Altered adipokines in obese adolescents: a cross-sectional and longitudinal analysis across the spectrum of glycemia

Abstract

Obesity and type 2 diabetes are rapidly increasing in the adolescent population. We sought to determine whether adipokines, specifically leptin, C1q/TNF-related proteins 1 (CTRP1) and CTRP9, and the hepatokine fibroblast growth factor 21 (FGF21), are associated with obesity and hyperglycemia in a cohort of lean and obese adolescents, across the spectrum of glycemia. In an observational, longitudinal study of lean and obese adolescents, we measured fasting laboratory tests, oral glucose tolerance tests, and adipokines including leptin, CTRP1, CTRP9, and FGF21. Participants completed baseline and 2-year follow-up study visits and were categorized as lean (LC, lean control; n = 30), obese normoglycemic (ONG; n = 61), and obese hyperglycemic (OHG; n = 31) adolescents at baseline and lean (n = 8), ONG (n = 18), and OHG (n = 4) at follow-up. Groups were compared using ANOVA and regression analysis, and linear mixed effects modeling was used to test for differences in adipokine levels across baseline and follow-up visits. Results showed that at baseline, leptin was higher in all obese groups (P < 0.001) compared with LC. FGF21 was higher in OHG participants compared with LC (P < 0.001) and ONG (P < 0.001) and positively associated with fasting glucose (P < 0.001), fasting insulin (P < 0.001), Homeostasis Model Assessment-Insulin Resistance Index (HOMA-IR; P < 0.001), and hemoglobin A1c (HbA1c; P = 0.01). CTRP1 was higher in OHG compared with ONG (P = 0.03). CTRP9 was not associated with obesity or hyperglycemia in this pediatric cohort. At 2 years, leptin decreased in ONG (P = 0.003) and FGF21 increased in OHG (P = 0.02), relative to lean controls. Altered adipokine levels are associated with the inflammatory milieu in obese youth with and without hyperglycemia. In adolescence, the novel adipokine CTRP1 was elevated with hyperglycemia, whereas CTRP9 was unchanged in this cohort.

NEW & NOTEWORTHY Leptin is higher in obese adolescents and FGF21 is higher in obese hyperglycemic adolescents. The novel adipokine CTRP1 is higher in obese hyperglycemic adolescents, whereas CTRP9 was unchanged in this adolescent cohort.

INTRODUCTION

Obesity affects up to 18% of youth in the United States, and the prevalence has been increasing over the past decade (1). Obesity and increased body mass index (BMI) are risk factors for insulin resistance, which has led to increasing prevalence of prediabetes and type 2 diabetes in the pediatric and adolescent populations (2, 3).

Obesity is associated with alterations in adipose-tissue-derived hormones (known as adipokines) that contribute to inflammation and insulin resistance (4–6). Although the role of adipokines and inflammatory cytokines has been extensively studied in the adult population with obesity and diabetes, there are more limited data in the pediatric population. However, with the pediatric obesity epidemic and increased prevalence of type 2 diabetes (T2DM) in children, it is important to understand the role of adipokines, both common and novel, in the setting of obesity and diabetes.

Adiponectin, an antidiabetic and anti-inflammatory adipokine, is decreased in both children and adults with obesity and metabolic syndrome, with hypoadiponectinemia being a risk factor for T2DM (7–12). Leptin is an appetite-regulating adipokine secreted by white adipose tissue that is elevated in the setting of obesity and associated with insulin resistance (13–17). Leptin-adiponectin imbalance is a biomarker for metabolic syndrome in children with obesity (14, 18, 19). Both adiponectin and the C1q/TNF-related proteins (CTRPs) belong to the larger C1q family of secreted plasma proteins and play important roles in regulating various aspects of glucose and/or lipid metabolism (20–24). CTRP1 and CTRP9 are novel adipokines that are elevated in adults with obesity and T2DM (25–27), but these novel adipokines have not been investigated in the pediatric or adolescent population. Fibroblast growth factor 21 (FGF21), a hepatokine, is primarily expressed and secreted by liver and functions as a potent activator of glucose uptake in adipocytes (28, 29). FGF21 is reported to be elevated in the setting of adult obesity (29–31), but its role in the setting of pediatric obesity and diabetes is understudied and less clear (13, 32, 33).

