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Adipocyte Size Threshold Matters: Link with Risk of Type 2 Diabetes and Improved Insulin Resistance After Gastric Bypass Aurelie Cotillard, Christine Poitou, Adriana Torcivia, Jean-Luc Bouillot, Arne Dietrich, Nora Klöting, Cécile Grégoire, Karine Lolmede, Matthias Blüher, and Karine Clément Sorbonne Universities (A.C., C.P., K.C.), University Pierre et Marie Curie-Paris 6, UMR_S U1166, Nutriomics, F-75013 Paris, France; Institute of Cardiometabolism and Nutrition, ICAN, AP-HP (A.C., C.P., C.G., K.C.), Pitié-Salpêtrière hospital, F-75013 Paris, France; INSERM, UMR_S U1166 (A.C., C.P., K.C.), Nutriomics, F-75013 Paris, France; Assistance Publique-Hôpitaux de Paris (A.T.), Pitié-Salpêtrière hospital, Surgery Department, F-75013 Paris, France; Assistance Publique-Hôpitaux de Paris (J.-L.B.), Ambroise Paré Hospital, Surgery Department, F-92012 Boulogne-Billancourt, France; Department of Surgery (A.D.), University of Leipzig, 04003-04357 Leipzig, Germany; Department of Medicine (N.K., M.B.), University of Leipzig, 04003-04357 Leipzig, Germany; and Junior Research Group Animal Models (N.K.), IFB Obesity Diseases, University of Leipzig, 04003-04357 Leipzig, Germany; AdipoPhyt (K.L.), F-75013 Paris, France
Context: Adipocyte volume has been associated with insulin resistance and type 2 diabetes. Objective: Our purpose was to identify an adipocyte volume threshold linked with increased insulin resistance risk, and to examine its association with insulin resistance improvement after bariatric surgery. Setting and Design: We investigated two cohorts of Caucasian women, candidates for bariatric surgery, from two institutional centers in France (age 42.0 ⫾ 11.5 years; body mass index, 47.6 ⫾ 6.9 kg/m2) and Germany (age 41.3 ⫾ 11.2 years; body mass index, 49.5 ⫾ 8.1 kg/m2). 38% of the subjects had gastric bypass surgery and were followed for 6 months after the intervention. We defined a group of subjects with type 2 diabetes or at risk of type 2 diabetes (DRD) and investigated the relations between adipocyte volume and this status before and after surgery. Results: In both cohorts, subjects with DRD presented enlarged adipocytes (France, P ⫽ 3⫻10⫺4; Germany, P ⫽3⫻10⫺10) and we were able to determine thresholds in each cohort above which diabetes risk was potentially increased (France: 1003⫾42 pL, Germany: 798⫾32 pL). Subjects above those adipocyte thresholds were less prone to disappearance of the DRD status after bypass surgery (France, risk ratio ⫽ 2.1, P ⫽ .024; Germany, risk ratio ⫽ 1.3, P ⫽ .05). Conclusions: We show in two cohorts of morbidly obese subjects that a specific adipocyte volume threshold may predict an increased risk for obesity-associated type 2 diabetes. However, this threshold might be established for each specific investigation site. Having a high adipocyte size is associated with a lower improvement of insulin resistance after bypass surgery in both cohorts. (J Clin Endocrinol Metab 99: E1466 –E1470, 2014)
besity is characterized by an increased accumulation of fat mass, which can happen through an increase of adipocyte volume (hypertrophy) or number (hyperpla-
O
sia) (1). The expansion of sc adipose tissue affects adipocyte cell biology and eventually whole-body glucose homeostasis. Adipocyte hypertrophy per se is also seen as a
ISSN Print 0021-972X ISSN Online 1945-7197 Printed in U.S.A. Copyright © 2014 by the Endocrine Society Received January 9, 2014. Accepted April 22, 2014. First Published Online April 29, 2014
Abbreviations: DRD, diabetic or at risk for diabetes; HAV, high-adipocyte volume; HOMAIR, homeostatic model assessment for insulin resistance.
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J Clin Endocrinol Metab, August 2014, 99(8):E1466 –E1470
doi: 10.1210/jc.2014-1074
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key event associated with in vitro and in vivo loss of insulin sensitivity in lean and obese conditions (2– 6). Subjects with larger adipocytes have a higher incidence for elevated levels of proinflammatory factors including leptin, IL-6, and IL-8 (7), and reduced levels of adiponectin, an adipokine associated with insulin-sensitivity (4). In obese subjects, hypertrophy seems thus associated with a deleterious effect on metabolism and inflammation. Quantitative associations have been found between adipocyte volume and insulin resistance, but there is no described threshold in adipocyte volume above which diabetic risk may accelerate significantly. Such thresholds have been investigated when looking at HbA1c and microvascular complications (8) and can be of major clinical interest to detect patients without obvious clinical symptoms and be able to adapt their therapy. Moreover, a way of modulating efficiently adipocyte cell size and improving insulin resistance is bypass surgery also well known to improve obesity comorbidities, including type 2 diabetes (9, 10). This observational study was conducted in two French and German cohorts of morbidly obese subjects candidates for bypass surgery to i) identify an adipocyte volume threshold potentially associated with increased insulin resistance and, ii) examine if adipocyte volume could be involved in improvement of insulin resistance after bypass surgery. To take into account subjects already presenting high insulin resistance, we defined a class including subjects who were diabetic or at risk for diabetes (DRD).
