Physical activity attenuates the body mass index–increasing
influence of genetic variation in the FTO gene1–3
Karani S Vimaleswaran, Shengxu Li, Jing Hua Zhao, Jian’an Luan, Sheila A Bingham, Kay-Tee Khaw, Ulf Ekelund,
Nicholas J Wareham, and Ruth JF Loos
Background: Intronic variation in the FTO (fat mass and obesity-
associated) gene has been unequivocally associated with increased
body mass index (BMI; in kg/m2) and the risk of obesity in pop-
ulations of different ethnicity.
Objective: We examined whether this robust genetic predisposition
to obesity can be attenuated by being more physically active.
Design: The FTO variant rs1121980 was genotyped in 20,374 par-
ticipants (39–79 y of age) from the European Prospective Investi-
gation into Cancer and Nutrition–Norfolk Study, an ethnically
homogeneous population-based cohort. Physical activity (PA) was
assessed with a validated self-reported questionnaire. The interac-
tion between rs1121980 and PA on BMI and waist circumference
(WC) was examined by including the interaction term in mixed-
Results: We confirmed that the risk (T) allele of rs1121980 was
significantly associated with BMI (0.31-unit increase per allele; P ,
0.001) and WC (0.77-cm increase per allele; P , 0.001). The PA
level attenuated the effect of rs1121980 on BMI and WC; ie,
whereas in active individuals the risk allele increased BMI by
0.25 per allele, the increase in BMI was significantly (P for inter-
action = 0.004) more pronounced (76%) in inactive individuals
(0.44 per risk allele). We observed similar effects for WC (P for
interaction = 0.02): the risk allele increased WC by 1.04 cm per
allele in inactive individuals but by only 0.64 cm in active individ-
Conclusions: Our results showed that PA attenuates the effect of the
FTO rs1121980 genotype on BMI and WC. This observation has
important public health implications because we showed that a ge-
netic susceptibility to obesity induced by FTO variation can be
overcome, at least in part, by adopting a physically active life-
style.Am J Clin Nutr 2009;90:425–8.
Human obesity is caused by a complex interplay of genes and
environment (1). Common intronic variants of the FTO (fat mass
and obesity-associated) gene have been found to be robustly
associated with obesity-related traits in humans (2–6). FTO was
first identified as an obesity-susceptibility gene by 2 independent
genome-wide association studies. The first was a genome-wide
association study for type 2 diabetes in which a cluster of
common variants in the first intron of the FTO gene showed
a highly significant association with type 2 diabetes mediated
the first genome-wide association study for BMI—showed in
.4000 Sardinians that the FTO gene variants in the first intron
were significantly associated with BMI even after replication in
European Americans and Hispanic Americans (3). These studies
units, which is equivalent to ’0.40–0.66. A third study published
at the same time as the first 2 studies identified FTO while testing
for population stratification (6). After these studies were con-
ducted, many others replicated the association between the FTO
variants and obesity-related traits in populations of different eth-
nic background and in adults and children (7–14).
In addition to the genetic component of obesity, lifestyle and
environmental factors such as diet and physical inactivity are
important contributors that could interact with a person’s genetic
predisposition (15). So far, 2 studies have shown that the in-
creased risk of obesity owing to genetic variation in FTO can be
attenuated through physical activity (PA) (16, 17). However,
a recent study in twins failed to show evidence of an interaction
between the FTO variant and the environment (18). This was
followed by a Finnish study in children (19), which also failed to
show an interaction between the FTO variant and leisure-time
power to detect an interaction (20). Therefore, we examined the
effect of the interaction between the FTO gene variant rs1121980
and PA on obesity-related traits [BMI and waist circumference
(WC)] in a large-scale population-based cohort, the European
1From the MRC Epidemiology Unit, Institute of Metabolic Science,
Cambridge, United Kingdom (KSV, SL, JHZ, JL, UE, NJW, and RJFL);
the CNC, Department of Public Health and Primary Care, University
of Cambridge, Cambridge, United Kingdom (SAB); and the Department of
bridge, United Kingdom (K-TK).
