1 Nature Reviews Genetics 2009 Vol: 10(7):431-442. DOI: 10.1038/nrg2594

The genetic contribution to non-syndromic human obesity

The last few years have seen major advances in common non-syndromic obesity research, much of it the result of genetic studies. This Review outlines the competing hypotheses about the mechanisms underlying the genetic and physiological basis of obesity, and then examines the recent explosion of genetic association studies that have yielded insights into obesity, both at the candidate gene level and the genome-wide level. With obesity genetics now entering the post-genome-wide association scan era, the obvious question is how to improve the results obtained so far using single nucleotide polymorphism markers and how to move successfully into the other areas of genomic variation that may be associated with common obesity.

Mentions
Figures
Figure 1: The leptin–melanocortin pathway.The central nervous system plays a primary part in regulating food intake through the brain–gut axis143, with the hypothalamus acting as the central regulator, receiving both long- and short-term food intake and energy expenditure feedback from the periphery. Signals are received from several tissues and organs, including: the gut, by hormones, such as ghrelin, peptide YY and cholecystokinin (CCK), and by mechanoreceptors measuring distension; and the pancreas, for example, through insulin and adipose tissue, and by hormones such as leptin and adiponectin144, 145. The hypothalamus integrates these signals and acts through various downstream pathways to maintain energy balance. Although this system is well suited to preventing weight loss in times of starvation, it is rather less efficient at preventing weight gain. The rise in leptin levels that accompanies increasing adiposity has only a limited effect on food intake owing to cellular resistance to leptin, which may have evolved as a mechanism of preventing starvation146. The melanocortin 4 receptor (MC4R) is highly expressed in the paraventricular nucleus (PVN) of the hypothalamus, where it has a key role in the control of appetite. Leptin released from adipose tissue binds to leptin receptors (LEPR) on agouti-related protein (AGRP)-producing neurons and proopionomelanocortin (POMC)-producing neurons in the arcuate nucleus (ARC) of the hypothalamus. Leptin binding inhibits AGRP production and stimulates the production of POMC, which undergoes post-translational modification to generate a range of peptides, including -, - and -melanocyte-stimulating hormone (MSH). AGRP and -MSH compete for MC4R — AGRP binding suppresses MC4R activity and -MSH binding stimulates MC4R activity. Decreased receptor activity generates an orexigenic signal, whereas increased receptor activity generates an anorexigenic signal. Signals from MC4R govern food intake through secondary effector neurons that lead to higher cortical centres, a process that involves brain-derived neurotrophic factor (BDNF) and neurotrophic tyrosine kinase receptor type 2 (NTRK2; also known as tropomyosin-related kinase B, TRKB). Figure 2: Odds ratios for genes associated with obesity in genome-wide studies.Odds ratios from genome-wide scans are shown for the closest gene to the associated SNP marker44, 74, 77, 94, 100, 104. BCDIN3D, BCDIN3 domain containing; BDNF, brain-derived neurotrophic factor; CTNNBL1, catenin, beta-like 1; ETV5, ets variant gene 5; FTO, fat mass and obesity associated; GNPDA2, glucosamine-6-phosphate deaminase 2; KCTD15, potassium channel tetramerization domain containing 15; MAF, v-maf musculoaponeurotic fibrosarcoma oncogene homologue; MC4R, melanocortin 4 receptor; MTCH2, mitochondrial carrier homologue 2; NEGR1, neuronal growth regulator 1; NPC1, Niemann–Pick disease type C1; PRL, prolactin; PTER, phosphotriesterase related; SEC16B, SEC16 homologue B; SH2B1, SH2B adaptor protein 1; TMEM18, transmembrane protein 18.
Altmetric
References
  1. Wang, Y., Beydoun, M. A., Liang, L., Caballero, B. & Kumanyika, S. K. Will all Americans become overweight or obese? Estimating the progression and cost of the US obesity epidemic. Obesity (Silver Spring) 16, 2323-2330 , (2008) .
    • . . . If current trends continue, over 50% of adults in the United States will be clinically obese by 2030 (Ref. 1), with global projections of 1.12 billion obese individuals by 2030 (Ref. 2) . . .
  2. Kelly, T., Yang, W., Chen, C. S., Reynolds, K. & He, J. Global burden of obesity in 2005 and projections to 2030. Int. J. Obes. (Lond.) 32, 1431-1437 , (2008) .
    • . . . If current trends continue, over 50% of adults in the United States will be clinically obese by 2030 (Ref. 1), with global projections of 1.12 billion obese individuals by 2030 (Ref. 2) . . .
  3. Sturm, R. Increases in morbid obesity in the USA: 2000-2005. Public Health 121, 492-496 , (2007) .
    • . . . Although the prevalence of obesity increased by 24% between 2000 and 2005, extreme obesity (body mass index (BMI) 40) increased by more than 50%, with a growth of 75% seen in the super-obese (BMI 50)3 . . .
  4. Ogden, C. L. et al. Prevalence of overweight and obesity in the United States, 1999-2004. JAMA 295, 1549-1555 , (2006) .
    • . . . The growth in obesity among adults has been paralleled by increases in obesity among children. 17% of children in the United States are considered obese (sex-specific BMI ninety-fifth percentile for age)4, which is projected to rise to 30% by 2030 (Ref. 1) . . .
  5. Sturm, R. The effects of obesity, smoking, and drinking on medical problems and costs. Health Aff. (Millwood) 21, 245-253 , (2002) .
    • . . . Obesity is a major contributor to morbidity and mortality worldwide, surpassing smoking and drinking in its negative effects on health5, which will negatively affect life expectancy of generations born after the rise of the obesity epidemic. . . .
  6. Stunkard, A. J., Foch, T. T. & Hrubec, Z. A twin study of human obesity. JAMA 256, 51-54.The first twin study of obesity that reported the substantial role of genetics , (1986) .
    • . . . Stunkard's seminal studies6, 7 gave a heritability estimate of 0.78 for weight, increasing to 0.81 in a 25-year follow-up study . . .
  7. Stunkard, A. J. et al. An adoption study of human obesity. N. Engl. J. Med. 314, 193-198 , (1986) .
    • . . . Stunkard's seminal studies6, 7 gave a heritability estimate of 0.78 for weight, increasing to 0.81 in a 25-year follow-up study . . .
  8. Turula, M., Kaprio, J., Rissanen, A. & Koskenvuo, M. Body weight in the Finnish Twin Cohort. Diabetes Res. Clin. Pract. 10 (Suppl. 1), S33-S36 , (1990) .
    • . . . Further twin studies have revealed heritability estimates of 0.7 for BMI in both adults and children8, 9 . . .
  9. Wardle, J., Carnell, S., Haworth, C. M. & Plomin, R. Evidence for a strong genetic influence on childhood adiposity despite the force of the obesogenic environment. Am. J. Clin. Nutr. 87, 398-404.A twin study showing that, even in an obesogenic environment, genetics has a significant effect on obesity , (2008) .
    • . . . Further twin studies have revealed heritability estimates of 0.7 for BMI in both adults and children8, 9 . . .
  10. Redden, D. T. et al. Regional admixture mapping and structured association testing: conceptual unification and an extensible general linear model. PLoS Genet. 2, e137 , (2006) .
    • . . . In addition, admixture mapping has shown that obesity correlates closely with the percentage of ancestry deriving from ethnic groups with an elevated prevalence of obesity10, 11 . . .
  11. Williams, R. C., Long, J. C., Hanson, R. L., Sievers, M. L. & Knowler, W. C. Individual estimates of European genetic admixture associated with lower body-mass index, plasma glucose, and prevalence of type 2 diabetes in Pima Indians. Am. J. Hum. Genet. 66, 527-538 , (2000) .
