Abstract
Background & Aims
Unacylated ghrelin (UnAG) modulates insulin sensitivity. Low plasma UnAG occurs in obesity and potentially contributes to obesity-associated insulin resistance. We hypothesized that moderate caloric restriction (CR) improves insulin sensitivity in obese people concurrent to increase in UnAG to potentially explain CR-induced changes in insulin sensitivity in obese people.
Methods
20 general community obese people were randomly assigned to 16-week CR (n=11) or control diet (n=9). We investigated the impact of CR on the interaction between insulin sensitivity changes [area under the curve (AUCg) of glucose infusion to maintain euglycemia during hyperinsulinemic-euglycemic clamp] and plasma total (TotalG), acylated (AG) and Unacylated ghrelin (UnAG). Plasma pro-inflammatory tumor necrosis factor alpha (TNFα) and anti-inflammatory interleukin-10 (IL-10) were also measured since changes in inflammation may contribute to UnAG activities.
Results
CR reduced BMI and increased insulin sensitivity (p<0.05). TotalG and UnAG but not AG increased in CR but not in Control (p<0.05). Il-10 and IL-10/TNFα ratio also increased in CR (p<0.05). Changes in UnAG were positively associated with changes in AUCg in all subjects (n=20; p<0.01) also after adjustment for treatment and changes in BMI and cytokines.
Conclusions
Caloric restriction modifies circulating ghrelin profile with selective increase in unacylated hormone in obese individuals. The current study supports the hypothesis that higher unacylated ghrelin contributes to improvements in insulin sensitivity following diet-induced weight loss in human obesity.
Keywords: Obesity, Unacylated ghrelin, Insulin resistance
BACKGROUND
The prevalence of overweight and obesity has reached worldwide epidemic proportions due to increasingly pervasive obesogenic lifestyle modifications, with complex individual, social and multidisciplinary healthcare challenges (1–4). Among complications related to obesity, insulin resistance represents one of the most prevalent, leading to metabolic syndrome, type 2 diabetes and cardiovascular disease, therefore importantly contributing to high morbidity and mortality (5, 6). Excess nutrient intake and impaired nutrient utilization may contribute to the onset of obesity-associated insulin resistance, and related low-grade systemic inflammation is reported to play a relevant pathogenic role (5, 7, 8). Caloric restriction is therefore an effective therapeutic intervention to enhance insulin action, potentially involving lower inflammation. Mechanisms underlying beneficial metabolic effects of caloric restriction remain however only partly understood (9–11).
The unacylated form (UnAG) of the orexigenic hormone acylated ghrelin (AG) is an emerging modulator of intermediate metabolism (12–18) and its metabolic effects include improvement of whole-body insulin action in lean and obese rodents (14, 19). UnAG activities appear to be mediated at least in part by increments in skeletal muscle insulin signalling activation (13, 14) through reduced mitochondrial and tissue reactive oxygen species generation and inflammation (13, 14). Consistent with these findings we recently demonstrated that total and unacylated but not acylated hormone are associated with and predict whole-body insulin action in general population cohorts (12). Also importantly we previously showed that obesity is characterized by changes in circulating ghrelin profile (20–22) with reduction of total and unacylated forms and preserved AG; altered ghrelin profile was also interestingly associated with reduced whole-body insulin action (12, 21). At the opposite extreme of the nutritional spectrum anorexia nervosa and malnutrition at large are commonly associated with high total circulating ghrelin (15, 23, 24).
The characterization of the role of UnAG on the modulation of insulin sensitivity in obesity might therefore potentially contribute to identify new clinically relevant therapeutic strategies and targets to counteract obesity-associated insulin resistance (14, 21). However, mechanisms regulating circulating UnAG and plasma ghrelin profile remain largely unknown. Potential changes in circulating UnAG following changes in dietary intake also remain largely to be defined, and no information is currently available for the potential of caloric restriction and weight loss on circulating ghrelin profile.
