Increased Skeletal Muscle 11 beta HSD1 mRNA Is Associated with Lower Muscle Strength in Ageing

Abstract

Sarcopenia, the loss of muscle mass and function with age, is associated with increased morbidity and mortality. Current understanding of the underlying mechanisms is limited. Glucocorticoids (GC) in excess cause muscle weakness and atrophy. We hypothesized that GC may contribute to sarcopenia through elevated circulating levels or increased glucocorticoid receptor (GR) signaling by increased expression of either GR or the GC-amplifying enzyme 11beta-hydroxysteroid dehydrogenase type 1 (11βHSD1) in muscle.
There were 82 participants; group 1 comprised 33 older men (mean age 70.2years, SD 4.4) and 19 younger men (22.2years, 1.7) and group 2 comprised 16 older men (79.1years, 3.4) and 14 older women (80.1years, 3.7). We measured muscle strength, mid-thigh cross-sectional area, fasting morning plasma cortisol, quadriceps muscle GR and 11βHSD1 mRNA, and urinary glucocorticoid metabolites. Data were analysed using multiple linear regression adjusting for age, gender and body size.
Muscle strength and size were not associated with plasma cortisol, total urinary glucocorticoids or the ratio of urinary 5β-tetrahydrocortisol +5α-tetrahydrocortisol to tetrahydrocortisone (an index of systemic 11βHSD activity). Muscle strength was associated with 11βHSD1 mRNA levels (β -0.35, p = 0.04), but GR mRNA levels were not significantly associated with muscle strength or size.
Although circulating levels of GC are not associated with muscle strength or size in either gender, increased cortisol generation within muscle by 11βHSD1 may contribute to loss of muscle strength with age, a key component of sarcopenia. Inhibition of 11βHSD1 may have therapeutic potential in sarcopenia.

Full text

Increased Skeletal Muscle 11bHSD1 mRNA Is Associated
with Lower Muscle Strength in Ageing
Alixe H. M. Kilgour
1
*, Iain J. Gallagher
2
, Alasdair M. J. MacLullich
1,2
, Ruth Andrew
3
, Calum D. Gray
4
,
Philippa Hyde
2
, Henning Wackerhage
5
, Holger Husi
2
, James A. Ross
2
, John M. Starr
1
, Karen E. Chapman
3
,
Kenneth C. H. Fearon
2
, Brian R. Walker
3
, Carolyn A. Greig
2
1Centre for Cognitive Ageing and Cognitive Epidemiology, Geriatric Medicine Unit, University of Edinburgh, Edinburgh, United Kingdom, 2Department of Clinical and
Surgical Sciences, Division of Health Sciences, School of Clinical Sciences, University of Edinburgh, Edinburgh, United Kingdom, 3Endocrinology Unit, Centre for
Cardiovascular Science, Queen’s Medical Research Institute, University of Edinburgh, Edinburgh, United Kingdom, 4Clinical Research Imaging Centre, Queen’s Medical
Research Institute, University of Edinburgh, Edinburgh, United Kingdom, 5School of Medical Sciences, University of Aberdeen, Aberdeen, United Kingdom
Abstract
Background:
Sarcopenia, the loss of muscle mass and function with age, is associated with increased morbidity and
mortality. Current understanding of the underlying mechanisms is limited. Glucocorticoids (GC) in excess cause muscle
weakness and atrophy. We hypothesized that GC may contribute to sarcopenia through elevated circulating levels or
increased glucocorticoid receptor (GR) signaling by increased expression of either GR or the GC-amplifying enzyme 11beta-
hydroxysteroid dehydrogenase type 1 (11bHSD1) in muscle.
Methods:
There were 82 participants; group 1 comprised 33 older men (mean age 70.2years, SD 4.4) and 19 younger men
(22.2years, 1.7) and group 2 comprised 16 older men (79.1years, 3.4) and 14 older women (80.1years, 3.7). We measured
muscle strength, mid-thigh cross-sectional area, fasting morning plasma cortisol, quadriceps muscle GR and 11bHSD1
mRNA, and urinary glucocorticoid metabolites. Data were analysed using multiple linear regression adjusting for age,
gender and body size.
