Inflammatory adipokines contribute to insulin resistance in active acromegaly and respond differently to different treatment modalities

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  • 1 Section of Specialized Endocrinology, Research Institute for Internal Medicine, Department of Internal Medicine and Endocrinology, Faculty of Medicine, Department of Endocrinology

Background

Active acromegaly is associated with insulin resistance, but it is uncertain whether inflammation in adipose tissue is a contributing factor.

Aim

To test if GH/IGF1 promotes inflammation in adipocytes, and if this is relevant for systemic insulin resistance in acromegaly. Furthermore, to investigate the effect of treatment modalities (transsphenoidal surgery (TS), somatostatin analogs (SAs), and pegvisomant (PGV)) on glucose metabolism and inflammatory biomarkers in acromegaly.

Methods

The in vitro effects of GH/IGF1 on gene expression of adipokines in human adipocytes were investigated. Body composition, glucose metabolism, and circulating adipokines (adiponectin (AD), high-molecular weight AD (HMWAD), leptin, vascular endothelial growth factor-A (VEGF-A), monocyte chemotactic protein 1 (MCP1), and thioredoxin (TRX)) were measured in 37 patients with active acromegaly before and after treatment.

Results

In vitro GH, but not IGF1, increased VEGF and MCP1 in human adipocytes. In all treatment groups, body fat increased and IGF1 decreased to the same extent. Fasting glucose decreased in the TS (P=0.016) and PGV (P=0.042) groups, but tended to increase in the SA group (P=0.078). Insulin and HOMA-IR decreased in both TS and SA groups, while the PGV group showed no changes. Serum VEGF and MCP1 decreased significantly in the TS group only (P=0.010, P=0.002), while HMWAD increased with PGV treatment only (P=0.018). A multivariate analysis model identified the changes in GH and VEGF as predictors of improvement in HOMA-IR after treatment (R2=0.39, P=0.002).

Conclusions

i) GH directly promotes inflammation of human adipocytes by increasing VEGF and MCP1 levels; ii) glucose metabolism and inflammation (VEGF and MCP1) improve to some extent after treatment, despite an increase in adipose tissue mass; and iii) the decrease in insulin resistance after therapy in acromegaly depends, to some extent, on treatment modalities.

Abstract

Background

Active acromegaly is associated with insulin resistance, but it is uncertain whether inflammation in adipose tissue is a contributing factor.

Aim

To test if GH/IGF1 promotes inflammation in adipocytes, and if this is relevant for systemic insulin resistance in acromegaly. Furthermore, to investigate the effect of treatment modalities (transsphenoidal surgery (TS), somatostatin analogs (SAs), and pegvisomant (PGV)) on glucose metabolism and inflammatory biomarkers in acromegaly.

Methods

The in vitro effects of GH/IGF1 on gene expression of adipokines in human adipocytes were investigated. Body composition, glucose metabolism, and circulating adipokines (adiponectin (AD), high-molecular weight AD (HMWAD), leptin, vascular endothelial growth factor-A (VEGF-A), monocyte chemotactic protein 1 (MCP1), and thioredoxin (TRX)) were measured in 37 patients with active acromegaly before and after treatment.

Results

In vitro GH, but not IGF1, increased VEGF and MCP1 in human adipocytes. In all treatment groups, body fat increased and IGF1 decreased to the same extent. Fasting glucose decreased in the TS (P=0.016) and PGV (P=0.042) groups, but tended to increase in the SA group (P=0.078). Insulin and HOMA-IR decreased in both TS and SA groups, while the PGV group showed no changes. Serum VEGF and MCP1 decreased significantly in the TS group only (P=0.010, P=0.002), while HMWAD increased with PGV treatment only (P=0.018). A multivariate analysis model identified the changes in GH and VEGF as predictors of improvement in HOMA-IR after treatment (R2=0.39, P=0.002).

Conclusions

i) GH directly promotes inflammation of human adipocytes by increasing VEGF and MCP1 levels; ii) glucose metabolism and inflammation (VEGF and MCP1) improve to some extent after treatment, despite an increase in adipose tissue mass; and iii) the decrease in insulin resistance after therapy in acromegaly depends, to some extent, on treatment modalities.

Introduction

Elevated fasting glucose levels, insulin resistance, and overt type 2 diabetes are common features of patients with active acromegaly (1). Lipolysis and increased levels of free fatty acids (FFAs), impairment of insulin signaling, and changes in adipokines and inflammation in adipose tissue are considered as potential underlying mechanisms (2, 3).

The most reproducible direct metabolic effect of growth hormone (GH) is stimulation of lipolysis and release of FFAs. The increased FFAs may affect insulin sensitivity by competition with glucose for substrate oxidation, impairment of insulin signaling, altering β-cell function, or triggering monocyte–macrophage accumulation in adipose tissue (2, 4, 5). Further, GH directly alters the insulin signal cascade activity in mice, but studies on humans have not supported these observations (6, 7, 8). Data regarding the effects of GH on circulating adipokines in human subjects are sparse and the results often contrast those obtained from animal models (9). Dysfunctional adipose tissue is recognized as a substantial contributor to general insulin resistance either by its own insulin-resistant state or, more significantly, by endocrine cross-talk with the tissues involved in glucose metabolism (10). Thus, several adipocyte-derived mediators play a central role in the regulation of insulin sensitivity, via their impact on inflammation and immunity (11, 12).

We have recently shown that serum levels of NAMPT – a known inflammatory cytokine – are elevated in acromegaly and that GH increases NAMPT expression in mature human adipocytes. Further, we suggested a pathogenic role of this adipokine in adipose tissue inflammation (3).

Different treatment modalities may impact glucose metabolism differently in acromegaly (13). For example, in addition to the central effect of somatostatin analogs (SAs), a direct effect was described in the periphery on key organs for glucose homeostasis (14, 15, 16, 17). Moreover, pegvisomant (PGV) acts as a specific GH antagonist, thus being considered an insulin sensitizer (18).

Based on the relationship between inflammation in adipose tissue and insulin resistance, we hypothesized that GH induces production of inflammatory adipokines, which relates to a systemic insulin resistance present in active acromegaly. Moreover, we speculated that glucose metabolism and circulating inflammatory markers change after therapy in a manner that depends on the treatment modality. We aimed to: i) quantify the in vitro effects of GH/insulin-like growth factor 1 (IGF1) on selected inflammatory adipokines in human mature adipocytes; ii) evaluate the association of these adipokines with glucose metabolism parameters in patients with acromegaly; and iii) examine the effect of different treatment modalities on inflammation and insulin resistance in active acromegaly.