Although a cross-sectional analysis of adiponectin has been reported for the current cohort (9), the aim of this study was to determine whether circulating levels of other adipokines, specifically leptin, FGF21, CTRP1, and CTRP9, are associated with obesity and hyperglycemia in this cohort of lean and obese adolescents. Furthermore, we examined whether these adipokines were predictive of longitudinal outcomes related to obesity and insulin resistance.

METHODS

Patient Population

This was an observational, longitudinal study of lean and obese pubertal (Tanner stage > 1), adolescents aged 12–17 yr, who had completed a baseline study visit, with a 2-year follow-up study visit in a subset of participants. Obese participants had a BMI ≥ 95 percentile for age and sex. A lean control (LC) group included participants with BMI = 5–85 percentile for age and sex. Exclusion criteria included major chronic illness (other than T2DM), pregnancy, genetic syndrome known to affect glucose tolerance, treatment with systemic steroids or high-dose inhaled steroids (>1,000 µg/day), known familial hypercholesterolemia, and medication use known to affect insulin sensitivity (i.e., metformin except for adolescents enrolled in the T2DM cohort). Participants were recruited from clinics affiliated with The Children’s Hospital of Philadelphia (CHOP), serving a largely urban, African American population. Additional inclusion criteria for adolescents with T2DM were hemoglobin A1c (HbA1c) < 8.5% and negativity for two out of three diabetes autoantibodies [glutamic acid decarboxylase (GAD65), islet cell cytoplasmic autoantibodies (ICA 512) and insulin antibodies]. Written informed consent and age-appropriate assent were obtained on the day of the study visit from all subjects before participation, and the study was approved by the CHOP Institutional Review Board.

Procedures

Study visits took place from October 2007 through April 2011 at the Clinical Translational Research Center (CTRC) of CHOP and the Hospital of the University of Pennsylvania, as previously described (9). Subjects were categorized into three groups: lean controls (LC), obese normoglycemic (ONG), and obese hyperglycemic (OHG). Participants in the lean control group had fasting laboratory tests performed but did not do an oral glucose tolerance test. Obese participants were instructed to have 3 days of a high-carbohydrate diet before the study visit in preparation for a 2-h oral glucose tolerance test (OGTT) and came in after a 12-h fast. At the start of the OGTT, baseline fasting laboratory tests were drawn, including glucose, insulin, HbA1c, lipid panel, leptin, adiponectin, FGF21, CTRP1, and CTRP9. Participants were then asked to ingest a glucose solution (1.75 g/kg up to max of 75 g) over 2 min. Blood was again drawn for glucose and insulin at 30, 60, 90, and 120 min. Obese participants not known to have T2DM at recruitment were categorized based on OGTT as obese normoglycemic if they had normal fasting and 2-h blood glucoses on OGTT and as obese hyperglycemic if they had impaired fasting glucose (IFG), impaired glucose tolerance (IGT), or diabetes as per American Diabetes Association (ADA) criteria (34). For this secondary analysis, subjects were categorized into three groups: lean controls (LC), obese normoglycemic (ONG), and obese hyperglycemic (OHG). HbA1c was not used for group categorization. Participants with known T2DM in the OHG group were required to discontinue oral diabetes medications before the study visit (4 days for metformin and 2 wk for thiazolidinediones). They were given strict dietary recommendations, and blood sugars were monitored closely by home glucometer, and in conjunction with the investigative team for 2 wk before the study visit. If fasting blood glucoses rose above 125 mg/dL, Glargine or Lantus insulin injections, and/or intermittent doses of short-acting subcutaneous insulin, were used to control blood sugars. Participants normally treated with insulin were continued on their usual insulin treatment until 36 h before the baseline visit for Glargine, 24 h before the baseline visit for Neutral Protamine Hagedorn (NPH) insulin, and by 8 PM the day before the baseline visit for short-acting insulin. IFG from either study day categorized the patient having IFG. Fasting insulin and glucose from the baseline visit were used to calculate Homeostasis Model Assessment-Insulin Resistance Index (HOMA-IR) as follows: [fasting insulin (µIU/mL) × fasting glycemia (mmol/L)]/22.5 for those without diabetes, as this measure is not validated in diabetes. Waist circumference was measured at the umbilicus. Triglycerides, total cholesterol, and HDL-C were assayed on a Hitachi 912 using Roche reagents. LDL-C was calculated using the Friedewald equation [LDL-C = TC − HDL-C − (TG/5)], where TG is triglycerides, TC is total cholesterol, HDL-C is high-density lipoprotein cholesterol. No subjects had a triglyceride level >4.52 mmol/L (400 mg/dL), which would have made the equation invalid. Insulin was measured by ELISA, using a kit from Alpco Diagnostics (Salem, NH).

