Conceived and designed the experiments: Adriano Falorni. Performed the experiments: GM BN FC VB FP GG SC CH. Analyzed the data: GM BN VB MR CH Alberto Falorni. Contributed reagents/materials/analysis tools: GM BN MD VB FP GG CH. Wrote the paper: GM CH. Coordinated all experiments and work: GM VB Adriano Falorni CH Alberto Falorni.
The authors have declared that no competing interests exist.
The aim of this study was to investigate sex differences and associations of high molecular weight (HMW) adiponectin, leptin and proinflammatory adipokines, individually or in combinations, with adiposity and insulin resistance (IR) measures in prepubertal childhood.
We studied 305 prepubertal children (boys/girls: 144/161; Tanner stage 1; age: 5-13 yr), included in a cohort of 44,231 adolescents who participated in an extensive Italian school-based survey. According to Cole's criteria, 105 individuals were lean (L; boys/girls: 59/46), 60 overweight (OW; boys/girls: 32/28) and 140 obese (OB; boys/girls: 70/70). Measurements comprised total and HMW adiponectin, leptin, as well as a panel of proinflammatory adipokines/chemokines associated with diabetes risk.
Leptin-, and the leptin-to-HMW adiponectin ratio (L/HMW)-, increased progressively (p<0.0001) from L to OW to OB boys and girls. When compared with L peers, OW and OB girls exhibited lower (p<0.001) HMW adiponectin levels, while in boys the HMW multimers did not differ significantly across the BMI-stratified groups. OB girls displayed higher (p<0.05) IL-8, IL-18, monocyte chemoattractant protein-1 (MCP-1) and soluble intercellular adhesion molecule-1 levels (sICAM-1) than L girls, whereas increased macrophage migration inhibitory factor (MIF) concentrations in OB vs OW boys were seen. HMW adiponectin (negatively), leptin or inflammatory markers (positively) correlated with adiposity and IR measures. In multivariate models, leptin represented a strong and independent determinant of HOMA-IR (R2 0.378; p<0.01). Adjustment for age, BMI
In prepubertal children, leptin emerges as a sex-independent discrimination marker of adiposity degree and as a useful, sex-associated predictor of the systemic insulin resistance.
Accumulating evidence indicates that chronic low-grade inflammation independently predicts the development of type 2 diabetes (T2D) and coronary heart disease (CHD)
Thus far, the alarming growth of childhood obesity is leading to a concomitant rise of the so-called “cardiometabolic syndrome” even in youth, explaining the relationship between higher BMI in adolescence and greater disease risk in adulthood
In this scenario, the characterization of a comprehensive profile of adipokines in adolescence appears of considerable interest for identification of “at-risk” individuals. Accordingly, in adults, the joint effect of leptin and adiponectin, as ascertained by the leptin-to-adiponectin ratio, has been proposed as a more reliable predictor of IR and vascular risk than measurement of adiponectin and leptin alone
As yet, in prepubertal childhood, the interrelations between HMW adiponectin, leptin and different inflammatory adipokines, as well as the effect modification by sex and adiposity have not been ascertained in detail
We studied 305 Italian children (boys/girls:144/161) aged 5–13 years, included in a cohort of 44,231 adolescents who participated in an extensive school-based project on growth conducted in the provinces of Perugia, Terni and Rieti of central Italy. The survey design and methods have been previously described in detail
Written informed consent was obtained from the parents of the children before their participation in the study, which has been approved by the Ethics Committee of the Umbria Region and carried out in accordance with the principles of the Helsinki Declaration.
