Am J Physiol Endocrinol Metab 295: E148 –E154, 2008.
First published May 6, 2008; doi:10.1152/ajpendo.00580.2007.
Acquired obesity and poor physical fitness impair expression of genes
of mitochondrial oxidative phosphorylation in monozygotic twins discordant
for obesity
Linda Mustelin,1,2 Kirsi H. Pietiläinen,2,3,4 Aila Rissanen,3 Anssi R. Sovijärvi,1 Päivi Piirilä,1
Jussi Naukkarinen,5 Leena Peltonen,5 Jaakko Kaprio,2,6 and Hannele Yki-Järvinen4,7
1
Department of Laboratory Medicine, Division of Clinical Physiology and Nuclear Medicine; Helsinki University Central
Hospital; 2Finnish Twin Cohort Study, Department of Public Health, University of Helsinki; 3Obesity Research Unit,
Department of Psychiatry; Helsinki University Central Hospital; 4Department of Medicine, Division of Diabetes, Helsinki
University Central Hospital; 5Department of Molecular Medicine, National Public Health Institute, Helsinki, and Department
of Medical Genetics and Research Program of Molecular Medicine, University of Helsinki; 6Department of Mental Health
and Alcohol Research, National Public Health Institute, Helsinki; and 7Minerva Medical Research Institute,
Helsinki, Finland
Submitted 7 September 2007; accepted in final form 22 April 2008
Mustelin L, Pietiläinen KH, Rissanen A, Sovijärvi AR, Piirilä P,
Naukkarinen J, Peltonen L, Kaprio J, Yki-Järvinen H. Acquired
obesity and poor physical fitness impair expression of genes of mitochondrial oxidative phosphorylation in monozygotic twins discordant for
obesity. Am J Physiol Endocrinol Metab 295: E148 –E154, 2008. First
published May 6, 2008; doi:10.1152/ajpendo.00580.2007.—Defects in
expression of genes of oxidative phosphorylation in mitochondria
have been suggested to be a key pathophysiological feature in familial
insulin resistance. We examined whether such defects can arise from
lifestyle-related factors alone. Fourteen obesity-discordant (BMI difference 5.2 ⫾ 1.8 kg/m2) and 10 concordant (1.0 ⫾ 0.7 kg/m2)
monozygotic (MZ) twin pairs aged 24 –27 yr were identified among
658 MZ pairs in the population-based FinnTwin16 study. Whole body
insulin sensitivity was measured using the euglycemic hyperinsulinemic clamp technique. Transcript profiles of mitochondrial genes were
compared using microarray data of fat biopsies from discordant twins.
Body composition of twins was determined using DEXA and maximal oxygen uptake (V̇O2max) and working capacity (Wmax) using a
bicycle ergometer exercise test with gas exchange analysis. The obese
cotwins had lower insulin sensitivity than their nonobese counterparts
(M value 6.1 ⫾ 2.0 vs. 9.2 ⫾ 3.2 mg 䡠 kg LBM⫺1 䡠 min⫺1, P ⬍ 0.01).
Transcript levels of genes involved in the oxidative phosphorylation
pathway (GO:0006119) in adipose tissue were lower (P ⬍ 0.05) in the
obese compared with the nonobese cotwins. The obese cotwins were
also less fit, as measured by V̇O2max (50.6 ⫾ 6.5 vs. 54.2 ⫾ 6.4 ml 䡠 kg
LBM⫺1 䡠 min⫺1, for obese vs. nonobese, P ⬍ 0.05), Wmax (3.9 ⫾ 0.5
vs. 4.4 ⫾ 0.7 W/kg LBM, P ⬍ 0.01) and also less active, by the
Baecke leisure time physical activity index (2.8 ⫾ 0.5 vs. 3.3 ⫾ 0.6,
P ⬍ 0.01). This implies that acquired poor physical fitness is associated with defective expression of the oxidative pathway components
in adipose tissue mitochondria.