    • . . . In addition, admixture mapping has shown that obesity correlates closely with the percentage of ancestry deriving from ethnic groups with an elevated prevalence of obesity10, 11 . . .
  12. Sivitz, W. I., Fink, B. D. & Donohoue, P. A. Fasting and leptin modulate adipose and muscle uncoupling protein: divergent effects between messenger ribonucleic acid and protein expression. Endocrinology 140, 1511-1519 , (1999) .
    • . . . Higher leptin levels in the rodent hypothalamus reverse the decrease in UCP1 mRNA expression observed in the fasting state12 and lead to increased sympathetic activation of BAT13 . . .
  13. Rahmouni, K. & Morgan, D. A. Hypothalamic arcuate nucleus mediates the sympathetic and arterial pressure responses to leptin. Hypertension 49, 647-652 , (2007) .
    • . . . Higher leptin levels in the rodent hypothalamus reverse the decrease in UCP1 mRNA expression observed in the fasting state12 and lead to increased sympathetic activation of BAT13 . . .
  14. Lowell, B. B. et al. Development of obesity in transgenic mice after genetic ablation of brown adipose tissue. Nature 366, 740-742.The first report to show that loss of BAT in transgenic mice leads to obesity , (1993) .
    • . . . The loss of BAT function in rodents is linked to metabolic dysfunction and obesity14, whereas experimentally induced BAT hypertrophy results in a lean, healthy phenotype15 . . .
  15. Ghorbani, M., Claus, T. H. & Himms-Hagen, J. Hypertrophy of brown adipocytes in brown and white adipose tissues and reversal of diet-induced obesity in rats treated with a 3-adrenoceptor agonist. Biochem. Pharmacol. 54, 121-131 , (1997) .
    • . . . The loss of BAT function in rodents is linked to metabolic dysfunction and obesity14, whereas experimentally induced BAT hypertrophy results in a lean, healthy phenotype15 . . .
  16. Nedergaard, J., Bengtsson, T. & Cannon, B. Unexpected evidence for active brown adipose tissue in adult humans. Am. J. Physiol. Endocrinol. Metab. 293, E444-E452 , (2007) .
    • . . . Until recently, BAT was not thought to have a major metabolic role in adult humans but there is now strong evidence of metabolically active BAT depots in adults16, 17, 18, 19 . . .
  17. van Marken Lichtenbelt, W. D. et al. Cold-activated brown adipose tissue in healthy men. N. Engl. J. Med. 360, 1500-1508 , (2009) .
    • . . . Until recently, BAT was not thought to have a major metabolic role in adult humans but there is now strong evidence of metabolically active BAT depots in adults16, 17, 18, 19 . . .
  18. Cypess, A. M. et al. Identification and importance of brown adipose tissue in adult humans. N. Engl. J. Med. 360, 1509-1517 , (2009) .
    • . . . Until recently, BAT was not thought to have a major metabolic role in adult humans but there is now strong evidence of metabolically active BAT depots in adults16, 17, 18, 19 . . .
  19. Virtanen, K. A. et al. Functional brown adipose tissue in healthy adults. N. Engl. J. Med. 360, 1518-1525 , (2009) .
    • . . . Until recently, BAT was not thought to have a major metabolic role in adult humans but there is now strong evidence of metabolically active BAT depots in adults16, 17, 18, 19 . . .
  20. Ozata, M., Ozdemir, I. C. & Licinio, J. Human leptin deficiency caused by a missense mutation: multiple endocrine defects, decreased sympathetic tone, and immune system dysfunction indicate new targets for leptin action, greater central than peripheral resistance to the effects of leptin, and spontaneous correction of leptin-mediated defects. J. Clin. Endocrinol. Metab. 84, 3686-3695 , (1999) .
    • . . . In addition, abnormalities of the sympathetic nervous system that are consistent with defects in the sympathetic afferent branch of thermogenesis have been observed in leptin-deficient adults20 . . .
  21. Henry, B. A., Dunshea, F. R., Gould, M. & Clarke, I. J. Profiling postprandial thermogenesis in muscle and fat of sheep and the central effect of leptin administration. Endocrinology 149, 2019-2026 , (2008) .
    • . . . The central administration of leptin has also been found to increase postprandial thermogenesis in sheep — like humans, sheep have brown adipocytes dispersed through white adipose tissue rather than the circumscribed BAT depots found in rodents21 . . .
  22. Seale, P. et al. PRDM16 controls a brown fat/skeletal muscle switch. Nature 454, 961-967 , (2008) .
    • . . . These findings, and recent discoveries elucidating the developmental pathways involved in BAT formation and differentiation, notably the roles of PR domain zinc finger protein 16 (PRDM16)22 and bone morphogenetic protein 7 (BMP7)23, emphasize that the role of BAT in human obesity may be significant. . . .
  23. Tseng, Y. H. et al. New role of bone morphogenetic protein 7 in brown adipogenesis and energy expenditure. Nature 454, 1000-1004 , (2008) .
    • . . . These findings, and recent discoveries elucidating the developmental pathways involved in BAT formation and differentiation, notably the roles of PR domain zinc finger protein 16 (PRDM16)22 and bone morphogenetic protein 7 (BMP7)23, emphasize that the role of BAT in human obesity may be significant. . . .
  24. Spalding, K. L. et al. Dynamics of fat cell turnover in humans. Nature 453, 783-787 , (2008) .
    • . . . A seminal study24 showed that fat mass in humans is determined by both adipocyte size and number, with larger populations of larger adipocytes in obese people . . .
  25. Freedman, D. S. et al. Childhood overweight and family income. MedGenMed 9, 26 , (2007) .
    • . . . One of the long-standing open questions in obesity research has been why over 75% of obese children go on to become obese adults, whereas only 10% of normal weight children become obese adults25 . . .
  26. Lofgren, P. et al. Long-term prospective and controlled studies demonstrate adipose tissue hypercellularity and relative leptin deficiency in the postobese state. J. Clin. Endocrinol. Metab. 90, 6207-6213 , (2005) .
    • . . . Studies of previously obese individuals who have lost weight have shown an association between adipose tissue hypercellularity and leptin deficiency26, which is likely to promote lipid accumulation in fat cells through increased appetite and lower energy expenditure. . . .
  27. O'Rahilly, S. & Farooqi, I. S. Human obesity: a heritable neurobehavioral disorder that is highly sensitive to environmental conditions. Diabetes 57, 2905-2910 , (2008) .
    • . . . But another view has recently emerged of obesity as a neurobehavioural disorder27, with defects in the neurological control of appetite and food intake playing a central part in pathogenesis . . .
  28. Zhang, Y. et al. Positional cloning of the mouse obese gene and its human homologue. Nature 372, 425-432.The paper that identified the first gene underlying obesity and that brought obesity research into the modern age , (1994) .
    • . . . After the identification of the leptin gene in mice and then in humans28, leptin deficiency was the first cause of monogenic obesity to be demonstrated in a human patient29 . . .
  29. Montague, C. T. et al. Congenital leptin deficiency is associated with severe early-onset obesity in humans. Nature 387, 903-908.The first reported evidence that monogenic obesity exists in humans , (1997) .
    • . . . After the identification of the leptin gene in mice and then in humans28, leptin deficiency was the first cause of monogenic obesity to be demonstrated in a human patient29 . . .
  30. Clement, K. et al. A mutation in the human leptin receptor gene causes obesity and pituitary dysfunction. Nature 392, 398-401 , (1998) .
    • . . . Examination of cases of severe early-onset obesity have continued to provide information on obesity genes, leading to the identification of variants in additional genes in the leptin–melanocortin pathway, including leptin receptor (LEPR)30, proopiomelanocortin (POMC)31, pro-hormone convertase subtilisin/kexin type 1 (PCSK1)32 and MC4R33, 34 . . .
