EVALUATION OF METABOLIC PROFILE IN CHILDREN WITH ATOPIC DERMATITIS

Background: Atopic dermatitis (AD) is a chronic inflammatory skin disease caused by the interaction between genetic predisposition and environmental factors. It is diagnosed based solely on clinical findings due to the lack of a specific biomarker. This study aimed to identify metabolic pathway alterations in children with AD and to examine their association with clinical findings. Methods: Serum samples were collected from 21 children (0–1 years old) diagnosed with AD and 10 age- and sex-matched healthy controls. Metabolomic analysis was conducted via IVDr-nuclear magnetic resonance (NMR) spectroscopy. Furthermore, correlation analyses were conducted between serum metabolite levels and clinical parameters, including SCORAD index, allergic status, and demographic characteristics. Results: The metabolic analysis revealed that the AD group demonstrated high serum metabolite levels in the very low density lipoprotein (VLDL) subfractions, including cholesterol ( p = 0.025), free cholesterol ( p = 0.031), phospholipids ( p = 0.003), and triglycerides ( p = 0.008). Contrarily, within the high density lipoprotein (HDL) fraction, the cholesterol ( p = 0.002), free cholesterol ( p = 0.008), phospholipid ( p = 0.005), and apoprotein ( p = 0.008) levels decreased. Meanwhile, the total particle count of intermediate density lipoprotein (IDL) ( p = 0.031) and IDL-ApoB concentration ( p = 0.023) increased. Among the low density lipoprotein (LDL) subfractions, the triglyceride levels were high in LDL1 ( p = 0.004) but low in LDL3 ( p = 0.031). The glutamine levels were also significantly higher ( p = 0.002), whereas the phenylalanine ( p = 0.039) and choline ( p < 0.001) levels were low. The serum metabolite levels were significantly correlated with the clinical and demographic characteristics of the disease, including SCORAD score ( p < 0,005) and allergic status ( p = 0.041). Conclusion: The results indicate that AD extends beyond cutaneous involvement and is associated with systemic metabolic alterations. Differences in metabolite levels and their correlation with clinical parameters provide deeper insights into the systemic impact of the disease. These results highlight the need for further exploration of AD pathogenesis and suggest a potential role for metabolic biomarkers in disease diagnosis and management. EVALUATION OF METABOLIC PROFILE IN CHILDREN WITH ATOPIC DERMATITIS Eda Erdem¹Ahmet Tarık Baykal² ³ Mustafa Serteser² ³ Burçin Beken⁴ Gülbin Bingöl⁴ ¹ Department of Pediatrics, School of Medicine, Acibadem Mehmet Ali Aydinlar University, Istanbul, Turkey ² Department of Medical Biochemistry, School of Medicine, Acibadem Mehmet Ali Aydinlar University, Istanbul, Turkey. ³Acibadem Labmed Clinical Laboratories, Istanbul, Turkey. ⁴Division of Pediatric Allergy and Immunology, Department of Pediatrics, Acibadem Mehmet Ali Aydinlar University School of Medicine, Istanbul, Turkey. Short title: Metabolic Profile in Pediatric Atopic Dermatitis Word count: 2857 ; Number of tables: 1; Number of figures: 5 Conflicts of Interest: The authors declare no conflicts of interest. Correspondence Eda Erdem, Department of Pediatrics, School of Medicine, Acibadem Mehmet Ali Aydinlar University, Istanbul, Turkey, [email protected], +905555853681

Background: Atopic dermatitis (AD) is a chronic inflammatory skin disease caused by the interaction between genetic predisposition and environmental factors. It is diagnosed based solely on clinical findings due to the lack of a specific biomarker. This study aimed to identify metabolic pathway alterations in children with AD and to examine their association with clinical findings.

Serum samples were collected from 21 children (0–1 years old) diagnosed with AD and 10 age- and sex-matched healthy controls. Metabolomic analysis was conducted via IVDr-nuclear magnetic resonance (NMR) spectroscopy. Furthermore, correlation analyses were conducted between serum metabolite levels and clinical parameters, including SCORAD index, allergic status, and demographic characteristics.

