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International Journal of Obesity (2013), 1–7
& 2013 Macmillan Publishers Limited All rights reserved 0307-0565/13
www.nature.com/ijo
ORIGINAL ARTICLE
Thyroid hormone receptor alpha gene variants increase the risk
of developing obesity and show gene–diet interactions
JM Fernández-Real1,2, D Corella2,3, L Goumidi4, JM Mercader5, S Valdés6,7,8, G Rojo Martı́nez6,7, F Ortega1,2, M-T Martinez-Larrad9,
JM Gómez-Zumaquero6,7, J Salas-Salvadó2,10, MA Martinez González11, MI Covas2,12, P Botas6,7, E Delgado6,7, D Cottel4, J Ferrieres13,
P Amouyel4, W Ricart1,2, E Ros2,14, A Meirhaeghe4, M Serrano-Rios9, F Soriguer4 and R Estruch2,15
OBJECTIVE: Thyroid hormone receptor-beta resistance has been associated with metabolic traits. THRA gene sequencing of an
obese woman (index case) who presented as empirical thyroid hormone receptor-a (THRA) resistance, disclosed a polymorphism
(rs12939700) in a critical region involved in TRa alternative processing.
DESIGN AND SUBJECTS: THRA gene variants were evaluated in three independent europid populations (i) in two population
cohorts at baseline (n ¼ 3417 and n ¼ 2265), 6 years later (n ¼ 2139) and (ii) in 4734 high cardiovascular risk subjects (HCVR,
PREDIMED trial).
RESULTS: The minor allele of the index case polymorphism (rs12939700), despite having a very low frequency (4%), was
significantly associated with higher body mass index (BMI) (P ¼ 0.042) in HCVR subjects. A more frequent THRA polymorphism
(rs1568400) was associated with higher BMI in subjects from the population (P ¼ 0.00008 and P ¼ 0.05) after adjusting for several
confounders. Rs1568400 was also strongly associated with fasting triglycerides (P dominant ¼ 3.99 10 5). In the same sample,
6 years later, age and sex-adjusted risk of developing obesity was significantly increased in GG homozygotes (odds ratio 2.93 (95%
confidence interval, 1.05–6.95)). In contrast, no association between rs1568400 and BMI was observed in HCVR subjects, in whom
obesity was highly prevalent. This might be explained by the presence of an interaction (P o0.001) among the rs1568400 variant,
BMI and saturated fat intake. Only when saturated fat intake was high (424.5 g d 1), GG carriers showed a significantly higher BMI
than A carriers after controlling for energy intake and physical activity.
CONCLUSIONS: THRA gene polymorphisms are associated with obesity development. This is a novel observation linking the THRA
locus to metabolic phenotypes.
International Journal of Obesity advance online publication, 12 February 2013; doi:10.1038/ijo.2013.11
Keywords: Thyroid hormone receptors; genetics; polymorphisms.
INTRODUCTION
The epidemic of obesity and associated comorbidities, such as
diabetes, is one of the most important global public health
problems.1,2 Obesity results from a chronic imbalance between
energy acquisition (food intake), energy expenditure (basal
metabolic rate, thermogenesis and physical activity), and the
tendency to deposit any excess energy as either fat or lean mass
(nutrient partitioning). Nearly 70% of interindividual differences in
adiposity may be attributable to genetic factors.3–5 At least 20
single gene disorders that affect the central sensing and control of
energy balance result in an autosomal form of human obesity.3,4,6
Several endocrine abnormalities predispose to obesity,7 including
thyroid dysfunction.8 Triiodothyronine (T3) and tetraiodothyronine
(T4) regulate energy metabolism and thermogenesis, and have
critical roles in glucose and lipid metabolism, food intake and
fatty acid oxidation.8,9 Even slight variations in thyroid function
contribute to variations in body mass index (BMI) and weight gain
with aging.10–12
Thyroid hormones are linked to lipogenesis in lipogenic tissues
through activated thyroid hormone receptor-induced gene
expression.13–15 The two major thyroid hormone receptor
isoforms are differentially expressed during development and
distributed in adult tissues.16 TRa has specific roles in the heart
and in cardiac pacemaking.17,18 Mice lacking TRa have an average
heart rate 20% lower than that of control animals.18. TRa also
mediates adaptive thermogenesis in brown adipose tissue.19,20
TRb regulates thyroid stimulating hormone (TSH) and the
metabolic actions of T3 in the liver.21,22 The two major thyroid
hormone receptor isoforms, TRa1 and TRa2, are functionally
antagonistic.19,22 TRa1 is an authentic thyroid hormone receptor
1
Department of Diabetes, Endocrinology and Nutrition. Institut d’Investigació Biomédica de Girona, Girona, Spain; 2CIBER Fisiopatologia de la Obesidad y la Nutrición, CIBEROBN
