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3. Population Pharmacokinetic Analysis and Simulation of Alternative Dosing Regimens for Biosimilars to Adalimumab and Etanercept in Patients with Rheumatoid Arthritis

Author

Ling, Stephanie F., primary, Ogungbenro, Kayode, additional, Darwich, Adam S., additional, Ariff, Amirah Binti Mohammad, additional, Nair, Nisha, additional, Bluett, James, additional, Morgan, Ann W., additional, Isaacs, John D., additional, Wilson, Anthony G., additional, Hyrich, Kimme L., additional, Barton, Anne, additional, and Plant, Darren, additional

Published
2024
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5. Population Pharmacokinetic Analysis and Simulation of Alternative Dosing Regimens for Biosimilars to Adalimumab and Etanercept in Patients with Rheumatoid Arthritis

Author

Ling, Stephanie F., Ogungbenro, Kayode, Darwich, Adam S., Ariff, Amirah Binti Mohammad, Nair, Nisha, Bluett, James, Morgan, Ann W., Isaacs, John D., Wilson, Anthony G., Hyrich, Kimme L., Barton, Anne, Plant, Darren, Ling, Stephanie F., Ogungbenro, Kayode, Darwich, Adam S., Ariff, Amirah Binti Mohammad, Nair, Nisha, Bluett, James, Morgan, Ann W., Isaacs, John D., Wilson, Anthony G., Hyrich, Kimme L., Barton, Anne, and Plant, Darren

Abstract

Efficacy to biologics in rheumatoid arthritis (RA) patients is variable and is likely influenced by each patient’s circulating drug levels. Using modelling and simulation, the aim of this study was to investigate whether adalimumab and etanercept biosimilar dosing intervals can be altered to achieve therapeutic drug levels at a faster/similar time compared to the recommended interval. RA patients starting subcutaneous Amgevita or Benepali (adalimumab and etanercept biosimilars, respectively) were recruited and underwent sparse serum sampling for drug concentrations. Drug levels were measured using commercially available kits. Pharmacokinetic data were analysed using a population approach (popPK) and potential covariates were investigated in models. Models were compared using goodness-of-fit criteria. Final models were selected and used to simulate alternative dosing intervals. Ten RA patients starting the adalimumab biosimilar and six patients starting the etanercept biosimilar were recruited. One-compartment PK models were used to describe the popPK models for both drugs; no significant covariates were found. Typical individual parameter estimates were used to simulate altered dosing intervals for both drugs. A simulation of dosing the etanercept biosimilar at a lower rate of every 10 days reached steady-state concentrations earlier than the usual dosing rate of every 7 days. Simulations of altered dosing intervals could form the basis for future personalised dosing studies, potentially saving costs whilst increasing efficacy., QC 20240627

Published
2024
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8. A proteomics study of rheumatoid arthritis patients on etanercept identifies putative biomarkers associated with clinical outcome measures.

Author

Ling, Stephanie F, Yap, Chuan Fu, Nair, Nisha, Bluett, James, Morgan, Ann W, Isaacs, John D, Wilson, Anthony G, Hyrich, Kimme L, Barton, Anne, and Plant, Darren

Subjects
PROTEIN analysis, RESEARCH funding, RHEUMATOID arthritis, ANTIRHEUMATIC agents, TREATMENT effectiveness, ETANERCEPT, LONGITUDINAL method, PROTEOMICS, MASS spectrometry, BIOMARKERS, GENETICS
Abstract

