ORIGINAL
ARTICLE
Gender-Specific Differences in Skeletal Muscle 11HSD1 Expression Across Healthy Aging Zaki K. Hassan-Smith, Stuart A. Morgan, Mark Sherlock, Beverly Hughes, Angela Taylor, Gareth Lavery, Jeremy W. Tomlinson, and Paul M. Stewart Centre for Endocrinology, Diabetes, and Metabolism (Z.K.H.-S., S.A.M., B.H., A.T., G.L.), School of Clinical and Experimental Medicine, Institute for Biomedical Research, University of Birmingham, Edgbaston B15 2TT, United Kingdom; Department of Endocrinology (M.S.), Adelaide and Meath Hospital, Tallaght, Dublin 24, Ireland; Trinity College (M.S.), Dublin 2, Ireland; Oxford Centre for Diabetes, Endocrinology, and Metabolism (J.W.T.), University of Oxford, Churchill Hospital, Headington, Oxford OX3 7LE, United Kingdom; and Faculty of Medicine and Health (P.M.S.), University of Leeds, Leeds LS2 9NL, United Kingdom
Context: Cushing’s syndrome is characterized by marked changes in body composition (sarcopenia, obesity, and osteoporosis) that have similarities with those seen in aging. 11-hydroxysteroid dehydrogenase type 1 (11-HSD1) converts glucocorticoids to their active form (cortisone to cortisol in humans), resulting in local tissue amplification of effect. Objective: To evaluate 11-HSD1 expression and activity with age, specifically in muscle. To determine putative causes for increased activity with age and its consequences upon phenotypic markers of adverse aging. Design: Cross-sectional observational study. Setting: National Institute for Health Research-Wellcome Trust Clinical Research Facility, Birmingham, United Kingdom. Patients or Other Participants: Healthy human volunteers age 20 to 81 years (n ⫽ 134; 77 women, 57 men). Interventions: Day attendance at research facility for baseline observations, body composition analysis by dual-energy x-ray absorptiometry, jump-plate mechanography, grip strength analysis, baseline biochemical profiling, urine collection, and vastus lateralis muscle biopsy. Main Outcome Measure(s): Skeletal muscle gene expression, urine steroid profile, bivariate correlations between expression/activity and phenotypic/biochemical variables. Results: Skeletal muscle 11-HSD1 expression was increased 2.72-fold in women over 60 years of age compared to those aged 20 – 40 years; no differences were observed in men. There was a significant positive correlation between skeletal muscle 11-HSD1 expression and age in women across the group (rho ⫽ 0.40; P ⫽ .009). No differences in expression of 11-HSD type 2, glucocorticoid receptor, or hexose-6-phosphate dehydrogenase between age groups were observed in either sex. Urinary steroid markers of 11-HSD1, 11-HSD type 2, or 5␣-reductase were similar between age groups. Skeletal muscle 11-HSD1 expression was associated with reduced grip strength in both sexes and correlated positively with percentage of body fat, homeostasis model of assessment for insulin resistance, total cholesterol, LH, and FSH and negatively with bone mineral content and IGF-1 in women. Conclusions: Skeletal muscle 11-HSD1 is up-regulated with age in women and is associated with reduced grip strength, insulin resistance, and an adverse body composition profile. Selective inhibition of 11-HSD1 may offer a novel strategy to prevent and/or reverse age-related sarcopenia.
doi: 10.1210/jc.2015-1516
J Clin Endocrinol Metab
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11-HSD1 Across Healthy Human Aging
ushing’s syndrome is characterized by changes in body composition (sarcopenia, central obesity, osteoporosis), development of metabolic dysfunction (insulin resistance), and cardiovascular disease (1), which have similarities to the aged phenotype. Circulating cortisol levels are maintained under negative feedback regulation via the hypothalamic-pituitary-adrenal axis. Studies examining age-associated changes in the hypothalamic-pituitary-adrenal axis have had mixed results (2, 3), although some demonstrate blunting of cortisol diurnal secretion along with increases in mean levels. Local glucocorticoid (GC) exposure is also regulated at the prereceptor level by the 11-hydroxysteroid dehydrogenase type 1 (11-HSD1) enzymes, with the type 1 isoform acting primarily as an oxoreductase converting inactive GCs to their active form (cortisone to cortisol in humans) (4). Prereceptor GC metabolism by 11-HSD1 has been implicated in the pathogenesis of the metabolic syndrome and a range of conditions including osteoporosis and glaucoma (4). There is growing evidence that 11-HSD1 expression/activity is elevated in key tissues including bone (5), adipose tissue (6), and skin (7) with aging and may be implicated in the development of associated disease states. 11-HSD1 has been shown to be present and functionally active in skeletal muscle (8) and to play a role in the pathogenesis of insulin resistance (9). Furthermore, in vitro and in vivo mouse models have demonstrated that 11-HSD1 regulates GC-induced muscle atrophy via the ubiquitin-proteasomal system (10, 11). With the additional recognition that loss of lean muscle mass contributes to adverse “healthspan,” we have performed a detailed assessment of prereceptor GC metabolism through measurement of skeletal muscle 11-HSD1 expression, along with hepatic and global activity, in both sexes across the age spectrum. Associations with potential phenotypic markers of adverse aging and regulators of 11-HSD1 were assessed using strength testing, body composition, and biochemical analyses.
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J Clin Endocrinol Metab
Female subjects were in the follicular phase of the menstrual cycle or, if postmenopausal, were not on hormone replacement therapy. Exclusion criteria included pregnancy and medical history of diabetes mellitus, ischemic heart disease, cerebrovascular disease, severe respiratory disease, and epilepsy. Other exclusion criteria were therapy in the past 12 months, use of drugs known to affect the GH-IGF-1 axis, and use of oral anticoagulants. Subjects prescribed aspirin were asked to discontinue treatment 3 days before muscle biopsy. Procedures were carried out over a 1-day visit to the National Institute for Health Research (NIHR)Wellcome Trust Clinical Research Facility at the Queen Elizabeth Hospital Birmingham. Patients arrived fasted at 8:30 AM, having collected a complete urine sample over the preceding 24 hours.
Initial observations Height, weight, and the mean of three blood pressure measurements (recorded using an automatic sphygmomanometer with the subject seated) were recorded on arrival.
Urine steroid profiling by gas chromatography/ mass spectrometry On receipt of the 24-hour urine collection, total volume was noted, and a 30-mL aliquot was transferred to a universal container and stored at ⫺80°C pending analysis. Gas chromatography/mass spectrometry (GC/MS) analysis was performed using established and previously described methodology (12, 13). Briefly, this was comprised of extraction of steroids and their conjugates from urine via solid phase extraction, followed by deconjugation and derivatization to produce methyloxime-trimethylsilyl ethers, suitable for GC/MS analysis. GC/MS analysis was performed using an Agilent GC/MS 5973 instrument. Steroids were quantified based on selected ion monitoring transitions relative to calibration steroid standards.
Dual-energy x-ray absorptiometry scan Dual-energy x-ray absorptiometry (DEXA) scanning (Hologic Discovery with DXA software version Apex 3.0; Hologic Inc) was used to assess full body composition and bone mineral density (BMD) (coefficient of variation for fat and lean mass, ⬍3%).
Strength testing
Subjects and Methods Human study protocol A total of 134 healthy volunteers (77 women, 57 men) between 20 and 81 years of age and with a body mass index (BMI) between 20 and 30 kg/m2 were recruited from local populations. ISSN Print 0021-972X ISSN Online 1945-7197 Printed in USA Copyright © by the Endocrine Society Received February 26, 2015. Accepted May 8, 2015.
Hand-held dynamometry Three maximal contractions from both the right and left hand were obtained with 15 seconds of rest using of a grip strength dynamometer (Takei Instruments). Peak absolute strength in kilograms and relative handgrip strength (kilograms of force per kilogram of body weight) were recorded. Abbreviations: BMI, body mass index; DBP, diastolic blood pressure; DEXA, dual-energy x-ray absorptiometry; DHEAS, dehydroepiandrosterone sulfate; GC, glucocorticoid; GC/ MS, gas chromatography/mass spectrometry; GR, GC receptor; HDL-C, high-density lipoprotein-cholesterol; HOMA-IR, homeostasis model of assessment for insulin resistance; 11-HSD1, 11-hydroxysteroid dehydrogenase type 1; 11-HSD2, 11-HSD type 2; Pmax, maximum power; THE, tetrahydrocortisone; THF, tetrahydrocortisol; Vmax, maximum velocity.
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doi: 10.1210/jc.2015-1516
Jump-plate mechanography This method utilizes forces measured by ground force reaction platform (Leonardo system; Novotec), over the course of a range of movements under the supervision of a trained operator working to a standard operating procedure. Maximum velocity (Vmax), maximum power (Pmax) output, and height of jump were calculated.
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a housekeeping gene for singleplex analysis. Reactions were performed using the Biomark system on a dynamic array integrated fluidic circuit (Fluidigm) according to the manufacturer’s protocols.
Statistical analysis
Samples were analyzed for urea, electrolytes, creatinine, lipids, glucose (Roche modular system; Roche), cortisol, TSH, free T4 (Advia Centaur; Bayer Diagnostics), dehydroepiandrosterone sulfate (DHEAS), SHBG, and GH (Immulite; Siemens AG) at the University Hospital Birmingham National Health Service Foundation Trust laboratories. Insulin was determined using a colorimetric ELISA (Mercodia) (coefficient of variation, ⬍5%). Homeostasis model of assessment for insulin resistance (HOMA-IR) was calculated using the following formula: fasting glucose (millimoles per liter)ⴱfasting insulin (milliinternational units per liter)/22.5.