  31. Krude, H. et al. Severe early-onset obesity, adrenal insufficiency and red hair pigmentation caused by POMC mutations in humans. Nature Genet. 19, 155-157 , (1998) .
    • . . . Examination of cases of severe early-onset obesity have continued to provide information on obesity genes, leading to the identification of variants in additional genes in the leptin–melanocortin pathway, including leptin receptor (LEPR)30, proopiomelanocortin (POMC)31, pro-hormone convertase subtilisin/kexin type 1 (PCSK1)32 and MC4R33, 34 . . .
  32. Jackson, R. S. et al. Obesity and impaired prohormone processing associated with mutations in the human prohormone convertase 1 gene. Nature Genet. 16, 303-306 , (1997) .
    • . . . Examination of cases of severe early-onset obesity have continued to provide information on obesity genes, leading to the identification of variants in additional genes in the leptin–melanocortin pathway, including leptin receptor (LEPR)30, proopiomelanocortin (POMC)31, pro-hormone convertase subtilisin/kexin type 1 (PCSK1)32 and MC4R33, 34 . . .
  33. Vaisse, C., Clement, K., Guy-Grand, B. & Froguel, P. A frameshift mutation in human MC4R is associated with a dominant form of obesity. Nature Genet. 20, 113-4.This paper, together with reference 34, first identified MC4R gene variants as the most prevalent form of monogenic human obesity , (1998) .
    • . . . Examination of cases of severe early-onset obesity have continued to provide information on obesity genes, leading to the identification of variants in additional genes in the leptin–melanocortin pathway, including leptin receptor (LEPR)30, proopiomelanocortin (POMC)31, pro-hormone convertase subtilisin/kexin type 1 (PCSK1)32 and MC4R33, 34 . . .
  34. Yeo, G. S. et al. A frameshift mutation in MC4R associated with dominantly inherited human obesity. Nature Genet. 20, 111-112 , (1998) .
    • . . . Examination of cases of severe early-onset obesity have continued to provide information on obesity genes, leading to the identification of variants in additional genes in the leptin–melanocortin pathway, including leptin receptor (LEPR)30, proopiomelanocortin (POMC)31, pro-hormone convertase subtilisin/kexin type 1 (PCSK1)32 and MC4R33, 34 . . .
  35. Holder, J. L. Jr, Butte, N. F. & Zinn, A. R. Profound obesity associated with a balanced translocation that disrupts the SIM1 gene. Hum. Mol. Genet. 9, 101-108 , (2000) .
    • . . . Mutations in three genes also involved in neural development have now been identified as the underlying cause of rare monogenic obesity: single-minded homologue 1 (SIM1)35, BDNF36 and neurotrophic tyrosine kinase receptor type 2 (NTRK2; also known as tropomyosin-related kinase B, TRKB)37 . . .
  36. Friedel, S. et al. Mutation screen of the brain derived neurotrophic factor gene (BDNF): identification of several genetic variants and association studies in patients with obesity, eating disorders, and attention-deficit/hyperactivity disorder. Am. J. Med. Genet. B Neuropsychiatr. Genet. 132B, 196-199 , (2005) .
    • . . . Mutations in three genes also involved in neural development have now been identified as the underlying cause of rare monogenic obesity: single-minded homologue 1 (SIM1)35, BDNF36 and neurotrophic tyrosine kinase receptor type 2 (NTRK2; also known as tropomyosin-related kinase B, TRKB)37 . . .
  37. Yeo, G. S. et al. A de novo mutation affecting human TrkB associated with severe obesity and developmental delay. Nature Neurosci. 7, 1187-1189 , (2004) .
    • . . . Mutations in three genes also involved in neural development have now been identified as the underlying cause of rare monogenic obesity: single-minded homologue 1 (SIM1)35, BDNF36 and neurotrophic tyrosine kinase receptor type 2 (NTRK2; also known as tropomyosin-related kinase B, TRKB)37 . . .
  38. Rankinen, T. et al. The human obesity gene map: the 2005 update. Obesity (Silver Spring) 14, 529-644 , (2006) .
    • . . . For obesity, more than 60 genome scans have been performed, resulting in the identification of 250 QTLs by 2006 (Ref. 38) . . .
  39. Boutin, P. et al. GAD2 on chromosome 10p12 is a candidate gene for human obesity. PLoS Biol. 1, E68 , (2003) .
    • . . . Positional cloning based on linkage results has identified promising candidate genes, including glutamate decarboxylase 2 (GAD2)39, ectonucleotide pyrophosphatase/phosphodiesterase 1 (ENPP1)40 and solute carrier family 6 (amino acid transporter), member 14 (SLC6A14)41, 42 . . .
  40. Meyre, D. et al. Variants of ENPP1 are associated with childhood and adult obesity and increase the risk of glucose intolerance and type 2 diabetes. Nature Genet. 37, 863-867 , (2005) .
    • . . . Positional cloning based on linkage results has identified promising candidate genes, including glutamate decarboxylase 2 (GAD2)39, ectonucleotide pyrophosphatase/phosphodiesterase 1 (ENPP1)40 and solute carrier family 6 (amino acid transporter), member 14 (SLC6A14)41, 42 . . .
  41. Suviolahti, E. et al. The SLC6A14 gene shows evidence of association with obesity. J. Clin. Invest. 112, 1762-72 , (2003) .
    • . . . Positional cloning based on linkage results has identified promising candidate genes, including glutamate decarboxylase 2 (GAD2)39, ectonucleotide pyrophosphatase/phosphodiesterase 1 (ENPP1)40 and solute carrier family 6 (amino acid transporter), member 14 (SLC6A14)41, 42 . . .
  42. Durand, E. et al. Polymorphisms in the amino acid transporter solute carrier family 6 (neurotransmitter transporter) member 14 gene contribute to polygenic obesity in French Caucasians. Diabetes 53, 2483-2486 , (2004) .
    • . . . Positional cloning based on linkage results has identified promising candidate genes, including glutamate decarboxylase 2 (GAD2)39, ectonucleotide pyrophosphatase/phosphodiesterase 1 (ENPP1)40 and solute carrier family 6 (amino acid transporter), member 14 (SLC6A14)41, 42 . . .
  43. Saunders, C. L. et al. Meta-analysis of genome-wide linkage studies in BMI and obesity. Obesity (Silver Spring) 15, 2263-2275 , (2007) .
    • . . . A recent meta-analysis of 37 published studies43 containing more than 31,000 individuals did not detect strong evidence for linkage for BMI or BMI-defined obesity at any locus . . .
  44. Frayling, T. M. et al. A common variant in the FTO gene is associated with body mass index and predisposes to childhood and adult obesity. Science 316, 889-894.The first obesity gene identified through a GWA study, although the study was for type 2 diabetes rather than obesity , (2007) .
  45. Bell, C. G., Walley, A. J. & Froguel, P. The genetics of human obesity. Nature Rev. Genet. 6, 221-34 , (2005) .
    • . . . Table 1 lists candidate genes reported in the period since our last Review in 2005 (Ref. 45). . . .
    • . . . Table 2 provides details of the main findings of the GWA work in obesity published so far, and it is immediately obvious that this approach has identified a group of genes that barely overlap with the candidate genes listed in Table 1 and in our previous Review45 . . .
  46. Jiang, Y. et al. Common variants in the 5' region of the leptin gene are associated with body mass index in men from the National Heart, Lung, and Blood Institute Family Heart Study. Am. J. Hum. Genet. 75, 220-230 , (2004) .