Objectives Biologic DMARDs (bDMARDs) are widely used in patients with RA, but response to bDMARDs is heterogeneous. The objective of this work was to identify pretreatment proteomic biomarkers associated with RA clinical outcome measures in patients starting bDMARDs. Methods Sequential window acquisition of all theoretical fragment ion spectra mass spectrometry (SWATH-MS) was used to generate spectral maps of sera from patients with RA before and after 3 months of treatment with the bDMARD etanercept. Protein levels were regressed against RA clinical outcome measures, i.e. 28-joint DAS (DAS28) and its subcomponents and DAS28 <2.6 (i.e. remission). The proteins with the strongest evidence for association were analysed in an independent, replication dataset. Finally, subnetwork analysis was carried out using the Disease Module Detection algorithm and biological plausibility of identified proteins was assessed by enrichment analysis. Results A total of 180 patients with RA were included in the discovery dataset and 58 in the validation dataset from a UK-based prospective multicentre study. Ten individual proteins were found to be significantly associated with RA clinical outcome measures. The association of T-complex protein 1 subunit η with DAS28 remission was replicated in an independent cohort. Subnetwork analysis of the 10 proteins from the regression analysis identified the ontological theme, with the strongest associations being with acute phase and acute inflammatory responses. Conclusion This longitudinal study of 180 patients with RA commencing etanercept has identified several putative protein biomarkers of treatment response to this drug, one of which was replicated in an independent cohort. [ABSTRACT FROM AUTHOR]

Published
2024
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12. A Method to Exploit the Structure of Genetic Ancestry Space to Enhance Case-Control Studies

