Subclinical inflammation in children with Down syndrome: implications for preventive care

Charu Sharma; Muhammad Jawad Hashim; Tarek El Azzabi; Sania Al Hamad; Ekhlass Mohammed; Javed Yasin; Yousef M. Abdulrazzaq; Elhadi Husein Aburawi

doi:10.6065/apem.2550148.074

Ann Pediatr Endocrinol Metab > Volume 31(2); 2026 > Article

Sharma, Hashim, Azzabi, Hamad, Mohammed, Yasin, Abdulrazzaq, and Aburawi: Subclinical inflammation in children with Down syndrome: implications for preventive care

Original Article

Annals of Pediatric Endocrinology & Metabolism 2026;31(2): 119-128.

Published online: April 30, 2026

DOI: https://doi.org/10.6065/apem.2550148.074

Subclinical inflammation in children with Down syndrome: implications for preventive care

Charu Sharma¹

, Muhammad Jawad Hashim²

, Tarek El Azzabi^3,⁴

, Sania Al Hamad⁵

, Ekhlass Mohammed⁵

, Javed Yasin⁶

, Yousef M. Abdulrazzaq⁵

, Elhadi Husein Aburawi⁵

¹Department of Genetics and Genomics, College of Medicine and Health Sciences, United Arab Emirates University, Al Ain, UAE

²Department of Family Medicine, College of Medicine and Health Sciences, United Arab Emirates University, Al Ain, UAE

³Department of Pediatrics, Al Ain Hospital, Al Ain, UAE

⁴Department of Pediatrics, Sheikh Khalifa Medical City Hospital, Al Ain, UAE

⁵Department of Pediatrics, College of Medicine and Health Sciences, United Arab Emirates University, Al Ain, UAE

⁶Department of Internal Medicine, College of Medicine and Health Sciences, United Arab Emirates University, Al Ain, UAE

Address for correspondence: Elhadi Husein Aburawi Department of Pediatrics, College of Medicine and Health Sciences, United Arab Emirates University, P. O. Box 15551, Al Ain, UAE Email: e.aburawi@uaeu.ac.ae

Received May 5, 2025 Revised November 5, 2025 Accepted December 3, 2025

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Purpose

Down syndrome (DS) is associated with metabolic dysregulation, obesity, and increased risk of chronic inflammation. This study aimed to assess subclinical inflammation in children with DS by evaluating inflammatory biomarkers, such as high-sensitivity C-reactive protein (hs-CRP), and their association with metabolic parameters including ghrelin, lipid profiles, and vitamin D levels.

Methods

A total of 49 children with DS (aged 1–18 years) and 22 age-matched healthy controls were enrolled. Anthropometric data, body fat percentage, and metabolic parameters were assessed. Inflammatory markers (hs-CRP, apolipoprotein-B [Apo B], adiponectin), metabolic hormones (ghrelin, insulin), and lipid profiles were determined from venous blood samples. Statistical analyses included bivariate correlation, analysis of variance, and multiple linear regression to identify predictors of inflammation.

Results

Children with DS exhibited significantly higher hs-CRP levels than controls (p=0.03), indicative of increased systemic inflammation. Higher hs-CRP levels were associated with older age (r=0.33, p=0.006), greater obesity (body mass index: r=0.32, p=0.011), and elevated serum insulin and low-density lipoprotein levels. Ghrelin levels correlated negatively with Apo B (r=-0.41, p<0.001) and positively with hs-CRP (r=0.30, p=0.012). Predictors of inflammation (based on hs-CRP) included older age, male sex, higher gamma-glutamyl transferase level, and a diagnosis of DS (adjusted R²=0.276).

Conclusions

Children with DS are prone to metabolic inflammation, with increasing age and obesity exacerbating inflammatory responses. Clinicians should monitor and manage weight, dyslipidemia, and inflammation in this population to prevent long-term complications such as cardiovascular diseases and insulin resistance.

Keywords: Down syndrome, Inflammation, High-sensitivity C-reactive protein, Ghrelin, Metabolic Dysfunction, Child, United Arab Emirates

Highlights

· Children with Down syndrome exhibit elevated levels of subclinical inflammation, which are further exacerbated by advancing age, increased adiposity, and metabolic dysregulation.

· This inflammatory state is associated with metabolic parameters, including insulin levels, lipid profiles, and appetite-regulating hormones such as ghrelin.

· Early clinical monitoring and weight management strategies may mitigate the risk of adverse long-term health outcomes.

Introduction

Down syndrome (DS) is one of the most prevalent chromosomal disorders globally, and in the United Arab Emirates (UAE) has an estimated incidence of 1 in 374 live births [1]. Individuals with DS are predisposed to a range of health complications, including metabolic disorders, obesity, and immune system dysregulation [2,3]. Individuals with DS have an increased body fat percentage (BF%) and altered metabolic regulation, contributing to elevated levels of proinflammatory cytokines [4].

