DÄ internationalArchive19/2013Molecular Genetic Aspects of Weight Regulation

Review article

Molecular Genetic Aspects of Weight Regulation

Dtsch Arztebl Int 2013; 110(19): 338-44. DOI: 10.3238/arztebl.2013.0338

Hebebrand, J; Hinney, A; Knoll, N; Volckmar, A; Scherag, A

Background: Family and twin studies have empirically revealed a 40% to 70% heritability of body-mass index, yet only a few hereditary factors have been identified to date that increase the risk of being overweight.

Methods: We present the current state of molecular genetic research on obesity with a selective review of the literature.

Results: A number of monogenic recessive mutations causing obesity have been identified, but these are rare. Various dominant mutations of the melanocortin-4 receptor gene are found in about 1% to 4% of all markedly obese persons. Current molecular genetic research focuses on the identification of common DNA variants affecting body weight; the genetic material of hundreds of thousands of people from around the world has now been investigated in genome-wide association studies. More than 30 variants conferring an increased risk have been identified, most of which are single nucleotide polymorphisms (SNPs) of no immediately clear functional significance. On average, these variants raise body weight by 500 g (range, 180 to 1400 g). Aside from SNPs, variations in the number of copies of specific DNA sequences have also been linked to obesity, as well as to subnormal weight. All the hereditary factors that have been identified to date account for about 5% of the variability of BMI. Extrapolation yields figures ranging from 10% to 15%.

Conclusions: The amount of genetic variability seen to date at the DNA level accounts only for a small fraction of the inter-individual variability of BMI. Obesity is thought to be a largely hereditary condition; the fact that its genetic basis has not yet been demonstrated may be due to various genetic or experimental factors.

LNSLNS

The increasing prevalence of overweight (BMI ≥ 25 kg/m2) and obesity (BMI ≥ 30 kg/m2), with the associated risks of cardiovascular disease, type 2 diabetes, various cancers, and joint disease, is arousing considerable and growing interest in the underlying risk factors (1, 2, e1). The populations of modern industrialized countries are exposed to a multitude of environmental factors that favor a positive energy balance. Energy uptake frequently exceeds energy consumption to such an extent that body fat increases to an above average level, resulting in overweight or obesity. The two primary causes are thought to be the low cost and ready availability of a wide range of tasty, high-energy foodstuffs and a lack of exercise both at work and during leisure time. Psychosocial factors play a role in how individual people cope with their obesity-facilitating environment. However, scientific demonstration of the causal involvement of particular environmental factors is not easy. For example, the postulated influence of sugar-containing drinks on long-term weight change in children and adolescents has only recently been underpinned by randomized controlled trials (3).

Numerous twin, family, and adoption studies have yielded insight into the relative contributions of hereditary and environmental factors to the body mass index (BMI) (4). According to twin and family studies, 40% to 70% of the interindividual variance in BMI is explained by genetic factors. This is termed heritability. While the increase in prevalence of excess body weight is attributable to altered environmental factors, genetic factors essentially determine the extent to which the predisposing environmental parameters actually lead to overweight in the individual. Interestingly, the contribution of genetic factors to the variance in BMI in the general population is the same today as it was 30 years ago. When estimating heritability it is important not to neglect environmental reactions. For example, an infant’s genetically caused excessive hunger (direct genetic effect) may, independent of cultural factors, lead to more frequent breastfeeding; this indirect effect represents the reaction of the environment to the biologically determined behavior (4).

Identical twins have highly correlated BMIs (intra-pair correlations around 0.7), and this holds true for twins who were separated directly after birth. In childhood a certain proportion of the BMI variance in these twins is explained by shared environmental factors, while in adulthood it is exclusively the non-shared environmental experiences. According to empirical studies the occurrence of obesity in two adult siblings is primarily attributable to hereditary factors; the similarity is not explained by growing up together in their original family. Given the ubiquitous presence of a obesity-facilitating environment in the industrial nations, it may not be possible to prove an influence of common environmental factors (4).

Based on the empirical findings, which clearly indicate heritability of the BMI, we set out to elucidate and discuss the current status of molecular genetic research into weight regulation.

