SAT0487 PREDICTIVE BIOMARKERS OF I IgA VASCULITIS WITH NEPHRITIS BY METABOLOMIC ANALYSIS
Authors: S. Demir, M. Çelebier, O. Kaplan, E. Sag, Y. Bilginer, S. Özen
Journal: Annals of the Rheumatic Diseases (2020)

Background: IgA vasculitis/ Henoch Schönlein Purpura (IgAV/HSP) is the most common vasculitis of childhood and renal involvement is the most serious long-term complication. A better understanding of the pathophysiology of the progression to kidney disease is required for better treatment to be achieved and current biomarkers of Ig A vasculitis with nephritis (IgAVN) lack the predictive value. Objectives: In this study, an untargeted metabolomics approach was performed to reveal the underlying molecular mechanism of disease pathogenesis and to find potential biomarkers of plasma samples from patients with IgAV and IgAVN. Methods: IgAV/HSP was diagnosed according to the Ankara criteria in 2008 (1). Forty-five patients, including 39 active IgAV patients (H), 6 IgAVN (N), and 6 age- and gender-matched healthy controls (C), were enrolled in the study. Plasma samples from subjects were collected on the same day of IgAV(HSP) diagnosis and before steroid or other immunosuppressive treatment initiated. This study has utilized liquid chromatography-mass spectrometry (LC-MS/ Q-TOF) to investigate the alterations in plasma metabolomic profiles. Three separate pools, health controls, active IgAV, and IgAVN were created. Peak picking, grouping, and comparison parts were performed (metabolite profiling) via XCMS ( https://xcmsonline.scripps.edu/ ) software. Results: Totally 2618 peaks were detected for group H, N and C. Among them 355 peaks were found to be statistically significant and reliable (p&lt;0.05) and 155 of these peaks were found to be changed (fold change &gt;1.5) between the groups C and H. On the other hand, 66 peaks were found to be changed (fold change &gt;1.5) between the groups H and N. The number of the peaks on the intersection of the peaks found to be changed between the groups (C and H) and (H and N) was 39. This situation was illustrated in Figure 1. Based on putative identification results, 15 peaks were matched with 24 metabolites. The list of these metabolites is given in Table 1. Table 1. Putative identification of 15 peaks found to be statistically different and having fold changes. Peak Putative Identification KEGG Codes rt (min ) N/H 1 5-Aminopentanamide C00990 2,10 0,36 1 5-Aminopentanoic acid C00431 2,10 0,36 1 2-Keto-6-aminocaproate C03239 2,10 0,36 1 (S)-5-Amino-3-oxohexanoate C03656 2,10 0,36 1 D-1-Piperideine-2-carboxylic acid C04092 2,10 0,36 2 Oxalureate C00802 15,52 0,50 3 Porphobilinogen C00931 14,78 9,62 4 (+)-cis-3,4-Dihydrophenanthrene-3,4-diol C04468 15,52 0,02 5 (-)-trans-Carveol C00964 12,69 1,82 6 DHAP(18:0) C03805 12,70 1,92 6 N-Acetyl-b-glucosaminylamine C01239 12,70 1,92 7 5-Methyltetrahydrofolic acid C00440 14,88 2,41 8 N2-Succinyl-L-ornithine C03415 15,52 0,05 8 N6-Acetyl-LL-2,6-diaminoheptanedioate C04390 15,52 0,05 9 Estrone C00468 12,71 1,90 10 N-Acetyl-4-O-acetylneuraminic acid C04015 14,89 2,41 10 N-Acetyl-7-O-acetylneuraminic acid C04016 14,89 2,41 11 Oleoyl-CoA C00510 15,52 0,26 12 Saccharopine C00449 15,52 0,26 13 Prostaglandin D2 C00696 17,81 2,05 13 Prostaglandin I2 C01312 17,81 2,05 14 Glycocholic acid C01921 13,78 0,61 15 Galactosylsphingosine C01747 24,41 0,45 15 Glucosylsphingosine C03108 24,41 0,45 Figure 1. The number of the peaks found on datamining process Conclusion: Certain differences in metabolites were identified between controls and IgAV patients and between those with and without kidney involvement. References: [1]Ozen S, Pistorio A, Iusan SM, Bakkaloglu A, Herlin T, Brik R, et al. EULAR/PRINTO/PRES criteria for Henoch-Schonlein purpura, childhood polyarteritis nodosa, childhood Wegener granulomatosis and childhood Takayasu arteritis: Ankara 2008. Part II: final classification criteria. Ann Rheum Dis 2010;69(5):798e806. Disclosure of Interests: Selcan Demir: None declared, Mustafa Çelebier: None declared, Ozan Kaplan: None declared, Erdal Sag Grant/research support from: Novartis and SOBI financially supported the HELIOS registry during the establishment of infrastructure, Yelda Bilginer Grant/research support from: Novartis and SOBI financially supported the HELIOS registry during the establishment of infrastructure, Seza Özen Consultant of: Novartis, Pfizer, Speakers bureau: SOBI, Novartis