International Journal of Obesity (2011) 35, 364–372 & 2011 Macmillan Publishers Limited All rights reserved 0307-0565/11 www.nature.com/ijo ORIGINAL ARTICLE The growth hormoneFIGF-I axis as a mediator for the association between FTO variants and body mass index: results of the Study of Health in Pomerania

D Rosskopf1,7, C Schwahn2,7, F Neumann1, A Bornhorst1, C Rimmbach1, M Mischke1, S Wolf1, I Geissler1, T Kocher3, H-J Grabe4, M Nauck2, J Hebebrand5, HK Kroemer1, N Friedrich2,HVo¨lzke6 and H Wallaschofski2

1Department of Pharmacology, Center for Pharmacology and Experimental Therapeutics, Ernst-Moritz-Arndt University, Greifswald, Germany; 2Institute for Clinical Chemistry and Laboratory Medicine, Ernst-Moritz-Arndt University, Greifswald, Germany; 3Dentistry Clinic, Ernst-Moritz-Arndt University, Greifswald, Germany; 4Department of Psychiatry and Psychotherapy, Ernst-Moritz-Arndt University, Stralsund, Germany; 5Department of Child and Adolescent Psychiatry, University of Duisburg-Essen, Essen, Germany and 6Institute for Community Medicine, Ernst-Moritz-Arndt University, Greifswald, Germany

Context: Risk alleles of the fat mass- and obesity-associated gene (FTO) are related not only to increased body mass index (BMI) values but also to mortality. It was speculated that cellular effects of the FTO gene affect most organs, especially their ability to maintain or regenerate proper function when afflicted by various diseases. FTO is highly expressed in the hypothalamus and also in the pituitary gland. The decrease in growth hormone (GH) secretion is known to cause a decrease in lean body mass in older subjects. Objective: We hypothesized an association of rs9926289 with insulin-like growth factor (IGF)-I. Design and setting: Cross-sectional data from the Study of Health in Pomerania, a population-based study in the northeastern part of Germany, were used. Participants: For the final analyses, 3882 subjects aged 20–79 years were available. Main outcome measures: Continuous IGF-I, low IGF-I according to clinically meaningful age- and gender-specific reference values, and BMI were used as outcome measures. Results: Over all age groups, a statistically significant relationship between FTO and IGF-I was found. In subjects younger than 55 years of age, homozygous carriers of the FTO risk allele exhibited lower serum IGF-I levels adjusted for 5-year age groups, gender and IGF-I binding protein 3 levels (linear regression, coefficient±s.e. for FTO AA genotype:À8.6±2.8; P ¼ 0.002). Further adjustments for obesity and diabetes did not suspend this association (coefficient:–7.8; P ¼ 0.005). As expected, the FTO AA genotype effect on BMI was reduced from 0.76 to 0.62 kg mÀ2 by including IGF-I. No relationship between FTO and IGF-I levels was found in subjects aged 55 years or older (À2.7±2.4; P ¼ 0.260 for FTO AA genotype adjusted for age, gender and IGF-I binding protein 3 levels). Conclusion: We propose that the GHFIGF-I axis is a mediator for the relationship between FTO and BMI. International Journal of Obesity (2011) 35, 364–372; doi:10.1038/ijo.2010.158; published online 24 August 2010

Keywords: body weights and measures; insulin-like growth factor I; epidemiology; genetics