Studies have reported that chronic low-grade systemic inflammation plays a significant role in exacerbating metabolic dysfunction. Elevated levels of high-sensitivity C-reactive protein (hs-CRP), a marker of systemic inflammation, are generally observed in individuals with DS, obesity, insulin resistance, and dyslipidemia [5]. Elevated hs-CRP level, even in the absence of overt infection, may be more reflective of metabolic rather than infectious inflammation [6,7]. Comparative analyses have shown a concurrent elevation of other inflammatory markers such as interleukin (IL)-6 and tumor necrosis factor (TNF)-α in individuals with elevated hs-CRP, reinforcing that hs-CRP is a reliable indicator of baseline subclinical inflammation in different conditions [8].

Among metabolic regulators, ghrelin, a hormone primarily secreted by the stomach, plays a crucial role in appetite regulation [9]. Its anti-inflammatory properties and regulatory effects on energy metabolism may serve potential mediating roles in DS-associated metabolic inflammation. However, the specific role of ghrelin in DS-related inflammation and metabolic dysfunction remains poorly understood. While one study reported comparable ghrelin levels in individuals with DS and their peers [10], another found reduced ghrelin levels in obese individuals [11].

In the UAE, DS-specific growth charts for weight, height, and head circumference have been developed. Regional data indicate that children with DS are significantly shorter and heavier than typically developing peers and show disproportionately high rates of overweight and obesity. This reinforces the need for tailored growth and health monitoring tools [12]. This cohort of patients exhibits excess adiposity, which drives subclinical systemic inflammation (increased hs-CRP); ghrelin, due to its metabolic and anti-inflammatory roles, may act as a potential mediator of this relationship. Studies from this region have also examined health outcomes in children and adolescents with DS-including physical status, feeding behaviors, and oral health [13].

Our aim in this study was to investigate interrelationships among hs-CRP, ghrelin, adiposity, and metabolic dysfunction among UAE children with DS. Our findings contribute to a more comprehensive understanding of the inflammatory and metabolic profile of DS patients within the UAE population.

Materials and methods

1. Study design and participants

This case-control study included 49 children with DS (aged 1–18 years) and 22 age-matched healthy controls recruited from a pediatric clinic.

2. Inclusion criteria

Children with DS confirmed by karyotype analysis were eligible for enrolment. Among them 47 cases exhibited nondisjunction, and 2 cases demonstrated Robertsonian translocations. No cases of mosaicism were identified. These patients underwent a comprehensive clinical review including vital-sign assessment. All patients were asymptomatic and afebrile, with no clinical evidence of acute infection or inflammation on the day of recruitment or immediately prior to blood sampling. Written informed consent was obtained from parents or legal guardians of all participants.

3. Exclusion criteria

Children with acute infection or inflammatory disease, as determined by clinical history and vital-sign evaluation, either on the day of enrolment or within the preceding 4 weeks, were excluded. Additionally, patients on immunosuppressive therapy and the presence of metabolic disorders unrelated to DS were excluded. Complete blood count and erythrocyte sedimentation rate values were not used as exclusion parameters in this study.

4. Data collection

The study was conducted between June 2019 and December 2023. Informed consent was obtained from the parents of all participants. Demographic data (age, sex, and medical history) and vital signs were recorded during blood sample collection. A trained research nurse conducted all anthropometric measurements, including weight, height, waist circumference, and hip circumference. Weight was recorded to the nearest 0.1 kg using a digital scale with the patient wearing light clothing (SECA scale, model 769 1321994). Height was measured to the nearest 0.1 cm in a standing position without shoes using the SECA scale, and body mass index (BMI) was calculated by dividing the weight in kilograms by the height in meters squared. Waist circumference was measured at the midpoint between the bottom of the rib cage and the tip of the iliac crest. Blood pressure (BP) and pulse were measured using a calibrated Welch Allyn automatic BP monitor (model: ProBP3400; USA), ensuring that the appropriate cuff size was used for each participant’s arm. BP was measured after at least 5 minutes of rest, and 3 consecutive readings were recorded at 5-minute intervals BF% was measured using a Tanita Body Composition Analyzer TBF-300 (Tanita Corp., Japan), which uses electrical impedance to estimate body fat composition.

5. Inflammatory biomarkers

The Roche Cobra Integra 400 Plus chemical analyzer (Roche, Germany) was used to measure complete lipid profile (total cholesterol, high-density lipoprotein cholesterol [HDL-C], low-density lipoprotein cholesterol [LDL-C], triglycerides [TG], apolipoprotein A [Apo A], apolipoprotein B [Apo B]), fasting glucose, alanine transaminase (ALT), aspartate transaminase (AST), uric acid, and gamma-glutamyl transferase (GGT) levels. Adiponectin (R&D Systems, USA; Catalog No. DRP300), leptin (R&D Systems; Catalog No. DLP00), and ghrelin (MyBioSource; Catalog No. MBS761535) levels were determined using enzyme-linked immunosorbent assay kits following the manufacturers’ protocols. Plasma concentrations of hs-CRP and vitamin D were quantified using Roche’s Cobas e411 analyzer.

