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THU0133 Lipidomics Profiling Differ in Patients with Rheumatoid Arthritis and Controls
  1. A. Södergren1,
  2. I. Surowiec2,
  3. I. Abreu3,
  4. R. Madsen2,
  5. J. Trygg2,
  6. S. Wållberg-Jonsson1
  1. 1Department of Public Health and Clinical Medicine/Rheumatology, Umeå University
  2. 2Computational Life Science Cluster, Department of Chemistry, University of Umeå
  3. 3Forest Genetics and Plant Physiology, Umeå Plant Science Centre, Umeå, Sweden

Abstract

Background Patients with rheumatoid arthritis (RA) have an increased mortality and morbidity due to cardiovascular disease (CVD). A premature atherosclerosis can be measured by ultrasound of intima media thickness (IMT). Omics studies such as metabolomics, proteomics and lipidomics have been extensively used to elucidate biological mechanisms of diseases through characterization and quantification of biological molecules and have already proven its usefulness in the clinical research area.

Objectives In this prospective 5-year follow up, we aimed to investigate the plasma lipidomics profiles in patients with RA compared to controls. We also aimed to analyze the relationship between these profiles and atherosclerosis measured by IMT.

Methods Patients from northern Sweden diagnosed with early RA are followed in an ongoing prospective study of co-morbidity. From these patients a subgroup aged ≤60 years (n=18), was consecutively included for measurements of IMT of a. carotis communis. The ultrasound measurements were performed at inclusion (T0), after 18 months (T18) and after 60 months (T60). 20 age/sex matched controls were included. Blood was drawn at all time points and stored in -80°C. A methanol/chloroform based protocol was used on the plasma samples to extract lipid species, which were then analyzed with LC-OrbitrapMS; compound detection and quantification was performed with Thermo Scientific SIEVE Software. Principal component analysis (PCA) and orthogonal partial least squares analysis (OPLS) models were used to model the data and highlight molecular patterns characteristic for studied groups of patients at different time points and the ones related to the IMT values.

Results Statistically significant and consistent changes in lipid profiles between RA patients and controls at each sampling point (T0, T18 and T60) were observed. At T0, higher levels of lipids were seen in RA patients, whereas at time points T18 and T60 the trend was exactly opposite – lower levels of lipids were present in RA patients compared to controls (Figure 1). Regarding changes in lipids profiles over time, significant OPLS-DA models could be obtained only for changes between T18 and T0. Also here, opposite behavior was observed for both groups of patients – for RA patients we observed a decrease of lipid levels in the 18-month period, whereas an increase was observed for controls.

To observe if there is any relation of lipid profiles to the IMT, we used OPLS modeling with IMT values as Y variable. For T0 we could obtain a statistically significant OPLS model only for RA samples, in which a consistent increase in plasma lipids was observed with increased IMT values. For time point T60, the relation was different – approximately half of the lipids were positively and half negatively correlated with IMT in RA patients with similar results for controls at T60.

Conclusions Lipidomics profiling shows that the metabolism of lipid species differs between patients with RA and controls, both at diagnosis and during five years follow up. Moreover, our results indicate that the metabolism of lipid species changes over time, both when trend for RA patients is compared to controls and when the development of atherosclerosis is followed.

Disclosure of Interest None declared

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