Introduction major risk factors for hypertension, dyslipidemia, type 2 diabetes, coronary heart disease, gallstones, fatty liver The obesity epidemic is a growing health problem in many disease and some cancer entities, to name a few. Obesity countries of the world because obesity and overweight are is defined as a body mass index (BMI) X30 kg mÀ2, and overweight as a BMI X25 kg mÀ2. BMI heritability is B 1 Correspondence: Dr C Schwahn, Institute for Clinical Chemistry and estimated at 60–70%. Laboratory Medicine, Ernst-Moritz-Arndt University, Ferdinand-Sauerbruch- Common variants in the first intron of the fat mass- and Strae, Greifswald, D-17475, Germany. obesity-associated gene (FTO) are related to increased BMI and E-mail: [email protected] 7 in turn to type 2 diabetes mellitus in genome-wide These two authors contributed equally to this work. 2–6 Received 27 September 2009; revised 5 May 2010; accepted 24 June 2010; association studies. Of all genetic factors contributing to published online 24 August 2010 polygenic obesity identified in genome-wide association IGF-I may link FTO risk variants and increased BMI D Rosskopf et al 365 studies, the effects of FTO variants are most pronounced. the liver on stimulation with GH and mediates most of When compared with subjects carrying no copy of the GH’s endocrine actions, including regulation of cell proli- risk allele, individuals homozygous for the risk allele had a feration, protein synthesis, carbohydrate homeostasis, bone 1.67-fold increased odds ratio for obesity, and mean body metabolism and the modulation of body composition.26–28 weights differed by almost 3 kg.3 The relationship between In this study, we suggest that IGF-I partly mediates the FTO risk alleles and BMI is due to an increase in fat mass;3 association between the FTO risk allele and BMI. however, the precise mechanisms by which risk alleles of FTO precipitate increased BMI have remained elusive. In manFpredominately in childrenFincreased energy Materials and methods intake7–9 and decreased satiety9 were suggested to link FTO risk alleles with obesity, findings, however, not unan- Study population imously reported.10 In contrast, reduced energy expenditure SHIP is a cross-sectional population-based health survey in and physical activity were not associated with FTO geno- West Pomerania, a region in the northeastern part of types.7,8,10,11 Nevertheless, physical activity modified the Germany. The detailed objectives and study design have degree of obesity achieved in the context of the risk allele of been published elsewhere.21 In brief, from a total population FTO.12,13 of 212 157 inhabitants, a sample of 6267 eligible subjects was These pathomechanisms in man differed from mice lacking drawn on the basis of the official population registry. the Fto gene.14 In this animal model, variant energy expendi- Inclusion criteria comprised of German citizenship and ture is part of a main phenotype. In such mice, a significant principal residency in the study area. The selection strategy reductioninadiposetissue,leanbodymassandpostnatal aimed at generating 12 equal 5-year age strata for both growth retardation were observed.14 Loss of Fto results genders each, representing an age range from 20 to 79 years. obviously in increased energy expenditure and systemic Finally, SHIP comprised of 4310 participants, corresponding sympathetic activation, despite relative hyperphagia and to a final participation proportion of 68.8%. Data collection spontaneous locomotor activity.14 Another type of mouse started in October 1997 and was completed in May model harbouring a deficient Fto protein with a missense 2001. The study protocol was reviewed by a board mutation supported the increased energy spending.15 of independent scientists and approved by the Ethics The ubiquitously occurring Fto is most abundantly Committee of the University of Greifswald. All participants expressed in the hypothalamus and the pituitary gave a written informed consent. gland,3,14,16–18 a plausible brain region, as most obesity Sociodemographic and medical characteristics were genes identified by genome-wide association are expressed assessed by computer-assisted personal interviews. Diabetes here.19 In the arcuate nucleus of the hypothalamus, rodent mellitus was defined as a self-reported history of diabetes Fto mRNA levels have been reported to be regulated by that was diagnosed by a physician. In preliminary analyses, feeding and fasting.16,18,20 Despite these attractive animal pregnant women (n ¼ 17) and subjects with cancer (n ¼ 51) models, comprehensive information of the role of FTOF were excluded. These exclusion criteria produced similar especially in manFis scarce. results, and all models presented are without any exclusion In this study, we examined the effects of the risk allele of criterion. Height and weight were measured for the calcula- FTO on different indexes of fatness in the Study of Health in tion of BMI. Overweight was defined as BMI of X25 kg mÀ2 Pomerania (SHIP),21 a population-based study in north- and obesity as BMI of X30 kg mÀ2. Waist and hip circum- eastern Germany, a region with high prevalence of over- ferences were measured by trained study nurses. weight and obesity. We found that the effect of FTO on BMI gradually diminished in men and women with advancing age, an observation shared by others.3,22–24 Jacobsson et al. Hormone analyses found no association between FTO and BMI when they GH is released in a pulsatile manner and adequate examina- analysed a cohort of 1115 men, who were repeatedly tions of GH secretion require repeated blood samplings, examined each decade starting from the age of 50 years.23 procedures that are highly unsuitable for epidemiological Similarly, Hardy et al. reported that the association between surveys. Determination of serum IGF-I concentration is FTO and BMI increased during childhood and adolescence, widely used as a stable biomarker for the long-term status peaked at around 20 years, diminished gradually with of GH secretion in clinical practice. Non-fasting blood advanced age and levelled off by the age of 53 years.22 samples were drawn from the cubital vein in the supine Given the age-dependent reduction of growth hormone position. The samples were stored at À80 1C until assay. In (GH) and insulin-like growth factor-I (IGF-I),25 we hypo- September 2005, serum IGF-I and IGF binding protein 3 thesized that the risk alleles of FTO were associated with the (IGFBP3) were determined by automated two-site chemi- GH–IGF-I axis. Biological evidence is based on the abundant luminescence immunoassays (Nichols Advantage; Nichols expression of FTO in the hypothalamus and pituitary gland, Institute Diagnostica GmbH, Bad Vilbel, Germany). In both both key organs for the GH–IGF-I axis and also for weight assays, biotin-labelled monoclonal antibodies were used as control. Circulating IGF-I is predominantly synthesized in capture, and in a second step, acridinium–ester-labelled