The metabolic analysis revealed that the AD group demonstrated high serum metabolite levels in the very low density lipoprotein (VLDL) subfractions, including cholesterol ( p = 0.025), free cholesterol ( p = 0.031), phospholipids ( p = 0.003), and triglycerides ( p = 0.008). Contrarily, within the high density lipoprotein (HDL) fraction, the cholesterol ( p = 0.002), free cholesterol ( p = 0.008), phospholipid ( p = 0.005), and apoprotein ( p = 0.008) levels decreased. Meanwhile, the total particle count of intermediate density lipoprotein (IDL) ( p = 0.031) and IDL-ApoB concentration ( p = 0.023) increased. Among the low density lipoprotein (LDL) subfractions, the triglyceride levels were high in LDL1 ( p = 0.004) but low in LDL3 ( p = 0.031). The glutamine levels were also significantly higher ( p = 0.002), whereas the phenylalanine ( p = 0.039) and choline ( p < 0.001) levels were low. The serum metabolite levels were significantly correlated with the clinical and demographic characteristics of the disease, including SCORAD score ( p < 0,005) and allergic status ( p = 0.041).

The results indicate that AD extends beyond cutaneous involvement and is associated with systemic metabolic alterations. Differences in metabolite levels and their correlation with clinical parameters provide deeper insights into the systemic impact of the disease. These results highlight the need for further exploration of AD pathogenesis and suggest a potential role for metabolic biomarkers in disease diagnosis and management.

Atopic dermatitis, infancy, pediatrics, metabolomics, nuclear magnetic resonance Key Message This study highlights that children with atopic dermatitis show significant alterations in their metabolic profile compared to healthy controls. The findings suggest that metabolic pathways, including lipid and amino acid metabolism, play an important role in the pathophysiology of the disease, beyond immune dysregulation. 1 | INTRODUCTION Atopic dermatitis (AD) or eczema is the most common chronic, relapsing, pruritic, and inflammatory skin disease in childhood. It often starts in early childhood and has a reported prevalence of 15%–20%, with its incidence rapidly increasing in developed countries (1). In Turkey, its reported prevalence ranges from 7.5% to 17.1% (2). Atopik dermatitis has a multifactorial etiology, including genetic predisposition, environmental factors, epidermal barrier dysfunction, and immune system abnormalities (3). Despite numerous clinical, laboratory, and experimental studies, the pathophysiology of AD remains incompletely understood. It is clinically diagnosed based on patient history and the characteristic morphological distribution of skin lesions. To date, a comprehensive molecular investigation of the genetic and environmental factors contributing to AD remains to be conducted. Atopic dermatitis, representing the first step of the atopic march, may progress over time to asthma and allergic rhinitis. During this process, AD is frequently accompanied by allergies to food, particularly egg, milk, peanut, and tree nuts (4,5). Metabolomic studies have focused on the identification and quantification of metabolites produced by biological activities in biological samples. As metabolite levels reflect metabolic pathways, their measurements support the understanding, diagnosis, and management of complex diseases (6). In recent years, metabolomic approaches have emerged as important tools for elucidating the underlying biological processes in AD. The primary objective of this study was to characterize the blood metabolite profiles of patients with AD and healthy controls via nuclear magnetic resonance-based (IVDr-NMR) metabolic phenotyping. The association of metabolic findings with clinical and laboratory parameters, SCORAD index, and specific allergic conditions in patients with AD was also evaluated. The results provide insights into the underlying mechanisms of AD and may facilitate the identification of potential biomarkers. 