Subjects and methods

Subjects

Thirty-seven patients diagnosed with active acromegaly (18 females and 19 males) were investigated prospectively. The diagnosis of acromegaly was based on clinical evaluation, elevated IGF1 levels, and a failure to suppress GH during an oral glucose tolerance test, in accordance with international guidelines (19). The patients were treated with either transsphenoidal surgery (TS; n=14), SA (Sandostatin LAR; n=16), or PGV (n=7). The TS and SA patients were examined at the Section of Endocrinology, Rikshospitalet, Oslo University Hospital (Norway) as participants in a prospective randomized study (ClinicalTrials.gov Identifier: NCT00521300) (20), while the PGV patients were investigated in an open, non-randomized trial at Department of Internal Medicine and Endocrinology, Aarhus University Hospital (Denmark) (21), as previously described. The TS and SA patients were treatment naïve. Five of the PGV patients received treatment before inclusion (four had previous surgery and one patient was treated with PGV). A good response to treatment was arbitrarily defined as a 50% decrease in IGF1 levels.

The study was approved by the Local Ethical Committee and was conducted according to the Declaration of Helsinki. Informed consent was obtained from all patients.

Blood sampling and biochemical measurements

Blood samples were drawn in the morning and after an overnight fast, and serum was collected and stored at −80 °C. GH was measured by immunoassay and serum IGF1 was measured by RIA as previously described (22, 23). GH day curve represents the mean of five GH values measured during 1 day, every 2 h. Insulin was analyzed by RIA (Millipore Corporation, MO, USA). Serum levels of leptin, adiponectin (AD), high-molecular weight AD (HMWAD), and vascular endothelial growth factor-A (VEGF-A) were measured by enzyme immune-assays (EIA) (R&D systems, Minneapolis, MN, USA). Thioredoxin (TRX, Abnova, Taipei City, Taiwan) and monocyte chemotactic protein 1 (MCP1; Peprotech, Rocky Hill, NJ, USA) were measured by EIA. Intra- and inter-assay coefficients of variation were <10% for all assays. Insulin resistance (HOMA-IR) and insulin secretion (HOMA-β) were calculated based on fasting insulin and glucose levels using the HOMA2 Calculator (24).

Body composition

Bone mineral density and body composition were measured by dual-energy X-ray absorptiometry as described previously (22). Bioelectrical impedance analysis (BIA) was performed in PGV patients as described previously (21).

Cell cultures

Human subcutaneous (SC; donor no. 16344 and lot no. 7F4245) and visceral (VA; donor no. 14324 and lot no. 6F3501) preadipocytes culture media and differentiation factors were purchased from Lonza Walkersville, Inc. (MD, USA). Preadipocytes were differentiated to mature adipocytes using differentiation media (PBM-2 with 10% FCS, 2 mM glutamine, 100 UI/ml penicillin, 100 μg/ml streptomycin, 0.5 μM insulin, 0.1 μM dexamethasone, 50 μM indomethacin, and 0.5 mM isobutyl-1-methylxanthine) for 14 days, as described previously (3). Differentiated adipocytes were washed twice with PBS, cultured overnight without FCS, and then stimulated with GH and IGF1 (100 and 500 ng/ml, R&D systems) for 3 and 12 h respectively.

In a separate set of experiments, mature SC adipocytes were stimulated for 3 h with GH (100 ng/ml) with or without the addition of the GH receptor antibody (GHRAb) (10 μg/ml, R&D systems).

In all experiments, culture media was collected and cells were harvested at the indicated time points using QIAzol lysis reagent (Qiagen).

Real-time quantitative PCR

Total RNA was isolated as described (3). For real-time PCR analyses, sequence-specific oligonucleotide primers that cross the exon–exon junction of the cDNA for VEGF (forward primer (FP), TCATCACGAAGTGGTGAAGTTCAT; reverse primer (RP), ATCAGGGTACTCCTGGAAGATGTC), MCP1 (FP, AAGCTGTGATCTTCAAGACCATTGT; RP, TGGAATCCTGAACCCACTTCTG), β-actin (FP, AGGCACCAGGGCGTGAT; RP, TCGTCCCAGTTGGTGACGAT), and glyceraldehyde-3-phosphate dehydrogenase (GAPDH; FP, CCAAGGTCATCCATGACAACTT; RP, AGGGGCCATCCACAGTCTT) were designed using Primer Express Software, version 2.0 (Applied Biosystems). Gene expression for IL1β, IL1Ra, PAI1, TNFα, IL6, IL8, TWEAK, Resistin, CCL3, CCL4, CCL5, CXCL1, CXCL12, and CX3CL were also measured. The sequence-specific primers are available upon request. A SYBR Green assay was performed using the qPCR Master Mix for SYBR Green I (Eurogentec, Seraing, Belgium). mRNA was quantified using the standard curve method of the ABI Prism 7500 (Applied Biosystems). Data were normalized to β-actin or GAPDH (reference genes).

Statistical analysis

One-way ANOVA was performed to asses the total variability of an in vitro group data. Further, unpaired student's sample t-test (two-tailed) was used to evaluate the differences between control and stimulated cells.

All the measurements were checked for normal distribution by visual methods (histograms and Q–Q plots) and further log-transformed if necessary. Data are presented as mean±s.d. or median (IQR).

To compare the variables before and after treatment (within-group differences), the Wilcoxon' match-pair test was performed. The Mann–Whitney U test was used to compare the changes between good responders and poor responders in the same group. The Kruskal–Wallis test with adjustment for multiple comparisons was used to compare the changes between three different treatment groups (between group differences).

Univariate correlation analysis was used to determine independent associations between variables. In addition, to determine the independent predictors of HOMA-IR change during the different treatment modalities, a subsequent multiple linear regression analysis was performed with inclusion of the variables that had a P value below 0.10 in the univariate analysis. All the statistical calculations were performed with SPPSS, version 18. P values were two-tailed and considered significant when <0.05.

Results

In vitro effect of GH/IGF1 on human adipocytes

Based on the hypothesis that GH promotes inflammation in the adipocytes, we investigated the in vitro effect of GH and IGF1 on gene expression of selected adipokines. We identified that GH increased VEGF and MCP1 expression in human mature adipocytes, while neither GH nor IGF1 regulated the expression of IL1β, IL1Ra, PAI1, TNFα, IL6, IL8, TWEAK, Resistin, CCL3, CCL4, CCL5, CXCL1, CXCL12, and CX3CL in SC adipocytes (data not shown). As shown in Fig. 1, GH increased VEGF and MCP1 expression levels at 3 and 12 h respectively, both in the SC and in VA adipocytes. In contrast to GH, no consistent effect was observed with IGF1. Further, when SC adipocytes were stimulated for 3 h with GH in the presence of GHRAb, the increase in VEGF was partially abrogated (Fig. 1C) and the increase in MCP1 was totally prevented (Fig. 1F), suggesting a direct effect of GH on induction of these cytokines.