In the current study we therefore assessed plasma total, acylated and unacylated ghrelin in obese individuals undergoing a 16-week moderate caloric restriction programme aimed at achieving 10% body weight reduction without modification of physical activity levels. The study was part of a larger protocol aimed at investigating mechanisms of improved insulin resistance by dietary restriction in humans with obesity and part of its results have been previously published (10). We tested here the hypotheses that in human obesity: 1) caloric restriction causes a selective increase of plasma UnAG without modification of acylated hormone; 2) changes in plasma UnAG are associated with changes in whole-body insulin sensitivity. We further assessed whether changes in systemic low-grade inflammation occurred on caloric restriction since UnAG is also reported to exert anti-inflammatory actions that could contribute to potential insulin-sensitizing effects.
METHODS
This study was performed in the context of a major project conducted with the aim of investigating the impact of CR on insulin sensitivity and related mechanisms in obese adults. Ghrelin and cytokine plasma measurements for this paper were specifically measured for this study in plasma samples collected in the below referenced human CR model protocol. Other results from this study have been published in a separate publication, where detailed information on study participants has also been reported (10).
Participants
20 obese (BMI>30 kg/m2) individuals were recruited and studied at the Division of Endocrinology and Metabolism, Mayo Clinic College of Medicine, Rochester, MN. Participants gave written informed consent, which was approved by the Mayo Foundation Institutional Review Board. Inclusion criteria were BMI >30 kg/m2, age 45–65 years; exclusion criteria were smoking, structured exercise more than twice weekly for >30 min, fasting blood glucose >7 mmol/L, renal failure, chronic active liver disease or active coronary artery disease, taking medications known to affect energy metabolism or insulin sensitivity and anticoagulant therapy.
Intervention
The study design and protocol were also previously described in detail (10). Following 5 days of maintenance diet provided by the Mayo Clinic Clinical Research Unit (CRU) kitchen and based on patient’s REE as previously determined to ensure baseline weight stability, all participants were randomly assigned to undergo caloric restriction (CR) or control diet (Control) for 16 weeks. CR was defined as removal of 1,000 kcal from habitual fat and carbohydrate intake with constant protein. Initial meal provision from the Mayo Clinic and weekly meetings with a registered dietician throughout the entire intervention ensured adherence to the CR diet and weight loss monitoring. Meetings with the registered dietician included analysis of weekly food recall information in order to facilitate corrections if needed. Failure to lose weight for 2 consecutive weeks activated the implementation of corrective strategies which consisted in further provision of controlled meals from the metabolic kitchen and, when needed to assist in adherence, portioned meal replacement products (New Lifestyle Diet Inc., San Ramon, CA). Additional meetings with the dietician were also ensured as needed. The Control group participants were instructed to maintain their normal eating and activities of daily living, that were monitored in both groups with an accelerometer (10).
Study protocol
Shortly, before and after 16-weeks CR or Control two outpatient visits under overnight fasting conditions and one inpatient visit were scheduled. For the inpatient visit, participants were admitted to the CRU on the evening of the fifth day of the weight-maintaining diet provided by the CRU metabolic kitchen (20% protein, 30% fat, 50% carbohydrate). A two-stage insulin euglycemic pancreatic clamp was performed on the following morning under10-hour fasted conditions as previously published (25). Hormonal infusions of glucagon, somatostatin and growth hormone for pancreatic clamp were started at 0700 h as previously described (10) and continued for 6 h. Insulin and dextrose infusions were performed to maintain blood glucose above 4.7 mmol/L from 0700 to 1000 h and then between 4.7 and 5.3 mmol/L from 1000 to 1300 h, based on 10 min-interval determinations. Blood sampling were collected for hormonal and biochemical measurements. Insulin sensitivity was calculated as Area under the Curve (AUCg) of glucose infused in the last hour of clamp. Body composition was assessed by DEXA scans (Lunar DPX-L; Lunar Radiation, Madison, WI) on outpatient visit and fat free mass was used to normalize insulin sensitivity measurements (10).