Results:
Muscle strength and size were not associated with plasma cortisol, total urinary glucocorticoids or the ratio of
urinary 5b-tetrahydrocortisol +5a-tetrahydrocortisol to tetrahydrocortisone (an index of systemic 11bHSD activity). Muscle
strength was associated with 11bHSD1 mRNA levels (b-0.35, p = 0.04), but GR mRNA levels were not significantly associated
with muscle strength or size.
Conclusion:
Although circulating levels of GC are not associated with muscle strength or size in either gender, increased
cortisol generation within muscle by 11bHSD1 may contribute to loss of muscle strength with age, a key component of
sarcopenia. Inhibition of 11bHSD1 may have therapeutic potential in sarcopenia.
Citation: Kilgour AHM, Gallagher IJ, MacLullich AMJ, Andrew R, Gray CD, et al. (2013) Increased Skeletal Muscle 11bHSD1 mRNA Is Associated with Lower Muscle
Strength in Ageing. PLoS ONE 8(12): e84057. doi:10.1371/journal.pone.0084057
Editor: Cedric Moro, INSERM/UMR 1048, France
Received September 10, 2013; Accepted November 18, 2013; Published December 31, 2013
Copyright: ß2013 Kilgour et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits
unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: The authors thank the British Heart Foundation and Chief Scientist Office of the Scottish Government for financial support. AHJK, AMJM and JMS are
members of The University of Edinburgh Centre for Cognitive Ageing and Cognitive Epidemiology, part of the cross council Lifelong Health and Wellbeing
Initiative. Funding from the BBSRC, EPSRC, ESRC and MRC is gratefully acknowledged. The funders had no role in study design, data collection and analysis,
decision to publish, or preparation of the manuscript.
Competing Interests: B.R.W. is an inventor on relevant patents owned by the University of Edinburgh and has consulted for several companies developing
selective 11bHSD1 inhibitors. No other potential conflicts of interest relevant to this article were reported. This does not alter the authors’ adherence to all the
PLOS ONE policies on sharing data and material.
* E-mail: a.kilgour@ed.ac.uk
Introduction
Sarcopenia is the loss of muscle mass and function which
accompanies even healthy ageing [1–3]. Both muscle mass and
function (i.e., power and strength) begin to decline from the third
decade with mass reducing by 1–2% per year and strength
reducing by around 2% per year [4–8]. Sarcopenia is associated
with an increased risk of falls and fractures, disability, loss of
independence and mortality [9–11]. Despite this public health
problem, current understanding of the mechanisms underlying
sarcopenia is limited, hampering progress in the development of
novel treatments for maintenance of muscle mass and physical
independence in old age. Theories underlying the development of
sarcopenia include: inflammation, cellular senescence, hormones
and growth factors and lifestyle factors (eg nutrition) [12,13].
One possible mechanism within the field of hormones and
growth factors is glucocorticoid dysregulation. It is well known that
glucocorticoids at pharmacological levels or in spontaneous
Cushing’s syndrome cause myopathy, with a combination of
muscle atrophy and dysfunction. Glucocorticoids are believed to
effect these changes on muscle through a combination of increased
protein breakdown (particularly through the ubiquitin-proteasome
system) [14], decreased protein synthesis (by inhibiting transport of
amino acids into muscle and inhibiting the action of insulin and
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IGF-1) [15] and decreasing production of IGF-1 and myostatin
[14]. In the context of sarcopenia, this mechanism could occur via
elevated circulating glucocorticoids due to age-related hypotha-
lamic-pituitary-adrenal (HPA) axis dysregulation. Alternatively, it
could occur selectively within the muscle, by increased activity of
the glucocorticoid receptor (GR) or the enzyme 11b-hydroxyste-
roid dehydrogenase type 1 (11bHSD1). 11bHSD1 converts
inactive cortisone to active cortisol and is known to be present
and biologically active in human muscle as well as many other
tissues [16–18]. Indeed a recent study by Tiganescu et al found
that elevated 11bHSD1 activity was inceased in skin biopsies from
older adults compared to younger adults and that this increased
activity was associated with markers of skin ageing (eg dermal
atrophy and deranged collagen structural organization) [19].