2 | METHODS 2.1 Study Population This prospective cohort study was conducted at Acıbadem Mehmet Ali Aydınlar University, Acibadem Maslak Hospital. It included 31 volunteers, including 21 (aged 0–1 years) with active lesions of AD and 10 age- and sex-matched healthy controls. AD was diagnosed by a physician in outpatient clinics based on the Hanifin and Rajka criteria (7). Disease severity was evaluated using the SCORAD (Scoring Atopic Dermatitis) index, with scores below 50 classified as mild to moderate AD and scores above 50 indicating severe AD (8). Patients with active infections, concomitant dermatologic conditions (e.g., seborrheic dermatitis or nummular dermatitis), or systemic diseases were excluded. Healthy children without a history of atopy or infection were selected as controls. Data on patients’ demographics, body weight, disease onset, and feeding patterns were collected. The study protocol was approved by the Ethics Committee of Mehmet Ali Aydınlar Acıbadem University (approval no.: 2025-01/66). Informed consent was obtained from the parents of eligible patients following a detailed explanation of the study. 2.2 Food-Specific IgE Measurement and Food Challenge Test Serum samples were collected from the patients during the active lesion phase of AD, prior to initiating any food elimination diet. The diagnosis of IgE-mediated food allergy was confirmed by elevated serum-specific IgE levels ( > 0.35 kU/L) to particular foods. After the detection of suspected foods through serum-specific IgE measurements, a dietary elimination was implemented for 2 – 4 weeks. In breastfed infants, the elimination diet was applied to the mothers. As all the study patients were aged below 1 year, all suspected cases were subjected to an open food challenge test. A difference of >10 points in the SCORAD score was considered significant for the diagnosis of food allergy (9). 2.3 Eosinophil Count The eosinophil counts were measured using an automated hematology analyzer (Sysmex XN-2000). The absolute eosinophil counts and percentages from complete blood counts were recorded. Levels below 500/mm³ were considered to be normal, whereas those above 500/mm³ were classified as elevated. 2.4 Plasma Sample Preparation – NMR Sample Preparation The collected blood samples were allowed to stand at room temperature for up to 20 min, followed by centrifugation at 4000 rpm for 10 min. The separated serum was aliquoted into labeled Eppendorf tubes in 500-μL portions and stored at −80°C until the day of analysis. Before analysis, serum samples were thawed at room temperature and then vortexed to mix thoroughly. Following the recommended procedures for in vitro analytical and diagnostic protocols, 400-μL Bruker Plasma solution and 400-μL serum were mixed in a 1.5-mL Eppendorf tube. For measurement, 600 μL of the mixture was transferred into 5-mm NMR tubes. 2.5 NMR Spectroscopy Data Acquisition and Processing Parameters NMR analyses were conducted using a Bruker Avance III HD 600-MHz spectrometer (Bruker BioSpin, Ettlingen, Germany) equipped with a 5-mm BBI probe and a Bruker SampleJet cooling system set to 5°C. Solvent-suppressed standard one-dimensional experiments (noesygppr1d) were conducted with 32 scans (+4 dummy scans), 98k data points, a relaxation delay of 4.0 s, and a spectral width of 30 ppm. Meanwhile, Carr–Purcell–Meiboom–Gill (CPMG) spin-echo experiments (cpmgpr1d) were conducted with 32 scans, 74k data points, and a spectral width of 20 ppm. After solvent presaturation, DIRE and JEDI pulse sequences (PGPE, PGSE, PGPDE, and PGSE-5) were performed with 64 scans, 98k data points, and a spectral width of 30 ppm. All spectral data were automatically processed using the TopSpin 3.6.2 and ICON NMR software for phase correction and baseline adjustment. Metabolomic and lipoprotein analyses of the samples were conducted through a server-based service provided by Bruker BioSpin GmbH. A total of 112 lipoprotein parameters were quantified using the B.I.LISA™ platform. Metabolite concentrations were determined using the B.I.QUANT-PS™ analysis package. Quality control procedures included temperature regulation, magnetic field homogeneity checks, and ERETIC (Electronic Reference To access In vivo Concentrations)–based quantification, confirmed with three standard reference samples prior to each set of measurements. The concentration values were calculated using calibration curves derived from reference compounds. 