Insulin sensitivity and secretion measures from OGTTs were calculated as follows: Matsuda index = 10,000/[sqrt(fasting glucose × fasting insulin)(mean glucose × mean insulin)] (35). Insulinogenic index (IGI) = delta insulin (0−30 min)/delta glucose (0−30 min) (36). Disposition index = (1/fasting insulin)/IGI (37). Quantitative insulin sensitivity check index (QUICKI) is a measure of insulin sensitivity = 1(log-transformed fasting insulin + log-transformed fasting glucose) (38).

Fat mass, fat-free mass, and percent body fat were also measured with dual-energy X-ray absorptiometry (DXA) using a Hologic QDR2000 instrument (Hologic, Waltham, MA) and analyzed using the Enhanced Whole Body V5.71A software provided by Hologic.

Laboratory Measurements

Human adiponectin was measured by ELISA (Alpco Diagnostics, Salem, NH). Human CTRP9, CTRP1, FGF21, and leptin were measured by ELISA (Biovendor, Czech Republic). Intra-assay coefficients of variation (CVs) were 5.9 ± 0.4 for leptin, with interassay CVs of 5.5 ± 1.16 (leptin). For the CTRP9 ELISA, as per the manufacturer, intra-assay variation was 5.5% and interassay variation was 7.9%. For the CTRP1 ELISA, as per the manufacturer, intra-assay variation was 2.7% and interassay variation was 8.5%. For the FGF21 ELISA, as per the manufacturer, intra-assay variation was 2% and interassay variation was 3.3%.

Statistical Analysis

Baseline demographic data were associated with lean control (LC) and obese groups (ONG and OHG) using linear modeling for quantitative measurements/traits, by calculating an overall ANOVA F statistic and corresponding P value for mean differences across groups and direct regression coefficients (and P values) for each obese group relative to the LC group. Categorical measurements/traits were associated with outcome group using chi-squared testing and extracting the corresponding P value (Table 1, Fig. 1). Baseline adipokines were correlated to clinical characteristics using the Pearson correlation coefficient, with corresponding t statistics and P values. A cutoff of P = 0.0055 was used to control for a false discovery rate at <0.05 and allowing for correlated and dependent tests (Fig. 2). Linear mixed-effects modeling was used to test for differences in adipokine levels across baseline and follow-up visits, associating each adipokine level with main effects of outcome group (LC, ONG, and OHG), visit (baseline or follow-up), and their statistical interaction (to assess temporal trends), adjusting for fixed effects of BMI, age, and gender, while treating each patient as a “unit of analysis” via the random intercept (Fig. 3). Analogous models were used to test for temporal changes across Matsuda, insulinogenic, and disposition indices, but these indices were only assessed in the subset of obese patients. P values < 0.05 were considered statistically significant across all analyses.

Table 1.