6. Statistical analysis

Data were analyzed using IBM SPSS Statistics ver. 31.0 (IBM Co., USA). After initial descriptive review, bivariate statistical associations were determined using correlation coefficients. Additional analyses included 1-way analysis of variance and multiple linear regression.

7. Ethical considerations

Ethical approval was obtained from the AAMD.HREC (Al Ain Medical District Human Research Ethics Committee) (Reference: DT/fa/09-69). The study was conducted in accordance with the Declaration of Helsinki following institutional ethical committee review. The study adhered to ethical guidelines to ensure the confidentiality and well-being of all participants.

Results

1. Anthropometric and metabolic profiles

Children with DS weighed significantly more (P=0.003) and were shorter (P<0.001) than controls (Table 1), but BMI differences were not significant. BF% was higher in DS children (P=0.096). Children with DS had lower weight-for-age percentiles and lower weight-for-age z-scores but higher BMI percentiles than controls. Other variables, such as consanguinity and sex, showed minor differences that were not statistically significant between the DS and normal control groups. Those with DS were not more likely to have consanguineous parents than healthy controls (odds ratio [OR], 1.2; 95% confidence interval [CI], 0.31–4.2). Children with DS were more likely to have subclinical inflammation (elevated hs-CRP) than healthy controls (OR, 6.6; 95% CI, 1.7– 25.3). As expected, mothers of children with DS were older at the time of pregnancy: mean age 34.5 (±standard deviation [SD] 6.5) years versus 22.8 (±SD 5.1) years for mothers of healthy children (P<0.001; Cohen d=5.9). Comparison of family history between children with DS and healthy controls did not show higher rates of obesity, dyslipidemia, diabetes, or hypertension among parents of cases than parents of controls (Table 1).

2. Analyses within the DS group

Further analysis within the DS group (n=49) revealed a near-equal distribution of male (n=25) and female (n=24) participants. Mean age of males (9.6 years) and females (7.2 years) was similar (P=0.092). There was a significant difference in weight between males and females (P= 0.045). Additionally, BMI was positively correlated with age (r=0.64, P<0.001). Fig. 1 shows obesity levels in children with DS. The marginal difference in fat-free mass (FFM) (P=0.056) and muscle mass (P=0.058) between the genders was not statistically significant. Other variables such as consanguinity and parental medical history showed differences, but these differences did not reach statistical significance (Table 2).

3. Inflammatory markers

hs-CRP levels were significantly higher in DS children than controls (P=0.030). Apolipoprotein B (Apo B) levels were also significantly higher in DS children (P<0.001), whereas adiponectin levels were significantly lower (P= 0.004). Ghrelin levels were significantly correlated positively with hs-CRP (r=0.30, P=0.012) but significantly negatively correlated with Apo B (r=-0.41, P<0.001) (Table 3). All biochemical assays performed were within the limits of variation (<7.8% for both inter- and intra-assay variability). Fig. 2 shows the effect of increased levels of inflammatory biomarkers and obesity with increasing age in children with DS (N=49). Fig. 3 shows the effect of weight, ghrelin and insulin levels in cases with high hs-CRP levels among 49 children with DS. Fig. 4 shows adjusted means of different biomarkers; these means were adjusted for differences in age, sex, and weight-forage centiles in the 2 groups.

4. Metabolic dysregulation

LDL and triglyceride levels were significantly higher in DS children than controls (P<0.001). Insulin resistance markers were significantly correlated with inflammation (insulin-hs-CRP: r=0.35, P=0.008). Vitamin D levels were significantly lower in children with DS and declined with age (r=-0.356, P=0.003) (Table 3). The metabolic biomarkers in children with DS with increased inflammation as determined by an elevated CRP level is tabulated in Table 4.

5. Regression analysis

A multivariate analysis was conducted to identify predictors of subclinical inflammation as measured via hs-CRP. Since the measured values of hs-CRP had a skewed, nonnormal distribution, a natural log transformation was performed prior to analysis.

Predictors of inflammation (hs-CRP-transformed) in DS included a diagnosis of DS (P=0.028) and elevated GGT level (P=0.025) (multiple linear regression; adjusted R²=0.276; normality test using the Shapiro-Wilk test, P=0.20). Multicollinearity was low (variance inflation factor values: Downs diagnosis, 1.15; GGT, 1.18; age, 1.19; sex, 1.1). Age and gender were included as covariates in the model (higher hs-CRP values were seen in older children and in boys). Ghrelin, leptin, adiponectin and insulin were not significant predictors in this study.