Analyses were performed using Prism for Mac version 5.0 (GraphPad Software Inc) unless otherwise stated. For PCR analyses, statistical tests were performed on ⌬CT values. Data were expressed in arbitrary units calculated by the formula 1000 ⫻ (2⫺⌬CT), or fold-change vs the 20- to 40-year age group (2⫺⌬⌬CT). Nonparametric tests were used with Kruskal-Wallis and Dunn’s post-test correction when comparing multiple groups. Bivariate correlations between variables were performed using Spearman’s test. Multivariable analyses were performed using multiple linear regression after log-transforming 11HSD1 expression so that assumptions of normality were not violated, using the Statistical Package for the Social Sciences (SPSS) version 21 (IBM). A P value ⬍ .05 was taken as the threshold for statistical significance.
Prednisolone generation test
Ethical approval
Prednisone has an identical affinity for 11-HSD1 as cortisone; the interconversion of oral prednisone to prednisolone has been used as a marker of predominantly hepatic 11-HSD1 activity (reflecting first-pass metabolism) (14). Baseline blood samples were taken at approximately 9 AM, before oral administration of 10 mg prednisone. Additional samples were collected at 20-minute intervals over a period of 4 hours. Samples for prednisone and prednisolone were analyzed in-house by liquid chromatography/mass spectrometry (25 men and 23 women analyzed). Steroids were extracted from 200 L of serum (after addition of an internal standard) via liquid/liquid extraction with 1 mL methyl tertiary butyl ether; the solvent was evaporated, and the sample was reconstituted in methanol/water before analysis by ultra-performance liquid chromatography-tandem mass spectrometry. Waters Xevo with Acquity ultra-performance liquid chromatography was utilized in these experiments with an HSS T3 1.8 M 1.2 ⫻ 50-mm column. Steroids were eluted using a methanol/water gradient system. All steroids were identified by a matching retention time and two identical mass transitions when compared to an authentic steroid standard. Mass transitions in positive ionization mode were: prednisone, 359 ⬎ 147 (quantifier) and 359 ⬎ 341 (qualifier); and prednisolone, 361 ⬎ 343 (quantifier) and 361 ⬎ 147 (qualifier). Steroids were quantified relative to a calibration series ranging from 0.25 to 500 ng/mL (15).
Ethical approval was obtained from the Coventry and Warwickshire Research Ethics Committee (REC reference no. 07/ H1211/168). The protocol was approved by the Scientific Committee of the NIHR-Wellcome Trust Clinical Research Facility at Queen Elizabeth Hospital Birmingham. The study commenced in October 2010 and was completed in March 2013. Volunteers were given written and verbal information on the study, and they gave written informed consent. After study completion, they received travel expenses, and clinically relevant results were passed on to general practitioners.
Fasting blood levels
Vastus lateralis muscle biopsy All biopsies were performed by a single investigator (Z.K.H.S.) in 45 women and 40 men using a percutaneous Bergstrom technique with suction to increase sample yield, as described by Tarnopolsky et al (16). The ages of subjects agreeing to muscle biopsies were similar to the overall cohort (women biopsied, 46.8 ⫾ 2.5 y vs whole cohort, 47.1 ⫾ 1.9 y, P ⫽ .93; men biopsied, 46.7 ⫾ 3.0 y vs whole cohort, 48.2 ⫾ 2.5 y, P ⫽ .69).
Quantitative (real-time) PCR Gene expression analysis was performed using Applied Biosystems reagents and expression assays. 18s rRNA was used as
Results Subject characteristics Characteristics of the 134 healthy volunteers (77 women, 57 men) in the study are outlined in Table 1. They were between 20 and 81 years old, with BMI between 20 and 30 kg/m2. BMI was greater in the 40 – 60 and ⬎ 60year age groups in men and women when compared to the 20- to 40-year-old subgroup (Table 1). Fat mass, as calculated by DEXA analysis, was greater in the 40 – 60 and ⬎ 60-year age groups, and bone mass was lower in the ⬎ 60-year age group in women. Pmax measured by jump-plate mechanography was lower in the 40 – 60 and ⬎ 60-year age groups in women and the ⬎ 60-year age groups in men. Vmax was lower in the 40 – 60 and ⬎ 60-year age groups in women and men. In women, but not men, fasting insulin, HOMA-IR, total cholesterol, FSH, and LH were all greater in the 40 – 60 and ⬎ 60-year age groups, and fasting glucose and high-density lipoproteincholesterol (HDL-C) were greater in the ⬎ 60-year age group. The 9 AM cortisol was lower with age in women and men. IGF-1 was lower in the ⬎ 60-year age groups in men
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Table 1.
11-HSD1 Across Healthy Human Aging
J Clin Endocrinol Metab
Subject Characteristics Women
Age Groups, y n Observational data SBP, mm Hg DBP, mm Hg BMI, kg/m2 Body composition Fat mass, kg Lean mass, kg Bone mass, (BMC) (kg) Strength testing Grip strength, kg Pmax, W/kg Vmax, m/s Serum biochemistry Fasting glucose, mmol/L Fasting insulin, pmol/ L HOMA-IR Total cholesterol, nmol/L HDL-C, mmol/L 9 AM cortisol, nmol/L SHBG, nmol/ L IGF-1, nmol/L FSH, IU/L LH, IU/L T, nmol/L DHEAS, nmol/L
20 – 40
Men
40 – 60
20 – 40
>60
40 – 60
>60
27
27
23
22
13
22
115 (110 –126) 75 (64 – 81) 22 (19 –24)
119 (111–128) 74 (67– 81) 26 (25–28)c
141 (133–158) 81 (67– 88) 24 (22–27)a
127 (120 –135) 77 (71– 86) 24 (22–25)
128 (125–147) 85 (78 –92) 28 (25–28)b
140 (122–155) 83 (68 –91) 25 (24 –29)a
16.5 (14.2–20.2) 24.5 (21.8 –27.0)c 21.3 (18.9 –23.4)a 14.8 (10.9 –19.2) 17.5 (13.5–18.6) 17.7 (13.8 –23.7) 41.6 (36.1– 43.4) 41.6 (38.2– 45.4) 39.9 (36.8 – 42.7) 57.8 (51.8 – 61.4) 62.7 (56.3–70.1) 57.6 (52.1– 63.3) 20.8 (19.2–23.1) 20.8 (19.6 –22.1)
18.5 (16.9 –21.3)a 25.1 (23.1–28.5) 27.1 (24.7–32.6) 25.8 (24.3–28.0)
28.4 (25.3–30.9) 28.7 (26.0 –30.0)
26.6 (23.1–30.1)
43.5 (38.8 –50.9) 49.6 (39.7– 61.5) 41.5 (36.6 – 47.6)
35.6 (32.5– 43.8) 31.2 (28.7–35.1)a 25.8 (23.6 –29.1)c 49.7 (45.4 –54.5) 39.6 (36.8 – 45.0) 34.5 (30.6 –37.1)c 2.1 (2.0 –2.3) 1.9 (1.7–1.9)b 1.7 (1.6 –1.9)c 2.6 (2.4 –2.8) 2.3 (2.1–2.6)a 2.0 (1.8 –2.2)c 4.5 (4.3– 4.7)
4.7 (4.3– 4.9)
4.9 (4.7–5.1)b
5.0 (4.7–5.1)
4.8 (4.6 –5.1)
5.1 (4.9 –5.6)
2.9 (2.0 – 4.1)
4.1 (3.4 –5.7)a
4.5 (3.3– 6.7)a
5.6 (3.6 –10.9)
5.1 (3.2–9.7)
6.0 (3.8 –9.1)
0.6 (0.4 – 0.8) 4.0 (3.7– 4.7)
0.8 (0.7–1.4)a 5.2 (4.8 –5.8)c
1.0 (0.7–1.5)c 5.6 (4.5– 6.4)c
1.2 (0.8 –1.6) 4.2 (4.0 – 4.9)
1.2 (0.7–2.4) 5.0 (4.2–5.7)
1.3 (0.9 –1.9) 5.0 (4.2–5.7)
1.5 (1.3–1.8)
1.7 (1.3–1.8)
1.9 (1.7–2.1)b
1.3 (1.2–1.5)
1.3 (1.1–1.5)
1.5 (1.3–1.6)
331 (213–596)
223 (193–278)a
212 (175–274)b
364 (281– 452)
272 (207–339)a 263 (214 –358)a
70.3 (50.2–93.0)
28.1 (21.2–33.4) 38.7 (28.0 – 43.2) 42.9 (31.9 – 62.6)c
11.8 (10.3–13.7)c 68.2 (53.4 – 81.6)c 27.0 (21.9 –37.3)c 0.45 (0.3– 0.7)b 1.4 (0.8 –2.4)c
24.2 (20.5–30.0) 3.3 (1.9 – 4.9) 3.3 (2.7– 4.9) 17.3 (12.7–20.2) 8.4 (7.1–10.0)
63.3 (45.4 –95.2) 57.9 (37.1–70.0) 24.1 (22.4 –27.3) 4.7 (2.2–5.8) 4.1 (1.4 –7.4) 0.8 (0.6 –1.0) 3.8 (2.7– 6.1)
20.7 (15.9 –23.7)c 16.1 (6.9 – 65.4)c 14.3 (6.6 – 41.3)c 0.7 (0.5– 0.9) 3.0 (2.0 –3.7)a
19.4 (16.1–24.7) 4.6 (2.9 – 8.4) 3.5 (3.0 –5.2) 13.1 (11.9 –18.4) 5.5 (4.5– 6.8)
16.7 (13.1–18.7)c 5.1 (3.8 –7.4)b 4.9 (3.5–7.2) 14.8 (10.8 –19.8) 2.8 (2.2–3.5)c
Abbreviation: SBP, systolic blood pressure. Data are expressed as median (interquartile range). Vmax represents maximal velocity during upward movement. a– c a P ⬍ .05; b P ⬍ .01; c P ⬍ .001, vs 20- to 40-year-old sex-matched cohort as calculated by Kruskal-Wallis analysis with Dunn’s multiple comparison tests (n ⫽ 77 women, 57 men).
