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Journal of Clinical Endocrinology & Metabolism, doi:10.1210/jc.2005-0131
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The Journal of Clinical Endocrinology & Metabolism Vol. 90, No. 8 4615-4621
Copyright © 2005 by The Endocrine Society

Adiponectin Predicts Insulin Resistance But Not Endothelial Function in Young, Healthy Adolescents

Atul Singhal, Nigel Jamieson, Mary Fewtrell, John Deanfield, Alan Lucas and Naveed Sattar

Medical Research Council, Childhood Nutrition Research Centre (A.S., A.L., M.F.), Department of Vascular Physiology (J.D.), Institute of Child Health, London WC1N 1EH, United Kingdom; and University Department of Vascular Biochemistry (N.J., N.S.), Glasgow Royal Infirmary, Glasgow G31 2ER, United Kingdom

Address all correspondence and requests for reprints to: A. Singhal, Medical Research Council, Childhood Nutrition Research Centre, Institute of Child Health, 30 Guilford Street, London WC1N 1EH, United Kingdom. E-mail: a.singhal{at}ich.ucl.ac.uk.


   Abstract
Top
 Abstract
Introduction
 Subjects and Methods
 Results
 Discussion
 References
 
Background: Adiponectin, an adipocyte-derived hormone found in lower concentration with greater adiposity, is suggested to reduce the risk of insulin resistance, atherosclerosis, and cardiovascular disease. We tested this hypothesis in a healthy, nonobese population.

Methods and Results: Brachial artery flow-mediated endothelial-dependent vasodilation and distensibility, measures of vascular function relevant to the early atherosclerotic process, were determined in 294 adolescents (aged 13–16 yr) using high-resolution vascular ultrasound. Fasting insulin concentration and the homeostasis model assessment of insulin resistance were used to estimate insulin resistance. Fat mass was measured by bioelectric impedance analysis; fasting serum adiponectin concentration by RIA; and lipid profile, fasting insulin, glucose, and C-reactive protein concentrations using standard laboratory techniques. Adiponectin concentration was associated with insulin resistance independent of potential confounding factors (e.g. –1.3% change in fasting insulin concentration per 10% increase in adiponectin concentration; 95% confidence interval, –2.4% to –0.1%; P = 0.03), but not with flow-mediated endothelial-dependent vasodilation or arterial distensibility.

Conclusions: Lower adiponectin concentration was associated with lower insulin sensitivity in a healthy, nonobese population. Our study supports the hypothesis that adiponectin benefits insulin sensitivity from a young age but, in contrast to experimental models and data from older subjects, does not affect vascular changes associated with early atherosclerosis.


   Introduction
Top
 Abstract
 Introduction
Subjects and Methods
 Results
 Discussion
 References
 
OBESITY IS A major independent risk factor for atherosclerotic cardiovascular disease (1). Yet the mechanisms that relate fat mass to vascular disease are poorly understood. Obese individuals demonstrate vascular endothelial dysfunction (2, 3, 4), which is central to the pathogenesis of atherosclerosis (5) and predicts cardiovascular risk (6). However, the molecular basis for the association between adiposity and endothelial dysfunction is uncertain.

Adipose tissue secretes various bioactive substances, or adipocytokines, which might affect vascular function. Adiponectin is one such molecule that has been suggested to have important antiatherogenic (7) and antidiabetic properties (8, 9). Low adiponectin concentrations are found in patients with obesity (10), insulin resistance (11, 12), or type 2 diabetes (12), and in individuals at high risk of coronary heart disease (13, 14). Studies in vitro suggest that adiponectin reduces the development of atherosclerosis by inhibiting TNF-{alpha}-mediated monocyte adhesion (15), the formation of foam cells (16), and smooth muscle cell proliferation (17) and by stimulating the production of nitric oxide from vascular endothelial cells (18). In vivo, endothelial function is impaired in adiponectin knockout mice (19), whereas forced adiponectin expression has been shown to reduce atherosclerotic lesions in a mouse model of atherosclerosis (20).

In humans, hypoadiponectinemia is associated with impaired endothelial function in patients with mild hypertension (19) and type 2 diabetes mellitus (21) and in healthy adults (21, 22). However, this finding is not consistent and, recently, adiponectin concentration was shown to be associated with endothelial-independent rather than endothelium-dependent vasodilation in adults (23). Moreover, there are relatively few data that support an effect of adiponectin on endothelial function independent of other metabolic cardiovascular risk factors, particularly in the young who are therefore early in the atherosclerotic process.