Figure 1
Figure 1

Effects of GH/IGF1 on VEGF (A, B and C) and MCP1 (D, E and F) expression in human SC (A, C, D and F) and VA (B and E) adipocytes. SC and VA were differentiated for 14 days, overnight FCS starved, and stimulated with GH (100 and 500 ng/ml), IGF1 (100 and 500 ng/ml) for 3 and 12 h and with GH (100 ng/ml) and GHRAb (10 μg/ml) for 3 h. GH dose dependently increased VEGF (A and B) and MCP1 (D and E) expression in SC (A and D) and VA (B and E) at 3 and 12 h. IGF1 presented no consistent effect. Further, the incubation of SC with GH and GHRAb prevented the GH-induced VEGF and MCP1 gene expression (C and F). Data are mean±s.e.m. (n=4; US, unstimulated; *P<0.05, **P<0.01, and ***P<0.001 vs unstimulated control, unpaired Student's sample t-test (two-tailed)).

Citation: European Journal of Endocrinology 170, 1; 10.1530/EJE-13-0523

Study population

Table 1 shows the main baseline demographics, body composition, and biochemical variables of the study populations, as a whole and stratified by the different treatments. At baseline, total body fat mass correlated positively with VEGF (r=0.38, P=0.026), leptin (r=0.86, P<0.001), insulin (r=0.59, P<0.001), and HOMA-IR (r=0.60, P<0.001) and negatively with GH (r=−0.60, P<0.001). Total body lean mass was correlated negatively with HMWAD (r=−0.61, P=0.001), AD (r=−0.43, P=0.034), and leptin (r=−0.50, P=0.007).

Table 1

Clinical and biochemical characteristics of patients before and after treatment.

AllTSSAPGV
BasalAfterPBasalAfterPBasalAfterPBasalAfterP
n3714167
Age (years)48±1147±1049±1148±14
Sex, male/female (n)19/185/99/75/2
BMI (kg/m2)27.9±3.828.0±4.20.36029.0±4.8 29.6±5.2 0.04627.0±3.1 27.0±3.2 0.34727.3 (7.1)26.7 (6.7)0.018
Body composition
 Total body fat (kg)19.5±10.123.5±11.2<0.00120.6 (18.9)26.7 (19.5)0.00218.5±10.3 21.8±10.10.00116.8 (22.7)a19.9 (13.6)a0.091
 Total body lean (kg)61.0±13.657.1±12.3<0.001 57.0 (19.7)54.2±12.00.00163.1±13.8 60.6 (21.5)<0.001
Biochemistry
 GH (μg/l)b26.3 (34.3)3.6 (10.3)<0.001 20.3 (34.3)1.7 (9.9)0.00433.5 (42.8)5.1 (24.6)<0.001NDND
 GH–OGTT (μg/l)c6.5 (8.6)0.49 (2.4)<0.001 6.0 (9.4)0.37 (2.3)0.0167.6 (9.6)1.0 (6.6)0.001NDND
 IGF1 (nM/l)87.8±26.641.8±23.6<0.001 80.5±22.131.5 (22) 0.00185.8±22.448.2±30.90.001104.0 (74)44.0 (22)0.018
 IGF1 (% ULN)216 (95)88 (81)<0.001 207 (95)70 (62) 0.001213 (111)92 (113)0.001336±140129 (68)0.018
 Good responsed24 (65%)10 (71%)8 (50%)6 (86%)
Glucose metabolism
 Glucose (mM/l)5.8±0.75.7±0.90.3645.7±0.75.0 (0.9)0.0165.6 (1.3)6.2±1.00.0785.5 (0.6)5.4 (0.6)0.042
 Insulin (μUI/ml)26.7 (15.8)13.9 (12.8)<0.001 31.1 (28.8)12.7 (13.4)0.00227.2±9.220.3±12.40.02017.3 (17.1)15.7 (22.7)1.00
 HOMA-IR3.1 (1.7)1.6 (1.5)<0.001 3.4 (3.2)1.4 (1.4)0.0023.1 (1.5)2.4±1.50.0202.0 (1.9)1.7 (2.4)1.00
 HOMA-β149 (105)116 (52)<0.001 216 (130)120 (60)0.003140 (81)105.3±30.30.002130.8±58.4140 (109)0.499
Adipokines
 AD (μg/ml)11.9±4.511.0±4.80.27012.3 (8.9)6.4 (11.1)0.03712.1 (7.5)12.5 (7.6)1.008.3 (6.5)10.4 (8.0)0.310
 HMWAD (μg/ml)6.2±3.46.4±3.00.3766.3 (5.5)3.7 (5.0)0.1365.8 (4.8)7.4±2.90.2154.9±2.15.7 (4.4)0.018
 HMWAD:AD ratio0.54±0.160.61±0.150.0300.51±0.210.63±0.200.1390.56±0.150.62±0.130.1120.52±0.140.55±0.100.499
 Leptin (μg/ml)8.0 (21.6)9.1 (23.5)0.31821.5 (20.6)19.2 (27.0)0.7543.7 (18.6)7.3 (15.4)0.0175.3 (37.6)5.0 (33.9)0.128
 VEGF (pg/ml)218 (309)224 (242)0.266391 (258)253 (198)0.010213 (276)236 (321)0.289104 (167)156±1040.799
 MCP1 (pg/ml)171±80136±560.001185 (100)125 (56)0.002182±94135 (84)0.121105 (45)91 (23)0.396
 TRX (ng/ml)23.1 (27.7)22.0 (14.8)0.00945.1±26.721.9 (19.7)0.01923.3 (29.3)25.5 (11.2)0.68323.0 (9.1)15.7 (9.7)0.063

BIA, bioelectrical impedance analysis; ND, not determined. Data are given as mean±s.d. or median (IQR); P values are within-group differences (Wilcoxon' match-pair test).

Total body fat is measured by BIA.

GH is presented as a mean of five values measured 1 day, every 2 h.

GH is presented as nadir value during OGTT.

Good response is defined as an IGF1 decrease by at least 50%.

In the entire cohort of patients, total body fat mass increased (3.5 (5.6) kg, P≤0.001) while total body lean mass decreased (3.2 (3.8) kg, P≤0.001) following treatment. Glucose metabolism variables (insulin, HOMA-IR, and HOMA-β) improved, together with a significant increase in the HMWAD:AD ratio and a significant decrease in MCP1 and TRX levels (Table 1). No significant changes were observed in the fasting glucose, AD, HMWAD, leptin, or VEGF levels (Table 1).

Regardless of treatment modality, IGF1 decreased and total body fat increased to the same extent in all the groups (Fig. 2A and B). However, fasting glucose decreased in the TS and PGV groups, and tended to increase in the SA group (Table 1). Insulin, HOMA-IR, and HOMA-β decreased in both the TS and SA groups, but not in the PGV group (Table 1, Fig. 2C and D). In the TS group, AD, VEGF, MCP1, and TRX decreased significantly. In the SA group leptin increased, while in the PGV group HMWAD increased significantly (Table 1).