Anthropometric data included height, body weight, body mass index (BMI), blood pressure, waist and hip circumferences, and the waist-to-hip ratio (WHR)
Blood samples were collected during routine analysis, after overnight fasting. Subjects were requested to maintain their usual diet 8-10 days before testing. After separation, sera aliquots were immediately stored at −70°C until analyzed. Follicle stimulating hormone (FSH) and luteinizing hormone (LH) were determined by immunoradiometric (IRMA) assay (CT Immunotec; Turin; Italy). Total testosterone (DRG, Milan, Italy) and dehydroepiandrosterone-sulphate (DHEA-S) (Radim, Rome, Italy) were assessed by radioimmunoassay (RIA), while free-testosterone and estradiol concentrations were evaluated by immunuoenzymatic assay (DiaMetra, Milan, Italy). Fasting plasma insulin was measured by RIA (Bouty, Cassina de' Pecchi, Milan, Italy), with intra- and inter-assay coefficients of variation (CV) <10%. Homeostasis model assessment of insulin resistance (HOMA-IR) was calculated as follows: fasting insulin (µU/ml) × fasting glucose (mmol/l)/22.5. Total adiponectin levels were analysed by RIA (Linco Research, St. Charles, MO, USA). HMW adiponectin oligomers were quantified by an enzyme-linked immunosorbent assay (ELISA) from ALPCO Diagnostics (Salem, NH, USA), according to the manufacturer's instructions. Under our experimental conditions, the intra- and inter-assay CV were both <5%. Finally, the serum concentration of leptin, interleukin (IL)-8, IL-18, monocyte chemoattractant protein-1 (MCP-1),
Categorized comparisons for sex- and BMI-stratified groups were analyzed by one-way ANOVA and Kruskal-Wallis test with appropriate post-hoc corrections (Bonferroni's, Tukey's and Kruskal-Wallis Z). Accordingly, for each response variable, the main effects of sex and BMI, as well as their interaction, were further ascertained by general linear models (factorial design). Univariate correlations were assessed by Spearman rho (
Before analysis, non-normally distributed data were appropriately transformed (Box-Cox transformation) to better approximate the Gaussian distribution (Kolmogorov-Smirnov test). Data are shown as mean±SD or median (25th; 75th percentile) for parametric and non parametric variables, respectively. P-values <0.05 were regarded as statistically significant. Statistical analysis was performed using Predictive Analytic Software release 17.0.2 (SPSS Inc., Chicago, IL, USA).
Participants' characteristics are outlined in
Boys | Girls | |||||
Lean (L) | Overweight (OW) | Obese (OB) | Lean (L) | Overweight (OW) | Obese (OB) | |
n. | 59 | 32 | 70 | 46 | 28 | 70 |
Age (yrs) | 9.2±2 | 9.9±1.3 |
8.6±1.1 | 8.6±1.8 | 8.8±1.6 | 9.3±1.3 |
BMI (kg/m |
16.0 (15.1–17.6) |
22.0 (20.9–22.7) |
25.7 (24.5–27.6) | 15.1 (14.2–16.2) |
21.3 (19.5–22.7) |
25.1 (23.8–26.8) |
BMIz-score | −0.45±0.7 |
1.2±0.2 |
2.0±0.3 | −0.64±0.8 |
1.2±0.2 |
