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The Journal of Clinical Endocrinology & Metabolism Vol. 89, No. 3 1096-1101
Copyright © 2004 by The Endocrine Society

Validation of Insulin Sensitivity Indices from Oral Glucose Tolerance Test Parameters in Obese Children and Adolescents

Catherine W. Yeckel, Ram Weiss, James Dziura, Sara E. Taksali, Sylvie Dufour, Tania S. Burgert, William V. Tamborlane and Sonia Caprio

Department of Pediatrics (C.W.Y., R.W., S.E.T., T.S.B., W.V.T., S.C.), and Children’s and Adult General Clinical Research Centers (J.D.); and Howard Hughes Medical Institute (S.D.), Yale University School of Medicine, New Haven, Connecticut 06520

Address all correspondence and requests for reprints to: Dr. Sonia Caprio, Department of Pediatrics, Yale University School of Medicine, P.O. Box 802064, New Haven, Connecticut 06520. E-mail: sonia.caprio{at}yale.edu.


    Abstract
 Top
 Abstract
 Introduction
 Subjects and Methods
 Results
 Discussion
 References
 
Given the extreme increase in prediabetes, type 2 diabetes, and the potential for metabolic syndrome in obese youth, identifying simplified indexes for assessing stimulated insulin sensitivity is critical. The purpose of this study was validation of two surrogate indexes of insulin sensitivity determined from the oral glucose tolerance test (OGTT): the composite whole body insulin sensitivity index (WBISI) and the insulin sensitivity index (ISI). An obese population (aged 8–18 yr) of normal and impaired glucose tolerance individuals was studied. One group (n = 38) performed both the euglycemic-hyperinsulinemic clamp and OGTT for comparison of insulin sensitivity measurements as well as 1H-magnetic resonance spectroscopy estimates of intramyocellular lipid content. Another larger (n = 368) cohort participated only in an OGTT. Both the WBISI and ISI represented good estimates (r = 0.78 and 0.74; P < 0.0005) for clamp-derived insulin sensitivity (glucose disposed, M-value), respectively. In the large cohort, the surrogate indexes demonstrated the shift toward poorer function and increased risk profile as a function of insulin resistance. Additionally, the WBISI and ISI correlated with intramyocellular lipid content (r = -0.74 and -0.71; P < 0.0001), a tissue marker for insulin resistance. Insulin sensitivity can be estimated using plasma glucose and insulin responses derived from the OGTT in obese youth with normal and impaired glucose tolerance.


    Introduction
 Top
 Abstract
 Introduction
 Subjects and Methods
 Results
 Discussion
 References
 
THE MARKED INCREASE in pediatric obesity over the last decade has resulted in an unprecedented rise in the incidence of type 2 diabetes mellitus in both children and adolescents (1). Even more worrisome is the recent observation that 22–25% of children and adolescents with severe obesity are prediabetic, as defined by American Diabetes Association criteria for impaired glucose tolerance (2). Subsequent studies in this cohort have demonstrated that youth with prediabetes have the most severe insulin resistance (3). Low insulin sensitivity in adults has also been linked to other metabolic syndrome-related characteristics, such as hypertension and dyslipidemia (4). Both adult (5, 6) and pediatric (7) obese individuals have been shown to accumulate intramyocellular lipid in direct relation to the degree of insulin resistance. This accumulation of intramyocellular lipid is believed to play a role in mediating peripheral insulin resistance (8, 9).

The primary means for measuring insulin sensitivity is the euglycemic-hyperinsulinemic clamp technique (10). Another common method is to use a frequent-sample iv glucose tolerance test, performing the minimal model assessment of insulin sensitivity (11, 12). However, both of these methods are labor intensive, costly, and relatively invasive. The homeostasis model assessment-insulin resistance (HOMA-IR) is based on measurement of fasting glucose and insulin levels and has been widely used to express insulin resistance across diverse populations (13). Although the HOMA-IR benefits from its practicality, it is based on measurements of basal glucose and insulin, whereas the insulin resistance of obesity is primarily due to an impairment of stimulated insulin concentrations to increase peripheral glucose uptake.

