Pre-defined gene co-expression modules in rheumatoid arthritis transition towards molecular health following anti-TNF therapy

Megan Sutcliffe, Nisha Nair, James Oliver, Ann W Morgan, John D Isaacs, Anthony Wilson, Suzanne Verstappen, Sebastien Viatte, Kimme Hyrich, Andrew Morris, Anne Barton, Darren Plant

Research output: Contribution to journalArticlepeer-review


Background: No reliable biomarkers to predict response to tumour necrosis factor inhibitors (TNFi) in rheumatoid arthritis (RA) patients currently exist. The aims of this study were to replicate changes in gene co-expression modules that were previously reported in response to TNFi therapy in RA; to test if changes in module expression are specific to TNFi therapy; and to determine whether module expression transitions towards a disease-free state in responding patients.

Method: Published transcriptomic data from the whole blood of disease-free controls (n = 10) and RA patients, treated with the TNFi adalimumab (n = 70) or methotrexate (n = 85), were studied. Treatment response was assessed using the EULAR response criteria following 3 or 6 months of treatment. Change in transcript expression between pre- and post-treatment was recorded for previously defined modules. Linear mixed models tested whether modular expression after treatment transitioned towards a disease-free state.

Results: For 25 of the 27 modules, change in expression between pre- and post-treatment in the adalimumab cohort replicated published findings. Of these 25 modules, 6 transitioned towards a disease-free state by 3-months (p < 0.05), irrespective of clinical response. One module (M3.2), related to inflammation and TNF biology, significantly correlated with response to adalimumab. Similar patterns of modular expression, with reduced magnitude, were observed in the methotrexate cohort.

Conclusion: This study provides independent validation of changes in module expression in response to therapy in RA. However, these effects are not specific to TNFi. Further studies are required to determine whether specific modules could assist molecular classification of therapeutic response.
Original languageEnglish
JournalRheumatology (Oxford)
Early online date4 Apr 2022
Publication statusPublished - 4 Apr 2022


  • Biological therapies; Biomarkers; Rheumatoid arthritis; TNFi; genetics; inflammation; transcriptomics; treatment response


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