2.1±0.4 |
Fat mass (kg) | 5.3 (3.7–7.3) |
10.8 (9.5–14.8) |
18.0 (14.1–22.8) | 4.4 (3.4–5.6) |
12.3 (9.0–14.01) |
15.7 (13.2–18.8) |
Waist circumference (cm) | 58.2 (53.2–61.0) |
73.5 (68.2–76.0) |
81.0 (76.0–87.3) | 54.0 (51.2–57.5) |
68.7 (66.6–74.5) |
78.0 (73.0–82.0) |
WHR | 0.85±0.04 |
0.88±0.04 | 0.92±0.07 | 0.85±0.04 |
0.91±0.15 |
0.88±0.05 |
Fasting glucose (mmol/l) | 4.5±0.5 | 4.4±0.5 | 4.4±0.4 | 4.2±0.6 | 4.3±0.4 | 4.4±0.4 |
Fasting insulin (pmol/l) | 40.9 (28.7–56.7) | 44.8 (37.5–58.8) |
66.0 (50.2–89.0) |
38.7 (21.5–52.2) |
59.2 (43.1–103.0) |
68.9 (52.4–97.6) |
HOMA-IR | 1.1 (0.8–1.7) | 1.2 (1.0–1.5) | 1.7 (1.3–2.3) |
1.0 (0.5–1.5) |
1.6 (1.2–1.4) |
1.8 (1.4–2.6) |
Total cholesterol (mmol/l) | 4.2 (3.9–4.9) | 4.4 (3.8–4.8) | 4.1 (3.8–4.6) | 4.6 (3.8–5.3) | 4.2 (3.8–4.6) | 4.2 (3.8–4.8) |
HDL-C (mmol/l) | 1.2 (1.0–1.3) | 1.1 (1.0–1.5) | 1.2 (0.9–1.4) | 1.2 (1.1–1.4) | 1.2 (1.0–1.4) | 1.1 (0.9–1.3) |
Triglycerides (mmol/l) | 0.6 (0.5–0.8) |
0.7 (0.5–0.8) |
0.8 (0.6–1.1) | 0.7 (0.6–0.8) |
0.8 (0.5–1.1) | 0.8 (0.7–1.3) |
SBPz-score | −0.070±0.912 | 0.426±0.922 | 0.157±1.020 | 0.001±0.882 | 0.132±0.889 | 0.317±0.987 |
DBPz-score | 0.295±0.672 | 0.356±0.779 | 0.547±0.712 | 0.249±0.864 | 0.206±0.751 | 0.357±0.687 |
FSH (IU/L) | 1.3 (0.6–2.0) | 0.7 (0.6–1.6) | 0.5 (0.1–1.0) |
1.6 (0.6–2.5) | 1.5 (0.7–2.9) | 1.0 (0.4–2.5) |
LH (IU/L) | 0.2 (0.1–0.8) |
0.3 (0.1–0.8) | 0.1 (0.1; 0.4) | 0.1 (0.1–0.2) | 0.2 (0.1–0.5) | 0.2 (0.2–0.3) |
Total testosterone (nmol/l) | 1.5 (0.7–1.7) | 0.7 (0.6–1.6) | 0.7 (0.7–1.0) | 0.7 (0.7–1.0) | 0.7 (0.7–1.3) | 0.7 (0.7–1.0) |
Free-testosterone (pmol/l) | 2.2 (1.4–3.5) | 2.1 (1.4–3.5) | 2.4 (1.6–3.8) | 2.4 (1.6–3.8) | 3.1 (1.9–3.6) | 2.4 (1.7–3.5) |
Estradiol (pmol/l) | NA | NA | NA | 73.6±32.6 | 72.9±32.6 | 64.3±31.4 |
DHEA-S (µmol/l) | 1.0 (0.8–2.5) | 1.8 (1.1–2.9) | 1.6 (0.8–2.8) | 0.9 (0.4–1.3) |
0.9 (0.6–1.5) | 1.3 (0.8–2.0) |
In categorized comparisons across the groups, total and HMW adiponectin showed a different sex distribution pattern (
Boxes represent median (line in the middle of the boxes) and interquartile ranges (25th and 75th percentile; lines at the bottom and the top of the boxes, respectively). Error bars are 5th and 95th percentiles. Differences between groups were analysed by Kruskal-Wallis test with Bonferroni's post-hoc correction. L: lean; OW: overweight; OB: obese; ¶p = 0.001 vs OB boys and OB girls; #p<0.001 vs OW and OB girls and vs OB boys; *p<0.0001 vs OW and OB boys and vs OW and OB girls; †p<0.0001 vs L and OB boys and vs L and OB girls; ‡p<0.0001 vs L and OW boys and vs L girls; **p<0.0001 vs L and OW boys and girls; §p<0.0001 vs L girls and boys.
In both sexes, leptin and L/HMW (
Overall, these data suggest that, while in L prepubertal children HMW adiponectin may exhibit a tendency toward a sexual dimorphism, leptin emerges as sex-independent discrimination marker of adiposity degree.