International Journal of Obesity IGF-I may link FTO risk variants and increased BMI D Rosskopf et al 366 monoclonal antibodies were used for detection. To deter- analyses of a binary outcome were performed by logistic mine IGF-I concentration, the samples underwent preana- regression. Odds ratio and its 95% confidence interval are lytical acidification to separate IGF-I from IGF-binding given. We used the criterion of change in the coefficient proteins. The analytical sensitivity of the IGF-I assay was of interest (for example, FTO) to estimate the effect of 6ngmlÀ1, the intraassay imprecision within the range of a confounder or a putative mediator on the relationship 63–766 ng mlÀ1 was 4.8% and interassay imprecision within analysed (for example, between FTO and BMI). A substantial the range of 62–811 ng mlÀ1 was 6.7%. The IGF-I assay has change was considered present if inclusion in the model led been calibrated against the World Health Organization to a X10% change in the coefficient of interest. A value of International Reference Reagent 1988, IGF-I 87/518. The Po0.05 was considered statistically significant. Analyses analytical sensitivity of the IGFBP3 assay was 20 ng mlÀ1, the were performed with STATA/SE software, version 10.1 intra and interassay imprecision rates within the range of (StataCorp LP, College Station, TX, USA). Smoothed plots 227–2703 ng mlÀ1 were 5.8 and 11%, respectively. The assay were used to show age and genotype dependencies in more reference standard was analytically prepared with glyco- detail. They were generated with the STATA command sylated recombinant human IGFBP3. Only one lot of ‘lowess’. For the amount of smoothing, we chose a reagents was used for all IGFBP3 measurements. For IGF-I bandwidth ¼ 0.8, indicating that 80% of the data are used concentration, a diurnal variation was reported.29 Values in smoothing each point. from midnight until 0400 h were slightly lower. This period, however, does not meet for SHIP. In additional analyses, we used clinically meaningful Results categories of ‘low’, ‘normal’ and ‘high’ serum IGF-I levels on the basis of reference values for clinical purposes derived Out of the 4310 participants of SHIP, 48 dissented to genetic from healthy SHIP participants.30 These reference values analyses and no DNA was available from 81 individuals. were assayed with the same method as described above. Genotyping failed in 113 individuals (call rate 97.3%). On the basis of quantile regression and the resulting gender- Owing to missing IGF-I or IGFBP3 levels, an additional and age-specific reference ranges,30 the highest 2.5% was 178 individuals were excluded. For a further eight indivi- considered to be ‘high’, whereas the lowest 2.5% was duals, no BMI could be calculated. Out of the remaining considered to be ‘low’. 3882 individuals available for the final analyses, 1359 (35.0%) subjects were carriers of the rs9926289 GG allele, 1851 (47.7%) were heterozygous and 672 (17.3%) subjects Genotyping carried the AA genotype. This distribution of rs9926289 We genotyped rs9926289, a polymorphism 24-bp adjacent was in accordance with the Hardy–Weinberg equilibrium to rs9939609, the single-nucleotide polymorphism ana- (P40.200) and mirrored the genotype distribution of lysed in the first study by Frayling et.al 3 HapMap analyses rs9939609 in other studies.3 revealed that rs9926289 and rs9939609 are completely Next, we analysed BMI, weight, waist and hip circumfer- linked. Furthermore, rs9926280 was identified as another ences and waist-to-hip ratio of all the participants of the variant strongly associated with BMI in this paper.3 The SHIP study, adjusted for gender and for 5-year age groups locus comprising rs9926289 was amplified using primers (Table 1a). No measures of fatness were associated with the 50-GAGGTTGCTCTGACGGCTGTAG-AGGATAGACCATAG-30 risk allele of FTO, either in an additive model or in a recessive and 50-GCCAGGATAGTTTCGATCTATTGACCTCATG-30. The one (Table 1a). PCR amplicon of 881 bp was digested for the variant A-allele When we analysed the age-dependent BMI and weight into two fragments of 551 and 330 bp with the restriction patterns, we noticed that mean BMI values levelled off and enzyme XbaI (Fermentas, Str Leon-Rot, Germany), whereas mean weight exhibited a turning point at around 55 years the wild-type G-allele remained unrestricted. In all, 200 (Figures 1a and b). As indicated in Introduction, such age- random samples were regenotyped and we observed only dependent effects of FTO were observed by others22–24 and, one divergent result (0.05%). coincidentally, the limit beyond which FTO had only a weak or absent effect on BMI was calculated at 53 years by Hardy et al.22 Subsequently, we chose 55 years of age as cutoff point. Statistical analysis For both age strata, the genotype distribution was in Data on quantitative characteristics are expressed as accordance with Hardy–Weinberg equilibrium (P40.200). means±s.d. or s.e., as indicated. Data on qualitative Table 1b shows data for individuals between 20 and 54 years characteristics are expressed as percentage values or absolute of age. FTO risk alleles were significantly associated with numbers as noted. Multivariable analyses of a continuous different indices of fatness. BMI amounted to 26.1±0.2 and outcome were performed by linear models. BMI was 26.9±0.2 for subjects with rs9926289 GG and AA genotypes, routinely treated as a linear value. However, BMI is not respectively. For homozygous individuals with the A allele, normally distributed. Analyses of log-transformed BMI mean weight differed by 2.3 kg from those homo- or values produced essentially the same results. Multivariable heterozygous for the G allele.

