Journal Article

POS0753 METABOLOMICS AND LIPIDOMICS IN JUVENILE LOCALIZED SCLERODERMA

Aquilani, A., Maglio, C., De Benedetti, F., Nicolai, R., Zhang, Y., Marasco, E.

2024

Overview

Background:Juvenile localised scleroderma (jLS) is a rare rheumatic disease in children characterized by inflammation and fibrosis in the skin [1, 2]. The cause and pathogenesis of jLS remain unclear, and both skin lesions and possible extracutaneous involvement may result in functional impairment and growth disturbances [2]. The treatment options to cure jLS are limited [3].In recent years, omics technologies have been used to identify novel biomarkers in different diseases [4, 5]. Among the different omics technologies, metabolomics and lipidomics provide snapshots of the metabolic network.Objectives:We aim to identify biomarkers and treatment targets for jLS using metabolomics and lipidomics.Methods:Children with jLS and age-matched controls were recruited at Bambino Gesù Children’s Hospital, Roma, Italy. The characteristics of the participants are shown in Table 1.Plasma samples from 9 controls and 12 patients with jLS (before treatment initiation and 17 months after treatment) were sent to Swedish Metabolomics Center, where liquid chromatography–mass spectrometry and gas chromatography–mass spectrometry were performed (Figure 1A). Peak intensities were recorded, and the data analysis was performed using Metaboanalyst 5.0 and Graphpad Prism 10 software. Pathway enrichment bubble plots were generated using SRplot [6]. Mann-Whitney test was used to compare healthy control and baseline patient groups, and Wilcoxon test was used to compare differences between baseline and treated patients.Results:In total, 250 metabolites and 194 putative lipids were annotated (Figure 1A). Patients at baseline had significantly lower peak intensities of lenticin, 3-hydroxybutyrylcarnitine, 1-dodecanoyllysophosphatidylcholine, phosphatidylcholine (PC) 38:6 and 40:9, and phosphatidylserine (PS) 38:1 as well as significantly higher peak intensities of L-tyrosine, phenylpyruvic acid, (3-hydroxyphenyl)hydracrylate, and cortisol compared to controls (Figure 2B). After treatment, peak intensities of adenosine monophosphate, hypoxanthine, 3-phosphoglyceric acid, lysophosphatidylcholine (LPC) 18:2, Cholesteryl Octanoate (CE 8:0), and 2-Hydroxylauroylcarnitine (CAR 12:0) were decreased, whereas peak intensities of L-octanoylcarnitine and eleven molecular species of triacylglycerols were increased compared to baseline patients (Figure 2D). The top enriched pathways are shown in Figure 2C and 2E.Conclusion:We have described the metabolic profile in blood of children with jLS for the first time. Children with jLS show a distinct metabolic profile compared to healthy children, especially in tyrosine-related pathways. Compared to baseline levels, the metabolism of several amino acids was altered after treatment, and the energy storage function might be modified as eleven molecular species of triacylglycerols were found decreased.REFERENCES:[1] Zulian, F., et al., Consensus-based recommendations for the management of juvenile localised scleroderma. Ann Rheum Dis, 2019. 78(8): p. 1019-1024.[2] Li, S.C. and R.J. Zheng, Overview of Juvenile localized scleroderma and its management. World J Pediatr, 2020. 16(1): p. 5-18.[3] Li, S.C., Treatment of juvenile localized scleroderma: current recommendations, response factors, and potential alternative treatments. Current Opinion in Rheumatology, 2022. 34(5): p. 245-254.[4] Puentes-Osorio, Y., et al., Potential clinical biomarkers in rheumatoid arthritis with an omic approach. Autoimmunity Highlights, 2021. 12(1).[5] Xiao, Y.A., et al., Multi-omics approaches for biomarker discovery in early ovarian cancer diagnosis. Ebiomedicine, 2022. 79.[6] Tang, D., et al., SRplot: A free online platform for data visualization and graphing. PLoS One, 2023. 18(11): p. e0294236.Table 1.Characteristics of the participantsCharacteristicsPatientsControlsN129Age, years10±410±4Females, n (%)6 (50)8 (89)Follow-up, months17±3Treatment:Prednisolone, n (%)10 (83)Methotrexate, n (%)12 (100)Tocilizumab, n (%)2 (17)Figure 1.Study design (A), volcano plot of all the annotated metabolites and lipids (B, D), metabolic pathway analysis with the most changed metabolites (C, E).Acknowledgements:Participants who donated the blood samplesDisclosure of Interests:Yuan Zhang: None declared, Angela Aquilani: None declared, Rebecca Nicolai: None declared, Fabrizio De Benedetti Speaker for Novartis and SOBI, Emiliano Marasco: None declared, Cristina Maglio: None declared.

• Publisher: BMJ Publishing Group Ltd and European League Against Rheumatism,Elsevier B.V
• Subject: Descriptive Studies / Omics / Scientific Abstracts