and women but was also lower in the 40- to 60-year group in women. Skeletal muscle gene expression 11-HSD1 gene expression from vastus lateralis was increased 2.72-fold in the ⬎ 60-year-old group in women when compared to the 20- to 40-year age group (P ⬍ .05) (Supplemental Table 1). There was a significant positive correlation between skeletal muscle 11-HSD1 expression and age in women across the groups (rho ⫽ 0.40; P ⫽
.009) (Figure 1A). This association remained significant when controlling for lean mass (P ⫽ .01), bone mass (P ⫽ .01), fat mass (P ⫽ .04), but not insulin resistance (P ⫽ .05) or BMI (P ⫽ .08) using multiple regression analysis. When women were divided by menopausal status on the basis of the absence of periods and serum FSH levels ⬎ 25 IU/L, 11-HSD1 expression was increased in the postmenopausal group (P ⫽ .005). A nonsignificant 1.8-fold increase in 11-HSD1 gene expression was observed in men aged ⬎ 60 years. No statistically significant differences in
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doi: 10.1210/jc.2015-1516
expression of 11-HSD type 2 (11-HSD2), GC receptor (GR), or hexose-6-phosphate dehydrogenase were observed between age groups. Significant correlations were observed between 11-HSD1 expression and a number of GC-regulated genes involved in muscle turnover (Supplemental Table 2). Urine steroid analysis As shown previously, cortisol secretion rate (reflected by total cortisol metabolites [g/24 h]; Supplemental Table 3) was higher in men than in women across every age group (20 – 40 year group: women, 5565 [3763–7148] vs men 9276 [6049 –16 132], P ⫽ .0008; 40 – 60 year group: women, 6520 [4503– 8000] vs men 10 192 [6945– 11 447], P ⫽ .002; and ⬎ 60 year group: women, 5812 [4692–7401] vs men 8948 [7150 –10 693], P ⫽ .0005), and “global” 11-HSD1 activity (reflected by the tetrahydrocortisol [THF]⫹5␣-THF/tetrahydrocortisone [THE] ratio) was higher in men than women in the ⬎ 60 year age group (1.01 [0.94 –1.12] vs 0.74 [0.65– 0.94]; P ⫽ .001), whereas there was a trend toward increased activity in men at the younger age groups (20 – 40 year group: men,
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0.94 [0.75–1.10], vs women, 0.84 [0.71–1.02], P ⫽ .34; and 40 – 60 year group: men, 1.19 [0.82–1.33], vs women, 0.87 [0.75–1.10], P ⫽ .09). However, within gender, there were no statistically significant differences in total cortisol metabolites or urine steroid metabolite markers of 11HSD1 or 11-HSD2 (Supplemental Table 3) with age. In men, there was evidence of a reduction in 5␣-reductase activity in the oldest group (P ⫽ .048). Bivariate correlations between 11-HSD1 expression/global activity and phenotypic markers 11-HSD1 expression was negatively correlated with bone mass (BMC) (P ⬍ .01), grip strength, and IGF-1 (both P ⬍ .05) in women, and diastolic blood pressure (DBP), total lean mass and grip strength (all P ⬍ .05) in men (Table 2 and Figure 2). The association with grip strength remained significant after controlling for HOMA-IR and serum IGF-1. 11-HSD1 expression was positively correlated with body fat (percentage) (P ⬍ .05), HOMA-IR (P ⬍ .05), total cholesterol (P ⬍ .01), and LH and FSH (both P ⬍ .001) in women. Urine THF⫹5␣THF/ THE correlated positively with bone mass (P ⬍ .05) in
Figure 1. 11-HSD1 expression by age and menopausal status. Skeletal muscle 11-HSD1 transcript levels were normalized to endogenous control 18S and presented here as percentage of maximum gender-specific expression. A and B, There was a significant positive correlation between skeletal muscle 11-HSD1 expression and age in women (rho ⫽ 0.40; P ⫽ .009) (A), but not men (B). C, Skeletal muscle 11-HSD1 expression was increased in postmenopausal women as determined by the absence of periods and serum FSH level ⬎ 25 IU/L (P ⫽ .005).
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Table 2.
11-HSD1 Across Healthy Human Aging
J Clin Endocrinol Metab
Bivariate Correlations Between Markers of 11-HSD1 Expression and Activity and Subject Characteristics Correlation Coefficients (Spearman) Women
Observational data SBP DBP BMI Body composition Total fat mass Body fat % Total lean mass Bone mass (BMC) Strength testing Grip strength S2LJ Pmax S2lJ Vmax Jump height Serum biochemistry Fasting glucose Fasting insulin HOMA-IR Total cholesterol HDL-C 9 AM cortisol SHBG IGF-1 FSH LH T DHEAS
Men
Skeletal Muscle 11-HSD1 Expression
Urine (THFⴙ5␣THF)/THE
Skeletal Muscle 11-HSD1 Expression
Urine (THFⴙ5␣THF)/THE
0.09 0.25 0.19
⫺0.05 ⫺0.02 ⫺0.00
⫺0.02 ⴚ0.36a ⫺0.15
0.02 0.06 0.27
0.24 0.33a ⫺0.23 ⴚ0.49b
0.16 0.09 0.23 0.29a
⫺0.24 ⫺0.07 ⴚ0.35a ⫺0.32
0.40b 0.28 0.33a 0.10
ⴚ0.37a ⫺0.26 ⫺0.11 ⫺0.11
0.23 0.01 0.01 ⫺0.04
ⴚ0.40a ⫺0.30 ⫺0.33 ⫺0.29
⫺0.16 ⴚ0.32a ⫺0.26 ⫺0.22
0.23 0.30 0.41a 0.49b 0.10 ⫺0.28 ⫺0.14 ⴚ0.38a 0.56c 0.50c ⫺0.03 ⫺0.19
0.03 0.14 0.14 0.09 ⫺0.01 0.14 ⫺0.19 0.15 ⫺0.12 ⫺0.01 0.09 0.10
0.15 ⫺0.08 ⫺0.12 0.08 0.09 0.11 0.20 ⫺0.18 ⫺0.00 0.08 0.14 ⫺0.05
0.11 0.15 0.17 ⫺0.07 ⫺0.05 0.03 0.08 ⫺0.09 ⫺0.13 ⫺0.24 ⴚ0.39b ⴚ0.31a
Abbreviation: SBP, systolic blood pressure. Data are expressed as correlation coefficients (Spearman correlations []). a– c a
P ⬍ .05; b P ⬍ .01; c P ⬍ .001 (n ⫽ 77 women and 57 men for urine analysis data; n ⫽ 45 women and 40 men for gene expression data).
women and total fat mass (P ⬍ .01) and total lean mass (P ⬍ .05) in men. Urine THF⫹5␣THF/THE correlated negatively with serum T (P ⬍ .01) and DHEAS (P ⬍ .05) in men. Prednisolone generation There were no significant correlations between area under the curve for prednisolone after oral administration of 10 mg prednisone and age in women (rho ⫽ 0.11; P ⫽ .62) or men (rho ⫽ 0.28; P ⫽ .17) (Supplemental Figure 1). Of note, there were no significant differences in age or 11-HSD1 gene expression between the subjects who received or did not receive prednisone.
