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A6.03 Lipidomics profiling differs 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
  2. 2Computational Life Science Cluster, Department of Chemistry, University of Umeå
  3. 3Forest Genetics and Plant Physiology, Umeå Plant Science Centre, Sweden

Abstract

Background and objectives 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.

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 analyse the relationship between these profiles and atherosclerosis measured by IMT.

Materials and methods Patients from northern Sweden diagnosed with early RA are followed in an ongoing prospective study. From these patients a subgroup aged ≤60 years (n = 18), was consecutively included for measurements of IMT 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 analysed with LC-OrbitrapMS; compound detection and quantification was performed with Thermo Scientific SIEVE Software.

Results Statistically significant and consistent changes in lipid profiles between RA patients and controls at each sampling point 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 (Figure 1). To observe if there is any relation of lipid profiles to the IMT, we used OPLS modelling with IMT values as Y variable. For IMT at T0 we could obtain a statistically significant model only for RA samples, here an increase in plasma lipids was observed with increased  IMT values. At T60 approximately half of the lipids were positively and half negatively correlated with IMT in RA patients.

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.

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