14) and 3) candidate gene studies of BMI and asthma (n=7). We used GWAS data from the Childhood Asthma Management Program (CAMP) to analyze associations between single nucleotide polymorphisms (SNPs) in these genes and asthma (n=359 subjects) and BMI (n=537).
One top BMI GWAS SNP from the literature, rs10938397 near GNPDA2, was associated with both BMI (p=4 × 10−4) and asthma (p=0.03). Of the top asthma GWAS SNPs and the candidate gene SNPs, none was found to be associated with both BMI and asthma. Gene-based analyses that included all available SNPs in each gene found associations (p<0.05) with both phenotypes for several genes: NEGR1, ROBO1, DGKG, FAIM2, FTO and CHST8 among the BMI GWAS genes; ILRL1/IL18R1, DPP10, PDE4D, MYB, PDE10A, IL33 and especially PTPRD among the asthma GWAS genes; and PRKCA among the BMI and asthma candidate genes.
SNPs within several genes showed associations to BMI and asthma at a gene level, but none of these associations were significant after correction for multiple testing. Our analysis of known candidate genes reveals some evidence for shared genetics between asthma and obesity, but other shared genetic determinants are likely to be identified in novel loci.
PMCID: PMC2941152  PMID: 20816195
Association; Asthma; BMI; Children; Genetics; GWAS; Obesity; Polymorphism; SNP
21.  Appetite regulation genes are associated with body mass index in black South African adolescents: a genetic association study 
BMJ Open  2012;2(3):e000873.
Obesity is a complex trait with both environmental and genetic contributors. Genome-wide association studies have identified several variants that are robustly associated with obesity and body mass index (BMI), many of which are found within genes involved in appetite regulation. Currently, genetic association data for obesity are lacking in Africans—a single genome-wide association study and a few replication studies have been published in West Africa, but none have been performed in a South African population.
To assess the association of candidate loci with BMI in black South Africans. The authors focused on single nucleotide polymorphisms (SNPs) in the FTO, LEP, LEPR, MC4R, NPY2R and POMC genes.
A genetic association study.
990 randomly selected individuals from the larger Birth to Twenty cohort (a longitudinal birth cohort study of health and development in Africans).
The authors genotyped 44 SNPs within the six candidate genes that included known BMI-associated SNPs and tagSNPs based on linkage disequilibrium in an African population for FTO, LEP and NPY2R. To assess population substructure, the authors included 18 ancestry informative markers. Weight, height, sex, sex-specific pubertal stage and exact age collected during adolescence (13 years) were used to identify loci that predispose to obesity early in life.
Sex, sex-specific pubertal stage and exact age together explain 14.3% of the variation in log(BMI) at age 13. After adjustment for these factors, four SNPs were individually significantly associated with BMI: FTO rs17817449 (p=0.022), LEP rs10954174 (p=0.0004), LEP rs6966536 (p=0.012) and MC4R rs17782313 (p=0.045). Together the four SNPs account for 2.1% of the variation in log(BMI). Each risk allele was associated with an estimated average increase of 2.5% in BMI.
The study highlighted SNPs in FTO and MC4R as potential genetic markers of obesity risk in South Africans. The association with two SNPs in the 3′ untranslated region of the LEP gene is novel.
Article summary
Article focus
This is a replication study aiming to reproduce BMI association findings from European cohorts in a South African population.
This study focused on genes linked to appetite control that were previously reported to show association with BMI or obesity and included FTO, LEP, LEPR, MC4R, NPY2R and POMC.
Adolescent data were used to facilitate the identification of genetic loci that predispose to obesity early in life, as it is known that overweight/obese children have an elevated risk of becoming obese adults.
Key messages
We found four SNPs were individually significantly associated with BMI: FTO rs17817449 (p=0.022), LEP rs10954174 (p=0.0004), LEP rs6966536 (p=0.012) and MC4R rs17782313 (p=0.045).
Together the four SNPs account for 2.1% of the variation in log(BMI).
We also demonstrated that an accumulation of risk alleles is linked to a significant increase in BMI—individuals with seven risk alleles had an 11.0% increase in median BMI compared with those with two risk alleles.
Strengths and limitations of this study
This study provides the first preliminary evidence of the role of genetic variants in obesity risk in an adolescent black South African population.