    • . . . Indeed, non-synonymous variants of LEP and LEPR have been associated with adult obesity46, 47, 48, with LEPR also implicated in extreme childhood obesity49 . . .
  47. Li, W. D. et al. Sequence variants in the 5' flanking region of the leptin gene are associated with obesity in women. Ann. Hum. Genet. 63, 227-234 , (1999) .
    • . . . Indeed, non-synonymous variants of LEP and LEPR have been associated with adult obesity46, 47, 48, with LEPR also implicated in extreme childhood obesity49 . . .
  48. Chagnon, Y. C. et al. Associations between the leptin receptor gene and adiposity in middle-aged Caucasian males from the HERITAGE family study. J. Clin. Endocrinol. Metab. 85, 29-34 , (2000) .
    • . . . Indeed, non-synonymous variants of LEP and LEPR have been associated with adult obesity46, 47, 48, with LEPR also implicated in extreme childhood obesity49 . . .
  49. Roth, H. et al. Transmission disequilibrium and sequence variants at the leptin receptor gene in extremely obese German children and adolescents. Hum. Genet. 103, 540-546 , (1998) .
    • . . . Indeed, non-synonymous variants of LEP and LEPR have been associated with adult obesity46, 47, 48, with LEPR also implicated in extreme childhood obesity49 . . .
  50. Mizuta, E. et al. Leptin gene and leptin receptor gene polymorphisms are associated with sweet preference and obesity. Hypertens. Res. 31, 1069-1077 , (2008) .
    • . . . More recently, polymorphisms in LEP and LEPR have been shown to be associated with sweet preference, suggesting an additional role for leptin signalling in obesity by regulating intake of sweet, typically calorie-rich foods50 . . .
  51. Challis, B. G. et al. A missense mutation disrupting a dibasic prohormone processing site in pro-opiomelanocortin (POMC) increases susceptibility to early-onset obesity through a novel molecular mechanism. Hum. Mol. Genet. 11, 1997-2004 , (2002) .
    • . . . A missense mutation disrupting POMC function was reported to increase susceptibility to early-onset obesity in several populations51, and common non-synonymous coding variants in PCSK1 have been associated with obesity in both adults and children52, 53 . . .
  52. Benzinou, M. et al. Common nonsynonymous variants in PCSK1 confer risk of obesity. Nature Genet. 40, 943-945 , (2008) .
    • . . . A missense mutation disrupting POMC function was reported to increase susceptibility to early-onset obesity in several populations51, and common non-synonymous coding variants in PCSK1 have been associated with obesity in both adults and children52, 53 . . .
  53. Hinney, A. et al. Genome wide association (GWA) study for early onset extreme obesity supports the role of fat mass and obesity associated gene (FTO) variants. PLoS ONE 2, e1361.The first GWA study to specifically recruit obese subjects , (2007) .
    • . . . A missense mutation disrupting POMC function was reported to increase susceptibility to early-onset obesity in several populations51, and common non-synonymous coding variants in PCSK1 have been associated with obesity in both adults and children52, 53 . . .
    • . . . The first case–control GWA study using current-generation SNP microarrays and obese probands was published in late 2007 (Ref. 53) . . .
  54. Dubern, B. et al. Mutational analysis of melanocortin-4 receptor, agouti-related protein, and alpha-melanocyte-stimulating hormone genes in severely obese children. J. Pediatr. 139, 204-209 , (2001) .
    • . . . Mutations in the MC4R gene resulting in amino acid substitutions that lead to loss of protein function typically cause monogenic obesity, but with variable penetrance54 . . .
  55. Geller, F. et al. Melanocortin-4 receptor gene variant I103 is negatively associated with obesity. Am. J. Hum. Genet. 74, 572-581 , (2004) .
    • . . . By contrast, the infrequent gain-of-function mutations V103I and I251L (found in 0.5% to 2% of the population) have been consistently associated with a protective effect against obesity55, 56, 57. . . .
  56. Heid, I. M. et al. Association of the 103I MC104R allele with decreased body mass in 7937 participants of two population based surveys. J. Med. Genet. 42, e21 , (2005) .
    • . . . By contrast, the infrequent gain-of-function mutations V103I and I251L (found in 0.5% to 2% of the population) have been consistently associated with a protective effect against obesity55, 56, 57. . . .
  57. Stutzmann, F. et al. Non-synonymous polymorphisms in melanocortin-4 receptor protect against obesity: the two facets of a Janus obesity gene. Hum. Mol. Genet. 16, 1837-1844 , (2007) .
    • . . . By contrast, the infrequent gain-of-function mutations V103I and I251L (found in 0.5% to 2% of the population) have been consistently associated with a protective effect against obesity55, 56, 57. . . .
  58. Bouatia-Naji, N. et al. ACDC/adiponectin polymorphisms are associated with severe childhood and adult obesity. Diabetes 55, 545-550 , (2006) .
    • . . . The common SNP -11391G>A, which is located in the proximal promoter of the adiponectin gene (ADIPOQ) and increases ADIPOQ expression (and adiponectin levels), has been associated with severe childhood and adult obesity in French Caucasians58 and with adult obesity in other populations59, 60, 61 . . .
  59. Nakatani, K. et al. Adiponectin gene variation associates with the increasing risk of type 2 diabetes in non-diabetic Japanese subjects. Int. J. Mol. Med. 15, 173-177 , (2005) .
    • . . . The common SNP -11391G>A, which is located in the proximal promoter of the adiponectin gene (ADIPOQ) and increases ADIPOQ expression (and adiponectin levels), has been associated with severe childhood and adult obesity in French Caucasians58 and with adult obesity in other populations59, 60, 61 . . .
  60. Sutton, B. S. et al. Genetic analysis of adiponectin and obesity in Hispanic families: the IRAS Family Study. Hum. Genet. 117, 107-118 , (2005) .
    • . . . The common SNP -11391G>A, which is located in the proximal promoter of the adiponectin gene (ADIPOQ) and increases ADIPOQ expression (and adiponectin levels), has been associated with severe childhood and adult obesity in French Caucasians58 and with adult obesity in other populations59, 60, 61 . . .
  61. Vimaleswaran, K. S. et al. A novel association of a polymorphism in the first intron of adiponectin gene with type 2 diabetes, obesity and hypoadiponectinemia in Asian Indians. Hum. Genet. 123, 599-605 , (2008) .
    • . . . The common SNP -11391G>A, which is located in the proximal promoter of the adiponectin gene (ADIPOQ) and increases ADIPOQ expression (and adiponectin levels), has been associated with severe childhood and adult obesity in French Caucasians58 and with adult obesity in other populations59, 60, 61 . . .
  62. Benzinou, M. et al. Endocannabinoid receptor 1 gene variations increase risk for obesity and modulate body mass index in European populations. Hum. Mol. Genet. 17, 1916-1921 , (2008) .
    • . . . The discovery of associations between obesity and genes encoding cannabinoid receptor 1 (CNR1)62, dopamine receptor 2 (DRD2)63, 64 and serotonin receptor 2C (HTR2C)65, 66 underscores the importance of neural signalling and the pathogenesis of obesity . . .
  63. Thomas, G. N., Tomlinson, B. & Critchley, J. A. Modulation of blood pressure and obesity with the dopamine D2 receptor gene Taq I polymorphism. Hypertension 36, 177-182 , (2000) .
    • . . . The discovery of associations between obesity and genes encoding cannabinoid receptor 1 (CNR1)62, dopamine receptor 2 (DRD2)63, 64 and serotonin receptor 2C (HTR2C)65, 66 underscores the importance of neural signalling and the pathogenesis of obesity . . .