Discussion This is the largest study assessing skeletal muscle 11HSD1 gene expression and cortisol metabolism across human aging. Our recruitment of 134 healthy volunteers complements previous studies that have investigated tissue-specific effects of 11-HSD1 in adipose tissue (n ⫽
46), skin (n ⫽ 40), and bone (n ⫽ 18) with age (5–7). Furthermore, our cohort includes male and female subjects distributed across the age range who have been extensively phenotyped by undergoing assessment of anthropometric data, body composition analysis by DEXA, grip strength dynamometry, jump-plate mechanography, serum biochemistry, vastus lateralis muscle biopsy, and urine steroid metabolite analysis. There are some general caveats when interpreting our findings; the first among these is the cross-sectional nature of the study, which is open to potential bias. For example, in aiming to recruit a “healthy” elderly cohort to minimize the established confounding issue of obesity and other medical conditions, this cohort cannot be representative of the wider population. Our cohort, over 70 years, was community-dwelling and independent, as well as being motivated to volunteer in a research study, so those with frailty and poor functional status (who arguably may have had higher 11-HSD1 activity) were unrepresented. Furthermore, structured information on exercise capability was not collected at baseline. We made multiple bivariate com-
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doi: 10.1210/jc.2015-1516
parisons, and although our 17 of 92 significant findings greatly exceed the assumed 5% type 1 error rate, it is important to note that some of these may be type 1 errors. Finally, we analyzed skeletal muscle 11-HSD1 gene expression, but not activity for logistical reasons (sample size); however previous studies have shown that these two parameters are well correlated (6). Expected differences in serum biochemistry between age groups are seen in our cohort with declines in hormones such as IGF-1 and androgens, along with the postmenopausal increase in gonadotropins. Body composition changes are also broadly in keeping with expectations in women, with increasing BMI and fat mass in middle age and declining bone mass in older women. Age-associated reductions in strength testing parameters were observed, whereas reductions in lean mass did not reach statistical significance. Our primary interest was to address whether 11HSD1 skeletal muscle gene expression increases with age. Our most striking finding was the elevation of 11-HSD1 seen in old vs young women, which is consistent with our central hypothesis. Although this is a novel finding, it is
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consistent with previous data confirming its expression and activity in skeletal muscle and up-regulation with age in other human tissues (5– 8). It is interesting that this local increase in 11-HSD1 expression did not translate into an elevation in urinary markers of global enzyme activity. It is possible that there are tissue-specific changes in 11HSD1 expression/activity with age, so that muscle-specific changes are offset by lack of, or counterchanges in other tissues. Indeed, our data showing no differences with age in hepatic first-pass conversion of prednisone to prednisolone are consistent with this. This contradicts the findings of a previous paper with smaller sample size, where urinary (5␣⫹5THF)/THE ratios were increased in postmenopausal vs premenopausal women, in association with raised adipose mRNA expression and hepatic firstpass conversion of cortisone to cortisol (6). Furthermore, studies of liver-specific 11-HSD1 knockout mice revealed that urinary markers of enzyme activity were unchanged (17). In recent years, studies using stable isotope tracers have provided evidence of tissue-specific differences in 11-HSD1 function. Driven by an interest in metabolic syndrome, studies have focused on liver and adi-
Figure 2. Bivariate correlations between 11-HSD1 expression and phenotypic markers of skeletal muscle aging. Skeletal muscle 11-HSD1 transcript levels were normalized to endogenous control 18S and presented here as percentage of maximum gender-specific expression. A and B, Skeletal muscle 11-HSD1 was negatively correlated with grip strength in women (A) (rho ⫽ ⫺0.37; P ⫽ .03) and men (B) (rho ⫽ ⫺0.40; P ⫽ .03). C and D, 11-HSD1 was negatively correlated with total lean mass determined by DEXA in men (D) (rho ⫽ ⫺0.35; P ⬍ .05) but not women (C) (rho ⫽ ⫺0.23; P ⫽ .16). Data were analyzed by Spearman correlations (rho). n ⫽ 45 women, 40 men.
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pose tissue, with the largest systemic contribution to “global” activity coming from liver. However, when faced with “tissue mass,” other organs, particularly skin and skeletal muscle, are likely to play a minor role. Interestingly, there is evidence of recycling between cortisone and cortisol in peripheral tissues, suggesting that the enzyme may function as a dehydrogenase as well as an oxoreductase in vivo (18, 19). We could speculate that these factors may be at play here. Again the “normality” of our cohort may have inadvertently masked changes in global 11HSD1 activity within advancing age, assuming that the most severely affected (obese, CVS risk, muscle loss) had the greatest defect in cortisol metabolism. In our study, there were also no differences between urinary markers of 11-HSD2 between age groups. Although there is a paucity of published data in this area, this runs counter to a paper by Campino et al (20), which showed evidence for a reduction in 11-HSD2 activity with age in a study of 196 healthy normotensive subjects. It is also notable that we observed no changes in gene expression of 11-HSD2, GR, and hexose-6-phosphate dehydrogenase between age groups. GCs have profound effects on muscle by promoting myofibrillar degradation and inhibiting anabolic pathways (21). Our bivariate correlations reveal an association between 11-HSD1 expression and reduced grip strength observed in both sexes, in keeping with our hypothesis that local tissue amplification of GCs affects muscle function, which supports the findings of a recent paper (22). 11-HSD1 expression positively correlated with genes known to be involved in muscle atrophy including the cell cycle regulators GADD45a and CDKN1A, acetylation factor P300, apoptotic factor caspase 3, cytokines TNF-␣, TGFB1, and downstream intracellular signaling molecule SMAD2. Surprisingly, 11-HSD1 expression was negatively correlated with ubiquitin ligases MAFbx/atrogin1 and MuRF1. Other negative correlations were observed with the muscle differentiation marker myogenin, muscle protein MYH2, anabolic factor ATF-4, and transcriptional coactivator PPARG1A. Skeletal muscle 11-HSD1 expression was also correlated with an increase in percentage body fat and insulin resistance in women. This is consistent with a number of studies investigating expression/activity in sc and visceral fat, although in some studies this relationship was not seen (4). It cannot be discounted that the observed increase in 11-HSD1 expression with age in women may be related to increasing insulin resistance. Previous papers have also shown evidence for a decline in hepatic 11-HSD1 activity in obesity (23). It is important to note, however, that our results are taken from healthy subjects with BMI ⬍ 30 kg/m2, so the dynamics of any relationship between 11-
J Clin Endocrinol Metab
HSD1 activity and fat mass may be different in obese cohorts or those with overt metabolic disease. Several studies have identified potential regulators of 11-HSD1 including GCs, growth factors, and proinflammatory cytokines (24). In this study, the sexual dimorphism in skeletal muscle 11-HSD1 expression with aging is consistent with the menopause as the driving factor. This is of particular interest because sarcopenia, osteoporosis, increasing fat mass, dyslipidemia, and a sharp increase in cardiovascular disease risk are closely associated with the menopause (23–26). It has been suggested that declining sex steroid (androgens and estrogens) to GC ratios could underpin the emergence of sarcopenia and features of the metabolic syndrome after the menopause (25, 26). Although the relationship between sex steroids and skeletal muscle 11-HSD1 expression has not been previously investigated, in vivo rodent studies demonstrate down-regulation of 11-HSD1 expression/activity with estradiol treatment in liver, visceral adipose tissue (27), testis (28), and kidney (29). Animal data demonstrate that sexual dimorphism in rodent liver 11-HSD1 expression/activity may be modified by administration of GH in a constant (female) or pulsatile (male) pattern (30, 31). Furthermore, human studies have shown reduced global activity of 11HSD1 in women compared to men, an effect that is also apparent in postmenopausal subjects (32). McInnes et al (33) showed that estrogen receptor- was increased in sc adipose tissue postmenopausally with expression correlated with 11-HSD1. In addition, an in vitro study confirmed up-regulation of 11-HSD1 in response to treatment with an estrogen receptor- agonist. There is a paucity of evidence investigating other potential postmenopausal factors with gonadotropins increasing 11HSD1 gene expression in rat granulosa cells in culture (34). In addition, progesterone has been shown to suppress 11-HSD1 activity in cultured human hepatocytes (35). The age-related decline in GH is well recognized, and there is a body of evidence supporting a role for GH acting via IGF-1 in suppressing 11-HSD1 expression/ activity from in vitro and clinical studies (36 –38). We observed a negative correlation between global activity of 11-HSD1 and serum T and DHEAS in men, but not women; previous cell culture experiments support a role for androgens in the regulation of this enzyme (36, 39, 40). This study is the first to examine these relationships in a tissue-specific manner in vivo. There are also some candidate regulators of 11-HSD1 that we were unable to assess in the study. Levels of proinflammatory cytokines increase with age, and a number of cell culture experiments including our own have demonstrated that these can increase 11-HSD1 expression (24).
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doi: 10.1210/jc.2015-1516
In summary, we present a detailed clinical study evaluating cortisol secretion and metabolism in human aging, with 134 participants of both sexes across the age spectrum who have been extensively phenotyped. We show that skeletal muscle 11-HSD1 expression is increased with age in healthy female subjects in association with an adverse body composition and metabolic phenotype. 11HSD1 expression was also associated with reduced grip strength and changes in key atrophy genes. The cause of increased muscle expression remains unknown but may be related to falling IGF-1 and/or estrogen levels. Our results set the scene for future studies examining 11-HSD1 in “patients” with aging-related disorders and exploring the role of selective inhibitors of 11-HSD1 in preventing/ reversing age-related sarcopenia.
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Acknowledgments The authors thank Peter Nightingale, Theresa Brady, Pamela Jones, and Claire Brown (National Institute for Health ResearchWellcome Trust Clinical Research Facility); Janet Lord, Donna O’Neill, and Iwona Bujalska (University of Birmingham); Nicola Crabtree and Andrew Toogood (Queen Elizabeth Hospital Birmingham); and Mark Cooper (University of Sydney).
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Address all correspondence and requests for reprints to: Zaki K. Hassan-Smith, BMedSci (Hons), MBBS, MRCP (UK), PhD, Centre for Endocrinology, Diabetes, and Metabolism, School of Clinical and Experimental Medicine, Second Floor, Institute for Biomedical Research, University of Birmingham, Edgbaston B15 2TT, United Kingdom. E-mail: [email protected]. The study was funded by the European Research Council (Advanced Grant “Precort” to P.M.S.). Disclosure Summary: The authors have nothing to disclose.
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35. Ricketts ML, Verhaeg JM, Bujalska I, Howie AJ, Rainey WE, Stewart PM. Immunohistochemical localization of type 1 11-hydroxysteroid dehydrogenase in human tissues. J Clin Endocrinol Metab. 1998;83:1325–1335. 36. Whorwood CB, Donovan SJ, Wood PJ, Phillips DI. Regulation of glucocorticoid receptor ␣ and  isoforms and type I 11-hydroxysteroid dehydrogenase expression in human skeletal muscle cells: a key role in the pathogenesis of insulin resistance? J Clin Endocrinol Metab. 2001;86(5):2296 –2308. 37. Toogood AA, Taylor NF, Shalet SM, Monson JP. Modulation of cortisol metabolism by low-dose growth hormone replacement in elderly hypopituitary patients. J Clin Endocrinol Metab. 2000; 85(4):1727–1730. 38. Frajese GV, Taylor NF, Jenkins PJ, Besser GM, Monson JP. Modulation of cortisol metabolism during treatment of acromegaly is independent of body composition and insulin sensitivity. Horm Res. 2004;61(5):246 –251. 39. Apostolova G, Schweizer RA, Balazs Z, Kostadinova RM, Odermatt A. Dehydroepiandrosterone inhibits the amplification of glucocorticoid action in adipose tissue. Am J Physiol Endocrinol Metab. 2005;288(5):E957–E964. 40. McNelis JC, Manolopoulos KN, Gathercole LL, et al. Dehydroepiandrosterone exerts antiglucocorticoid action on human preadipocyte proliferation, differentiation, and glucose uptake. Am J Physiol Endocrinol Metab. 2013;305(9):E1134 –E1144.