This study was only moderately powered to detect association with BMI, and not all genes were exhaustively investigated.
TagSNP selection would have been enhanced if South African data were available for this approach.
PMCID: PMC3358621  PMID: 22614171
22.  Exploring the Developmental Overnutrition Hypothesis Using Parental–Offspring Associations and FTO as an Instrumental Variable 
PLoS Medicine  2008;5(3):e33.
The developmental overnutrition hypothesis suggests that greater maternal obesity during pregnancy results in increased offspring adiposity in later life. If true, this would result in the obesity epidemic progressing across generations irrespective of environmental or genetic changes. It is therefore important to robustly test this hypothesis.
Methods and Findings
We explored this hypothesis by comparing the associations of maternal and paternal pre-pregnancy body mass index (BMI) with offspring dual energy X-ray absorptiometry (DXA)–determined fat mass measured at 9 to 11 y (4,091 parent–offspring trios) and by using maternal FTO genotype, controlling for offspring FTO genotype, as an instrument for maternal adiposity. Both maternal and paternal BMI were positively associated with offspring fat mass, but the maternal association effect size was larger than that in the paternal association in all models: mean difference in offspring sex- and age-standardised fat mass z-score per 1 standard deviation BMI 0.24 (95% confidence interval [CI]: 0.22 to 0.26) for maternal BMI versus 0.13 (95% CI: 0.11, 0.15) for paternal BMI; p-value for difference in effect < 0.001. The stronger maternal association was robust to sensitivity analyses assuming levels of non-paternity up to 20%. When maternal FTO, controlling for offspring FTO, was used as an instrument for the effect of maternal adiposity, the mean difference in offspring fat mass z-score per 1 standard deviation maternal BMI was −0.08 (95% CI: −0.56 to 0.41), with no strong statistical evidence that this differed from the observational ordinary least squares analyses (p = 0.17).
Neither our parental comparisons nor the use of FTO genotype as an instrumental variable, suggest that greater maternal BMI during offspring development has a marked effect on offspring fat mass at age 9–11 y. Developmental overnutrition related to greater maternal BMI is unlikely to have driven the recent obesity epidemic.
Using parental-offspring associations and theFTO gene as an instrumental variable for maternal adiposity, Debbie Lawlor and colleagues found that greater maternal BMI during offspring development does not appear to have a marked effect on offspring fat mass at age 9-11.
Editors' Summary
Since the 1970s, the proportion of children and adults who are overweight or obese (people who have an unhealthy amount of body fat) has increased sharply in many countries. In the US, 1 in 3 adults is now obese; in the mid-1970s it was only 1 in 7. Similarly, the proportion of overweight children has risen from 1 in 20 to 1 in 5. An adult is considered to be overweight if their body mass index (BMI)—their weight in kilograms divided by their height in meters squared—is between 25 and 30, and obese if it is more than 30. For children, the healthy BMI depends on their age and gender. Compared to people with a healthy weight (a BMI between 18.5 and 25), overweight or obese individuals have an increased lifetime risk of developing diabetes and other adverse health conditions, sometimes becoming ill while they are still young. People become unhealthily fat when they consume food and drink that contains more energy than they need for their daily activities. It should, therefore, be possible to avoid becoming obese by having a healthy diet and exercising regularly.
Why Was This Study Done?
Some researchers think that “developmental overnutrition” may have caused the recent increase in waistline measurements. In other words, if a mother is overweight during pregnancy, high sugar and fat levels in her body might permanently affect her growing baby's appetite control and metabolism, and so her offspring might be at risk of becoming obese in later life. If this hypothesis is true, each generation will tend to be fatter than the previous one and it will be very hard to halt the obesity epidemic simply by encouraging people to eat less and exercise more. In this study, the researchers have used two approaches to test the developmental overnutrition hypothesis. First, they have asked whether offspring fat mass is more strongly related to maternal BMI than to paternal BMI; it should be if the hypothesis is true. Second, they have asked whether a genetic indicator of maternal fatness—the “A” variant of the FTO gene—is related to offspring fat mass. A statistical association between maternal FTO genotype (genetic make-up) and offspring fat mass would support the developmental nutrition hypothesis.
