Übergewicht und Gene...

NEJM Volume 359:2603-2604 December 11,2008 Number 24
Energy In, Energy Out, and the Effects of Obesity-Related Genes
Rudolph L. Leibel, M.D.

More than 100 genes have been implicated in the determination of body weight. These genes, acting primarily in or through the central nervous system (primarily the hypothalamus and brain stem), affect conscious and unconscious aspects of food intake and energy expenditure. They include genes mediating brain sensing of fat stores, calorie flux in the gut, hedonic responses to specific foods, rates of energy expenditure, and even inclination to physical activity.1,2,3 In some populations, mutations in one of these genes — the melanocortin 4 receptor (MC4R), which conveys hypothalamic signals suppressing food intake and increasing energy expenditure — can account for 3 to 5% of severe obesity (body-mass index [BMI] >40, with BMI defined as the weight in kilograms divided by the square of the height in meters).4 Other quantitatively significant single genes have been hard to identify. Possible reasons for this failure may be that obesity is so physiologically complex that no single gene or even handful of genes is likely to have a dispositive role, that examining gene–gene interactions is difficult without large numbers of subjects, and that variations among current candidate genes are not the most important contributors to human adiposity.
Enter the genomewide association study,5 which uses large numbers of common single-nucleotide polymorphisms (SNPs) in DNA spaced more or less evenly across the human genome to identify genetic variation associated with ordinal or cardinal phenotypes. Unlike the candidate-gene approach, the genomewide association study is genetically agnostic: it looks for genetic intervals associated with the phenotype or phenotypes; the constituent genes are "discovered" after the fact by examining those in the implicated interval. The fat mass and obesity–associated gene (FTO) examined in the article by Cecil et al. in this issue of the Journal6 was previously identified as a new obesity candidate by a genomewide association study.7
Frayling et al.7 found a strong association between SNPs (e.g., rs9939609) and adiposity in the first intron of FTO. This association has been replicated in several additional studies, using data on more than 80,000 adults and children. The statistical power of the association (P=~1.2x10–29) in the aggregate data is much higher than for any previous candidate-gene association study.
Cecil et al. studied the effects of genetic variation in the region around SNP rs9939609 in children. The major effect appears to be on energy intake and preference for foods of high caloric density. The magnitude of the increase in energy intake correlated with the A allele of this SNP is high enough to account for some or all of the differences in adiposity. No effect of genotype at rs9939609 on resting energy expenditure (corrected for body size) was detected, and physical activity was actually estimated to be increased in these children. Given the findings of studies of the molecular physiology of weight regulation, excess intake (rather than reduced basal energy expenditure) is probably the major mechanism for obesity in humans. Conducting studies of the contributions of genetic variation to the risk of obesity during the dynamic process of weight gain is crucial, because once a stable weight is reached, energy intake per unit of metabolic mass does not differ between obese and lean people.8
Two known genes lie within the implicated genetic interval. One is FTO (a locus associated with fat mass and obesity), which has been implicated in nucleic acid demethylation and is highly expressed in the arcuate nucleus of the hypothalamus; the other, called fantom, or FTM (KIAA1005 or RPGRIP1L), begins transcription at a location only 200 base pairs upstream from the 5' end of FTO. FTM is a structural component of the ciliary body, present on all cells, that plays a role in a wide range of cellular and organ functions.9 Elements of the cilium are mutant in Bardet–Biedl syndrome, which includes obesity among its characteristic phenotypes.10
Fasting decreases the expression of both FTO and FTM in the hypothalamus in murine models, suggesting that these molecules may function to suppress energy intake. One SNP (rs8050136) in intron 1 of FTO, which is located near rs9939609, encodes for a binding site for a transcription factor, cut-like 1 (CUTL1). Experimental reduction of CUTL1 transcript in human fibroblasts is associated with reduced expression of both FTO and FTM, consistent with their joint regulation in vivo.11 Both genes are plausible candidates for influencing energy homeostasis. It is possible, of course, that both genes are involved in conveying the strong statistical association of this genetic interval with obesity. In fact, a genomewide association study is inherently biased toward the discovery of intervals containing several contributing genes.
In the original genomewide association study conducted by Frayling et al.,7 the frequency of the rs9939609 A allele (increased obesity risk) was 0.45 in Europeans, 0.52 in West Africans, and 0.14 in Chinese. In their meta-analysis of available genomewide association study data (primarily in whites), the odds ratio for the A allele was 1.31 for obesity and 1.18 for overweight. Although the variance in BMI accounted for by rs9939609 was only 1%, the population attributable risks for overweight and obesity were 12.7% and 20.4%, respectively. Hence, although this locus accounts for only a small proportion of differences in the BMI in the entire population, it plays a substantial role — in these people, in these environments — in conveying the risk of actually becoming overweight or obese. In the Avon longitudinal study of parents and children (7477) in the United Kingdom, cited in Frayling et al.,7 each A allele increased BMI by about 0.4 by the age of 11 years, increasing the relative risk of obesity by 35% and overweight by 16%. The effect was not seen at birth but was apparent by 7 years and was due to increases in body fat alone.
The population attributable risk for obesity conveyed by the FTO–FTM region is high but probably not sufficient to support its use as a clinical screening tool, since the gene or genes responsible are not yet known, and no specific prophylactic or therapeutic intervention is yet apparent for this or other common genetic variants contributing to obesity (e.g., MC4R). However, the day is not too far off when we will, by "scoring" alleles of perhaps 15 to 20 such genes, be able to predict individual risk of type 2 diabetes, obesity, and other diseases. The important role that environment plays in enabling or resisting such susceptibility is clear evidence that such risk can be modified.

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