Two other insulin sensitivity indexes have been demonstrated in adults to have a high degree of correlation with the euglycemic-hyperinsulinemic clamp-derived M-values for stimulated insulin sensitivity. Both indexes use parameters obtained from a standard oral glucose tolerance test (OGTT): 1) the whole body insulin sensitivity index (WBISI), developed by Matsuda and DeFronzo and validated in adults (14); and 2) the insulin sensitivity index (ISI), developed by Soonthornpun et al. (15). Neither index has been validated in children or adolescents. As the OGTT can also be used for estimation of the first phase insulin responses to a glucose challenge (insulinogenic index), parameters derived solely from the OGTT can be used to generate feedback curves representing the relationship between insulin secretion and insulin sensitivity (16).

The present study was undertaken to validate the WBISI and ISI indexes to assess insulin sensitivity in a high risk obese pediatric population of diverse ethnic background with normal and impaired glucose tolerance. The insulin sensitivity indexes derived from the OGTT were examined in light of their ability to provide insight into the feedback relationship between insulin secretion and insulin sensitivity as well as to correlate the degree of insulin sensitivity with intramyocellular lipid accumulation. We also explored the potential use of these surrogates in the broader context of defining the metabolic risk profile of youth with moderate to severe obesity.


    Subjects and Methods
 Top
 Abstract
 Introduction
 Subjects and Methods
 Results
 Discussion
 References
 
Study population

All children and adolescents were recruited from the Yale Pediatric Weight Management Clinic. A detailed medical and family history was obtained from all subjects, and a physical examination was performed. All subjects were in good health and had normal thyroid function. The study protocols were approved by the institutional review board of Yale University School of Medicine. Written parental consent and child assent were obtained before the study.

For the validation studies, two separate groups of obese children and adolescents (aged 8–18 yr) were studied using both the OGTT and the euglycemic-hyperinsulinemic clamp procedures: 26 with normal glucose tolerance (NGT) and 12 with impaired glucose tolerance (IGT). Additionally, we studied 312 NGT and 56 IGT subjects using only a standard 75-g OGTT. Body mass index (BMI) was calculated as weight in kilograms divided by height in meters squared. All subjects had a BMI above the 95th percentile for age and sex and thus were classified as obese (17). Based on the year 2000 growth charts, this category of BMI is referred to as overweight by the Centers for Disease Control. Table 1Go provides the gender and ethnic makeup of the study cohorts along with basic demographic data. Data more specifically comparing NGT and IGT pathophysiology in many of the subjects participating in the clamp procedures have been presented previously (3). In this study NGT and IGT comparisons were made to emphasize the ability of OGTT-derived indices to discern group differences in insulin sensitivity.


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TABLE 1. Clinical and metabolic phenotype of children and adolescents with NGT and IGT

 
Testing procedures

OGTT. A standard [1.75 g/kg body weight (up to 75 g)] OGTT was performed in all children and adolescents to establish glucose tolerance status. Subjects were studied at Children’s Clinical Research Center of Yale University School of Medicine at 0800 h after a 10- to 12-h overnight fast. After the local application of a topical anesthetic cream containing 2.5% lidocaine and 2.5% prilocaine, one antecubital iv catheter was inserted for blood sampling and was maintained patent by a normal saline drip. Two baseline samples were then obtained at -15 and 0 min for measurements of plasma glucose and insulin. Thereafter, the flavored glucose (Orangedex, Custom Laboratories, Baltimore, MD) was given orally, and blood samples were obtained every 30 min for 180 min for measurements of plasma glucose and insulin. IGT was defined, according to American Diabetes Association guidelines, as a 2-h blood glucose level of 140–200 mg/dl (7.8 mmol/liter).

Euglycemic-hyperinsulinemic clamp. The clamp studies were carried out at either the Yale Children’s Clinical Research Center or General Clinical Research Center beginning at 0730 h after an overnight fast of 10–12 h as previously described (3). The procedure required two iv catheters: one was used for blood sampling (arterialized by heating the hand), and the other (antecubital) was used for the infusion of insulin and 20% dextrose solutions. The catheters were placed under local anesthetic (1% buffered lidocaine). Thereafter, [2H2]glucose was administered as a prime-constant infusion (11 µmol/m2·min) starting 180 min before beginning the insulin infusion. Samples for fasting glucose and insulin measurements were taken during the final 40 min before the start of the euglycemic-hyperinsulinemic clamp (insulin rate equal to 80 mU/m2·min). Euglycemia was maintained at each subject’s resting glucose concentration with a variable infusion of 20% dextrose and was monitored every 5–10 min for 120 min of the clamp. Glucose infusion rates for insulin sensitivity measurements were taken during the final 40 min of the 120-min clamp period.