(CB06/03), Instituto de Salud Carlos III, Girona, Spain; 3Genetic and Molecular Epidemiology Unit, Department of Preventive Medicine. University of Valencia, Valencia, Spain;
4
INSERM, U744; Institut Pasteur de Lille; Univ. Lille Nord de France; UDSL, Lille, France; 5Joint IRB-BSC program on Computational Biology. Barcelona Supercomputing Center,
Barcelona, Catalonia, Spain; 6Servicio de Endocrinologı́a y Nutrición, Hospital Universitario Carlos Haya, Malaga, Spain; 7CIBER of Diabetes and Metabolism (CIBERDEM) (CB07/08),
Instituto de Salud Carlos III, Malaga, Spain; 8Hospital Central de Asturias, Oviedo, Spain; 9Spanish Biomedical Research Centre in Diabetes and Associated Metabolic Disorders
(CIBERDEM) and Instituto de Investigación Sanitaria del Hospital Clı́nico San Carlos (IdISSC), Madrid, Spain; 10Human Nutrition Department, School of Medicine, University Rovira i
Virgili, Reus, Spain; 11Department of Preventive Medicine and Public Health, University of Navarra, Spain; 12Cardiovascular Risk and Nutrition Research Group, IMIM-Institut de
Recerca del Hospital del Mar, Barcelona, Spain; 13INSERM, U558, Faculté de Médecine, Université Paul Sabatier, Toulouse, France; 14Lipid Unit, Service of Endocrinology, Hospital
Clinic, Barcelona, Spain and 15Department of Internal Medicine, Hospital Clinic, IDIB APS, University of Barcelona, Barcelona, Spain. Correspondence: Dr JM Fernández-Real,
Section of Diabetes, Endocrinology and Nutrition, Hospital of Girona ‘Dr Josep Trueta’, Carretera de Franc¸a s/n, Girona 17007, Spain.
E-mail: [email protected]
Received 28 September 2012; revised 29 November 2012; accepted 19 December 2012
TRa gene polymorphism and obesity
JM Fernández-Real et al
2
that binds T3 and mediates its activity. TRa2 is a variant receptor
that lacks a functional hormone-binding site and antagonizes
the ability of TRa1 to activate gene transcription in the presence
of T3.23 Thus, the regulation of TRa alternative processing is
important for determining the cellular levels of TRa1 and
TRa2 mRNAs, which, in turn, are critical for modulating the
response to T3.
TSH levels are increased in some obese subjects, suggesting
thyroid hormone resistance. This is supported by the observation
of decreased thyroid hormone receptors in circulating mononuclear cells of obese individuals24 and decreased negative
feedback between TSH and peripheral T3 levels.25,26
The current study stems from a clinical observation of an obese
woman who showed empirical thyroid hormone receptor-a
(THRA) resistance. THRA gene sequencing showed a polymorphism in a critical region involved in TRa alternative processing. We
then hypothesized that THRA polymorphisms could be associated
with obesity.
MATERIALS AND METHODS
General population samples
Cohort 1. Data and samples from 3417 apparently healthy subjects were
obtained from population-based prospective studies performed in four
regions of Spain between 1996 and 1999 (700 subjects from the North27–
Asturias, 760 from North-East28–Girona, 906 from the Center29–Segovia
and 1051 from the South30 of Spain–Malaga). Eligible participants (all
Caucasians) were selected at random from the census and after a
screening visit were invited to participate. The participation rate was
higher than 70%. Baseline studies included a standardized questionnaire,
physical examination and laboratory tests. Fasting serum and plasma were
withdrawn and stored at 80 1C until analysis. Two thousand one
hundred thirty-nine participants from the centers in the North, North-East
and South regions of Spain were re-evaluated between 2003 and 2005
(63% of the original cohort).
Cohort 2. Participants were recruited as part of the World Health
Organization-MONICA population survey conducted from 1995 to 1997 in
the Lille Urban Community in northern France (n ¼ 1155) and the HauteGaronne county in southern France (n ¼ 1170).31 The protocol was
approved by the appropriate independent ethics committee in each center.
High cardiovascular risk (PREDIMED) cohort
From October 2003 to October 2007, subjects at high cardiovascular risk
were selected by physicians in Primary Care Centers affiliated with 10
teaching hospitals in Spain to participate in the PREDIMED study.32 Eligible
subjects were community-dwelling people who fulfilled at least one of two
criteria: type 2 diabetes; or 3 or more cardiovascular risk factors (current
smoking, hypertension, dyslipidemia, BMI X25 kg m 2 and family history
of premature cardiovascular disease). Hypertension was defined as blood
pressure X140/90 mm Hg or treatment with antihypertensive medication,
and dylipidemia as high plasma low-density lipoprotein-cholesterol
(X160 mg dl 1 or lipid-lowering therapy) or low plasma high-density
lipoprotein-cholesterol (p40 mg dl 1 in men and p50 mg dl 1 in
women).