Establishing links between GC and sarcopenia could lead to novel
therapies, as several 11bHSD1 inhibitors are currently in clinical
development for type 2 diabetes and other degenerative diseases,
including cognitive dysfunction [20].
There is some evidence of an association between increased
plasma and salivary cortisol and lower muscle mass and strength
but these data are inconsistent [21–24]. Glucocorticoid metabo-
lites in a 24 hour urine sample may be more informative than
plasma cortisol levels since they reflect glucocorticoid status over
the diurnal cycle. Additionally ratios of the metabolites can be
used as an index of peripheral 11bHSD activity [25]. However, no
studies to date have examined the relationship between urinary
glucocorticoid metabolites and sarcopenia. Similarly, there are no
published data examining the relationship between GR and
11bHSD1 expression and muscle loss and function in older adults.
Importantly, expression of 11bHSD1 and GR mRNA has been
shown to reflect glucocorticoid activity, for example there is a
correlation between 11bHSD1 mRNA expression and enzyme
function [26].
The aim of this study was to investigate the relationship between
plasma and urinary glucocorticoid metabolites and levels of
mRNA encoding GR and 11bHSD1 in skeletal muscle, with
muscle size and strength. We hypothesized that increased
glucocorticoid signaling in skeletal muscle acting through GR
by, (a) elevated circulating cortisol, (b) increased expression of
11bHSD1 or (c) increased expression of GR, is associated with
reduced muscle size and strength.
Methods
Participants
Participants were healthy volunteers recruited at two sites in
Scotland: young and older men were recruited in Aberdeen
(Group 1) and older men and women were recruited in Edinburgh
(Group 2). This allowed us to test for possible age and gender
effects. Participants were defined as healthy after applying
previously published health selection criteria to the responses to
a questionnaire [27]. Existing samples were available from two
nearby cities in Scotland so these were used for analysis, rather
than beginning a new de novo cohort collection. No comparisons
were made between these two independent cohorts.
Ethics Statement
Written informed consent was obtained and all procedures
received local ethical committee approval. In Edinburgh this was
by the Lothian Local Research Ethics Committee 02 and in
Aberdeen this was by the North of Scotland Research Ethics
Committees. The study conformed to the standards set by the
Declaration of Helsinki.
Anthropometry
Body weight was measured with participants in light clothing
using a beam scale (Seca, UK). Height was measured using a wall
mounted stadiometer.
Muscle Function
Maximum voluntary isometric knee extensor strength was
measured using an established method [28]. Following instruction,
the participant made a maximum voluntary contraction (Newtons)
which was held for 5 seconds. Three separate measurements were
obtained and the highest value was used in subsequent analysis.
Muscle Size
Mid-thigh quadriceps cross-sectional area (CSA) was measured
using a 1.5T MR scanner (Phillips Gyroscan Intera). T1-weighted
axial images were taken with the isocentre of the magnetic field
located at the mid-femur point which was landmarked prior to the
scan according to International Standards of Anthropometric
Assessment (ISAK) guidelines 2001. Imaging parameters were:
slice thickness 10 mm; acquisition matrix 5126512; echo time
(TE) 15 ms; repetition time (TR) 425 ms; and flip angle 90u. The
CSA of the quadriceps was quantified using Analyze 8.0 (Mayo
Clinic, Rochester, USA) according to a previously published
technique [29]. Two of the subjects from Group 2 did not undergo
MRI due to claustrophobic symptoms.
Plasma Cortisol
Blood samples were obtained from participants in the morning
after overnight fast (mean time 0945h, range 0915–1030h). Plasma
cortisol was measured by competitive immunoassay with direct
chemiluminescent technology using the Bayer Advia Centaur
method (see http://labmed.ucsf.edu/labmanual/db/resource/
Centaur_Cortisol.pdf).
Quadriceps Muscle Biopsy
Quadriceps femoris samples were obtained from the region of
vastus lateralis via percutaneous needle biopsy using a Bergstrom
needle [30]. The biopsy was obtained in a sterile environment by
sharp dissection under local anaesthetic using 1% lidocaine. The
samples were then snap frozen in liquid nitrogen and stored at
280uC before analysis [31].
