Diabetologia (2012) 55:1424–1434
DOI 10.1007/s00125-011-2442-8
ARTICLE
Effect of exercise training on insulin sensitivity, mitochondria
and computed tomography muscle attenuation in overweight
women with and without polycystic ovary syndrome
S. K. Hutchison & H. J. Teede & D. Rachoń &
C. L. Harrison & B. J. Strauss & N. K. Stepto
Received: 25 August 2011 / Accepted: 9 December 2011 / Published online: 13 January 2012
# Springer-Verlag 2012
Abstract
Aims/hypothesis Polycystic ovary syndrome (PCOS) is an
insulin resistant (IR) state. Increased skeletal muscle lipid
content and impaired mitochondrial biogenesis have been
implicated in the pathogenesis of IR. We investigated
whether differences in these variables explain the IR of
Electronic supplementary material The online version of this article
(doi:10.1007/s00125-011-2442-8) contains peer-reviewed but unedited
supplementary material, which is available to authorised users.
S. K. Hutchison : H. J. Teede : D. Rachoń : C. L. Harrison :
N. K. Stepto
Jean Hailes Foundation Research, School of Public Health and
Preventative Medicine, Monash University,
Melbourne, VIC, Australia
S. K. Hutchison : H. J. Teede
Diabetes Unit, Southern Health,
Melbourne, VIC, Australia
D. Rachoń
Department of Clinical and Experimental Endocrinology,
Medical University of Gdańsk,
Gdańsk, Poland
C. L. Harrison
Department of Physiology, Monash University,
Melbourne, VIC, Australia
B. J. Strauss
Department of Medicine, Monash University,
Melbourne, VIC, Australia
N. K. Stepto
Institute of Sport Exercise and Active Living, Victoria University,
Melbourne, VIC, Australia
N. K. Stepto (*)
School of Sport and Exercise Science, Victoria University,
PO Box 14428, Melbourne, VIC 8001, Australia
e-mail: Nigel.Stepto@vu.edu.au
women affected by PCOS and whether improvements in
IR with exercise are reflected by changes in these variables.
Methods Sixteen PCOS and 13 non-PCOS overweight
women were assessed, and eight PCOS and seven nonPCOS women were reassessed after 12 weeks of moderate
and vigorous exercise training. Outcomes included insulin
sensitivity (glucose infusion rate [GIR]), skeletal muscle
gene expression and protein abundance, enzyme activity of
selected mitochondrial components, and computed tomography (CT) attenuation-estimated muscle lipid.
Results GIR was lower in women with PCOS versus those
without (p 00.01) and increased with exercise in both
groups. Baseline CT muscle attenuation suggested a trend
to less muscle lipid in PCOS, which increased with exercise
training, with a difference in the change in muscle lipid
(p00.01, age-corrected), compared with non-PCOS women.
GIR correlated with PGC1A gene expression across the
whole group; skeletal muscle expression of mitochondrial
biogenesis markers was not different between groups at
baseline, or after training. Neither lipid changes nor mitochondrial changes correlated with changes in GIR.
Conclusions/interpretation Differences in IR in women with
and without PCOS were not explained by differences in skeletal muscle lipid or mitochondrial parameters. Improvements in
IR with exercise were dissociated from mitochondrial parameters. CT muscle attenuation suggested a differential capacity of
PCOS muscle to store lipid compared with non-PCOS.
Trial registration: Clinicaltrials.gov ISRCTN84763265
Funding: National Health & Medical Research Council
(Grant number 606553), Monash University and The Jean
Hailes Foundation.
Keywords Insulin resistance . Mitochondrial function .
Muscle lipid content . Polycystic ovary syndrome
Diabetologia (2012) 55:1424–1434
Abbreviations
β-HAD
β-Hydroxyacyl-CoA dehydrogenase
CS
Citrate synthase
CT
Computed tomography
Ct
Cycle threshold
DGAT1
Diacylglycerol acyltransferase
GIR
Glucose infusion rate
HU
Hounsfield unit
IMCL
Intramyocellular lipid
IR
Insulin resistance
NRF1
Nuclear respiratory factor-1
OXPHOS Oxidative phosphorylation
PCOS
Polycystic ovary syndrome
PGC1α
Peroxisome-proliferator activated receptor γ
coactivator 1α
SHBG
Sex hormone-binding globulin
TFAM
Mitochondrial transcription factor A
V O2max
Maximal oxygen uptake
Introduction
Polycystic ovary syndrome (PCOS) is the most common
endocrinopathy of reproductive-age women, affecting 8–
18% [1]. Women with PCOS (PCOS women) have both
increased intrinsic insulin resistance (IR) compared with body
composition of matched women without PCOS (non-PCOS
women) [2–4] and obesity-related extrinsic IR. IR in PCOS
underpins reproductive and metabolic features [2] including
increased risk of prediabetes and type 2 diabetes [3, 5]. The
mechanism of IR in PCOS remains unclear [3].