Analytical procedures
Plasma glucose concentration was measured every 10 min during the insulin clamp with an Analox glucose analyzer (Analox Instruments, London, U.K.). Peripheral insulin sensitivity was determined from the rate of glucose infusion to maintain euglycemia during the high-dose insulin clamp. Plasma total and acylated ghrelin were measured as previously described using commercially available ELISA kits (Merck, Burlington, MA, USA) on fresh frozen plasma sample aliquots as available, i.e. for 20 (baseline) or 19 (post treatment) studied subjects; plasma unacylated ghrelin was calculated as the difference between total and acylated hormone (12, 26). Plasma cytokines IL-1beta, TNF-alpha and IL-10 were measured using xMAP technology as previously described (13, 14) according to manufacturer’s instructions (Merck, Burlington, MA, USA).
Statistical Analyses
Comparisons between groups and timepoints were performed by two-way ANOVA, followed by post-hoc Tukey’s analysis. Associations were evaluated by Spearman correlation analysis, to limit any misrecognition of potential confounding factors with non linear associations and to relatively small sample size. However, post-hoc Pearson correlation analysis provided comparable results. Independency of the association between changes in ghrelin forms and changes in insulin sensitivity was tested by stepwise multiple regression. Models included other associated variables, as identified at correlation analysis. Among parameters sharing similar clinical meaning, only one was included in multiple regression models in order to avoid collinearity. p values <0.05 were considered statistically significant. Analysis was performed by SPSS v.17 software. Continuous variables are presented as mean±standard error.
RESULTS
Study participants characteristics
Participants in the two CR and Control groups were matched at baseline for age, sex, BMI and body composition (10). Also, metabolic parameters including plasma glucose, insulin and direct assessment of insulin sensitivity by AUCg during clamp were not significantly different (p>0.05) at baseline. 16-week dietary treatment lowered body weight (−10.4±1.2 kg), BMI, fat and lean mass, while no changes were observed in any parameter in the Control group (body weight change: +1.0±0.7 kg; Table 1).
Table 1: Characteristics of the subjects.
Sex, age, height, weight, body mass index (BMI), plasma glucose and insulin levels and insulin sensitivity (last hour glucose infusion in a 6h euglycemic hyperinsulinemic clamp – area under the curve, AUCg) in studied subjects at baseline and after 16-week caloric restriction (CR) or control diet. No statistically significant difference was observed at baseline between groups.
| CR |
Control |
|||
|---|---|---|---|---|
| Baseline | Post | Baseline | Post | |
| n | 11 | 11 | 9 | 9 |
| Male/Female | 5/6 | 4/5 | ||
| Age [y] | 55±2 | 53±2 | ||
| Height [cm] | 170±2 | 178±4 | ||
| Weight [kg] | 102±5 | 91±5 * | 109±7 | 110±8 |
| BMI [kg/m2] | 35.2±1.3 | 31.8±1.1 * | 34.4±1.4 | 34.6±1.5 |
| Glucose [mg/dL] | 106±3 | 102±2 | 105±3 | 105±4 |
| Insulin [μIU/mL] | 12.7±1.8 | 6.7±0.9 * | 11.3±2.5 | 11.2±2.3 |
| Clamp AUCg [mg·kgFFM−1·min−1] | 430±74 | 629±62 # | 596±107 | 614±119 |
p<0.05 vs. other groups
p<0.05 vs. baseline.
Plasma ghrelin profile: effects of CR (Figure 1)
Figure 1: Plasma ghrelin profile.
Plasma total, acylated and unacylated ghrelin levels in studied subjects at baseline and after 16-week caloric restriction (CR) or control diet. *:p<0.05 vs. other groups.
TotalG, AG and UnAG levels were comparable at baseline in CR and Control. TotalG and UnAG selectively increased following CR with no changes in AG (P<0.05 vs Baseline) while baseline and 16-week values were superimposable in Control (p>0.05).
Plasma IL-1beta, TNF-alpha and IL-10: effects of CR (Figure 2)
Figure 2: Plasma cytokine profile.
Circulating cytokine profile in studied subjects at baseline and after 16-week caloric restriction (CR) or control diet. *:p<0.05 vs. baseline.
Pro- and anti-inflammatory cytokine plasma concentrations were comparable at baseline in CR and Control. Anti-inflammatory IL-10 was selectively higher following CR (P<0.05 vs Baseline) with no changes in the control group. No changes were conversely observed in either group for plasma pro-inflammatory IL-1beta and TNF-alpha. The validated marker of low-grade systemic inflammation IL-10/TNF-alpha ratio was importantly selectively higher following treatment in CR but not in control group.
