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Pediatric Endocrinology |
Departments of Medicine (T.R.), Public Health (Ma.K.), and Diagnostic Radiology (T.K.), University of Turku, FIN-20520 Turku, Finland; Research and Development Centre (J.M., Me.K.), Social Insurance Institution, FIN-20720, Turku, Finland; Department of Human Molecular Genetics (A.J.), National Public Health Institute and Department of Forensic Medicine, University of Helsinki, FIN-00300 Helsinki, Finland; Department of Psychiatry, Helsinki University Central Hospital (A.R.), FIN-00180 Helsinki, Finland; Physical Activity Sciences Laboratory (C.B.), Laval University, Quebec G1K 7PH, Canada; and Department of Public Health (J.K.), University of Helsinki, FIN-00014 Helsinki, Finland
Address all correspondence and requests for reprints to: Dr. Tapani Rönnemaa, Department of Medicine, University of Turku, FIN-20520 Turku, Finland.
| Abstract |
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| Introduction |
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When comparing the glucose metabolism in unrelated obese and nonobese subjects, as has been the case in previous studies, differences in the genetic background of the subjects were not taken into account. However, genetic factors may be of importance, as approximately 50% of the variation in body fat distribution is genetically determined (7). One strategy to assess the independent impact of obesity on glucose metabolism without the confounding effects of genetic factors is to examine identical twins who are discordant for obesity. Therefore, we compared glucose metabolism in 23 identical nondiabetic twin pairs who had, on the average, a 7-kg/m2 difference in body mass index (BMI). Special attention was paid to the distribution of body fat, as determined by magnetic resonance imaging.
| Subjects and Methods |
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The Finnish Twin Cohort includes all pairs (4307 monozygous, 9581 like-sexed dizygous pairs) of adult Finnish twins born before 1958 and alive in 1975 (8). Based on a postal questionnaire sent to the twins in 1990, identical twin pairs born between 1932 and 1957 and discordant for obesity were identified. Discordance for obesity was defined as a BMI difference of at least 4 kg/m2 and, in addition, the BMI of the obese co-twin had to be more than 27 kg/m2, and the BMI of the lean co-twin had to be less than 25 kg/m2. Subjects with a history of thyroid disorders, psychiatric diseases, diabetes, major musculoskeletal problems, and other diseases, or taking medications (e.g. diuretics or ß-blockers) possibly affecting glucose metabolism were excluded. All eligible twin pairs, based on a response letter, were invited to take part in the present study in 1992, provided that they still fulfilled the criteria. A total of 28 twin pairs were examined.
The physical examination revealed that two of the pairs had a BMI difference less than 3 kg/m2, and they were excluded. Three pairs had a BMI difference between 3 and 4 kg/m2, and they were included in the final study population. The obese co-twin of one pair was found to have previously undiagnosed overt diabetes mellitus, and this pair was excluded.
Zygosity of the twin pairs was originally based on a validated self-administered questionnaire (9). The monozygosity of the pairs of the present study was confirmed by dermatomatoglyphic analysis of fingertip prints (10, 11) by a highly experienced expert. All except six pairs were confirmed to be monozygotic. DNA samples of the six pairs with uncertain zygosity were typed for markers at six different polymorphic gene loci (DIS80, APOB, D17S30, COL2A1, VWA, and HUMTH). Four of the pairs were found to be monozygotic, and the two other pairs were dizygotic; these two pairs were excluded.
Thus, the final study sample consisted of 23 nondiabetic identical twin pairs (14 female, 9 male) with more than 3 kg/m2 difference in BMI and having no diseases or medications possibly affecting the results.
Methods
Glucose metabolism was assessed in a 2-h glucose (75 g) tolerance test with glucose and insulin measurements at 0, 30, 60, 90, and 120 min. Serum glucose was measured by the glucose dehydrogenase method (Merck Diagnostica, Darmstadt, Germany). Plasma insulin was measured by RIA (Pharmacia Diagnostics, Uppsala, Sweden). The antiserum of this kit is specific for insulin and does not cross-react with proinsulin or C-peptide (cross-reactivities < 0.1%). An insulin sensitivity index was calculated according to the formula of Cederholm and Wibell (12). Serum free fatty acids (FFAs) were measured enzymatically after an overnight fast using acyl-CoA synthetase, acyl CoA oxidase, and peroxidase (Wako Chemicals, Neuss, Germany). Smoking was defined as regular smoking at the time of examination.
Percentage of body fat was determined using the so-called four-component method. The method is based on the division of body mass into four components with different densities: fat tissue 0.9007 g/cm3), water (0.994 g/cm3), minerals (3.042 g/cm3), and proteins (1.34 g/cm3). Water mass was estimated by bioelectric impedance method (BIA-101A/S, RJL System Inc., Clemens, MI). Mineral mass was estimated by dual-energy x-ray absorptiometry (Norland XR26, Norland Corporation, Fort Atkinson, WI). The density of the whole body was estimated by underwater weighing corrected for information on body water and mineral mass. The proportion of fat tissue was calculated from the density of the whole body according to the formula of Siri (13).