Muscle lipid content has been proposed to play a role in
IR, with various measures correlating with IR (reviewed by
Lara-Castro and Garvey [6]) including computed tomography (CT) muscle attenuation [7]. Lipid is stored both around
and within muscle cells. Elevated intramyocellular lipid
(IMCL) is hypothesised to mediate IR. IMCL increase itself
may be a consequence of impaired mitochondrial function
[8]. CT muscle attenuation, although unable to distinguish
intra- from extra-myocellular lipid, is a non-invasive assessment of muscle lipid content that correlates with IMCL
assessed using biopsy tissue and magnetic resonance spectroscopy [9, 10]. The role of muscle lipid content in IR is not
clear in PCOS.
Reduced skeletal muscle mitochondrial function has been
associated with IR in patients with type 2 diabetes [11],
those at risk of diabetes [12], and the elderly [13]. Peroxisome
proliferator-activated receptor γ coactivator 1α (PGC1α) is a
key nuclear-encoded regulator of mitochondrial biogenesis
and energy metabolism [14, 15]. PGC1A (also known as
PPARGC1A) gene expression is lower in patients with type 2
diabetes than controls [16] and correlates with downregulation
1425
of genes encoding enzymes involved with oxidative phosphorylation (OXPHOS) [17]. Similar findings were obtained
in a cross-sectional study of IR PCOS women [18]; however,
confounding factors were not documented. Protein abundance
of OXPHOS components and enzyme activity has not been
studied in PCOS to date.
Some interventions in obesity and type 2 diabetes improve IR and mitochondrial function in parallel; however,
results can be discordant (reviewed by Turner and Heilbronn
[19]). The only interventional study in PCOS to investigate
mitochondrial function showed that the insulin sensitiser,
pioglitazone, improved both IR and mitochondrial function
[20]. Improved mitochondrial function has been demonstrated with exercise [21]. The response to exercise is not as
clear in obese and diabetic patient groups. Exercise combined with energy restriction improves mitochondrial function in obese people [22], but exercise alone failed to
improve mitochondrial function in those whose IR improved [23]. IMCL has been shown to decrease with dietinduced weight loss in type 2 diabetes, but did not change
with a combination of diet and exercise [24]. Despite the
relationship between increased IMCL and IR, exercise may
increase IMCL content while improving IR, the so-called
‘athlete’s paradox’ [25]. To our knowledge, the effect of
exercise training on mitochondrial function and muscle lipid
content has not been studied in PCOS.
PCOS is a condition characterised by IR greater than
expected for body weight. We hypothesise that high muscle
lipid content and/or low mitochondrial content contribute to
this IR. Furthermore we expected exercise-induced improvements in IR would be accompanied by reduced muscle lipid
content and increased mitochondrial biogenesis.
Methods
Participants Overweight and obese (BMI >27 kg/m2) sedentary premenopausal women with (n016) and without (n013)
PCOS were recruited from community advertisements. PCOS
was diagnosed by an endocrinologist (S.K. Hutchison) after
clinical exclusion of other causes of hyperandrogenism based
on the 1990 National Institutes of Health criteria as previously
reported [26]. All non-PCOS women had regular menses and
no evidence of clinical or biochemical hyperandrogenism.
Exclusion criteria included type 2 diabetes, regular physical
activity and pregnancy [26]. The Southern Health Research
Advisory and Ethics Committee approved the study, and
participants gave written informed consent.
Study design At screening 3 months before baseline, standard
diet and lifestyle advice was delivered (Heart Foundation
recommendations [www.heartfoundation.org.au]). Medications affecting end points, including insulin sensitisers, anti-
1426
androgens and hormonal contraceptives, were ceased. Data
were collected after 3 months (baseline) and after 12 weeks of
exercise training (study completion) in the follicular phase of
the menstrual cycle wherever feasible.
Exercise intervention Participants undertook 12 weeks of
supervised, progressive, moderate and vigorous exercise
training on a motorised treadmill as described previously.
Briefly, participants attended three 1 h sessions each week,
which sequentially alternated between moderate-intensity
(walking or jogging at 70% of maximal oxygen uptake
[V O2max ]) and high-intensity (six 5 min intervals with a
2 min recovery period at ∼95–100% of V O2max ) interval
training. Participants’ exercise was progressively increased
over the study [27]. V O2max tests were repeated at 6 and
12 weeks to assess changes in fitness and maximal heart
rate. Heart rate monitors were used in all sessions (Polar
Electro Oy, Kempele, Finland).
Clinical and biochemical measurements Participants’ body
weight, height, BMI, waist circumference and percentage
body fat were measured by body composition technicians in
Monash Medical Centre Body Composition Laboratory.
Mean thigh muscle attenuation on CT scan was used to
assess muscle lipid content. Participants were placed in a
supine position, and a cross-sectional scan of both legs was
obtained at the mid-thigh (defined as the mid-point between
the anterior iliac crest and the patella). All scans were
performed using a General Electric Lightspeed CT scanner
(GE Medical Systems, Milwaukee, WI, USA) and saved as
DICOM images for analysis. Standard CT procedures of
120 kV, 5 mm thickness and a 512×512 matrix were used
for all participants, and images were analysed using SliceO-Matic version 4.3 software (Tomovision, Magog, QC,
Canada). Attenuation levels for delineating fat (less than –30
Hounsfield units [HU]) and muscle (−29 to 150 HU) and
manual demarcation of muscle from bone and subcutaneous
and intermuscular fat were used as previously described [28].