(32–79%) (24, 41, 70). These results raise the possibility that
shared genetic influences underlie the association between
obesity, insulin resistance, and fitness. Recently, it has been
suggested that mitochondrial dysfunction might be a key factor
in development of insulin resistance (37). Several studies have
reported type 2 diabetic patients and “prediabetic” insulinresistant subjects to have impaired structure and function of
mitochondria (28, 48, 53, 54, 66) and decreased expression of
genes encoding key enzymes in oxidative metabolism and
mitochondrial function (47, 52). Petersen et al. (54) reported
reduced mitochondrial phosphorylation in insulin-resistant offspring of patients with type 2 diabetes compared with insulinsensitive control subjects. Decreased oxidative capacity of
mitochondria in insulin-resistant subjects was therefore suggested to be due to an inherited genetic defect (54).
Studies of monozygotic (MZ) twins have greatly contributed
to our understanding of environmental and lifestyle factors
impacting human phenotypes (43). Among genetically identical individuals, intrapair differences are caused ultimately by
environmental factors and can thus be used to study relationships while controlling for genetic influences. In the present
study, we studied genetically identical twins who were either
concordant or discordant for obesity to determine whether
lifestyle-related factors (obesity and/or physical inactivity)
decrease V̇O2max and influence the transcript levels of genes
involved in mitochondrial oxidative phosphorylation.
MATERIALS AND METHODS
OBESITY IS ASSOCIATED WITH poor physical fitness (15) and
insulin resistance (31, 32). Recent studies have suggested that
genetic factors account for a substantial fraction (estimates of
50 –90%) of the population variance in BMI (39, 65), insulin
action (23–52%) (16, 27, 35, 46, 60) and physical activity
Subjects. The study participants were recruited from the FinnTwin16 cohort (26, 62), a population-based, longitudinal study of five
consecutive birth cohorts (1975–1979) of twins and their siblings and
parents.
Twin pairs to the current study were recruited on the basis of their
responses to questions on weight and height at the age of 23–27 yr.
After all MZ twin pairs (n ⫽ 658) had been screened, we identified 18
pairs with a reported BMI difference of at least 4 kg/m2, such that one
cotwin was nonobese (mean BMI 25 kg/m2), whereas the other was
obese (mean BMI 30 kg/m2) (17, 25, 58, 59). Fourteen of these pairs
Address for reprint requests and other correspondence: L. Mustelin, Dept. of
Medicine, Div. of Diabetes, Haartmaninkatu 8, Rm. C426B, 00029 HUCH,
Helsinki, Finland.
The costs of publication of this article were defrayed in part by the payment
of page charges. The article must therefore be hereby marked “advertisement”
in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.
body composition; cardiorespiratory fitness; spiroergometry; gene
expression
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ACQUIRED POOR FITNESS IMPAIRS GENE EXPRESSION
(8 male and 6 female pairs) participated. In addition to these discordant pairs, we studied 10 concordant MZ pairs (5 male and 5 female
pairs) with a BMI difference of less than 2 kg/m2.
The subjects were healthy and normotensive and did not use any
medications except for oral contraceptives. Their weight had been
stable for at least 3 mo prior to the study. Two pairs had a family
history of type 2 diabetes. Monozygosity was confirmed by genotyping of 10 informative genetic markers (59). The subjects provided
written informed consent. The protocol was designed and performed
according to the principles of the Helsinki Declaration and was
approved by the Ethics Committee of the Helsinki University Central
Hospital.
Study design. In each subject, whole body insulin sensitivity, body
composition, and cardiorespiratory fitness were measured. The measurement of whole body insulin sensitivity was performed using the
euglycemic insulin clamp technique after an overnight fast. Prior to
the clamp, a needle biopsy of abdominal subcutaneous adipose tissue
was taken from 13 discordant pairs, as previously described (57). The
sample used for microarray analysis was immediately frozen in liquid
nitrogen and stored at ⫺80°C until isolation of RNA.