Syndromal and monogenic forms of obesity

Syndromal forms of obesity, e.g. Prader–Willi syndrome, often go hand in hand with reduced intelligence and dysmorphic features and must therefore be distinguished from nonsyndromal forms of obesity; an overview of the relevant molecular findings can be found in the article by Blüher et al. (5).

The discovery that the autosomal-recessively inherited leptin deficiency leads to extreme obesity in humans (6) lent considerable impetus to molecular research into obesity. It has been shown that mutations in a single gene suffice to cause hyperphagia and onset of extreme obesity in infancy in persons of normal intelligence. Furthermore, leptin deficiency has been successfully treated in individual cases by the administration of recombinant leptin (7). The diagnosis of leptin deficiency in a 14-year-old girl (8)—the only known case in a person of Central European origin—with a BMI of 31.5 kg/m2 shows that extreme obesity does not necessarily occur. Up to the age of 8 years, this girl’s body weight was “only” at the 97th percentile for her age. The metabolism in leptin deficiency is in many respects comparable with that of fasting persons; because the important satiety hormone leptin is absent, various metabolic processes are regulated centrally via the hypothalamus as in the fasting state.

Further monogenic forms of obesity have been discovered, all of them rare and all of them belonging to the hypothalamic leptin-melanocortinergic regulatory system.

Major gene effects

The melanocortin-4 receptor (MC4R) is an important receptor in the leptin-melanocortinergic regulatory system (Figure 1). Since obesity is the cardinal symptom of the MC4R-knockout mouse, the MC4R gene was investigated for mutations, and joint inheritance of mutations and obesity was initially described in 1998 in two families (9, 10). When leptin binds to the corresponding leptin receptor in the hypothalamus, one result is increased synthesis of pro-opiomelanocortin (POMC); α-melanocyte-stimulating hormone (α-MSH), a cleavage product of POMC, binds to MC4R and induces a feeling of satiety together with increased energy expenditure caused by elevated sympathetic tone. If receptor function is reduced by mutations, the α-MSH signal does not exert its normal effect.

Leptin is generated in adipose tissue and transported via the bloodstream to the hypothalamus. The binding of leptin to leptin receptors (ObRb) stimulates the expression of cocaineand amphetamine-regulated transcript (CART) and pro-opiomelanocortin (POMC)
Leptin is generated in adipose tissue and transported via the bloodstream to the hypothalamus. The binding of leptin to leptin receptors (ObRb) stimulates the expression of cocaineand amphetamine-regulated transcript (CART) and pro-opiomelanocortin (POMC)
Figure 1
Leptin is generated in adipose tissue and transported via the bloodstream to the hypothalamus. The binding of leptin to leptin receptors (ObRb) stimulates the expression of cocaineand amphetamine-regulated transcript (CART) and pro-opiomelanocortin (POMC)

To date around 160 functionally relevant mutations have been detected in MC4R (11); 1% to 4% of all obese persons carry such mutations (12). Adult male and female mutation carriers weigh an average of 15 kg and up to 30 kg, respectively, more than family members without mutations (13). Thus, these major gene effects have a lesser phenotypic effect on body weight compared to the monogenic-recessive forms of obesity. Moreover, not every carrier of a functionally relevant MC4R mutation develops obesity (12).

Furthermore, compared with other children with obesity, carriers of MC4R mutations are characterized by accelerated height increase, an increased incidence of hyperinsulinemia (14), and a lower blood pressure than usual for their BMI (e2). Because carriers also seem to display reduced nerve conduction velocity (15), reduced sympathetic tone could contribute to the development of obesity. Interestingly, two young mutation carriers with extreme obesity lost a great deal of weight when treated with indirect sympathicomimetics (16, e3). In vitro studies suggest that specific treatment with MC4R agonists may be effective in a subgroup of mutation carriers (17).

Polygenic weight regulation

In parallel with the molecular genetic research in other complex phenotypes, in recent years molecular genetic research into obesity has focused on the identification of predisposing genetic variants that are common in the general population. The underlying hypothesis (common disease–common variant hypothesis) is that frequent alleles of several or many genes, each with a small effect on the BMI, determine an individual person’s weight by the sum of the variants present (Figure 2). Genotyping of thousands of people is necessary for detection and confirmation of such variants; accordingly, the effects are usually confirmed only in meta-analyses. Earlier investigations of candidate genes mostly involved small numbers of cases and controls; only occasionally were the respective results confirmed.