Materials and Methods Two cohorts of European morbidly obese women The French and German cohorts consisted respectively of 217 and 78 Caucasian women involved in bariatric surgery programs (Supplemental Methods). Sixty eight (31.3%) of the French subjects and 25 (32.1%) of the German subjects had type 2 diabetes with fasting glycemia greater than 7 mmol/L and/or the use of an antidiabetic drug (Supplemental Methods). In 37 (13, respectively) nondiabetic subjects in the French (German, respectively) cohort, the homeostatic model assessment for insulin resistance (HOMA-IR) values was greater than 5.384 (3.55, respectively) (75th percentile). These subjects were considered at risk for diabetes as previously proposed (11). We thus defined a class regrouping these 105 (French) and 38 (German) diabetic or at risk for diabetes (DRD) subjects (48.4% of the French cohort and 48.7% of the German cohort). Among them, 79 French subjects and 33 German subjects underwent gastric bypass surgery and were followed for 6 months after the intervention. Using the same criteria and the same HOMA-IR threshold as before surgery, we defined DRD subjects 6 months after surgery. Resolution was considered as the switch from DRD before surgery to non-DRD after surgery. Anthropometric and biochemical parameters were measured as described in Supplemental Methods.
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Statistical analysis Values are expressed as mean ⫾ SD and all statistics were performed using the R software (12). Statistical tests were twotailed. When required, P values were adjusted for multiples tests by Benjamini-Hochberg correction (13). A threshold of .05 was applied for statistical significance. Differences between both cohorts, and between DRD and non-DRD subjects were evaluated using Student t tests. Prevalence of DRD status in the exposure group (high adipocyte size) was plotted against adipocyte volume thresholds. The curve was fitted using nonlinear least square regression by a logistic function. The adipocyte threshold for maximal speeding up in diabetes risk was defined as the point of maximal acceleration of the curve (Supplemental Methods). Differences between subjects solving or not their DRD status were evaluated using non parametric statistics due to the small number of subjects in the German cohort. Mann-Whitney-Wilcoxon tests were used for quantitative variables, and Fisher exact tests were used for qualitative variables. We further investigated these relationships in the French cohort using univariate or multivariate linear models. Diabetes duration value for nondiabetic subjects was set to ⫺1. Model selection was performed using exhaustive search with the R leaps library (14).
Results Anthropometric and biochemical characteristics Anthropometric and biochemical characteristics of the subjects are shown in Table 1. The proportion of DRD women was comparable in both cohorts and approximately 50%. No differences between cohorts were observed regarding age, fat mass, or mean adipocyte volume. However, differences were observed depending on the DRD status (Table 1). Non-DRD German women had a healthier profile with lower fat mass and adipocyte volume compared with nonDRD French women. They presented higher adiponectin and high-density lipoprotein cholesterol levels with lower insulin and HOMA-IR values. Contrastingly, DRD German subjects were significantly heavier with a poorer cholesterol profile. However, they had decreased diabetes duration, better blood glucose control (HbA1c values), and none of them received insulin treatment (Supplemental Methods). In both cohorts, DRD subjects were older and more insulin resistant (HOMA-IR), with larger adipocytes (⫹12% and ⫹29% in the French and German cohorts respectively). However, the distribution of adipocyte volume in the German cohort was more compact with less extremely high values compared with the French cohort. Importantly, the distribution profiles of DRD and non-DRD subjects differed between cohorts, all German subjects with an adipocyte volume above 1000 pL being DRD (Supplemental Figure 1). An adipocyte volume threshold for acceleration in risk of diabetes To investigate the existence of a threshold above which the increase in diabetes risk accelerates substantially in
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Table 1.
Adipocyte Size Threshold and Insulin Resistance
J Clin Endocrinol Metab, August 2014, 99(8):E1466 –E1470
Anthropometric and Biochemical Characteristics of the Subjects in Both Cohorts French Cohort
German Cohort
Characteristic
Non-DRD
DRD
Non-DRD
DRD
n Age, y Adiposity markers Body weight, kgb Body mass index (kg/m2) Fat mass, kg Adipocyte volume, pL No. of adipocytes Leptin, ng/mL Plasma glucose homeostasis and insulin sensitivity Glucose, mmol/L Insulin, UI/mL HOMA-IR HbA1c (%)b (mmol/mol) Adiponectin, g/mL Diabetes duration, y Plasma lipid homeostasis Total cholesterol, mmol/L High-density lipoprotein cholesterol, mmol/L Triglycerides, mmol/L Inflammatory markers IL-6, pg/mLb hs-CRP, mg/L
112 38.34 ⫾ 10.39
105 45.87 ⫾ 11.49a
40 36 ⫾ 8.86
38 46.92 ⫾ 10.74a
125.41 ⫾ 19.12 46.74 ⫾ 6.77 58.62 ⫾ 11.19 883.75 ⫾ 157.36 7.6e13 ⫾ 2.1e13 57.48 ⫾ 25.49
128.23 ⫾ 20.46 48.45 ⫾ 7.05 59.04 ⫾ 11.7 989.75 ⫾ 231.69a 6.8e13 ⫾ 1.9e13a 51.41 ⫾ 26.96
127.2 ⫾ 17.43 45.98 ⫾ 5.36 52.18 ⫾ 10.76c 788.83 ⫾ 114.94c 7.3e13 ⫾ 1.3e13 46.99 ⫾ 8.91c
145 ⫾ 27.39ac 53.25 ⫾ 8.87ac 67.29 ⫾ 16.98ac 1015.79 ⫾ 140.87a 7.4e13 ⫾ 2.2e13 58.68 ⫾ 15.58a
5.05 ⫾ 0.55 14.07 ⫾ 5.48 3.14 ⫾ 1.21 5.67 ⫾ 0.32 (38 ⫾ 3.5) 6.49 ⫾ 2.91 NA
7.19 ⫾ 2.26a 26.19 ⫾ 15.35a 8.18 ⫾ 5.25a 7.08 ⫾ 1.84a (54 ⫾ 20.1) 4.92 ⫾ 2.69a 4.69 ⫾ 5.19
5.24 ⫾ 0.42 5.61 ⫾ 4.44c 1.32 ⫾ 1.07c 5.67 ⫾ 0.89 (38 ⫾ 9.7) 7.87 ⫾ 1.96c NA
7.24 ⫾ 2.34a 29.13 ⫾ 16.05a 9.38 ⫾ 5.45a 6.41 ⫾ 0.89ac (47 ⫾ 9.7) 5.13 ⫾ 2.73a 2.52 ⫾ 2.56c
4.92 ⫾ 0.82 1.3 ⫾ 0.36 1.32 ⫾ 0.55
4.72 ⫾ 0.91 1.19 ⫾ 0.36 1.82 ⫾ 0.89a
4.95 ⫾ 0.92 1.44 ⫾ 0.19c 1.57 ⫾ 0.61
5.31 ⫾ 1.07c 0.99 ⫾ 0.26ac 1.74 ⫾ 0.78
3.38 ⫾ 1.99 10.86 ⫾ 8.04
4.37 ⫾ 3.09a 10.64 ⫾ 8.58
6.67 ⫾ 4.34c 13.42 ⫾ 18.88
6.56 ⫾ 3.7c 10.21 ⫾ 8.11
hs-CRP, high-sensitivity C-reactive protein; NA, not available. Values are expressed as mean ⫾ SD. a
P ⬍ .05 between DRD subjects and non-DRD subjects.