In the present study, we examined the association between adiponectin, insulin resistance, and endothelial dysfunction and its relation to the inflammatory and metabolic disturbances associated with adiposity. We studied adolescents (aged 13–16 yr) to permit evaluation of the role of adiponectin early in the development of insulin resistance and vascular disease, without the presence of confounding risk factors common in older populations. Our subjects had a broad representative range of body fatness, thereby enabling us to investigate the relative importance of adiponectin concentration and adiposity on insulin resistance and vascular function in a healthy, nonobese population.


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

The 294 adolescents studied (aged 13–16 yr) were recruited from a preterm birth cohort (216 participants) and from schools in the same communities (78 born at term) (24, 25). All subjects were nonsmokers and were clinically well. Informed consent was obtained from the subjects and their parents, and the study was approved by national and local research ethics committees.

Flow-mediated arterial dilation

Brachial artery flow-mediated endothelial-dependent dilation (FMD) was measured as described previously (26). Briefly, the brachial artery was imaged in longitudinal section, 5–10 cm above the elbow, using a 7-MHz linear array transducer and an Acuson 128XP/10 system (Siemens Corp., Mountain View, CA). A pneumatic cuff was inflated around the forearm to 300 mm Hg for 5 min followed by rapid deflation causing a large increase in blood flow (reactive hyperemia). End diastolic B-mode images were used to measure arterial diameter (for 1 min resting, 5 min cuff inflation, and 3 min postcuff deflation). FMD was expressed as a percentage change from baseline arterial diameter or as the absolute maximal change between pre- and posthyperemic brachial artery diameter adjusted for prehyperemic diameter using regression analysis (26).

Arterial distensibility

Arterial distension was measured in the right brachial artery using high-resolution ultrasound and a Wall Tracking System (Ingenious Medical Systems, Arnhem, The Netherlands) (27). The mean change in diameter between diastole and systole over a 5-sec period was measured. An average of three distension measurements was computed. Blood pressure was measured in the left brachial artery using an automated device (Accutorrsat; Datascope Corp., Montvale, NJ) during distension measurement in the right arm. This provided a representative measurement of the pulse pressure in the right brachial artery, which was used to derive arterial distensibility from arterial distension (27). Blood pressure was also determined before the measurement of arterial distensibility, and the mean of the two measurements was used to assess associations of mean arterial blood pressure with adiponectin concentration.

Anthropometric, demographic, fat mass, and biochemical measurements

Body mass index (BMI) was calculated from height and weight measurements, and for analyses nonobese individuals were defined as those with a BMI less than 25 kg/m2. Fat mass was determined by bioelectric impedance analysis (EZ Comp 1500; Fitness Concepts Inc., Park City, UT) and skinfold thickness. Fat mass was obtained from the manufacturer’s internal algorithm and was also calculated using the equations of Schaefer et al. (28), which are suitable for adolescents. Triceps, biceps, subscapular, and suprailiac skinfold thicknesses were measured using skinfold calipers. The SD scores (z scores) for weight, height, and BMI were calculated using reference growth data. Tanner stage was determined by self-assessment (25).

Blood was obtained by venepuncture between 0900 and 1100 h after an overnight fast, and serum was stored at –80 C. Serum adiponectin concentrations were determined using RIA (Linco Research Inc., St. Charles, MO) with a detection limit of (intra- and interassay coefficients of variation of <8% and a lower sensitivity of 0.8 µg/ml). Fasting concentrations of high sensitivity C-reactive protein (CRP), insulin, total cholesterol, high-density lipoprotein (HDL) cholesterol, and low-density lipoprotein (LDL) cholesterol were determined using standard laboratory methods. Homeostasis model assessment of insulin resistance (HOMA-IR), an index of insulin resistance, was calculated using an equation as described (29).

Statistical analysis

Multiple linear regression analysis was used to assess associations between adiponectin concentration and the outcome variables (vascular function assessed by brachial arterial FMD and distensibility and insulin resistance assessed by fasting insulin concentration and HOMA-IR). Arterial distensibility is usually represented as the distensibility coefficient calculated as the change in cross-sectional area between diastole and systole, relative to the area at diastole divided by pulse pressure. However, to assess associations between arterial distensibility and adiponectin concentration, absolute arterial distension was used as the dependent variable and adjusted for pulse pressure and baseline arterial diameter using regression analysis as described previously (27). Similarly for FMD, the absolute change in posthyperemic diameter was used in regression models and adjusted for baseline arterial diameter (26). Associations between outcomes and adiponectin concentration were also all adjusted for potential confounding factors—age, sex, and waist circumference (see Table 2Go) and for anthropometric measures (i.e. z score for weight and height).