Effect estimators of genetic variants for body weight identified by meta-analysis of genomewide association studies
Effect estimators of genetic variants for body weight identified by meta-analysis of genomewide association studies
Figure 2
Effect estimators of genetic variants for body weight identified by meta-analysis of genomewide association studies

Interestingly, a MC4R variant (V103I) was the first variant to be found and confirmed in large samples: the effect strength is the highest recorded among all polygenic variants discovered so far (18, 19, e4). Heterozygous carriers weigh on average 1.5 kg less than carriers without the I103 receptor allele. This single-nucleotide polymorphism (SNP) in MC4R has a frequency of around 3% in the German population. The I103 receptor variant brings about an increase in MC4R function (e5), so that carriers of the variant presumably have a slightly reduced energy intake and have minimally higher energy expenditure than carriers without the I103 receptor variant.

Beginning in 2005, genome-wide association studies (GWAS) revolutionized molecular genetic research into complex diseases and phenotypes. These analyses permit, in every proband, characterization of over 2 million SNPs distributed more or less evenly throughout the genome. Comparison of the frequencies of SNPs in cases and controls enables identification of chromosome segments that predispose to particular phenotypes (20). One of the largest and most extensive GWAS meta-analyses to date was that on the phenotype BMI by the Genetic Investigation of Anthropometric Traits (GIANT) consortium, covering 46 studies with GWAS data sets from 123 865 individuals of European origin (21). The SNPs with the lowest p-values were investigated further in up to 125 931 additional DNA samples. Altogether, 14 chromosome segments already detected in previous smaller GWAS meta-analyses were confirmed and 18 new segments were identified. The p-value for all of these 32 chromosome segments was under 5 × 10–8, the value generally accepted as genome-wide threshold of significance. Such a low p-value is necessary because of the high number of SNPs that have to be tested to minimize false-positive results.

The frequencies of the alleles that predispose to overweight lie between 4% and 87%; the average BMI increase per allele ranges from 0.06 to 0.39 kg/m2, corresponding to 194 to 1264 g in a 180-cm-tall man (Figure 3). On average, each of the 32 risk alleles increases the BMI by 0.17 kg/m2. Altogether, however, the alleles of all 32 chromosome segments explain only 1.5% of the total variance of BMI. Comparisons of GWAS data sets from children and adolescents with those from adults suggest extensive overlapping of risk alleles for overweight and obesity (2123), so that for the moment there is no molecular genetic explanation for the difference between early- and late-onset obesity. Moreover, the risk alleles identified to date differ hardly at all between persons of European and East Asian origin (e6, e7) (Figure 3).

Combined estimated additive effect of the risk alleles that predispose to overweight on weight increase in a 180-cm-tall adult male from the European population
Combined estimated additive effect of the risk alleles that predispose to overweight on weight increase in a 180-cm-tall adult male from the European population
Figure 3
Combined estimated additive effect of the risk alleles that predispose to overweight on weight increase in a 180-cm-tall adult male from the European population

Little is known to date about the function of the chromosome segments that have been identified. While some SNPs lie directly in genes and thus these genes may be assumed to participate in weight regulation, other SNPs are located between genes, so it is not immediately clear which gene is involved (21). Two chromosome segments will now be described in brief:

  • SNPs located ca. 180 kilobases (kb) from the 3´ end of MC4R yielded one of the strongest association signals. Interestingly, the risk allele also entails greater adult height, 2 mm on average (24). Since there are no other genes in the vicinity of the signal, it can be assumed in light of the known role of MC4R in weight regulation that the risk allele causes reduced expression and thus slightly lowers the melanocortinergic tone.
  • GWAS analysis identified the fat mass– and obesity-associated gene (FTO) as relevant for type 2 diabetes, but only BMI-adjusted analysis demonstrated that the higher risk of type 2 diabetes is explained exclusively by the weight-increasing effect of variants in intron 1 of the gene (25). The BMI of heterozygous (ca. 49% of the European population) and homozygous (16%) carriers is respectively 0.4 and 0.8 kg/m2 higher on average. Expression of the gene is enhanced in carriers of at least one risk allele (26). Transgenic mouse models have shown that absence of FTO results in underweight (27) and overexpression in overweight (28). Homozygous and heterozygous human carriers of the obesity risk allele take up 200 kilocalories more per day (29). The principal substrate of FTO enzyme is the nucleoside N6-methyladenosine, a frequently occurring RNA modification (30).