Discussion

This study corroborates existing evidence that children with DS exhibit increased inflammatory responses, particularly in those with elevated BMI, older age, and signs of metabolic dysregulation. A comparative analysis involving 95 adolescents with DS and 113 typically developing controls revealed that the DS group had significantly higher BMI, waist-to-height ratio, waist circumference, and BF%. Additionally, children with DS displayed elevated inflammatory biomarkers, including complement factors C3 and C4, as well as total serum proteins [14]. Interestingly, this study found no significant differences in inflammatory markers based on gender; however, FFM and muscle mass showed significant differences between sexes, suggesting potential gender-related differences in body composition that merit further exploration. The present study identified early dyslipidemia in children with DS, a significant risk factor for cardiovascular disease. These findings are consistent with a case-control study involving 69 children (31 with DS and 38 controls), which revealed a distinct lipid profile in the DS group characterized by elevated triglyceride levels and HDL-C, alongside reduced LDL-C levels [15]. In a larger cross-sectional study of 386 children with DS aged 2–18 years, the most prevalent lipid abnormalities included low HDL-C (45.9%) and hypertriglyceridemia (26.2%). Notably, significant associations were observed between dyslipidemia, general obesity, and central adiposity [16], highlighting the critical need for early and regular lipid screening in children with DS to mitigate long-term cardiovascular risks.

The key predictors of systemic inflammation identified in this study were age, ghrelin levels, and BF%. Age was independently linked to increased hs-CRP levels in a previous study involving adult women [17]. Furthermore, evidence from pediatric cohorts suggests a temporal relationship between obesity and inflammation, with higher body fat percentiles correlating with elevated hs-CRP levels—an association that poses significant implications for chronic disease risk in later life [10]. The positive correlation between hs-CRP and obesity supports a proinflammatory state exacerbated by increased adiposity, as noted in previous literature [17].

Ghrelin appears to be involved in complex inflammatory processes through a compensatory physiological response, potentially linked to altered metabolic pathways [18]. This has been observed in inflammatory bowel diseases such as Crohn disease and ulcerative colitis [19,20]. A study among obese youth showed a negative correlation between fasting plasma ghrelin and insulin resistance, implying that elevated insulin may suppress ghrelin secretion [21]. Another study reported lower fasting ghrelin levels in obese children than normal weight children, indicating its regulatory role in energy balance [22]. However, despite the anticipated inverse relationship, we found a positive correlation between ghrelin and hs-CRP levels in this study. Despite limited studies on ghrelin in children with DS, this population is characterized by increased rates of obesity and chronic inflammation.

Inflammatory markers such as TNF-α and IL-6, which are elevated in obesity, may interfere with the regulation of appetite-related hormones like ghrelin. However, in the present study, we did not measure TNF-α and IL-6, but focused on other inflammatory markers such as ghrelin, hs-CRP, Apo B, insulin and insulin resistance, which were significantly different between the DS and control groups. Uric acid levels were significantly higher in the group with elevated hs-CRP levels than the normal hs-CRP-level group.

Additionally, we noted significant differences in Apo B levels between the DS and control groups. Elevated Apo B levels in individuals with DS further emphasize the increased risk of cardiovascular disease in this population [16], reinforcing the necessity for careful cardiovascular risk assessment. The findings of this study also suggest that DS may represent a state of early-onset insulin resistance, as evidenced by elevated serum insulin levels. This aligns with previous research indicating that obese children with DS have higher insulin levels and exhibit early markers of insulin resistance compared to their typically developing peers [23].

As a secondary finding, vitamin D did not differ between DS and controls overall (P=0.888), but within the DS group, those with an elevated CRP level (hs-CRP > 1 mg/L) had lower vitamin D levels than their peers with normal CRP levels (P=0.033). This pattern supports monitoring and optimizing vitamin D status in patients with DS, while keeping the primary emphasis on the ghrelin–inflammation axis.

An inverse correlation between serum vitamin D and hs-CRP levels was reported in an earlier study, highlighting its role in modulating inflammatory pathways in newborns [24]. These findings support early vitamin D supplementation as a preventive measure to reduce inflammation in this high-risk population.

In conclusion, this study demonstrated that children with DS have increased systemic inflammation influenced by age, obesity, and metabolic irregularities. Thus, routine assessment of inflammatory markers, lipid profiles, and vitamin D levels is essential in this population. Additionally, ghrelin was identified as a potential mediator of metabolic inflammation in DS, with its correlation to hs-CRP suggesting a compensatory role in the inflammatory state. Emphases on early screening and intervention strategies to address dyslipidemia, insulin resistance, and vitamin D deficiency should be mandatory. Further research is needed to understand the complex interplay between obesity, inflammation, and metabolic dysregulation in this vulnerable population.