RNA Isolation
Total RNA was isolated from quadriceps muscle biopsies using
the Qiazol reagent (Qiagen, Crawley, UK) and miRNeasy RNA
isolation columns (Qiagen, Crawley, UK). Briefly biopsies were
homogenised in 1400 ul or 700 ul Qiazol depending on the size of
the tissue sample using a Polytron PT1200E (Kinematica AG).
Total RNA was isolated from the homogenised muscle using
miRNEasy columns with an on column DNAse treatment step
using the RNase-Free DNase Set (Qiagen, Crawley, UK). After
elution from the column into 30 ul nuclease free H
2
O, RNA was
quantified using the Nanodrop instrument (Labtech, UK) and
quality assessed using the Bioanalyzer (Agilent, UK). All samples
had 260/280 ratios above 1.8, and RIN scores above 7.5.
cDNA Preparation and qPCR
RNA samples were converted to cDNA using the Ovation RNA
Amplification kit (Nugen, Netherlands). RNA was diluted to
10 ng/ul and 50 ng total RNA was used in the amplification
reaction carried out according to the manufacturer’s instructions,
yielding between 3 ug and 11 ug cDNA. For qPCR, cDNA was
diluted to ,50 ng/ul. Quantitative RT-PCR reactions were run,
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in triplicate, on an Applied Biosystems Step One Plus system. The
reaction mix was POWER SYBR Green x2 Master mix 12.5 ul,
forward primer (10 uM) 1 ul, reverse primer (10 uM) 1 ul, H2O
9.5 ul and cDNA 1 ul. Reaction conditions were 95uC for 10
mins, 95uC for 15s, 60uC for 60s (40 cycles) followed by melting
curve generation from 60uCto95uC. Ct values were examined
and within triplicates any value greater than 0.3 Ct were removed
before means were calculated. Data were then analysed using the
delta Ct method with HPRT as a normaliser. After normalisation
data were inverted and scaled such that the largest value for each
gene was set to 100.
Primer sequences used were NR3C1 FP –
CTGTCGCTTCTCAATCAGACTC; RP – GCATTGCT-
TACTGAGCCTTTTG; 11bHSD1 FP –
AGGCTGCTGCCTGCTTAGGA; RP – AGCCCCA-
GAATGGGGAGGAGA; HPRT FP – TGACACTGGCAAAA-
CAATGCA; RP- GGTCCTTTTCACCAGCAAGCT. HPRT
was chosen as a normaliser as preliminary analysis of housekeep-
ing gene performance showed HPRT to be stable across samples
and expressed at a similar level to genes of interest compared to b-
actin, GAPDH, b2M and 18S.
Urinary Glucocorticoid Metabolism
24 hour urine samples were collected to quantify urinary
glucocorticoid metabolites using gas chromatography electron
impact mass spectrometry following solid phase extraction,
hydrolysis of conjugates and formation of their methoxime-
trimethylsilyl derivatives, as described previously [25].
Two composites of the data were used in subsequent analyses.
Firstly, total urinary steroids, comprising the sum of 5b-tetra-
hydrocortisol (5bTHF), 5a-tetrahydrocortisol (5aTHF), the main
urinary metabolites of cortisol, and tetrahydrocortisone (THE), the
main urinary metabolite of cortisone (total urinary GC = 5bTHF
+5aTHF+THE). Secondly, an indirect indicator of systemic
11bHSD activity, comprising the ratio of 5bTHF and 5aTHF
to THE (ratio of cortisol to cortisone metabolites = (5bTHF
+5aTHF)/THE).
Statistical Analysis
Statistical analysis was performed using SPSS version 18.0.
Bivariate correlations were performed using Spearman’s rho to
allow analysis of the non-parametric variables. Forced entry
multiple linear regression was performed and the data from the
Table 1. Group characteristics.