Insulin sensitivity: effects of CR
Insulin sensitivity, determined as AUCg of glucose infusion rate during clamp, significantly increased in CR (p<0.05) with no changes in Control (Table 1). Insulin, glucagon, and growth hormone plasma concentrations remained constant by design throughout the clamp period, with suppressed C-peptide levels (10).
Associations between insulin sensitivity and plasma ghrelin profile
In association analysis, insulin sensitivity was associated with total ghrelin. Comparing hormone forms, this finding reflected a selective association with UnAG, while AG was not positively associated with AUCg before and after the 16-week intervention (not shown). Globally, changes from baseline to after 16-week in both UnAG and TotalG were also importantly positively associated with changes in AUCg (Figure 3). Changes in AUCg were also negatively associated with changes in BMI and TNFa (Table 2). Associations between UnAG, TotalG and AUCg notably remained statistically significant (P<0.05) after adjustment for changes in BMI, changes in both pro- and anti-inflammatory TNF-alpha and IL-10 plasma concentrations and treatment (Control vs CR; Table 3).
Figure 3: Association analysis between changes in insulin sensitivity and ghrelin levels.
Association between changes (Δ) in insulin sensitivity (last hour glucose infusion in a 6h euglycemic hyperinsulinemic clamp – area under the curve, AUCg) and changes in total, acylated and unacylated ghrelin plasma levels in all study subjects (n=19) between baseline after 16-week caloric restriction (CR) or control diet. FFM: Free fatty mass as measured by DEXA. p<0.05 is considered to be significant.
Table 2: Association analysis.
Association analysis between changes (Δ) after 16-week caloric restriction or control diet in body weight, Body Mass Index (BMI), plasma glucose and insulin levels, circulating cytokine profile and insulin sensitivity (last hour glucose infusion in a 6h euglycemic hyperinsulinemic clamp – area under the curve, AUCg) in all studied subjects. ρ: Spearman’s rho. p<0.05 is considered to be significant.
| Δ AUCg | ||
|---|---|---|
| ρ | p | |
| Δ Weight | −0.574 | <0.01 |
| Δ BMI | −0.533 | <0.05 |
| Δ Glucose | −0.630 | <0.01 |
| Δ Insulin | −0.626 | <0.01 |
| Δ IL-1β | −0.328 | 0.170 |
| Δ TNFα | −0.507 | <0.05 |
| Δ IL-10 | 0.026 | 0.915 |
| Δ IL-10/TNFα | 0.232 | 0.340 |
Table 3 – Multiple regression analyses.
Multiple regression analyses between changes (Δ) after 16-week caloric restriction or control diet in total (TotalG), acylated (AG), unacylated ghrelin (UnAG) and changes in insulin sensitivity (last hour glucose infusion in a 6h euglycemic hyperinsulinemic clamp – area under the curve, AUCg; dependent variable) in studied subjects (n = 19) in different statistical adjustment models. B: Unstandardized coefficient; SE: Standard Error; t: t-value. p<0.05 is considered to be significant.