Figure 2
Figure 2

Changes in biochemical variables and total body fat during treatments (TS (white square), SA (dark gray square), and PGV (light gray square)). IGF1 decreased (A) and total body fat increased (B) to the same extent in all the groups. Glucose decreased in the TS and PGV groups, and tended to increase in the SA group (C). HOMA-IR decreased in both the TS and SA groups, but not in the PGV group (D). P values are between-group differences in change from baseline to 12 months (TS), 6 months (SA), and 1 month (PGV) (Kruskal–Wallis test with multiple comparison adjustment). Data are presented as mean±min/max values.

Citation: European Journal of Endocrinology 170, 1; 10.1530/EJE-13-0523

Disease activity after treatment predicts improvement in glucose and inflammatory markers

The next step was to identify if the treatment response correlated with changes in selected biomarkers of inflammation and glucose metabolism. The patients were divided into good and poor responders based on the decrease in IGF1 levels following treatment (Fig. 3A). A normalization of IGF1 levels is expected when the optimal PGV treatment is used. However, one patient in the PGV group was considered as a poor responder based on a decrease in IGF1 by only 46.9%. Consequently, we did not perform statistical analysis between good and poor responders in the PGV group. The increase in body fat and the changes in MCP1 were similar between good responders and poor responders (Fig. 3B and E). Insulin (data not shown) and HOMA-IR (Fig. 3C) were improved in the TS group independent of treatment response and in good responders SA, and remained unchanged in poor responders SA. Moreover, in poor responders SA, an increase in serum VEGF was observed (Fig. 3D).

Figure 3
Figure 3

Different response between good and poor responders during treatments (TS (white square), SA (dark gray square), and PGV (light gray square)). The patients were divided as good responders (a decrease of ≥50% in IGF1) or poor responders (a decrease of <50% in IGF1). (A). Total body fat (B) and MCP1 (E) changed similar between good responders and poor responders in the TS and SA groups. Changes in HOMA-IR (C), VEGF (D) and TRX (F) differed between good responders and poor responders in the SA group. TS group, good responders (n=10) and poor responders (n=4); SA group, good responders (n=8) and poor responders (n=8); PGV group, good responders (n=6) and poor responders (n=1). Data are presented as mean±min/max values. P values are between-group differences in change from baseline to 12 months (TS), 6 months (SA), and 1 month PGV (Kruskal–Wallis test with multiple comparison adjustment). P values (#P<0.05, ##P<0.01, and ###P<0.001) are within-group differences in change between good and poor responders (Mann–Whitney U test). Statistical measurement of within-group differences for PGV group was not performed.

Citation: European Journal of Endocrinology 170, 1; 10.1530/EJE-13-0523

Determinants of insulin resistance (HOMA-IR) change during treatment for acromegaly

In addition to a positive correlation with total body fat mass, HOMA-IR was also positively correlated with leptin (r=0.43, P=0.009) and VEGF (r=0.43, P=0.011) in the whole population study before treatment. HOMA-IR decreased significantly following treatment both with TS (55.7 (26) %, P=0.002) and SA (31.9 (56) %, P=0.02). HOMA-IR did not change significantly in the PGV group (Fig. 2D). We performed a univariate correlation analysis to determine independent associations between the changes in HOMA-IR, body composition, and circulating biomarkers in relation to treatment in acromegaly (Table 2). As expected, a decrease in disease activity as estimated by a decrease in GH levels and of total lean body mass was correlated with changes in HOMA-IR. The change in circulating VEGF was correlated with the change in HOMA-IR.

Table 2

Determinants of HOMA-IR change after treatment of acromegaly.

Univariate R (P if trend)Multiple linear regression β/P
Age0.15
Total fat BM−0.06
Total lean BM0.42 (0.024)0.30/0.079
GH0.58 (0.001)0.37/0.036
IGF10.33 (0.054)
AD0.33 (0.063)
HMWAD0.21
Leptin0.08
VEGF0.41 (0.016)0.35/0.032
MCP10.28
TRX0.13
TotalR2=0.39/0.002

BM, body mass; R2, adjusted.

Furthermore, a multiple regression analysis model identified the changes in GH and VEGF as positive predictors for the improvement of HOMA-IR after treatment (Table 2).

Discussion

In this study, we adopted an exploratory approach measuring gene expression of multiple cytokines expressed in human mature adipocytes and considered to potentially induce insulin resistance. We demonstrated that GH, but not IGF1, increased the gene expression of VEGF and MCP1, whereas the expression of several other cytokines was unaffected by both GH and IGF1. VEGF is the master regulator of angiogenesis, while MCP1 is a known cytokine that recruits monocytes, T cells, and dendritic cells at the site of inflammation (25, 26). Accumulation of an increased number of adipose tissue macrophages (and subsequently a chronic state of tissue inflammation) is an important cause of insulin resistance (11). Our in vitro results showing that GH directly increases VEGF and MCP1 in mature adipocytes support the hypothesis that by increasing the inflammatory potential of mature adipocytes, GH could promote insulin resistance in adipose tissue in active acromegaly. Sustained increases in VEGF levels have been shown to induce islet hypervascularization, fibrosis, and inflammation, resulting in β-cell death and hyperglycaemia indicating a direct role of VEGF in deteriorating glucose metabolism (27). Indeed, adipose tissue levels of VEGF have been demonstrated to correlate with the degree of insulin resistance in obesity (28). In accordance, our in vivo findings, showing a correlation between circulating VEGF and insulin resistance at baseline as well as following treatment in active acromegaly, suggest that this association is not necessarily dependent on fat mass but on the degree of inflammation in adipose tissue. This is supported by our data showing a significant decrease in insulin resistance following treatment of active acromegaly, despite an increase in total fat mass. Thus, the expansion of adipose tissue may not necessarily be regarded as a factor that deteriorate the insulin sensitivity, because normal functional adipose tissue protects against diabetes by acting, first and foremost, as a storage depot for FFA (29).

Previous studies have shown that some of the mechanisms involved in GH-induced impairment of glucose metabolism include increased lipolysis, FFAs and a downstream impairment of insulin signaling in rodent models (2). In addition, GH may directly enhance the inflammatory trait of adipose tissue that contributes and potentiates the development of insulin resistance (3). In acromegaly, macrophages and other immune cell types in adipose tissue are exposed to high local concentrations of FFAs released by GH-induced lipolysis. FFAs can potentially act as signals themselves and activate inflammation in macrophages by interacting with TLR4–NF-κB/JNK inflammatory signaling pathways (11). In this way, the adipose tissue's macrophages and other immune cells may express and exacerbate the response to the inflammatory signals in acromegaly.

We previously described that GH increases MCP1 in subcutaneous adipocytes through a mechanism dependent of NAMPT enzymatic activity (3). This study presented confirmatory and new data, which showed that visceral adipocytes also respond to GH stimulation in a similar way.