Exclusion criteria included history of cardiovascular disease, any severe
chronic illness (terminal cancer, severe hepatic or renal diseases and/or
dementia), and drug or alcohol addiction. In this substudy, we analyzed the
first 4734 subjects who entered the trial and provided informed consent
for genetic analyses. The study protocol was approved by the local ethics
committees of each participating institution and all participants provided
informed consent.
Laboratory determinations
Analytes determined for each participant were: serum glucose levels
(glucose–oxidase method); cholesterol and triglyceride levels by enzymatic
procedures; and high-density lipoprotein cholesterol level after precipitation with phosphotungstic acid and magnesium chloride, as previously
reported.27,32 Serum TSH, free T4 and free T3 were measured in all centers
by electrochemiluminescence (Roche Diagnostics, GmbH, Mannheim,
Germany) with intra- and inter-assay coefficients of variation less than 5%.
International Journal of Obesity (2013) 1 – 7
In the MONICA studies, all measurements were performed in a central
laboratory (Purpan Hospital, Toulouse, France). Fasting triglyceride levels
were measured using enzyme assays (Boehringer Mannheim, Mannheim,
Germany).
Genotyping of THRA gene polymorphisms
THRA rs12939700 and rs1568400 polymorphisms were determined using a
7900HT Sequence Detection system (Applied Biosystems by Life Technologies, Norwalk, CT, USA) and predesigned fluorescent allelic discrimination
TaqMan assay by standard procedures (Assay ID C_9511338_10). For quality
control purposes, 10% of randomly selected samples were genotyped a
second time, with no discrepancies. The genotyping success rates were
between 96.3 and 98.5%. The populations were in Hardy–Weinberg
equilibrium for the studied polymorphims in all populations studied.
Statistical analyses
t-test and ANOVA were used to compare crude differences of means
between genotypes when indicated. The SNP association was computed
using a general linear model implemented in SNPassoc software
(Barcelona, Spain).33,34 Logistic regression analyses were carried out to
estimated the odds ratio and 95% confidence intervals for obesity
depending on THRA genotypes. The reference class was set as the
homozygosity for the major allele among controls in all cases. P-values
were derived from likelihood ratio tests. The best model was chosen using
the Akaike Information Criteria.34 Multivariate adjustment of means was
undertaken by analysis of covariance. The interaction between the THRA
polymorphism and fat intake in determining BMI or other anthropometric
variables was carried out by linear regression analysis. The P-value for the
interaction term between fat intake (as dichotomic (cut-off the median
value) or as a 3-category variables (tertiles)) and the THRA polymorphism
was obtained in the hierarchical multivariate interaction model containing
dummy variables for fat intake, the THRA polymorphism, their multiplicative term,and the additional control for the indicated covariates.
Stratified analyses by genotype were also carried out, and the lineal trend
between categories of fat intake was estimated by analysis of covariance.
In the MONICA cohorts general linear models were used to compare mean
values of variables by genotype groups. The statistical analyses were
performed using SPSS software (version 15.0; Chicago, IL, USA).
RESULTS
Index case
The index case was an obese (BMI 31.2 kg m 2) 48-year-old
woman referred to the hospital outpatients’ clinics for evaluation
of thyroid dysfunction. Hypothyroidism had been diagnosed 6
months earlier on the basis of serum thyroxine values of
0.9 ng dl 1 (normal 0.8–1.8) and TSH of 12.8 mU l 1 (normal
0.2–4.5), and treatment with l-thyroxine gradually increased up to
175 mg d 1. During this period she sustained an 18 kg weight loss
while remaining entirely asymptomatic. The general examination,
including the thyroid gland, was normal; her heart rate was
56 beats per min and an electrocardiogram disclosed no
abnormalities. T4 was 2.2 ng dl 1 (normal 0.8–1.8) and
TSHo0.001 mU l 1. An overdose of l-thyroxine was suspected
and the dose was reduced to 150 mg d 1. Two months later, TSH
was 1.2 mU l 1 and T4 1.5 ng dl 1 and the heart rate remained
unchanged.
Given the relatively low heart rate in the presence of
hyperthyroidism, some form of THRA resistance was suspected.
Sequencing of the entire THRA locus showed that the patient was
heterozygous for a rs12939700 (C/A) polymorphism located in
intron 9, considered as critical in the regulation of splicing.35 We
also decided to study a polymorphism in the THRA gene with the
highest heterozygosity (rs1568400, 635 A/G) in linkage
disequilibrium with rs12939700.
