Objectives Development of anti-drug antibodies (ADAs) is a barrier to long-term efficacy of biologic therapies in rheumatoid arthritis (RA), but no biomarkers exist to predict ADA formation. This study explored the potential of serum metabolomics to predict development of ADAs to adalimumab in patients with RA.

Methods Serum from patients with RA (n=47), treatment naïve for tumour necrosis factor-alpha inhibitor therapy, were collected before, Month(M)1 and M12 following initiation of adalimumab therapy as standard of care. Sera were tested for ADAs and patients were stratified according to M12 ADA status (ADA-positive n=21; ADA-negative n=26). Serum metabolomics was performed using a NMR-based platform. Metabolomic and clinical data were analysed using machine learning (ML) to develop a signature associated with ADA development.

Results ML analysis of baseline serum metabolomics and clinical data identified a signature that distinguished patients according to their future M12 ADA status (ADA-positive/ADA-negative) prior to first adalimumab treatment (area under the receiver operator curve, AUC-ROC=0.78), which out-performed clinical parameters alone (AUC-ROC=0.78). Metabolites related to cholesterol transport including large high and very low-density lipoproteins (L-HDL/VLDL) and small low density-lipoprotein (S-LDL) and clinical markers body mass index (BMI) and erythrocyte sedimentation rate were top discriminating features. Patients stratified as ADA-positive/ADA-negative at baseline also had different serum metabolic responses to adalimumab at M1 and M12. Finally, a putative predictive score for future ADA status was generated comprising L-HDL, L-LDL, extra-large VLDL subsets and BMI.

Conclusion These results support the potential of serum metabolomics as a predictive tool for immunogenicity risk in RA.

Key messages

Machine learning models identified serum metabolomic signatures associated with future treatment immunogenicity.

Lipid-related metabolites suggest changes in lipid metabolism could influence ADA susceptibility.

The authors have declared no competing interest.

This work was supported by a UCL & Birkbeck MRC Doctoral Training Program studentship supporting AEO (MR/N013867/1) JJM was supported by the UCLH NIHR Biomedical Research Centre. The Innovative Medicines Initiative Joint grant agreement no 115303, as part of the ABIRISK consortium (Anti-Biopharmaceutical Immunization: Prediction and analysis of clinical relevance to minimize the risk) supported RA patient recruitment and ADA testing.

I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.

Yes

The details of the IRB/oversight body that provided approval or exemption for the research described are given below:

Ethical approval was granted by the Comite de Protection des Personnes Ile de France VII for France (reference 13 048); the Medical Ethical Committee of the Academisch Medisch Centrum, Amsterdam for the Netherlands (reference 2013 304 B20131074); the Local Ethics Committee of Azienda Ospedaliero Universitaria Careggi for Italy (reference 2012/0035982); and the National Research Ethics Service Committee London, City and East (reference 14/LO/0506) for the UK. All participants provided informed written consent.

I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals.

Yes

I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).

Yes

I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable.

Yes

All anonymised metabolomic data will be made available on publication