What Did the Researchers Do and Find?
In 1991–1992, the Avon Longitudinal Study of Parents and Children (ALSPAC) enrolled about 14,000 pregnant women and now examines their offspring at regular intervals. The researchers first used statistical methods to look for associations between the self-reported prepregnancy BMI of the parents of about 4,000 children and the children's fat mass at ages 9–11 years measured using a technique called dual energy X-ray absorptiometry. Both maternal and paternal BMI were positively associated with offspring fat mass (that is, fatter parents had fatter children) but the effect of maternal BMI was greater than the effect of paternal BMI. When the researchers examined maternal FTO genotypes and offspring fat mass (after allowing for the offspring's FTO genotype, which would directly affect their fat mass), there was no statistical evidence to suggest that differences in offspring fat mass were related to the maternal FTO genotype.
What Do These Findings Mean?
Although the findings from first approach provide some support for the development overnutrition hypothesis, the effect of maternal BMI on offspring fat mass is too weak to explain the recent obesity epidemic. Developmental overnutrition could, however, be responsible for the much slower increase in obesity that began a century ago. The findings from the second approach provide no support for the developmental overnutrition hypothesis, although these results have wide error margins and need confirming in a larger study. The researchers also note that the effects of developmental overnutrition on offspring fat mass, although weak at age 9–11, might become more important at later ages. Nevertheless, for now, it seems unlikely that developmental overnutrition has been a major driver of the recent obesity epidemic. Interventions that aim to improve people's diet and to increase their physical activity levels could therefore slow or even halt the epidemic.
Additional Information.
Please access these Web sites via the online version of this summary at
See a related PLoS Medicine Perspective article
The MedlinePlus encyclopedia has a page on obesity (in English and Spanish)
The US Centers for Disease Control and Prevention provides information on all aspects of obesity (in English and Spanish)
The UK National Health Service's health Web site (NHS Direct) provides information about obesity
The International Obesity Taskforce provides information about preventing obesity and on childhood obesity
The UK Foods Standards Agency, the United States Department of Agriculture, and Shaping America's Health all provide useful advice about healthy eating for adults and children
The ALSPAC Web site provides information about the Avon Longitudinal Study of Parents and Children and its results so far
PMCID: PMC2265763  PMID: 18336062
23.  Genetic Susceptibility to Obesity and Related Traits in Childhood and Adolescence 
Diabetes  2010;59(11):2980-2988.
Large-scale genome-wide association (GWA) studies have thus far identified 16 loci incontrovertibly associated with obesity-related traits in adults. We examined associations of variants in these loci with anthropometric traits in children and adolescents.
Seventeen variants representing 16 obesity susceptibility loci were genotyped in 1,252 children (mean ± SD age 9.7 ± 0.4 years) and 790 adolescents (15.5 ± 0.5 years) from the European Youth Heart Study (EYHS). We tested for association of individual variants and a genetic predisposition score (GPS-17), calculated by summing the number of effect alleles, with anthropometric traits. For 13 variants, summary statistics for associations with BMI were meta-analyzed with previously reported data (Ntotal = 13,071 children and adolescents).
In EYHS, 15 variants showed associations or trends with anthropometric traits that were directionally consistent with earlier reports in adults. The meta-analysis showed directionally consistent associations with BMI for all 13 variants, of which 9 were significant (0.033–0.098 SD/allele; P < 0.05). The near-TMEM18 variant had the strongest effect (0.098 SD/allele P = 8.5 × 10−11). Effect sizes for BMI tended to be more pronounced in children and adolescents than reported earlier in adults for variants in or near SEC16B, TMEM18, and KCTD15, (0.028–0.035 SD/allele higher) and less pronounced for rs925946 in BDNF (0.028 SD/allele lower). Each additional effect allele in the GPS-17 was associated with an increase of 0.034 SD in BMI (P = 3.6 × 10−5), 0.039 SD, in sum of skinfolds (P = 1.7 × 10−7), and 0.022 SD in waist circumference (P = 1.7 × 10−4), which is comparable with reported results in adults (0.039 SD/allele for BMI and 0.033 SD/allele for waist circumference).
Most obesity susceptibility loci identified by GWA studies in adults are already associated with anthropometric traits in children/adolescents. Whereas the association of some variants may differ with age, the cumulative effect size is similar.