The most evident improvement in glucose/inflammatory parameters was observed in the TS group. In the SA group, fasting glucose showed an increasing tendency, together with the improvement in insulin, HOMA-IR, and HOMA-β. Previously, it has been shown that SAs may lower glucose tolerance due to suppression of pancreatic insulin secretion, but improve insulin sensitivity by lowering GH levels (13, 30, 31, 32). Indeed, the improvement in glucose metabolism in the SA group in our study seems to be associated with a good response to treatment. A surprising finding was that in poor responders SA, but not TS, an increase in circulating VEGF levels was observed. This is probably not to be explained by a direct effect of SAs on peripheral tissues as different studies showed that somatosatin analogs present anti-VEGF properties in different tumor models (33). Rather, the observed increase in VEGF levels in these patients may represent an indirect effect, due to a persistence of increased levels of GH and active disease.

TRX is induced and secreted by a variety of oxidative stresses and shows protective functions against oxidative stress. Serum/plasma TRX levels are good markers for oxidative stresses in various disorders. TRX levels are increased in different acute inflammatory states (myocarditis, viral infection, and HIV) or cancer (34). Serum TRX levels decreased significantly following TS and showed a decreasing trend in the PGV group, probably because of a decrease in the oxidative stress and consecutively due to a decreased demand for an anti-oxidative protein, but remained unchanged in the SA group. Taken together, our results showed that despite an improvement in insulin resistance and an increase in leptin levels (probably as a consequence of a partial control of disease activity), the patients in the SA group exhibited unchanged circulating levels of additional adipokines.

In this study, we did not find an amelioration of insulin sensitivity, estimated by HOMA-IR in the PGV group, although we previously showed that treatment with PGV improved insulin sensitivity in these patients as measured by euglycemic–hyperinsulinemic clamp (21). HOMA-IR is derived from fasting glucose and insulin levels and reflects primarily basal hepatic insulin sensitivity (24). By contrast, the hyperinsulinemic clamp reflects insulin-stimulated glucose disposal predominantly into skeletal muscle (35). It is therefore likely that four weeks' treatment with PGV mainly improved insulin sensitivity in the skeletal muscle (21). Alternatively, the lack of a significant improvement in HOMA-IR in our study could be due to a type 2 error.

An increase in HMWAD levels, independent of changes in glucose metabolism, was observed in the PGV group. This suggests that the increase in HMWAD is a direct effect of blocking the GH receptor and not a secondary result due to the changes in insulin sensitivity. Our findings are supported by a study that describes the increased levels of HMWAD in mouse lacking GH receptor (36). Given our results, it may be interesting to study if GH modulates disulfide bond A oxidoreductase-like protein (DsbA-L), a recently described protein that promotes AD multimerization (37). HMWAD is thought to be the most biologically active form of AD in terms of glucose homeostasis. High levels of total AD and HMWAD were associated with a lower incidence of diabetes and peripheral artery disease (38, 39). Furthermore, we observed that the addition of GHRAb prevented the GH increase in VEGF and MCP1 in mature adipocytes. This indicates that the decrease of inflammation in adipose tissue may represent an additional mechanism to explain the insulin sensitizer properties of PGV.

The main limitation of our study is the limited number of patients in the different treatment modalities and different duration of treatment in these groups. However, the duration of treatment seems of minor concern as the decrease in IGF1 levels and the increase in body fat were similar between different treatment modalities. The peculiar increase in VEGF in poor responders treated with SA is difficult to explain, and further studies with a higher number of patients are needed before a definitive conclusion is made. The in vitro studies are limited by the use of preadipocytes from different donors and the possible associated variability.

In summary, this study together with our previous results demonstrate that GH directly increases the inflammatory phenotype of human mature adipocytes, indicating a possible contribution of adipose tissue to the systemic insulin resistance in active acromegaly. The improvement of systemic insulin resistance depended to some extent upon treatment modality and was predicted by a decrease in GH and VEGF circulating levels.

Declaration of interest

N C Olarescu, T Ueland, K Godang, and R Lindberg-Larsen have nothing to declare. J Bollerslev received unrestricted research grants from Pfizer and Novartis and served as an advisory board member for Pfizer. J O L Jørgensen received unrestricted research grants from Pfizer, Novartis, and IPSEN and serves as an advisory board member for Pfizer. None of the authors have conflicts of interest.

Funding

The study was supported by an unrestricted research grant from Pfizer, Inc.

References

  • 1

    Melmed S. Medical progress: acromegaly. New England Journal of Medicine 2006 355 25582573. (doi:10.1056/NEJMra062453).

  • 2

    Moller N, Jorgensen JO. Effects of growth hormone on glucose, lipid, and protein metabolism in human subjects. Endocrine Reviews 2009 30 152177. (doi:10.1210/er.2008-0027).

    • Search Google Scholar
    • Export Citation
  • 3

    Olarescu NC, Ueland T, Lekva T, Dahl TB, Halvorsen B, Aukrust P, Bollerslev J. Adipocytes as a source of increased circulating levels of nicotinamide phosphoribosyltransferase/visfatin in active acromegaly. Journal of Clinical Endocrinology and Metabolism 2012 97 13551362. (doi:10.1210/jc.2011-2417).

    • Search Google Scholar
    • Export Citation
  • 4

    Yeop HC, Kargi AY, Omer M, Chan CK, Wabitsch M, O'Brien KD, Wight TN, Chait A. Differential effect of saturated and unsaturated free fatty acids on the generation of monocyte adhesion and chemotactic factors by adipocytes: dissociation of adipocyte hypertrophy from inflammation. Diabetes 2010 59 386396. (doi:10.2337/db09-0925).

    • Search Google Scholar
    • Export Citation
  • 5

    Samuel VT, Petersen KF, Shulman GI. Lipid-induced insulin resistance: unravelling the mechanism. Lancet 2010 375 22672277. (doi:10.1016/S0140-6736(10)60408-4).

    • Search Google Scholar
    • Export Citation
  • 6

    del Rincon JP, Iida K, Gaylinn BD, McCurdy CE, Leitner JW, Barbour LA, Kopchick JJ, Friedman JE, Draznin B, Thorner MO. Growth hormone regulation of p85α expression and phosphoinositide 3-kinase activity in adipose tissue: mechanism for growth hormone-mediated insulin resistance. Diabetes 2007 56 16381646. (doi:10.2337/db06-0299).

    • Search Google Scholar
    • Export Citation
  • 7

    Takano A, Haruta T, Iwata M, Usui I, Uno T, Kawahara J, Ueno E, Sasaoka T, Kobayashi M. Growth hormone induces cellular insulin resistance by uncoupling phosphatidylinositol 3-kinase and its downstream signals in 3T3-L1 adipocytes. Diabetes 2001 50 18911900. (doi:10.2337/diabetes.50.8.1891).

    • Search Google Scholar
    • Export Citation
  • 8

    Krusenstjerna-Hafstrom T, Madsen M, Vendelbo MH, Pedersen SB, Christiansen JS, Moller N, Jessen N, Jorgensen JO. Insulin and GH signaling in human skeletal muscle in vivo following exogenous GH exposure: impact of an oral glucose load. PLoS ONE 2011 6 e19392. (doi:10.1371/journal.pone.0019392).