2The EPIC-Norfolk study is supported by program grants from the Med-
ical Research Council UK and Cancer Research UK and with additional
support from the European Union, Stroke Association, British Heart Foun-
dation, Department of Health, Food Standards Agency, and the Wellcome
3Address correspondence to RJF Loos, MRC Epidemiology Unit, Institute
of Metabolic Science, Box 285, Addenbrooke’s Hospital, Hills Road, Cam-
bridge CB2 0QQ, United Kingdom. E-mail: email@example.com.
Received February 18, 2009. Accepted for publication June 1, 2009.
First published online June 24, 2009; doi: 10.3945/ajcn.2009.27652.
Am J Clin Nutr 2009;90:425–8. Printed in USA. ? 2009 American Society for Nutrition
by guest on October 20, 2015
Prospective Investigation into Cancer and Nutrition (EPIC)–
Norfolk Study, comprising .20,000 individuals.
SUBJECTS AND METHODS
Study population and recruitment procedures
Our study included participants from the EPIC-Norfolk study,
an ongoing prospective population-based cohort study of 25,631
residents living in the city of Norwich and its surrounding towns
and rural areas. All men and women aged 39–79 y from the
consenting general practices were invited to participate in the
baseline health check between 1993 and 1997. From January
1998, we invited participants for a second health examination,
which was attended by 15,786 people by October 2000. Full
details on participant recruitment and study procedures were
described previously (21, 22). In brief, trained nurses examined
the study participants at both health checks; height and weight
were measured, and BMI was calculated as weight (kg)/height2
(m). WC was measured at the minimum circumference at the
natural waistline between the lower rib margins and iliac crest,
or at the level of the umbilicus if there was no natural waistline.
The current analyses included individuals who had extracted
DNA available and with data on BMI at baseline (n = 20,374)
and during follow-up (n = 11,909). The characteristics of the
study cohort at baseline and follow-up are shown in Table 1.
The study was approved by the Norfolk, United Kingdom,
Health District Ethics Committee.
PA was assessed by a brief validated questionnaire including
questions on occupational (sedentary, standing, physical work,
and heavy manual work) and recreational (cycling, exercise)
activities to compute an index of habitual activity (23). The
frequency (h/wk) of recreational PA during both summer and
winter was recorded, and the average daily PAwas calculated as
total hours of PA per week divided by 7. On the basis of this
average activity score, individuals were assigned to 1 of 4 PA
categories: inactive (sedentary job, no recreational activity),
moderately inactive (sedentary job, ,0.5 h/d of recreational
activity or standing job, no recreational activity), moderately
active (sedentary job, 0.5–1.0 h/d of recreational activity or
standing job, ,0.5 h/d of recreational activity or physical job,
no recreational activity), and active (sedentary job, .1 h/d of
recreational activity or standing job, .1 h/d of recreational
activity or physical job with some recreational activity or heavy
Genotyping of the FTO variant rs1121980 was performed by
using Custom TaqMan SNP Genotyping Assays (Applied Bio-
systems, Warrington, United Kingdom). The genotyping assays
were carried out on 10 ng genomic DNA in a 5-lL 384-well
TaqMan assay by using a PTC-225 Thermal Cycler (MJ Re-
search, Watertown, MA), cycling at 95?C for 10 min and then
40 cycles of 15 sec at 92?C and 1 min at 54?C. The ABI PRISM
7900HT Sequence Detection System (Applied Biosystems) was
used for endpoint detection and allele calling. The call rate for
genotyping was 98%, and the concordance rate was 99%. The
genotypes of the variant were in Hardy-Weinberg equilibrium
(P = 0.90).
A goodness-of-fit chi-square test was performed to confirm
whether the observed genotype counts were in Hardy-Weinberg
equilibrium. To make full use of data available at baseline and
follow-up examinations, a mixed-effect model was used to ex-
amine the association between the FTO variant and BMI and WC
assuming an additive effect and adjusted for age, sex, and PA.
