Different alterations of glomerular filtration rate and their association with uric acid in children and adolescents with type 1 diabetes or with overweight/obesity

Hyperfiltration (HF) occurs early in diabetes or obesity (OB)‐associated renal disease. Alterations of glomerular filtration rate (GFR) in childhood OB remain unclear.

In the development of CKD in children and adolescents with type 1 diabetes (T1D) and those without diabetes but with overweight (OW)/OB, an early stage of renal hyperfiltration (HF) is proposed. In children and adolescents with T1D, HF has been associated with increased risk of microalbuminuria and of a rapid decline in glomerular filtration rate (GFR), 4,5 a predominant clinical feature of diabetic nephropathy. 6 Nonetheless, a recent report from the DCCT/EDIC has underestimated the role of HF as a risk factor for CKD or macroalbuminuria in 446 adults with T1D followed during a median of 28 years. 7 Therefore, if HF has clinical relevance in children and adolescents with T1D remains yet to be determined. Unlike HF, increasing uric acid levels were associated with worse renal outcomes, cardiovascular events and mortality in adults with T1D. 8,9 However, adolescents with T1D showed reduced uric acid levels, underscoring its use as a risk factor in these patients. 10,11 Even though, increasing uric acid levels in pediatric T1D may still be associated with a rapid GFR decline, as an inverse correlation with GFR was shown. 10,11 On the other hand, a study showed that children and adolescents with OW/OB without diabetes featured HF at a similar proportion than those with T1D. 12 However, no other studies compared both pediatric populations. The comparison of GFR values between children with OW/OB vs normal-weight peers showed inconsistent results; thus, the impact of childhood OW/OB on renal function remains unclear. [12][13][14][15][16] While some authors reported associations between decreased GFR and increasing body mass index (BMI) and presence of cardiometabolic risk factors, others did the same with elevated GFR. [12][13][14][15][16] In an Italian retrospective study including 2957 children (aged: 3-18 years) with OB, z-BMI positively correlated with GFR. However, pubertal development, HOMA-IR, and duration of OB were all inversely correlated with GFR and the study concluded that longer duration of OB in children could impact negatively the GFR. 14 If similar alterations of the GFR are present or not in children and adolescents with T1D and with OW/OB without diabetes is relevant for establishing prevention strategies.
In regard to uric acid levels, an association with cardiometabolic risk factors in children and adolescents with OW/OB was clearly established. 15,17,18 However, its association with GFR alterations has not been analyzed in this age group. The TODAY study showed that higher uric acid levels were associated with increased risk of hypertension and microalbuminuria in youth with type 2 diabetes (T2D). 19 Thus, uric acid constitutes a candidate biomarker for screening youths with OB showing elevated risk of renal impairment. The importance of identifying such patients arises from the prolonged exposure to other comorbid CKD risk factors, apart from OB, like insulin resistance and dyslipidemia. This fact might contribute to explain why at similar ages children and adolescents with T2D presented a 2.5x higher risk of diabetic kidney disease and a 4x higher risk of renal failure than those with T1D. 20,21 Our hypothesis was that GFR alterations and its associations with uric acid levels in children with OW/OB would be similar to those observed in children with T1D. The aim of this study was to evaluate and to compare the prevalence of GFR alterations, and to analyze its association with uric acid in children and adolescents with T1D vs OW/OB. Secondary analysis included the effects of cardiometabolic risk factors over serum uric acid in OW/OB.

| Study design and sample size
This was a prospective, single-center, cross-sectional study. The expected prevalence of renal HF in the group of patients with OW/OB was 15% according to the literature. 12 The sample size to detect such prevalence with a 5% of accuracy and a 95% confidence was 196.
In order to calculate the number of patients with T1D in the study, an expected HF prevalence of 30% was set. 4,12 Next, we used a non-inferiority approach for the comparison of two proportions with a critical value (α) = .05, an 80% power and a non-inferiority margin (δ) of −0.10. The resulting number of patients with T1D to be included was 24. OpenEpi (Emory University, Atlanta, Georgia) and R (R Foundation, Vienna, Austria) were used for sample size calculations.