Whole body insulin sensitivity. Whole body insulin sensitivity was
measured using the euglycemic hyperinsulinemic clamp technique as
previously described (10, 58). The rate of the continuous insulin
infusion was 1 mU 䡠 kg⫺1 䡠 min⫺1.
Gene expression in adipose tissue. Total RNA was prepared from
frozen fat tissue (on average 250 mg) using the RNeasy Lipid Tissue
Mini Kit (Qiagen) according to the manufacturer’s protocol. Quality
of RNA was analyzed using the 2100 Bioanalyzer platform (Agilent
Technologies). Two micrograms of total RNA was treated according
to the conventional Affymetrix eukaryotic RNA labeling protocols
(Affymetrix, Santa Clara, CA). Fifteen micrograms of biotin-labeled
cRNA was fragmented according Affymetrix eukaryotic sample protocol. Hybridization, staining, and washing of the Affymetrix U133
Plus 2.0 chips were performed using the Affymetrix Fluidics Station
450 and Hybridization Oven 640 under standard conditions. Preprocessing of expression data was done using the GC-RMA algorithm.
Prior to analysis, the expression values were cotwin normalized,
which involved dividing the obese twin’s expression values with those
of the thin cotwin to correct for the identical genetic background.
The pathway analysis was done with an in-house nonparametric
analysis algorithm, where the objective is to find the optimal regulated
pathway compositions without prior criteria for significance for individual genes’ significant regulation or arbitrary P value/fold change
cutoffs, as described previously (57). Briefly, the probe sets were
ranked by the median fold change values between obese and lean
twins to “upregulated” and “downregulated” vectors. The Affymetrix
ProbeSetIDs were mapped to human genes using cross-references in
the Ensembl database, and the genes were queried for their GO
annotations. The topology of the GO tree (DAG tree) was fully
utilized by enumerating all available routes toward the root of the GO
tree and adding all encountered vertexes as GO annotations of the
given gene. For detecting the affected GO gene groups (“pathways”),
an iterative hypergeometric distribution P value-based calculation was
used, where the objective is to find the optimum P value for a set of
genes that belong to the same annotated GO gene collection (maximal
regulation for the pathway). Furthermore, the data were exhaustively
permuted by randomizing the gene ranks for each GO category, and
an empirical P value was interpreted from the distribution of 10,000
permutation cycles. The oxidative phosphorylation pathway (GO:
0006119) was queried as part of these pathway analyses (57) of the
genome-wide microarray expression profiles. The global pathway
analyses evaluate the significance of all individual GO categories
while taking into account the structure of the tree.
Gene transcription was compared using previously reported realtime PCR data (25, 56) and current Affymetrix data. The relationships
were as follows: 11␤-hydroxysteroid dehydrogenase-1 (11␤-HSD-1;
r ⫽ 0.68, P ⫽ 0.005), glucocorticoid receptor-␣ (r ⫽ 0.45, P ⫽ 0.11),
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adiponectin [r ⫽ 0.06, not significant (NS)], lipoprotein lipase (LPL;
r ⫽ 0.63, P ⫽ 0.012), peroxisome proliferator-activated receptor-␥
(PPAR␥; r ⫽ 0.77, P ⫽ 0.0001), leptin (r ⫽ 0.52, P ⫽ 0.01), CD68
(r ⫽ 0.09, NS), IL-6 (r ⫽ ⫺0.26, NS), and TNF-␣ (r ⫽ ⫺0.05, NS).
Body composition measurements. Body composition, including fat
mass, lean body mass (LBM), and percent whole body fat was
measured by dual-energy X-ray absorptiometry (DEXA; Lunar Prodigy, Madison, WI; software version 2.15) (44).