PMCID: PMC2963559  PMID: 20724581
24.  Generalization of adiposity genetic loci to US Hispanic women 
Nutrition & Diabetes  2013;3(8):e85-.
Obesity is a public health concern. Yet the identification of adiposity-related genetic variants among United States (US) Hispanics, which is the largest US minority group, remains largely unknown.
To interrogate an a priori list of 47 (32 overall body mass and 15 central adiposity) index single-nucleotide polymorphisms (SNPs) previously studied in individuals of European descent among 3494 US Hispanic women in the Women's Health Initiative SNP Health Association Resource (WHI SHARe).
Cross-sectional analysis of measured body mass index (BMI), waist circumference (WC) and waist-to-hip ratio (WHR) were inverse normally transformed after adjusting for age, smoking, center and global ancestry. WC and WHR models were also adjusted for BMI. Genotyping was performed using the Affymetrix 6.0 array. In the absence of an a priori selected SNP, a proxy was selected (r2⩾0.8 in CEU).
Six BMI loci (TMEM18, NUDT3/HMGA1, FAIM2, FTO, MC4R and KCTD15) and two WC/WHR loci (VEGFA and ITPR2-SSPN) were nominally significant (P<0.05) at the index or proxy SNP in the corresponding BMI and WC/WHR models. To account for distinct linkage disequilibrium patterns in Hispanics and further assess generalization of genetic effects at each locus, we interrogated the evidence for association at the 47 surrounding loci within 1 Mb region of the index or proxy SNP. Three additional BMI loci (FANCL, TFAP2B and ETV5) and five WC/WHR loci (DNM3-PIGC, GRB14, ADAMTS9, LY86 and MSRA) displayed Bonferroni-corrected significant associations with BMI and WC/WHR. Conditional analyses of each index SNP (or its proxy) and the most significant SNP within the 1 Mb region supported the possible presence of index-independent signals at each of these eight loci as well as at KCTD15.
This study provides evidence for the generalization of nine BMI and seven central adiposity loci in Hispanic women. This study expands the current knowledge of common adiposity-related genetic loci to Hispanic women.
PMCID: PMC3759132  PMID: 23978819
obesity; Hispanic; women; genetics; generalization
25.  Analysis of the contribution of FTO, NPC1, ENPP1, NEGR1, GNPDA2 and MC4R genes to obesity in Mexican children 
BMC Medical Genetics  2013;14:21.
Recent genome wide association studies (GWAS) and previous positional linkage studies have identified more than 50 single nucleotide polymorphisms (SNPs) associated with obesity, mostly in Europeans. We aimed to assess the contribution of some of these SNPs to obesity risk and to the variation of related metabolic traits, in Mexican children.
The association of six European obesity-related SNPs in or near FTO, NPC1, ENPP1, NEGR1, GNPDA2 and MC4R genes with risk of obesity was tested in 1,463 school-aged Mexican children (Ncases = 514; Ncontrols = 949). We also assessed effects of these SNPs on the variation of body mass index (BMI), fasting serum insulin levels, fasting plasma glucose levels, total cholesterol and triglyceride levels, in a subset of 1,171 nonobese Mexican children.
We found a significant effect of GNPDA2 rs10938397 on risk of obesity (odds ratio [OR] = 1.30; P = 1.34 × 10-3). Furthermore, we found nominal associations between obesity risk or BMI variation and the following SNPs: ENPP1 rs7754561, MC4R rs17782313 and NEGR1 rs2815752. Importantly, the at-risk alleles of both MC4R rs17782313 and NPC1 rs1805081 showed significant effect on increased fasting glucose levels (β = 0.36 mmol/L; P = 1.47 × 10-3) and decreased fasting serum insulin levels (β = −0.10 μU/mL; P = 1.21 × 10-3), respectively.
Our present results suggest that some obesity-associated SNPs previously reported in Europeans also associate with risk of obesity, or metabolic quantitative traits, in Mexican children. Importantly, we found new associations between MC4R and fasting glucose levels, and between NPC1 and fasting insulin levels.
PMCID: PMC3577489  PMID: 23375129
Obesity; Mexican children; Single nucleotide polymorphism

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