2.6 Statistical Analysis The associations between metabolic findings and clinical and laboratory data related to the disease were evaluated. The patients’ demographic and clinical characteristics were summarized using descriptive statistics, including counts, percentages, means, and standard deviations. The proportional differences between the patients and the control groups were analyzed using Fisher’s exact test, whereas continuous variables were compared using the Mann–Whitney U test and Fisher’s exact test, as appropriate. The associations between metabolites and SCORAD score, age at disease onset, total IgE, and eosinophil counts were evaluated via Spearman correlation analysis. Data normality was assessed using skewness and kurtosis values (±1.5). All statistical analyses were conducted using IBM SPSS Statistics version 26.0. To identify metabolic biomarkers, NMR data were subjected to multivariate statistical analyses. Principal component analysis and partial least squares discriminant analysis were employed for dimensionality reduction and group discrimination. EZinfo 3.0 (MassLynx v4.1, Waters) was used for these analyses. The normality of the identified biomarkers was tested using the Shapiro–Wilk test. Subsequently, group comparisons were performed and evaluated using Analyze-it for Microsoft Excel (v30.2, Analyze-it Software Ltd., Leeds, UK). Finally, metabolomic data were subjected to cluster analysis to reveal metabolic pathway differences between the groups. For all tests, a p -value < 0.05 was considered statistically significant. 3.1 Population Characteristics Among the 21 patients with AD, 10 (47.6%) were male and 11 (52.4%) were female. Their median age was 7.5 months (Q1 = 5.00 – Q3 = 9.00), and their median body weight was 8920 g (Q1 = 7800 – Q3 = 10,400). For the mode of delivery, 16 (76.2%) were delivered vaginally and 5 (23.8%) via cesarean section. Furthermore, 13 patients (61.9%) had a family history of allergy, and 8 (38.1%) had none. Among the 10 healthy controls, 5 (50.0%) were male and 5 (50.0%) were female. Their median age was 7.0 months (Q1 = 6.00 – Q3 = 8.00), and their median body weight was 9760 g (Q1 = 8600 – Q3 = 10,500). The mode of delivery was equally distributed between vaginal and cesarean births (50%) in both groups. No statistically significant differences were observed between the AD and control groups in terms of age, sex, mode of delivery, or body weight ( p > 0.05). The median age of disease onset was 3.00 months (Q1 = 2.00 – Q3 = 6.00), with onset observed as early as 1 month and as late as 9 months. Meanwhile, the median SCORAD index was 22.00 (Q1 = 18.00 – Q3 = 35.00). Food-specific IgE evaluation showed positivity in 9 patients (42.9%) for egg, 5 (23.8%) for milk, and 6 (28.5%) for other foods. 3.2 Lipoprotein Analysis Comparison of serum total lipid parameters between the AD and control groups showed a statistically significant difference only in the number of intermediate density lipoprotein (IDL) particles ( p = 0.031). The AD group had significantly higher IDL-ApoB levels than the control group ( p = 0.031). Among the high density lipoprotein (HDL) lipoprotein content parameters, the HDL- cholesterol (HDCH) ( p = 0.012), HDL - free cholesterol (HDFC) ( p = 0.007), and HDL- phospholipid (HDPL) ( p = 0.022) levels were significantly lower in the AD group. Despite the lack of significant difference in total serum very low density lipoprotein (VLDL) levels between the groups, subfraction analyses revealed significantly higher levels of the VLDL-triglyceride fractions V2TG ( p = 0.008), V3TG ( p = 0.022), and V4TG ( p = 0.043); VLDL-cholesterol fractions V3CH ( p = 0.025) and V4CH ( p = 0.025); VLDL-free cholesterol levels V1FC ( p = 0.031) and V3FC ( p = 0.048); and VLDL-phospholipid levels V1PL ( p = 0.015), V2PL ( p = 0.003), and V3PL ( p = 0.007) in the AD than in the control group. Overall, no significant differences were observed in total low density lipoprotein (LDL) amounts or LDL subfractions. However, the LDL1 triglyceride levels were significantly elevated in the AD group ( p = 0.004), whereas the LDL3 triglyceride levels were significantly decreased ( p = 0.031) (Figure 1). The high density lipoprotein- triglyceride fractions H4TG levels were significantly higher in the AD than in the control group ( p < 0.001). Significant differences were also observed in the cholesterol, free cholesterol, phospholipid, ApoA1 (A1), and ApoA2 (A2) contents of the HDL fractions. Specifically, the levels of H1CH ( p = 0.008), H2CH ( p = 0.002), H1FC ( p = 0.008), H2FC ( p = 0.017), H1PL ( p = 0.008), H2PL ( p = 0.005), H1A1 ( p = 0.008), and H2A1 ( p = 0.012) were significantly lower in the AD group (Figure 2). 