Polymorphism of the index case in the high-risk population
(PREDIMED)
This THRA polymorphism rs12939700 (A/C) polymorphism was
analyzed in 4734 high-risk individuals, in whom a very low
& 2013 Macmillan Publishers Limited
TRa gene polymorphism and obesity
JM Fernández-Real et al
3
frequency of the variant allele was shown. The prevalence of
genotypes in high-risk subjects was 93% CC (n ¼ 4401 subjects),
6.8% CA (n ¼ 323) and 0.2% AA (n ¼ 10). Carriers of the A allele had
a higher weight and BMI than CC homozygotes (P ¼ 0.042;
Table 1). Moreover, carriers of the A allele had a higher prevalence
of obesity (BMI X30 kg m 2) than CC subjects (53.3% vs 45.2%;
P ¼ 0.030).
Cross-sectional studies
General population study. rs1568400 ( 635A/G) and obesity-related
phenotypes. The frequencies of the different genotypes were
50.2% AA, 42.1% AG and 7.7% GG, and were similar in the four
regions (that is, frequency of GG in Girona 8.0%, in Asturias 7.9%,
in Segovia 7.3% and in Málaga 8.7%). The merged sample of
general population was composed of 3417 individuals (54.3% AA,
51.4% GA and 47.6% GG subjects were women). Among them, G
allele carriers (similar in age to AA homozygotes) were significantly
more obese and showed an increased average waist circumference, total cholesterol and fasting triglyceride concentrations
(Table 2 and Figure 1). The association with BMI remained
significant after adjusting for age, gender, triglycerides and region
(P ¼ 0.00008 in a dominant model, P ¼ 0.00034 in a codominant
model, and P ¼ 0.00011 in a log-additive model). There was also a
strong association between the rs1568400 SNP and fasting
triglyceride levels (p dominant ¼ 3.99 10 5), such as G allele
carriers showed the highest triglyceride levels. This association
remained significant after controlling for age, BMI, sex, fasting
glucose and region (Table 3A). This polymorphism was not
significantly associated with fasting glucose, low-density lipoprotein cholesterol or high-density lipoprotein cholesterol. The
associations with obesity and fasting triglycerides were independently replicated in the MONICA cohorts (Table 3B).
Longitudinal study
Relationship between rs1568400 SNP and development of obesity.
Of the initial general population sample, 2139 participants were
re-evaluated after a mean follow-up of 6.2±0.8 years. In this
Table 1.
Anthropometric and biochemical variables according to
thyroid hormone receptor alpha gene polymorphism (rs12939700) in
4734 participants in the PREDIMED trial
rs12939700
N
Age (years)
Weight (kg)
BMI (kg m 2)
Waist (cm)
Total cholesterol (mg dl 1)
LDL cholesterol (mg dl 1)
HDL cholesterol (mg dl 1)
Triglycerides (mg dl 1)
Fasting glucose (mg dl 1)
Energy intake (kcal d 1)
Carbohydrates (g d 1)
Proteins (g d 1)
Total fat (g d 1)
Saturated fat (g d 1)
MUFA (g d 1)
PUFA (g d 1)
CC
CA þ AA
Mean (s.d.)
Mean (s.d.)
4401
67.1 (6.3)
76.3 (11.7)
29.8 (4.1)
100.0 (10.6)
211.6 (38.5)
131.2 (35.6)
53.8 (13.2)
133.7 (74.2)
127.3 (46.2)
2325 (654)
242 (87)
94 (24)
102 (32)
26 (10)
51 (17)
16.3 (7.4)
333
66.6 (6.1)
77.6 (12.9)
30.3 (4.3)
100.6 (11.6)
214.3 (40.5)
133.8 (35.7)
53.1 (13.2)
136.2 (72.8)
131.6 (47.5)
2324 (716)
240 (89)
96 (29)
102 (35)
26 (11)
50 (18)
16.2 (7.1)
P
—
0.131
0.042
0.042
0.304
0.224
0.218
0.404
0.564
0.128
0.982
0.729
0.196
0.989
0.342
0.708
0.794
Abbreviations: HDL, high-density lipoprotein; LDL, low-density lipoprotein;
MUFA, monounsaturated fatty acids; PUFA, polyunsaturated fatty acids.
& 2013 Macmillan Publishers Limited
analysis, subjects with abnormal TSH values (o0.2 and
X4.0 mU l 1) were excluded from the calculations.(Table 4A)
shows the main characteristics of this population. Age, gender
and years of follow-up were similar in carriers and non-carriers
of the G allele of rs1568400. Compared with the other genotypes,
GG homozygotes had a significantly higher BMI (P ¼ 0.001)
both at baseline and at follow-up evaluations. Similarly,
average weight and waist circumference increases were also
significantly higher among GG homozygotes (P ¼ 0.020 and 0.048,
respectively). After adjusting for age, gender and thyroid function,
the obesity incidence was significantly increased in GG
homozygotes (Odds ratio 2.93 (95% confidence interval 1.05 to
6.95); P ¼ 0.01) compared with their nonhomozygous counterparts
(Table 4B).
