Pos0460 metabolomics Across Age Identifies Unique Changes in the Serum Metabolic Profile in Patients With Sle

Abstract

BackgroundCardiovascular disease (CVD) is a leading cause of mortality in patients with systemic lupus erythematosus (SLE, female:male ratio of 9:1) through accelerated atherosclerosis, the build-up of lipids and inflammation in the major artery walls, compared to age and sex matched healthy individuals. This is due to chronic inflammation, dyslipidaemia and other cardiometabolic defects that exacerbate with age (1). SLE in women aged of 35-44 increases the risk of coronary artery disease by 50 times and there is a 100-300-fold increased CVD-related mortality risk in young patients that develop SLE before the age of 18. Investigating metabolic defects in young patients and how they progress with age could help us understand the progressive mechanisms of atherosclerosis in SLE.ObjectivesThis study investigated detailed changes in the metabolomic profile of female patients with SLE and matched healthy controls across age.MethodsSerum NMR metabolomics (>250 metabolites, Nightingale) covering glycolysis metabolites, amino acids and 130 lipid measures was performed on serum from a cohort of female SLE patients (n=164, 13-72 years of age, median 35) and matched healthy controls (HCs, n=120, 15-76 years of age, median 36) and analysed by linear regression and Venn analysis. Multiple t-tests (corrected for multiple comparisons by false discovery rate) were used to assess unique metabolic changes by age group between SLE patients and HCs (≤25, n=62/43; 26-49, n=50/46; ≥50, n=52/31) and dysregulated metabolic pathways were assessed using metaboanalyst software. The metabolic impact of disease activity measures and treatments was assessed by Spearman correlations and unpaired t-tests respectively.ResultsTwenty-five metabolites were significantly altered in all SLE age groups compared to HCs, dominated by atheroprotective high density lipoprotein (HDL) subsets and their surface-bound peptide, apolipoprotein(Apo)A1, all of which were significantly decreased in SLE compared to HCs (p<0.0001 in ages combined). In addition, the concentration of glycoprotein acetyls (GlycA, inflammatory biomarker) was increased in SLE in all age groups compared to HCs (p<0.0001 in ages combined). Importantly, ApoA1 correlated negatively with disease activity measures (SLEDAI, p=0.005; BILAG, p=0.0009; dsDNA, p=0.003; ESR, p=0.0006) and positively with lymphocyte count (p=0.0005), whilst GlycA correlated positively with ESR (p<0.0001) and CRP (p<0.0001). Alternatively, metabolites unique to specific age groups in SLE compared to HCs included reduced amino acid subsets in the ≤25 age group, increased atherogenic very low density lipoproteins and reduced polyunsaturated fatty acids in the 26-49 age group, and increased atherogenic low density lipoproteins in the ≥50 age group.Separately, metabolites associated with the glycolysis pathway (p=0.004, metaboanalyist), including acetone, citrate, creatinine, glycerol, lactate and pyruvate, had significant positive correlations with age in SLE patients, but not in HCs. These metabolites were not significantly associated with disease activity measures. However, pyruvate (p=0.01) and lactate (p=0.009) were significantly upregulated in prednisolone treated patients, whilst citrate (p=0.002) and creatinine (p= 0.005) were downregulated in hydroxychloroquine treated patients.ConclusionIncreasing HDL (ApoA1) levels whilst maintaining low disease activity in patients with SLE from a young age could improve cardiometabolic risk outcomes. This could be achieved through improved nutrition, lipid targeted therapies and better treatment strategies. Focusing on understanding and monitoring biomarkers of the glycolytic pathway could aid treatment decisions and help avoid adverse metabolic effects of current anti-inflammatory therapies in SLE (1).References[1]Robinson G.A, Pineda-Torra I, Ciurtin C, Jury E.C. Lipid metabolism in autoimmune rheumatic disease: implications for modern and conventional therapies. J Clin Invest. 2022;132(2):e148552. https://doi.org/10.1172/JCI148552.AcknowledgementsThe authors would like to thank all of the patients and healthy blood donors, as well as Prof. Arne Akbar and Dr. Chris Wincup for additional patient and healthy donor samples.Disclosure of InterestsNone declared.