  64. Epstein, L. H. et al. Food reinforcement, the dopamine D2 receptor genotype, and energy intake in obese and nonobese humans. Behav. Neurosci. 121, 877-886 , (2007) .
    • . . . The discovery of associations between obesity and genes encoding cannabinoid receptor 1 (CNR1)62, dopamine receptor 2 (DRD2)63, 64 and serotonin receptor 2C (HTR2C)65, 66 underscores the importance of neural signalling and the pathogenesis of obesity . . .
  65. McCarthy, S. et al. Complex HTR2C linkage disequilibrium and promoter associations with body mass index and serum leptin. Hum. Genet. 117, 545-557 , (2005) .
    • . . . The discovery of associations between obesity and genes encoding cannabinoid receptor 1 (CNR1)62, dopamine receptor 2 (DRD2)63, 64 and serotonin receptor 2C (HTR2C)65, 66 underscores the importance of neural signalling and the pathogenesis of obesity . . .
  66. Pooley, E. C. et al. A 5-HT2C receptor promoter polymorphism (HTR2C - 759C/T) is associated with obesity in women, and with resistance to weight loss in heterozygotes. Am. J. Med. Genet. B Neuropsychiatr. Genet. 126B, 124-127 , (2004) .
    • . . . The discovery of associations between obesity and genes encoding cannabinoid receptor 1 (CNR1)62, dopamine receptor 2 (DRD2)63, 64 and serotonin receptor 2C (HTR2C)65, 66 underscores the importance of neural signalling and the pathogenesis of obesity . . .
  67. Fuemmeler, B. F. et al. Genes implicated in serotonergic and dopaminergic functioning predict BMI categories. Obesity (Silver Spring) 16, 348-355 , (2008) .
    • . . . Genes involved in regulating serotonin function (SLC6A4) and monoamine levels (MAOA) have also been shown to be predictive of BMI67. . . .
  68. Heo, M. et al. A meta-analytic investigation of linkage and association of common leptin receptor (LEPR) polymorphisms with body mass index and waist circumference. Int. J. Obes. Relat. Metab. Disord. 26, 640-646 , (2002) .
    • . . . For example, a meta-analysis of LEPR studies failed to find association between variants in this gene and obesity68 . . .
  69. The International HapMap Consortium. The International HapMap Project. Nature 426, 789-796.The original description of the project to map the human variation that underpins much of the current human genetic studies , (2003) .
    • . . . The foundation of the GWA study is the HapMap69, an international project aimed at defining the range of common genetic variation in the human genome . . .
  70. The International HapMap Consortium. A haplotype map of the human genome. Nature 437, 1299-1320 , (2005) .
    • . . . By utilizing HapMap information on SNPs and linkage disequilibrium patterns70, 71, companies such as Illumina and Affymetrix have developed array-based platforms for the large-scale analysis of hundreds of thousands of SNPs in thousands of subjects, making GWA studies possible (see Ref. 72 for a review). . . .
  71. The International HapMap Consortium. A second generation human haplotype map of over 3.1 million SNPs. Nature 449, 851-861 , (2007) .
    • . . . By utilizing HapMap information on SNPs and linkage disequilibrium patterns70, 71, companies such as Illumina and Affymetrix have developed array-based platforms for the large-scale analysis of hundreds of thousands of SNPs in thousands of subjects, making GWA studies possible (see Ref. 72 for a review). . . .
  72. McCarthy, M. I. et al. Genome-wide association studies for complex traits: consensus, uncertainty and challenges. Nature Rev. Genet. 9, 356-369 , (2008) .
    • . . . By utilizing HapMap information on SNPs and linkage disequilibrium patterns70, 71, companies such as Illumina and Affymetrix have developed array-based platforms for the large-scale analysis of hundreds of thousands of SNPs in thousands of subjects, making GWA studies possible (see Ref. 72 for a review). . . .
    • . . . There is good guidance available on the design of genetic studies110, 111, and the limitations of current GWA study designs are well known72, 112 . . .
  73. Iyengar, S. K. & Elston, R. C. The genetic basis of complex traits: rare variants or "common gene, common disease"? Methods Mol. Biol. 376, 71-84 , (2007) .
    • . . . For example, this approach relies on the common disease–common variant hypothesis, which states that common diseases are caused by a few common gene variants rather than a large number of rare variants, and this has recently been challenged (see Ref. 73 for a review) . . .
  74. Willer, C. J. et al. Six new loci associated with body mass index highlight a neuronal influence on body weight regulation. Nature Genet. 41, 25-34.A meta-analysis of 15 GWA studies for BMI associations reporting six novel loci , (2009) .
  75. Dina, C. et al. Variation in FTO contributes to childhood obesity and severe adult obesity. Nature Genet. 39, 724-726 , (2007) .
    • . . . In 2007, two groups simultaneously identified FTO as containing a common variant unequivocally associated with BMI and increased risk for obesity44, 75 . . .
    • . . . The second study75 reported quantitatively similar data . . .
  76. The Wellcome Trust Case Control Consortium. Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls. Nature 447, 661-678.A large-scale GWA study of seven common diseases, including type 2 diabetes , (2007) .
    • . . . The Wellcome Trust Case Control Consortium performed a GWA scan for type 2 diabetes76, resulting in the identification of FTO as strongly associated . . .
  77. Loos, R. J. & Bouchard, C. FTO: the first gene contributing to common forms of human obesity. Obes. Rev. 9, 246-50 , (2008) .
  78. Gerken, T. et al. The obesity-associated FTO gene encodes a 2-oxoglutarate-dependent nucleic acid demethylase. Science 318, 1469-1472 , (2007) .
    • . . . FTO is widely expressed in the brain, with evidence from animal studies indicating a particularly high level of expression in the hypothalamic nuclei, which are involved in regulating energy balance78 . . .
  79. Speakman, J. R., Rance, K. A. & Johnstone, A. M. Polymorphisms of the FTO gene are associated with variation in energy intake, but not energy expenditure. Obesity (Silver Spring) 16, 1961-1965 , (2008) .
    • . . . Both human and animal studies indicate that the gene may have a role in the regulation of appetite, with the risk allele associated with modestly increased food intake79, 80 and decreased satiety81 in humans . . .
  80. Wardle, J., Llewellyn, C., Sanderson, S. & Plomin, R. The FTO gene and measured food intake in children. Int. J. Obes. (Lond.) , (2008) .
    • . . . Both human and animal studies indicate that the gene may have a role in the regulation of appetite, with the risk allele associated with modestly increased food intake79, 80 and decreased satiety81 in humans . . .
  81. Wardle, J. et al. Obesity associated genetic variation in FTO is associated with diminished satiety. J. Clin. Endocrinol. Metab. 93, 3640-3643 , (2008) .
    • . . . Both human and animal studies indicate that the gene may have a role in the regulation of appetite, with the risk allele associated with modestly increased food intake79, 80 and decreased satiety81 in humans . . .
  82. Wahlen, K., Sjolin, E. & Hoffstedt, J. The common rs9939609 gene variant of the fat mass- and obesity-associated gene FTO is related to fat cell lipolysis. J. Lipid Res. 49, 607-611 , (2008) .
    • . . . The risk allele is also associated with decreased lipolytic activity in adipocytes, indicating a possible role in fat cell lipolysis82 . . .
  83. Andreasen, C. H. et al. Low physical activity accentuates the effect of the FTO rs9939609 polymorphism on body fat accumulation. Diabetes 57, 95-101 , (2008) .
    • . . . Physical activity has been reported to modify the effects of the FTO risk allele, as it seems to have a stronger effect in people who are less active83. . . .
  84. Loos, R. J. et al. Common variants near MC4R are associated with fat mass, weight and risk of obesity. Nature Genet. 40, 768-775 , (2008) .