Author

Barclay, Murray, Peyrin-Biroulet, Laurent, Chamaillard, Mathias, Colombel, Jean-Frederick, Cottone, Mario, Croft, Anthony, D’Incà, Renata, Halfvarson, Jonas, Hanigan, Katherine, Henderson, Paul, Hugot, Jean-Pierre, Karban, Amir, Kennedy, Nicholas A., Khan, Mohammed Azam, Lémann, Marc, Levine, Arie, Massey, Dunecan, Milla, Monica, Montgomery, Grant W., Ng, Sok Meng Evelyn, Oikonomou, Ioannis, Peeters, Harald, Proctor, Deborah D., Rahier, Jean-Francois, Roberts, Rebecca, Rutgeerts, Paul, Seibold, Frank, Stronati, Laura, Taylor, Kirstin M., Törkvist, Leif, Ublick, Kullak, Van Limbergen, Johan, Van Gossum, Andre, Vatn, Morten H., Zhang, Hu, Zhang, Wei, Andrews, Jane M., Bampton, Peter A., Florin, Timothy H., Gearry, Richard, Krishnaprasad, Krupa, Lawrance, Ian C., Mahy, Gillian, Radford-Smith, Graham, Roberts, Rebecca L., Simms, Lisa A., Amininijad, Leila, Cleynen, Isabelle, Dewit, Olivier, Franchimont, Denis, Georges, Michel, Laukens, Debby, Theatre, Emilie, Van Gossum, André, Vermeire, Severine, Aumais, Guy, Baidoo, Leonard, Barrie, Arthur M., III, Beck, Karen, Bernard, Edmond-Jean, Binion, David G., Bitton, Alain, Brant, Steve R., Cho, Judy H., Cohen, Albert, Croitoru, Kenneth, Daly, Mark J., Datta, Lisa W., Deslandres, Colette, Duerr, Richard H., Dutridge, Debra, Ferguson, John, Fultz, Joann, Goyette, Philippe, Greenberg, Gordon R., Haritunians, Talin, Jobin, Gilles, Katz, Seymour, Lahaie, Raymond G., McGovern, Dermot P., Nelson, Linda, Ng, Sok Meng, Ning, Kaida, Paré, Pierre, Regueiro, Miguel D., Rioux, John D., Ruggiero, Elizabeth, Schumm, L. Philip, Schwartz, Marc, Scott, Regan, Sharma, Yashoda, Silverberg, Mark S., Spears, Denise, Steinhart, A. Hillary, Stempak, Joanne M., Swoger, Jason M., Tsagarelis, Constantina, Zhang, Clarence, Zhao, Hongyu, Aerts, Jan, Ahmad, Tariq, Arbury, Hazel, Attwood, Anthony, Auton, Adam, Ball, Stephen G., Balmforth, Anthony J., Barnes, Chris, Barrett, Jeffrey C., Barroso, Inês, Barton, Anne, Bennett, Amanda J., Bhaskar, Sanjeev, Blaszczyk, Katarzyna, Bowes, John, Brand, Oliver J., Braund, Peter S., Bredin, Francesca, Breen, Gerome, Brown, Morris J., Bruce, Ian N., Bull, Jaswinder, Burren, Oliver S., Burton, John, Byrnes, Jake, Caesar, Sian, Cardin, Niall, Clee, Chris M., Coffey, Alison J., Connell, John M.C., Conrad, Donald F., Cooper, Jason D., Dominiczak, Anna F., Downes, Kate, Drummond, Hazel E., Dudakia, Darshna, Dunham, Andrew, Ebbs, Bernadette, Eccles, Diana, Edkins, Sarah, Edwards, Cathryn, Elliot, Anna, Emery, Paul, Evans, David M., Evans, Gareth, Eyre, Steve, Farmer, Anne, I, Ferrier, Nicol, Flynn, Edward, Forbes, Alistair, Forty, Liz, Franklyn, Jayne A., Frayling, Timothy M., Freathy, Rachel M., Giannoulatou, Eleni, Gibbs, Polly, Gilbert, Paul, Gordon-Smith, Katherine, Gray, Emma, Green, Elaine, Groves, Chris J., Grozeva, Detelina, Gwilliam, Rhian, Hall, Anita, Hammond, Naomi, Hardy, Matt, Harrison, Pile, Hassanali, Neelam, Hebaishi, Husam, Hines, Sarah, Hinks, Anne, Hitman, Graham A., Hocking, Lynne, Holmes, Chris, Howard, Eleanor, Howard, Philip, Howson, Joanna M.M., Hughes, Debbie, Hunt, Sarah, Isaacs, John D., Jain, Mahim, Jewell, Derek P., Johnson, Toby, Jolley, Jennifer D., Jones, Ian R., Jones, Lisa A., Kirov, George, Langford, Cordelia F., Lango-Allen, Hana, Lathrop, G. Mark, Lee, James, Lee, Kate L., Lees, Charlie, Lewis, Kevin, Lindgren, Cecilia M., Maisuria-Armer, Meeta, Maller, Julian, Mansfield, John, Marchini, Jonathan L., Martin, Paul, Massey, Dunecan C.O., McArdle, Wendy L., McGuffin, Peter, McLay, Kirsten E., McVean, Gil, Mentzer, Alex, Mimmack, Michael L., Morgan, Ann E., Morris, Andrew P., Mowat, Craig, Munroe, Patricia B., Myers, Simon, Newman, William, Nimmo, Elaine R., O’Donovan, Michael C., Onipinla, Abiodun, Ovington, Nigel R., Owen, Michael J., Palin, Kimmo, Palotie, Aarno, Parnell, Kirstie, Pearson, Richard, Pernet, David, Perry, John R.B., Phillips, Anne, Plagnol, Vincent, Prescott, Natalie J., Prokopenko, Inga, Quail, Michael A., Rafelt, Suzanne, Rayner, Nigel W., Reid, David M., Renwick, Anthony, Ring, Susan M., Robertson, Neil, Robson, Samuel, Russell, Ellie, St Clair, David, Sambrook, Jennifer G., Sanderson, Jeremy D., Sawcer, Stephen J., Schuilenburg, Helen, Scott, Carol E., Scott, Richard, Seal, Sheila, Shaw-Hawkins, Sue, Shields, Beverley M., Simmonds, Matthew J., Smyth, Debbie J., Somaskantharajah, Elilan, Spanova, Katarina, Steer, Sophia, Stephens, Jonathan, Stevens, Helen E., Stirrups, Kathy, Stone, Millicent A., Strachan, David P., Su, Zhan, Symmons, Deborah P.M., Thompson, John R., Thomson, Wendy, Tobin, Martin D., Travers, Mary E., Turnbull, Clare, Vukcevic, Damjan, Wain, Louise V., Walker, Mark, Walker, Neil M., Wallace, Chris, Warren-Perry, Margaret, Watkins, Nicholas A., Webster, John, Weedon, Michael N., Wilson, Anthony G., Woodburn, Matthew, Wordsworth, B. Paul, Yau, Chris, Young, Allan H., Zeggini, Eleftheria, Brown, Matthew A., Burton, Paul R., Caulfield, Mark J., Compston, Alastair, Farrall, Martin, Gough, Stephen C.L., Hall, Alistair S., Hattersley, Andrew T., Hill, Adrian V.S., Mathew, Christopher G., Pembrey, Marcus, Satsangi, Jack, Stratton, Michael R., Worthington, Jane, Hurles, Matthew E., Duncanson, Audrey, Ouwehand, Willem H., Parkes, Miles, Rahman, Nazneen, Todd, John A., Samani, Nilesh J., Kwiatkowski, Dominic P., McCarthy, Mark I., Craddock, Nick, Deloukas, Panos, Donnelly, Peter, Blackwell, Jenefer M., Bramon, Elvira, Casas, Juan P., Corvin, Aiden, Jankowski, Janusz, Markus, Hugh S., Palmer, Colin N.A., Plomin, Robert, Rautanen, Anna, Trembath, Richard C., Viswanathan, Ananth C., Wood, Nicholas W., Spencer, Chris C.A., Band, Gavin, Bellenguez, Céline, Freeman, Colin, Hellenthal, Garrett, Pirinen, Matti, Strange, Amy, Blackburn, Hannah, Bumpstead, Suzannah J., Dronov, Serge, Gillman, Matthew, Jayakumar, Alagurevathi, McCann, Owen T., Liddle, Jennifer, Potter, Simon C., Ravindrarajah, Radhi, Ricketts, Michelle, Waller, Matthew, Weston, Paul, Widaa, Sara, Whittaker, Pamela, Bodea, Corneliu A., Neale, Benjamin M., Ripke, Stephan, Devlin, Bernie, and Roeder, Kathryn