Mean muscle attenuation was determined by averaging all
pixels within the range −29 to 150 HU. The higher the attenuation, the less lipid is present in the muscle [7].
V O2max and maximum heart rate were assessed using the
MOXUS modular system (AEI Technologies, Pittsburgh, PA,
USA) while participants exercised on a treadmill (Biodex
RTM 500, New York, USA) until volitional fatigue [27].
Insulin sensitivity was assessed by the euglycaemic–
hyperinsulinaemic clamp technique as previously described
[26]. Clamp timing was standardised to 48 h after exercise,
and included a standardised high-carbohydrate diet before an
overnight fast. Insulin (Actrapid; Novo Nordisk, Bagsvaerd,
Denmark) was infused at 40 mU m−2 min−1 for 120 min, with
plasma glucose maintained at ∼5 mmol/l using variable infusion rates of 25% glucose. Glucose infusion rates (GIRs) were
Diabetologia (2012) 55:1424–1434
calculated during steady state, achieved in the last 30 min of
the clamp and expressed as glucose (mg) per body surface
area (m2) per min [26].
Blood sampling and analysis were performed as previously described [26]. HbA1c was determined using highperformance liquid chromatography using the Glycohemoglobin Analyzer model HLC-723 GHbV A1c2.2 (Tosoh
Corporation, Tokyo, Japan). The free androgen index was
calculated as testosterone/sex hormone-binding globulin
(SHBG)×100.
Muscle samples Thigh vastus lateralis muscle was obtained
by percutaneous biopsy under local anaesthesia immediately
before the insulin clamp [29]. Muscle biopsy samples were
blotted and dissected free of any connective and fat tissue,
immediately frozen in liquid nitrogen, and then stored
at −80°C for later analysis.
Muscle total RNA isolation Total RNA was isolated from the
muscle (15–20 mg) using the RNeasy Total RNA Kit (Qiagen,
Hilden, Germany) as previously described [29]. The total
RNA content and purity were established by measuring absorbance at 260 and 280 nm (NanoDrop; Eppendorf South
Pacific, North Ryde, NSW, Australia). Afterwards, each
sample was diluted with RNase-free water to a concentration
of 10 ng/μl and stored at −80°C for subsequent analysis.
Reverse transcription and real-time PCR RNA samples
were reverse transcribed in a thermal cycler (Perkin Elmer
GeneAmp PCR 2400 thermal cycler; Perkin Elmer, Rowville,
VIC, Australia) using Taqman reverse transcription reagents
(Applied Biosystems, Foster City, CA, USA) in 10 μl reaction
mixtures containing 1× Taqman RT buffer, 5.5 mmol/l MgCl2,
500 μmol/l 2′-deoxynucleoside 5′-triphosphate, 2.5 μmol/l
random hexamers, 0.4 U/μl RNase inhibitor and 1.25 U/μl
multiscribe reverse transcriptase. The reaction conditions were
as follows: 25°C for 10 min, 48°C for 30 min, and 95°C for
5 min.
Relative gene expression was quantified by real-time
PCR. All reactions were performed according to the multiplex cycle threshold (Ct) method using the reference gene
(ribosomal 18S) and the gene of interest in the same well.
The reference gene did not change with exercise. PCRs were
performed on a BioRad i-CYCLER iQ real-time PCR detection system in 25 μl reaction volume of BioRad iQ
Supermix PCR mix (BioRad Laboratories, Gladesville,
NSW, Australia), Applied Biosystems pre-developed assay
reagent for 18S, the forward and reverse primers and probes
of the genes of interest (electronic supplementary material
[ESM] Table 1) and sterile water. Probes and primers were
designed (Primer Express version 1.0; Applied Biosystems)
from the human gene sequence accessed from GenBank/
EMBL [30].
Diabetologia (2012) 55:1424–1434
Comparative Ct calculations for the expression of the
studied genes were performed subtracting the 18S Ct values
from Ct values of the gene of interest to derive a ΔCt value.
The expression of the studied genes was then calculated
according to the formula: 2 $Ct [31].
Protein extraction and analyses (western blots) Muscle tissue (15–20 mg) was homogenised (Polytron; Brinkman
Instruments, New York, NY, USA) in ice-cold buffer containing 50 mmol/l HEPES, 150 mmol/l NaCl, 10 mmol/l NaF,
1 mmol/l Na3VO4, 5 mmol/l EDTA, 0.5% Triton X-100, 10%
glycerol (vol./vol.), 2 μg/ml leupeptin, 100 μg/ml phenylmethanesulfonyl fluoride and 2 μg/ml aprotinin. All chemicals were from Sigma-Aldrich (North Ryde, NSW, Australia).