The concentrations of inflammatory chemokines and cytokines are shown in
Boys | Girls | |||||
Lean (L) | Overweight (OW) | Obese (OB) | Lean (L) | Overweight (OW) | Obese (OB) | |
n. | 59 | 32 | 70 | 46 | 28 | 70 |
IL-8 (pg/ml) | 4.1 (1.9–7.7) | 4.8 (2.7–7.0) | 5.0 (2.5–10.4) | 4.6 (2.7–6.3) | 3.4 (2.3–5.3) | 5.3 (3.6–9.9) |
IL-18 (pg/ml) | 241.3 (170.9–320.9) | 188.4 (136.9–276.2) | 200.1 (149.2–265.5) | 182.6 (121.6–262.9) | 178.1 (144.7–242.9) | 240.6 (159.7–334.5) |
MCP-1 (pg/ml) | 688.7 (490.9–1058.9) | 785.3 (611.7–987.9) | 866.6 (601–1146.5) | 543.7 (419.7–809.6) | 781.1 (471.9–1038.4) | 821.4 (677.7–1051.9) |
RANTES (ng/ml) | 138.6 (101.5–219.8) | 143.1 (89.7–200.3) | 166.8 (134.2–219.6) | 132.3 (99.9–232.9) | 163.7 (135.7–230.2) | 185.1 (123.5–232.6) |
MIF (pg/ml) | 3756 (3221–4562) | 3617 (3141–4043) |
4190 (3525–4784) |
3893 (3244–5047) | 3927 (3484–4639) | 4332 (3585–5046) |
sICAM-1 (ng/ml) | 32.1 (29.0–38.4) | 30.9 (26.1–37.0) | 33.2 (28.0–40.0) | 31.6 (26.5–36.4) | 33.2 (28.6–43.1) | 34.2 (29.2–40.1) |
IP-10 (pg/ml) | 166.6 (131.7–259.1) | 178.2 (130.9–241.1) | 177.3 (145.8–221.2) | 168.2 (125.9–245.0) | 176.4 (129.5–276.6) | 193.1 (159.2–256.3) |
Resistin (pg/ml) | 1701 (1276–1872) | 1644 (1273–2017) | 1728 (1412–2095) | 1541 (1270–2140) | 1539 (1320–2091) | 1884 (1476–2168) |
Altogether, these data confirm the lack of a universal upregulation of the immune response also in prepubertal obesity
In order to ascertain the interrelationships between HMW adiponectin, leptin and inflammatory cytokines/chemokines, individually or in combinations, with sex, adiposity or IR, we performed correlation analyses and constructed multivariate models in the combined study population and within each sex.
First, in both sexes, we found no significant association of leptin, HMW adiponectin or inflammatory molecules with gonadal steroids (supplementary
Second, multivariate regression models were constructed to predict HMW adiponectin levels (
Model | Independent Variable(s) | β |
|
Model R2 |
|
Fasting insulin | −0.221 | <0.0001 | 0.049 |
|
Fasting insulin | −0.142 | 0.037 | 0.068 |
BMI |
−0.160 | 0.019 | ||
|
Fasting insulin | −0.100 | 0.151 | 0.093 |
BMI |
−0.128 | 0.063 | ||
Triglycerides | −0.112 | 0.078 | ||
HDL | −0.122 | 0.041 | ||
|
Fasting insulin | −0.127 | 0.085 | 0.102 |
BMI |
−0.230 | 0.017 | ||
Triglycerides | −0.135 | 0.039 | ||
HDL | −0.130 | 0.099 | ||
Leptin | 0.159 | 0.121 | ||
sICAM-1 | −0.028 | 0.652 | ||
|
Fasting insulin | −0.123 | 0.098 | 0.106 |
BMI |
−0.225 | 0.027 | ||
Triglycerides | −0.144 | 0.030 | ||
HDL | 0.108 | 0.085 | ||
Leptin | 0.152 | 0.180 | ||
sICAM-1 | −0.033 | 0.603 | ||
Age | 0.012 | 0.867 | ||
Sex |
0.060 | 0.353 |
*Sex entered in regression model as “dummy” variable (0 = girls; 1 = boys).