Published
2016
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16. Pre-treatment calprotectin (MRP8/14) provides no added value to testing CRP alone in terms of predicting response to TNF inhibitors in rheumatoid arthritis in a post hoc analysis

Author

Smith, Samantha Louise, primary, Alexander, Sheree, additional, Nair, Nisha, additional, Viatte, Sebastien, additional, Eyre, Stephen, additional, Hyrich, Kimme L, additional, Morgan, Ann W, additional, Wilson, Anthony G, additional, Isaacs, John D, additional, Plant, Darren, additional, and Barton, Anne, additional

Published
2023
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23. Pre-defined gene co-expression modules in rheumatoid arthritis transition towards molecular health following anti-TNF therapy

Author

Sutcliffe, Megan, primary, Nair, Nisha, additional, Oliver, James, additional, Morgan, Ann W, additional, Isaacs, John D, additional, Wilson, Anthony G, additional, Verstappen, Suzanne M M, additional, Viatte, Sebastien, additional, Hyrich, Kimme L, additional, Morris, Andrew P, additional, Barton, Anne, additional, and Plant, Darren, additional

Published
2022
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25. HLA-B*27 is associated with CNO in a European cohort.

Author

O'Leary, Daire, Al Julandani, Dalila Ali, Zia, Muhammad, Klotsche, Jens, Minden, Kirsten, Roderick, Marion, Ramanan, Athimalaipet V., Killeen, Orla G., and Wilson, Anthony G.

Subjects
FIXED effects model, INFLAMMATORY bowel diseases, FISHER exact test, COMBINED ratio, ODDS ratio
Abstract

Objectives: To determine the influence of HLA-B27 positivity on risk of developing chronic nonbacterial osteomyelitis (CNO). Methods: HLA-B*27 genotype was assessed in 3 European CNO populations and compared with local control populations (572 cases, 33,256 controls). Regional or whole-body MRI was performed at diagnosis and follow-up in all cases which reduces the risk of disease misclassification. Genotyping was performed using either next generation DNA sequencing or PCR based molecular typing. Statistical analysis used Fisher's exact test with Bonferroni correction and a fixed effects model for meta-analysis of odds ratios. Results: HLA-B*27 frequency was higher in all 3 populations compared with local controls (combined odds ratio (OR) = 2.2, p-value = 3 × 10–11). This association was much stronger in male compared with female cases (OR = 1.99, corrected p-value = 0.015). However, the HLA-B*27 status was not statistically significantly associated with co-occurrence of psoriasis, arthritis or inflammatory bowel disease. Conclusion: Carriage of HLA-B*27 is associated with greater risk of developing CNO, particularly in male cases. [ABSTRACT FROM AUTHOR]

Published
2023
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26. Non-trough adalimumab and certolizumab drug levels associated with a therapeutic EULAR response in adherent patients with rheumatoid arthritis.