Homogenates were then centrifuged (16,000×g for 60 min at
4°C), and the supernatant fractions were removed and rapidly
frozen in liquid nitrogen. Protein concentrations of the muscle
lysates were determined using the BCA assay kit (Pierce,
Rockford, IL, USA). For analysis of protein abundance , equal
quantities of protein (35 μg) were resolved by SDS-PAGE on
10% polyacrylamide gels, transferred to a nitrocellulose membrane, blocked with 5% BSA, and immunoblotted overnight
with the antibodies (diluted 1:1000) directed against: complex
I subunit NDUFB8 (MS105); complex II–30 kDa (MS203);
complex III–core protein 2 (MS304); complex IV subunit II
(MS405); complex V α subunit (MS507; MitoProfile Total
OXPHOS Complexes Detection Kit, Eugene, OR, USA); and
PGC1α (1:1,000; Chemicon International, Boronia, VIC,
Australia). After incubation with horseradish peroxidaseconjugated secondary antibody (1:2,000; Amersham Biosciences, Castle Hill, NSW, Australia), the immunoreactive
proteins were detected with enhanced chemiluminescence
(Perkin Elmer) and quantified by densitometry.
Analysis of muscle enzyme activity The remaining muscle
biopsy fragments (5–10 mg) were homogenised in 1:50
dilution (wt/vol.) of a 175 mmol/l potassium buffer solution.
Citrate synthase (CS) and β-hydroxyacyl-CoA dehydrogenase (β-HAD) activities were analysed by measuring the
disappearance of NADH spectrophotometrically at a constant
temperature of 25°C [32].
Statistical analysis All data are presented as mean±SE.
Data were assessed for normality using Kolmogorov–Smirnov
tests and log-transformed where appropriate (insulin). Results
are presented for 29 participants at baseline (16 PCOS and 13
non-PCOS women) except for GIR (n028, PCOS n016, nonPCOS n012). At completion, results are presented for n015
(PCOS n08, non-PCOS n07) except for GIR (n014, PCOS
n07, non-PCOS n07) and CT data (n014, PCOS n08, nonPCOS n06). Two-tailed statistical analysis was performed
using SPSS for Windows 17.0 software (SPSS, Chicago, IL,
USA), with statistical significance set at α level of p<0.05.
1427
Data were assessed using Student’s t test with general linear
modelling to correct for age. The χ2 test was used for difference in proportions. Relationships between variables were
examined using bivariate (Spearman) correlations. The effect
of exercise training was examined using repeated-measures
ANOVA (PCOS status×time) with correction for age and
BMI. Change in variable was defined as ratio of pretreatment
to post-treatment value.
Results
Participants comprised a subset from a previous study
[26] and were included if adequate muscle biopsy tissue
was available. In total, 16 PCOS and 13 non-PCOS
women completed the 3-month run-in with stable diet
and withdrawal of relevant medications. Eight PCOS
and seven non-PCOS women completed 12 weeks of
training.
PCOS vs non-PCOS women: baseline characteristics
(Table 1) PCOS women were younger than non-PCOS
women (30.7± 1.4 vs 34.5±1.1 years, p00.04) and had
higher androgen concentrations and lower SHBG and
HDL concentrations. PCOS women had ∼36% lower GIR
(p00.01) than non-PCOS women despite similar BMI and
body fat percentage, fitness measured by V O2max , and frequency of family history of type 2 diabetes. There was a
trend to greater CT thigh muscle attenuation in the PCOS
women (49.5±0.67 vs 47.5±0.93 HU, p00.08), reflecting
lower muscle lipid content. Correction for age did not alter
the findings (data not shown).
PCOS vs non-PCOS women: markers of mitochondrial
biogenesis and function There were no differences between
PCOS and non-PCOS women in PGC1A, TFAM and NRF1
gene expression (Fig. 1a) and no differences in protein
abundance or gene expression of OXPHOS enzymes
(Fig. 1a,c). However, there were trends to lower PGC1A
gene expression (p00.16) and higher PGC1α protein abundance (p00.11) in the PCOS group with an inverse correlation between protein and mRNA levels (r0−0.37, p00.05).
There was no difference in CS and β-HAD activity between
PCOS and non-PCOS women (Fig. 1b).
There was a correlation between GIR and PGC1A gene
expression (r00.44, p00.02) (Fig. 2a) irrespective of PCOS
status with a trend to a negative correlation with PGC1α
protein abundance (r0−0.34, p00.09). None of the other
mitochondrial markers correlated with GIR. Triacylglycerol
was associated with PGC1A gene expression (r0−0.68,
p<0.01) but not PGC1α protein abundance (Fig. 2b). There
was no correlation between the mitochondrial measurements
and V O2max , BMI, weight or age. Thigh muscle attenuation
1428
Diabetologia (2012) 55:1424–1434
Table 1 Baseline characteristics
of participants
Data are means±SE except for
insulin (median [interquartile
range]; p values from
log-transformed data)
Characteristic
Non-PCOS (n013)
30.7±1.4
103.1±2.8
106.3±3.2
0.47
BMI (kg/m²)
Body fat (%)
36.0±1.3
49.7±1.4
37.0±1.7
48.1±1.0
0.64
0.33
Thigh muscle attenuation (HU)
GIR (mg m−2 min−1)
Fasting glucose (mmol/l)
47.5±0.93
257.6±18.6
4.8±0.1
49.5±0.67
170±24.1
4.9±0.1
0.08
0.01
0.36
Fasting insulin (pmol/l)
Testosterone (nmol/l)
84.2 (68.3–134.1)
1.6±0.2
169.2 (114.0–212.7)
2.7±0.2
0.03
<0.01
SHBG (nmol/l)
45.3±8.2
28.3±2.0
0.04
FAI
Cholesterol (mmol/l)
4.6 ±1.0
4.8±0.2
10.4±1.1
5.0±0.3
<0.01
0.68
Triacylglycerol (mmol/l)
1.2±0.2
1.5±0.2
0.22
HDL-cholesterol (mmol/l)
1.3±0.1
1.0±0.1
0.02
LDL-cholesterol (mmol/l)
V O2max (ml kg−1 min−1)
3.0±0.2
25.0±0.9
3.3±0.2
23.7±1.3
0.43
0.43
across the whole group, and there was a significant
between-group difference in change in weight (p00.03)
and waist circumference (p00.02), both decreasing more
in the non-PCOS than in the PCOS women (Table 2). GIR
increased with training, with a significant within-group improvement in the PCOS group (p00.01) and a trend to
improvement in the non-PCOS group (p00.07), with no
between-group difference.