b
P ⬍ .05 between both cohorts.
c
P ⬍ .05 between both cohorts for a given DRD status.
both or each cohort, we considered the prevalence of the DRD status above a given value of adipocyte volume. This prevalence significantly increased with adipocyte volume and the curve was well fitted by a logistic function in both cohorts (Figure 1, A and B). The curve presented a maximal acceleration for an adipocyte volume of 1003 ⫾ 42 pL in the French cohort and a lower value of 798 ⫾ 32 pL in the German cohort (Materials and Methods). Subjects above those adipocyte volume thresholds will henceforth be denoted high-adipocyte volume (HAV) subjects. The risk ratio associated with DRD in the HAV group was 1.38 with P ⫽ .027 (4.88, respectively; P ⫽ 5⫻10⫺5) in the French (German, respectively) cohort. Whereas this threshold objective was not status prediction (AUC ⫽ 0.61 in the French cohort with logistic regression), its main purpose was to detect subjects that may be at higher risk of developing type 2 diabetes or insulin resistance. Considering that HAV non-DRD subjects should be followed with more care, 26 (20, respectively) patients were concerned in the French (German, respectively) cohort.
the French cohort, this percentage of resolution differed depending on basal adipocyte volume: 86% in the non-HAV subjects and 62% in the HAV subjects (P ⫽ .024, risk ratio ⫽ 2.1). Concordantly, the adipocyte volume was significantly higher in the nonsolved group (Figure 1, C and D). A similar trend was observed in the smaller German cohort (P ⫽ .05, risk ratio ⫽ 1.3). Using all clinical variables associated with the DRD status (Supplemental Table 1) in addition to diabetes duration, we built univariate models in the French cohort to predict DRD status resolution. The best model was obtained with diabetes duration and the next best models included HbA1c, adipocyte volume, glucose level, and age (Supplemental Figure 2A). With model selection on these five parameters, adipocyte volume was included when using an adjusted r2 criterion, but not with a bayesian information criteria (Supplemental Figure 2, B and C). Small differences between qualities of the models underline a nonstable model selection, but these results suggest a role of adipocyte size in DRD status resolution after bypass.
Adipocyte volume associates with resolution of DRD status after gastric bypass Six months after bypass, 61 French women (77%) and only 13 German women (39%) resolved their DRD status. In
Discussion Here we were able to show that the concept of an adipocyte size threshold for determining an increase risk of
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mental triggers (such as food patterns or physical activity) and criteria for treatments might differ. Even if all subjects were of Caucasian origin, there might still be some genetic differences explaining these discrepancies. Most importantly, having a large adipocyte size was associated with a lower incidence of remission of the insulin resistance state 6 months after bypass surgery in both cohorts. When taking into account usual predictors such as blood glucose hoc d meostasis or diabetes duration, adipocyte volume was still of importance, even if its role is difficult to evaluate in a context where variables are strongly interrelated. It could be of interest to identify these subjects with less improvement of their metabolic state after bypass surgery, particularly in the context of metabolic surgery dedicated to patients with an altered metabolic status but not the body mass index cut-off for bariatric surgery. Clinical and indiFigure 1. DRD status before and after surgery in association with adipocyte volume. A) and B): vidual variables have been proposed prevalence of DRD subjects above each threshold of adipocyte volume in the French cohort A) as putative predictors of improveand in the German cohort B). A logistic function (black line) was fitted on the gray curve. The dashed line stands for the maximum acceleration in the increase of diabetes risk. The gray ment of insulin resistance and parhistogram illustrates the distribution of adipocyte volume in the population. RSE: residual SE for ticularly age and history of diabetes the sigmoid fit. C) and D): Adipocyte volume in subjects solving or not their DRD status in the (16). Here we suggest that adipocyte French cohort C) and in the German cohort D). **, P ⬍ .01; #, P ⬍ .1. volume should be considered when looking for predictors or explanainsulin resistance could be replicated in two cohorts of tions for insulin resistance improvement and/or diabetes French and German Caucasian women, candidates for remission after bariatric surgery. Its contribution may be bariatric surgery. This threshold was identified in severe small and linear modeling has limitations, but pieces of obesity and it could be interesting to extend this measure evidence linking adipocyte volume to insulin resistance in less obese but diabetic subjects undergoing metabolic suggest biological relevance. This stimulates the interest in surgery (15). The purpose of this threshold being to detect testing this variable in different bariatric surgery populasubjects who may be at higher risk of developing type 2 diabetes or insulin resistance, an additional step would be tions. In 2011, Laurencikiene et al (17) showed that more to validate its use in a prospective cohort study with a lipolysis occurs in larger adipocytes, and that it