3.3 Metabolit Analyses Evaluation of serum metabolite levels revealed that glutamine levels were significantly higher in the patient group (p = 0.002), while phenylalanine (p = 0.039) and choline (p < 0.001) levels were significantly lower compared to controls (Figure 3). 3.4 Correlation Analyses The correlation analysis between the SCORAD index and metabolite levels revealed a significant negative correlation with VLDL5-cholesterol (V5CH) (r = 0.441; p < 0.005) and 2-oxoglutaric acid (r = −0.466; p < 0.005), whereas the ornithine levels showed a significant positive correlation with SCORAD (r = 0.473; p < 0.005). Age at disease onset showed significant negative correlations with HDL fraction parameters, including HDFC (r = −0.581; p < 0.001), H1FC (r = −0.497; p < 0.005), H3FC (r = −0.488; p < 0.005), H1PL (r = −0.488; p < 0.005), H2A1 (r = −0.452; p < 0.005), and H3A1 (r = −0.457; p < 0.005), as well as with the lysine (r = −0.510; p < 0.005) and pyruvic acid (r = −0.481; p < 0.005) levels. Sex-based comparisons showed that male patients had significantly lower levels of the VLDL subfractions V3TG ( p = 0.043), V4TG ( p = 0.043), V3FC ( p = 0.036), and V3PL ( p = 0.043) than female patients (Figure 4). Patients with egg allergy had significantly lower serum creatinine levels ( p = 0.041). Meanwhile, patıents with allergy to cow’s milk had significantly lower levels of H2PL ( p = 0.032), H3PL ( p = 0.025), and H3A1 ( p = 0.050). Among patients positive for specific IgE against foods other than milk and egg, the levels of L5FC ( p = 0.014), L5PL ( p = 0.029), L5AB ( p = 0.029), and citric acid ( p = 0.045) were significantly elevated, whereas the 2-hydroxybutyric acid levels were significantly decreased ( p = 0.018) (Figure 5). Patients with a family history of allergy had significantly higher levels of succinic acid ( p = 0.003), 3-hydroxybutyric acid ( p = 0.016), acetone ( p = 0.016), and dimethyl sulfone ( p = 0.025) than those without. 4 | Discussion Atopik dermatitis is a multifactorial disease that is associated not only with immune dysregulation but also with disturbances in metabolic processes (10). This study is the first to investigate NMR-based metabolic profile in patients with AD aged 0–1 year. The findings indicated significant correlations between metabolic pathways and clinical parameters, suggesting that AD is closely associated with neuroimmune and metabolic processes. Although no significant difference was observed in total VLDL levels between the groups, subfraction analyses revealed that the AD group had elevated triglyceride, cholesterol, free cholesterol, and phospholipid levels compared with the control group. The negative correlation between SCORAD index and VLDL5 cholesterol levels suggests potential alterations in liver-derived VLDL metabolism. Sex-based comparisons showed that male patients had lower VLDL triglyceride, free cholesterol, and phospholipid levels than female patients, indicating that lipid metabolism is less affected in the former patients. The elevated IDL levels in the AD group aligned with the increased VLDL content; a high IDL-ApoB ratio and unchanged LDL levels suggest that IDL particles are largely cleared by the liver. Imbalances in triglyceride distribution within LDL subfractions further support lipid metabolism disturbances (11). As LDL constitutes a major component of basement membrane cholesterol, its association with AD is plausible (12). In addition, LDL plays a role in hepatic bile acid synthesis. Previous studies have reported decreased levels of conjugated bile acids, such as glycine and taurine, in children with AD (13). The observed increase in triglyceride levels alongside reductions in cholesterol, phospholipid, ApoA1, and ApoA2 levels within HDL particles indicate impaired reverse cholesterol transport (14). Within our cohort, egg allergy was the most frequently identified food allergy, and the affected patients exhibited significantly lower creatinine levels, consistent with the findings from previous NMR-based studies in the literature (15). Patients with milk allergy had decreased levels of phospholipids and apoproteins in HDL subfractions, indicating