International Journal of Obesity IGF-I may link FTO risk variants and increased BMI D Rosskopf et al 367 In SHIP participants beyond the age of 55 years, however,

3859; BMI, weight, waist and hip circumferences were virtually ¼ value n

P- identical between the different FTO genotypes (Table 1c). Figures 1c and d illustrate the age-dependent effects of the FTO genotypes on BMI values.

55 years, dependent We questioned the biological rationale for this age- X dependent effect, that is, the risk allele of FTO had its most 0.59 0.664 0.003 0.919 0.002 0.819 0.72 0.665 0.52 0.007 0.39 0.090 0.84 0.341 0.61 0.064 0.47 0.300 0.77 0.009 0.57 0.199 0.004 0.856 0.29 0.446 0.25 0.013 0.19 0.221 pronounced and dynamic effect in periods when weight gain ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± was the highest. Potentially, this life-course variation was 0.26 0.31 0.80 0.22 À À À À 0.0003 0.0005 0.0007 indicative of secretory patterns of the GH–IGF-I axis. Figure 2 À À À 2212). (c) Age illustrates this age-dependent pattern for IGF-I. It is note- ¼ n worthy that mean IGF-I levels differed only minutely beyond the age of 55 years. The analysis of mean IGF-I levels across all age groups revealed lower levels for homozygous carriers -value Effect of FTO alleles P of the FTO risk allele (Table 2a). This association was more pronounced in subjects younger than 55 years of age (Table 2a). Adjustment for age, gender, IGFBP3 and obesity 0.004 0.923 0.59 0.685 0.003 0.716 0.002 0.885 0.72 0.714 0.53 0.002 1.42 0.39 0.045 0.67 0.62 0.017 1.14 0.47 0.146 0.49 0.84 0.372 0.77 0.003 2.01 0.57 0.105 0.73 0.25 0.002 0.62 0.29 0.495 0.19 0.095 0.23 or BMI left the association between FTO genotype and IGF-I ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± stable. Additional adjusting for diabetes mellitus changed 0.24 0.26 0.75 0.20 2213; waist or hip measures: À À À À ±

0.0003 FTO

¼ the coefficient of only marginally, from À7.8 2.8 to À n À7.9±2.8 (n ¼ 2211). To analyse the clinical relevance of the FTO effect on IGF-I levels, we classified IGF-I values into ‘low’ (n ¼ 143) and -value Effect of FTO alleles

P ‘normal’ or ‘high’ (n ¼ 3739) categories. Given the consider- able age dependence of IGF-I levels, we have compiled reference values for clinical purposes derived from healthy 30 0.002 0.885 0.32 0.685 0.002 0.182 0.001 0.001 0.400 0.0003 0.39 0.799 0.28 0.022 1.62 0.21 0.186 0.79 0.33 0.017 1.48 0.25 0.142 0.68 0.46 0.453 0.41 0.016 2.32 0.31 0.225 0.93 0.1 0.010 0.76 0.16 0.766 0.10 0.125 0.32 SHIP participants. Odds ratio of all SHIP participants 1668) ± ± ± ± ± ± ± ± ± ± ± ± ± ± ±

¼ homozygous for the rs9926289 A allele to be in the ‘low’ n 0.13 0.10 0.34 0.05 IGF-I category amounted to 1.6 and 2.0 before and after À À À À 0.0003 À Age- and gender adjusted only Age- and gender adjusted only Additionally adjusted for IGF-I and IGFBP3

Effect of FTO alleles adjustments for age, gender and IGFBP3 (Table 2b). For subjects younger than 55 years of age, homozygous carriers of the risk allele had more than twice the odds of belonging 0.003 0.5 0.003 0.002 0.002 0.001 0.7 0.5 0.65 0.4 0.28 0.6 0.79 0.4 0.37 0.8 0.7 0.99 0.5 0.38 0.2 0.34 0.2 0.16 0.3 to the ‘low’ IGF-I level group (Table 2b). A significant ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± relationship between IGFBP3 levels and the alleles of rs9926289 was not found. The association between FTO and BMI (or other measures