PCOS vs non-PCOS women: effect of exercise training
(Table 2) Exercise attendance was similar for both groups
(97% PCOS, 92% non-PCOS, p00.19). V O2max improved
with exercise training (p<0.01) within each group (Table 2).
Exercise training resulted in decreased BMI and weight
a
b
1.5
Enzyme activity (AU)
mRNA expression (AU)
0.04
34.5±1.1
Waist (cm)
correlated with β-HAD (r00.38, p00.04) and was inversely
correlated with HDL (r0−0.38, p00.04).
1.0
0.5
0.0
PGC1A
Protein abundance (AU)
p value
Age (years)
FAI, free androgen index
c
PCOS (n016)
TFAM
NRF1
1.5
1.0
0.5
0.0
COX-4
β-HAD
CS
2.0
d
1.5
Con
UT
100 kDa
1.0
0.5
T
PCOS
UT
T
PGC1α
50 kDa
37 kDa
Complex V
Complex III
Complex II
25 kDa
20 kDa
Complex IV
Complex I
0.0
PGC1α
Complex I Complex II Complex III Complex IV Complex V
Fig. 1 mRNA expression, protein production and enzyme activity of
mitochondrial biogenesis genes. a mRNA expression of PGC1A, mitochondrial transcription factor A (TFAM), nuclear respiratory factor-1
(NRF1) and cytochrome oxidase subunit 4 (COX4) genes determined
by real time quantitative PCR. b β-HAD and CS enzyme activity was
determined by measuring the disappearance of NADH spectrophotometrically. c Protein production of PGC1α, complex I (subunit
NDUFB8), complex II (30 kDa subunit), complex III (core protein
2), complex IV (subunit II), complex V (α subunit) measured by
western blotting. d Representative immunoblots of PGC1α and the
mitochondrial complex proteins for a control (Con) and a PCOS
woman (PCOS), in both untrained (UT) and trained (T) state. Data
represent means ± SE from 16 PCOS (black bars) expressed relative to
13 non-PCOS (white bars) women (AU, arbitrary units; control 01)
Diabetologia (2012) 55:1424–1434
a
40
Mean thigh muscle attenuation
on CT (HU)
a
1429
PGC1A mRNA (×10−6)
35
30
25
20
15
10
52
51
50
49
48
47
46
Non-PCOS
PCOS
5
b
0
50
100
150
200
250
Glucose infusion rate (mg
b
300
m−2
350
400
min−1)
40
PGC1A mRNA (×10−6)
35
30
Triacylglycerols (mmol/l)
0
25
1.8
*
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0
Non-PCOS
PCOS
20
15
10
5
0
0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
4.0
4.5
Fig. 3 Change in CT thigh muscle attenuation and triacylglycerol with
exercise training. Data represent means±SE from eight PCOS and
seven non-PCOS women before and after exercise (black and white bars,
respectively). Significant within-group change with exercise (*p<0.05).
Significant between-group differences in change in CT attenuation and
triacylglycerol with exercise training (†p<0.05 adjusted for age)
Triacylglycerol (mmol/l)
Fig. 2 Scatterplot of PGC1A gene expression versus (a) GIR (trend
line PGC1A 01.32×10−6 +2.34×GIR×10−6) and (b) triacylglycerol
(trend line PGC1A 02.43×10−6 −4.75×TG×10−7, where TG is triacylglycerol). Black circles, PCOS; white circles, non-PCOS
As previously reported, there was a between-group difference in the change in triacylglycerol (p00.01), with
PCOS women showing a reduction in triacylglycerol
(p00.02), and no change in non-PCOS women (p00.09;
Fig. 3) [26]. Fasting insulin decreased within the PCOS
group (p00.04). There was a between-group difference in the
change in CT muscle attenuation (p00.05, p00.01 corrected
for age) with trends to decreased attenuation in the PCOS
women (p00.19), reflecting increased muscle lipid content,
compared with the increased attenuation in non-PCOS women
(p00.18), reflecting the opposite (Fig. 3). The change in triacylglycerol correlated with change in thigh muscle attenuation
(r00.54, p00.04).