Cardiorespiratory exercise test. Work-conducted maximal exercise
test with gas exchange analysis (spiroergometry) was performed using
an electrically braked bicycle ergometer (900 ERG Ergometer; Marquette Hellige, Marquette Medical Systems) and by using a breathby-breath gas exchange analysis system (Vmax 229, Sensormedics)
with the test subject sitting upright. The initial workload was 40 W for
women and 50 W for men. It was then increased by 40 and 50 W,
respectively, at 3-min intervals until exhaustion [19 –20/20 on the
Borg scale for perceived exertion or respiratory quotient (RQ ⫽
V̇CO2/V̇O2) of at least 1.1].
Blood pressure was measured manually using a stethoscope and a
sphygmomanometer (Erka) from the left arm before, during, and 6 –10
min after exercise. A 12-lead ECG (Mason-Likar) was continuously
monitored and recorded during the exercise test using a computerized
device (Case12, Marquette). For measurement of respiratory gases, a
tightly attached face mask (Rudolph series 7910, Hans Rudolph) with
a dead space of 185 ml was used. Arterial O2 saturation (SaO2) was
assessed noninvasively with two pulse oxymeters (Datex-Ohmeda
3900 and Datex-Ohmeda 3800; Datex-Ohmeda). One sensor was
attached to the earlobe and one to the left middle finger.
A mass flow sensor of the gas exchange device (Sensormedics) was
used to measure forced expiratory volume in one second before
exercise, and tidal volume and minute ventilation during exercise.
From the breath-by-breath recordings ventilatory and gas exchange
variables were averaged at 30-s intervals using microcomputer-assisted equipment. The variables used for analysis are explained below.
Maximal oxygen uptake (V̇O2max) was defined as the peak oxygen
uptake. Maximal working capacity (Wmax) was defined as the mean
workload during the last 3 min of exercise. Mechanical efficiency (73)
and anaerobic threshold (AT) assessed from the slope change of
V̇CO2/V̇O2 were also calculated.
Physical activity. Physical activity was assessed using the Baecke
questionnaire (2). Work index refers to physical activity at work, sport
index to sport during leisure time, and leisure time index to physical
activity during leisure time excluding sports.
Statistical analyses. Student’s paired t-test was used to compare the
means between the leaner and heavier cotwins for normally distributed variables and Wilcoxon’s signed rank test for the intrapair
comparison of nonnormally distributed data. Statistical analyses were
performed using Stata 8.2 for Windows software (StataCorp, College
Station, TX). Calculation of correlation coefficients between acquired
intrapair differences in body composition and intrapair differences in
fitness or metabolic measurement controls for genetic and shared
environmental influences within MZ pairs. Pearson correlation and
linear regression was used in the intrapair and individual univariate
analyses. Multiple linear regression models were used to control for
confounding factors in some analyses. When using individual twins,
the P values were corrected for clustered sampling of cotwins within
pairs by survey methods (61). To combine male and female pairs, we
used sex-specific z-transformed values (i.e., mean of 0 and SD of 1)
of the study variables in all analyses.
RESULTS
Body composition. A pairwise comparison of the critical
traits for obesity-discordant and -concordant pairs is shown in
Table 1. In the discordant pairs, the heavier cotwin had, on
average, a 5.4 kg/m2 higher BMI, a 9.4% higher fat percentage,
12.9 kg more fat, and 2.4 kg more LBM than the leaner cotwin.