Group 1 younger
men (n = 19)
Group 1 older
men (n = 33) p-value
a
Group 2 older
men (n = 16)
Group 2 older
women (n = 14) p-value
b
Age (years) 22.2 (1.7) 70.2 (4.4) ,0.001 79.1 (3.4) 80.1 (3.7) n/s
Height (cm) 177.6 (6.7) 171.9 (5.4) 0.001 171.3 (6.1) 157.6 (5.9) ,0.001
BMI (kg/m
2
)24.0 (2.5) 25.2 (2.5) n/s 25.3 (3.9) 24.1 (3.1) n/s
Muscle Size (cm
2
)92.7 (11.5) 67.3 (7.4) ,0.001 63.5 (7.3) 43.8 (6.8) ,0.001
Muscle Strength (Newton) 774.9 (136.6) 525.2 (73.6) ,0.001 364.7 (79.7) 273.4 (73.4) 0.003
Total Urinary GC* (microg/
day)
9887 (7721–18372) 10224 (7841–17000) n/s 8192 (5534–12506) 4925 (3699–6806) n/s
11bHSD activity (urine
THFs:THE)
1.12 (0.37) 1.15 (0.45) n/s 1.28 (0.79) 0.81 (0.49) n/s
Plasma cortisol (nmol/litre) – – 349 (106) 321 (65) n/s
GR mRNA – – 59.4 (24.5) 58.3 (18.8) n/s
11bHSD1 mRNA – – 25.3 (19.7) 32.2 (31.8) n/s
Data are mean (SD) except *non-parametric data therefore median and IQ range shown.
a. Independent t test between younger and older men in Group 1.
b. Independent t test between men and women in Group 2.
n/s = not significant.
doi:10.1371/journal.pone.0084057.t001
Table 2. Bivariate correlations including muscle size and strength.
Group 1 muscle size Group 1 muscle strength Group 2 muscle size Group 2 muscle strength
Height .34* .22 .68** .42*
BMI –.04 –.07 .32 .38*
Total urinary GC –.04 .01 .61** .45*
11bHSD activity –.09 –.05 .35 .16
Plasma cortisol – – –.20 –.31
GR mRNA ––.11.04
11bHSD1 mRNA – – –.15 –.29
Data are Spearman’s Rho Correlation Coefficients.
**p,0.01 (2-tailed).
*p,0.05 (2-tailed).
doi:10.1371/journal.pone.0084057.t002
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two groups were analysed separately, when possible, to test
reproducibility. Due to the large difference in age between the
older and younger groups, age was analysed as a binary variable in
the multivariate regression. Group 1 (n =52) had 80% power at
the p =0.05 level to detect a correlation of r = 0.38 and Group 2
(n = 30) had 80% power at the p = 0.05 level to detect a correlation
of r = 0.49. In view of the power calculations and the exploratory
nature of the study, adjusting for multiple hypotheses testing was
not deemed to be appropriate.
Results
In total, 82 participants were recruited. Table 1 shows numbers
of participants and their age, height, BMI, and the main outcome
variables for each group. Independent t tests found significant sex
and age related differences for height, muscle size and muscle
strength but not for BMI or any measure of glucocorticoid status
(Table 1). Table 2 shows bivariate correlations, which confirmed
that measures of body size (height and BMI) were significantly
associated with muscle size and strength. Therefore in constructing
multivariate models we adjusted for body size as well as age and
gender, which had been selected a priori due to their accepted
relationships with muscle size and strength. BMI correlated with
total urinary GC (rho = 0.60, p = 0.0005) and plasma cortisol
(rho = 20.52, p = 0.006), whereas height did not significantly
correlate with total urinary GC or plasma cortisol (p.0.05 for
both). Therefore in multivariate analyses with urinary GC and
plasma cortisol as predictor variables we adjusted for potential
confounding by BMI, gender and age (see Tables 3 & 4). Neither
BMI nor height correlated with the muscle GR or 11bHSD1
mRNA expression levels. Therefore because height correlated
more significantly with muscle size and strength than BMI
(Table 2), we adjusted for height and gender for the multivariate
analyses with muscle GR and 11bHSD1 mRNA as predictor
variables (Table 4).
Plasma cortisol was measured in Group 2 only. There were no
significant association between fasting morning plasma cortisol
and muscle size and a non-significant negative trend with muscle
strength (b20.35, p = 0.08) (Table 4). In both groups neither total
urinary glucocorticoids nor the ratio of cortisol:cortisone metab-
olites were associated with muscle size or strength (Tables 3 & 4).