Copy number variants

Copy number variants (CNV) are duplications, deletions, insertions, and other changes in DNA sequences ranging in length from 1 kb to several megabases (e8). One frequently occurring CNV that involves deletion of a 45-kb sequence of noncoding DNA is correlated with genetic variants of an SNP at the 5´end of the neuronal growth regulator 1 gene (NEGR1). This SNP yielded one of the strongest signals for BMI in the GIANT GWAS meta-analysis (21). Presumably the deletion contains expression-relevant sequences of NEGR1 (31). To what extent other frequently occurring CNV influence body weight remains to be clarified (32). Approximately one in every 250 persons with extreme obesity has a 16p11.2 deletion inherited from a parent. De-novo deletions of this region frequently go together with reduced intelligence and/or congenital anomalies, which may be associated with obesity (33). The deleted region embraces around 30 genes; one of these is SH2B1, in which GWAS meta-analyses had also already identified obesity risk alleles (Figure 3). In contrast, duplications of this region often result in underweight (34).

Missing and hidden heritability of BMI variance

The genetic variability detected by molecular genetic research to date explains around 5% of interindividual BMI variance. By extrapolation (21), analysis of 730 000 GWAS data sets might reveal around 250 further chromosome segments with effect strengths similar to those of the 32 segments identified so far; altogether, up to 10% to 15% of the genetically related BMI variance would then be explained. The preliminary publication of a meta-analysis of around 330 000 individuals (Loos RJF, Vedantam S, Day F, et al.: Meta-analyses of genetic associations in up to 339,224 individuals identify 61 new loci for BMI, confirming a neuronal contribution to body weight regulation and implicating several novel pathways. 30th Annual Scientific Meeting of The Obesity Society, San Antonio, USA, 20–24 September 2012) seem to confirm this projection. If all SNPs of a GWAS are counted, not only those with a very low p-value, up to 17% of BMI variance can already be explained empirically (35).

The possible explanations for the missing or as yet undiscovered (hidden) molecular basis for the empirically postulated high heritability include the following (36):

  • The heritability is systematically overestimated.
  • Variants in many hundreds of genes contribute to BMI variance; such variants could, for example, increase weight by an average of 50 g. Millions of DNA samples would be required to detect such variants reliably. Both metabolic factors and behavior contribute to weight; even just the variable contributions of fat and lean mass to total body weight illustrate the complexity of the underlying biophysiological regulation processes and thus the high number of participating genes.
  • A single gene segment could—as with the MC4R gene—carry genetic variants with opposing weight effects.
  • There could be further, as yet unidentified monogenic forms of obesity, or further major genes that are difficult to detect with the GWAS technology.
  • More accurate phenotyping could help to reveal stronger effects.
  • Nonadditive effects could be important for weight regulation. The variants identified to date seem to be exclusively additive (Figure 3) (21). Complex gene–gene, gene–environment, or genome–environment interactions could considerably hamper detection of the relevant genetic variability.
  • Certain variants might influence a person’s weight only when inherited from the male or from the female parent (imprinting). Other epigenetic mechanisms appear possible.

Outlook

As with other complex phenotypes/disorders, the coding DNA sequences of all genes (the exome) and the whole genome of a large number of obese persons are currently being resequenced. For example, the Wellcome Trust in the UK is funding complete genome resequencing of 4000 individuals and exome sequencing of a further 6000 persons with diseases (including 2000 with extreme obesity) (37). Future studies will show whether rare mutations in specific genes occur more frequently in individuals with (extreme) obesity (common disease–rare variant hypothesis). The potential presence of such mutations must be considered in persons with extreme obesity; the times are over when extreme obesity could be interpreted as the exclusive result of a lack of willpower. The knowledge of existing mutations can also be used for prediction. For instance, we could identify children of normal weight who are at high risk of becoming obese later, and enroll them in obesity prevention programs. However, such a strategy would have to be shown to be superior to general obesity prevention measures before being put into practice.