Interaction of rs1568400 SNP with fat intake in the PREDIMED
cohort. This polymorphism was determined in baseline samples
of 4695 high-risk subjects from the PREDIMED trial. The prevalence
of the genotypes was 50.9% AA, 40.2% AG and 8.9% GG. We found
no significant associations between the rs1568400 SNP and
obesity-related variables in this population (Table 5). Considering
the previous association of rs1568400 SNP with BMI in the general
population sample, the lack of association in these high-risk
subjects prompted us to look for a potential gene–diet interaction
for this polymorphism.
When we examined the main macronutrients of the diet (that is,
carbohydrates, proteins and lipids) estimated by food frequency
questionnaires, we observed a statistically significant interaction
with total fat intake in determining BMI (Po0.001). More in depth
evaluation of this interaction showed saturated fat to have the
highest effect on BMI. On testing the interaction between
rs1568400 SNP and saturated fat intake expressed as a dichotomous variable (above and below the median intake in the whole
population: 24.5 g d 1) in determining BMI, we found a highly
statistically significant interaction term (Po0.001). Thus, when
saturated fat was below the median (o24.5 g d 1), the rs1568400
SNP was not associated with BMI (29.74 þ / 0.09 Kg m 2 for
Table 2. Anthropometric and biochemical variables of the subjects
from the general population according to thyroid hormone receptor
alpha -635A/G gene polymorphism (rs1568400)
n (3417)
Sex (men/women)
Age (years)
Body mass index
(Kg m 2)
Waist
circumference (cm)
Men
Women
Systolic blood
pressure (mm Hg)
Diastolic blood
pressure (mm Hg)
Total cholesterol
(mg dl 1)
LDL cholesterol
(mg dl 1)
HDL cholesterol
(mg dl 1)
Fasting triglyceridesa
Fasting glucose
(mg dl 1)
AA
G carriers
P
1719
791/928
50.6±12.4
28.28±5.2
1698
847/851
50.42±12.65
28.78±5.56
—
0.60
0.007
93.73±13.09
95.1±13.43
0.009
91.6±13.7
95.9±11.9
129.84±21.51
92.9±14.4
97.09±12.1
130.12±20.72
0.08
0.09
0.69
76.74±10.47
77.86±11.28
0.24
201.11±33.33
210.28±38.35
0.034
126.5±31.46
133.66±37.08
0.24
56.88±15.94
56.31±16.28
0.30
93 (66–134)
101.9±34.8
100 (71–147)
103.24±38.6
o0.0001
0.31
Abbreviations: HDL, high-density lipoprotein; LDL, low-density lipoprotein
Values are mean±s.d. aexpressed as medians and interquartile range.
International Journal of Obesity (2013) 1 – 7
TRa gene polymorphism and obesity
JM Fernández-Real et al
4
2.03
95% CI Log fasting triglycerides (mg/dl)
95% CI Body mass index (kgr/m2)
29.0
28.8
p=0.007
28.6
28.4
28.2
2.02
p<0.0001
2.01
2.00
1.99
1.98
1.97
28.0
AA
G allele carriers
thyroid hormone receptor alpha gene polymorphism
(rs1568400)
AA
G allele carriers
thyroid hormone receptor alpha gene polymorphism
(rs1568400)
Figure 1. Effect of the rs1568400 polymorphism of the THRA gene on mean BMI and mean log fasting triglycerides in a general population
sample. Bars are 95% confidence intervals.
Table 3A.
Association of the rs1568400 SNP with log plasma fasting
triglyceride levels in the general population sample, controlling for
body mass index, age, sex, glucose and region of origin
Number
Of
subjects
Log 10
trigl
(mean)
Se
dif
95% CI
P
Codominant
AA
AG
GG
1735
1442
266
1.98
2.02
2.03
0.006
0.007
0.014
0
0.027
0.034
0
0.01–0.04
0.01–0.06
0.00071
Dominant
AA
AG-GG
1735
1708
1.98
2.02
0.006
0.006
0
0.028
0
0.01–0.04
0.00016
rs1568400
AA þ AG vs 29.37 þ / 0.33 kg m 2 for GG; P ¼ 0.306). However,
when saturated fat intake was above the median (424.5 g d 1),
this polymorphism was associated with significantly higher
BMI in GG subjects (29.38 þ / 0.09 Kg m 2 for AA þ AG vs
30.49 þ / 0.29 kg m 2 for GG; P ¼ 0.015), replicating the
association found in the general population samples. This
interaction remained statistically significant even after further
controlling for age, sex, total energy intake and physical
activity. Moreover, to examine a possible dose-response
relationship, population tertiles of saturated fat intake were
considered (o21.1 g d 1; 21.1 to 28.3 g d 1 and 428.3 g d 1).