We used muscle biopsies from a subset of Group 2 to examine
the relationships between GR and 11bHSD1 mRNA levels and
muscle size and strength. Increased 11bHSD1 mRNA was
significantly associated with lower muscle strength after adjust-
ment for sex and height (b20.35, p = 0.039, n = 22:12 men mean
age 79.8 (sd 3.6) and 10 women, mean age 80.5 (sd 4.1)). There
were no significant relationships between GR mRNA and muscle
size or strength, or between 11bHSD1 mRNA and muscle size
(Table 4).
Discussion
This study investigated the relationship between circulating and
tissue indices of glucocorticoid status and muscle size and strength
in two groups. Group 1 allowed comparison of older with younger
men. There were no age differences in urinary cortisol metabolites,
although muscle biopsies were not obtained in this group so we did
not test the effect of ageing per se on muscle mRNA levels. Group 2
allowed comparison of older men with older women. There were
no differences in plasma cortisol, urinary glucocorticoid metabo-
lites or muscle GR or 11bHSD1 mRNA levels between the sexes
in this relatively small sample. Within each group we explored
associations between glucocorticoid variables and muscle size and
strength after adjustment for potential confounding effects of age,
gender and body size as appropriate. In these analyses, indices of
HPA axis function, including morning plasma cortisol and 24 h
urinary cortisol metabolite excretion, were not associated with
muscle strength or size. Additionally urinary cortisol:cortisone
metabolite ratios, which principally reflect 11bHSD activity in the
major organs of liver and kidney, were not associated with muscle
strength or size. However, in muscle itself, higher levels of mRNA
encoding the cortisol-amplifying enzyme 11bHSD1 were associ-
ated with reduced muscle strength. This finding is consistent with
the hypothesis that enhanced glucocorticoid signalling within
muscle contributes to sarcopenia.
To our knowledge there have been no previous investigations of
muscle glucocorticoid signaling in human sarcopenia. We
Table 3. Regression coefficients for the glucocorticoid measures in models predicting muscle size/strength (Group 1).
Glucorticoid Measure Muscle Size
Beta (sig, n)
Muscle Strength
Beta (sig, n)
Total Urinary GC
a
20.10 (p.0.05, 52) ,20.01 (p.0.05, 52)
THFs:THE
a
,0.01 (p.0.05, 52) 0.04 (p.0.05, 52)
a
adjusting for age and BMI.
doi:10.1371/journal.pone.0084057.t003
Table 4. Regression coefficients for the glucocorticoid measures in models predicting muscle size/strength (Group 2).
Glucorticoid Measure Muscle Size
Beta (sig, n)
Muscle Strength
Beta (sig, n)
Plasma Cortisol
a
20.12 (p.0.05, 25) 20.35 (p.0.05, 27)
Total Urinary GC
a
0.23 (p.0.05, 28) 0.18 (p.0.05, 30)
THFs:THE
a
0.08 (p.0.05, 28) 0.10 (p.0.05, 30)
GR mRNA
b
0.03 (p.0.05, 20) 0.04 (p.0.05, 22)
11bHSD1 mRNA
b
20.17 (p.0.05, 20) 20.35 (p = 0.04, 22)
a
adjusting for gender and BMI.
b
adjusting for gender and height.
doi:10.1371/journal.pone.0084057.t004
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hypothesized that because 11bHSD1 and GR regulate the
exposure of target tissues to glucocorticoids, increased expression
of 11bHSD1 and GR could therefore contribute to sarcopenia in
the absence of an increase in circulating GCs. We found that
increased 11bHSD1 mRNA expression in muscle is associated
with lower muscle strength. This is consistent with this hypothesis.
We did not find a relationship between 11bHSD1 mRNA
expression and muscle size, but in normal ageing, muscle strength
is reported to deteriorate more rapidly than muscle size; suggesting
a decline in force generating capacity with age [5,32]. A number of
contributory mechanisms have been proposed to explain this (eg
increased muscle fibre stiffness); our data suggest a possible role for
increased GC action at the muscle level. GC may affect strength
more than muscle mass by exacerbating glycation of the myosin
molecule, which appears to slow the intrinsic shortening velocity of
the muscle fibre, decrease force per cross-sectional area and
increase intramuscular collagen cross-linking which can cause
muscle stiffness [33,34]. In addition, GC may cause mitochondrial
dysfunction and reduced oxidative capacity, which would similarly
result in a decrease in force generating capacity [35]. 11bHSD1 is
known to act locally within muscle, resulting in measurable
production of cortisol in samples from veins draining human
muscle, and therefore increased 11bHSD1 mRNA expression is
likely to increase myocellular cortisol levels thereby mediating
these effects [18]. More research with larger samples and with a
wider range of severity of sarcopenia is required to investigate the
relationship between 11bHSD1 expression and activity and
muscle ageing.