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Table 1. Characteristics of MZ cotwins discordant
and concordant for obesity
Discordant Pairs
Heavier
Concordant Pairs
Leaner
No. of subjects
14
14
Age, yr
25.7⫾1.5 25.6⫾1.5
Birth weight, g
2588⫾481 2464⫾526
Height, cm
171⫾9
171⫾9
Body weight, kg
89.8⫾9.4 74.5⫾8.8‡
BMI, kg/m2
30.6⫾2.0 25.4⫾1.8‡
%Body fat
38.3⫾6.5 29.5⫾8.5‡
Fat mass, kg
34.0⫾5.1 21.4⫾5.7‡
LBM, kg
52.8⫾9.8 50.4⫾10.2*
M value/LBM, mg 䡠 kg
–1
–1
LBM 䡠 min
6.1⫾2.1
9.1⫾2.9†
Blood hemoglobin, g/l 144⫾11
140⫾11
Heavier
Leaner
10
25.6⫾1.2
2537⫾702
173⫾8
81.5⫾22.1
27.3⫾7.4
27.0⫾11.7
21.0⫾10.6
53.6⫾10.9
10
25.7⫾1.2
2581⫾595
173⫾7
78.9⫾20.7*
26.3⫾7.2†
24.8⫾11.8*
18.9⫾10.3*
53.8⫾10.3
7.5⫾3.2
144⫾12
7.4⫾2.8
145⫾10
Data shown as mean ⫾ SD. MZ, monozygotic; LBM, lean body mass. *P ⬍
0.05, †P ⬍ 0.01, ‡P ⬍ 0.001 (Student’s paired t-test).
In the concordant pairs, the respective differences were 1.0
kg/m2, 2.2%, 2.1 kg fat, and 0.3 kg LBM.
Insulin sensitivity. The obese cotwins had significantly lower
whole body insulin sensitivity (M value) than their nonobese
counterparts (Table 1). Intrapair differences in whole body
insulin sensitivity were associated with those in V̇O2max (␤ ⫽
0.55, P ⬍ 0.05) in a model adjusting for BMI. In the obesityconcordant pairs, there were no differences between the
cotwins in insulin sensitivity.
Fitness. Cardiorespiratory exercise tests did not show any
pathological circulatory or respiratory changes in any measured and monitored variable. SaO2 remained normal (⬎96%)
in all subjects throughout the test. The cotwins of the concordant pairs did not differ from each other with respect to any of
the cardiorespiratory variables (Table 2). In the discordant
pairs, the obese cotwin had a significantly lower V̇O2max when
expressed per kilogram body weight (V̇O2max/kg, P ⬍ 0.001) or
kilogram LBM (V̇O2max/LBM, P ⬍ 0.05) than the nonobese
cotwin. Maximal working capacity, expressed per kilogram
LBM (Wmax/LBM), was significantly lower in the obese than
in the nonobese cotwin (P ⬍ 0.01). The obese cotwin also had
lower mechanical efficiency than the nonobese one (P ⬍ 0.05).
Regarding physical activity, the obese cotwin had a lower
leisure time index than the nonobese one (2.8 vs. 3.3, obese vs.
lean, P ⬍ 0.01). Work or sport indexes did not differ between
the cotwins (2.4 vs. 2.4 and 3.1 vs. 3.0, respectively). Correlations between V̇O2max/LBM and the physical and biochemical characteristics are shown in Table 3.
Transcript levels. The genome-wide transcript profiling of
fat biopsies showed that genes involved in the mitochondrial
oxidative phosphorylation pathway were significantly downregulated in the obese compared with the nonobese cotwins
(nominal P ⬍ 0.001, permuted P ⬍ 0.05). The rank of the
oxidative phosphorylation pathway was 123 among 184 significantly downregulated pathways. Among 68 genes in the
pathway, 31 were responsible for the optimum pathway composition (Fig. 1). The mean centroid [describing the average
activity of the regulated part of the pathway, as described by
Mootha et al. (47)] was calculated for the oxidative phosphorylation pathway and used to examine possible correlation with
V̇O2max. The oxidative phosphorylation pathway was found to
significantly correlate with V̇O2max and the M value in the twin
subjects (Fig. 2). These associations also remained significant
after adjusting for percent body fat in a multiple regression
model (␤ ⫽ 0.45, P ⬍ 0.05; ␤ ⫽ 0.29, P ⬍ 0.05, respectively).