might link longer-term follow-up. Whereas a threshold was clearly adipocyte hypertrophy to the risk of developing type 2 identified, it is remarkable that the thresholds were dif- diabetes, although these results were not consistent with a ferent in the two cohorts. This difference was partly ex- prediction model established by Jo et al (18). It has also plained by method differences in adipocyte size measure- been recently suggested that it might be possible to imments (systematic comparison of the two methods in prove insulin sensitivity by reducing adipocyte lipolysis Supplemental Information). The cohorts also presented (19), raising the hope of treatments for those subjects with different clinical characteristics depending on their DRD HAV. Although we demonstrated the concept of an adipocyte status, and adipocyte volume distribution profiles of DRD and non-DRD subjects were different between both co- size threshold for increased risk of insulin resistance, difhorts. Whereas both countries follow similar international ferent thresholds were obtained in the two cohorts due to criteria for bypass surgery, national specificity of environ- biological and technical variations, underlying the limita-
a
b
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Adipocyte Size Threshold and Insulin Resistance
tion that this critical threshold should be determined in each given population and depending of the technique used for cell size measurement. This association between an adipocyte threshold and increased risk of insulin resistance should, however, not mislead to think that subjects below this threshold are risk free of developing carbohydrate intolerance. In addition, insulin resistance was evaluated using the HOMA-IR, which accounts for the glucose toxicity component of insulin resistance, but not for the lipid-toxicity component. Finally, the DRD status that we used is a composite group including nondiabetic insulin-resistant subjects and diabetic subjects with or without medication. Although both represent insulin-resistant states, resolution of diabetes does not necessarily only depends on improvement of insulin resistance, but also on  cell reserve (20). Specific studies focusing on larger cohorts of only diabetic or nondiabetic insulin-resistant subjects with longer-term follow-up will be useful.
Acknowledgments We thank Dr Florence Marchelli and Valentine Lemoine (APHP), Pitié-Salpêtrière, Paris, for the constitution of the database; and Jean-François Bedel, Jenifer Alban, and Patricia Ancel, Pitié-Salpêtrière, Paris, for measuring in routine adipocyte size. We thank the LNC laboratory for providing the data presented in the Supplemental Information. Address all correspondence and requests for reprints to: Karine Clément, Institute of Cardiometabolism and Nutrition, Hôpital Pitié-Salpêtrière, 75013 Paris, France. E-mail: [email protected]. This work was supported by the Emergence Program (Université Pierre et Marie Curie), PHRC 02076 (Assistance Publique des Hôpitaux de Paris), CRC FIBROTA (Direction of Clinical Research), ANR Fibrota and the national program “Investissements d’avenir” with the reference ANR-10-IAHU-05 (National Agency of Research and Fondation pour la Recherche Médicale), Kompetenznetz Adipositas (Competence network for Obesity, German Obesity Biomaterial Bank, GOBB) funded by the Federal Ministry of Education and Research (FKZ 01GI1128, FKZ 01EO1001 to N.K.), grant from Deutsche Forschungsgemeinschaft the SFB 1052: “Obesity mechanisms (project B1 to M.B. and B4 to N.K.). K.C. and A.C. received a grant from Roche company. French and German teams received a grant from EU Metacardis program (FP7). Disclosure Summary: The authors have nothing to disclose.
References 1. Björntorp P, Sjöström L. Number and size of adipose tissue fat cells in relation to metabolism in human obesity. Metab Clin Exp. 1971; 20:703–713.
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2. Salans LB, Knittle JL, Hirsch J. The role of adipose cell size and adipose tissue insulin sensitivity in the carbohydrate intolerance of human obesity. J Clin Invest. 1968;47:153–165. 3. Stern JS, Batchelor BR, Hollander N, Cohn CK, Hirsch J. Adiposecell size and immunoreactive insulin levels in obese and normalweight adults. Lancet. 1972;2:948 –951. 4. Chandalia M, Lin P, Seenivasan T, et al. Insulin resistance and body fat distribution in South Asian men compared to Caucasian men. PLoS ONE. 2007;2:e812. 5. Hoffstedt J, Arner E, Wahrenberg H, et al. Regional impact of adipose tissue morphology on the metabolic profile in morbid obesity. Diabetologia. 2010;53:2496 –2503. 6. Klöting N, Fasshauer M, Dietrich A, et al. Insulin-sensitive obesity. Am J Physiol Endocrinol Metab. 2010;299:E506 –515. 7. Skurk T, Alberti-Huber C, Herder C, Hauner H. Relationship between adipocyte size and adipokine expression and secretion. J Clin Endocrinol Metab. 2007;92:1023–1033. 8. Sabanayagam C, Liew G, Tai ES, et al. Relationship between glycated haemoglobin and microvascular complications: is there a natural cut-off point for the diagnosis of diabetes? Diabetologia. 2009; 52:1279 –1289. 9. Cancello R, Henegar C, Viguerie N, et al. Reduction of macrophage infiltration and chemoattractant gene expression changes in white adipose tissue of morbidly obese subjects after surgery-induced weight loss. Diabetes. 2005;54:2277–2286. 