    • Search Google Scholar
    • Export Citation
  • 9

    Wabitsch M, Hauner H, Heinze E, Teller WM. The role of growth hormone/insulin-like growth factors in adipocyte differentiation. Metabolism 1995 44 4549. (doi:10.1016/0026-0495(95)90220-1).

    • Search Google Scholar
    • Export Citation
  • 10

    Olefsky JM, Glass CK. Macrophages, inflammation, and insulin resistance. Annual Review of Physiology 2010 72 219246. (doi:10.1146/annurev-physiol-021909-135846).

    • Search Google Scholar
    • Export Citation
  • 11

    Glass CK, Olefsky JM. Inflammation and lipid signaling in the etiology of insulin resistance. Cell Metabolism 2012 15 635645. (doi:10.1016/j.cmet.2012.04.001).

    • Search Google Scholar
    • Export Citation
  • 12

    Tilg H, Moschen AR. Adipocytokines: mediators linking adipose tissue, inflammation and immunity. Nature Reviews. Immunology 2006 6 772783. (doi:10.1038/nri1937).

    • Search Google Scholar
    • Export Citation
  • 13

    Sherlock M, Woods C, Sheppard MC. Medical therapy in acromegaly. Nature Reviews. Endocrinology 2011 7 291300. (doi:10.1038/nrendo.2011.42).

  • 14

    Krusenstjerna-Hafstrom T, Vestergaard ET, Buhl M, Nielsen R, Clasen BF, Nielsen S, Moller N, Pedersen SB, Jorgensen JO. Acute peripheral metabolic effects of intraarterial leg infusion of somatostatin in healthy young men. Journal of Clinical Endocrinology and Metabolism 2011 96 25812589. (doi:10.1210/jc.2011-0592).

    • Search Google Scholar
    • Export Citation
  • 15

    Moller N, Bagger JP, Schmitz O, Jorgensen JO, Ovesen P, Moller J, Alberti KG, Orskov H. Somatostatin enhances insulin-stimulated glucose uptake in the perfused human forearm. Journal of Clinical Endocrinology and Metabolism 1995 80 17891793. (doi:10.1210/jc.80.6.1789).

    • Search Google Scholar
    • Export Citation
  • 16

    Alberti KG, Christensen NJ, Christensen SE, Hansen AP, Iversen J, Lundbaek K, Seyer-Hansen K, Orskov H. Inhibition of insulin secretion by somatostatin. Lancet 1973 2 12991301. (doi:10.1016/S0140-6736(73)92873-0).

    • Search Google Scholar
    • Export Citation
  • 17

    Pokrajac A, Frystyk J, Flyvbjerg A, Trainer PJ. Pituitary-independent effect of octreotide on IGF1 generation. European Journal of Endocrinology 2009 160 543548. (doi:10.1530/EJE-08-0822).

    • Search Google Scholar
    • Export Citation
  • 18

    Drake WM, Rowles SV, Roberts ME, Fode FK, Besser GM, Monson JP, Trainer PJ. Insulin sensitivity and glucose tolerance improve in patients with acromegaly converted from depot octreotide to pegvisomant. European Journal of Endocrinology 2003 149 521527. (doi:10.1530/eje.0.1490521).

    • Search Google Scholar
    • Export Citation
  • 19

    Giustina A, Barkan A, Casanueva FF, Cavagnini F, Frohman L, Ho K, Veldhuis J, Wass J, Von Werder K, Melmed S. Criteria for cure of acromegaly: a consensus statement. Journal of Clinical Endocrinology and Metabolism 2000 85 526529. (doi:10.1210/jc.85.2.526).

    • Search Google Scholar
    • Export Citation
  • 20

    Carlsen SM, Lund-Johansen M, Schreiner T, Aanderud S, Johannesen O, Svartberg J, Cooper JG, Hald JK, Fougner SL, Bollerslev J. Preoperative octreotide treatment in newly diagnosed acromegalic patients with macroadenomas increases cure short-term postoperative rates: a prospective, randomized trial. Journal of Clinical Endocrinology and Metabolism 2008 93 29842990. (doi:10.1210/jc.2008-0315).

    • Search Google Scholar
    • Export Citation
  • 21

    Lindberg-Larsen R, Moller N, Schmitz O, Nielsen S, Andersen M, Orskov H, Jorgensen JO. The impact of pegvisomant treatment on substrate metabolism and insulin sensitivity in patients with acromegaly. Journal of Clinical Endocrinology and Metabolism 2007 92 17241728. (doi:10.1210/jc.2006-2276).

    • Search Google Scholar
    • Export Citation
  • 22

    Ueland T, Fougner SL, Godang K, Schreiner T, Bollerslev J. Serum GH and IGF-I are significant determinants of bone turnover but not bone mineral density in active acromegaly: a prospective study of more than 70 consecutive patients. European Journal of Endocrinology 2006 155 709715. (doi:10.1530/eje.1.02285).

    • Search Google Scholar
    • Export Citation
  • 23

    Jorgensen JO, Feldt-Rasmussen U, Frystyk J, Chen JW, Kristensen LO, Hagen C, Orskov H. Cotreatment of acromegaly with a somatostatin analog and a growth hormone receptor antagonist. Journal of Clinical Endocrinology and Metabolism 2005 90 56275631. (doi:10.1210/jc.2005-0531).

    • Search Google Scholar
    • Export Citation
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    Wallace TM, Levy JC, Matthews DR. Use and abuse of HOMA modeling. Diabetes Care 2004 27 14871495. (doi:10.2337/diacare.27.6.1487).

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    Hursting SD, Hursting MJ. Growth signals, inflammation, and vascular perturbations: mechanistic links between obesity, metabolic syndrome, and cancer. Arteriosclerosis, Thrombosis, and Vascular Biology 2012 32 17661770. (doi:10.1161/ATVBAHA.111.241927).

    • Search Google Scholar
    • Export Citation
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    Dahlman I, Kaaman M, Olsson T, Tan GD, Bickerton AS, Wahlen K, Andersson J, Nordstrom EA, Blomqvist L, Sjogren A. A unique role of monocyte chemoattractant protein 1 among chemokines in adipose tissue of obese subjects. Journal of Clinical Endocrinology and Metabolism 2005 90 58345840. (doi:10.1210/jc.2005-0369).

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    Agudo J, Ayuso E, Jimenez V, Casellas A, Mallol C, Salavert A, Tafuro S, Obach M, Ruzo A, Moya M. Vascular endothelial growth factor-mediated islet hypervascularization and inflammation contribute to progressive reduction of β-cell mass. Diabetes 2012 61 28512861. (doi:10.2337/db12-0134).

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    Tinahones FJ, Coin-Araguez L, Mayas MD, Garcia-Fuentes E, Hurtado-Del-Pozo C, Vendrell J, Cardona F, Calvo RM, Obregon MJ, El Bekay R. Obesity-associated insulin resistance is correlated to adipose tissue vascular endothelial growth factors and metalloproteinase levels. BMC Physiology 2012 12 4. (doi:10.1186/1472-6793-12-4).