It cannot at present be reliably estimated what proportion of the variance of BMI can be explained at the DNA level. As in other complex phenotypes, the heritability can only partly be explained by molecular genetic means. A very large number of genetic variants affect body weight. Examples of gene–gene, gene–environment, or genome–environment interactions are virtually unknown as yet but can certainly be assumed to exist. Such interactions could possibly go a long way towards explaining the lack of heritability (38, 39). Treatment strategies are beginning to emerge for carriers of MC4R mutations. Further diagnostic or therapeutic implications of the detected hereditary factors are not yet foreseeable.

Conflict of interest statement

Prof. Hebebrand holds patent DE 501040234. This procedure serves to detect compounds suited to the treatment and prevention of obesity. Furthermore, he has received payments for his work as Editor-in-Chief of the journal “Obesity Facts—the European Journal of Obesity.” As author of the book “Irrtum Übergewicht” he received a honorarium from the publisher, Zabert Sandmann Verlag.

Prof. Hinney, Dipl. troph. Knoll, M.Sc. Biol. Volckmar, and PD Dr. Scherag declare that no conflict of interest exists.

Manuscript received on 2 July 2012, revised version accepted on
7 January 2013.

Translated from the original German by David Roseveare.

Corresponding author:
Prof. Dr. med. Johannes Hebebrand
Kliniken/Institut der Universität Duisburg-Essen
Universitätsklinikum Essen
Klinik für Psychiatrie, Psychosomatik und
Psychotherapie des Kindes- und Jugendalters
Wickenburgstr. 21, 45147 Essen, Germany
johannes.hebebrand@uni-due.de

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Department of Child and Adolescent Psychiatry, LVR-Klinikum Essen, University of Duisburg-Essen:
Prof. Dr. med. Hebebrand, Prof. Dr. rer. nat. Hinney, Dipl. troph. Knoll, M.Sc. Biol. Volckmar
Institute for Medical Informatics, Biometry and Epidemiology, University of Duisburg-Essen:
PD Dr. rer. physiol. Scherag
Leptin is generated in adipose tissue and transported via the bloodstream to the hypothalamus. The binding of leptin to leptin receptors (ObRb) stimulates the expression of cocaineand amphetamine-regulated transcript (CART) and pro-opiomelanocortin (POMC)
Leptin is generated in adipose tissue and transported via the bloodstream to the hypothalamus. The binding of leptin to leptin receptors (ObRb) stimulates the expression of cocaineand amphetamine-regulated transcript (CART) and pro-opiomelanocortin (POMC)
Figure 1
Leptin is generated in adipose tissue and transported via the bloodstream to the hypothalamus. The binding of leptin to leptin receptors (ObRb) stimulates the expression of cocaineand amphetamine-regulated transcript (CART) and pro-opiomelanocortin (POMC)
Effect estimators of genetic variants for body weight identified by meta-analysis of genomewide association studies
Effect estimators of genetic variants for body weight identified by meta-analysis of genomewide association studies
Figure 2
Effect estimators of genetic variants for body weight identified by meta-analysis of genomewide association studies
Combined estimated additive effect of the risk alleles that predispose to overweight on weight increase in a 180-cm-tall adult male from the European population
Combined estimated additive effect of the risk alleles that predispose to overweight on weight increase in a 180-cm-tall adult male from the European population
Figure 3
Combined estimated additive effect of the risk alleles that predispose to overweight on weight increase in a 180-cm-tall adult male from the European population
Key messages
1. Richter-Kuhlmann EA: Gesundheitssurvey des Robert-Koch-Instituts: Zivilisationskrankheiten nehmen zu. Dtsch Arztebl 2012; 109(26): A 1376. VOLLTEXT
2.Lenz M, Richter T, Mühlhauser I: The morbidity and mortality associated with overweight and obesity in adulthood: a systematic review. Dtsch Arztebl Int 2009; 106: 641–8. VOLLTEXT
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