Hassan-Smith et al
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ARTICLE
Gender-Specific Differences in Skeletal Muscle 11HSD1 Expression Across Healthy Aging Zaki K. Hassan-Smith, Stuart A. Morgan, Mark Sherlock, Beverly Hughes, Angela Taylor, Gareth Lavery, Jeremy W. Tomlinson, and Paul M. Stewart Centre for Endocrinology, Diabetes, and Metabolism (Z.K.H.-S., S.A.M., B.H., A.T., G.L.), School of Clinical and Experimental Medicine, Institute for Biomedical Research, University of Birmingham, Edgbaston B15 2TT, United Kingdom; Department of Endocrinology (M.S.), Adelaide and Meath Hospital, Tallaght, Dublin 24, Ireland; Trinity College (M.S.), Dublin 2, Ireland; Oxford Centre for Diabetes, Endocrinology, and Metabolism (J.W.T.), University of Oxford, Churchill Hospital, Headington, Oxford OX3 7LE, United Kingdom; and Faculty of Medicine and Health (P.M.S.), University of Leeds, Leeds LS2 9NL, United Kingdom
Context: Cushing’s syndrome is characterized by marked changes in body composition (sarcopenia, obesity, and osteoporosis) that have similarities with those seen in aging. 11-hydroxysteroid dehydrogenase type 1 (11-HSD1) converts glucocorticoids to their active form (cortisone to cortisol in humans), resulting in local tissue amplification of effect. Objective: To evaluate 11-HSD1 expression and activity with age, specifically in muscle. To determine putative causes for increased activity with age and its consequences upon phenotypic markers of adverse aging. Design: Cross-sectional observational study. Setting: National Institute for Health Research-Wellcome Trust Clinical Research Facility, Birmingham, United Kingdom. Patients or Other Participants: Healthy human volunteers age 20 to 81 years (n ⫽ 134; 77 women, 57 men). Interventions: Day attendance at research facility for baseline observations, body composition analysis by dual-energy x-ray absorptiometry, jump-plate mechanography, grip strength analysis, baseline biochemical profiling, urine collection, and vastus lateralis muscle biopsy. Main Outcome Measure(s): Skeletal muscle gene expression, urine steroid profile, bivariate correlations between expression/activity and phenotypic/biochemical variables. Results: Skeletal muscle 11-HSD1 expression was increased 2.72-fold in women over 60 years of age compared to those aged 20 – 40 years; no differences were observed in men. There was a significant positive correlation between skeletal muscle 11-HSD1 expression and age in women across the group (rho ⫽ 0.40; P ⫽ .009). No differences in expression of 11-HSD type 2, glucocorticoid receptor, or hexose-6-phosphate dehydrogenase between age groups were observed in either sex. Urinary steroid markers of 11-HSD1, 11-HSD type 2, or 5␣-reductase were similar between age groups. Skeletal muscle 11-HSD1 expression was associated with reduced grip strength in both sexes and correlated positively with percentage of body fat, homeostasis model of assessment for insulin resistance, total cholesterol, LH, and FSH and negatively with bone mineral content and IGF-1 in women. Conclusions: Skeletal muscle 11-HSD1 is up-regulated with age in women and is associated with reduced grip strength, insulin resistance, and an adverse body composition profile. Selective inhibition of 11-HSD1 may offer a novel strategy to prevent and/or reverse age-related sarcopenia.
doi: 10.1210/jc.2015-1516
J Clin Endocrinol Metab
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ushing’s syndrome is characterized by changes in body composition (sarcopenia, central obesity, osteoporosis), development of metabolic dysfunction (insulin resistance), and cardiovascular disease (1), which have similarities to the aged phenotype. Circulating cortisol levels are maintained under negative feedback regulation via the hypothalamic-pituitary-adrenal axis. Studies examining age-associated changes in the hypothalamic-pituitary-adrenal axis have had mixed results (2, 3), although some demonstrate blunting of cortisol diurnal secretion along with increases in mean levels. Local glucocorticoid (GC) exposure is also regulated at the prereceptor level by the 11-hydroxysteroid dehydrogenase type 1 (11-HSD1) enzymes, with the type 1 isoform acting primarily as an oxoreductase converting inactive GCs to their active form (cortisone to cortisol in humans) (4). Prereceptor GC metabolism by 11-HSD1 has been implicated in the pathogenesis of the metabolic syndrome and a range of conditions including osteoporosis and glaucoma (4). There is growing evidence that 11-HSD1 expression/activity is elevated in key tissues including bone (5), adipose tissue (6), and skin (7) with aging and may be implicated in the development of associated disease states. 11-HSD1 has been shown to be present and functionally active in skeletal muscle (8) and to play a role in the pathogenesis of insulin resistance (9). Furthermore, in vitro and in vivo mouse models have demonstrated that 11-HSD1 regulates GC-induced muscle atrophy via the ubiquitin-proteasomal system (10, 11). With the additional recognition that loss of lean muscle mass contributes to adverse “healthspan,” we have performed a detailed assessment of prereceptor GC metabolism through measurement of skeletal muscle 11-HSD1 expression, along with hepatic and global activity, in both sexes across the age spectrum. Associations with potential phenotypic markers of adverse aging and regulators of 11-HSD1 were assessed using strength testing, body composition, and biochemical analyses.
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Female subjects were in the follicular phase of the menstrual cycle or, if postmenopausal, were not on hormone replacement therapy. Exclusion criteria included pregnancy and medical history of diabetes mellitus, ischemic heart disease, cerebrovascular disease, severe respiratory disease, and epilepsy. Other exclusion criteria were therapy in the past 12 months, use of drugs known to affect the GH-IGF-1 axis, and use of oral anticoagulants. Subjects prescribed aspirin were asked to discontinue treatment 3 days before muscle biopsy. Procedures were carried out over a 1-day visit to the National Institute for Health Research (NIHR)Wellcome Trust Clinical Research Facility at the Queen Elizabeth Hospital Birmingham. Patients arrived fasted at 8:30 AM, having collected a complete urine sample over the preceding 24 hours.
Initial observations Height, weight, and the mean of three blood pressure measurements (recorded using an automatic sphygmomanometer with the subject seated) were recorded on arrival.
Urine steroid profiling by gas chromatography/ mass spectrometry On receipt of the 24-hour urine collection, total volume was noted, and a 30-mL aliquot was transferred to a universal container and stored at ⫺80°C pending analysis. Gas chromatography/mass spectrometry (GC/MS) analysis was performed using established and previously described methodology (12, 13). Briefly, this was comprised of extraction of steroids and their conjugates from urine via solid phase extraction, followed by deconjugation and derivatization to produce methyloxime-trimethylsilyl ethers, suitable for GC/MS analysis. GC/MS analysis was performed using an Agilent GC/MS 5973 instrument. Steroids were quantified based on selected ion monitoring transitions relative to calibration steroid standards.
Dual-energy x-ray absorptiometry scan Dual-energy x-ray absorptiometry (DEXA) scanning (Hologic Discovery with DXA software version Apex 3.0; Hologic Inc) was used to assess full body composition and bone mineral density (BMD) (coefficient of variation for fat and lean mass, ⬍3%).
Strength testing
Subjects and Methods Human study protocol A total of 134 healthy volunteers (77 women, 57 men) between 20 and 81 years of age and with a body mass index (BMI) between 20 and 30 kg/m2 were recruited from local populations. ISSN Print 0021-972X ISSN Online 1945-7197 Printed in USA Copyright © by the Endocrine Society Received February 26, 2015. Accepted May 8, 2015.
Hand-held dynamometry Three maximal contractions from both the right and left hand were obtained with 15 seconds of rest using of a grip strength dynamometer (Takei Instruments). Peak absolute strength in kilograms and relative handgrip strength (kilograms of force per kilogram of body weight) were recorded. Abbreviations: BMI, body mass index; DBP, diastolic blood pressure; DEXA, dual-energy x-ray absorptiometry; DHEAS, dehydroepiandrosterone sulfate; GC, glucocorticoid; GC/ MS, gas chromatography/mass spectrometry; GR, GC receptor; HDL-C, high-density lipoprotein-cholesterol; HOMA-IR, homeostasis model of assessment for insulin resistance; 11-HSD1, 11-hydroxysteroid dehydrogenase type 1; 11-HSD2, 11-HSD type 2; Pmax, maximum power; THE, tetrahydrocortisone; THF, tetrahydrocortisol; Vmax, maximum velocity.
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doi: 10.1210/jc.2015-1516
Jump-plate mechanography This method utilizes forces measured by ground force reaction platform (Leonardo system; Novotec), over the course of a range of movements under the supervision of a trained operator working to a standard operating procedure. Maximum velocity (Vmax), maximum power (Pmax) output, and height of jump were calculated.