1H-magnetic resonance (MR) spectroscopy (1H-MRS) of intramyocellular lipid (IMCL). Localized 1H-MRS spectra of the soleus muscle were acquired on a 2.1 T Biospec system (Bruker Instruments, Inc., Billerica, MA), as previously described (7). The 1H-MRS method to quantify IMCL measures the relative intensity of the methylene [(CH2)n-; 1.25 parts/million] resonance with that of water (6). The investigator who performed and analyzed the data for IMCL was blinded to the clinical status of the subjects.

Biochemical analyses. Plasma glucose was determined using a glucose analyzer by the glucose oxidase method (Beckman Instruments, Brea, CA). Plasma insulin was measured by RIA (Linco Research, Inc., St. Charles, MO) with less than 1% cross-reactivity with C peptide and proinsulin.

Calculations

Basal insulin resistance measurement. The HOMA-IR was calculated as follows: HOMA-IR = FI x FG divided by 22.5, where FI is the fasting insulin concentration (microunits per milliliter) and FG is the fasting glucose level (millimoles per liter). Lower HOMA-IR values indicate greater insulin sensitivity, whereas higher HOMA-IR values indicate lower insulin sensitivity (insulin resistance).

Indexes of insulin sensitivity from the OGTT. The composite WBISI is based on values of insulin (microunits per milliliter) and glucose (milligrams per deciliter) obtained from the OGTT and the corresponding fasting values, as originally described by Matsuda and DeFronzo (14). Similarly, the ISI uses parameters from the OGTT as developed by Soonthorpun and colleagues (15):

where ISI = [1.9/6 x body weight (kg) x fasting plasma glucose (mmol/liter) + 520 - 1.9/18 x body weight x area under curve for glucose (mmol/h·liter) — urinary glucose (mmol/1.8)]/[area under curve for insulin (pmol/h·liter) x body weight].

Euglycemic-hyperinsulinemic clamp measurement of insulin sensitivity

M-value of insulin sensitivity. The traditional means for assessing insulin sensitivity is based on the euglycemic-hyperinsulinemic clamp (10): M-value = INF - UC - SC, where INF is the necessary infusion rate (milligrams per meter squared per minute) of glucose to maintain the euglycemic clamp, UC is the correction for urinary loss of glucose, and SC is the space constant, which adjusts for the changes in glucose concentration during the clamp.

ß-Cell function for hyperbolic plots. The insulinogenic index (IGI), a commonly used index of ß-cell function, was also calculated from the OGTT data: IGI = {delta} insulin (0–30 min) in microunits per milliliter divided by the {delta} glucose (0–30 min) in milligrams per deciliter.

Statistical analysis

All analyses were performed using SAS version 8.02 (SAS Institute, Cary, NC). Data are expressed as the mean ± SEM or as a percentage where appropriate. We tested differences between clamp and OGTT-only groups using {chi}2 analysis, two-tailed unpaired t tests, or Mann-Whitney U tests as appropriate. Demographic and metabolic OGTT-derived insulin sensitivity indexes were compared with M-values from the euglycemic-hyperinsulinemic clamp using Pearson correlation coefficients, and the resulting correlated correlation coefficients were compared using the method described by Meng et al. (18). We compared metabolic risk factors across levels of insulin sensitivity by ANOVA with Tukey’s post hoc testing. Hyperbolic feedback curves were estimated, and the effect of glucose tolerance status was evaluated by a general linear model with secretion regressed on sensitivity after log transformation of both secretion and sensitivity indexes.


    Results
 Top
 Abstract
 Introduction
 Subjects and Methods
 Results
 Discussion
 References
 
There were no significant differences between characteristics comparing the clamp and OGTT-only groups in each category of glucose tolerance. As shown in Table 1Go, there were also no differences in the clamp and OGTT-only groups for fasting and oral glucose-stimulated plasma glucose and insulin levels during the OGTT in each category of oral glucose tolerance.