The distribution of body fat was measured by magnetic resonance imaging (MRI) (14). Imaging was performed at 0.1 tesla (Mega4R, Instrumentarium Co., Imaging Division, Helsinki, Finland). Axial and sagittal localizers were used to obtain a transaxial T1-weighted image (relaxation time/echo time = 155/20, slice thickness 10 mm) at the level of the fourth lumbar vertebra. Visceral and sc fat areas were measured. MRI was not performed in three pairs, either because of claustrophobia or because of temporary malfunctioning of the MRI equipment. These three pairs were excluded from analyses concerning body fat distribution.
A paired t test was used to compare means and the McNemars test to compare the proportions of obese and lean co-twins. Pearson correlation coefficients were calculated to quantify the association between intrapair differences in adiposity or its distribution and intrapair differences in variables of glucose metabolism. Multiple regression analyses were performed to analyze the independent contributions of visceral fat and body fat percentage to glucose metabolism. All statistical analyses were performed using Statistical Analysis System (SAS) statistical programs.
| Results |
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To quantify the relationship between adiposity or its distribution with
glucose metabolism, we correlated intrapair differences in adiposity
variables to indicators of insulin sensitivity (Table 2
,
Fig. 2
). Intrapair differences in BMI and percentage of
body fat did not show any significant correlation to the metabolic
variables. Intrapair differences in AVF area were those most
significantly correlated to intrapair differences in glucose and
insulin AUCs and to intrapair difference in insulin sensitivity index.
In contrast, intra-pair differences in sc fat area showed no
correlation to intrapair differences in indices of glucose
metabolism. In multiple regression analyses, the association between
intrapair differences in AVF area and differences in glucose metabolism
remained significant when adjustment was made for differences in body
fat percentage (Table 3
). The whole model explained
3150% of the variation in intrapair differences in glucose
metabolism.
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| Discussion |
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Discordance for obesity in identical twins is a rare phenomenon. We found only 50 out of approximately 1500 twin pairs fulfilling our discordance criterion. Therefore, an important question is whether all twin pairs studied were really monozygous. We paid special attention to this by performing fingertip print analyses in all pairs and an analysis of alleles at six marker loci in those pairs in whom the identity could not be fully confirmed by fingertip print characteristics. Therefore, it is highly unlikely that any of the pairs studied would have been dizygous. Of course, we cannot exclude the possibility that postconception tissue-selective mutation potentially affecting adipose tissue could have occurred in some of the pairs.
To study glucose metabolism, we performed an oral glucose tolerance test with samples collected every 30 min for glucose and insulin measurements. As indicators of insulin sensitivity, we used fasting insulin, insulin area, and a sensitivity index calculated according to Cederholm & Wibell (12). Although we did not directly measure insulin sensitivity by the hyperinsulinemic-euglycemic clamp technique (17), our indicators, even fasting insulin, are well correlated with clamp results in nondiabetic subjects (18). Moreover, all indicators of insulin sensitivity in the present study exhibit consistent relationships with body fat and its distribution. We used MRI at the level of the fourth lumbar vertebra to assess body fat distribution. Results obtained with MRI correlate strongly with those obtained with computed tomography, and the reproducibility of the MRI method is good (19).
Although visceral fat accumulation itself seems to be responsible for the low insulin sensitivity in subjects with this type of obesity, other environmental factors could act as confounders. For example, smoking is related to insulin resistance (20), and it may also favor upper body fat accumulation (21). In our study, the proportion of smokers did not differ significantly between obese and nonobese co-twins when analyzed as whole groups or as subgroups with either visceral or sc fat accumulation. In fact, the number of smokers tended to be somewhat higher among lean co-twins, suggesting that the results were not confounded by smoking.
Regarding the mechanism by which visceral fat may result in reduced insulin sensitivity, it has been proposed that increased flux of FFAs from intraabdominal fat stores to the liver and systemic circulation leads to a higher preponderance of tissues to fat use instead of glucose as fuel (22, 23). We did not measure FFA kinetics, but similar FFA levels in obese and lean co-twins, independent of fat distribution, suggest that if the flux of FFAs from visceral fat is increased, it is likely compensated by their increased use (24).
We conclude that when genetic factors are controlled for, subjects prone to AVF accumulation are more susceptible to experiencing reduced insulin sensitivity, whereas subjects with a tendency to ASF deposition exhibit only modest or no disturbances in glucose metabolism.
| Acknowledgments |
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| Footnotes |
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Received June 20, 1996.
Revised October 25, 1996.
Accepted October 31, 1996.
| References |
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