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a housekeeping gene for singleplex analysis. Reactions were performed using the Biomark system on a dynamic array integrated fluidic circuit (Fluidigm) according to the manufacturer’s protocols.
Statistical analysis
Samples were analyzed for urea, electrolytes, creatinine, lipids, glucose (Roche modular system; Roche), cortisol, TSH, free T4 (Advia Centaur; Bayer Diagnostics), dehydroepiandrosterone sulfate (DHEAS), SHBG, and GH (Immulite; Siemens AG) at the University Hospital Birmingham National Health Service Foundation Trust laboratories. Insulin was determined using a colorimetric ELISA (Mercodia) (coefficient of variation, ⬍5%). Homeostasis model of assessment for insulin resistance (HOMA-IR) was calculated using the following formula: fasting glucose (millimoles per liter)ⴱfasting insulin (milliinternational units per liter)/22.5.
Analyses were performed using Prism for Mac version 5.0 (GraphPad Software Inc) unless otherwise stated. For PCR analyses, statistical tests were performed on ⌬CT values. Data were expressed in arbitrary units calculated by the formula 1000 ⫻ (2⫺⌬CT), or fold-change vs the 20- to 40-year age group (2⫺⌬⌬CT). Nonparametric tests were used with Kruskal-Wallis and Dunn’s post-test correction when comparing multiple groups. Bivariate correlations between variables were performed using Spearman’s test. Multivariable analyses were performed using multiple linear regression after log-transforming 11HSD1 expression so that assumptions of normality were not violated, using the Statistical Package for the Social Sciences (SPSS) version 21 (IBM). A P value ⬍ .05 was taken as the threshold for statistical significance.
Prednisolone generation test
Ethical approval
Prednisone has an identical affinity for 11-HSD1 as cortisone; the interconversion of oral prednisone to prednisolone has been used as a marker of predominantly hepatic 11-HSD1 activity (reflecting first-pass metabolism) (14). Baseline blood samples were taken at approximately 9 AM, before oral administration of 10 mg prednisone. Additional samples were collected at 20-minute intervals over a period of 4 hours. Samples for prednisone and prednisolone were analyzed in-house by liquid chromatography/mass spectrometry (25 men and 23 women analyzed). Steroids were extracted from 200 L of serum (after addition of an internal standard) via liquid/liquid extraction with 1 mL methyl tertiary butyl ether; the solvent was evaporated, and the sample was reconstituted in methanol/water before analysis by ultra-performance liquid chromatography-tandem mass spectrometry. Waters Xevo with Acquity ultra-performance liquid chromatography was utilized in these experiments with an HSS T3 1.8 M 1.2 ⫻ 50-mm column. Steroids were eluted using a methanol/water gradient system. All steroids were identified by a matching retention time and two identical mass transitions when compared to an authentic steroid standard. Mass transitions in positive ionization mode were: prednisone, 359 ⬎ 147 (quantifier) and 359 ⬎ 341 (qualifier); and prednisolone, 361 ⬎ 343 (quantifier) and 361 ⬎ 147 (qualifier). Steroids were quantified relative to a calibration series ranging from 0.25 to 500 ng/mL (15).
Ethical approval was obtained from the Coventry and Warwickshire Research Ethics Committee (REC reference no. 07/ H1211/168). The protocol was approved by the Scientific Committee of the NIHR-Wellcome Trust Clinical Research Facility at Queen Elizabeth Hospital Birmingham. The study commenced in October 2010 and was completed in March 2013. Volunteers were given written and verbal information on the study, and they gave written informed consent. After study completion, they received travel expenses, and clinically relevant results were passed on to general practitioners.
Fasting blood levels
Vastus lateralis muscle biopsy All biopsies were performed by a single investigator (Z.K.H.S.) in 45 women and 40 men using a percutaneous Bergstrom technique with suction to increase sample yield, as described by Tarnopolsky et al (16). The ages of subjects agreeing to muscle biopsies were similar to the overall cohort (women biopsied, 46.8 ⫾ 2.5 y vs whole cohort, 47.1 ⫾ 1.9 y, P ⫽ .93; men biopsied, 46.7 ⫾ 3.0 y vs whole cohort, 48.2 ⫾ 2.5 y, P ⫽ .69).
Quantitative (real-time) PCR Gene expression analysis was performed using Applied Biosystems reagents and expression assays. 18s rRNA was used as
Results Subject characteristics Characteristics of the 134 healthy volunteers (77 women, 57 men) in the study are outlined in Table 1. They were between 20 and 81 years old, with BMI between 20 and 30 kg/m2. BMI was greater in the 40 – 60 and ⬎ 60year age groups in men and women when compared to the 20- to 40-year-old subgroup (Table 1). Fat mass, as calculated by DEXA analysis, was greater in the 40 – 60 and ⬎ 60-year age groups, and bone mass was lower in the ⬎ 60-year age group in women. Pmax measured by jump-plate mechanography was lower in the 40 – 60 and ⬎ 60-year age groups in women and the ⬎ 60-year age groups in men. Vmax was lower in the 40 – 60 and ⬎ 60-year age groups in women and men. In women, but not men, fasting insulin, HOMA-IR, total cholesterol, FSH, and LH were all greater in the 40 – 60 and ⬎ 60-year age groups, and fasting glucose and high-density lipoproteincholesterol (HDL-C) were greater in the ⬎ 60-year age group. The 9 AM cortisol was lower with age in women and men. IGF-1 was lower in the ⬎ 60-year age groups in men
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Table 1.
11-HSD1 Across Healthy Human Aging
J Clin Endocrinol Metab
Subject Characteristics Women
Age Groups, y n Observational data SBP, mm Hg DBP, mm Hg BMI, kg/m2 Body composition Fat mass, kg Lean mass, kg Bone mass, (BMC) (kg) Strength testing Grip strength, kg Pmax, W/kg Vmax, m/s Serum biochemistry Fasting glucose, mmol/L Fasting insulin, pmol/ L HOMA-IR Total cholesterol, nmol/L HDL-C, mmol/L 9 AM cortisol, nmol/L SHBG, nmol/ L IGF-1, nmol/L FSH, IU/L LH, IU/L T, nmol/L DHEAS, nmol/L
20 – 40
Men
40 – 60
20 – 40
>60
40 – 60
>60
27
27
23
22
13
22
115 (110 –126) 75 (64 – 81) 22 (19 –24)
119 (111–128) 74 (67– 81) 26 (25–28)c
141 (133–158) 81 (67– 88) 24 (22–27)a
127 (120 –135) 77 (71– 86) 24 (22–25)
128 (125–147) 85 (78 –92) 28 (25–28)b
140 (122–155) 83 (68 –91) 25 (24 –29)a
16.5 (14.2–20.2) 24.5 (21.8 –27.0)c 21.3 (18.9 –23.4)a 14.8 (10.9 –19.2) 17.5 (13.5–18.6) 17.7 (13.8 –23.7) 41.6 (36.1– 43.4) 41.6 (38.2– 45.4) 39.9 (36.8 – 42.7) 57.8 (51.8 – 61.4) 62.7 (56.3–70.1) 57.6 (52.1– 63.3) 20.8 (19.2–23.1) 20.8 (19.6 –22.1)
18.5 (16.9 –21.3)a 25.1 (23.1–28.5) 27.1 (24.7–32.6) 25.8 (24.3–28.0)
28.4 (25.3–30.9) 28.7 (26.0 –30.0)
26.6 (23.1–30.1)
43.5 (38.8 –50.9) 49.6 (39.7– 61.5) 41.5 (36.6 – 47.6)
35.6 (32.5– 43.8) 31.2 (28.7–35.1)a 25.8 (23.6 –29.1)c 49.7 (45.4 –54.5) 39.6 (36.8 – 45.0) 34.5 (30.6 –37.1)c 2.1 (2.0 –2.3) 1.9 (1.7–1.9)b 1.7 (1.6 –1.9)c 2.6 (2.4 –2.8) 2.3 (2.1–2.6)a 2.0 (1.8 –2.2)c 4.5 (4.3– 4.7)
4.7 (4.3– 4.9)
4.9 (4.7–5.1)b
5.0 (4.7–5.1)
4.8 (4.6 –5.1)
5.1 (4.9 –5.6)
2.9 (2.0 – 4.1)
4.1 (3.4 –5.7)a
4.5 (3.3– 6.7)a
5.6 (3.6 –10.9)
5.1 (3.2–9.7)
6.0 (3.8 –9.1)
0.6 (0.4 – 0.8) 4.0 (3.7– 4.7)
0.8 (0.7–1.4)a 5.2 (4.8 –5.8)c
1.0 (0.7–1.5)c 5.6 (4.5– 6.4)c
1.2 (0.8 –1.6) 4.2 (4.0 – 4.9)
1.2 (0.7–2.4) 5.0 (4.2–5.7)
1.3 (0.9 –1.9) 5.0 (4.2–5.7)
1.5 (1.3–1.8)
1.7 (1.3–1.8)
1.9 (1.7–2.1)b
1.3 (1.2–1.5)
1.3 (1.1–1.5)
1.5 (1.3–1.6)
331 (213–596)
223 (193–278)a
212 (175–274)b
364 (281– 452)
272 (207–339)a 263 (214 –358)a
70.3 (50.2–93.0)
28.1 (21.2–33.4) 38.7 (28.0 – 43.2) 42.9 (31.9 – 62.6)c
11.8 (10.3–13.7)c 68.2 (53.4 – 81.6)c 27.0 (21.9 –37.3)c 0.45 (0.3– 0.7)b 1.4 (0.8 –2.4)c
24.2 (20.5–30.0) 3.3 (1.9 – 4.9) 3.3 (2.7– 4.9) 17.3 (12.7–20.2) 8.4 (7.1–10.0)
63.3 (45.4 –95.2) 57.9 (37.1–70.0) 24.1 (22.4 –27.3) 4.7 (2.2–5.8) 4.1 (1.4 –7.4) 0.8 (0.6 –1.0) 3.8 (2.7– 6.1)
20.7 (15.9 –23.7)c 16.1 (6.9 – 65.4)c 14.3 (6.6 – 41.3)c 0.7 (0.5– 0.9) 3.0 (2.0 –3.7)a
19.4 (16.1–24.7) 4.6 (2.9 – 8.4) 3.5 (3.0 –5.2) 13.1 (11.9 –18.4) 5.5 (4.5– 6.8)
16.7 (13.1–18.7)c 5.1 (3.8 –7.4)b 4.9 (3.5–7.2) 14.8 (10.8 –19.8) 2.8 (2.2–3.5)c
Abbreviation: SBP, systolic blood pressure. Data are expressed as median (interquartile range). Vmax represents maximal velocity during upward movement. a– c a P ⬍ .05; b P ⬍ .01; c P ⬍ .001, vs 20- to 40-year-old sex-matched cohort as calculated by Kruskal-Wallis analysis with Dunn’s multiple comparison tests (n ⫽ 77 women, 57 men).