Indexes of insulin sensitivity

Using the euglycemic-hyperinsulinemic clamp to measure insulin-stimulated glucose metabolism (M-value; see Subjects and Methods), we observed a significant difference in insulin sensitivity between the NGT and IGT obese children and adolescents [M-value, 266 ± 23 14 mg/m2·min (1.48 mmol/m2·min) and 178 ± 14 mg/m2·min (0.99 mmol/m2·min) in NGT and IGT groups, respectively; P < 0.025; Table 2Go]. The insulin sensitivity indexes derived from the OGTT for both the clamp and OGTT-only groups are also shown in Table 2Go. For the small clamp group, we identified significant differences between the NGT and IGT subjects for all indexes, except the ISI, which was of borderline significance (P = 0.055). In the larger OGTT-only group, all indexes were able to detect significant differences between the NGT and IGT subjects.


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TABLE 2. Indexes of insulin sensitivity

 
Relationship between HOMA, WBISI, and ISI indexes of insulin sensitivity and M-values in the clamp group

Using the M-values from the euglycemic-hyperinsulinemic clamp as the accepted means for expressing insulin sensitivity, we next examined the relationship between M-values and HOMA-IR, WBISI, and ISI. As shown in Fig. 1Go, we found a direct linear correlation between M-values and each of the other three indexes of insulin sensitivity examined. The correlation between M-value and WBISI (r = 0.78) was significantly greater than the correlation between M-values and HOMA-IR (r = -0.57). The ISI was similar in magnitude to the WBISI (r = 0.74), but this correlation was not statistically better than that of the HOMA.



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FIG. 1. Relationships between the euglycemic-hyperinsulinemic M-value and the HOMA-IR index of insulin resistance (top) and the OGTT-derived indexes of insulin sensitivity, WBISI (middle) and ISI (bottom). All relationships were significant (P < 0.005). The WBISI correlation was significantly better than that of the HOMA-IR (P < 0.01). {square}, NGT individuals; {blacksquare}, IGT individuals. The M-value is the term used to indicate the level of insulin sensitivity: the amount of glucose required to sustain euglycemia during hyperinsulinemia. HOMA-IR is based on basal glucose and insulin values only. The WBISI and the ISI are indexes of insulin-stimulated sensitivity.

 
Stratification of the OGTT-only subjects by the WBISI

As the WBISI was the most robust index of insulin sensitivity, we next divided NGT subjects in the large OGTT-only group into tertiles of insulin sensitivity based on the WBISI. Comparisons between metabolic profiles were made between the subjects in each NGT tertile and simultaneously compared with the metabolic profile of the IGT subjects. As shown in Table 3Go, NGT subjects in the lowest tertile of insulin sensitivity were as insulin resistant as IGT subjects. Moreover, severely insulin-resistant NGT and IGT subjects did not differ significantly in any metabolic category except for high density lipoprotein (HDL), plasma glucose levels at 120 min, and the insulinogenic index. The insulinogenic index was significantly augmented in these resistant NGT subjects vs. the IGT and most sensitive NGT subjects (P < 0.05). IGT and severely resistant NGT subjects also had significantly higher plasma triglyceride concentrations and lower HDL levels than the more insulin-sensitive NGT subjects (Table 3Go).


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TABLE 3. Metabolic risk profile based on level of insulin sensitivity

 
Using the WBISI to examine the feedback relationship between ß-cell function and insulin sensitivity in the obese pediatric population

The IGI is another parameter derived from the OGTT and is widely used to estimate first phase insulin secretion. The hyperbolic functions that describe the relationships between ß-cell function (IGI) vs. insulin sensitivity (as assessed by the WBISI and ISI) are shown in Fig. 2Go. The curve relating insulin responses to insulin sensitivity was significantly shifted to the left in IGT vs. NGT subjects (P < 0.0001).



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FIG. 2. Hyperbolic feedback curves using the WBISI (top) and the ISI (bottom) indexes as the surrogates for insulin sensitivity. The insulinogenic index provides the estimation of ß-cell function. A significant leftward shift was detected among the IGT population relative to the NGT for both indexes (P < 0.0001). {square}, NGT individuals; {blacksquare}, IGT individuals.

 
Using the WBISI to examine the relationship between insulin sensitivity and intramyocellular lipid accumulation

There was a strong relationship between the WBISI (r = -0.74; P < 0.0001) and ISI (r = -0.71; P < 0.0001) and the degree of intramyocellular lipid accumulation (Fig. 3Go).



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FIG. 3. The relationship between composite WBISI (top) and ISI (bottom) indexes for insulin sensitivity and the quantity of IMCL as a percentage of the water resonance peak by 1H-MRS for 29 of the clamp group participants. The linear regressions were significant (P < 0.0001) based on the log-log transformation of data for both indexes. {square}, NGT individuals; {blacksquare}, IGT individuals.