The primary limitations of this study are its relatively small sample size, which may affect the generalizability of the findings, and the absence of longitudinal data to assess long-term health outcomes. The control group included a substantial number of overweight and obese children due to the high prevalence of childhood obesity in the region. While results of a subset analysis (after excluding overweight and obese children in the control group) were reported, matching or weighting techniques were not used to compare the 2 groups. Fasting sampling was not possible as parents with DS did not provide consent for this. Additionally, some patients in the DS group had elevated hs-CRP levels without any clinical explanation.

Notes

Conflicts of interest

No potential conflict of interest relevant to this article was reported.

Funding

This study was funded by United Arab Emirates University.

Data availability

The data that support the findings of this study can be provided by the corresponding author upon reasonable request.

Acknowledgments

We gratefully to the support provided by UAE University and extend our sincere thanks to all the participants who contributed to this study.

Author contribution

Conceptualization: EHA; Data curation: CS, TEA, SAH, EM, JY, YMA; Formal analysis: CS, MJH, SAH, EM, JY, YMA; Funding acquisition: EHA; Methodology: CS, MJH, TEA, SAH, EM, YMA, EHA; Project administration: MJH, EHA; Visualization: EHA; Writing - original draft: CS; Writing - review & editing: CS, MJH, TEA, SAH, EM, JY, YMA, EHA

Fig. 1.

Obesity in children with Down syndrome. CDC, Centers for Disease Control and Prevention; IOTF, International Obesity Task Force; WHO, World Health Organization.

Fig. 2.

Increase in levels of inflammatory biomarkers and obesity with increasing age in children with Down syndrome (N=49). (A) C-reactive protein (high-sensitivity CRP). (B) Weight percentile. (C) Low-density lipoprotein (LDL) cholesterol. (D) Insulin. (E) Gamma-glutamyl transferase (GGT). (F) Vitamin D.

Fig. 3.

Greater weight, ghrelin, and insulin levels in cases with high hs-CRP levels among 49 children with DS. (A) Weight percentile. (B) Ghrelin. (C) Insulin. Children with DS were divided into 2 groups: an inflamed group (hs-CRP levels > 1.0 mg/L; n=24) and a not-inflamed group (hs-CRP levels<1.0 mg/L; n=23). hs-CRP, high-sensitivity C-reactive protein; DS, Down syndrome.

Fig. 4.

Adjusted comparison of inflammatory biomarkers between children with Down syndrome and healthy controls. The graph shows adjusted means (estimated marginal means) obtained using a univariate general linear model with age, sex, and weight-for-age centile as covariates. *Ghrelin values were divided by 100 to be able to show them on the same scale. Adiponectin levels were inversely correlated with inflammation: lower values indicate greater inflammation. hs-CRP, high-sensitivity C-reactive protein; GGT, gamma-glutamyl transferase; LDL, low-density lipoprotein.

Table 1.

Clinical characteristics of children with Down syndrome compared to healthy controls

Characteristic	Down syndrome (N=49)	Control group (N=22)	All cases (N=71)	P-value
Age (yr)	8.4±4.9	10.8±3.8	9.1±4.7	0.048
Weight (kg)	30.4±16.7	46.6±25.7	36.0±21.5	0.003
Height (cm)	121.2±24.4	148.1±23.5	130.4±27.2	<0.001
BMI (kg/m²)	18.9±4.1	19.7±6.1	19.2±4.8	0.506
BMI (percentile)	63.7±31.1	55.6±35.7	61.2±32.5	0.332
Weight-for-age (percentile)	41.6±31.4	62.4±31.6	48.4±32.7	0.013
Weight-for-age (z-score)	-0.41±1.3	0.64±1.3	-0.07±1.4	0.003
Body fat (kg)	7.1±7.8	12.2±11.8	9.7±10.2	0.104
Body fat (%)	16.8±9.8	22.0±10.6	19.4±10.4	0.096
Fat-free mass (kg)	31.6±14.5	34.5±15.8	33.0±15.1	0.526
Muscle mass (kg)	29.9±13.8	32.7±15.0	31.3±14.3	0.519
Male sex	25 (51.0)	10 (45.5)	35 (49.3)	0.664
Parental consanguinity	9 (18.4)	4 (18.2)	13 (18.3)	0.827
Father’s medical history
Hypertension	9 (20.5)	0 (0)	9 (13.6)	0.022
Dyslipidemia	4 (9.1)	0 (0)	4 (6.1)	0.145
Diabetes	10 (22.7)	5 (22.7)	15 (22.7)	1.000
Obesity	3 (6.8)	8 (36.4)	11 (16.7)	0.002
Mother’s medical history
Hypertension	3 (6.8)	0 (0)	3 (4.5)	0.210
Dyslipidemia	2 (4.5)	0 (0)	2 (3.0)	0.310
Diabetes	3 (7.1)	2 (9.1)	5 (7.8)	0.783
Obesity	6 (14.3)	10 (45.5)	16 (25.0)	0.006

Table 2.