Author

Hum, Ryan M, Ho, Pauline, Nair, Nisha, Jani, Meghna, Morgan, Ann W, Isaacs, John D, Wilson, Anthony G, Hyrich, Kimme L, Plant, Darren, Barton, Anne, and Collaborators, the BRAGGSS

Subjects
SCIENTIFIC observation, CONFIDENCE intervals, TIME, SELF-evaluation, CERTOLIZUMAB pegol, RHEUMATOID arthritis, DRUG monitoring, DRUGS, TUMOR necrosis factors, RESEARCH funding, DESCRIPTIVE statistics, ADALIMUMAB, PATIENT compliance, RECEIVER operating characteristic curves, SENSITIVITY & specificity (Statistics), DATA analysis software, LONGITUDINAL method, CHEMICAL inhibitors
Abstract

Objectives Interventions aimed at increasing TNF-α inhibitor serum drug levels (SDLs) may improve treatment response; however, previous studies suggesting SDL cut-offs have not accounted for treatment adherence. The aim of this study was to establish the relationship between adalimumab/certolizumab SDLs and EULAR good vs non-/moderate response and to define SDL cut-offs associated with good response in fully adherent patients. Methods In a prospective observational study, 475 patients with RA were treated with certolizumab (n  = 192) or adalimumab (n  = 283). At baseline and 3, 6 and 12 months, patients had 28-joint DAS, self-reported treatment adherence and SDLs measured. Fully adherent patients were analysed as a subgroup. Follow-up data at 3, 6 and 12 months were analysed separately. Median SDLs were compared in good vs non-/moderate response patients and receiver operating characteristics (ROC) curves were used to establish cut-off SDLs. Results Fully adherent good responders had significantly higher median adalimumab/certolizumab SDLs compared with non-/moderate responders (P  = 0.04 and P  = 0.0005, respectively). ROC analysis reported 3 month non-trough adalimumab SDLs discriminated good vs non-/moderate response with an area under the curve (AUC) of 0.63 (95% CI 0.52, 0.75), with a cut-off of 7.5 mg/l being 39.1% specific and 80.9% sensitive. Similarly, 3 month non-trough certolizumab SDLs discriminated good vs non-/moderate response with an AUC of 0.65 (95% CI 0.51, 0.78), with a cut-off of 26.0 mg/l being 43.9% specific and 77.8% sensitive. Conclusion In fully adherent patients, higher SDLs are detected in good responders, suggesting that interventions to improve SDLs, such as encouraging adherence, could improve treatment response. The 3 month non-trough SDL cut-offs of 7.5 mg/l for adalimumab and 26.0 mg/l for certolizumab may be useful in clinical practice. [ABSTRACT FROM AUTHOR]

Published
2023
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27. Assessing the potential of epigenetic targets as biomarkers in the diagnosis and treatment of rheumatoid arthritis.

Author

Nair, Nisha and Wilson, Anthony G.

Subjects
RHEUMATOID arthritis diagnosis, BIOMARKERS, EPIGENETICS, DNA methylation, RHEUMATOID arthritis, HISTONE methylation
Abstract

Although there are gold-standard diagnostic guidelines and effective treatments to slow the disease progression of rheumatoid arthritis (RA), approximately 40% of patients still do not respond adequately to their initial treatment. The identification of specific and sensitive biomarkers for early and accurate diagnosis and response to treatment is a clinical priority and could reduce the time to effective therapy to mitigate the severity of tissue damage. Emerging studies show that epigenetic biomarkers play a role in RA-related pathways and are worthy targets that warrant further characterization. In this review, the current significant literature around epigenetic studies of RA will be discussed, specifically, DNA methylation and histone modifications, being the most extensively studied. The pitfalls of biomarker studies in RA and how to potentially overcome barriers to their clinical application will be discussed. Epigenetic studies have shed light on mechanisms that mediate RA pathogenesis and potential roles as biomarkers of diagnosis and treatment response in conjunction with other biomarkers. Although these biomarkers are informative, limitations lie in their ease of use in clinical management and the requirement to ensure that the data are robust in large and diverse populations. [ABSTRACT FROM AUTHOR]