β-coefficients,
Third, we explored whether leptin, HMW adiponectin or the L/HMW might have explained the systemic IR as estimated by HOMA-IR. In the combined study population (
Independent variables | |||||||||
Model | Leptin | HMW | L/HMW | ||||||
β |
|
Model R2 | β |
|
Model R2 | β |
|
Model R2 | |
1 |
0.551 | <0.0001 | 0.304 | −0.206 | 0.001 | 0.04 | 0.548 | <0.0001 | 0.300 |
2 |
0.326 | <0.0001 | 0.352 | −0.058 |
|
0.323 | 0.306 | <0.0001 | 0.355 |
3 |
0.291 | <0.01 | 0.378 | −0.055 |
|
0.357 | 0.272 | <0.01 | 0.381 |
*Unadjusted model.
Model adjusted for age, BMI
Additional adjustment for sex, sICAM-1, IL-8, MCP-1, RANTES, MIF and IP-10. Sex entered in regression model as “dummy” variable (0 = girls; 1 = boys). NS, statistically not significant. β-coefficients and
Boys | |||||||||
Independent variables | |||||||||
Leptin | HMW | L/HMW | |||||||
Model | β |
|
Model R2 | β |
|
Model R2 | β |
|
Model R2 |
1 |
0.471 | <0.0001 | 0.222 | −0.124 |
|
0.015 | 0.465 | <0.0001 | 0.217 |
2 |
0.193 |
|
0.264 | −0.04 |
|
0.256 | 0.204 |
|
0.269 |
3 |
0.167 |
|
0.308 | −0.057 |
|
0.303 | 0.196 |
|
0.314 |
Girls | |||||||||
Independent variables | |||||||||
Leptin | HMW | L/HMW | |||||||
Model | β |
|
Model R2 | β |
|
Model R2 | β |
|
Model R2 |
1 |
0.627 | <0.0001 | 0.393 | −0.265 | <0.01 | 0.070 | 0.606 | <0.0001 | 0.368 |
2 |
0.49 | <0.0001 | 0.454 | −0.058 |
|
0.392 | 0.351 | <0.01 | 0.434 |
3 |
0.415 | <0.01 | 0.513 | −0.044 |
|
0.47 | 0.304 | <0.01 | 0.500 |
*Unadjusted model.
Model adjusted for age, BMI
Additional adjustment for sICAM-1, IL-8, MCP-1, RANTES, MIF and IP-10.
Finally, multivariate models indicated the BMI
Model | Independentvariable(s) | β |
|
Model R2 |
|
BMI |
0.779 | <0.0001 | 0.606 |
|
BMI |
0.636 | <0.0001 | 0.667 |
HOMA-IR | 0.192 | <0.0001 | ||
Triglycerides | 0.160 | <0.0001 | ||
LDL | −0.045 |
|
||
|
BMI |
0.641 | <0.0001 | 0.671 |
HOMA-IR | 0.194 | <0.0001 | ||
Triglycerides | 0.153 | <0.0001 | ||
LDL | −0.044 |
|
||
HMW | 0.054 |
|
||
MCP-1 | 0.003 |
|
||
RANTES | 0.054 |
|
||
MIF | −0.035 |
|
||
Sex |
−0.071 | 0.051 |
*Sex entered in regression model as “dummy” variable (0 = girls; 1 = boys). NS, statistically not significant; β-coefficients,
Altogether, these findings circumstantiate the concept that, in prepubertal age, adiposity may concur with altered lipid profile to the impairment of HMW adiponectin, which appears partly independent from low-grade inflammation. Finally, in this cohort of prepubertal children, we found that leptin, at least in girls, was an independent determinant of the basal insulin resistance, and, independently from sex, it emerged as a stronger contributor of HOMA-IR than HMW adiponectin.
This study shows that, already in prepubertal age, obesity is linked with hyperleptinemia, impaired HMW adiponectin levels, as well as alterations of specific immune mediators with minor sex-associated differences. Notably, in this very young population, leptin, rather than HMW adiponectin, emerges as a sex-independent discrimination marker of adiposity degree, as well as a sex-related predictor of basal insulin resistance. Finally, also in prepubertal obesity, we confirm the lack of a universal upregulation of the immune response.