1669; waist or hip measures: of body composition) was partially mediated by IGF-I and 0.002 0.90 0.2 105.5 0.001 0.84 0.001 0.87 0.3 94.5 0.2 102.1 0.2 103.5 0.3 86.5 0.2 89.9 0.4 78.4 0.3 78.9 0.2 78.7 0.1 26.9 0.1 27.6 0.1 28.5 ¼ ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± n IGFBP3, the coefficient of the FTO rs9926289 AA genotype was diminished more than 10% in subjects younger than linear models for cross-sectional data. (a) All age groups, dependent variable (parameter) adjusted for 5-year age groups and gender ( 55 years of age (Table 1b). F We repeated the analyses with age cutoff points of 50 and s.e. 0.002 0.90 0.3 105.7 0.002 0.84 0.001 0.87 0.4 94.8 0.3 100.5 0.2 102.8 0.3 85.0 0.3 89.2 0.5 79.3 0.4 76.6 0.3 77.8 0.1 26.2 0.1 27.2 0.2 28.7

± 60 years instead of 55 years. Although the former strength- ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ened the relationship between FTO and BMI in males, but

55 years, dependent variable (parameter) adjusted for 5-year age groups and gender ( weakened it in females, the latter showed a vice versa result o genotype groups compared with an age cutoff point of 55 years. In non- 0.002 0.90 0.4 105.7 0.002 0.85 0.002 0.87 0.5 94.8 0.3 100.5 0.3 102.7 0.4 85.2 0.3 89.3 0.5 79.2 0.5 76.6 0.4 77.8 0.2 26.2 0.1 27.3 0.2 28.7 gender-stratified analyses, for both altered cutoff points, the FTO ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± FTO effect on IGF-I and the mediator effect of IGF-I in the s.e. or as coefficient FTO

± relationship between and BMI were still present in

3857). (b) Age younger age groups, but to a lower extent compared with the ) 27.2 ) 28.6 ) 26.1 ¼ 2 2 2 n À À À analyses presented.

Discussion Body composition across

As there is, beyond a doubt, an associative role of FTO Waist to hip ratio 0.90 c Body mass index (kg m b Body mass index (kg m Hip circumference (cm) 105.8 Waist to hip ratio 0.84 Waist to hip ratio 0.86 Waist circumference (cm) 94.7 Hip circumference (cm) 100.5 Hip circumference (cm) 102.8 Waist circumference (cm) 84.8 Waist circumference (cm) 89.1 Weight (kg) 79.4 Weight (kg) 76.6 Weight (kg) 77.8 Table 1 Parameter GG AG GG/AG AAData are presented as mean Additive model Recessive model a Body mass index (kg m variable (parameter) adjusted for 5-year age groups and gender ( waist or hip measures: on BMI in Caucasians, in-depth (patho)physiological

International Journal of Obesity IGF-I may link FTO risk variants and increased BMI D Rosskopf et al 368 32 32 31 31 30 30 29 29 28 28 27 27 26 26 25 male 25 FTO Genotype AA 24 female 24 23 AG

Body Mass Index [kg/m²] 23 Body Mass Index [kg/m²] 22 22 GG 20 25 30 35 40 45 50 55 60 65 70 75 80 20 25 30 35 40 45 50 55 60 65 70 75 80 Age [years] Age [years]

95 32 90 31 85 30 29 80 28 27 75 26 Weight [kg] 70 25 FTO Genotype male 24 AA 65 female 23 AG Body Mass Index [kg/m²] 60 22 GG 20 25 30 35 40 45 50 55 60 65 70 75 80 20 25 30 35 40 45 50 55 60 65 70 75 80 Age [years] Age [years]

Figure 1 Relationship between age and body mass index (a) or weight (b), stratified by gender. Relationship between age and body mass index across FTO genotypes in males (c) and females (d). Data of error bars are means (95% confidence intervals) of 5-year age groups. The curves of points refer to smoothed plots of continuous age. For the amount of smoothing, we chose a bandwith ¼ 0.8, indicating that 80% of the data are used in smoothing each point.