Published
2023
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28. Non-Trough Adalimumab and Certolizumab Pegol Serum Drug Levels in Rheumatoid Arthritis Associated with a Therapeutic EULAR Response:&nbsp;Results from the Biologics in Rheumatoid Arthritis Genetics and Genomics Study Syndicate (BRAGGS) Cohort

Author

Hum, Ryan Malcolm, primary, Ho, Pauline, additional, Nair, Nisha, additional, Jani, Meghna, additional, Morgan, Ann W., additional, Isaacs, John D., additional, Wilson, Anthony G., additional, Hyrich, Kimme L., additional, Plant, Darren, additional, Barton, Anne, additional, and Collaborators, BRAGGSS, additional

Published
2022
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31. Clinical Utility of Random Anti–Tumor Necrosis Factor Drug–Level Testing and Measurement of Antidrug Antibodies on the Long-Term Treatment Response in Rheumatoid Arthritis

Author

Jani, Meghna, Chinoy, Hector, Warren, Richard B., Griffiths, Christopher E. M., Plant, Darren, Fu, Bo, Morgan, Ann W., Wilson, Anthony G., Isaacs, John D., Hyrich, Kimme L., Barton, Anne, Prouse, P. J., Moitra, R. K., Shawe, D. J., Nisar, M., Fairburn, K., Nixon, J., Barnes, T., Hui, M., Coady, D., Wright, D., Morley, C., Raftery, G., Bracewell, C., Bridges, M., Armstrong, D., Chuck, A. J., Hailwood, S., Kumar, N., Ashok, D., Reece, R., OʼReilly, S. C., Ding, T., Badcock, L. J., Deighton, C. M., Raj, N., Regan, M. R., Summers, G. D., Williams, R. A., Lambert, J. R., Stevens, R., Wilkinson, C., Kelly, C. A., Hamilton, J., Heycock, C. R., Saravanan, V., Cope, A., Garrood, T., Ng, N., Kirkham, B., Green, M., Gough, A., Lawson, C., Das, D., Borbas, E., Wazir, T., Emery, P., Bingham, S., Bird, H. A., Conaghan, P. G., Pease, C. T., Wakefield, R. J., Buch, M., Bruce, I., Gorodkin, R., Ho, P., Parker, B., Smith, W., Jenkins, E., Mukhtyar, C., Gaffney, K., Macgregor, A. J., Marshall, T., Merry, P., DeSilva, C., Birrell, F. N., Crook, P. R., Szebenyi, B., Bates, D., James, D., Gillott, T., Alvi, A., Grey, C., Browning, J., McHale, J. F., Gaywood, I. C., Jones, A. C., Lanyon, P., Pande, I., Doherty, M., Gupta, A., Courtney, P. A., Srikanth, A., Abhishek, A., Das, L., Pattrick, M., Snowden, H. N., Bowden, A. P., Smith, E. E., Klimiuk, P., Speden, D. J., Naz, S., Ledingham, J. M., Hull, R. G., McCrae, F., Cooper, A., Young-Min, S. A., Wong, E., Shaban, R., Woolf, A. D., Davis, M., Hutchinson, D., Endean, A., Mewar, D., Tunn, E. J., Nelson, K., Kennedy, T. D., Dubois, C., Pauling, J., Korendowych, E., Jenkinson, T., Sengupta, R., Bhalla, A., McHugh, N., OʼNeil, T., Herrick, A. L., Jones, A. K., Cooper, R. G., Dixon, W. G., Harrison, B., Buckley, C. D., Carruthers, D. C., Elamanchi, R., Gordon, P. C., Grindulis, K. A., Khattak, F., Raza, K., Situnayake, K., Akil, M., Till, S., Dunkley, L., Tattersall, R., Kilding, R., Tait, T., Maxwell, J., Kuet, K.-P., Plant, M. J., Clarke, F., Fordham, J. N., Tuck, S., Pathare, S. K., Paul, A., Marguerie, C. P., Rigby, S. P., Dunn, N., Abbas, I., Filer, C., Abernethy, V. E., Clewes, A. R., Dawson, J. K., Kitas, G., Erb, N., Klocke, R., Whallett, A. J., Douglas, K., Pace, A., Sandhu, R., John, H., Shand, L., Lane, S., Foster, H., Griffiths, B., Griffiths, I., Kay, L., Ng, W.-F., Platt, P. N., Walker, D. J., Peterson, P., Lorenzi, A., Friswell, M., Thompson, B., Lee, M., Pratt, A., Hopkinson, N. D., Dunne, C. A., Quilty, B., Marks, J., Mukherjee, S., Mulherin, D., Chalam, S. V., Price, T., Sheeran, T., Venkatachalam, S., Baskar, S., Al-Allaf, W., McKenna, F., Shah, P., Filer, A., Bowman, S. J., Jobanputra, P., Rankin, E. C., Allen, M., Chaudhuri, K., Dubey, S., Price-Forbes, A., Ravindran, J., Samanta, A., Sheldon, P., Hassan, W., Francis, J., Kinder, A., Neame, R., Moorthy, A., Bukhari, M., Ottewell, L., Palkonyai, E., Hider, S., Hassell, A., Menon, A., Dowson, C., Kamath, S., Packham, J., Dutta, S., Price, S., Roddy, E., Paskins, Z., OʼReilly, D. T., Rajagopal, V., Bhagat, S., Chattopadhyay, C. B., Quinn, D., Isdale, A., Brown, A., Saleem, B., Foo, B., Al Saffar, Z., and Koduri, G.