We found no relationship between GR mRNA expression and
muscle mass or strength. It is possible that polymorphisms of GR
modulate the effect of GC on muscle, and that level of expression
is less important than genotype. For example male carriers of the
ER22/23EK polymorphism in GR, which is associated with
relative GC resistance, have greater muscle mass and strength
than non-carriers [36].
There are no published studies investigating the association
between urinary GC and muscle size or strength. However, there
are studies reporting associations between salivary and plasma
GCs and muscle size and function. In a previous study of men and
women .75 years higher salivary, but not serum, cortisol was
associated with lower appendicular skeletal mass (ASM) measured
using DEXA [21]. Similarly, in a large longitudinal ageing study
higher salivary but not serum cortisol predicted loss of grip
strength over 6 years, but there was no association of cortisol with
baseline grip strength or ASM [22]. A smaller study including both
young and older men found that increased serum cortisol
correlated with lower knee extensor strength in both age groups
and with quadriceps cross-sectional area only in the older group
[23]. The Caerphilly Prospective Study, which included measure-
ments of cortisol status and physical performance over 20 years,
found that higher mid-life plasma cortisol predicted faster walking
speeds in older age, although salivary cortisol did not correlate
with walking speed or balance in older age [24]. Collectively, these
studies provide contradictory evidence relating salivary or plasma
cortisol to muscle strength and mass. Taken with our data, there
does not appear to be a consistent association between activation
of the HPA axis and age-associated sarcopenia. These negative
findings are important in excluding this plausible hypothesis.
Some limitations of this study should be acknowledged. We
examined the effect of GC on ageing muscle using a younger and
older group of volunteers separated in age by nearly 50 years and
by many lifestyle factors; a problem inherent to cross-sectional
studies. Longitudinal studies investigating rate of decline of muscle
mass and function and measures of GC would be more
informative but are difficult to conduct due to the slow decline
of muscle mass and strength during ageing. The sample sizes were
relatively modest, particularly with respect to muscle GC data
which were obtained from only a subset of Group 2 who
underwent muscle biopsy. It has also been shown that sarcopenia
affects the upper and lower limbs differently and our study
investigated only the lower limbs [4,37–39]. Also, our healthy
older volunteers constituted a sample which may be not fully
representative of the ageing population; this may influence the
generalisability of our results. Finally, we used mRNA expression
as a marker of activity rather than a direct measure of 11bHSD1
activity, however several studies have found correlations between
mRNA expression and enzyme activity in rodents and humans, so
we regard mRNA as an appropriate indicator of 11b-HSD1
activity [26].
Conclusion
Sarcopenia is one of the major causes of frailty and disability in
older people. It is associated with greatly increased risk of loss of
independence and institutionalization. In this novel investigation
of healthy old and young people we found a significant association
between increased muscle 11bHSD1 expression and lower
quadriceps strength. We found no significant associations between
plasma cortisol, urinary GC metabolites or GR expression and
muscle mass or strength. Longitudinal studies are now required to
investigate these relationships and to further explore the possibility
of 11bHSD1 inhibitors as a novel treatment for sarcopenia.
Acknowledgments
We are grateful to staff of the Wellcome Trust Clinical Research Facility,
Edinburgh for assistance in conducting the study.
Author Contributions
Conceived and designed the experiments: AMJM HW JR BW KCHF
CAG. Performed the experiments: IG PH HW CAG. Analyzed the data:
AHMK IG RA CG PH HW JS BW CAG. Contributed reagents/
materials/analysis tools: CG HH RA KC BW. Wrote the paper: AHMK
JS KCHF BW CAG.
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