| Δ Insulin sentitivity (AUCg) | |||||
|---|---|---|---|---|---|
| B | SE | t | p | ||
| Δ TotalG | Model 1 | 0.774 | 0.233 | 3.320 | <0.01 |
| Model 2a | 0.637 | 0.230 | 2.767 | <0.05 | |
| Model 2b | 0.759 | 0.229 | 3.318 | <0.01 | |
| Model 3a | 0.543 | 0.260 | 2.099 | <0.05 | |
| Model 3b | 0.584 | 0.262 | 2.228 | <0.05 | |
| Δ AG | Model 1 | −0.574 | 1.683 | −0.341 | 0.737 |
| Model 2a | 0.643 | 1.573 | 0.409 | 0.688 | |
| Model 2b | −0.182 | 1.717 | −0.106 | 0.917 | |
| Model 3a | 1.035 | 1.384 | 0.747 | 0.467 | |
| Model 3b | 0.465 | 1.505 | 0.309 | 0.762 | |
| Δ UnAG | Model 1 | 0.815 | 0.230 | 3.544 | <0.01 |
| Model 2a | 0.669 | 0.239 | 2.799 | <0.05 | |
| Model 2b | 0.791 | 0.228 | 3.464 | <0.01 | |
| Model 3a | 0.595 | 0.281 | 2.163 | <0.05 | |
| Model 3b | 0.621 | 0.274 | 2.272 | <0.05 | |
Data adjustments:
Model 1: Δ BMI
Model 2a: Model 1 + Δ TNFα
Model 2b: Model 1 + Δ IL-10
Model 3a: Model 2a + group
Model 3b: Model 2b + group
DISCUSSION
The current study demonstrated that 1) 16-week moderate caloric restriction in obese individuals modify circulating ghrelin profile with increase in unacylated but not acylated hormone; 2) in the same subjects, changes in unacylated ghrelin such as those described after CR are positively associated with beneficial effects on whole-body insulin sensitivity; 3) these associations are independent of major potential confounders including concomitant changes in body mass as well as changes in systemic low-grade inflammation. The current findings support a notion that higher unacylated ghrelin is a contributor to metabolic benefits in improving insulin sensitivity following diet-induced weight loss in obese people. Unacylated ghrelin is emerging as a positive modulator of intermediate metabolism resulting in beneficial metabolic profile including lower insulin resistance in the general population as well as in obese people with metabolic syndrome (12, 14–16, 21). Previous studies indeed demonstrated that obesity may alter circulating ghrelin profile by reducing total as well as unacylated hormone levels that may therefore conversely contribute to obesity-induced insulin resistance and metabolic complications. The current study notably provides to the best of our knowledge the first evidence that caloric restriction modulates circulating ghrelin profile in obese humans both quantitatively and qualitatively by selectively increasing plasma unacylated hormone. Modulators of ghrelin acylation by ghrelin O-acyl transferase (GOAT) remain largely unknown but nutrients and nutritional status have been reported to regulate GOAT activity in experimental models (18, 26). GOAT activation indeed was reported to be enhanced by calories and fat availability (27) resulting in potentially adaptive appetite stimulation with energy storage and survival advantage at times of erratic food availability and intake. We accordingly previously reported acute increments in circulating acylated ghrelin following acute elevation of mostly long-chain circulating fatty acids in rodents (26) with positive associations between circulating fatty acid concentrations and plasma acylated ghrelin in a large general population human samples (26). Plasma total fatty acid concentration did not fall under the current experimental conditions. It is however possible that lower fatty acid availability at ghrelin acylation sites potentially downregulate GOAT activity (26). Modulation of local tissue fatty acid metabolism was indeed reported to play a relevant independent regulatory role in rodent models following experimental manipulations leading to extreme variability of diet-and microbiota-derived precursors (28). Future mechanistic studies are needed to elucidate this relevant issue.
The current findings support our hypothesis that changes in unacylated ghrelin contribute to our previous results showing improved glucose metabolism following caloric restriction in obese individuals (10). We previously demonstrated that unacylated ghrelin modulates fundamental metabolic pathways regulating insulin action and glucose metabolism in skeletal muscle in both physiological and pathological rodent models including obesity and chronic kidney disease (13, 14). Unacylated ghrelin activities include downregulation of tissue inflammation with enhanced anti-inflammatory cytokine levels (13, 14) and anti-inflammatory changes occurred in the current study at systemic level following caloric restriction. Changes in low-grade systemic inflammation were importantly associated with changes in insulin sensitivity (29–31) whereas associations between unacylated ghrelin and insulin sensitivity were independent of plasma inflammatory profile in the current study. While additional studies are needed to directly test potential interactions between unacylated ghrelin and systemic and tissue inflammation in modulating metabolic benefits of dietary treatment in obesity, the current findings support a potential clinical relevance for UnAG in the development of therapeutic strategies aiming at counteracting obesity-associated insulin resistance.