Comparison of male and female children with Down syndrome (n=49).

Characteristic	Male (N=25)	Female (N=24)	All cases (N=49)	P-value
Age (yr)	9.6±5.2	7.2±4.3	8.4±4.9	0.092
Weight (kg)	35.0±19.6	24.7±10.1	30.4±16.7	0.045
Height (cm)	126.7±24.8	114.7±22.9	121.2±24.4	0.115
BMI (kg/m²)	19.7±5.1	17.8±2.2	18.9±4.1	0.129
BMI (percentile)	68.6±28.2	64.8±27.5	60.5±32.5	0.650
Weight-for-age (percentile)	53.7±36.4	42.7±27.7	48.4±32.7	0.170
Weight-for-age (z-score)	0.10±1.6	-0.25±1.1	-0.07±1.4	0.298
Body fat (kg)	8.2±9.5	5.2±3.5	7.1±7.8	0.396
Body fat (%)	16.9±10.9	16.5±8.7	16.8±9.8	0.933
Fat-free mass (kg)	36.4±16.7	24.5±6.3	31.6±14.5	0.056
Muscle mass (kg)	34.5±15.9	23.2±6.0	29.9±13.8	0.058
Parental consanguinity	4 (16.7)	5 (25.0)	9 (20.5)	0.466
Father’s medical history
Hypertension	6 (25.0)	3 (15.0)	9 (20.5)	0.670
Dyslipidemia	3 (12.5)	1 (5.0)	4 (9.1)	0.389
Diabetes	4 (16.7)	6 (30.0)	10 (22.7)	0.293
Obesity	2 (8.3)	1 (5.0)	3 (6.8)	0.662
Mother’s medical history
Hypertension	2 (8.3)	1 (5.0)	3 (6.8)	0.662
Dyslipidemia	1 (4.2)	1 (5.0)	2 (4.5)	0.895
Diabetes	2 (9.1)	1 (5.0)	3 (7.1)	0.607
Obesity	5 (22.7)	1 (5.0)	6 (14.3)	0.101

Values are presented as mean±standard deviation or number (%).

BMI, body mass index.

P-values are for comparisons between male and female children using 1-way analysis of variance for continuous variables and the chi-square test for discrete variables.

Table 3.

Metabolic biomarkers in children with Down syndrome (DS) and controls

Biomarkers	Down syndrome (N=49)	Control group (N=22)	All cases (N=71)	P-value	Cohen d (95% CI)
Glucose (mmol/L)	4.9±0.8	5.6±1.0	5.1±.9	0.005	-0.81 (-1.33 to -0.29)
Vitamin D (ng/ml)	24.6±11.3	25.0±6.5	24.7±9.9	0.888	-0.04 (-0.54 to 0.46)
Liver
ALT (U/L)	4.8±1.8	6.6±2.9	5.4±2.3	0.002	-0.82 (-1.34 to -0.30)
AST (U/L)	10.8±4.7	26.2±9.7	15.7±9.8	< 0.001	-2.31 (-2.95 to -1.69)
GGT (U/L)	16.5±5.8	14.3±3.3	15.8±5.2	0.113	0.43 (-0.08 to 0.94)
Lipids
TC (mg/dL)	4.0±0.8	1.3±1.8	3.1±1.7	< 0.001	2.26 (1.63 to 2.88)
LDL (mg/dL)	2.5±0.8	1.2±0.3	2.1±0.9	< 0.001	1.89 (1.30 to 2.48)
HDL (mg/dL)	1.0±0.4	4.1±0.8	2.0±1.6	< 0.001	-5.61 (-6.66 to -4.56)
TG (mg/dL)	1.1±0.5	2.5±0.8	1.6±0.9	< 0.001	-2.31 (-2.94 to -1.68)
Inflammatory biomarkers
Ghrelin (pg/mL)	489.8±134.1	356.0±80.6	447.1±134.6	< 0.001	1.11 (0.57 to 1.65)
hs-CRP (mg/L)	2.3±3.2	0.8±0.2	1.8±2.7	0.030	0.57 (0.05 to 1.07)
Apo A (g/L)	1.6±0.4	1.6±0.8	1.6±0.5	0.882	0.00 (-0.50 to 0.50)
Apo B (g/L)	0.9±0.2	1.5±0.2	1.1±0.4	< 0.001	-3.00 (-3.70 to -2.30)
Adiponectin (µg/mL)	14.8±4.8	19.5±8.1	16.3±6.3	0.004	-0.78 (-1.30 to -0.26)
Leptin (ng/mL)	14.1±11.9	20.8±15.8	16.2±13.5	0.053	-0.51 (-1.02 to 0.00)
Insulin (µIU/mL)	11.2±7.5	26.3±20.9	16.0±15.0	< 0.001	-1.14 (-1.69 to -0.61)
Uric acid (µmol/L)	271.2±96.1	238.4±98.9	260.72±97.1	0.194	0.34 (-0.17 to 0.84)
Insulin resistance	2.42±1.6	6.53±5.1	3.73±3.67	<0.001	-1.32 (-1.87 to -0.77)

Values are presented as mean±standard deviation.