10. Pories WJ, Swanson MS, MacDonald KG, et al. Who would have thought it? An operation proves to be the most effective therapy for adult-onset diabetes mellitus. Ann Surg. 1995;222:339 –350; discussion 350 –352. 11. Balkau B, Charles MA. Comment on the provisional report from the WHO consultation. European Group for the Study of Insulin Resistance (EGIR). Diabet. Med. 1999;16:442– 443. 12. R Development Core Team 2011 R: A Language and Environment for Statistical Computing Internet. Vienna, Austria: R Foundation for Statistical Computing; Available from: http://www.R-project. org. 13. Benjamini Y, Hochberg Y. Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing. J R Stat Soc Series B Stat Methodol. 1995;57:289 –300. 14. Thomas Lumley using Fortran code by Alan Miller 2009 leaps: regression subset selection Internet. Available from: http://CRAN.Rproject.org/package⫽leaps. 15. Ahn SM, Pomp A, Rubino F. Metabolic surgery for type 2 diabetes. Ann N Y Acad Sci. 2010;1212:E37– 45. 16. Adams ST, Salhab M, Hussain ZI, Miller GV, Leveson SH. Preoperatively determinable factors predictive of diabetes mellitus remission following Roux-en-Y gastric bypass: a review of the literature. Acta Diabetol. 2013;50:475– 478. 17. Laurencikiene J, Skurk T, Kulyté A, et al. Regulation of lipolysis in small and large fat cells of the same subject. J Clin Endocrinol Metab. 2011;96:E2045–2049. 18. Jo J, Shreif Z, Periwal V. Quantitative dynamics of adipose cells. Adipocyte. 2012;1:80 – 88. 19. Girousse A, Tavernier G, Valle C, et al. Partial inhibition of adipose tissue lipolysis improves glucose metabolism and insulin sensitivity without alteration of fat mass. PLoS Biol. 2013;11:e1001485. 20. Dutia R, Brakoniecki K, Bunker P, et al. Limited recovery of -cell function after gastric bypass despite clinical diabetes remission. Diabetes. 2014;63(4):1214 –23.
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Adipocyte Size Threshold Matters: Link with Risk of Type 2 Diabetes and Improved Insulin Resistance After Gastric Bypass Aurelie Cotillard, Christine Poitou, Adriana Torcivia, Jean-Luc Bouillot, Arne Dietrich, Nora Klöting, Cécile Grégoire, Karine Lolmede, Matthias Blüher, and Karine Clément Sorbonne Universities (A.C., C.P., K.C.), University Pierre et Marie Curie-Paris 6, UMR_S U1166, Nutriomics, F-75013 Paris, France; Institute of Cardiometabolism and Nutrition, ICAN, AP-HP (A.C., C.P., C.G., K.C.), Pitié-Salpêtrière hospital, F-75013 Paris, France; INSERM, UMR_S U1166 (A.C., C.P., K.C.), Nutriomics, F-75013 Paris, France; Assistance Publique-Hôpitaux de Paris (A.T.), Pitié-Salpêtrière hospital, Surgery Department, F-75013 Paris, France; Assistance Publique-Hôpitaux de Paris (J.-L.B.), Ambroise Paré Hospital, Surgery Department, F-92012 Boulogne-Billancourt, France; Department of Surgery (A.D.), University of Leipzig, 04003-04357 Leipzig, Germany; Department of Medicine (N.K., M.B.), University of Leipzig, 04003-04357 Leipzig, Germany; and Junior Research Group Animal Models (N.K.), IFB Obesity Diseases, University of Leipzig, 04003-04357 Leipzig, Germany; AdipoPhyt (K.L.), F-75013 Paris, France
Context: Adipocyte volume has been associated with insulin resistance and type 2 diabetes. Objective: Our purpose was to identify an adipocyte volume threshold linked with increased insulin resistance risk, and to examine its association with insulin resistance improvement after bariatric surgery. Setting and Design: We investigated two cohorts of Caucasian women, candidates for bariatric surgery, from two institutional centers in France (age 42.0 ⫾ 11.5 years; body mass index, 47.6 ⫾ 6.9 kg/m2) and Germany (age 41.3 ⫾ 11.2 years; body mass index, 49.5 ⫾ 8.1 kg/m2). 38% of the subjects had gastric bypass surgery and were followed for 6 months after the intervention. We defined a group of subjects with type 2 diabetes or at risk of type 2 diabetes (DRD) and investigated the relations between adipocyte volume and this status before and after surgery. Results: In both cohorts, subjects with DRD presented enlarged adipocytes (France, P ⫽ 3⫻10⫺4; Germany, P ⫽3⫻10⫺10) and we were able to determine thresholds in each cohort above which diabetes risk was potentially increased (France: 1003⫾42 pL, Germany: 798⫾32 pL). Subjects above those adipocyte thresholds were less prone to disappearance of the DRD status after bypass surgery (France, risk ratio ⫽ 2.1, P ⫽ .024; Germany, risk ratio ⫽ 1.3, P ⫽ .05). Conclusions: We show in two cohorts of morbidly obese subjects that a specific adipocyte volume threshold may predict an increased risk for obesity-associated type 2 diabetes. However, this threshold might be established for each specific investigation site. Having a high adipocyte size is associated with a lower improvement of insulin resistance after bypass surgery in both cohorts. (J Clin Endocrinol Metab 99: E1466 –E1470, 2014)
besity is characterized by an increased accumulation of fat mass, which can happen through an increase of adipocyte volume (hypertrophy) or number (hyperpla-
O
sia) (1). The expansion of sc adipose tissue affects adipocyte cell biology and eventually whole-body glucose homeostasis. Adipocyte hypertrophy per se is also seen as a
ISSN Print 0021-972X ISSN Online 1945-7197 Printed in U.S.A. Copyright © 2014 by the Endocrine Society Received January 9, 2014. Accepted April 22, 2014. First Published Online April 29, 2014
Abbreviations: DRD, diabetic or at risk for diabetes; HAV, high-adipocyte volume; HOMAIR, homeostatic model assessment for insulin resistance.