and women but was also lower in the 40- to 60-year group in women. Skeletal muscle gene expression 11-HSD1 gene expression from vastus lateralis was increased 2.72-fold in the ⬎ 60-year-old group in women when compared to the 20- to 40-year age group (P ⬍ .05) (Supplemental Table 1). There was a significant positive correlation between skeletal muscle 11-HSD1 expression and age in women across the groups (rho ⫽ 0.40; P ⫽
.009) (Figure 1A). This association remained significant when controlling for lean mass (P ⫽ .01), bone mass (P ⫽ .01), fat mass (P ⫽ .04), but not insulin resistance (P ⫽ .05) or BMI (P ⫽ .08) using multiple regression analysis. When women were divided by menopausal status on the basis of the absence of periods and serum FSH levels ⬎ 25 IU/L, 11-HSD1 expression was increased in the postmenopausal group (P ⫽ .005). A nonsignificant 1.8-fold increase in 11-HSD1 gene expression was observed in men aged ⬎ 60 years. No statistically significant differences in
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doi: 10.1210/jc.2015-1516
expression of 11-HSD type 2 (11-HSD2), GC receptor (GR), or hexose-6-phosphate dehydrogenase were observed between age groups. Significant correlations were observed between 11-HSD1 expression and a number of GC-regulated genes involved in muscle turnover (Supplemental Table 2). Urine steroid analysis As shown previously, cortisol secretion rate (reflected by total cortisol metabolites [g/24 h]; Supplemental Table 3) was higher in men than in women across every age group (20 – 40 year group: women, 5565 [3763–7148] vs men 9276 [6049 –16 132], P ⫽ .0008; 40 – 60 year group: women, 6520 [4503– 8000] vs men 10 192 [6945– 11 447], P ⫽ .002; and ⬎ 60 year group: women, 5812 [4692–7401] vs men 8948 [7150 –10 693], P ⫽ .0005), and “global” 11-HSD1 activity (reflected by the tetrahydrocortisol [THF]⫹5␣-THF/tetrahydrocortisone [THE] ratio) was higher in men than women in the ⬎ 60 year age group (1.01 [0.94 –1.12] vs 0.74 [0.65– 0.94]; P ⫽ .001), whereas there was a trend toward increased activity in men at the younger age groups (20 – 40 year group: men,
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0.94 [0.75–1.10], vs women, 0.84 [0.71–1.02], P ⫽ .34; and 40 – 60 year group: men, 1.19 [0.82–1.33], vs women, 0.87 [0.75–1.10], P ⫽ .09). However, within gender, there were no statistically significant differences in total cortisol metabolites or urine steroid metabolite markers of 11HSD1 or 11-HSD2 (Supplemental Table 3) with age. In men, there was evidence of a reduction in 5␣-reductase activity in the oldest group (P ⫽ .048). Bivariate correlations between 11-HSD1 expression/global activity and phenotypic markers 11-HSD1 expression was negatively correlated with bone mass (BMC) (P ⬍ .01), grip strength, and IGF-1 (both P ⬍ .05) in women, and diastolic blood pressure (DBP), total lean mass and grip strength (all P ⬍ .05) in men (Table 2 and Figure 2). The association with grip strength remained significant after controlling for HOMA-IR and serum IGF-1. 11-HSD1 expression was positively correlated with body fat (percentage) (P ⬍ .05), HOMA-IR (P ⬍ .05), total cholesterol (P ⬍ .01), and LH and FSH (both P ⬍ .001) in women. Urine THF⫹5␣THF/ THE correlated positively with bone mass (P ⬍ .05) in
Figure 1. 11-HSD1 expression by age and menopausal status. Skeletal muscle 11-HSD1 transcript levels were normalized to endogenous control 18S and presented here as percentage of maximum gender-specific expression. A and B, There was a significant positive correlation between skeletal muscle 11-HSD1 expression and age in women (rho ⫽ 0.40; P ⫽ .009) (A), but not men (B). C, Skeletal muscle 11-HSD1 expression was increased in postmenopausal women as determined by the absence of periods and serum FSH level ⬎ 25 IU/L (P ⫽ .005).
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Hassan-Smith et al
Table 2.
11-HSD1 Across Healthy Human Aging
J Clin Endocrinol Metab
Bivariate Correlations Between Markers of 11-HSD1 Expression and Activity and Subject Characteristics Correlation Coefficients (Spearman) Women
Observational data SBP DBP BMI Body composition Total fat mass Body fat % Total lean mass Bone mass (BMC) Strength testing Grip strength S2LJ Pmax S2lJ Vmax Jump height Serum biochemistry Fasting glucose Fasting insulin HOMA-IR Total cholesterol HDL-C 9 AM cortisol SHBG IGF-1 FSH LH T DHEAS
Men
Skeletal Muscle 11-HSD1 Expression
Urine (THFⴙ5␣THF)/THE
Skeletal Muscle 11-HSD1 Expression
Urine (THFⴙ5␣THF)/THE
0.09 0.25 0.19
⫺0.05 ⫺0.02 ⫺0.00
⫺0.02 ⴚ0.36a ⫺0.15
0.02 0.06 0.27
0.24 0.33a ⫺0.23 ⴚ0.49b
0.16 0.09 0.23 0.29a
⫺0.24 ⫺0.07 ⴚ0.35a ⫺0.32
0.40b 0.28 0.33a 0.10
ⴚ0.37a ⫺0.26 ⫺0.11 ⫺0.11
0.23 0.01 0.01 ⫺0.04
ⴚ0.40a ⫺0.30 ⫺0.33 ⫺0.29
⫺0.16 ⴚ0.32a ⫺0.26 ⫺0.22
0.23 0.30 0.41a 0.49b 0.10 ⫺0.28 ⫺0.14 ⴚ0.38a 0.56c 0.50c ⫺0.03 ⫺0.19
0.03 0.14 0.14 0.09 ⫺0.01 0.14 ⫺0.19 0.15 ⫺0.12 ⫺0.01 0.09 0.10
0.15 ⫺0.08 ⫺0.12 0.08 0.09 0.11 0.20 ⫺0.18 ⫺0.00 0.08 0.14 ⫺0.05
0.11 0.15 0.17 ⫺0.07 ⫺0.05 0.03 0.08 ⫺0.09 ⫺0.13 ⫺0.24 ⴚ0.39b ⴚ0.31a
Abbreviation: SBP, systolic blood pressure. Data are expressed as correlation coefficients (Spearman correlations []). a– c a
P ⬍ .05; b P ⬍ .01; c P ⬍ .001 (n ⫽ 77 women and 57 men for urine analysis data; n ⫽ 45 women and 40 men for gene expression data).
women and total fat mass (P ⬍ .01) and total lean mass (P ⬍ .05) in men. Urine THF⫹5␣THF/THE correlated negatively with serum T (P ⬍ .01) and DHEAS (P ⬍ .05) in men. Prednisolone generation There were no significant correlations between area under the curve for prednisolone after oral administration of 10 mg prednisone and age in women (rho ⫽ 0.11; P ⫽ .62) or men (rho ⫽ 0.28; P ⫽ .17) (Supplemental Figure 1). Of note, there were no significant differences in age or 11-HSD1 gene expression between the subjects who received or did not receive prednisone.