The mixed-effect model takes into account related measure-
ments from both health examinations and accounts for unequal
spaced observations across individuals. It is worth clarifying that
the short follow-up period (3.6 y) did not allow us to conduct
a longitudinal analysis, and the analysis approach in the current
study was cross-sectional in nature. The interaction between the
FTO variant and PA on BMI and WC was examined by in-
cluding the variant-PA interaction term in the mixed-effect
models. Least-squares means of different genotypes across all
PA levels were calculated by using the mixed-effect model,
adjusted for age and sex. Because the effect of rs1121980 was
more pronounced in the inactive group than in the other 3 PA
groups, PA was dichotomized into an inactive and an active
group, with moderately inactive, moderately active, and active
groups combined as the active group, and the interaction be-
tween the FTO variant and the 2 PA levels on BMI and WC was
examined. All analyses were conducted by using SAS version
9.1 (SAS Institute Inc, Cary, NC).
Association of rs1121980 FTO variant with obesity
We found that the T allele of the rs1121980 FTO variant
showed a highly significant association with BMI [0.31-unit
increase per allele (95% CI: 0.25, 0.36); P , 0.001] and WC
[0.76-cm increase per allele (95% CI: 0.61, 0.92); P , 0.001]
Characteristics of the study cohort at baseline and follow-up by sex
Waist circumference (cm)
Physical activity level [n (%)]
Waist circumference (cm)
59.1 6 9.31
26.5 6 3.3
95.7 6 9.7
58.6 6 9.3
26.1 6 4.2
82.1 6 10.7
63.0 6 9.0
26.9 6 3.3
96.1 6 9.7
61.9 6 9.0
26.4 6 4.3
81.7 6 10.6
1Mean 6 SD (all such values).
VIMALESWARAN ET AL
by guest on October 20, 2015
Interaction of the FTO variant with PA across the 4
We found no association of the FTO gene variant with PA
level (P = 0.45). We then tested the interaction between PA and
the FTO variant on BMI and WC across the 4 PA levels. Al-
though the interaction was not statistically significant (P for
interaction = 0.055), we found that the strength of the associa-
tion between rs1121980 and BMI increased with decreasing PA
level [b (SE): active, 0.26 (0.062) per risk allele; moderately
active, 0.28 (0.061) per risk allele; moderately inactive, 0.22
(0.056) per risk allele; inactive, 0.44 (0.059) per risk allele].
Although the interaction between PA and the FTO variant on
WC was not significant either, we did not see a trend similar to
that seen with BMI (Figure 2).
Interaction of the FTO variant with PA across the 2
When the PA-rs1121980 analysis was carried out with 2 levels
of PA, inactive and active, we found that PA significantly at-
tenuated the effect of rs1121980 on both BMI (P for interaction =
0.004) and WC (P for interaction = 0.02) (Figure 2). The BMI
increase per FTO risk allele was more pronounced (76%) in
inactive individuals [CC: 26.58 6 0.07; CT: 27.05 6 0.06; TT:
27.45 6 0.10; 0.44 per risk allele (SE: 0.06, P , 0.001)]
compared with the BMI increase among active individuals [CC:
26.01 6 0.04; CT: 26.23 6 0.03; TT: 26.51 6 0.06; 0.25 per risk
allele (SE: 0.03, P , 0.001)]. We observed similar effects for
WC; in active individuals the risk (T) allele increased WC by
0.64 cm (SE: 0.09) [CC: 87.35 6 0.11 cm; CT: 88.04 6 0.09
cm; TT: 88.63 6 0.15 cm; P = 2.26 E212], whereas in inactive
individuals the risk (T) allele increased WC by 1.04 cm (SE:
0.15) per allele [CC: 90.07 6 0.19 cm; CT: 91.28 6 0.15 cm;
TT: 92.12 6 0.25 cm; P = 1.3E211].