DISCUSSION
The present study shows that, independent of genetic factors,
obesity is associated with poor fitness, low insulin sensitivity,
and decreased transcript levels of genes involved in mitochondrial oxidative phosphorylation. This conclusion is based on a
study of a group of genetically identical MZ twin pairs discordant or concordant for BMI. MZ twin pairs discordant for
obesity offer a unique opportunity to study effects of acquired
obesity independently of confounding genetic influences while
matching for age, sex, and many socioeconomic, childhood,
and familial factors. Monozygosity in the present study was
confirmed by genotyping of 10 informative genetic markers
(59). This study design controls in an ideal way for the genetic
effect on obesity. Obese cotwins were shown to have lower
whole body insulin sensitivity, V̇O2max, and Wmax relative to
Table 2. Cardiorespiratory exercise test: characteristics of MZ twin pairs discordant and concordant for obesity
Discordant Pairs
No. of subjects
Wmax, W
Wmax/LBM, W/kg LBM
V̇O2max, l/min
V̇O2max/BW, ml 䡠 kg BW–1 䡠 min–1
V̇O2max/LBM, ml 䡠 kg LBM–1 䡠 min–1
Mechanical efficiency, %
RQ
AT, l/min
AT/LBM, ml 䡠 kg LBM–1 䡠 min–1
Resting heart rate, min⫺1
Maximal heart rate, min⫺1
Resting systolic BP, mmHg
Resting diastolic BP, mmHg
Maximal systolic BP, mmHg
Concordant Pairs
Heavier
Leaner
Heavier
Leaner
14
197⫾41
3.9⫾0.5
2.60⫾0.59
29.2⫾4.7
50.8⫾6.2
22.0⫾1.4
1.1⫾0.04
1.3⫾0.5
25.3⫾7.2
78⫾9
187⫾7
133⫾15
71⫾12
193⫾30
14
215⫾63
4.4⫾0.6†
2.67⫾0.70
36.0⫾7.4‡
54.2⫾6.1*
23.1⫾1.3*
1.1⫾0.1
1.5⫾0.5
30.2⫾6.0*
75⫾11
187⫾10
126⫾15*
68⫾8
190⫾24
10
226⫾65
4.2⫾0.8
2.81⫾0.81
35.9⫾12.5
52.1⫾9.0
23.2⫾1.1
1.2⫾0.1
1.3⫾0.3
25.0⫾5.1
75⫾12
187⫾9
120⫾7
64⫾4
191⫾21
10
234⫾56
4.4⫾0.7
2.88⫾0.62
38.2⫾10.8
53.8⫾6.9
23.3⫾1.4
1.1⫾0.03
1.3⫾0.3
25.8⫾6.7
71⫾13
185⫾7
123⫾11
65⫾10
187⫾18
Data shown as mean ⫾ SD. V̇O2max, maximal O2 uptake, Wmax, maximal working capacity; BW, total body weight; RQ, respiratory quotient (V̇CO2max/
V̇O2max); AT, anaerobic threshold; BP, blood pressure. *P ⬍ 0.05, †P ⬍ 0.01, ‡P ⬍ 0.001 (Student’s paired t-test).
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Table 3. Correlations between V̇O2max/kg LBM and physical
and biochemical characteristics in all MZ twins (n ⫽ 48)
Correlation Coefficient
Birth weight, g
Height, cm
Body weight, kg
BMI, kg/m2
%Body fat
Fat mass, kg
M value/LBM, mg 䡠 kg LBM–1 䡠 min–1
Resting energy expenditure, kJ/day
Mean adipose tissue gene expression of oxidative
phosphorylation pathway (mean-centroid)a
⫺0.15
⫺0.15
⫺0.44†
⫺0.42†
⫺0.16
⫺0.22
0.45†
⫺0.26
0.42*
n ⫽ 22 (twins of discordant pairs for whom both gene expression data and
V̇O2max were available). *P ⬍ 0.05, †P ⬍ 0.01 (Pearson correlation corrrected
for clustered twin data).
a
their LBM than their nonobese counterparts. These physiological changes were accompanied by the significantly lower
transcript levels of genes involved in the mitochondrial oxidative phosphorylation pathway in adipose tissue.