250 (ii) FTO effects on body composition are partially mediated 240 by the GH–IGF-I axis. These results deserve a detailed 230 220 discussion. 210 200 190 Enzymatic and molecular actions of FTO 180 170 FTO is a member of the AlkB-related non-heme dioxygenase 160 (Fe(II-)- and 2-oxoglutarate-dependent dioxygenases) super- IGF-I [ng/ml] 150 family of proteins.20,31–34 These non-heme iron enzymes, 140 which require Fe2 þ as a cofactor and 2-oxoglutarate and 130 120 male dioxygen as cosubstrates, reverse alkylated DNA and RNA 110 female damages by oxidative demethylation. In vitro FTO protein 100 had a strong preference for 3-methythymidine in single- 20 25 30 35 40 45 50 55 60 65 70 75 80 stranded DNA and for 3-methyluracil in single-stranded Age [years] RNA, although these methyl residues are uncommon in man. Another study has shown that more common motifs Figure 2 Relationship between age and insulin-like growth factor-I (IGF-I) stratified by gender. Data of error bars are means (95% confidence intervals) as 1-methyladenine and 3-methylcytosine were substrates 35 of 5-year age groups. The curves of points refer to smoothed plots of of FTO, although with less activity. A link between FTO continuous age. For the amount of smoothing we chose a bandwidth ¼ 0.8, demethylase activity and obesity was suggested by the indicating that 80% of the data are used in smoothing each point. observation that a single mutation in mouse FTO protein (Ile367Phe) lost its enzymatic action and was associated with a lean phenotype. mechanisms of the control in weight gain by FTO are largely Given that FTO belongs to the family of DNA repair elusive. The main findings of this study are (i) evidence of a enzymes, this issue could spark interest in the GH–IGF-I axis. clinically meaningful association between FTO risk alleles In animal models, disordered genomic repair mechanisms and lower IGF-I levels, which may spark a concept in which cause obesity and metabolic syndromes.36–39 Moreover,

International Journal of Obesity IGF-I may link FTO risk variants and increased BMI D Rosskopf et al 369 Table 2 IGF-I serum concentration across FTO genotype groups for cross-sectional data

Successive adjustment o55 years of age (n ¼ 2213) X55 years of age (n ¼ 1669) All age groups (n ¼ 3882)

Coefficient (±s.e.) P-value Coefficient (±s.e.) P-value Coefficient (±s.e.) P-value

(a) Linear regressiona Unadjusted À8.6±3.3 0.010 À1.8±2.8 0.510 À6.1±2.4 0.013 Age and gender À7.5±2.9 0.010 À1.4±2.8 0.613 À4.8±2.0 0.019 +IGFBP3 À8.6±2.8 0.002 À2.6±2.4 0.275 À5.9±1.9 0.002 +Obesity À7.8±2.8 0.005 À2.6±2.4 0.270 À5.6±1.9 0.003

Successive adjustment o55 years of age (n ¼ 2213) X55 years of age (n ¼ 1669) All age groups (n ¼ 3882)

Odds ratio 95% CI P-value Odds ratio 95% CI P-value Odds ratio 95% CI P-value

(b) Logistic regression for ‘low’ vs. ‘normal’ or ‘high’ IGF-I levels according to clinically meaningful age- and gender-specific reference valuesb Unadjusted 2.4 1.4–4.0 0.001 1.1 0.6–2.0 0.763 1.6 1.1–2.4 0.012 Age and gender 2.4 1.4–4.2 0.001 1.1 0.6–2.0 0.767 1.6 1.1–2.4 0.012 +IGFBP3 3.1 1.8–5.3 o0.001 1.1 0.6–2.2 0.691 2.0 1.3–3.0 0.001 +Obesity 2.7 1.5–4.8 0.001 1.2 0.6–2.3 0.603 1.9 1.2–2.9 0.003

Abbreviations: CI, confidence interval; IGFBP3, IGF binding protein 3; OR, odds ratio; s.e., standard error. aThe coefficient of the FTO risk allele (recessive model) was successively adjusted for age (5-year age groups) and gender, IGFBP3 and obesity. The results remained essentially the same when body mass index instead of obesity was included in the model (coefficient: À7.9±2.8; P ¼ 0.004 for subjects o55 years of age). If pregnant women and individuals with cancer were omitted, this did not change the effect. bThe odds ratio of the FTO risk allele (recessive model) was successively adjusted for age (5-year age groups) and gender, IGFBP3 and obesity. The results remained essentially the same when body mass index instead of obesity was included in the model (OR 2.8; 95% CI, 1.6–4.9; Po0.001 for subjects o55 years of age). If pregnant women and individuals with cancer were omitted, this did not change the effect.