Baseline characteristics of study subjects

Characteristics	Lean	ONG	OHG	P Value (All Groups)	P Value (ONG vs. OHG)
N	30	61	31
Sex, female, n (%)	13 (43)	41 (67)	16 (52)	0.07	0.2
Age, yr	14.7 (1.3)	14.5 (1.4)	14.4 (1.4)	0.7	0.7
Race, n (%), African American	24 (80)		25 (81)	0.3	0.6
Tanner stage, n (%)				0.005	0.1
2	0 (0)	2 (3)	1 (3)
3	1 (3)	4 (7)	6 (19)
4	15 (50)	11(18)	6 (19)
5	14 (47)	44 (72)	17 (55)
Weight, kg	56.4 (7.8)	95.8 (21)	100.4 (21.5)	<0.0001	0.3
Body mass index, kg/m2	20.1 (1.8)	34.7 (6)	35.3 (6.7)	<0.0001	0.7
Waist circumference, cm	71 (6.5)	103 (15)	108 (15)	<0.0001	0.1
Fasting glucose, mg/dL	86.6 (5.8)	88.3 (5.7)	97.7 (10.7)	<0.0001	<0.0001
Fasting insulin, µIU/mL	8.4 (4.2)	21.0 (12.3)	29.7 (18.7)	<0.0001	0.008
HOMA-IR	1.8 (0.9)	4.6 (3)	7.1 (4.1)	<0.0001	0.001
Hemoglobin A1c, %	5.2 (0.3)	5.3 (0.3)	5.7 (0.7)	<0.0001	<0.0001
Total cholesterol, mg/dL	150 (26)	152.6 (31)	153 (31)	0.9	0.9
Triglycerides, mg/dL	56 (19.2)	78.9 (35)	86 (31.5)	0.0004	0.3
HDL cholesterol, mg/dL	56 (13)	43 (10)	40 (9)	<0.0001	0.1
LDL cholesterol, mg/dL	83 (18.6)	94 (29)	96 (28.3)	0.09	0.7
Adiponectin, ng/mL	6648 (2436)	4233 (1684)	4192 (2361)	<0.0001	0.9
Leptin, ng/mL	13 (14)	87 (42)	59 (17)	<0.0001	0.002
FGF21, pg/mL	54 (57)	52 (53)	123 (89)	<0.0001	<0.0001
CTRP1, ng/mL	332 (99)	307 (83)	352 (118)	0.09	0.03
CTRP9, ng/mL	15 (19)	12 (16)	9 (10)	0.4	0.4
Matsuda index	NA	0.04 (0)	0.03 (0)		0.4
Insulinogenic index	NA	4.5 (3.9)	3.8 (3.6)		0.4
Disposition index	NA	0.25 (0.2)	0.17 (0.3)		0.2

Data are represented as means ± SD, with P values calculated by ANOVA for all groups and by Student’s t test for two-group comparisons. In the OHG group, missing Tanner staging for one subject. Matsuda index, insulinogenic index, and disposition index were not assessed in lean patients because OGTTs were not performed. CTRP1, C1q/TNF-related proteins 1; CTRP9, C1q/TNF-related proteins 9; FGG21, fibroblast growth factor 21; HOMA-IR, Homeostasis Model Assessment-Insulin Resistance Index; NA, not assessed; OGTT, oral glucose tolerance test; OHG, obese hyperglycemic; ONG, obese normoglycemic.

Figure 1.

Relationship between adipokines and adolescent cohorts; LC (n = 30), ONG (n = 61), and OHG (n = 31). *P < 0.05 with black lines indicating comparison groups. All boxplots shown in the figures, display the median as the center, interquartile range (IQR, 25th and 75th percentiles) as the box ranges, and 1.5 times the IQR as the whiskers. LC: n = 13 females/17 males, ONG: n = 41 females/20 males, and OHG: n = 16 females/15 males. CTRP1, C1q/TNF-related proteins 1; CTRP9, C1q/TNF-related proteins 9; FGG21, fibroblast growth factor 21; LC, lean control; ONG, obese normoglycemic; OHG, obese hyperglycemic.

Figure 2.

The heatmap demonstrates the relationship between metabolic characteristics and adipokines. Red is positively associated and blue is negatively associated, with darker or lighter indicating the magnitude of the association. *P < 0.0055 account for multiple comparisons.

Figure 3.

Changes in adipokine levels between baseline and follow-up in the adolescent cohorts. LC: n = 8 (5 females/3 males), ONG: n = 18 (12 females/6 males), and OHG: n = 4 (1 female/3 males). CTRP1, C1q/TNF-related proteins 1; CTRP9, C1q/TNF-related proteins 9; FGG21, fibroblast growth factor 21; LC, lean control; ONG, obese normoglycemic; OHG, obese hyperglycemic.