 

    Discussion
 Top
 Abstract
 Introduction
 Subjects and Methods
 Results
 Discussion
 References
 
The present study demonstrates that insulin sensitivity can be estimated using plasma glucose and insulin responses derived from the OGTT in obese children and adolescents. Using M-values derived from the euglycemic-hyperinsulinemic clamp as the accepted means of expressing insulin sensitivity, the ISI (r = 0.74) and WBISI (r = 0.78) yielded a high level of agreement. The WBISI was significantly better correlated with M-values than the widely used HOMA-IR. The relationship between M-values and WBISI in our obese children was similar to that reported in validation studies in adults across a wide range of insulin sensitivities (14). We would anticipate a slight drop in correlation [closer to that reported in the adult (14)] if more overweight than lean subjects were studied due to the increase in expected variability of insulin sensitivity in these individuals. The ISI has not previously been validated in obese or insulin-resistant pediatric or adult subjects. It is particularly noteworthy that with all four methods of assessment in this study, insulin sensitivity was substantially reduced in IGT compared with NGT subjects in the OGTT-only group.

Although OGTTs are more difficult to perform than simple measurements of fasting glucose and insulin levels, the OGTT is a minimal risk procedure that is applicable for large scale screening and for repeated studies in individual subjects. An added advantage of the OGTT is that it simultaneously provides a means to identify youth with IGT or even frank diabetes (2). Consequently, the WBISI and ISI that are derived from the OGTT appear to be useful outcome measures for clinical trials in obese children and adolescents that are directed at improving insulin sensitivity and glucose tolerance. In adults with type 2 diabetes, the WBISI was used effectively to characterize a dose-response relationship during treatment with pioglitazone (19).

There were a number of individuals in the NGT group who had WBISI values that overlapped with those in the IGT group. Interestingly, these severely insulin-resistant NGT subjects were similar to the IGT group in terms of most other metabolic parameters, except, of course, plasma glucose at 120 min [116 mg/dl (6.4 mmol/liter) in NGT vs. 155 mg/dl (8.6 mmol/liter) in IGT]. Preservation of NGT in these severely resistant youth may be due to their ability to increase early plasma insulin responses to a glucose challenge. Indeed, these NGT individuals had an augmented insulinogenic index compared with the IGT and the most insulin-sensitive tertile of NGT subjects (P < 0.05). Although both the IGT and resistant NGT groups were dyslipidemic compared with the more insulin-sensitive NGT individuals, the IGT cohort was found to have HDL levels further reduced from the most resistant NGT cohort.

A major advantage to using the WBISI or ISI and the insulinogenic index from the OGTT is the ability to use these assessments to construct feedback relationship curves that relate insulin sensitivity to ß-cell responsiveness. This hyperbolic relationship, first proposed by Bergman (20) and later validated by Kahn (16), has generally used a minimal model-based index for sensitivity or the M-value from a clamp. In this study we demonstrated that the feedback curves can also be produced directly from data derived from the OGTT without having to perform the more intensive clamp or modeling experiments.

The insulinogenic index itself is a useful index of insulin secretory capacity. Nevertheless, interpretation of the insulinogenic response is fraught with problems of interpretation in severely insulin-resistant subjects, because values for both normal and impaired function can coexist in the same range. In contrast, feedback relationship curves provide a less ambiguous framework for assessing insulin secretion in the context of altered insulin sensitivity. We found a distinct leftward shift in the distribution between the NGT and IGT populations using the WBISI or ISI. Employing this feedback analysis provided a clear demonstration of the continuum of disease progression in these obese youth, consistent with that found in adults (21). Therefore, combining the WBISI or ISI with the surrogate of ß-cell function should also be a useful technique to evaluate the impact of intervention strategies in studies that involve large groups of obese children and adolescents once the more explicit physiology is determined in the smaller clamp-based investigations.

Consistent with the M-value for assessing insulin sensitivity (3, 7), the WBISI and ISI were also found to correlate well with the degree of intramyocellular lipid content. This relationship reveals a plateau when approaching a state of very low insulin-stimulated glucose disposal (low insulin sensitivity) and the large range in possible insulin sensitivities when approaching an IMCL of approximately 1%. The low level represents the typical value for normal healthy individuals (6). Thus, the WBISI and ISI indexes of insulin sensitivity may be potentially useful tools for more mechanistic-related studies examining peripheral insulin resistance in larger populations.


