Using serum metabolomics to predict development of anti-drug antibodies in multiple sclerosis patients treated with IFNβ

Published: 3 July 2020| Version 1 | DOI: 10.17632/jbjh3gmknw.1
Kirsty Waddington,
Artemis Papadaki,
Leda Coelewij,
Marsilio Adiani,
Petra Nytrova,
Eva Kubala Havrdova,
Anna Fogdell-Hahn,
Rachel Farrell,
Pierre Dönnes,
Ines Pineda-Torra,
Liz Jury


Hypothesis: Serum metabolomics can be used to predict immunogenicity against IFNβ in multiple sclerosis patients A prospective cohort of multiple sclerosis (MS) patients was recruited across six European countries as part of the Anti-Biopharmaceutical Immunization: prediction and analysis of clinical relevance to minimize the RISK consortium (ABIRISK consortium; Serum samples were collected from MS patients prior to IFNβ treatment (M0), and after 3 (M3) and 12 (M12) months to be used for anti-drug antibody detection (ADA) and metabolomic analysis. 228 serum metabolites and lipids were quantified using an established nuclear magnetic resonance spectroscopy platform (Nightingale Health). The dataset includes absolute concentrations (mmol), and relative measures (ratios, percentages) from 82 MS patients (M0 and M12). 9 were missing at M3, leaving n=73 at this time-point. Serum was tested for both binding (bAbs) and neutralizing (nAbs) ADA, measured with an enzyme-linked immunosorbent assay (ELISA) (Ingenhoven et al., 2017) and cell-based luciferase reporter gene assay (Hermanrud et al., 2016), respectively. Patients were classified as ADA positive if they were positive for bAbs, or had a nAbs titer >320 U/mL within 12 months of starting treatment. Patients were considered ADA negative if they were negative for both assays. Patients with missing data or negative for bAbs and with a nAbs titer <320 U/mL were excluded.



Metabolomics, Multiple Sclerosis, Immunogenicity, Lipoprotein Metabolism