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    • Export Citation
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  • View in gallery

    Effects of GH/IGF1 on VEGF (A, B and C) and MCP1 (D, E and F) expression in human SC (A, C, D and F) and VA (B and E) adipocytes. SC and VA were differentiated for 14 days, overnight FCS starved, and stimulated with GH (100 and 500 ng/ml), IGF1 (100 and 500 ng/ml) for 3 and 12 h and with GH (100 ng/ml) and GHRAb (10 μg/ml) for 3 h. GH dose dependently increased VEGF (A and B) and MCP1 (D and E) expression in SC (A and D) and VA (B and E) at 3 and 12 h. IGF1 presented no consistent effect. Further, the incubation of SC with GH and GHRAb prevented the GH-induced VEGF and MCP1 gene expression (C and F). Data are mean±s.e.m. (n=4; US, unstimulated; *P<0.05, **P<0.01, and ***P<0.001 vs unstimulated control, unpaired Student's sample t-test (two-tailed)).

  • View in gallery

    Changes in biochemical variables and total body fat during treatments (TS (white square), SA (dark gray square), and PGV (light gray square)). IGF1 decreased (A) and total body fat increased (B) to the same extent in all the groups. Glucose decreased in the TS and PGV groups, and tended to increase in the SA group (C). HOMA-IR decreased in both the TS and SA groups, but not in the PGV group (D). P values are between-group differences in change from baseline to 12 months (TS), 6 months (SA), and 1 month (PGV) (Kruskal–Wallis test with multiple comparison adjustment). Data are presented as mean±min/max values.

  • View in gallery

    Different response between good and poor responders during treatments (TS (white square), SA (dark gray square), and PGV (light gray square)). The patients were divided as good responders (a decrease of ≥50% in IGF1) or poor responders (a decrease of <50% in IGF1). (A). Total body fat (B) and MCP1 (E) changed similar between good responders and poor responders in the TS and SA groups. Changes in HOMA-IR (C), VEGF (D) and TRX (F) differed between good responders and poor responders in the SA group. TS group, good responders (n=10) and poor responders (n=4); SA group, good responders (n=8) and poor responders (n=8); PGV group, good responders (n=6) and poor responders (n=1). Data are presented as mean±min/max values. P values are between-group differences in change from baseline to 12 months (TS), 6 months (SA), and 1 month PGV (Kruskal–Wallis test with multiple comparison adjustment). P values (#P<0.05, ##P<0.01, and ###P<0.001) are within-group differences in change between good and poor responders (Mann–Whitney U test). Statistical measurement of within-group differences for PGV group was not performed.

  • 1

    Melmed S. Medical progress: acromegaly. New England Journal of Medicine 2006 355 25582573. (doi:10.1056/NEJMra062453).

  • 2

    Moller N, Jorgensen JO. Effects of growth hormone on glucose, lipid, and protein metabolism in human subjects. Endocrine Reviews 2009 30 152177. (doi:10.1210/er.2008-0027).

    • Search Google Scholar
    • Export Citation
  • 3

    Olarescu NC, Ueland T, Lekva T, Dahl TB, Halvorsen B, Aukrust P, Bollerslev J. Adipocytes as a source of increased circulating levels of nicotinamide phosphoribosyltransferase/visfatin in active acromegaly. Journal of Clinical Endocrinology and Metabolism 2012 97 13551362. (doi:10.1210/jc.2011-2417).

    • Search Google Scholar
    • Export Citation
  • 4

    Yeop HC, Kargi AY, Omer M, Chan CK, Wabitsch M, O'Brien KD, Wight TN, Chait A. Differential effect of saturated and unsaturated free fatty acids on the generation of monocyte adhesion and chemotactic factors by adipocytes: dissociation of adipocyte hypertrophy from inflammation. Diabetes 2010 59 386396. (doi:10.2337/db09-0925).

    • Search Google Scholar
    • Export Citation
  • 5

    Samuel VT, Petersen KF, Shulman GI. Lipid-induced insulin resistance: unravelling the mechanism. Lancet 2010 375 22672277. (doi:10.1016/S0140-6736(10)60408-4).

    • Search Google Scholar
    • Export Citation
  • 6

    del Rincon JP, Iida K, Gaylinn BD, McCurdy CE, Leitner JW, Barbour LA, Kopchick JJ, Friedman JE, Draznin B, Thorner MO. Growth hormone regulation of p85α expression and phosphoinositide 3-kinase activity in adipose tissue: mechanism for growth hormone-mediated insulin resistance. Diabetes 2007 56 16381646. (doi:10.2337/db06-0299).

    • Search Google Scholar
    • Export Citation
  • 7

    Takano A, Haruta T, Iwata M, Usui I, Uno T, Kawahara J, Ueno E, Sasaoka T, Kobayashi M. Growth hormone induces cellular insulin resistance by uncoupling phosphatidylinositol 3-kinase and its downstream signals in 3T3-L1 adipocytes. Diabetes 2001 50 18911900. (doi:10.2337/diabetes.50.8.1891).

    • Search Google Scholar
    • Export Citation
  • 8

    Krusenstjerna-Hafstrom T, Madsen M, Vendelbo MH, Pedersen SB, Christiansen JS, Moller N, Jessen N, Jorgensen JO. Insulin and GH signaling in human skeletal muscle in vivo following exogenous GH exposure: impact of an oral glucose load. PLoS ONE 2011 6 e19392. (doi:10.1371/journal.pone.0019392).

    • Search Google Scholar
    • Export Citation
  • 9

    Wabitsch M, Hauner H, Heinze E, Teller WM. The role of growth hormone/insulin-like growth factors in adipocyte differentiation. Metabolism 1995 44 4549. (doi:10.1016/0026-0495(95)90220-1).

    • Search Google Scholar
    • Export Citation
  • 10

    Olefsky JM, Glass CK. Macrophages, inflammation, and insulin resistance. Annual Review of Physiology 2010 72 219246. (doi:10.1146/annurev-physiol-021909-135846).

    • Search Google Scholar
    • Export Citation
  • 11

    Glass CK, Olefsky JM. Inflammation and lipid signaling in the etiology of insulin resistance. Cell Metabolism 2012 15 635645. (doi:10.1016/j.cmet.2012.04.001).

    • Search Google Scholar
    • Export Citation
  • 12

    Tilg H, Moschen AR. Adipocytokines: mediators linking adipose tissue, inflammation and immunity. Nature Reviews. Immunology 2006 6 772783. (doi:10.1038/nri1937).

    • Search Google Scholar
    • Export Citation
  • 13

    Sherlock M, Woods C, Sheppard MC. Medical therapy in acromegaly. Nature Reviews. Endocrinology 2011 7 291300. (doi:10.1038/nrendo.2011.42).