impaired reverse cholesterol transport. Among the other food allergies, increased free cholesterol, phospholipid, apoprotein, and citric acid levels were observed in LDL5 subfractions, whereas the β-hydroxybutyric acid levels were decreased. These findings reinforce the role of lipid and energy metabolism alterations in the AD pathophysiology (16). Studies conducting detailed analyses of lipoprotein subfractions are scarce. Our study makes a pioneering contribution to the literature by providing a comprehensive evaluation of lipoproteins, encompassing both class level and subfraction composition. Amino acid metabolism analysis revealed higher glutamine levels and lower phenylalanine and choline levels in the AD group. Phenylalanine serves as a precursor for catecholamines, such as dopamine, noradrenaline, and adrenaline, and plays a role in immune modulation (17). Choline is crucial for acetylcholine synthesis and membrane integrity preservation, regulating the cholinergic anti-inflammatory response through acetylcholine (18,19). Cholinergic receptor dyregulation or acetylcholine level alterations may exacerbate pruritus and influence immune cell activity in the skin (20,21). Changes in phosphatidylcholine levels have also been reported in patients with AD, potentially increasing epidermal barrier permeability (22). Glutamine contributes to energy production through the tricarboxylic acid cycle via alpha-ketoglutaric acid (23). The negative correlation between alpha-ketoglutaric acid levels and the SCORAD index indicates energy metabolism disruption. Meanwhile, the positive correlation between ornithine levels and the SCORAD index may reflect an adaptive response to increased nitrogen load during inflammation. In addition, the negative correlation between age at disease onset and the levels of lysine and pyruvic acid suggests alterations in amino acid metabolism. As regards energy metabolism, patients with a family history of allergy exhibited elevated levels of acetone and β-hydroxybutyric acid, which are key ketogenesis end products, indicating the activation of alternative metabolic pathways to meet energy demands. This finding supports the concept that AD is not only an immunological disorder but also a systemic biochemical imbalance influencing energy metabolism (19, 24). The limitations of this study are the relatively small sample size and the lower sensitivity of NMR-based metabolomic analyses than mass spectrometry-based methods. In mass spectrometry, peptides with low abundance can be obscured by highly abundant peptides with similar properties. Contrarily, ¹H-NMR spectroscopy provides a powerful and highly informative approach for the structural determination of molecules in solution, with excellent analytical reproducibility. Although the study was originally planned to include serum measurements of periostin, interleukin-4, interleukin-13, and interleukin-18 and to examine their correlations with the metabolic profile, financial constraints required a reduction in the study scope. Nevertheless, the metabolomic profiling and correlation analyses conducted herein offer comprehensive insights into the AD pathophysiology, enhancing our understanding of disease-related metabolic alterations. In conclusion, our study shows systemic alterations in lipid profiles, amino acid metabolism, and energy production pathways in the AD pathogenesis. The significant correlations between metabolic pathways and clinical parameters suggest that the disease is influenced by neuroimmune–metabolic interactions, providing valuable insights for the development of diagnostic and therapeutic strategies. This pioneering work quantitatively demonstrates differences in NMR-based lipid profiles, lipoprotein subfractions, and other metabolites in patients with AD aged 0–1 year. These findings lay the groundwork for future research into AD etiopathogenesis, diagnosis, and treatment. With ongoing advancements, metabolomic analyses may emerge as a valuable screening tool, comparable to genetic diagnostics, contributing to the early detection and prevention of chronic diseases in contemporary clinical practice. Informed Consent Statement: The study protocol was approved by the Ethics Committee of Acıbadem Mehmet Ali Aydınlar University. Informed consent was obtained from the parents of all participants.