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  		TABLE 2. Adiponectin concentration and anthropometry

 
Fasting concentrations of adiponectin, insulin, leptin, and triglyceride and arterial distension and HOMA-IR were not normally distributed and were loge transformed and then multiplied by 100 before statistical analyses (30). Therefore, the SD for loge adiponectin concentration multiplied by 100 represents the coefficient of variation, and regression coefficients for the 100 loge-transformed adiponectin, insulin resistance, or arterial distension data represent the percentage change in outcome per unit change in independent variable (30). Thus, for regression analyses that included adiponectin concentration as an independent variable, the coefficients represent the percentage change in outcome per percentage change in adiponectin concentration (presented in the results as per 10% change in adiponectin concentration, for simplicity). Regression analyses were repeated using quartiles of the adiponectin distribution (untransformed) as the independent variable. CRP concentration could not be transformed and, hence, nonparametric statistics were used. Statistical significance was taken as P < 0.05 for all analyses, which were two-tailed.


   Results
Top
 Abstract
 Introduction
 Subjects and Methods
 Results
Discussion
 References
 
Adiponectin levels did not differ significantly in adolescents born at term or before term (P = 0.4, data not presented). The interactions between adiponectin concentration and preterm birth, or sex, on measures of insulin resistance (fasting insulin concentration and HOMA-IR) and vascular health (FMD or arterial distensibility) were not statistically significant (P > 0.2). This justifies analyzing the combined population, whose anthropometric, demographic, metabolic, and vascular characteristics are summarized in Table 1Go.


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  		TABLE 1. Demographic, metabolic, and arterial variables in 294 subjects

 
Adiponectin concentration and anthropometry

The BMI of study participants (ranging from 14–41 kg/m2) was representative of the general population as shown by the mean BMI z score of 0.4 (Table 1Go). Adiponectin levels were significantly related to sex, waist circumference, and age, but not to Tanner stage, z scores for height and weight, or measures of fat mass (BMI z score, sum of skinfolds, and fat mass calculated using EZ comp analyzer or Schaefer’s equations) (Table 2Go).

Adiponectin concentration and cardiovascular risk factors

Adiponectin concentration was significantly associated with HDL cholesterol concentration but not with other cardiovascular risk factors (Table 3Go), including CRP concentration (r = –0.1, P = 0.1) and blood pressure (data not presented). As reported previously (25), CRP concentration correlated with fat mass (r = 0.2; P = 0.001).


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  		TABLE 3. Insulin resistance, vascular function, and adiponectin concentration

 
Insulin resistance and adiponectin

In univariate analyses, associations between insulin resistance and adiponectin concentration just failed to reach statistical significance [regression coefficient = –1.2% change in fasting insulin concentration per 10% increase in adiponectin concentration; 95% confidence interval (CI), –2.4–0.1%; P = 0.07; for HOMA-IR: regression coefficient = –1.3%; 95% CI, –2.7–0.1%; P = 0.07]. However, after adjustment for potential confounding factors (age, sex, waist circumference, and z scores for height and weight), insulin resistance was significantly and inversely related to adiponectin concentration (Table 3Go). Similarly, both measures of insulin resistance were associated with quartiles of the adiponectin distribution (P < 0.03 for both), and this association remained significant after adjustment for potential confounding factors (P < 0.01 for both). Furthermore, the association of insulin resistance with adiponectin concentration was independent of confounding factors, together with a family history of diabetes (P = 0.03 for both fasting insulin concentration and HOMA-IR), or when the analyses were confined to adolescents with a BMI less than 25 (n = 215) (P < 0.03 for both measures of insulin resistance).

Insulin resistance remained significantly associated with adiponectin concentration after adjustment for potential confounding factors (see Subjects and Methods above) together with HDL cholesterol concentration (P = 0.04 for both HOMA-IR and fasting insulin concentration). Similarly, insulin resistance was significantly associated with adiponectin concentration independent of confounding factors together with leptin concentration (P < 0.03 for both HOMA-IR and fasting insulin concentration), or together with triglyceride concentration (P = 0.02 for both measures of insulin resistance; other data not presented).

Furthermore, both measures of insulin resistance were significantly associated with adiponectin concentration after adjusting for confounding factors (see Subjects and Methods above), together with three measures of fat mass (sum of skinfolds and fat mass calculated using EZ comp analyzer or Schaefer’s equations) (regression coefficients ranging from –1.2 to –1.4%, P = 0.03 to P = 0.04, other data not presented), and demonstrated a trend to significance after adjustment for confounding factors together with CRP concentration (regression coefficient for fasting insulin = –1.1%, 95% CI: –2.3–0.01%; P = 0.05; for HOMA-IR = –1.3%, 95% CI: –2.6–0.01%; P = 0.05).