| Study population
Children and adolescents (aged: 5-17 years) with OW/OB and without diabetes who were referred for nutritional counseling to the T1D was diagnosed according to ISPAD guidelines. 22 Every child and adolescent with T1D (aged: 5-17 years) followed up in our center was invited to participate in the study. Out of 40 patients with T1D, 36 agreed to participate. Exclusion criteria were ACR >3.39 mg/mmol (n = 2), fasting c-peptide levels >0.2 mmol/L (n = 1), concomitant liver disease and use of any other medication different from insulin. One patient was excluded as it was born prematurely with an extremely low birth weight (900 g), as well as, three other patients who missed the protocol examinations. The final number of children and adolescents with T1D was 29.
All the patients studied in the protocol and their legal tutors or parents gave their written consent and assent to participate in the study. The Bioethics Committee of the Complejo Médico Churruca-Visca reviewed and approved the study protocol. All the procedures within the study followed the Ethical Principles stated in the Declaration of Helsinki.

| Clinical and biochemical assessment
Every patient did a clinical examination including weight, height, waist circumference, and blood pressure (BP). BMI was calculated and OW/OB classified according to the definitions of the World Health Organization (WHO). 23 WC was measured at the midpoint between the iliac crest and the last rib and elevated WC classified as >90th percentile according to the Bogalusa Heart Study. 24

| Statistical analysis
The Shapiro-Wilk test was used to evaluate the normal distribution of continuous variables. Comparisons were made by the Student t test or Mann-Whitney U test, according to data distribution. For the comparison of categorical variables, chi-square test was used. When comparing more than three categories, Benjamini-Hochberg correction for multiple comparisons was applied. Two-way analysis of variance (ANOVA) was used to evaluate differences between male and female patients with or without GFR alterations across the children with OW/OB. Variables with a skewed distribution were log-transformed before entering the analysis. Univariate correlations were assessed by Spearman Correlation test. Stepwise multiple linear regression was used to look for independent predictors of GFR and uric acid levels. Standardized residuals from linear regression tests were checked for normality to be confident of the model adequacy. SPSS 25.0 (IBM) was used for statistical analyses.
Statistically significant tests showed a significance value (P) < .05.  Table 1 shows the general characteristics of the children and adolescents with T1D and with OW/OB. The group of patients with T1D was older and predominantly pubertal in comparison with the patients with OW/OB. As expected, both groups differed in the z-BMI, waist circumference, glucose metabolism markers, and NEFA levels. Regarding lipid levels, T1D patients showed higher HDL-C levels ( Table 1). In addition, patients with T1D exhibited lower cystatin C and uric acid, as well as higher GFR and ACR than OW/OB. Creatinine concentration was similar between patients with T1D and OW/OB. A significant interaction on GFR values was observed between the groups and pubertal stage (F = 6.610; P = .011). The difference in GFR was larger among pubertal patients of the different groups (125 ± 23 vs 104 ± 17 mL/min.1.73 m 2 , for T1D and OW/OB groups, respectively). The prevalence of elevated BP and the concentration of hsCRP was similar between the groups.

| Alterations of the GFR in the studied population
The prevalence of HF in children and adolescents with T1D was significantly higher than in those with OW/OB (Figure 1). In the OW/OB group, a 10% of the subjects showed low GFR (Figure 1).