V̇O2max was reduced in the obese compared with the nonobese twin when expressed per kilogram LBM and per kilogram
body weight but not when expressed as milliliters per minute.
The finding that V̇O2max per minute is not negatively influenced
by obesity is consistent with several studies (9, 18, 36, 40, 42,
63), as is the finding that V̇O2max per kilogram total body
weight is lower in obese than in nonobese subjects (9, 12, 18,
Fig. 2. Relationships between mean oxidative phosphorylation pathway activity and maximal O2 consumption (V̇O2max; r ⫽ 0.42, P ⬍ 0.05; A) and the M
value (r ⫽ 0.35, P ⬍ 0.05; B). LBM, lean body mass. Scale unit is 1 SD, and
the sample mean is in the middle of the scale.
Fig. 1. Transcription of the genes in the oxidative phosphorylation pathway
(GO:0006119) was coordinately downregulated in the obese cotwins’ adipose
tissue compared with transcription in the nonobese cotwins’ adipose tissue in 13
monozygotic (MZ) twin pairs discordant for obesity. The nonobese cotwins’ gene
expression values are set as 1.0. The x-axis shows the ratio of the obese to non-bese
cotwins’ expression values. On the y-axis are the 30 most differentially expressed
genes until optimum pathway composition was reached.
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22, 36, 42, 63, 64). Since muscle tissue is the main site of V̇O2
during maximal exertion, V̇O2max divided by LBM seems the
most unbiased way of comparing cardiorespiratory fitness of
individuals of different sizes (11, 72). Previous studies expressing V̇O2max per kilogram LBM have shown either decreased (9,
22, 23, 67, 69) or unchanged (12, 18, 34, 40) V̇O2max in obese
compared with nonobese subjects. Possibly, genetic differences as well as those in age, sex, family environment, and
physical activity could, together with small sample sizes, have
confounded comparison of obese and nonobese subjects in the
latter studies (12, 18, 34, 40).
Several studies have reported impaired mitochondrial activity (28, 48, 53–55, 66) or decreased transcript levels of genes
involved in mitochondrial oxidative metabolism (47, 52) in
skeletal muscle of insulin-resistant subjects. Kelley et al. (28)
reported smaller mitochondria and reduced activity of the
electron transport chain in obese subjects and type 2 diabetic
patients compared with normal-weight, insulin-sensitive control subjects. Patti et al. (52) and Mootha et al. (47) both found
reduced expression of genes encoding proteins involved in
mitochondrial oxidative metabolism in skeletal muscle from
insulin-resistant subjects. Reduced rates of mitochondrial
phosphorylation (54), impaired insulin-stimulated ATP synthesis (55), reduced mitochondrial density (48), and prolonged
phosphocreatine recovery half-time (66) have also been found
to characterize skeletal muscle of type 2 diabetic patients.
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These results supported the concept that mitochondrial dysfunction and subsequent impairments in the oxidative metabolism characterize insulin-resistant subjects, possibly representing critical etiological factors (37). Very recently, however, Boushel et al. (7) suggested that mitochondrial function is
normal in type 2 diabetes. They showed that, although overall
muscle oxidative capacity was lower in the type 2 diabetic
patients, their mitochondrial function was unimpaired. They
thus concluded that the impairment of oxidative phosphorylation and electron transport can be attributed to diminished
mitochondrial content in the diabetic muscle.