In this case, we again observed significant effects of the rs1568400
SNP for this interaction. In the regression model, a highly
statistical significant interaction term (Po0.001) was obtained
both in the crude model and after adjustment for age, gender,
diabetes, total energy intake and physical activity. In the stratified
analysis depending on the genotype, we observed a statistically
significant P-value for lineal trend across tertiles of fat intake in
subjects homozygous for the G allele. Figure 2 shows the
interaction effect between saturated fat intake and the
rs1568400 variant in determining BMI when saturated fat was
considered as tertiles of intake. When saturated fat intake was low,
the variant allele was not associated with a higher BMI. However,
when saturated fat intake was high, the GG genotype was
significantly associated with a higher BMI. Similar interaction
results were obtained when weight or waist circumference were
used as outcomes instead of BMI (data not shown). The results of
this interaction were homogeneous for both men and women
(data not shown).
International Journal of Obesity (2013) 1 – 7
DISCUSSION
Genome-wide association studies have allowed the identification
of many gene variants related to obesity. Another way of
identifying ‘candidate’ genes is through genetic analysis of
peculiar clinical cases. The index case presented here was an
obese woman overtreated with l-thyroxine. Being biochemically
hyperthyroid, this woman lost 18 kg in 6 months, with no changes
in heart rate characteristic of elevated thyroid hormones.
Sequencing of the THRA locus disclosed a polymorphism in a
critical region involved in the regulation of splicing. As this index
case was obese, we analyzed two polymorphisms of the THRA
locus that belonged to different blocks in association with BMI in
three samples, two obtained from population-based studies and
the other from subjects at high cardiovascular risk participating in
the PREDIMED trial. In the latter, the polymorphism present in the
index case (rs12939700) was associated with obesity. Another
polymorphism (rs1568400) that has a relatively high frequency in
the population was also associated with BMI according to both
cross-sectional (in two independent general populations of Spain
and France) and follow-up analyses in the Spanish populationbased cohort. This association with obesity was also confirmed in
the publicly available genome-wide association study of the
Genetic Investigation of ANthropometric Traits (GIANT) consortium (P ¼ 0.01, n ¼ 119 524 subjects).6 Interestingly, a SNP 45.6 Kb
from rs1568400, rs1045929 (D’ ¼ 0.43, r2 ¼ 0.056) in the thyroid
hormone receptor-associated protein (TRAP100/MED24) gene was
also associated with obesity (P ¼ 0.004).6 The lack of association of
rs12939700 and the weak association of rs1568400 in the GIANT
consortium genome-wide association study data could be due to
the different models of inheritance used to test the association in
the present study, compared with those used by the GIANT
consortium. While only the P-values for the association under the
additive model is reported by GIANT consortium, our association
was only significant when using the dominant model for
both rs1568400 and rs12939700. This emphasizes the need of
reporting the genome-wide association study summary data in
other models of inheritance besides the commonly used additive
model. In addition, large meta-analyses, such as those performed
by the GIANT consortium rely on genotype imputation, and
inaccuracy in this process, which particularly affects low frequency
variants, such as rs12939700, could result in loss of power to
detect a significant association.
The THRA rs1568400 variant was not associated with obesity in
the large cohort of subjects at increased cardiovascular risk from
the PREDIMED cohort. This may be explained by the fact that
almost all of these subjects had a BMI X25 kg m 2 as one of the
& 2013 Macmillan Publishers Limited
TRa gene polymorphism and obesity
JM Fernández-Real et al
5
Table 3B. Z-scores of clinical variables according to THRA genotypes in combined MONICA Lille and Toulouse
rs1568400
Zscore_BMI
Zscore_WAIST
Zscore_HIP
Zscore_WHR
Zscore_TG*
AA (1230)
AG (866)
GG (169)
P (dominant)
P (recessive)
0.03±0.98
0.02±0.99
0.04±0.98
0.0002±1.00
0.004±1.05
0.04±1.03
0.04±1.01
0.05±1.02
0.01±0.98
0.03±1.00
0.06±1.00
0.03±1.01
0.09±1.01
0.04±1.04
0.12±0.66
0.05
0.15
0.02
0.68
0.57
0.57
0.77
0.29
0.41
0.02
P-values are adjusted for age, sex, alcohol consumption, smoking habit, physical activity level and center ( þ BMI for TG). *P values were calculated on logtransformed data. Significant values are depicted in bold.
Table 4A.