Of interest, we previously reported anti-oxidative activities of unacylated ghrelin can occur with suppression of mitochondrial and non-mitochondrial oxidant emissions in skeletal muscle in rodent models (13, 14). In the current studies no reduction of mitochondrial oxidant emissions was observed in skeletal muscle biopsy samples (10). Species differences as well as different experimental designs with sustained changes in diet and nutritional status induced in the current human but not in previous rodent studies could have contribute to these discrepancies. Different muscle groups were also notably selected for mitochondrial measurements (10, 13, 14) and ghrelin activities on skeletal muscle energy metabolism have been reported to be muscle group-dependent in vivo (32). Potential anti-oxidative activities of unacylated ghrelin in human skeletal muscle should therefore be further investigated under different nutritional experimental conditions and potentially in different skeletal muscles.
Association analysis does not necessarily imply a causal relationship between changes in unacylated ghrelin levels and insulin sensitivity. Also, the nature of this study did not allow for other in-depth investigation of the mechanisms involved in these findings. However, previous studies in animal models showing that UnAG treatment was able to improve insulin sensitivity both at tissue and systemic levels also in high-fat fed mice (14), strongly suggest a potential mechanistic and causal role for UnAG also in the current results. Finally, we acknowledge that the present protocol was performed in a relatively small specific cohort which allowed good homogeneity for baseline parameters and sufficient statistical power. Extrapolation to other age or ethnic groups should therefore be undertook with caution. In conclusion, the current studies indicate that caloric restriction is a novel modulator of circulating ghrelin profile causing a selective increase in circulating unacylated but not acylated hormone in obese individuals. In line with previous results in animal models demonstrating that higher unacylated ghrelin contributes to metabolic benefits including insulin sensitivity, the current study likely supports this finding also in obese people following caloric restriction and weight loss. Importantly, the interaction between insulin sensitivity and ghrelin changes seem to occur independently of body weight loss and anti-inflammatory changes.
Acknowledgements
The authors are greatly indebted to the skillful assistance of Daniel Jakaitis, Jill Schimke, Dawn Morse, Roberta Soderberg, Deborah Sheldon, Lynne Johnson, and Melissa Aakre in the Division of Endocrinology and Metabolism, Mayo Clinic College of Medicine, Rochester, MN. Meal replacements for the caloric restriction group were donated by New Lifestyle Diet (San Ramon, CA).
Funding: Funding for this work was provided by National Institute of Diabetes and Digestive and Kidney Diseases grants U24-DK-100469, T32-DK-007198 (M.L.J.), R01-DK-41973 (K.S.N.), and UL1-TR-000135, and by National Center for Advancing Translational Sciences grants KL2-TR-000136-07 (M.L.J.). Additional support was provided by the Mayo Foundation and the Murdock-Dole Professorship (to K.S.N.).
Footnotes
Conflict of interest: Authors have no potential conflicts of interest relevant to this article to disclose.
Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could a?ect the content, and all legal disclaimers that apply to the journal pertain.
REFERENCES
- 1.Collaboration NCDRF. Trends in adult body-mass index in 200 countries from 1975 to 2014: a pooled analysis of 1698 population-based measurement studies with 19.2 million participants. Lancet. 2016;387(10026):1377–96. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Withrow D, Alter DA. The economic burden of obesity worldwide: a systematic review of the direct costs of obesity. Obes Rev. 2011;12(2):131–41. [DOI] [PubMed] [Google Scholar]