When pursuing the explanation for the discrepant findings in
the above studies, physical activity/fitness of the study groups
needs to be considered. In the study by Mootha et al. (47),
subjects with impaired glucose tolerance as well as those with
type 2 diabetes had significantly lower V̇O2max than those with
normal glucose tolerance. This could indicate a lower level of
physical activity in the insulin-resistant study groups compared
with the control group, although this was not specifically
assessed. Schrauwen-Hinderling et al., on the other hand,
found no significant difference in V̇O2max between obese subjects with type 2 diabetes and similarly obese subjects with
normal glucose tolerance (66). Since there was a trend toward
better V̇O2max in the non-insulin-resistant subjects, the nonsignificant result might simply reflect the small study sample (12
diabetic subjects and 9 nondiabetic control subjects). In only
two of the above studies (54, 55) were the study groups
matched for physical activity. The method of physical activity
assessment was not, however, explained in the studies by
Petersen et al. (54, 55). Additionally, two studies investigated
only subjects defined as sedentary (48, 52) but presented no
further data on their physical activity. In conclusion, none of
the studies reporting mitochondrial dysfunction in insulinresistant subjects properly measured physical activity and/or
fitness, although exercise training is known to increase mitochondrial content and oxidative capacity of skeletal muscle
fibers (1, 19 –21) as well as to enhance insulin sensitivity (6, 8,
49, 50, 68) and prevent progression of impaired glucose tolerance to type 2 diabetes (13, 30, 33, 51).
In the present study, we found significant reduction of
transcript levels of genes encoding components of mitochondrial oxidative phosphorylation in adipose tissue in obese
monozygotic cotwins. We recognize the limitation of the use of
adipose tissue instead of skeletal muscle tissue. However, our
results of fat biopsies are in line with previous studies reporting
reduced oxidative metabolism and downregulation of genes
involved in oxidative phosphorylation in obese and insulinresistant subjects’ muscle (28, 47, 48, 52–55, 66). The finding
that this is also true in obese and nonobese subjects with
identical genes is novel. It shows that lifestyle-related factors,
mainly physical inactivity and acquired obesity, are enough to
significantly impair expression of genes encoding proteins
involved in mitochondrial oxidative phosphorylation. This is in
agreement with the findings of Boushel et al. (7) as well as
intervention studies reporting improvements of mitochondrial
function in response to physical activity (45, 71).
Although we found that the reduced transcript levels of
genes encoding mitochondrial oxidative phosphorylation in
obesity is influenced by environmental and acquired factors, it
does not exclude the possibility that genetic factors contribute
to regulation of mitochondrial oxidative metabolism, as has
AJP-Endocrinol Metab • VOL
been shown for V̇O2max (4, 5, 14, 29, 38), physical activity (24,
41), and the V̇O2max response to physical training (3). The
heritability estimates for V̇O2max vary between 50 and 67% in
the two most recent studies (4, 38).
In conclusion, acquired obesity decreases physical fitness,
whole body insulin sensitivity, and expression of mitochondrial genes involved in oxidative phosphorylation independently of genetic influences. These data suggest that physical
inactivity may have contributed to the defects in mitochondrial
oxidative phosphorylation described in type 2 diabetic patients
and prediabetic subjects. The latter possibility, however, needs
to be tested in an intervention study.
ACKNOWLEDGMENTS
We thank Erjastiina Heikkinen, Katja Tuominen, and Mia Urjansson for
excellent assistance, Juha Saharinen for expertise, and Anna Keski-Rahkonen
for collegial help and valuable comments on the manuscript.
GRANTS
Data collection and analyses have been supported by the National Institute
on Alcohol Abuse and Alcoholism (Grants AA-08315, AA-00145, and AA12502), the European Union Fifth Framework Program (QLRT-1999-00916,
QLG2-CT-2002-01254), the Academy of Finland (Grants 44069, 100499, and
201461), and Helsinki University Central Hospital grants. L. Mustelin and K.
Pietiläinen were supported by the Juho Vainio Foundation and K. Pietiläinen
by the Yrjö Jahnsson Foundation. L. Peltonen and J. Kaprio were supported by
the Center of Excellence in Common Disease Genetics of the Academy of
Finland.
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