CI, confidence interval; ALT, alanine transaminase; AST, aspartate transaminase; GGT, gamma-glutamyl transferase; TC, total cholesterol; LDL, low-density lipoprotein; HDL, highdensity lipoprotein; TG, triglycerides; hs-CRP, high-sensitivity C-reactive protein; Apo A, apolipoprotein-A; Apo B, apolipoprotein-B.

P-values are for comparisons between DS and health control children using 1-way analysis of variance.

Table 4.

Metabolic biomarkers in children with Down syndrome (DS) with increased inflammation as determined by an elevated CRP level

Biomarker	Inflamed (hs-CRP > 1 mg/L) (N=24)	Normal (hs-CRP<1 mg/L) (N=23)	All subjects (N=47)	P-value
Age (yr)	10.5±4.3	5.9±4.2	8.3±4.8	<0.001
Weight percentile (%)	76.8±20.7	53.5±29.4	65.9±27.5	0.003
Glucose (mmol/L)	4.9±0.9	4.9±0.8	4.9±0.8	0.921
Vitamin D (ng/mL)	21.2±6.9	28.2±13.8	24.6±11.3	0.033
Liver
ALT (U/L)	5.1±2.0	4.5±1.5	4.8±1.8	0.285
AST (U/L)	11.4±4.9	10.2±4.4	10.8±4.7	0.392
GGT (U/L)	18.6±6.4	14.3±4.3	16.5±5.8	0.009
Lipids
TC (mg/dL)	3.9±0.7	4.0±0.9	4.0±0.8	0.942
LDL (mg/dL)	2.4±0.7	2.5±0.8	2.5±0.8	0.829
HDL (mg/dL)	0.9±0.4	1.0±0.5	1.0±.4	0.426
TG (mg/dL)	1.1±0.4	1.1±0.5	1.1±.5	0.889
Inflammatory biomarkers
Ghrelin (pg/mL)	490.8±119.9	488.8±150.3	489.8±134.1	0.959
hs-CRP (mg/L)	4.0±3.8	0.5±0.2	2.3±3.2	<0.001
Apo A (g/L)	1.5±0.3	1.6±0.4	1.6±0.4	0.467
Apo B (g/L)	0.9±0.2	0.9±0.2	0.9±0.2	0.566
Adiponectin (µg/mL)	14.5±5.4	15.2±4.1	14.8±4.8	0.647
Leptin (ng/mL)	17.4±15.4	10.7±4.9	14.1±11.9	0.052
Insulin (µIU/mL)	12.8±8.0	9.6±6.8	11.2±7.5	0.148
Uric acid	320.9±99.2	219.3±59.5	271.2±96.1	<0.001
Insulin resistance	2.7±1.7	2.1±1.4	2.4±1.6	0.172

Values are presented as mean±standard deviation.

CRP, C-reactive protein; hs-CRP, high-sensitivity CRP; ALT, alanine transaminase; AST, aspartate transaminase; GGT, gamma-glutamyl transferase; TC, total cholesterol; LDL, lowdensity lipoprotein; HDL, high-density lipoprotein; TG, triglycerides; Apo A, apolipoprotein-A; Apo B, apolipoprotein-B.

P-values are for comparisons between DS and health control children using 1-way analysis of variance.

References

1. Murthy SK, Malhotra AK, Mani S, Shara ME, Al-Rowaished EE, Naveed S, et al. Incidence of Down syndrome in Dubai, UAE. Med Princ Pract 2007;16:25-8.

2. Pellegrini FP, Marinoni M, Frangione V, Tedeschi A, Gandini V, Ciglia F, et al. Down syndrome, autoimmunity and T regulatory cells. Clin Exp Immunol 2012;169:238-43.

3. Ordoñez FJ, Fornieles-Gonzalez G, Camacho A, Rosety MA, Rosety I, Diaz AJ, et al. Anti-inflammatory effect of exercise, via reduced leptin levels, in obese women with Down syndrome. Int J Sport Nutr Exerc Metab 2013;23:239-44.

4. Gutierrez-Hervas A, Gómez-Martínez S, Izquierdo-Gómez R, Veiga OL, Perez-Bey A, Castro-Piñero J, et al. Inflammation and fatness in adolescents with and without Down syndrome: UP & DOWN study. J Intellect Disabil Res 2020;64:170-9.