    • . . . Two recent GWA studies have found strong association between SNPs located 188 kb away from the MC4R gene and BMI, waist circumference and obesity84, 85 . . .
    • . . . In the larger study84, analysis of 660 nuclear families ascertained through an obese child or adolescent proband (BMI > ninety-fifth percentile) revealed significant overtransmission of the risk allele (p = 2.4 10-4) . . .
  85. Chambers, J. C. et al. Common genetic variation near MC4R is associated with waist circumference and insulin resistance. Nature Genet. 40, 716-188 , (2008) .
    • . . . Two recent GWA studies have found strong association between SNPs located 188 kb away from the MC4R gene and BMI, waist circumference and obesity84, 85 . . .
  86. Andreasen, C. H. et al. Non-replication of genome-wide based associations between common variants in INSIG2 and PFKP and obesity in studies of 18,014 Danes. PLoS ONE 3, e2872 , (2008) .
    • . . . The association between this MC4R variant and obesity has also been replicated in a Danish study86 . . .
    • . . . Although an early first-generation array-based GWA study identified insulin-induced gene 2 (INSIG2) as a candidate obesity gene88, this result was not supported by number of subsequent large studies86, 89, 90, 91, 92 . . .
  87. Qi, L., Kraft, P., Hunter, D. J. & Hu, F. B. The common obesity variant near MC4R gene is associated with higher intakes of total energy and dietary fat, weight change and diabetes risk in women. Hum. Mol. Genet. 17, 3502-8 , (2008) .
    • . . . The variant has been associated with higher overall food intake and higher dietary fat intake87 . . .
  88. Herbert, A. et al. A common genetic variant is associated with adult and childhood obesity. Science 312, 279-283 , (2006) .
    • . . . Although an early first-generation array-based GWA study identified insulin-induced gene 2 (INSIG2) as a candidate obesity gene88, this result was not supported by number of subsequent large studies86, 89, 90, 91, 92 . . .
  89. Dina, C. et al. Comment on "A common genetic variant is associated with adult and childhood obesity". Science 315, 187b; author reply 187e , (2007) .
    • . . . Although an early first-generation array-based GWA study identified insulin-induced gene 2 (INSIG2) as a candidate obesity gene88, this result was not supported by number of subsequent large studies86, 89, 90, 91, 92 . . .
  90. Rosskopf, D. et al. Comment on "A common genetic variant is associated with adult and childhood obesity". Science 315, 187; author reply 187e , (2007) .
    • . . . Although an early first-generation array-based GWA study identified insulin-induced gene 2 (INSIG2) as a candidate obesity gene88, this result was not supported by number of subsequent large studies86, 89, 90, 91, 92 . . .
  91. Loos, R. J., Barroso, I., O'Rahilly, S. & Wareham, N. J. Comment on "A common genetic variant is associated with adult and childhood obesity". Science 315, 187c; author reply 187e , (2007) .
    • . . . Although an early first-generation array-based GWA study identified insulin-induced gene 2 (INSIG2) as a candidate obesity gene88, this result was not supported by number of subsequent large studies86, 89, 90, 91, 92 . . .
  92. Lyon, H. N. et al. The association of a SNP upstream of INSIG2 with body mass index is reproduced in several but not all cohorts. PLoS Genet. 3, e61 , (2007) .
    • . . . Although an early first-generation array-based GWA study identified insulin-induced gene 2 (INSIG2) as a candidate obesity gene88, this result was not supported by number of subsequent large studies86, 89, 90, 91, 92 . . .
  93. Scuteri, A. et al. Genome-wide association scan shows genetic variants in the FTO gene are associated with obesity-related traits. PLoS Genet. 3, e115 , (2007) .
    • . . . The first current-generation GWA study was published in mid-2007 (Ref. 93), and used families recruited from the general population . . .
  94. Meyre, D. et al. Genome-wide association study for early-onset and morbid adult obesity identifies three new risk loci in European populations. Nature Genet. 41, 157-159.The first GWA study for severe adult and child obesity reporting three novel loci , (2009) .
  95. Su, A. I. et al. Large-scale analysis of the human and mouse transcriptomes. Proc. Natl Acad. Sci. USA 99, 4465-4470 , (2002) .
    • . . . The association with NPC1 is of particular interest, as the NPC1 gene is expressed at particularly high levels in the brain (notably the hypothalamus)95 and its protein product plays a part in endosomal cholesterol trafficking in the central nervous system, the immune system and the liver96, 97, 98 . . .
  96. Amigo, L. et al. Relevance of Niemann-Pick type C1 protein expression in controlling plasma cholesterol and biliary lipid secretion in mice. Hepatology 36, 819-828 , (2002) .
    • . . . The association with NPC1 is of particular interest, as the NPC1 gene is expressed at particularly high levels in the brain (notably the hypothalamus)95 and its protein product plays a part in endosomal cholesterol trafficking in the central nervous system, the immune system and the liver96, 97, 98 . . .
  97. Ikonen, E. Cellular cholesterol trafficking and compartmentalization. Nature Rev. Mol. Cell Biol. 9, 125-138 , (2008) .
    • . . . The association with NPC1 is of particular interest, as the NPC1 gene is expressed at particularly high levels in the brain (notably the hypothalamus)95 and its protein product plays a part in endosomal cholesterol trafficking in the central nervous system, the immune system and the liver96, 97, 98 . . .
  98. Vance, J. E. Lipid imbalance in the neurological disorder, Niemann-Pick C disease. FEBS Lett. 580, 5518-5524 , (2006) .
    • . . . The association with NPC1 is of particular interest, as the NPC1 gene is expressed at particularly high levels in the brain (notably the hypothalamus)95 and its protein product plays a part in endosomal cholesterol trafficking in the central nervous system, the immune system and the liver96, 97, 98 . . .
  99. Xie, C., Turley, S. D., Pentchev, P. G. & Dietschy, J. M. Cholesterol balance and metabolism in mice with loss of function of Niemann-Pick C protein. Am. J. Physiol. 276, E336-E344 , (1999) .
    • . . . Npc1 knockout mice show late-onset weight loss, poor food intake, a defect in cholesterol transport and neurological deficits99. . . .
  100. Liu, Y. J. et al. Genome-wide association scans identified CTNNBL1 as a novel gene for obesity. Hum. Mol. Genet. 17, 1803-1813 , (2008) .
  101. Cauchi, S. & Froguel, P. TCF7L2 genetic defect and type 2 diabetes. Curr. Diab. Rep. 8, 149-155 , (2008) .
    • . . . The most significant SNP was strongly associated with BMI and fat mass; this finding is particularly interesting as it may indicate a novel mechanism for the development of obesity — through the Wnt signalling pathway, which is strongly linked to type 2 diabetes genetics (see Ref. 101 for a review) . . .
  102. Ross, S. E. et al. Inhibition of adipogenesis by Wnt signaling. Science 289, 950-953 , (2000) .
    • . . . Wnt–-catenin signalling has a number of functions that have implications for obesity, notably inhibiting adipogenesis102 and initiating taste bud development103. . . .
  103. Liu, F. et al. Wnt--catenin signaling initiates taste papilla development. Nature Genet. 39, 106-112 , (2007) .
    • . . . Wnt–-catenin signalling has a number of functions that have implications for obesity, notably inhibiting adipogenesis102 and initiating taste bud development103. . . .
  104. Thorleifsson, G. et al. Genome-wide association yields new sequence variants at seven loci that associate with measures of obesity. Nature Genet. 41, 18-24 , (2009) .
  105. Froguel, P. & Blakemore, A. I. The power of the extreme in elucidating obesity. N. Engl. J. Med. 359, 891-893 , (2008) .