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J Clin Endocrinol Metab, August 2014, 99(8):E1466 –E1470
doi: 10.1210/jc.2014-1074
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doi: 10.1210/jc.2014-1074
key event associated with in vitro and in vivo loss of insulin sensitivity in lean and obese conditions (2– 6). Subjects with larger adipocytes have a higher incidence for elevated levels of proinflammatory factors including leptin, IL-6, and IL-8 (7), and reduced levels of adiponectin, an adipokine associated with insulin-sensitivity (4). In obese subjects, hypertrophy seems thus associated with a deleterious effect on metabolism and inflammation. Quantitative associations have been found between adipocyte volume and insulin resistance, but there is no described threshold in adipocyte volume above which diabetic risk may accelerate significantly. Such thresholds have been investigated when looking at HbA1c and microvascular complications (8) and can be of major clinical interest to detect patients without obvious clinical symptoms and be able to adapt their therapy. Moreover, a way of modulating efficiently adipocyte cell size and improving insulin resistance is bypass surgery also well known to improve obesity comorbidities, including type 2 diabetes (9, 10). This observational study was conducted in two French and German cohorts of morbidly obese subjects candidates for bypass surgery to i) identify an adipocyte volume threshold potentially associated with increased insulin resistance and, ii) examine if adipocyte volume could be involved in improvement of insulin resistance after bypass surgery. To take into account subjects already presenting high insulin resistance, we defined a class including subjects who were diabetic or at risk for diabetes (DRD).
Materials and Methods Two cohorts of European morbidly obese women The French and German cohorts consisted respectively of 217 and 78 Caucasian women involved in bariatric surgery programs (Supplemental Methods). Sixty eight (31.3%) of the French subjects and 25 (32.1%) of the German subjects had type 2 diabetes with fasting glycemia greater than 7 mmol/L and/or the use of an antidiabetic drug (Supplemental Methods). In 37 (13, respectively) nondiabetic subjects in the French (German, respectively) cohort, the homeostatic model assessment for insulin resistance (HOMA-IR) values was greater than 5.384 (3.55, respectively) (75th percentile). These subjects were considered at risk for diabetes as previously proposed (11). We thus defined a class regrouping these 105 (French) and 38 (German) diabetic or at risk for diabetes (DRD) subjects (48.4% of the French cohort and 48.7% of the German cohort). Among them, 79 French subjects and 33 German subjects underwent gastric bypass surgery and were followed for 6 months after the intervention. Using the same criteria and the same HOMA-IR threshold as before surgery, we defined DRD subjects 6 months after surgery. Resolution was considered as the switch from DRD before surgery to non-DRD after surgery. Anthropometric and biochemical parameters were measured as described in Supplemental Methods.
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Statistical analysis Values are expressed as mean ⫾ SD and all statistics were performed using the R software (12). Statistical tests were twotailed. When required, P values were adjusted for multiples tests by Benjamini-Hochberg correction (13). A threshold of .05 was applied for statistical significance. Differences between both cohorts, and between DRD and non-DRD subjects were evaluated using Student t tests. Prevalence of DRD status in the exposure group (high adipocyte size) was plotted against adipocyte volume thresholds. The curve was fitted using nonlinear least square regression by a logistic function. The adipocyte threshold for maximal speeding up in diabetes risk was defined as the point of maximal acceleration of the curve (Supplemental Methods). Differences between subjects solving or not their DRD status were evaluated using non parametric statistics due to the small number of subjects in the German cohort. Mann-Whitney-Wilcoxon tests were used for quantitative variables, and Fisher exact tests were used for qualitative variables. We further investigated these relationships in the French cohort using univariate or multivariate linear models. Diabetes duration value for nondiabetic subjects was set to ⫺1. Model selection was performed using exhaustive search with the R leaps library (14).
Results Anthropometric and biochemical characteristics Anthropometric and biochemical characteristics of the subjects are shown in Table 1. The proportion of DRD women was comparable in both cohorts and approximately 50%. No differences between cohorts were observed regarding age, fat mass, or mean adipocyte volume. However, differences were observed depending on the DRD status (Table 1). Non-DRD German women had a healthier profile with lower fat mass and adipocyte volume compared with nonDRD French women. They presented higher adiponectin and high-density lipoprotein cholesterol levels with lower insulin and HOMA-IR values. Contrastingly, DRD German subjects were significantly heavier with a poorer cholesterol profile. However, they had decreased diabetes duration, better blood glucose control (HbA1c values), and none of them received insulin treatment (Supplemental Methods). In both cohorts, DRD subjects were older and more insulin resistant (HOMA-IR), with larger adipocytes (⫹12% and ⫹29% in the French and German cohorts respectively). However, the distribution of adipocyte volume in the German cohort was more compact with less extremely high values compared with the French cohort. Importantly, the distribution profiles of DRD and non-DRD subjects differed between cohorts, all German subjects with an adipocyte volume above 1000 pL being DRD (Supplemental Figure 1). An adipocyte volume threshold for acceleration in risk of diabetes To investigate the existence of a threshold above which the increase in diabetes risk accelerates substantially in
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Table 1.