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J Dtsch Dermatol Ges . 2023;21(3):229-236. doi:10.1111/ddg.14960 Tables Table 1. Demographic characteristics of the AD and control groups | AD group (n=21) | Control group (n=10) | | | Age (months) (Med Q1–Q3) | 7,50 (5,00 – 9,00) | 7,00 (6,00-8,00) | | Sex (n/%) | || | ♂ Male | 10 (47,6%) | 5 (50,0%) | | ♀ Female | 11 (52,4%) | 5 (50,0%) | | Body weight (gram) (Med. Q1–Q3) | 8920 (7800 – 10.400) | 9760 (8600 – 10.500) | | Mode of delivery (n/%) | || | Vaginal delivery | 16 (76,2%) | 5 (50,0%) | | Cesarean delivery | 5 (23,8%) | 5 (50,0%) | Figure Captions Figure 1. Comparison of LDL subfraction triglyceride levels between children with atopic dermatitis and healthy controls. LDL1 triglyceride levels were significantly elevated in the AD group ( p = 0.004), whereas LDL3 triglyceride levels were significantly decreased ( p = 0.031). Figure 2. Comparison of HDL subfraction components between children with atopic dermatitis and healthy controls. The H4TG levels were significantly higher in the AD group than in the control group ( p < 0.001). In contrast, the contents of cholesterol, free cholesterol, phospholipid, ApoA1 (A1), and ApoA2 (A2) in the HDL fractions were significantly lower in the AD group, including H1CH ( p = 0.008), H2CH ( p = 0.002), H1FC ( p = 0.008), H2FC ( p = 0.017), H1PL ( p = 0.008), H2PL ( p = 0.005), H1A1 ( p = 0.008), and H2A1 ( p = 0.012). Figure 3. Comparison of serum metabolite levels between children with atopic dermatitis and healthy controls. Glutamine levels were significantly higher in the AD group ( p = 0.002), whereas phenylalanine ( p = 0.039) and choline ( p < 0.001) levels were significantly lower compared to the control group. Figure 4. Sex-based comparison of VLDL subfraction components in children with atopic dermatitis. Male patients showed significantly lower levels of V3TG ( p = 0.043), V4TG ( p = 0.043), V3FC ( p = 0.036), and V3PL ( p = 0.043) compared with female patients. Figure 5. Comparison of serum metabolite and lipoprotein subfraction levels according to food allergy status in children with atopic dermatitis. Patients with egg allergy had significantly lower serum creatinine levels ( p = 0.041). Those with cow’s milk allergy showed significantly lower levels of H2PL ( p = 0.032), H3PL ( p = 0.025), and H3A1 ( p = 0.050). In contrast, patients with specific IgE positivity to foods other than milk and egg had significantly higher levels of L5FC ( p = 0.014), L5PL ( p = 0.029), L5AB ( p = 0.029), and citric acid ( p = 0.045), while 2-hydroxybutyric acid levels were significantly decreased ( p = 0.018). Information & Authors Information Version history Copyright This work is licensed under a Non Exclusive No Reuse License. Authors Metrics & Citations Metrics Article Usage 212views 110downloads Citations Download citation Eda Erdem, Ahmet Tarık Baykal, Mustafa Serteser, et al. EVALUATION OF METABOLIC PROFILE IN CHILDREN WITH ATOPIC DERMATITIS. 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