    • . . . However, if there are genes predisposing to severe obesity then extreme subjects must be recruited105 . . .
  106. Lasky-Su, J. et al. On the replication of genetic associations: timing can be everything! Am. J. Hum. Genet. 82, 849-858 , (2008) .
    • . . . In addition, many studies do not consider the possible differences between analysing child and adult obesity, and the importance of this has recently been shown106 by the identification of associations that vary in strength depending on the age of the subjects studied. . . .
  107. Cookson, W., Liang, L., Abecasis, G., Moffatt, M. & Lathrop, M. Mapping complex disease traits with global gene expression. Nature Rev. Genet. 10, 184-194 , (2009) .
    • . . . The transcript levels are then analysed as quantitative traits for genetic linkage to the phenotype of interest107 . . .
  108. Li, H. et al. Transcriptomic and metabonomic profiling of obesity-prone and obesity-resistant rats under high fat diet. J. Proteome Res. 7, 4775-4783 , (2008) .
    • . . . In metabolomics, work has already identified different phenotypic profiles between obesity-prone and obesity-resistant mice fed on a high fat diet that correlate well with transcriptomics results108 . . .
  109. Boden, G. et al. Increase in endoplasmic reticulum stress-related proteins and genes in adipose tissue of obese, insulin-resistant individuals. Diabetes 57, 2438-2444 , (2008) .
    • . . . For example, a recent analysis of endoplasmic reticulum stress-related proteins in adipose tissue from obese individuals identified three upregulated proteins: calreticulin, protein disulphide isomerase A3 and glutathione S-transferase P109. . . .
  110. Zondervan, K. T. & Cardon, L. R. Designing candidate gene and genome-wide case-control association studies. Nature Protoc. 2, 2492-2501 , (2007) .
    • . . . There is good guidance available on the design of genetic studies110, 111, and the limitations of current GWA study designs are well known72, 112 . . .
  111. Rao, D. C. An overview of the genetic dissection of complex traits. Adv. Genet. 60, 3-34 , (2008) .
    • . . . There is good guidance available on the design of genetic studies110, 111, and the limitations of current GWA study designs are well known72, 112 . . .
  112. Teo, Y. Y. Common statistical issues in genome-wide association studies: a review on power, data quality control, genotype calling and population structure. Curr. Opin. Lipidol. 19, 133-143 , (2008) .
    • . . . There is good guidance available on the design of genetic studies110, 111, and the limitations of current GWA study designs are well known72, 112 . . .
  113. Iles, M. M. What can genome-wide association studies tell us about the genetics of common disease? PLoS Genet. 4, e33 , (2008) .
    • . . . It is true that no variant so far discovered accounts for more than a small fraction of the genetic variation, and it has been suggested that much larger case–control GWA approaches will be needed to obtain the statistical power that is needed to detect common variants of small effect113 . . .
  114. Cupples, L. A. Family study designs in the age of genome-wide association studies: experience from the Framingham Heart Study. Curr. Opin. Lipidol. 19, 144-150 , (2008) .
    • . . . Although case–control studies are popular because of the ease with which the subjects can be recruited, they are vulnerable to spurious results owing to population substructure and the difficulty in controlling for gene–environment interactions, something that family-based study designs can address114 . . .
  115. Manolio, T. A., Bailey-Wilson, J. E. & Collins, F. S. Genes, environment and the value of prospective cohort studies. Nature Rev. Genet. 7, 812-820 , (2006) .
    • . . . In addition, prospectively recruited population samples115, in which risk factors and exposures can be estimated prior to disease onset, need to be carried out to gain insights into gene–environment interactions . . .
  116. Lowe, J. K. et al. Genome-wide association studies in an isolated founder population from the Pacific Island of Kosrae. PLoS Genet. 5, e1000365 , (2009) .
    • . . . A GWA study using subjects from the isolated Pacific island of Kosrae found little similarity in results for many quantitative traits, including no association between BMI and FTO or MC4R variants116 . . .
  117. Blakemore, A. I. et al. A rare variant in the visfatin gene (NAMPT/PBEF1) is associated with protection from obesity. Obesity (Silver Spring) (in the press) , .
    • . . . However, there are now sufficient reports of rare variants of strong effect in complex common disease — for example, in obesity117, susceptibility to infection118 and type 1 diabetes119 — to support the idea that both common and rare variants contribute to common disease . . .
  118. Khor, C. C. et al. A Mal functional variant is associated with protection against invasive pneumococcal disease, bacteremia, malaria and tuberculosis. Nature Genet. 39, 523-528 , (2007) .
    • . . . However, there are now sufficient reports of rare variants of strong effect in complex common disease — for example, in obesity117, susceptibility to infection118 and type 1 diabetes119 — to support the idea that both common and rare variants contribute to common disease . . .
  119. Nejentsev, S., Walker, N., Riches, D., Egholm, M. & Todd, J. A. Rare variants of IFIH1, a gene implicated in antiviral responses, protect against type 1 diabetes. Science 324, 387-389 , (2009) .
    • . . . However, there are now sufficient reports of rare variants of strong effect in complex common disease — for example, in obesity117, susceptibility to infection118 and type 1 diabetes119 — to support the idea that both common and rare variants contribute to common disease . . .
  120. Jones, S. et al. Exomic sequencing identifies PALB2 as a pancreatic cancer susceptibility gene. Science 324, 217 , (2009) .
    • . . . Sequencing all known coding DNA, known as exomic sequencing120, and deep sequencing in specific genomic regions are now possible and are a fast way to identify all the sequence variants of interest . . .
  121. Stranger, B. E. et al. Relative impact of nucleotide and copy number variation on gene expression phenotypes. Science 315, 848-853.The first paper to describe the effects of copy number variation on gene expression , (2007) .
    • . . . Copy number variants (CNVs), which include copy number gains (duplications or insertions), losses (deletions) and rearrangements, have been estimated to account for nearly 18% of heritable variance in gene expression121 . . .
  122. de Smith, A. J. et al. Array CGH analysis of copy number variation identifies 1,284 new genes variant in healthy white males: implications for association studies of complex diseases. Hum. Mol. Genet. 16, 2783-2794 , (2007) .
    • . . . Of particular relevance to obesity, gene ontology analyses indicate that the genes overlapped by CNVs are enriched for those involved in brain development, sensory perception (including olfaction) and immune responses122, 123 . . .
  123. Feuk, L., Carson, A. R. & Scherer, S. W. Structural variation in the human genome. Nature Rev. Genet. 7, 85-97 , (2006) .
    • . . . Of particular relevance to obesity, gene ontology analyses indicate that the genes overlapped by CNVs are enriched for those involved in brain development, sensory perception (including olfaction) and immune responses122, 123 . . .
  124. Peiffer, D. A. et al. High-resolution genomic profiling of chromosomal aberrations using Infinium whole-genome genotyping. Genome Res. 16, 1136-1148 , (2006) .
    • . . . The recent development of high-density SNP arrays that are specifically designed to enhance CNV discovery124, 125 and the simultaneous development of novel algorithms to detect CNVs from the data produced by these arrays (see Ref. 126 for a review) have offered the possibility of simultaneous genome-wide SNP and CNV profiling to generate a more complete picture of genetic variation. . . .
  125. McCarroll, S. A. et al. Integrated detection and population-genetic analysis of SNPs and copy number variation. Nature Genet. 40, 1166-1174 , (2008) .
    • . . . The recent development of high-density SNP arrays that are specifically designed to enhance CNV discovery124, 125 and the simultaneous development of novel algorithms to detect CNVs from the data produced by these arrays (see Ref. 126 for a review) have offered the possibility of simultaneous genome-wide SNP and CNV profiling to generate a more complete picture of genetic variation. . . .