    Acknowledgments
 
We are particularly grateful to all of the children and adolescents who participated in the clamp and OGTT studies. We thank the nursing staff of Yale University School of Medicine Children’s and General Clinical Research Centers for their excellent care of the subjects and their professional assistance during the studies.


    Footnotes
 
This work was supported by NIH Grants RO1-HD-40787 and RO1-HD-28016 (to S.C.), the Stephen I. Morse Pediatric Diabetes Research Fund (to R.W.), the Jeanne B. Kempner Scholar Award (to C.W.Y.), and Award K24-HD-01464 for Patient-Oriented Research (to S.C.) and in part by Yale Children’s Clinical Research Center Grant MO1-RR-00125 and General Clinical Research Center Grant MO1-RR-06022, General Clinical Research Centers Program, National Center for Research Resources, NIH.

Abbreviations: BMI, Body mass index; HDL, high-density lipoprotein; 1H-MRS, 1H-MR spectroscopy; HOMA-IR, homeostasis model assessment-insulin resistance; IGI, insulinogenic index; IGT, impaired glucose tolerance; IMCL, intramyocellular lipid content; ISI, insulin sensitivity index; MR, magnetic resonance; NGT, normal glucose tolerance; OGTT, oral glucose tolerance test; WBISI, whole body insulin sensitivity index.

Received September 2, 2003.

Accepted December 16, 2003.


    References
 Top
 Abstract
 Introduction
 Subjects and Methods
 Results
 Discussion
 References
 