Subjects’ characteristics according to thyroid hormone receptor alpha -635A/G gene polymorphism (rs1568400)
North–Asturias
n (%)
Gender (% women)
Baseline age, year
Baseline BMI, kg m 2
Age at follow-up, year
Years of follow-up
BMI at follow-up, kg m 2
Weight increase, kg
South—Pizarra
AA
AG
GG
AA
AG
GG
358 (52.4)
53.9
52.1±12.7
27±3.9
58.3±12.7
6.26±0.2
27.63±4.2
1.67±5
271(39.7)
53.1
52.4±11.9
27.44±4.4
58.6±11.9
6.24±0.2
28.12±4.6
1.85±5.4
54(7.9)
59.38a
54.9±11.1a
29.45±6.1c
61.2±13.2a
6.24±0.2a
30.13±6.5c
1.88±4.9d
443 (47.7)
64.4
39.8±13.6
27.62±5.2
46.7±14.1
6.46±2.3
28.87±5.5
2.65±5.9
404(43.5)
61.2
40.6±13.9
27.22±4.9
47.2±14.1
6.44±1.6
28.33±4.9
2.18±6.2
81(8.7)
51.9a
36.42±14.41b
26.95±5d
43.9±13.7b
6.03±1.7a
29.70±5.2d
4.44±6.8e
a
P ¼ NS within each study. bP ¼ 0.01 for within study comparisons. cP ¼ 0.001 adjusted for age and sex. dP ¼ NS adjusted for age and sex and education level.
P ¼ 0.02 adjusted for age and sex and education level.
e
Table 4B. Risk of developing obesity according to thyroid hormone
receptor alpha -635A/G gene polymorphism (rs1568400)
OR
95 CI %
P
Asturias
AA
AG
GG
reference
1.43
2.95a
0.76–2.68
1.05–7.73
0.26
0.03
Pizarra
AA
AG
GG
reference
1.14
2.93a
0.65–1.98
1.23–6.95
0.63
0.01
Pizarra
AA
AG
GG
reference
0.97
3.19b
0.53–1.75
1.031–7.75
0.92
0.01
Pizarra
AA
AG
GG
reference
1.25
2.99c
0.71–2.21
1.34–7.16
0.42
0.01
a
Adjusted for age and sex and education level. bAdjusted for age and sex
and education level and TSH at baseline. cAdjusted for age and sex and
education level and TSH at follow-up.
inclusion criteria and, therefore, there were few non-obese
patients in the cohort. Nevertheless, in depth analysis of this
selected population showed a gene–diet interaction between the
THRA rs1568400 polymorphism and fat intake. Only individuals
with the GG genotype and a high intake of saturated fat showed a
significant association with increased BMI. The findings in high-risk
& 2013 Macmillan Publishers Limited
subjects were different to those observed in the general
population, probably because some of the former were counseled
by their family physicians to reduce total energy and saturated fat
intake. The association of this polymorphism and obesity traits
may only be observed in an obesogenic environment. Importantly,
the THRA rs1568400 gene polymorphism was not only crosssectionally associated with obesity. Longitudinally, subjects with
this gene variant had a threefold increased risk of developing
obesity.
Thyroid hormone stimulates the basal metabolic rate and
adaptive thermogenesis. In fact, the relationship among thyroid
function, energy metabolism and body fat is firmly established.19
Up to now, evidence concerning the possible role of THRA in
obesity and metabolism has been exclusively obtained from animal
models. The introduction of a dominant negative mutation derived
from a resistance to thyroid hormone-associated THRB mutation
into the THRA gene (P398H) resulted in increased adiposity and
sensitivity to diet-induced obesity.36 However, introduction of
other types of mutations led to a lean phenotype.37,38
In recent years it has been increasingly recognized that the
hypothalamus-pituitary-thyroid axis regulates satiety signals
through MC4R (melanocortin receptor-4) and NPY/AgRP neurons
and UCP2.39–41 Unlike T3, the administration of the TRb-specific
agonist GC-1 had no effect on food intake in rats, suggesting that
the orexigenic effects of thyroid hormone may also be mediated
by THRA.42 It has been speculated that hyperphagia in classical
resistance to thyroid hormones (TRb-driven) is mediated by
elevated thyroid hormones acting centrally via THRA.43
The THRA rs1568400 polymorphism was also associated with
fasting triglycerides (Tables 3A and 3B). This association remained
significant after controlling for the main confounders. In addition,
there was an interaction between this polymorphism and fat
intake. In fact, THRA is a gene expressed in the rat jejunum and
International Journal of Obesity (2013) 1 – 7
TRa gene polymorphism and obesity
JM Fernández-Real et al
6
Table 5. Anthropometric and biochemical variables according to thyroid hormone receptor alpha-635A/G gene polymorphism (rs1568400) in 4695
participants in the PREDIMED trial
N
Age (years)
Weight (kg)
BMI (kg m 2)
Waist (cm)
Total cholesterol (mg dl 1)
LDL-C (mg dl 1)
HDL-C (mg dl 1)
Triglycerides (mg dl 1)
Fasting glucose (mg dl 1)
AA
AG
GG
Mean (s.d.)
Mean (s.d.)
Mean (s.d.)