| Correlation of GFR with uric acid levels and cardiometabolic risk factors in OW/OB
In children and adolescents with OW/OB, the GFR alterations dif-  (Table S1). Differences between female and male prepubertal children were evident in cystatin C and ACR but not in creatinine or uric acid levels (Table S1). Among the pubertal patients, those with low GFR were preferentially male and showed higher LDL-C, non-HDL-C and uric acid than those with GFR between 90 and 135 mL/min.1.73 m 2 . Sex differences were observed in HDL-C, cystatin C, and GFR (Table S2). Table S3 shows the univariate correlations of GFR with metabolic variables in prepubertal and pubertal children by separate. The only variables that differently correlated with GFR according to the pubertal stage were ACR, NEFA, and plasma lipids. In prepubertal children, GFR directly correlated with ACR and inversely with NEFA levels (Table S3). In pubertal subjects, HDL-C positively correlated with GFR, while LDL-C did it inversely (Table S3).
A trend toward a lower GFR was evident as age, pubertal development, WC, LDL-C, uric acid, NEFA, and other cardiometabolic risk factors increased. Therefore, correlations were assessed in the whole group despite known physiological differences due to pubertal development (ie, higher HOMA-IR, lower LDL-C, etc.). As expected age, male sex and pubertal stage were negatively correlated with GFR (all P < .001). Furthermore, in age-and sex-adjusted correlations, uric acid and NEFA levels were significantly correlated with GFR (r = −.24, P = .003 and r = −.20, P = .014, respectively). To evaluate if these factors were independent predictors of GFR, a stepwise multivariate linear regression was done. This analysis showed that age, sex, and uric acid levels explained a 33% of GFR variability in the studied population of children and adolescents with OW/OB (Table 2). When age was not included in the model, pubertal stage took its place in the regression model without major deviations (data not shown).
As several cardiometabolic risk factors correlated with uric acid, we performed a regression analysis to evaluate the independent contributors to uric acid levels in OW/OB (Table 3). Elevated BP, age, z-  BMI, and NEFA levels were independent predictors of almost half of uric acid variability in a model adjusted by pubertal stage, insulin resistance, GFR, and plasma lipids.

| DISCUSSION
The present study shows that GFR values were lower in children and adolescents with OW/OB as they present higher age, uric acid levels and go through pubertal development. On the other hand, HF in children and adolescents with T1D was related to worse metabolic and BP control, as also pointed out by others. 4,5 Thus, refuting our hypothesis, the alterations of GFR were different between children and adolescents with T1D and with OW/OB without diabetes.
Although contrary to a previous study, 12  In this aspect, uric acid levels as a renal disease marker in children with OW/OB merit further studies. The role of uric acid as a risk biomarker for diabetic kidney disease has already been established in children and adolescents with T2D and adults with T1D. 8,19 However, in agreement with other study, 10 uric acid was not correlated with renal function or cardiometabolic risk factors in our group of children and The present was a cross-sectional study and it was not possible to confirm if the patients with OW/OB will show or not a rapid decline in GFR. The lack of data on OB duration limited the interpretation of our results, in particular among pubertal children. In addition, non-alcoholic fatty liver disease (NAFLD), which is prevalent in childhood OB (up to 34%; 30 ), was not part of the protocol examinations. A recent report showed that NAFLD was a significant predictor of low GFR among a series of 230 children and adolescents with OW/OB (46% showing NAFLD). 31 Longitudinal studies will clarify the relationship between NAFLD and impaired renal function in childhood OB.
The strengths of our study rely on the exclusion of patients with microalbuminuria and with any other inflammatory condition (based on clinical and biochemical parameters) that could have affected the biochemical variables studied. In addition, the use of a creatinine and cystatin C equation for the calculation of GFR is a clear strength in comparison to other studies only using creatinine concentration.
However, our classification was based only in one evaluation of the GFR and the reported frequencies of GFR alterations may be biased.
Nonetheless, the observed prevalence of HF in youths with T1D and of GFR alterations in OW/OB was similar to previous reports. 10,12 In the present study, the GFR reference range was previously verified in a group of 26 children and adolescents with normal weight. This point combined with the fact that subjects with HF and low GFR were found in the same study supports our evaluation of the GFR. However, the lack of metabolic data in normal weight subjects could suppose a limitation to our conclusions beyond those regarding GFR alterations. Finally, although some patients showed 2 years of diabetes duration, insulin deficiency was ascertained by a fasting C-peptide >0.2 nmol/L as an exclusion criterion.
In conclusion, GFR alterations were different between children and adolescents with T1D and with OW/OB. Higher uric acid, older age, and puberty were related to lower GFR values in OW/OB children. Whether these represent different physiopathological mechanisms or are the consequence of a more rapid impairment of renal function associated with longer exposure to cardiometabolic risk factors remains to be determined.