- 3.Barazzoni R, Bischoff SC, Boirie Y, Busetto L, Cederholm T, Dicker D, et al. Sarcopenic obesity: Time to meet the challenge. Clin Nutr. 2018;37(6 Pt A):1787–93. [DOI] [PubMed] [Google Scholar]
- 4.Bischoff SC, Boirie Y, Cederholm T, Chourdakis M, Cuerda C, Delzenne NM, et al. Towards a multidisciplinary approach to understand and manage obesity and related diseases. Clin Nutr. 2017;36(4):917–38. [DOI] [PubMed] [Google Scholar]
- 5.Barazzoni R, Gortan Cappellari G, Ragni M, Nisoli E. Insulin resistance in obesity: an overview of fundamental alterations. Eat Weight Disord. 2018;23(2):149–57. [DOI] [PubMed] [Google Scholar]
- 6.Alberti KGMM, Eckel RH, Grundy SM, Zimmet PZ, Cleeman Jl, Donato KA, et al. Harmonizing the metabolic syndrome: a joint interim statement of the International Diabetes Federation Task Force on Epidemiology and Prevention; National Heart, Lung, and Blood Institute; American Heart Association; World Heart Federation; International Atherosclerosis Society; and International Association for the Study of Obesity. Circulation. 2009;120(16):1640–5. [DOI] [PubMed] [Google Scholar]
- 7.Samuel VT, Shulman Gl. The pathogenesis of insulin resistance: integrating signaling pathways and substrate flux. J Clin Invest. 2016;126(l):12–22. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Barbarroja N, Lopez-Pedrera R, Mayas MD, Garcia-Fuentes E, Garrido-Sanchez L, Macias-Gonzalez M, et al. The obese healthy paradox: is inflammation the answer? Biochem J. 2010;430(1): 141–9. [DOI] [PubMed] [Google Scholar]
- 9.Dube JJ, Amati F, Toledo FGS, Stefanovic-Racic M, Rossi A, Coen P, et al. Effects of weight loss and exercise on insulin resistance, and intramyocellular triacylglycerol, diacylglycerol and ceramide. Diabetologia. 2011;54(5):1147–56. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Johnson ML, Distelmaier K, Lanza IR, Irving BA, Robinson MM, Konopka AR, et al. Mechanism by Which Caloric Restriction Improves Insulin Sensitivity in Sedentary Obese Adults. Diabetes. 2016;65(l):74–84. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Toledo FGS, Menshikova EV, Azuma K, Radikova Z, Kelley CA, Ritov VB, et al. Mitochondrial capacity in skeletal muscle is not stimulated by weight loss despite increases in insulin action and decreases in intramyocellular lipid content. Diabetes. 2008;57(4):987–94.. [DOI] [PubMed] [Google Scholar]
- 12.Barazzoni R, Gortan Cappellari G, Semolic A, lus M, Mamolo L, Dore F, et al. Plasma total and unacylated ghrelin predict 5-year changes in insulin resistance. Clin Nutr. 2016;35(5): 1168–73. [DOI] [PubMed] [Google Scholar]
- 13.Gortan Cappellari G, Semolic A, Ruozi G, Vinci P, Guarnieri G, Bortolotti F, et al. Unacylated ghrelin normalizes skeletal muscle oxidative stress and prevents muscle catabolism by enhancing tissue mitophagy in experimental chronic kidney disease. Faseb J. 2017;31(12):5159–71. [DOI] [PubMed] [Google Scholar]
- 14.Gortan Cappellari G, Zanetti M, Semolic A, Vinci P, Ruozi G, Falcione A, et al. Unacylated Ghrelin Reduces Skeletal Muscle Reactive Oxygen Species Generation and Inflammation and Prevents High-Fat Diet-Induced Hyperglycemia and Whole-Body Insulin Resistance in Rodents. Diabetes. 2016;65(4):874–86. [DOI] [PubMed] [Google Scholar]
- 15.Gortan Cappellari G, Barazzoni R. Ghrelin forms in the modulation of energy balance and metabolism. Eat Weight Disord. 2018. [DOI] [PubMed] [Google Scholar]
- 16.G Gortan Cappellari, Zanetti M,Vinci P,Guarnieri G,Barazzoni R.Unacylated Ghrelin: A Novel Regulator of Muscle Intermediate Metabolism With Potential Beneficial Effects in Chronic Kidney Disease. J Ren Nutr. 2017;27(6):474–7. [DOI] [PubMed] [Google Scholar]