We found that the risk (T) allele of rs1121980, which is part of
a cluster of ?40 single nucleotide polymorphisms (SNPs) that
are highly correlated (linkage disequilibrium r2. 0.80 in CEU
of the HapMap) in white populations, was significantly associ-
ated with BMI and WC in the EPIC-Norfolk Study. Our results
are consistent with the findings of previous studies, which
showed an unequivocal association between FTO variants and
BMI (2–4). Although the influence of FTO on BMI is relatively
modest, it is consistent across studies observed in individuals of
European descent. Other studies have shown that each risk allele
increases BMI by ’0.40–0.66 (4) and WC by ’1.0–2.4 cm.
These effect sizes are comparatively higher than those seen in
FIGURE 1. Association between the FTO variant and body mass index
(A) and waist circumference (B). A mixed-effect model was used to examine
the association between the FTO variant and body mass index and waist
circumference, with the assumption of an additive effect and with adjustment
for age, sex, and physical activity.
FIGURE 2. Effect of the interaction between the FTO variant and
physical activity on body mass index (A) and on waist circumference (B).
*P value for interaction between the FTO variant and physical activity
between the active and inactive groups; **P value for interaction between
the FTO variant and physical activity between the 4 levels of physical
activity. Least-squares means of different genotypes across all physical
activity levels were calculated by using the mixed-effect model, with
adjustment for age and sex.
FTO VARIANT, OBESITY, AND PHYSICAL ACTIVITY
by guest on October 20, 2015
our study, which could be attributed to the older age of our study
In addition, we found that PA attenuated the effect of
inactive individuals was twice as large as that in active indi-
viduals. Our results agree with those of 2 recent studies that
showed a similar attenuation by PA on the association between
the FTO gene variant and BMI (16, 17). A study in 5554 middle-
aged Danes found an interaction between the FTO variant
(rs9939609) and self-reported PA (P for interaction = 0.007),
where the BMI increase per risk allele was more pronounced in
physically inactive individuals (1.95 per risk allele) than in ac-
tive individuals (0.47 per risk allele) (16). The SNP rs1121980 is
in high linkage disequilibrium (r2= 0.84) with the SNP
rs9939609 and thus reflects the same locus. We expected that the
results would have been similar if we had genotyped rs9939609.
Both SNPs are part of a large cluster of ?40 SNPs that are
highly correlated (linkage disequilibrium: r2. 0.80 in CEU of
the HapMap) in white populations. Likewise, a study in 704 Old
Order Amish (17) found an interaction between the FTO variant
(rs1861868) and PA (P for interaction = 0.01), where the BMI
increase per risk allele was more pronounced in individuals
within the lower half of the PA distribution (1.12 6 0.33 per risk
allele) than in individuals in the upper half of the PA distribution
(0.30 6 0.3 per risk allele). In contrast, a heritability study in
3353 Australian adult twins failed to show evidence of an in-
teraction between the FTO variant and the environment (18),
and a Finnish study in 438 children also failed to show an in-
teraction between the FTO variant and leisure-time PA (19).
These inconsistencies in results may have been due to lack of
power because of small sample sizes, which can be overcome by
population studies with large number of samples. Furthermore,
the twin study did not actually measure lifestyle, but tested for
effect modification by environment influences using statistical
modeling. In this regard, our study is important because the
EPIC-Norfolk Study is population-based and the largest study to
date. However, one cannot rule out the occurrence of reporting
bias in the self-reported PA; therefore, it is important to replicate
the finding with more direct measures of PA.
In conclusion, despite the fact that genetic variation in FTO is
robustly associated with increased BMI and WC, our results
showed that PA can attenuate this genetic effect. This observa-
tion has important public health implications, because we
showed that a genetic predisposition to obesity induced by
variation in FTO can be overcome, at least in part, by adopting
a physically active lifestyle.
The authors’ responsibilities were as follows—KSVand RJFL: wrote the
manuscript; SL: performed the statistical analyses; and JHZ, JL, SAB, K-TK,
UE, and NJW: contributedto the drafts ofthe manuscript. None of the authors
had a personal or financial conflict of interest.
1. Loos RJ, Rankinen T. Gene-diet interactions on body weight changes.
J Am Diet Assoc 2005;105:S29–34.
2. Frayling TM, Timpson NJ, Weedon MN, et al. A common variant in the
FTO gene is associated with body mass index and predisposes to
childhood and adult obesity. Science 2007;316:889–94.