There were no changes in any of the mitochondrial
markers with exercise training within the whole group or
between the two groups (Table 3). Within-group analyses
revealed that electron-transport chain complex V α subunit
and core 2 protein (complex III) increased in the non-PCOS
group (p00.02 and p00.04, respectively), and expression of
the COX4 (also known as COX4I1) gene increased in the
PCOS group (p00.02; Table 3).
Discussion
The results of this study show that overweight women with
PCOS had lower insulin sensitivity than a weight- and
fitness-matched comparison group. Contrary to our prediction, however, there was no evidence that this difference in
insulin sensitivity could be explained by a corresponding
reduction in muscle mitochondrial content or functional
markers. A novel finding was a trend to higher muscle
attenuation (lower muscle lipid) in the PCOS women at
baseline and a differential between-group effect of exercise
training on thigh muscle attenuation. We have previously
reported a similar between-group effect on serum triacylglycerol [26], with levels decreasing in the PCOS women with
training. CT thigh muscle attenuation tended to decrease in
the PCOS women, reflecting higher muscle lipid content
after exercise training, whereas there was a trend to increased thigh muscle attenuation in the non-PCOS women.
No direct correlation was found between these measures and
GIR, but it does suggest an unexpected differential capacity
for lipid storage in PCOS women that may contribute to the
metabolic phenotype. There were no differences in a broad
range of genes, proteins and enzyme activities reflecting
mitochondrial biogenesis and function when compared with
non-PCOS women of similar weight. Furthermore, mitochondrial markers did not change with exercise training-
1430
Table 2 Effects of exercise training on weight, hormonal and metabolic variables
Variable
Non-PCOS (n07)
PCOS (n08)
p value for effect
of exercise training
p value for change
over study, PCOS
vs non-PCOS
Pre
Post
Pre
Post
BMI (kg/m²)
37.6±2.3
36.4±2.0a
Weight (kg)
Waist (cm)
Thigh muscle attenuation (HU)
Fasting glucose (mmol/l)
100.4±5.6
105.6±3.7
48.0±1.2
4.7±0.1
97.6±5.0a
100.6±4.7a
48.7±1.2
4.8±0.1
35.6±2.2
95.2±6.6
104.6±5.1
50.2±1.1
5.1±0.2
35.5±2.3
94.6±6.8
105.6±4.9
49.7±1.0
5±0.1
0.02
<0.01
0.09
0.82
0.97
0.06
0.03
0.02
0.05b
0.58
Fasting insulin (pmol/l)
GIR (mg m−2 min−1)
SHBG (nmol/l)
Testosterone (nmol/l)
FAI
Cholesterol (mmol/l)
Triacylglycerol (mmol/l)
HDL-cholesterol (mmol/l)
LDL-cholesterol (mmol/l)
V O2max (ml kg−1 min−1)
115.8 (76.0–149.0)
240.4±20.0
56±13.7
1.5±0.2
3.4±0.8
4.7±0.4
1.0±0.1
1.2±0.1
3.0±0.3
25.8±1.4
127.2 (79.1–158.0)
297.5±34.7
58.6±11.2
1.9±0.4
4.0±1.3
5.0±0.4
1.3±0.2
1.3±0.1
3.2±0.4
30.5±1.5a
169.2 (136.1–285.1)
142.1±46.2
26.7±2.9
2.7±0.2
10.7±1.5
4.6±0.4
1.4±0.2
0.9±0.1
3.1±0.4
25.9±3.3
120.6 (78.7–286.3)a
178.4±41.5a
30.5±3.5
2.7±0.3
9.5±1.5
4.5±0.3
1.0 ±0.2a
1.0±0.1
3.0±0.3
33.3±3.5a
0.73
0.01
0.31
0.21
0.67
0.74
0.43
0.17
0.80
<0.01
0.09
0.46
0.85
0.21
0.15
0.29
<0.01
0.87
0.6
0.19
Data are means±SE except for insulin (median [interquartile range]; p values from log-transformed data)
a
Significant within-group change with exercise (p<0.05)
b
Significant between-group change with exercise when corrected for age (p00.01)
FAI, free androgen index
Diabetologia (2012) 55:1424–1434
Diabetologia (2012) 55:1424–1434
1431
induced increase in insulin sensitivity in either group. This
suggests that previously observed relationships between IR
states and mitochondrial dysfunction are not applicable to
the intrinsic IR of PCOS.
Previous data have linked high levels of IMCL, measured
directly and with imaging techniques, with IR (reviewed by
Lara-Castro and Garvey [6]). Using CT thigh muscle attenuation, an estimate of muscle lipid content that correlates with
IMCL [9], we found a trend to lower baseline muscle lipid
content in the more IR PCOS versus non-PCOS women. In
support of this finding, an earlier study found that the relationship between IR and IMCL was present only in lean men [33].