- 17.Benso A, St-Pierre DH, Prodam F, Gramaglia E, Granata R, van der Lely AJ,et al. Metabolic effects of overnight continuous infusion of unacylated ghrelin in humans. Eur J Endocrinol. 2012;166(5):911–6. [DOI] [PubMed] [Google Scholar]
- 18.Muller TD, Nogueiras R, Andermann ML, Andrews ZB, Anker SD, Argente J, et al. Ghrelin. Mol Metab. 2015;4(6):437–60. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Delhanty PJD,Sun Y,Visser JA,vanKerkwijk A,Huisman M, vanIjcken WFJ,et al. Unacylated ghrelin rapidly modulates lipogenic and insulin signaling pathway gene expression in metabolically active tissues of GHSR deleted mice. PLoS One. 2010;5(7):e11749. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Barazzoni R,Zanetti M,Nagliati C,Cattin MR,Ferreira C,Giuricin M,et al. Gastric bypass does not normalize obesity-related changes in ghrelin profile and leads to higher acylated ghrelin fraction. Obesity (Silver Spring). 2013;21(4):718–22. [DOI] [PubMed] [Google Scholar]
- 21.Barazzoni R,Zanetti M,Ferreira C,Vinci P,Pirulli A,Mucci M, et al. Relationships between desacylated and acylated ghrelin and insulin sensitivity in the metabolic syndrome. J Clin Endocrinol Metab. 2007;92(10):3935–40. [DOI] [PubMed] [Google Scholar]
- 22.Barazzoni R,Aleksova A,Armellini I,Cattin MR,Zanetti M,Carriere C,et al. Adipokines, ghrelin and obesity-associated insulin resistance in nondiabetic patients with acute coronary syndrome. Obesity (Silver Spring). 2012;20(12):2348–53. [DOI] [PubMed] [Google Scholar]
- 23.Atalayer D,Gibson C,Konopacka A,Geliebter A. Ghrelin and eating disorders. Prog Neuropsychopharmacol Biol Psychiatry. 2013;40:70–82. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Barazzoni R, Gortan Cappellari G, Zanetti M, Guarnieri G. Ghrelin and muscle metabolism in chronic uremia. J Ren Nutr. 2012;22(1):171–5. [DOI] [PubMed] [Google Scholar]
- 25.Lanza IR, Short DK, Short KR, Raghavakaimal S, Basu R, Joyner MJ, et al. Endurance exercise as a countermeasure for aging. Diabetes. 2008;57(11):2933–42. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Barazzoni R, Gortan Cappellari G, Semolic A, lus M, Dore F, Giacca M, et al. Intravenous lipid infusion and total plasma fatty acids positively modulate plasma acylated ghrelin invivo. Clin Nutr. 2017;36(3):775–81. [DOI] [PubMed] [Google Scholar]
- 27.Kirchner H, Gutierrez JA, Solenberg PJ, Pfluger PT, Czyzyk TA, Willency JA, et al. GOAT links dietary lipids with the endocrine control of energy balance. Nat Med. 2009;15(7):741–5.. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Ikenoya C, Takemi S, Kaminoda A, Aizawa S, Ojima S, Gong Z, et al. beta-Oxidation in ghrelin-producing cells is important for ghrelin acyl-modification. Sci Rep. 2018;8(1):9176. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.de Rooij SR, Nijpels G, Nilsson PM, Nolan JJ, Gabriel R, Bobbioni-Harsch E, et al. Low-grade chronic inflammation in the relationship between insulin sensitivity and cardiovascular disease (RISC) population: associations with insulin resistance and cardiometabolic risk profile. Diabetes Care. 2009;32(7):1295–301. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.Duncan BB, Schmidt Ml, Pankow JS, Ballantyne CM, D Couper, Vigo A, et al. Low-grade systemic inflammation and the development of type 2 diabetes: the atherosclerosis risk in communities study. Diabetes. 2003;52(7):1799–805. [DOI] [PubMed] [Google Scholar]
- 31.Xu L, Kitade H, Ni Y, Ota T. Roles of Chemokines and Chemokine Receptors in Obesity-Associated Insulin Resistance and Nonalcoholic Fatty Liver Disease. Biomolecules. 2015;5(3):1563–79. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32.Barazzoni R, Bosutti A, Stebel M, Cattin MR,Roder E, Visintin L,et al. Ghrelin regulates mitochondrial-lipid metabolism gene expression and tissue fat distribution in liver and skeletal muscle. Am J Physiol Endocrinol Metab. 2005;288(1):E228–35. [DOI] [PubMed] [Google Scholar]