Vascular function and adiponectin concentration

Arterial distensibility and FMD were not significantly related to adiponectin concentration in the whole population or when analyzed separately by sex (Table 3Go). Similar findings were obtained using quartiles of the adiponectin distribution (untransformed) as the independent variable (P > 0.5 for all analyses) (other data not presented). However the association between arterial distensibility and leptin concentration, described in this population previously (25), remained significant after adjustment for adiponectin concentration (regression coefficient = –1.6% change in arterial distensibility per 10% change in leptin concentration, 95% CI –2.6 to –0.5%; P = 0.003).

Measures of insulin resistance and metabolic cardiovascular risk factors (Table 3Go), other than leptin (25), were not associated with FMD (data not shown) or, as presented previously, with arterial distensibility (25). FMD was also not significantly related to BMI (P = 0.6) or to total cholesterol (P = 0.7) or CRP concentration (P = 0.7) (data not presented).


   Discussion
Top
 Abstract
 Introduction
 Subjects and Methods
 Results
 Discussion
References
 
In a large study of a healthy population, we found that lower adiponectin concentration was associated with indices of insulin resistance in adolescents but not with endothelial dysfunction or arterial distensibility. Our data support the hypothesis that adiponectin affects insulin sensitivity even in the young but does not influence the development of endothelial dysfunction early in the atherosclerotic process.

Our findings are consistent with previous studies in humans (8) and animals (9), which indicate that low plasma adiponectin contributes to the pathogenesis of insulin resistance and type 2 diabetes. Adiponectin concentration was associated with insulin sensitivity even in adolescence, before the development of obesity and lifestyle risk factors for type 2 diabetes more common in adulthood. Importantly, the association of adiponectin with insulin resistance was independent of fat mass, CRP, leptin, triglyceride and HDL cholesterol concentration, family history of diabetes, and visceral adiposity (as measured by waist circumference). Our observations, therefore, strongly support an effect of adiponectin on insulin sensitivity, independent of adiposity and its associated metabolic and inflammatory disturbances.

Previous studies on the association of adiponectin concentration with insulin resistance in the young are conflicting. In obese and high-risk populations, adiponectin concentration is associated with measures of insulin resistance in most studies (31, 32, 33) (but not in all) (34), and weight loss has beneficial effects (33). However, in a nonobese population, only age and HDL concentration were associated with adiponectin concentration (35). Differences in age, genetic background, selection criteria, and statistical analysis could explain the discrepancy between this previous report and our findings. However, importantly, unlike previous reports, we found that insulin resistance was associated with adiponectin concentration even when the analysis was confined to only lean adolescents (i.e. BMI < 25). Our findings, therefore, strongly support the hypothesis that adiponectin affects insulin resistance even in those who are not obese.

In contrast to previous reports in adults (19, 21, 22), adiponectin concentration was not associated with endothelial dysfunction in adolescents. One potential explanation for this is simply a reduced sensitivity due to a narrow range for endothelial function in healthy adolescents. However, this explanation is unlikely because risk factors for atherosclerosis (e.g. lipid profile and birth weight) have been associated with the same measures of endothelial function in even younger children (26). Moreover, mean FMD in the present study (6.5%) was comparable with a healthy population aged 9–11 yr (4.7%) (26). Another potential explanation is that previous studies were in older people who are more likely to have established atherosclerosis. Consequently, confounding by the cumulative effects of cardiovascular risk factors (e.g. dyslipidaemia, elevated blood pressure, or many novel markers) associated with both obesity (and hence lower adiponectin concentration) and vascular disease could account for previous associations between adiponectin and endothelial dysfunction. Alternatively, a low adiponectin concentration over a longer period, as in adults, may be required to impair endothelial function. Finally, because endothelial function is impaired in those who are severely obese, the association between vascular function and adiponectin might be stronger in obese individuals than in a nonobese population such as ours.

We also found no evidence of an indirect effect of adiponectin on endothelial function as postulated previously (21). For instance, although adiponectin concentration was positively associated with HDL cholesterol concentration and insulin sensitivity, these latter factors were not related to endothelial dysfunction. Thus, our observations are consistent with a recent study (4), which found that weight loss improved endothelial function independent of the increase in adiponectin concentration.