RESULTS

Patient Demographics and Baseline Clinical Characteristics

Our cohort included 122 patients (52 males and 70 females) with a mean age of 14.5 ± 1.4 yr (range, 12.1–17.3 yr). Mean BMI of lean participants (n = 30) was 20 ± 1.8 kg/m² (range, 16.4–23.7) and of obese youth (n = 92) was 34.9 ± 6.2 kg/m² (range: 26.7–54), P < 0.01. The study participants included 97 African American (80%), 11 White (9%), 11 mixed-race (9%), and three other (2%). Tanner stages of the overall baseline cohort were as follows: Tanner 2 (3%), Tanner 3 (9%), Tanner 4 (26%), and Tanner 5 (62%). Baseline mean metabolic parameters were within the normal ranges for all laboratory testing in the lean group. The baseline characteristics of all study subjects are summarized in Table 1. The obese groups (ONG and OHG) showed significantly higher mean BMI (by design), waist circumference, fasting glucose, insulin, HOMA-IR, HbA1c, triglycerides, and leptin when compared with the lean control group. HDL-cholesterol and adiponectin were significantly lower in the obese groups compared with the lean group.

Adipokine Differences across Patient Groups

The relationship between adipokines and patient groups is demonstrated in Fig. 1, A–E. Leptin was significantly higher in obese youth compared with lean individuals and higher in the ONG group compared with OHG groups (P < 0.001). FGF21 was significantly higher in the OHG group compared with the ONG and lean groups (P < 0.001). There were no differences in CTRP9 between the lean, ONG, and OHG cohorts. CTRP1 was higher in the OHG compared with the ONG cohort (P = 0.03).

Association between Adipokines Levels and Metabolic Parameters

Leptin was higher in females than males, but there was otherwise no difference in any of the adipokine levels by age, sex, or race/ethnicity. As shown in the heatmap (Fig. 2), both leptin and FGF21 are positively associated with increasing weight and BMI (P < 0.001). Leptin is also positively correlated with fasting insulin and HOMA-IR (P < 0.001) and negatively correlated with QUICKI (P < 0.001). FGF21 is positively associated with fasting glucose (P < 0.001), fasting insulin (P < 0.001), and HOMA-IR (P < 0.001) and negatively associated with QUICKI (P < 0.001). Although not significant with a P value cutoff of P = 0.0055 to account for multiple comparisons, FGF21 was positively associated with HbA1c (P = 0.01), and CTRP9 was inversely correlated with insulin (P = 0.03) and HOMA-IR (P = 0.04) and positively associated with QUICKI (P = 0.02). CTRP1 was positively associated with fasting glucose (P = 0.05). Although leptin was negatively associated with adiponectin (P = 0.01), CTRP9 was positively associated with adiponectin (P = 0.03). Further analysis examining components of body composition showed that fat mass and percent body fat were positively associated with leptin and negatively associated with CTRP9. Fat-free mass was not associated with any of the target adipokines.

Longitudinal Trajectory of Adipokines

Of the participating subjects, 30 patient samples were available for follow-up analysis (LC = 8, ONG = 18, and OHG = 4), and these subjects had no significant changes in BMI and remained in their initial cohorts when tested again 2 years after visit 1. Figure 3 demonstrates the longitudinal trajectories of the adipokines between baseline and follow-up visits. Linear mixed-effects modeling controlling for gender, age, and BMI showed that leptin at baseline was highly correlated with leptin at follow-up, and leptin decreased significantly in the ONG groups by follow-up relative to lean controls (P = 0.003). FGF21 increased over time in the OHG group relative to lean controls (P = 0.02). CTRP1, CTRP9, and adiponectin did not change significantly over time, even when adjusted for BMI. Longitudinal changes in adipokines were independent of BMI and age.