Obese men in the same study had surprisingly low levels of
IMCL. In the present study, there was an unexpected differential response of muscle lipid content to exercise training, with
PCOS women increasing and non-PCOS women decreasing
lipid, while IR decreased in both groups. Another study in
overweight and obese adults found that exercise-induced
improvements in insulin sensitivity were accompanied by
increases in IMCL [34, 35]. Meex et al. [35] demonstrated a
trend to increased IMCL with exercise in male patients with
type 2 diabetes, whose IR improved, but, in contrast with the
present study, mitochondrial function also improved. It was
postulated that the increased IMCL may represent recruitment
of non-oxidative type 2 fibres or improved lipid partitioning
through the enzyme diacylglycerol acyltransferase (DGAT1)
[35]. DGAT1 is critical for triacylglycerol synthesis, and overexpression in rodent skeletal muscle leads to muscle
triacylglycerol accumulation with paradoxically decreased IR
[36]. This partitioning of lipids may reduce build-up of
triacylglycerol-derived metabolites, such as diacylglycerol
and ceramides, that interfere with insulin signalling [37].
Our data suggest a difference in the capacity of sedentary
PCOS women to store lipid in skeletal muscle compared
with non-PCOS women. These findings parallel differences
between men and non-PCOS women. Men have lower
IMCL than women despite being more IR [38]. With endurance exercise, men exhibit lower lipid oxidation than women [39], and an acute exercise bout leads to muscle
triacylglycerol breakdown in women but not in men [40].
Furthermore, PCOS women have more visceral fat than
non-PCOS women, which decreases with exercise training
in PCOS women only [26], again mimicking the response of
visceral fat to exercise that occurs in men when compared
with non-PCOS women [41]. The influence of hyperandrogenism on the metabolic phenotype of PCOS is not clear.
These findings suggest a possible ‘androgenic’ pattern of
lipid storage and its response to exercise training in PCOS.
Androgens did not correlate with any of these lipid measures.
This warrants further direct assessment of IMCL in PCOS
including its cellular distribution, the presence of ceramides
and diacylglycerol, and the activity of lipolytic and liposynthetic pathways such as DGAT1.
Interaction between mitochondrial function and IMCL
accumulation may be the important factor for determining
insulin sensitivity [42]. The literature supports an association
Table 3 Effect of exercise on protein abundance and gene expression and enzyme function
Characteristic
Protein abundance
PGC1α
Complex I
Complex II
Complex III
Complex IV
Complex V
Enzyme activity
β-HAD
CS
Gene expression
PGC1A
TFAM
NRF1
COX4
PCOS (n08)
Non-PCOS (n07)
p value for change
over study, PCOS
vs non-PCOS
Pre
Post
Pre
Post
2.0±0.6
0.9±0.2
0.8±0.2
1.0±0.4
1.1±0.3
1.5±0.5
1.7±0.4
0.8±0.2
0.7±0.2
1.0±0.3
1.0±0.2
1.4±0.4
1.0±0.3
1.0±0.3
1.0±0.2
1.0±0.3
1.0±0.2
1.0±0.3
1.5±0.4
1.3±0.3
1.5±0.4
1.4±0.4a
1.3±0.2
1.5±0.4a
0.83
0.48
0.36
0.18
0.24
0.19
0.46
0.26
0.10
0.15
0.13
0.08
0.9±0.1
0.9±0.1
1.0±0.1
0.9±0.1
1.0±0.0
1.0±0.1
1.1±0.1
1.0±0.1
0.16
0.84
0.97
1.00
0.8±0.1
0.8±0.1
0.8±0.1
0.8±0.1
0.8±0.1
0.9±0.1
0.7±0.1
1.0±0.1a
1.0±0.1
1.0±0.2
1.0±0.1
1.0±0.1
0.8±0.1
0.8±0.0
0.9±0.1
1.0±0.1
0.24
0.57
0.38
0.20
0.14
0.12
0.94
0.20
Data are means±SE
Arbitrary units expressed relative to non-PCOS women at baseline (1.0)
a
p value for
effect of exercise
training
Significant within-group change with exercise (p<0.05)
1432
between skeletal muscle mitochondrial dysfunction, high adiposity and IR in people with obesity and type 2 diabetes and
IR in first-degree relatives of those with type 2 diabetes, but
controversy remains [19]. The present study found a modest
correlation between IR and expression of PGC1A, but no
difference in any mitochondrial markers between PCOS women and non-PCOS women. Some studies have reported a
similar dissociation between IR and mitochondrial function
[19, 43], which was highlighted by Nair et al [44] when
comparing mitochondrial function of Asian–Indians with
northern Europeans. In contrast with the present study, most
studies of mitochondrial function and IR do not adequately
control for physical activity, family history of type 2 diabetes,
and body composition. However, as with our data, when
patients with diabetes are well matched with normoglycaemic
controls for body composition and physical activity, the two
groups have similar mitochondrial function [45].
In PCOS, one previous study on the role of mitochondria
[18] used a microarray approach and found reduced
OXPHOS gene expression in skeletal muscle of PCOS
women compared with weight-matched controls. The
authors linked this to reduced PGC1A expression in PCOS,
previously shown in type 2 diabetes [16, 17]. In contrast,
our study found no difference in either OXPHOS gene
expression and protein abundance or PGC1A gene expression. The reasons for disparities between this and other
studies of IR and mitochondrial function are not clear [19].