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I. M. Libman, E. Barinas-Mitchell, A. Bartucci, R. Robertson, and S. Arslanian
Reproducibility of the Oral Glucose Tolerance Test in Overweight Children
J. Clin. Endocrinol. Metab., November 1, 2008; 93(11): 4231 - 4237.
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J. Clin. Endocrinol. Metab.Home page
S. F. Witchel
Ontogeny of Polycystic Ovary Syndrome: A Creative Approach
J. Clin. Endocrinol. Metab., May 1, 2008; 93(5): 1576 - 1578.
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Diabetes CareHome page
N. Bouhours-Nouet, S. Dufresne, F. B. de Casson, E. Mathieu, O. Douay, F. Gatelais, S. Rouleau, and R. Coutant
High Birth Weight and Early Postnatal Weight Gain Protect Obese Children and Adolescents From Truncal Adiposity and Insulin Resistance: Metabolically healthy but obese subjects?
Diabetes Care, May 1, 2008; 31(5): 1031 - 1036.
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DiabetesHome page
S. E. Taksali, S. Caprio, J. Dziura, S. Dufour, A. M.G. Cali, T. R. Goodman, X. Papademetris, T. S. Burgert, B. M. Pierpont, M. Savoye, et al.
High Visceral and Low Abdominal Subcutaneous Fat Stores in the Obese Adolescent: A Determinant of an Adverse Metabolic Phenotype
Diabetes, February 1, 2008; 57(2): 367 - 371.
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DiabetesHome page
C. Le Stunff, A. Dechartres, V. Mariot, C. Lotton, C. Trainor, E. Miraglia Del Giudice, D. Meyre, I. Bieche, I. Laurendeau, P. Froguel, et al.
Association Analysis Indicates That a Variant GATA-Binding Site in the PIK3CB Promoter Is a Cis-Acting Expression Quantitative Trait Locus for This Gene and Attenuates Insulin Resistance in Obese Children
Diabetes, February 1, 2008; 57(2): 494 - 502.
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J. Clin. Endocrinol. Metab.Home page
C. Le Stunff, A. Dechartres, E. Miraglia Del Giudice, P. Froguel, and P. Bougneres
A Single-Nucleotide Polymorphism in the p110 Gene Promoter Is Associated with Partial Protection from Insulin Resistance in Severely Obese Adolescents
J. Clin. Endocrinol. Metab., January 1, 2008; 93(1): 212 - 215.
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J. Clin. Endocrinol. Metab.Home page
C. Herder, S. Schneitler, W. Rathmann, B. Haastert, H. Schneitler, H. Winkler, R. Bredahl, E. Hahnloser, and S. Martin
Low-Grade Inflammation, Obesity, and Insulin Resistance in Adolescents
J. Clin. Endocrinol. Metab., December 1, 2007; 92(12): 4569 - 4574.
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Diabetes CareHome page
A. M.G. Cali, T. L. Zern, S. E. Taksali, A. M. de Oliveira, S. Dufour, J. D. Otvos, and S. Caprio
Intrahepatic Fat Accumulation and Alterations in Lipoprotein Composition in Obese Adolescents: A perfect proatherogenic state
Diabetes Care, December 1, 2007; 30(12): 3093 - 3098.
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Diabetes CareHome page
H. Zheng, M. Patel, R. Cable, L. Young, and S. D. Katz
Insulin Sensitivity, Vascular Function, and Iron Stores in Voluntary Blood Donors
Diabetes Care, October 1, 2007; 30(10): 2685 - 2689.
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Arch Pediatr Adolesc MedHome page
S. Snitker, K. Y. Le, E. Hager, B. Caballero, and M. M. Black
Association of Physical Activity and Body Composition With Insulin Sensitivity in a Community Sample of Adolescents
Arch Pediatr Adolesc Med, July 1, 2007; 161(7): 677 - 683.
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Diabetes CareHome page
D. Yeste, J. Vendrell, R. Tomasini, M. Broch, M. Gussinye, A. Megia, and A. Carrascosa
Interleukin-6 in Obese Children and Adolescents With and Without Glucose Intolerance
Diabetes Care, July 1, 2007; 30(7): 1892 - 1894.
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Am. J. Physiol. Endocrinol. Metab.Home page
S. Sakaue, S. Ishimaru, D. Ikeda, Y. Ohtsuka, T. Honda, J.-i. Suzuki, Y. Kawakami, J. Ishii, and M. Nishimura
Estimation of beta-cell function from the data of the oral glucose tolerance test
Am J Physiol Endocrinol Metab, June 1, 2007; 292(6): E1575 - E1580.
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Diabetes CareHome page
J. M. Lee, M. J. Okumura, M. M. Davis, W. H. Herman, and J. G. Gurney
Prevalence and Determinants of Insulin Resistance Among U.S. Adolescents: A population-based study.
Diabetes Care, November 1, 2006; 29(11): 2427 - 2432.
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J. Clin. Endocrinol. Metab.Home page
N. Santoro, G. Cirillo, A. Amato, C. Luongo, P. Raimondo, A. D'Aniello, L. Perrone, and E. Miraglia del Giudice
Insulin Gene Variable Number of Tandem Repeats (INS VNTR) Genotype and Metabolic Syndrome in Childhood Obesity
J. Clin. Endocrinol. Metab., November 1, 2006; 91(11): 4641 - 4644.
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J. Clin. Endocrinol. Metab.Home page
T. S. Burgert, S. E. Taksali, J. Dziura, T. R. Goodman, C. W. Yeckel, X. Papademetris, R. T. Constable, R. Weiss, W. V. Tamborlane, M. Savoye, et al.
Alanine Aminotransferase Levels and Fatty Liver in Childhood Obesity: Associations with Insulin Resistance, Adiponectin, and Visceral Fat
J. Clin. Endocrinol. Metab., November 1, 2006; 91(11): 4287 - 4294.
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J. Clin. Endocrinol. Metab.Home page
J. C. Winer, T. L. Zern, S. E. Taksali, J. Dziura, A. M. G. Cali, M. Wollschlager, A. A. Seyal, R. Weiss, T. S. Burgert, and S. Caprio
Adiponectin in Childhood and Adolescent Obesity and Its Association with Inflammatory Markers and Components of the Metabolic Syndrome
J. Clin. Endocrinol. Metab., November 1, 2006; 91(11): 4415 - 4423.
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Am. J. Physiol. Endocrinol. Metab.Home page
G. Perseghin, R. Bonfanti, S. Magni, G. Lattuada, F. De Cobelli, T. Canu, A. Esposito, P. Scifo, G. Ntali, F. Costantino, et al.
Insulin resistance and whole body energy homeostasis in obese adolescents with fatty liver disease
Am J Physiol Endocrinol Metab, October 1, 2006; 291(4): E697 - E703.
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Eur J EndocrinolHome page
M. Lopez-Capape, M. Alonso, E. Colino, C. Mustieles, J. Corbaton, and R. Barrio
Frequency of the metabolic syndrome in obese Spanish pediatric population.
Eur. J. Endocrinol., August 1, 2006; 155(2): 313 - 319.
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J. Clin. Endocrinol. Metab.Home page
K. H. Paik, Y. H. Choe, W. H. Park, Y. J. Oh, A. H. Kim, S. H. Chu, S. W. Kim, E. K. Kwon, S. J. Han, W. Y. Shon, et al.
Suppression of Acylated Ghrelin during Oral Glucose Tolerance Test Is Correlated with Whole-Body Insulin Sensitivity in Children with Prader-Willi Syndrome
J. Clin. Endocrinol. Metab., May 1, 2006; 91(5): 1876 - 1881.
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J. Clin. Endocrinol. Metab.Home page
E. Ortega, J. Koska, A. D. Salbe, P. A. Tataranni, and J. C. Bunt
Serum {gamma}-Glutamyl Transpeptidase Is a Determinant of Insulin Resistance Independently of Adiposity in Pima Indian Children
J. Clin. Endocrinol. Metab., April 1, 2006; 91(4): 1419 - 1422.
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RadiologyHome page
M. Torriani, B. J. Thomas, E. F. Halpern, M. E. Jensen, D. I. Rosenthal, and W. E. Palmer
Intramyocellular Lipid Quantification: Repeatability with 1H MR Spectroscopy
Radiology, August 1, 2005; 236(2): 609 - 614.
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PediatricsHome page
A. Mohn, M. Marcovecchio, and F. Chiarelli
Is Homeostasis Model Assessment Better Than the Quantitative Insulin-Sensitivity Check Index and Fasting Glucose/Insulin Ratio?
Pediatrics, August 1, 2005; 116(2): 515 - 515.
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DiabetesHome page
H. Chen, G. Sullivan, and M. J. Quon
Assessing the Predictive Accuracy of QUICKI as a Surrogate Index for Insulin Sensitivity Using a Calibration Model
Diabetes, July 1, 2005; 54(7): 1914 - 1925.
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J. Clin. Endocrinol. Metab.Home page
R. Weiss, S. E. Taksali, S. Dufour, C. W. Yeckel, X. Papademetris, G. Cline, W. V. Tamborlane, J. Dziura, G. I. Shulman, and S. Caprio
The "Obese Insulin-Sensitive" Adolescent: Importance of Adiponectin and Lipid Partitioning
J. Clin. Endocrinol. Metab., June 1, 2005; 90(6): 3731 - 3737.
[Abstract] [Full Text] [PDF]