OGTT Data at Baseline between Groups and at Follow-up

Participants in the OHG group had higher glucose and insulin levels on OGTT compared with those in the ONG group (P < 0.01). At baseline, there were no differences in the Matsuda index or insulinogenic index between the groups. At baseline, there was an association between the insulinogenic index and FGF21 levels, specifically driven by the OHG group (interaction P value = 0.044), but there were no other significant relationships between OGTT indices and adipokines. Although there was no intervention between the baseline and follow-up visits, we sought to identify any natural longitudinal changes in insulin resistance across time. However, there were no changes in Matsuda index, insulinogenic index, or disposition index (P = 0.65) over time. Only baseline adiponectin showed a significant negative correlation with follow-up fasting glucose (P = 0.007). Otherwise, baseline adipokine levels did not predict longitudinal changes in BMI, glucose, HOMA-IR, and HbA1c.

DISCUSSION

As the prevalence of pediatric obesity and diabetes increases, it is becoming more apparent that the inflammatory milieu that exists in adults with obesity is also present in obese youth. Several studies have reported abnormalities and changes in adipokine levels as a marker of adipose tissue dysfunction in the pediatric population (13, 39, 40). Although our data support previously reported trends in leptin and FGF21, to our knowledge, this is the first study examining the novel adipokines CTRP1 and CTRP9 in obese youth. Furthermore, we explored the longitudinal trajectory of adipokines in both lean and obese youth over a 2-year observational time frame, offering a new look at the ongoing relationship of adipokines and pediatric obesity.

Adiponectin, a well-recognized, anti-inflammatory, and insulin-sensitizing adipokine, has been shown to be lower in children and adolescents with obesity and is negatively associated with the development of metabolic syndrome, insulin resistance, and hypertension in pediatric subjects (9, 14, 39, 41). The relationship of adiponectin has been previously described in this cohort, demonstrating that obese subjects have lower adiponectin levels than lean controls (9). Although adiponectin levels did not change over time in this cohort, baseline adiponectin levels were negatively correlated with follow-up glucose level. This is consistent with results from the TODAY (Treatment Options for type 2 Diabetes in Adolescents and Youth) study, in which lower adiponectin at enrollment was a predictor of treatment failure in youth with type 2 diabetes (42). Worsening β-cell function, as measured by the disposition index, has been well described in youth with type 2 diabetes (42), but we did not see a change in disposition index over time and among groups in this cohort. This may be due to the small follow-up group sizes but may also not be seen in these individuals who remained within their original groups over 2 years, without further deterioration in glycemic control.

Similar to previous studies in adults and youth (13, 14, 40, 43, 44), leptin levels were significantly higher in the obese groups compared with the lean control group. Previous studies in pediatrics have shown discrepant results on the relationship of leptin and type 2 diabetes (44–46). We found leptin levels to be lower in obese adolescents with hyperglycemia, similar to the study by Reinehr et al. (44) showing lower leptin levels in a cohort of obese adolescents with T2DM compared with age-matched, gender-matched, and BMI-matched adolescents without type 2 diabetes, whereas other studies have shown higher leptin levels in adolescents with type 2 diabetes (45). Interestingly, in our cohort, although leptin levels at baseline and 2 years later were highly correlated, there was a decrease in leptin levels in the ONG group over the 2-year time frame, independent of BMI. This was a small subset of patients, and larger longitudinal studies will need to further evaluate this trend.

FGF21 is a hepatokine that plays an important role in adipose tissue metabolism by promoting glucose uptake by adipocytes (47, 48) and reduces blood glucose in diabetic mouse models (49). Several studies have shown higher FGF21 levels in obese compared with lean children (13, 33, 50), and although we did not find a significant difference in FGF21 levels between lean and obese subjects, FGF21 was significantly associated with BMI. However, our aggregated obese cohort includes a range of insulin resistance and thus may not match cohorts of obese children that were reported in previous studies (33, 50). We showed that FGF21 is elevated in the OHG group and continues to rise over time in that cohort. This is consistent with findings from the BCAMS (Beijing Children and Adolescents Metabolic Syndrome Study) study of Chinese children that also found higher FGF21 levels in subjects with impaired glucose tolerance compared with normal glucose tolerance (40). In our study, FGF21 was similarly positively associated with glucose, insulin, HOMA-IR, and HbA1c. Elevated FGF21 levels in obesity and impaired glucose tolerance may reflect a compensatory mechanism, as a longitudinal analysis of weight loss in children was associated with a decrease in FGF21 levels (33). A study in normal-weight children and obese youth showed no correlation between baseline FGF21 levels and the dynamic changes in glucose and insulin levels during the OGTT, but the authors hypothesized that this was due to glucose tolerance in their obese cohort (51). However, we identified an association between the insulinogenic index and FGF21 levels, specifically driven by the OHG group, which supports the compensatory mechanism hypothesis in that FGF21 levels rise with early-phase insulin response during OGTT (33).