Published
2015
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35. Evidence of NLRP3-inflammasome activation in rheumatoid arthritis (RA); genetic variants within the NLRP3-inflammasome complex in relation to susceptibility to RA and response to anti-TNF treatment

Author

Mathews, Rebeccah J, Robinson, James I, Battellino, Michele, Wong, Chi, Taylor, John C, Eyre, Steve, Churchman, Sarah M, Wilson, Anthony G, Isaacs, John D, Hyrich, Kimme, Barton, Anne, Plant, Darren, Savic, Sinisa, Cook, Graham P, Sarzi-Puttini, Piercarlo, Emery, Paul, Barrett, Jennifer H, Morgan, Ann W, and McDermott, Michael F

Published
2014
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36. Testing the role of vitamin D in response to antitumour necrosis factor α therapy in a UK cohort: a Mendelian randomisation approach

Author

Yarwood, Annie, Viatte, Sebastien, Plant, Darren, Morgan, Ann W, Isaacs, John, Wilson, Anthony G, Hyrich, Kimme, Eyre, Steve, Barton, Anne, Gaston, H, Mulherin, D, Price, T, Sheeran, T, Chalam, V, Baskar, S, Emery, P, Morgan, A W, Buch, M, Bingham, S, O’Reilly, S, Badcock, L, Regan, M, Ding, T, Deighton, C, Summers, G, Raj, N, Stevens, R, Williams, N, Isaacs, J, Platt, P, Walker, D, Kay, L, Griffiths, B, Ng, W-F, Peterson, P, Lorenzi, A, Foster, H, Friswell, M, Thompson, B, Lee, M, Griffiths, I, Hassell, A, Dawes, P, Dowson, C, Kamath, S, Packham, J, Shadforth, M, Williams, R, Mukhtyar, C, Harrison, B, Snowden, N, Naz, S, Ledingham, J, Hull, R, McCrae, F, Thomas, A, Young Min, S, Shaban, R, Wong, E, Kelly, C, Heycock, C, Hamilton, J, Saravanan, V, Wilson, G, Bax, D, Dunkley, L, Akil, M, Tattersall, R, Kilding, R, Till, S, Boulton, J, Tait, T, Bukhari, M, Halsey, J, Ottewell, L, Buckley, C, Situnayake, D, Carruthers, D, Grindulis, K, Khatack, F, Elamanchi, S, Raza, K, Filer, A, Jubb, R, Abernathy, R, Plant, M, Pathare, S, Clarke, F, Tuck, S, Fordham, J, Paul, A, Bridges, M, Hakim, A, O’Reilly, D, Rajagopal, V, Bhagat, S, Edwards, C, Prouse, P, Moitra, R, Shawe, D, Bamji, A, Klimiuk, P, Bowden, A, Mitchell, W, Bruce, I, Barton, A, Gorodkin, R, Ho, P, Hyrich, K, Dixon, W, Rai, A, Kitas, G, Erb, N, Klocke, R, Douglas, K, Pace, A, Sandhu, R, Whallett, A, Birrell, F, Allen, M, Chaudhuri, K, Chattopadhyay, C, McHale, J, Jones, A, Gupta, A, Pande, I, Gaywood, I, Lanyon, P, Courtney, P, Doherty, M, Chinoy, H, O’Neill, T, Herrick, A, Jones, A, Cooper, R, Bucknall, R, Marguerie, C, Rigby, S, Dunn, N, Green, S, Al-Ansari, A, Webber, S, Hopkinson, N, Dunne, C, Quilty, B, Szebenyi, B, Green, M, Quinn, M, Isdale, A, Brown, A, Saleem, B, Samanta, A, Sheldon, P, Hassan, W, Francis, J, Kinder, A, Neame, R, Moorthy, A, Al-Allaf, W, Taggart, A, Fairburn, K, McKenna, F, Green, M, Gough, A, Lawson, C, Piper, M, Korendowych, E, Jenkinson, T, Sengupta, R, Bhalla, A, McHugh, N, Bond, Debbie, Luqmani, R, Bowness, B, Wordsworth, P, David, J, Smith, W, Mewar, D, Tunn, E, Nelson, K, Kennedy, T, Nixon, J, Woolf, A, Davis, M, Hutchinson, D, Endean, A, Coady, D, Wright, D, Morley, C, Raftery, G, Bracewell, C, Kidd, L, Abbas, I, Filer, C, and Kallarackal, G