In obese children, persistent low-grade inflammation appears to increase the metabolic risk in later life. The importance to investigate adipose-derived mediators during the developmental stages of overweight and obesity allows to identify at what age and degree of adiposity these pathological events may occur. Our current work describes the combined associations of obesity, IR and sex on a cluster of adipokines in prepubertal children. The characterization of a wide panel of adipose-derived mediators, rather than measurement of single molecules only, appears of considerable importance in youth since current conventional risk factors may not be sensitive enough to detect high-risk individuals, and the prognostic information provided may be different to those in older obese subjects.
As yet, most of the studies on children analyzed a limited number of adipose-produced mediators, and comparative analyses for sex and pubertal stage were not always stratified over wide BMI ranges
Among the adipokines, adiponectin and leptin are unique hormones because these pleiotropic mediators are almost exclusively secreted by the adipocytes, and their systemic levels reflect the degree of fat accrual in a reciprocal manner
As long as at this age consistent effects of gonadal steroids appear unlikely, different reasons may underlie the dysfunctional profile of these adipokines. First, the lack of interconversion of the adiponectin complexes in the bloodstream highlights the importance of the adipocyte secretory pathway in determining the circulating pattern of adiponectin isoforms
Second, since hyperinsulinemia or IR may either induce hyperleptinemia or promote the selective downregulation of the HMW adiponectin forms
Third, although HMW adiponectin, leptin and inflammatory markers appear to some extent interdependent, the addition of leptin and sICAM-1 as “inflammation-related” confounders did not improve the prediction of HMW adiponectin, fostering the concept that, although mutually antagonistic, low-grade inflammation and HMW adiponectin may reflect two distinct features of the immune response, as previously postulated
In adolescents, various and controversial studies addressed the sex-associated variability of total adiponectin and leptin
On the other hand, sex represented an “effect modifier” in the interaction between leptin and basal IR. Our observation that leptin was an independent determinant of HOMA-IR in girls, but not in boys (
Turning to the other major finding of this study, childhood obesity is not characterized by a generalized immune activation, but rather a differential upregulation of specific chemokines/cytokines with minor sex differences
This study has some limitations that need to be considered. The cross-sectional nature of the survey does not allow conclusions to be drawn about the true prognostic values and the molecular mechanisms underlying the relationships between adipokines and IR. In addition, since in prepubertal age overweight and obesity may not necessarily track into adulthood, the prognostic relevance of these results should be further ascertained. However, obesity-linked variations of adipokines levels we found were almost comparable to those that predicted the risk of diabetes in adults
These constraints have to be weighed against the strengths of our survey which reside in the sample size, the representative nature of the population studied, the extensive characterization of the study participants, the simultaneous determination of multiple adipokines as well as the careful adjustment for various confounders using multivariable methods.
In conclusion, our findings demonstrate that, as early as in prepubertal age, adiposity exhibits an unfavourable pattern of adipokines with minor sex-associated differences. However, among the adipose-derived mediators, leptin can be envisioned as a sex-independent discrimination marker of adiposity degree and, at least in girls, a reliable indicator of the systemic insulin resistance as estimated by HOMA-IR. Therefore, in prepubertal children, hyperleptinemia may allow the early identification of “at-risk” individuals, providing important prognostic information in predicting the impairment of glucose homeostasis.
Spearman's rho correlation coefficients (r
(DOC)
Spearman's rho correlation coefficients (r
(DOC)
Spearman's rho correlation coefficients (r
(DOC)
Partial correlation coefficients of leptin, HMW adiponectin, L/HMW, pro-inflammatory adipokines and insulin-resistance measures after adjustment for BMI
(DOC)
Multiple regression models for the prediction of leptin (dependent variable) in boys. β-coefficients,
(DOC)
Multiple regression models for the prediction of leptin (dependent variable) in girls. β-coefficients,
(DOC)