Discussion This is the largest study assessing skeletal muscle 11HSD1 gene expression and cortisol metabolism across human aging. Our recruitment of 134 healthy volunteers complements previous studies that have investigated tissue-specific effects of 11-HSD1 in adipose tissue (n ⫽
46), skin (n ⫽ 40), and bone (n ⫽ 18) with age (5–7). Furthermore, our cohort includes male and female subjects distributed across the age range who have been extensively phenotyped by undergoing assessment of anthropometric data, body composition analysis by DEXA, grip strength dynamometry, jump-plate mechanography, serum biochemistry, vastus lateralis muscle biopsy, and urine steroid metabolite analysis. There are some general caveats when interpreting our findings; the first among these is the cross-sectional nature of the study, which is open to potential bias. For example, in aiming to recruit a “healthy” elderly cohort to minimize the established confounding issue of obesity and other medical conditions, this cohort cannot be representative of the wider population. Our cohort, over 70 years, was community-dwelling and independent, as well as being motivated to volunteer in a research study, so those with frailty and poor functional status (who arguably may have had higher 11-HSD1 activity) were unrepresented. Furthermore, structured information on exercise capability was not collected at baseline. We made multiple bivariate com-
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doi: 10.1210/jc.2015-1516
parisons, and although our 17 of 92 significant findings greatly exceed the assumed 5% type 1 error rate, it is important to note that some of these may be type 1 errors. Finally, we analyzed skeletal muscle 11-HSD1 gene expression, but not activity for logistical reasons (sample size); however previous studies have shown that these two parameters are well correlated (6). Expected differences in serum biochemistry between age groups are seen in our cohort with declines in hormones such as IGF-1 and androgens, along with the postmenopausal increase in gonadotropins. Body composition changes are also broadly in keeping with expectations in women, with increasing BMI and fat mass in middle age and declining bone mass in older women. Age-associated reductions in strength testing parameters were observed, whereas reductions in lean mass did not reach statistical significance. Our primary interest was to address whether 11HSD1 skeletal muscle gene expression increases with age. Our most striking finding was the elevation of 11-HSD1 seen in old vs young women, which is consistent with our central hypothesis. Although this is a novel finding, it is
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consistent with previous data confirming its expression and activity in skeletal muscle and up-regulation with age in other human tissues (5– 8). It is interesting that this local increase in 11-HSD1 expression did not translate into an elevation in urinary markers of global enzyme activity. It is possible that there are tissue-specific changes in 11HSD1 expression/activity with age, so that muscle-specific changes are offset by lack of, or counterchanges in other tissues. Indeed, our data showing no differences with age in hepatic first-pass conversion of prednisone to prednisolone are consistent with this. This contradicts the findings of a previous paper with smaller sample size, where urinary (5␣⫹5THF)/THE ratios were increased in postmenopausal vs premenopausal women, in association with raised adipose mRNA expression and hepatic firstpass conversion of cortisone to cortisol (6). Furthermore, studies of liver-specific 11-HSD1 knockout mice revealed that urinary markers of enzyme activity were unchanged (17). In recent years, studies using stable isotope tracers have provided evidence of tissue-specific differences in 11-HSD1 function. Driven by an interest in metabolic syndrome, studies have focused on liver and adi-
Figure 2. Bivariate correlations between 11-HSD1 expression and phenotypic markers of skeletal muscle aging. Skeletal muscle 11-HSD1 transcript levels were normalized to endogenous control 18S and presented here as percentage of maximum gender-specific expression. A and B, Skeletal muscle 11-HSD1 was negatively correlated with grip strength in women (A) (rho ⫽ ⫺0.37; P ⫽ .03) and men (B) (rho ⫽ ⫺0.40; P ⫽ .03). C and D, 11-HSD1 was negatively correlated with total lean mass determined by DEXA in men (D) (rho ⫽ ⫺0.35; P ⬍ .05) but not women (C) (rho ⫽ ⫺0.23; P ⫽ .16). Data were analyzed by Spearman correlations (rho). n ⫽ 45 women, 40 men.
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11-HSD1 Across Healthy Human Aging
pose tissue, with the largest systemic contribution to “global” activity coming from liver. However, when faced with “tissue mass,” other organs, particularly skin and skeletal muscle, are likely to play a minor role. Interestingly, there is evidence of recycling between cortisone and cortisol in peripheral tissues, suggesting that the enzyme may function as a dehydrogenase as well as an oxoreductase in vivo (18, 19). We could speculate that these factors may be at play here. Again the “normality” of our cohort may have inadvertently masked changes in global 11HSD1 activity within advancing age, assuming that the most severely affected (obese, CVS risk, muscle loss) had the greatest defect in cortisol metabolism. In our study, there were also no differences between urinary markers of 11-HSD2 between age groups. Although there is a paucity of published data in this area, this runs counter to a paper by Campino et al (20), which showed evidence for a reduction in 11-HSD2 activity with age in a study of 196 healthy normotensive subjects. It is also notable that we observed no changes in gene expression of 11-HSD2, GR, and hexose-6-phosphate dehydrogenase between age groups. GCs have profound effects on muscle by promoting myofibrillar degradation and inhibiting anabolic pathways (21). Our bivariate correlations reveal an association between 11-HSD1 expression and reduced grip strength observed in both sexes, in keeping with our hypothesis that local tissue amplification of GCs affects muscle function, which supports the findings of a recent paper (22). 11-HSD1 expression positively correlated with genes known to be involved in muscle atrophy including the cell cycle regulators GADD45a and CDKN1A, acetylation factor P300, apoptotic factor caspase 3, cytokines TNF-␣, TGFB1, and downstream intracellular signaling molecule SMAD2. Surprisingly, 11-HSD1 expression was negatively correlated with ubiquitin ligases MAFbx/atrogin1 and MuRF1. Other negative correlations were observed with the muscle differentiation marker myogenin, muscle protein MYH2, anabolic factor ATF-4, and transcriptional coactivator PPARG1A. Skeletal muscle 11-HSD1 expression was also correlated with an increase in percentage body fat and insulin resistance in women. This is consistent with a number of studies investigating expression/activity in sc and visceral fat, although in some studies this relationship was not seen (4). It cannot be discounted that the observed increase in 11-HSD1 expression with age in women may be related to increasing insulin resistance. Previous papers have also shown evidence for a decline in hepatic 11-HSD1 activity in obesity (23). It is important to note, however, that our results are taken from healthy subjects with BMI ⬍ 30 kg/m2, so the dynamics of any relationship between 11-
J Clin Endocrinol Metab
HSD1 activity and fat mass may be different in obese cohorts or those with overt metabolic disease. Several studies have identified potential regulators of 11-HSD1 including GCs, growth factors, and proinflammatory cytokines (24). In this study, the sexual dimorphism in skeletal muscle 11-HSD1 expression with aging is consistent with the menopause as the driving factor. This is of particular interest because sarcopenia, osteoporosis, increasing fat mass, dyslipidemia, and a sharp increase in cardiovascular disease risk are closely associated with the menopause (23–26). It has been suggested that declining sex steroid (androgens and estrogens) to GC ratios could underpin the emergence of sarcopenia and features of the metabolic syndrome after the menopause (25, 26). Although the relationship between sex steroids and skeletal muscle 11-HSD1 expression has not been previously investigated, in vivo rodent studies demonstrate down-regulation of 11-HSD1 expression/activity with estradiol treatment in liver, visceral adipose tissue (27), testis (28), and kidney (29). Animal data demonstrate that sexual dimorphism in rodent liver 11-HSD1 expression/activity may be modified by administration of GH in a constant (female) or pulsatile (male) pattern (30, 31). Furthermore, human studies have shown reduced global activity of 11HSD1 in women compared to men, an effect that is also apparent in postmenopausal subjects (32). McInnes et al (33) showed that estrogen receptor- was increased in sc adipose tissue postmenopausally with expression correlated with 11-HSD1. In addition, an in vitro study confirmed up-regulation of 11-HSD1 in response to treatment with an estrogen receptor- agonist. There is a paucity of evidence investigating other potential postmenopausal factors with gonadotropins increasing 11HSD1 gene expression in rat granulosa cells in culture (34). In addition, progesterone has been shown to suppress 11-HSD1 activity in cultured human hepatocytes (35). The age-related decline in GH is well recognized, and there is a body of evidence supporting a role for GH acting via IGF-1 in suppressing 11-HSD1 expression/ activity from in vitro and clinical studies (36 –38). We observed a negative correlation between global activity of 11-HSD1 and serum T and DHEAS in men, but not women; previous cell culture experiments support a role for androgens in the regulation of this enzyme (36, 39, 40). This study is the first to examine these relationships in a tissue-specific manner in vivo. There are also some candidate regulators of 11-HSD1 that we were unable to assess in the study. Levels of proinflammatory cytokines increase with age, and a number of cell culture experiments including our own have demonstrated that these can increase 11-HSD1 expression (24).
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doi: 10.1210/jc.2015-1516
In summary, we present a detailed clinical study evaluating cortisol secretion and metabolism in human aging, with 134 participants of both sexes across the age spectrum who have been extensively phenotyped. We show that skeletal muscle 11-HSD1 expression is increased with age in healthy female subjects in association with an adverse body composition and metabolic phenotype. 11HSD1 expression was also associated with reduced grip strength and changes in key atrophy genes. The cause of increased muscle expression remains unknown but may be related to falling IGF-1 and/or estrogen levels. Our results set the scene for future studies examining 11-HSD1 in “patients” with aging-related disorders and exploring the role of selective inhibitors of 11-HSD1 in preventing/ reversing age-related sarcopenia.
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Acknowledgments The authors thank Peter Nightingale, Theresa Brady, Pamela Jones, and Claire Brown (National Institute for Health ResearchWellcome Trust Clinical Research Facility); Janet Lord, Donna O’Neill, and Iwona Bujalska (University of Birmingham); Nicola Crabtree and Andrew Toogood (Queen Elizabeth Hospital Birmingham); and Mark Cooper (University of Sydney).
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Address all correspondence and requests for reprints to: Zaki K. Hassan-Smith, BMedSci (Hons), MBBS, MRCP (UK), PhD, Centre for Endocrinology, Diabetes, and Metabolism, School of Clinical and Experimental Medicine, Second Floor, Institute for Biomedical Research, University of Birmingham, Edgbaston B15 2TT, United Kingdom. E-mail: [email protected]. The study was funded by the European Research Council (Advanced Grant “Precort” to P.M.S.). Disclosure Summary: The authors have nothing to disclose.
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