Unlike our previous observations for leptin (25) and cholesterol (27), adiponectin concentration was not significantly associated with arterial distensibility, a measure of structural changes in the arterial wall associated with atherosclerosis. Therefore, although metabolic disturbances related to obesity are associated with lower arterial distensibilty in children (25, 27), the lack of a similar association with adiponectin concentration does not support the hypothesis that adiponectin mediates the link between body fatness and the abnormal vascular biology of early atherosclerosis. Furthermore, the association of leptin with lower arterial stiffness was independent of adiponectin concentration, an observation that is in accordance with a recent study in adults, which found that leptin, but not adiponectin concentration, independently predicted the later risk of stroke (36).

We considered several potential limitations in interpreting our data. Firstly, compared with a recent report that showed an association between adiponectin and endothelial function (21), our population had lower BMI and waist circumference, and so we may have lacked individuals at higher risk of endothelial dysfunction. Nonetheless, BMI in our participants was representative of the wider population, and even in this nonobese population we observed the expected associations between low adiponectin concentration and adiposity (10) (e.g. waist circumference) and HDL concentration (11). Secondly, compared with reports in adults (11), our study was relatively underpowered to assess sex differences in the association between adiponectin and insulin resistance. Although not statistically significant, this association appeared to be stronger in girls (Table 3Go), possibly because of the greater increase in adiposity and insulin resistance during the pubertal growth spurt in girls compared with boys. Thirdly, because complex tests cannot be easily conducted in large-scale studies in children, we used a marker rather than a direct measure of insulin resistance (e.g. the insulin tolerance test). However, we made similar observations for fasting insulin concentration and the HOMA-IR, both of which are validated (37) and widely used measures of insulin resistance in children and adolescents (32, 35, 37). Similarly, FMD is an indirect measure of endothelial dysfunction. However, the technique measures the vascular changes associated with atherosclerosis (5), has been widely used and validated in children (38), shows strong dose-response associations with known cardiovascular risk factors (39), and in older subjects predicts clinical cardiovascular risk (6). Finally, many adolescents in our study were born preterm. Nevertheless, this was unlikely to be a source of bias because prematurity did not affect vascular function and the interactions between adiponectin and preterm birth on insulin resistance and vascular function were not statistically significant.

Like most other reports, our study was cross-sectional and therefore cannot prove causation. Nonetheless, there is increasing evidence for causal link between adiponectin and insulin sensitivity that is mediated via receptors that promote glucose uptake and metabolism in the liver and muscles (40). For instance, adiponectin-deficient mice are both insulin resistant and prone to diabetes (41), and replenishment of adiponectin reverses insulin resistance in mice models of lipoatrophy, obesity, and type 2 diabetes (9). Furthermore, in humans, a diabetes susceptibility locus has been mapped to chromosome 3q27 (42), the location of the gene encoding adiponectin whose expression is reduced in adipose tissue of obese Caucasians with type 2 diabetes (43). In obese children and adolescents with prediabetes, intramyocellular and intraabdominal lipid accumulation—and not necessarily increased weight per se—are related to a reduction in peripheral insulin sensitivity (44). Adiponectin’s downstream metabolic effects include stimulation of glucose utilization and fatty-acid oxidation by the activation of AMP-activated protein kinase (40). Therefore, an adverse affect of low adiponectin concentration on muscle fatty oxidation could impair insulin sensitivity in the young before the onset of clinical obesity and so could help explain our findings in relatively lean individuals.

The association of low adiponectin concentration with insulin resistance in adolescents has important implications for the current epidemic of childhood obesity. Being obese as a child has been suggested to increase the risk of the metabolic syndrome as a consequence of the longer exposure of arteries to the atherogenic metabolic milieu associated with greater adiposity (45). As insulin resistance is central to this syndrome, our observations raise the possibility that a lower adiponectin concentration is a key link between body composition in children and a greater risk of later type 2 diabetes mellitus and cardiovascular disease. Importantly, low adiponectin concentration has predictive value for the future risk of type 2 diabetes in older individuals (8), in high-risk populations (46), and recently in obese children (32). Our study now suggests that low adiponectin concentration could adversely affect insulin sensitivity in healthy, nonobese adolescents. The role of adiponectin in the pathogenesis of insulin resistance in the young therefore merits further consideration.


   Footnotes
 
First Published Online May 10, 2005

Abbreviations: BMI, Body mass index; CI, confidence interval; CRP, C-reactive protein; FMD, flow-mediated endothelial-dependent vasodilation; HDL, high-density lipoprotein; HOMA-IR, homeostasis model assessment of insulin resistance; LDL, low-density lipoprotein.

Received January 24, 2005.

Accepted April 29, 2005.


   References
Top
 Abstract
 Introduction
 Subjects and Methods
 Results
 Discussion
 References
 

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