  126. Baross, A. et al. Assessment of algorithms for high throughput detection of genomic copy number variation in oligonucleotide microarray data. BMC Bioinformatics 8, 368 , (2007) .
    • . . . The recent development of high-density SNP arrays that are specifically designed to enhance CNV discovery124, 125 and the simultaneous development of novel algorithms to detect CNVs from the data produced by these arrays (see Ref. 126 for a review) have offered the possibility of simultaneous genome-wide SNP and CNV profiling to generate a more complete picture of genetic variation. . . .
  127. Horsthemke, B. & Wagstaff, J. Mechanisms of imprinting of the Prader-Willi/Angelman region. Am. J. Med. Genet. A 146A, 2041-2052 , (2008) .
    • . . . The effect of epigenetics has long been known in syndromic obesity, in which genomic imprinting is crucial to the disease phenotype in Prader–Willi syndrome127 . . .
  128. Dong, C. et al. Possible genomic imprinting of three human obesity-related genetic loci. Am. J. Hum. Genet. 76, 427-437 , (2005) .
    • . . . There is also evidence of parent-of-origin effects, suggesting imprinting, being linked to common polygenic obesity in other areas of the genome128, 129 . . .
  129. Guo, Y. F. et al. Assessment of genetic linkage and parent-of-origin effects on obesity. J. Clin. Endocrinol. Metab. 91, 4001-4005 , (2006) .
    • . . . There is also evidence of parent-of-origin effects, suggesting imprinting, being linked to common polygenic obesity in other areas of the genome128, 129 . . .
  130. Stoger, R. The thrifty epigenotype: an acquired and heritable predisposition for obesity and diabetes? Bioessays 30, 156-166 , (2008) .
    • . . . Although it is difficult to distinguish between purely environmental effects and effects of the environment on epigenetic factors, epigenetics has been proposed as the mechanism underlying propagation of obesity from mother to child by a 'thrifty epigenotype'130 . . .
  131. Bibikova, M. et al. High-throughput DNA methylation profiling using universal bead arrays. Genome Res. 16, 383-393 , (2006) .
    • . . . Genome-wide measurement of epigenetic variation has recently been made possible using techniques such as DNA-methylation-specific microarrays131 and methylated DNA immunoprecipitation and resequencing132 . . .
  132. Weber, M. et al. Chromosome-wide and promoter-specific analyses identify sites of differential DNA methylation in normal and transformed human cells. Nature Genet. 37, 853-862 , (2005) .
    • . . . Genome-wide measurement of epigenetic variation has recently been made possible using techniques such as DNA-methylation-specific microarrays131 and methylated DNA immunoprecipitation and resequencing132 . . .
  133. English, S. B. & Butte, A. J. Evaluation and integration of 49 genome-wide experiments and the prediction of previously unknown obesity-related genes. Bioinformatics 23, 2910-2917.The first attempt at a systems biology approach to integrating obesity research results identifies novel genes , (2007) .
    • . . . A pioneering systems-based meta-analysis that focused on obesity drew on data from 49 genome-wide experiments — including microarrays, proteomic and gene expression analysis, and RNAi studies in humans, mice, rats and worms133 . . .
  134. Gorber, S. C., Tremblay, M., Moher, D. & Gorber, B. A comparison of direct vs. self-report measures for assessing height, weight and body mass index: a systematic review. Obes. Rev. 8, 307-326 , (2007) .
  135. Wells, J. C., Ruto, A. & Treleaven, P. Whole-body three-dimensional photonic scanning: a new technique for obesity research and clinical practice. Int. J. Obes. (Lond.) 32, 232-238 , (2008) .
  136. Ellis, K. J. et al. Body-composition assessment in infancy: air-displacement plethysmography compared with a reference 4-compartment model. Am. J. Clin. Nutr. 85, 90-95 , (2007) .
  137. Shen, W. & Chen, J. Application of imaging and other noninvasive techniques in determining adipose tissue mass. Methods Mol. Biol. 456, 39-54 , (2008) .
  138. Vlachos, I. S., Hatziioannou, A., Perelas, A. & Perrea, D. N. Sonographic assessment of regional adiposity. AJR Am. J. Roentgenol. 189, 1545-1553 , (2007) .
  139. Westerterp, K. R. & Goris, A. H. Validity of the assessment of dietary intake: problems of misreporting. Curr. Opin. Clin. Nutr. Metab. Care 5, 489-493 , (2002) .
  140. Swanson, M. Digital photography as a tool to measure school cafeteria consumption. J. Sch. Health 78, 432-437 , (2008) .
  141. Pencina, M. J., Millen, B. E., Hayes, L. J. & D'Agostino, R. B. Performance of a method for identifying the unique dietary patterns of adult women and men: the Framingham nutrition studies. J. Am. Diet Assoc. 108, 1453-1460 , (2008) .
  142. Dialektakou, K. D. & Vranas, P. B. Breakfast skipping and body mass index among adolescents in Greece: whether an association exists depends on how breakfast skipping is defined. J. Am. Diet Assoc. 108, 1517-1525 , (2008) .
  143. Morton, G. J., Cummings, D. E., Baskin, D. G., Barsh, G. S. & Schwartz, M. W. Central nervous system control of food intake and body weight. Nature 443, 289-295 , (2006) .
  144. Henry, B. A. & Clarke, I. J. Adipose tissue hormones and the regulation of food intake. J. Neuroendocrinol. 20, 842-849 , (2008) .
  145. Rosen, E. D. & Spiegelman, B. M. Adipocytes as regulators of energy balance and glucose homeostasis. Nature 444, 847-853 , (2006) .
  146. Spiegelman, B. M. & Flier, J. S. Obesity and the regulation of energy balance. Cell 104, 531-543 , (2001) .
  147. Wegner, L. et al. Common variation in LMNA increases susceptibility to type 2 diabetes and associates with elevated fasting glycemia and estimates of body fat and height in the general population: studies of 7,495 Danish whites. Diabetes 56, 694-698 , (2007) .
  148. Baessler, A. et al. Genetic linkage and association of the growth hormone secretagogue receptor (ghrelin receptor) gene in human obesity. Diabetes 54, 259-267 , (2005) .
  149. Gylvin, T. et al. Functional SOCS1 polymorphisms are associated with variation in obesity in whites. Diabetes Obes. Metab. 11, 196-203 , (2009) .
  150. Talbert, M. E. et al. Polymorphisms near SOCS3 are associated with obesity and glucose homeostasis traits in Hispanic Americans from the Insulin Resistance Atherosclerosis Family Study. Hum. Genet. 125, 153-162 , (2009) .
  151. Zobel, D. et al. Variation in the gene encoding Kruppel-like factor 7 influences body fat: studies of 14,818 Danes. Eur. J. Endocrinol. 160, 603-609 , (2009) .
  152. Yanagiya, T. et al. Association of single-nucleotide polymorphisms in MTMR9 gene with obesity. Hum. Mol. Genet. 16, 3017-3026 , (2007) .
  153. Wermter, A. K. et al. Preferential reciprocal transfer of paternal/maternal DLK1 alleles to obese children: first evidence of polar overdominance in humans. Eur. J. Hum. Genet. 16, 1126-1134 , (2008) .
  154. Stone, S. et al. TBC1D1 is a candidate for a severe obesity gene and evidence for a gene/gene interaction in obesity predisposition. Hum. Mol. Genet. 15, 2709-20 , (2006) .
  155. Siddiq, A. et al. Single nucleotide polymorphisms in the neuropeptide Y2 receptor (NPY2R) gene and association with severe obesity in French white subjects. Diabetologia 50, 574-84 , (2007) .
Expand