  • 14

    Krusenstjerna-Hafstrom T, Vestergaard ET, Buhl M, Nielsen R, Clasen BF, Nielsen S, Moller N, Pedersen SB, Jorgensen JO. Acute peripheral metabolic effects of intraarterial leg infusion of somatostatin in healthy young men. Journal of Clinical Endocrinology and Metabolism 2011 96 25812589. (doi:10.1210/jc.2011-0592).

    • Search Google Scholar
    • Export Citation
  • 15

    Moller N, Bagger JP, Schmitz O, Jorgensen JO, Ovesen P, Moller J, Alberti KG, Orskov H. Somatostatin enhances insulin-stimulated glucose uptake in the perfused human forearm. Journal of Clinical Endocrinology and Metabolism 1995 80 17891793. (doi:10.1210/jc.80.6.1789).

    • Search Google Scholar
    • Export Citation
  • 16

    Alberti KG, Christensen NJ, Christensen SE, Hansen AP, Iversen J, Lundbaek K, Seyer-Hansen K, Orskov H. Inhibition of insulin secretion by somatostatin. Lancet 1973 2 12991301. (doi:10.1016/S0140-6736(73)92873-0).

    • Search Google Scholar
    • Export Citation
  • 17

    Pokrajac A, Frystyk J, Flyvbjerg A, Trainer PJ. Pituitary-independent effect of octreotide on IGF1 generation. European Journal of Endocrinology 2009 160 543548. (doi:10.1530/EJE-08-0822).

    • Search Google Scholar
    • Export Citation
  • 18

    Drake WM, Rowles SV, Roberts ME, Fode FK, Besser GM, Monson JP, Trainer PJ. Insulin sensitivity and glucose tolerance improve in patients with acromegaly converted from depot octreotide to pegvisomant. European Journal of Endocrinology 2003 149 521527. (doi:10.1530/eje.0.1490521).

    • Search Google Scholar
    • Export Citation
  • 19

    Giustina A, Barkan A, Casanueva FF, Cavagnini F, Frohman L, Ho K, Veldhuis J, Wass J, Von Werder K, Melmed S. Criteria for cure of acromegaly: a consensus statement. Journal of Clinical Endocrinology and Metabolism 2000 85 526529. (doi:10.1210/jc.85.2.526).

    • Search Google Scholar
    • Export Citation
  • 20

    Carlsen SM, Lund-Johansen M, Schreiner T, Aanderud S, Johannesen O, Svartberg J, Cooper JG, Hald JK, Fougner SL, Bollerslev J. Preoperative octreotide treatment in newly diagnosed acromegalic patients with macroadenomas increases cure short-term postoperative rates: a prospective, randomized trial. Journal of Clinical Endocrinology and Metabolism 2008 93 29842990. (doi:10.1210/jc.2008-0315).

    • Search Google Scholar
    • Export Citation
  • 21

    Lindberg-Larsen R, Moller N, Schmitz O, Nielsen S, Andersen M, Orskov H, Jorgensen JO. The impact of pegvisomant treatment on substrate metabolism and insulin sensitivity in patients with acromegaly. Journal of Clinical Endocrinology and Metabolism 2007 92 17241728. (doi:10.1210/jc.2006-2276).

    • Search Google Scholar
    • Export Citation
  • 22

    Ueland T, Fougner SL, Godang K, Schreiner T, Bollerslev J. Serum GH and IGF-I are significant determinants of bone turnover but not bone mineral density in active acromegaly: a prospective study of more than 70 consecutive patients. European Journal of Endocrinology 2006 155 709715. (doi:10.1530/eje.1.02285).

    • Search Google Scholar
    • Export Citation
  • 23

    Jorgensen JO, Feldt-Rasmussen U, Frystyk J, Chen JW, Kristensen LO, Hagen C, Orskov H. Cotreatment of acromegaly with a somatostatin analog and a growth hormone receptor antagonist. Journal of Clinical Endocrinology and Metabolism 2005 90 56275631. (doi:10.1210/jc.2005-0531).

    • Search Google Scholar
    • Export Citation
  • 24

    Wallace TM, Levy JC, Matthews DR. Use and abuse of HOMA modeling. Diabetes Care 2004 27 14871495. (doi:10.2337/diacare.27.6.1487).

  • 25

    Hursting SD, Hursting MJ. Growth signals, inflammation, and vascular perturbations: mechanistic links between obesity, metabolic syndrome, and cancer. Arteriosclerosis, Thrombosis, and Vascular Biology 2012 32 17661770. (doi:10.1161/ATVBAHA.111.241927).

    • Search Google Scholar
    • Export Citation
  • 26

    Dahlman I, Kaaman M, Olsson T, Tan GD, Bickerton AS, Wahlen K, Andersson J, Nordstrom EA, Blomqvist L, Sjogren A. A unique role of monocyte chemoattractant protein 1 among chemokines in adipose tissue of obese subjects. Journal of Clinical Endocrinology and Metabolism 2005 90 58345840. (doi:10.1210/jc.2005-0369).

    • Search Google Scholar
    • Export Citation
  • 27

    Agudo J, Ayuso E, Jimenez V, Casellas A, Mallol C, Salavert A, Tafuro S, Obach M, Ruzo A, Moya M. Vascular endothelial growth factor-mediated islet hypervascularization and inflammation contribute to progressive reduction of β-cell mass. Diabetes 2012 61 28512861. (doi:10.2337/db12-0134).

    • Search Google Scholar
    • Export Citation
  • 28

    Tinahones FJ, Coin-Araguez L, Mayas MD, Garcia-Fuentes E, Hurtado-Del-Pozo C, Vendrell J, Cardona F, Calvo RM, Obregon MJ, El Bekay R. Obesity-associated insulin resistance is correlated to adipose tissue vascular endothelial growth factors and metalloproteinase levels. BMC Physiology 2012 12 4. (doi:10.1186/1472-6793-12-4).

    • Search Google Scholar
    • Export Citation
  • 29

    Bays HE. Adiposopathy is “sick fat” a cardiovascular disease? Journal of the American College of Cardiology 2011 57 24612473. (doi:10.1016/j.jacc.2011.02.038).

    • Search Google Scholar
    • Export Citation
  • 30

    Baldelli R, Battista C, Leonetti F, Ghiggi MR, Ribaudo MC, Paoloni A, D'Amico E, Ferretti E, Baratta R, Liuzzi A. Glucose homeostasis in acromegaly: effects of long-acting somatostatin analogues treatment. Clinical Endocrinology 2003 59 492499. (doi:10.1046/j.1365-2265.2003.01876.x).

    • Search Google Scholar
    • Export Citation
  • 31

    Tzanela M, Vassiliadi DA, Gavalas N, Szabo A, Margelou E, Valatsou A, Vassilopoulos C. Glucose homeostasis in patients with acromegaly treated with surgery or somatostatin analogues. Clinical Endocrinology 2011 75 96102. (doi:10.1111/j.1365-2265.2011.03996.x).

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