Adipocyte Size Threshold and Insulin Resistance
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Anthropometric and Biochemical Characteristics of the Subjects in Both Cohorts French Cohort
German Cohort
Characteristic
Non-DRD
DRD
Non-DRD
DRD
n Age, y Adiposity markers Body weight, kgb Body mass index (kg/m2) Fat mass, kg Adipocyte volume, pL No. of adipocytes Leptin, ng/mL Plasma glucose homeostasis and insulin sensitivity Glucose, mmol/L Insulin, UI/mL HOMA-IR HbA1c (%)b (mmol/mol) Adiponectin, g/mL Diabetes duration, y Plasma lipid homeostasis Total cholesterol, mmol/L High-density lipoprotein cholesterol, mmol/L Triglycerides, mmol/L Inflammatory markers IL-6, pg/mLb hs-CRP, mg/L
112 38.34 ⫾ 10.39
105 45.87 ⫾ 11.49a
40 36 ⫾ 8.86
38 46.92 ⫾ 10.74a
125.41 ⫾ 19.12 46.74 ⫾ 6.77 58.62 ⫾ 11.19 883.75 ⫾ 157.36 7.6e13 ⫾ 2.1e13 57.48 ⫾ 25.49
128.23 ⫾ 20.46 48.45 ⫾ 7.05 59.04 ⫾ 11.7 989.75 ⫾ 231.69a 6.8e13 ⫾ 1.9e13a 51.41 ⫾ 26.96
127.2 ⫾ 17.43 45.98 ⫾ 5.36 52.18 ⫾ 10.76c 788.83 ⫾ 114.94c 7.3e13 ⫾ 1.3e13 46.99 ⫾ 8.91c
145 ⫾ 27.39ac 53.25 ⫾ 8.87ac 67.29 ⫾ 16.98ac 1015.79 ⫾ 140.87a 7.4e13 ⫾ 2.2e13 58.68 ⫾ 15.58a
5.05 ⫾ 0.55 14.07 ⫾ 5.48 3.14 ⫾ 1.21 5.67 ⫾ 0.32 (38 ⫾ 3.5) 6.49 ⫾ 2.91 NA
7.19 ⫾ 2.26a 26.19 ⫾ 15.35a 8.18 ⫾ 5.25a 7.08 ⫾ 1.84a (54 ⫾ 20.1) 4.92 ⫾ 2.69a 4.69 ⫾ 5.19
5.24 ⫾ 0.42 5.61 ⫾ 4.44c 1.32 ⫾ 1.07c 5.67 ⫾ 0.89 (38 ⫾ 9.7) 7.87 ⫾ 1.96c NA
7.24 ⫾ 2.34a 29.13 ⫾ 16.05a 9.38 ⫾ 5.45a 6.41 ⫾ 0.89ac (47 ⫾ 9.7) 5.13 ⫾ 2.73a 2.52 ⫾ 2.56c
4.92 ⫾ 0.82 1.3 ⫾ 0.36 1.32 ⫾ 0.55
4.72 ⫾ 0.91 1.19 ⫾ 0.36 1.82 ⫾ 0.89a
4.95 ⫾ 0.92 1.44 ⫾ 0.19c 1.57 ⫾ 0.61
5.31 ⫾ 1.07c 0.99 ⫾ 0.26ac 1.74 ⫾ 0.78
3.38 ⫾ 1.99 10.86 ⫾ 8.04
4.37 ⫾ 3.09a 10.64 ⫾ 8.58
6.67 ⫾ 4.34c 13.42 ⫾ 18.88
6.56 ⫾ 3.7c 10.21 ⫾ 8.11
hs-CRP, high-sensitivity C-reactive protein; NA, not available. Values are expressed as mean ⫾ SD. a
P ⬍ .05 between DRD subjects and non-DRD subjects.
b
P ⬍ .05 between both cohorts.
c
P ⬍ .05 between both cohorts for a given DRD status.
both or each cohort, we considered the prevalence of the DRD status above a given value of adipocyte volume. This prevalence significantly increased with adipocyte volume and the curve was well fitted by a logistic function in both cohorts (Figure 1, A and B). The curve presented a maximal acceleration for an adipocyte volume of 1003 ⫾ 42 pL in the French cohort and a lower value of 798 ⫾ 32 pL in the German cohort (Materials and Methods). Subjects above those adipocyte volume thresholds will henceforth be denoted high-adipocyte volume (HAV) subjects. The risk ratio associated with DRD in the HAV group was 1.38 with P ⫽ .027 (4.88, respectively; P ⫽ 5⫻10⫺5) in the French (German, respectively) cohort. Whereas this threshold objective was not status prediction (AUC ⫽ 0.61 in the French cohort with logistic regression), its main purpose was to detect subjects that may be at higher risk of developing type 2 diabetes or insulin resistance. Considering that HAV non-DRD subjects should be followed with more care, 26 (20, respectively) patients were concerned in the French (German, respectively) cohort.
the French cohort, this percentage of resolution differed depending on basal adipocyte volume: 86% in the non-HAV subjects and 62% in the HAV subjects (P ⫽ .024, risk ratio ⫽ 2.1). Concordantly, the adipocyte volume was significantly higher in the nonsolved group (Figure 1, C and D). A similar trend was observed in the smaller German cohort (P ⫽ .05, risk ratio ⫽ 1.3). Using all clinical variables associated with the DRD status (Supplemental Table 1) in addition to diabetes duration, we built univariate models in the French cohort to predict DRD status resolution. The best model was obtained with diabetes duration and the next best models included HbA1c, adipocyte volume, glucose level, and age (Supplemental Figure 2A). With model selection on these five parameters, adipocyte volume was included when using an adjusted r2 criterion, but not with a bayesian information criteria (Supplemental Figure 2, B and C). Small differences between qualities of the models underline a nonstable model selection, but these results suggest a role of adipocyte size in DRD status resolution after bypass.