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DiabetesHome page
R. Weiss, S. Caprio, M. Trombetta, S. E. Taksali, W. V. Tamborlane, and R. Bonadonna
{beta}-Cell Function Across the Spectrum of Glucose Tolerance in Obese Youth
Diabetes, June 1, 2005; 54(6): 1735 - 1743.
[Abstract] [Full Text] [PDF]


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J. Clin. Endocrinol. Metab.Home page
F. Bacha and S. A. Arslanian
Ghrelin Suppression in Overweight Children: A Manifestation of Insulin Resistance?
J. Clin. Endocrinol. Metab., May 1, 2005; 90(5): 2725 - 2730.
[Abstract] [Full Text] [PDF]


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PediatricsHome page
M. Keskin, S. Kurtoglu, M. Kendirci, M. E. Atabek, and C. Yazici
Homeostasis Model Assessment Is More Reliable Than the Fasting Glucose/Insulin Ratio and Quantitative Insulin Sensitivity Check Index for Assessing Insulin Resistance Among Obese Children and Adolescents
Pediatrics, April 1, 2005; 115(4): e500 - e503.
[Abstract] [Full Text] [PDF]


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J. Clin. Endocrinol. Metab.Home page
C. W. Yeckel, S. E. Taksali, J. Dziura, R. Weiss, T. S. Burgert, R. S. Sherwin, W. V. Tamborlane, and S. Caprio
The Normal Glucose Tolerance Continuum in Obese Youth: Evidence for Impairment in {beta}-Cell Function Independent of Insulin Resistance
J. Clin. Endocrinol. Metab., February 1, 2005; 90(2): 747 - 754.
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J. Clin. Endocrinol. Metab.Home page
F. Brandou, J.-F. Brun, and J. Mercier
Limited Accuracy of Surrogates of Insulin Resistance during Puberty in Obese and Lean Children at Risk for Altered Glucoregulation
J. Clin. Endocrinol. Metab., February 1, 2005; 90(2): 761 - 767.
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