2387
67.2 (6.1)
76.5 (11.2)
29.8 (4.1)
100.3 (10.8)
212.4 (38.5)
131.7 (34.0)
54.0 (13.4)
133.9 (74.0)
126.4 (46.1)
1889
66.8 (6.3)
76.0 (11.6)
29.9 (4.4)
99.7 (10.5)
210.6 (38.5)
130.5 (34.0)
53.4 (12.8)
132.0 (71.1)
128.8 (46.3)
419
67.2 (6.7)
76.5 (12.1)
30.0 (4.1)
100.4 (10.8)
210.8 (40.1)
132.2 (50.2)
53.4 (13.2)
138.1 (95.5)
128.2 (44.0)
P
0.149
0.502
0.826
0.210
0.355
0.494
0.350
0.333
0.296
Abbreviations: HDL, high-density lipoprotein; LDL, low-density lipoprotein P-value for comparison of means between genotypes (ANOVA test).
32
BMI (Kg/m2)
P interaction THRA x saturated fat <0.001
P<0.05
30
28
AA AG+GG
tertile 1
AA AG+GG
tertile 2
AA
AG+GG
tertile 3
Saturated fat intake (tertiles)
Figure 2. Interaction between the rs1568400 polymorphism of the
THRA gene with saturated fat intake (tertiles) in determining BMI in
the PREDIMED cohort.
involved not only in carbohydrate and lipid absorption but also in
the development of the intestine.44,45 Interestingly, patients with
classical resistance to thyroid hormones (usually associated with
mutations in thyroid hormone receptor b) also showed slightly
elevated fasting triglycerides43 and the targeting of thyroid
hormone receptor with receptor-beta agonists has previously
shown to reduce both plasma cholesterol and triglyceride levels.46
In fact, dyslipidemia is a well-known characteristic of subjects with
hypothyroidism,47 suggesting that G carriers show some degree of
tissue hypothyroidism.
In summary, both the study of crude associations between the
selected SNPs at the THRA locus and the study of gene–
environment (fat intake) interactions have yielded interesting
results regarding their association with obesity and metabolic
phenotypes. The mechanisms for these associations should be
further studied given that TRa1 could contribute to adipose tissue
expandability.48
CONFLICT OF INTEREST
The authors declare no conflict of interest.
ACKNOWLEDGEMENTS
We greatly appreciate the technical assistance of Gerard Pardo and Oscar Rovira (Unit
of Diabetes, Endocrinology and Nutrition. Institut d’Investigació Biomèdica de Girona,
Hospital Universitari de Girona Dr Josep Trueta). JMM was supported by Sara Borrell
International Journal of Obesity (2013) 1 – 7
fellowship from the Instituto de Salud Carlos III. This work was supported by research
grants from the Ministerio de Educación y Ciencia (MEC) (SAF2008-02073 and
PI070954), the Instituto de Salud Carlos III (CIBERobn) and Consejerı́a de Salud Junta
de Andalucı́a (PI-0327-2010). JMM was supported by Sara Borrell Fellowship from the
Instituto Carlos III. CIBERobn de Fisiopatologı́a de la Obesidad y Nutrición and CIBER
de Diabetes y Enfermedades Metabólicas Asociadas are ISCIII projects. Funding was
also obtained from the Commission’s Sixth Framework Program (CRESCENDO
consortium, integrated project LSHM-CT-2005-018652), ANR GENOPAT (2008P006850) and INSERM. The French arm of the World Health Organization-MONICA
population study was funded by grants from the Conseil Régional du Nord-Pas de
Calais, the Caisse Primaire d’Assurance Maladie de Sélestat, the Association Régionale
de Cardiologie d’Alsace, ONIVINS, Parke-Davis, the Mutuelle Générale de l’Education
Nationale (MGEN), the Réseau National de Santé Publique, the Direction Générale de
la Santé, the INSERM, the Institut Pasteur de Lille and the Unité d’Evaluation du
Center Hospitalier et Universitaire de Lille, and to the THRA study group for their help
in recruitment of subjects (Enrique Gómez-Gracia (University of Málaga, Málaga,
Spain), Miguel Fiol (University Institute for Health Sciences Investigation, Palma de
Mallorca, Spain), Fernando Arós (Hospital Txagorritxu, Vitoria, Spain), José Lapetra
(San Pablo Health Center, Sevilla, Spain), Luis Serra-Majem (Las Palmas University, Las
Palmas, Spain, Xavier Pintó (Hospital de Bellvitge, Hospitales de Llobregat, Spain),
Carolina Ortega-Azorı́n and Marı́a Arregui (Genetic and Molecular Epidemiology Unit.
Department of Preventive Medicine. University of Valencia, Valencia, Spain)).
AUTHOR CONTRIBUTIONS
RE researched data and contributed to discussion; DC, LG, JMM, SV, GRM, FO,
JMG-Z, JS-S, MIC, ER, MS-R, FS researched data; M-TM-L, MAMG, PB, ED, DC, JF,
PA, WR, AM: contributed to discussion and JMF-R: researched data and wrote
the manuscript.
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