Adipocyte volume associates with resolution of DRD status after gastric bypass Six months after bypass, 61 French women (77%) and only 13 German women (39%) resolved their DRD status. In
Discussion Here we were able to show that the concept of an adipocyte size threshold for determining an increase risk of
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mental triggers (such as food patterns or physical activity) and criteria for treatments might differ. Even if all subjects were of Caucasian origin, there might still be some genetic differences explaining these discrepancies. Most importantly, having a large adipocyte size was associated with a lower incidence of remission of the insulin resistance state 6 months after bypass surgery in both cohorts. When taking into account usual predictors such as blood glucose hoc d meostasis or diabetes duration, adipocyte volume was still of importance, even if its role is difficult to evaluate in a context where variables are strongly interrelated. It could be of interest to identify these subjects with less improvement of their metabolic state after bypass surgery, particularly in the context of metabolic surgery dedicated to patients with an altered metabolic status but not the body mass index cut-off for bariatric surgery. Clinical and indiFigure 1. DRD status before and after surgery in association with adipocyte volume. A) and B): vidual variables have been proposed prevalence of DRD subjects above each threshold of adipocyte volume in the French cohort A) as putative predictors of improveand in the German cohort B). A logistic function (black line) was fitted on the gray curve. The dashed line stands for the maximum acceleration in the increase of diabetes risk. The gray ment of insulin resistance and parhistogram illustrates the distribution of adipocyte volume in the population. RSE: residual SE for ticularly age and history of diabetes the sigmoid fit. C) and D): Adipocyte volume in subjects solving or not their DRD status in the (16). Here we suggest that adipocyte French cohort C) and in the German cohort D). **, P ⬍ .01; #, P ⬍ .1. volume should be considered when looking for predictors or explanainsulin resistance could be replicated in two cohorts of tions for insulin resistance improvement and/or diabetes French and German Caucasian women, candidates for remission after bariatric surgery. Its contribution may be bariatric surgery. This threshold was identified in severe small and linear modeling has limitations, but pieces of obesity and it could be interesting to extend this measure evidence linking adipocyte volume to insulin resistance in less obese but diabetic subjects undergoing metabolic suggest biological relevance. This stimulates the interest in surgery (15). The purpose of this threshold being to detect testing this variable in different bariatric surgery populasubjects who may be at higher risk of developing type 2 diabetes or insulin resistance, an additional step would be tions. In 2011, Laurencikiene et al (17) showed that more to validate its use in a prospective cohort study with a lipolysis occurs in larger adipocytes, and that it might link longer-term follow-up. Whereas a threshold was clearly adipocyte hypertrophy to the risk of developing type 2 identified, it is remarkable that the thresholds were dif- diabetes, although these results were not consistent with a ferent in the two cohorts. This difference was partly ex- prediction model established by Jo et al (18). It has also plained by method differences in adipocyte size measure- been recently suggested that it might be possible to imments (systematic comparison of the two methods in prove insulin sensitivity by reducing adipocyte lipolysis Supplemental Information). The cohorts also presented (19), raising the hope of treatments for those subjects with different clinical characteristics depending on their DRD HAV. Although we demonstrated the concept of an adipocyte status, and adipocyte volume distribution profiles of DRD and non-DRD subjects were different between both co- size threshold for increased risk of insulin resistance, difhorts. Whereas both countries follow similar international ferent thresholds were obtained in the two cohorts due to criteria for bypass surgery, national specificity of environ- biological and technical variations, underlying the limita-
a
b
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Adipocyte Size Threshold and Insulin Resistance
tion that this critical threshold should be determined in each given population and depending of the technique used for cell size measurement. This association between an adipocyte threshold and increased risk of insulin resistance should, however, not mislead to think that subjects below this threshold are risk free of developing carbohydrate intolerance. In addition, insulin resistance was evaluated using the HOMA-IR, which accounts for the glucose toxicity component of insulin resistance, but not for the lipid-toxicity component. Finally, the DRD status that we used is a composite group including nondiabetic insulin-resistant subjects and diabetic subjects with or without medication. Although both represent insulin-resistant states, resolution of diabetes does not necessarily only depends on improvement of insulin resistance, but also on  cell reserve (20). Specific studies focusing on larger cohorts of only diabetic or nondiabetic insulin-resistant subjects with longer-term follow-up will be useful.
Acknowledgments We thank Dr Florence Marchelli and Valentine Lemoine (APHP), Pitié-Salpêtrière, Paris, for the constitution of the database; and Jean-François Bedel, Jenifer Alban, and Patricia Ancel, Pitié-Salpêtrière, Paris, for measuring in routine adipocyte size. We thank the LNC laboratory for providing the data presented in the Supplemental Information. Address all correspondence and requests for reprints to: Karine Clément, Institute of Cardiometabolism and Nutrition, Hôpital Pitié-Salpêtrière, 75013 Paris, France. E-mail: [email protected]. This work was supported by the Emergence Program (Université Pierre et Marie Curie), PHRC 02076 (Assistance Publique des Hôpitaux de Paris), CRC FIBROTA (Direction of Clinical Research), ANR Fibrota and the national program “Investissements d’avenir” with the reference ANR-10-IAHU-05 (National Agency of Research and Fondation pour la Recherche Médicale), Kompetenznetz Adipositas (Competence network for Obesity, German Obesity Biomaterial Bank, GOBB) funded by the Federal Ministry of Education and Research (FKZ 01GI1128, FKZ 01EO1001 to N.K.), grant from Deutsche Forschungsgemeinschaft the SFB 1052: “Obesity mechanisms (project B1 to M.B. and B4 to N.K.). K.C. and A.C. received a grant from Roche company. French and German teams received a grant from EU Metacardis program (FP7). Disclosure Summary: The authors have nothing to disclose.
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