Skov et al [18] selected PCOS women on the basis of IR
severity, perhaps amplifying differences found, and family
history of type 2 diabetes, fitness and body composition
were not documented. In the present study, in which the
PCOS group was not selected on the basis of IR and
potential confounders were addressed, mitochondrial dysfunction does not appear to contribute to intrinsic PCOSrelated IR.
PGC1α, through its effects on mitochondrial biogenesis
and energy metabolism, has been implicated in the pathogenesis of IR [15]. A correlation between GIR and PGC1A
was found for the whole group, supporting a relationship
between PGC1A and IR but not specific to women with
PCOS. However, animal studies using gene knockout and
transgenic overexpression strategies have been conflicting
but, overall, not supportive of the hypothesis that skeletal
muscle PGC1α is causally related to IR (reviewed by Patti
and Corvera [46]). Apart from the relationship with PGC1A,
the present study found no relationship between GIR and
downstream factors, including PGC1α protein production,
nuclear respiratory factor-1 (NRF1), mitochondrial transcription factor A (TFAM) or mitochondrial genes and proteins. Post-transcriptional regulation of PGC1α, such as
acetylation [47], may in part account for the dissociation
between gene expression and protein abundance and the
expected downstream effects.
Diabetologia (2012) 55:1424–1434
A number of interventions that improve IR, including
physical activity, weight loss and insulin sensitisers, also
improve mitochondrial function (reviewed by Turner and
Heilbronn [19]). However, other studies have demonstrated
improved IR without improved mitochondrial function [19,
24, 48, 49]. Exercise training has long been shown to
improve mitochondrial function [21]. In the present study,
although exercise improved fitness and IR in both groups,
mitochondrial variables did not change. In support of our
findings, Heilbronn et al [23] demonstrated improvement in
IR in obese men with exercise training without change in
mitochondrial enzyme activity or mitochondrial biogenesis.
Absence of responses to exercise may reflect the type and
length of exercise training, site of muscle sampled, or resistance of muscle to increases in mitochondrial biogenesis and
function. Taken together these data suggest that obese women
with and without PCOS respond to exercise differently and
warrant further exploration with inclusion of lean control
groups.
Limitations of this study include small sample size, albeit
larger than similar studies investigating differences in mitochondrial function between groups [11]. Our groups were
not age-matched, but correcting for age did not affect, and
age did not correlate with, any mitochondrial markers (not
shown). This study did assess a number of different markers
of mitochondrial biogenesis, but did not assess mitochondrial function, size or number. CT was used to measure
muscle lipid content, but cannot distinguish intra- from
extra-myocellular lipid. However, CT muscle attenuation
correlated more closely with IMCL than with extramyocellular lipid [9, 10]. Further study of muscle lipid content in
PCOS by more direct techniques is warranted. Despite these
limitations, CT does sample large areas of muscle not possible
with biopsy techniques, and would be more amenable to
performing larger scale clinical studies in both lean and obese
PCOS and non-PCOS women.
Conclusions In summary, there were differential effects of
exercise training on circulating and muscle lipids between
groups. PCOS women had significantly higher serum triacylglycerol at baseline and a trend to higher CT muscle
attenuation, or less muscle lipid. Exercise led to a decrease
in serum triacylglycerol and CT muscle attenuation relative
to non-PCOS women. This suggests that PCOS women may
store less lipid in skeletal muscle than non-PCOS women
and that exercise may increase muscle lipid storage in PCOS
women relative to non-PCOS women. No differences were
observed in markers of mitochondrial function between
overweight PCOS and non-PCOS women of comparable
weight, despite a clear difference in IR. No major changes
in mitochondrial markers were seen with 12 weeks of exercise
training in either group. Therefore muscle lipid storage, but
not skeletal muscle mitochondrial function, may contribute to
Diabetologia (2012) 55:1424–1434
IR in women affected by PCOS and its amelioration with
exercise. Further investigations on other potential mediators
of IR in PCOS and the effects of exercise are warranted.
Acknowledgements Pathology was completed at Southern Health
Laboratories. Tissue analysis of mitochondrial genes, proteins and
enzyme activities was completed at the Baker Research Institute,
Monash University, Melbourne, VIC, Australia, under the supervision
of M. Febbraio and C. Bruce. Reagents were provided by the Baker
Research Laboratory. E. Paul assisted with statistical analysis. Muscle
biopsies were performed by B. Canny. An abstract was presented at the
7th Annual meeting of the Androgen Excess-PCOS Society, 2009.
Funding This investigator-initiated trial was supported by grants
from the National Health & Medical Research Council (NH&MRC)
Grant number 606553 (to H.J. Teede, B.J. Strauss, N.K. Stepto and
S.K. Hutchison) as well as Monash University (N.K. Stepto and H.J.
Teede) and The Jean Hailes Foundation. H.J. Teede is an NH&MRC
Research Fellow. S.K. Hutchison and C.L. Harrison are NH&MRC
PhD Scholars.
Duality of interest The authors declare that there is no duality of
interest associated with this manuscript.
Contribution statement SKH analysed and interpreted the data, and
drafted the manuscript. HJT and NKS were responsible for conception
and design and critically revised the manuscript for important intellectual
content. DR, CLH and BJS analysed the data, and critically revised the
manuscript for important intellectual content. All authors approved the
final version for publication.
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