disordered DNA repair seems to be tightly linked to an high prevalence of overweight and obesity.2–6 These findings inhibited GH secretion and to distinctly reduced IGF-I levels are restricted essentially to men and women younger than and has been implicated in mechanisms of ageing.36–39 55 years of age, a life-course effect of FTO reported However, linking FTO to these syndromes in the absence of repeatedly.3,22–24 Obviously, mean gains in weight and BMI experimental evidence is entirely notional. mediated by FTO are most dynamic in younger and middle- A recent genetic study in man reported circumstantial age spans of life, periods that are often disease free. We evidence that DNA methylation controlled appetite.40 In hypothesized on the biological rationale of this effect and detail, epistatic interaction between the risk allele of FTO, we identified the GH–IGF-I axis as a possible candidate. alleles of the leptin receptor and alleles of DNMT3B (DNA (cytosine-5-)-methyltransferase 3b) regulated postprandial responses in hunger and satiety. It is obvious to speculate Role of FTO in the hypothalamus that DNMT3B and FTO have a role in DNA methylation/ Although FTO transcripts are widely expressed, all reports demethylation. agree that highest levels are found in the brain with the It is noteworthy that the crystal structure of the FTO highest abundance in the hypothalamus.3,14,16–18 Refined protein was recently elucidated.32 As FTO closely resembled in situ hybridization studies detected prominent expression other AlkB proteins, specific features were established; levels in regions that are critically involved in energy for instance, an extra loop in the structure. The authors balance control, such as the arcuate, paraventricular, dorso- suspected that single-stranded RNAFand not DNAFis the medial and ventromedial nuclei.20 High hypothalamic primary substrate of FTO. Thus, specific demethylation of FTO transcript levelsFagain with high local abundance in 3-methyluracil could affect the half-life or specific functions the arcuate nucleusFhave also been reported in animal of target RNAs by FTO.32 Eventually, this mechanism could models.16–18,41 Tung et al. showed that fasting reduced FTO create a new principle in cell signalling. So far, it remains levels in the arcuate nucleus, whereas a high-fat diet resulted impossible to predict the physiological substrates of FTO. in a 2.5-fold increase.18 Manipulating FTO in the arcuate nucleus by stereotactic injections altered food intake, but did not affect transcription of gene in the arcuate nucleus FTO and body mass index classically associated with food intake, such as agouti-related As already referred to in the introductory section of this protein homologue, proopiomelanocortin and neuro- report, FTO is the strongest common genetic variation peptide Y.18 However, the transcription of Stat3 was distinctly associated with BMI and obesity.2–6 We could confirm the modified by the FTO microinjection. Stat3 is a signalling association of the FTO rs9926289 A allele with BMI and body molecule critical for leptin receptor signalling,18 but is also weight for SHIP, which comprises a German population with implicated in GH-releasing hormone receptor signalling.42