CTRP1 is a secreted adipokine that enhances fatty acid oxidation and promotes whole body energy expenditure (20, 22). CTRP1 is increased in obesity and may represent a compensatory mechanism in the setting of increased inflammation (52). Studies in adults have shown that CTRP1 levels are increased in obesity and obesity-associated disorders, including metabolic syndrome (53), type 2 diabetes (26, 54, 55), hypertension (56), and nonalcoholic fatty liver disease (57, 58). Similar to the study by Muendlein et al. (57), we also found CTRP1 levels to be associated with fasting glucose in the pediatric population. Although we did not find a clear association of CTRP1 with obesity in pediatric subjects, we found that CTRP1 was higher in obese youth with hyperglycemia relative to ONG, similar to the known associations with obesity in adults. Although most studies in adults, including our own (27), demonstrate associations between higher CTRP9 levels and obesity, prediabetes, and diabetes (25, 27, 59), we did not find an association of CTRP9 with obesity or hyperglycemia in this pediatric cohort. The elevated CTRP9 levels typically seen in adult obesity are thought to be due to a compensatory mechanism and possibly this has not yet occurred in the pediatric population. This would also explain the positive association of CTRP9 and adiponectin in this young cohort, in contrast to the inverse relationship seen in adults (25, 27, 54, 59).

Our study has several strengths. It is the first study, to our knowledge, to examine the novel adipokines CTRP1 and CTRP9 in the pediatric population. In addition, the longitudinal component of the study demonstrates the trajectory of adipokines in pediatric subjects, both lean and obese, over a 2-year time frame. The cross-sectional design limits the ability to infer causation, and the longitudinal analyses are limited by the modest sample size of the follow-up cohort and possible selection bias of follow-up participants. Of note, our cohort was predominantly African American youth, so the results may not be generalizable to other races. However, the study population is also unique in that this demographic is not typically represented in studies of adipokine biology in humans. Although not statistically significant, there were fewer females represented in the lean control group than the obese groups.

In summary, adipokine abnormalities are present in youth with obesity and diabetes and may represent a direct consequence or compensatory mechanism of the obese state. As we continue to follow the growing population of obese and diabetic youth into adulthood, we hope to gain a better understanding of the implications of this early adipose tissue dysfunction and inflammatory state on future metabolic function.

DATA AVAILABILITY

Some or all datasets generated during and/or analyzed during the current study are not publicly available but are available from the corresponding author on reasonable request.

GRANTS

This work was supported by the National Institutes of Health (NIH) National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) Grant DK084171 (to G.W.W). S.N.M was supported by the NIH/NIDDK Patient-Oriented Research Career Development Award K23 PA05143 and the Clinical and Translational Research Center of the National Center for Research Resources (UL1-RR-024134) to the Children’s Hospital of Philadelphia.

DISCLOSURES

No conflicts of interest, financial or otherwise, are declared by the authors.

AUTHOR CONTRIBUTIONS

R.M.W., G.W.W., and S.N.M. conceived and designed research; R.M.W., S.R., X.L., D.C.S., and G.W.W. performed experiments; R.M.W., A.E.J., S.R., X.L., D.C.S., A.T.S., G.W.W., and S.N.M. analyzed data; R.M.W., S.R., X.L., G.W.W., and S.N.M. interpreted results of experiments; R.M.W., A.E.J., and A.T.S. prepared figures; R.M.W., A.E.J., G.W.W., and S.N.M. drafted manuscript; R.M.W., A.E.J., S.R., X.L., D.C.S., A.T.S., G.W.W., and S.N.M. edited and revised manuscript; R.M.W., A.E.J., S.R., X.L., D.C.S., A.T.S., G.W.W., and S.N.M. approved final version of manuscript.