5. Huggard D, Kelly L, Ryan E, McGrane F, Lagan N, Roche E, et al. Increased systemic inflammation in children with Down syndrome. Cytokine 2020;127:154938.

6. Cardoso-Saldaña G, Juárez-Rojas JG, Zamora-González J, Raygoza-Pérez M, Martinez-Alvarado R, Posadas-Sánchez R, et al. C-reactive protein levels and their relationship with metabolic syndrome and insulin resistance in Mexican adolescents. J Pediatr Endocrinol Metab 2007;20:797-805.

7. Kotani K, Sakane N. C-reactive protein and reactive oxygen metabolites in subjects with metabolic syndrome. J Int Med Res 2012;40:1074-81.

8. Manti S, Cutrupi MC, Cuppari C, Ferro E, Dipasquale V, Di Rosa G, et al. Inflammatory biomarkers and intellectual disability in patients with Down syndrome. J Intellect Disabil Res 2018;62:382-90.

9. Fructuoso M, Rachdi L, Philippe E, Denis RG, Magnan C, Le Stunff H, et al. Increased levels of inflammatory plasma markers and obesity risk in a mouse model of Down syndrome. Free Radic Biol Med 2018;114:122-30.

10. Magge SN, O'Neill KL, Shults J, Stallings VA, Stettler N. Leptin levels among prepubertal children with Down syndrome compared with their siblings. J Pediatr 2008;152:321-6.

11. Buss J, Havel PJ, Epel E, Lin J, Blackburn E, Daubenmier J. Associations of ghrelin with eating behaviors, stress, metabolic factors, and telomere length among overweight and obese women: preliminary evidence of attenuated ghrelin effects in obesity? Appetite 2014;76:84-94.

12. Aburawi EH, Nagelkerke N, Deeb A, Abdulla S, Abdulrazzaq YM. National growth charts for United Arab Emirates children with Down syndrome from birth to 15 years of age. J Epidemiol 2015;25:20-9.

13. Osaili TM, Attlee A, Naveed H, Maklai H, Mahmoud M, Hamadeh N, et al. Physical status and parent-child feeding behaviours in children and adolescents with Down syndrome in the United Arab Emirates. Int J Environ Res Public Health 2019;16:2264.

14. Kusters MA, Manders NC, de Jong BA, van Hout RW, Rijkers GT, de Vries E. Functionality of the pneumococcal antibody response in Down syndrome subjects. Vaccine 2013;31:6261-5.

15. Orimadegun BE, Akinnusi OF, Ashubu OF, Salaudeen IA. Comparative analysis of plasma lipids and apolipoproteins in children with Down syndrome and implications for cardiovascular risk. Arch Basic Appl Med 2024;12:96-101.

16. Garcia-de la Puente S, Flores-Arizmendi KA, Delgado-Montemayor MJ, Vargas-Robledo TT. Lipid profile of Mexican children with Down syndrome. BMC Pediatr 2021;21:77.

17. Singer K, Eng DS, Lumeng CN, Gebremariam A, M Lee J. The relationship between body fat mass percentiles and inflammation in children. Obesity (Silver Spring) 2014;22:1332-6.

18. Arslan N, Erdur B, Aydin A. Hormones and cytokines in childhood obesity. Indian Pediatr 2010;47:829-39.

19. Ma Y, Zhang H, Guo W, Yu L. Potential role of ghrelin in the regulation of inflammation. FASEB J 2022;36:e22508.

20. Ates Y, Degertekin B, Erdil A, Yaman H, Dagalp K. Serum ghrelin levels in inflammatory bowel disease with relation to disease activity and nutritional status. Dig Dis Sci 2008;53:2215-21.

21. Ikezaki A, Hosoda H, Ito K, Iwama S, Miura N, Matsuoka H, et al. Fasting plasma ghrelin levels are negatively correlated with insulin resistance and PAI-1, but not with leptin, in obese children and adolescents. Diabetes 2002;51:3408-11.

22. Zou CC, Liang L, Wang CL, Fu JF, Zhao ZY. The change in ghrelin and obestatin levels in obese children after weight reduction. Acta Paediatr 2009;98:159-65.

23. Yahia S, El-Farahaty RM, El-Hawary AK, El-Hussiny MA, Abdel-Maseih H, El-Dahtory F, et al. Leptin, insulin and thyroid hormones in a cohort of Egyptian obese Down syndrome children: a comparative study. BMC Endocr Disord 2012;12:22.

24. Tao RX, Zhou QF, Xu ZW, Hao JH, Huang K, Mou Z, et al. Inverse Correlation between Vitamin D and C-Reactive Protein in Newborns. Nutrients 2015;7:9218-28.