International Journal of Obesity IGF-I may link FTO risk variants and increased BMI D Rosskopf et al 370 The hypophyseal secretion of GH is mainly regulated by or unchanged IGF-I levels in obesity was recently resolved by three hypothalamic peptides that are secreted into the a large study of more than 6000 subjects over the whole pituitary portal blood: GH-releasing hormone, somatostatin range of BMI. The DETECT study supported a biphasic and ghrelin. The arcuate nucleus is the major origin of relation of IGF-I and BMI.54 Both, a BMI of less than 20 or GH-releasing hormone.43,44 Ghrelin, an appetite-stimulating higher than 35 kg mÀ2, were associated with a lower serum circulating hormone from the stomach and intestine, is a IGF-I level than a BMI between 20 and 35 kg mÀ2. The waist- potent stimulator of pituitary GH secretion.45 Ghrelin is also to-hip ratio in this cohort was negatively correlated to IGF-I, locally produced in the arcuate nucleus.44 supporting an influence of visceral fat. Given the coincidence of high FTO expression levels In our study, adjustment for obesity or BMI did not in hypothalamic areas that control GHFand thus IGF-IF suspend the association of FTO variants with IGF-I levels. secretion, a potential role of FTO in GH regulation remains Solely in older and commonly obese individuals was the to be established. Although the available studies on association of FTO variants with IGF-I levels no longer hypothalamic FTO transcript regulation in animals revealed detectable. However, this observation does not contradict a discrepant details, they conclusively showed that starvation scenario in which reduced IGF-I levels in association with actually affected hypothalamic FTO expression.17,20,41 There the FTO risk alleles contribute to an increase in BMI during is even circumstantial evidence that GH-releasing hormone dynamic phases of weight gain, even in preadipose states. levels in the hypothalamus are negatively correlated with FTO 41 levels. FTO, IGF-I morbidity and mortality It has long been established that fasting in man enhances Accumulating evidence suggests that IGF-I is an independent GH secretion and affects GH release rhythms, which 55,56 risk factor for mortality. For SHIP, inverse associations could hint at common mechanisms46,47 linking starvation- between IGF-I or IGFBP3 levels and mortality from all causes, dependent FTO expression and GH release. However, CVD or cancer in men, and between IGFBP3 and all-cause detailed experimental evidence remains to be established. 57 mortality in women, were found. Interestingly, for FTO, reports exist that the increase in mortality cannot be explained solely by its FTO effect on obesity and The GH–IGF-I axis and FTO 58,59 diabetes. In a cohort of Danish men, the A allele of The measurement of GH itself is not suitable for epidemio- FTO had an effect on mortality similar to that of smoking. logical studies because of its pulsatile release pattern. There- Adjustment for fatness covariates attenuated the association fore, quantification of serum IGF-I levels is widely used for the 59 only slightly. This effect was due to all-cause mortality and assessment of the GH–IGF-I axis, both in clinical and 59 particularly due to diseases of the nervous system. experimental medicine.48,49 Our data showed that age- and Recently, another group reported on the association between gender-adjusted serum IGF-I levels are significantly lower in the risk allele of FTO and reduced brain volume in the homozygous carriers of the FTO rs9926289 A allele. Moreover, 60 healthy elderly. It is tempting to speculate whether IGF-I when we analysed clinically relevant ‘low’ IGF-I levels, we could be the mediator between FTO risk allele and increased detected odds ratios for participants homozygous for the morbidity and mortality. rs9926289A allele in the range of 1.6–2.0. Numerous studies reveal a strong genetic basis for IGF-I level. A longitudinal study followed up over a period of 20 years demonstrated in a Conclusion set of healthy individuals a marked dissociation in individual IGF-I serum level, which, in some individuals, never over- In conclusion, we have provided evidence from an epide- lap.50 Studies in a large Swedish cohort of 248 twins revealed a miological survey that FTO risk variants are related to an relative genetic influence of 63% for IGF-I, clearly higher than increased BMI. Moreover, the FTO risk alleles were associated that observed in the same study for interlinked factors with lower IGF-I levels independently of obesity or IGFBP3. such as insulin (48%) or IGFBP1 (36%).51 More importantly, FTO is expressed in the brain in hypothalamic regions that the comparison between monozygotic and dizygotic twins, as govern the GHFIGF-I axis. Starvation affects FTO transcript well as the influence of environmental factors evaluated by levels in these brain nuclei. The genetic mechanisms twins reared apart or together, clearly supported a dominant associated with FTO risk alleles comprise, most likely, an genetic influence with a much higher correlation of IGF-I altered FTO transcription. FTO itself is an enzyme involved levels in monozygotic compared with dizygotic twins and in RNA or DNA repair. It is unclear whether FTOFas other little influence of the environment. FTO may constitute such enzymes in this familyFexhibits sensory actions that are a genetic factor for the homeostasis of IGF-I. translated into RNA or DNA modifications. Interestingly, altered DNA repair has a strong effect on IGF1 serum levels. Although these pieces may fit into a mechanistic scheme, IGF-I and obesity the mutual interactions and the elucidation of causal Obesity has been associated with decreasing IGF-I levels.52,53 relationships await further experimental research to supple- The apparent discrepancy in the results showing decreased ment the epidemiological evidence presented here.

International Journal of Obesity IGF-I may link FTO risk variants and increased BMI D Rosskopf et al 371 Conflict of interest leisure-time physical activity. J Clin Endocrinol Metab 2009; 94: 1281–1287. 11 Jonsson A, Renstrom F, Lyssenko V, Brito EC, Isomaa B, Berglund G The authors, apart from JH, have nothing do disclosure. et al. Assessing the effect of interaction between an FTO variant JH received German national grants. He also received (rs9939609) and physical activity on obesity in 15 925 Swedish and honoraria, but not directly related to this work, from Roche. 2511 Finnish adults. Diabetologia 2009; 52: 1334–1338. 12 Andreasen CH, Stender-Petersen KL, Mogensen MS, Torekov SS, Wegner L, Andersen G et al. Low physical activity accentuates the effect of the FTO rs9939609 polymorphism on body fat Acknowledgements accumulation. Diabetes 2008; 57: 95–101. 13 Mitchell JA, Church TS, Rankinen T, Earnest CP, Sui X, Blair SN. FTO genotype and the weight loss benefits of moderate intensity SHIP is part of the Community Medicine Net (http://ship. exercise. Obesity (Silver Spring) 2010; 18: 641–643. community–medicine.de) of the Ernst Moritz Arndt 14 Fischer J, Koch L, Emmerling C, Vierkotten J, Peters T, Bruning JC University of Greifswald, which is funded by grants from et al. Inactivation of the Fto gene protects from obesity. Nature the German Federal Ministry of Education and Research 2009; 458: 894–898. 15 Church C, Lee S, Bagg EA, McTaggart JS, Deacon R, Gerken T et al. (BMBF, Grant 01ZZ96030); the Ministry for Education, A mouse model for the metabolic effects of the human fat mass Research, and Cultural Affairs; and the Ministry for Social and obesity associated FTO gene. PLoS Genet 2009; 5: e1000599. 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