3. Scuteri A, Sanna S, Chen WM, et al. Genome-wide association scan
shows genetic variants in the FTO gene are associated with obesity-
related traits. PLoS Genet 2007;3:e115.
4. Loos RJ, Bouchard C. FTO: the first gene contributing to common forms
of human obesity. Obes Rev 2008;9:246–50.
5. Hinney A, Nguyen TT, Scherag 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 2007;2:
6. Dina C, Meyre D, Gallina S, et al. Variation in FTO contributes
to childhood obesity and severe adult obesity. Nat Genet 2007;39:
7. Hotta K, Nakata Y, Matsuo T, et al. Variations in the FTO gene are
associated with severe obesity in the Japanese. J Hum Genet 2008;53:
8. Hunt SC, Stone S, Xin Y, et al. Association of the FTO gene with BMI.
Obesity (Silver Spring) 2008;16:902–4.
9. Grant SF, Li M, Bradfield JP, et al. Association analysis of the FTO gene
with obesity in children of Caucasian and African ancestry reveals
a common tagging SNP. PLoS One 2008;3:e1746.
10. Tan JT, Dorajoo R, Seielstad M, et al. FTO variants are associated with
obesity in the Chinese and Malay populations in Singapore. Diabetes
11. Zhang F, Xu L, Jin L, Wang XF. A common variant in the FTO gene is
associated with obesity in the Uyghur population. J Endocrinol Invest
12. Yajnik CS, Janipalli CS, Bhaskar S, et al. FTO gene variants are strongly
associated with type 2 diabetes in South Asian Indians. Diabetologia
13. Chang YC, Liu PH, Lee WJ, et al. Commonvariation in the fat mass and
obesity-associated (FTO) gene confers risk of obesity and modulates
BMI in the Chinese population. Diabetes 2008;57:2245–52.
14. Freathy RM, Timpson NJ, Lawlor DA, et al. Common variation in the
FTO gene alters diabetes-related metabolic traits to the extent expected
given its effect on BMI. Diabetes 2008;57:1419–26.
15. Marti A, Martinez-Gonza ´lez MA, Martinez JA. Interaction between
genes and lifestyle factors on obesity. Proc Nutr Soc 2008;67:1–8.
16. Andreasen CH, Stender-Petersen KL, Mogensen MS, et al. Low physical
activity accentuates the effect of the FTO rs9939609 polymorphism on
body fat accumulation. Diabetes 2008;57:95–101.
17. Rampersaud E, Mitchell BD, Pollin TI, et al. Physical activity and the
association of common FTO gene variants with body mass index and
obesity. Arch Intern Med 2008;168:1791–7.
18. Cornes BK, Lind PA, Medland SE, Montgomery GW, Nyholt DR,
Martin NG. Replication of the association of common rs9939609 variant
of FTO with increased BMI in an Australian adult twin population but
no evidence for gene by environment (G · E) interaction. Int J Obes
19. Hakanen M, Raitakari OT, Lehtima ¨ki T, et al. FTO genotype is asso-
ciated with body mass index after the age of 7 years but not with energy
intake or leisure-time physical activity. J Clin Endocrinol Metab 2009;
20. Wong MY, Day NE, Luan JA, Chan KP, Wareham NJ. The detection of
gene-environment interaction for continuous traits: should we deal with
measurement error by bigger studies or better measurement? Int J Ep-
21. Riboli E, Kaaks R. The EPIC Project: rationale and study design. Eu-
ropean Prospective Investigation into Cancer and Nutrition. Int J Epi-
22. Day N, Oakes S, Luben R, et al. EPIC-Norfolk: study design and
characteristics of the cohort. European Prospective Investigation of
Cancer. Br J Cancer 1999;80:95–103.
23. Wareham NJ, Jakes RW, Rennie KL, et al. Validity and repeatability of
the EPIC-Norfolk physical activity questionnaire. Int J Epidemiol 2002;
VIMALESWARAN ET AL
by guest on October 20, 2015