Published
2014
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37. Additional file 1 of Transcriptome-wide study of TNF-inhibitor therapy in rheumatoid arthritis reveals early signature of successful treatment

Author

Oliver, James, Nair, Nisha, Orozco, Gisela, Smith, Samantha, Kimme L. Hyrich, Morgan, Ann, Isaacs, John, Wilson, Anthony G., Barton, Anne, and Plant, Darren

Subjects
parasitic diseases, skin and connective tissue diseases
Abstract

Additional file 1: Table S1. Differentially expressed transcripts in adalimumab good-responders between baseline (pre-treatment) and 3-months of adalimumab treatment. The annotation for each probe was retrieved from the Affymetrix array manifest [MacDonald JW (2017). pd.hta.2.0: Platform Design Info for Affymetrix HTA-2_0. R package version 3.12.2]. Transcripts with a positive fold-change exhibited increased expression at 3-months compared to baseline. Transcripts with a negative fold-change exhibited reduced expression at 3-months compared to baseline.

Published
2021
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38. Additional file 3 of Transcriptome-wide study of TNF-inhibitor therapy in rheumatoid arthritis reveals early signature of successful treatment

Author

Oliver, James, Nair, Nisha, Orozco, Gisela, Smith, Samantha, Kimme L. Hyrich, Morgan, Ann, Isaacs, John, Wilson, Anthony G., Barton, Anne, and Plant, Darren

Subjects
sense organs, skin and connective tissue diseases
Abstract

Additional file 3: Figure S1. Correlation between change in transcript expression level and change in DAS28 score in good responders for the top 10 differentially expressed transcripts according to p-value. Figure S2. Correlation between change in transcript expression level and change in swollen joint count (SJC) in good responders for the top 10 differentially expressed transcripts according to p-value. Figure S3. Correlation between change in transcript expression level and change in tender joint count (TJC) in good responders for the top 10 differentially expressed transcripts according to p-value. Figure S4. Correlation between change in transcript expression level and change in C-reactive protein (CRP) levels in good responders for the top 10 differentially expressed transcripts according to p-value.

Published
2021
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39. Additional file 2 of Transcriptome-wide study of TNF-inhibitor therapy in rheumatoid arthritis reveals early signature of successful treatment

Author

OIiver, James, Nair, Nisha, Orozco, Gisela, Smith, Samantha, Kimme L. Hyrich, Morgan, Ann, Isaacs, John, Wilson, Anthony G., Barton, Anne, and Plant, Darren

Abstract

Additional file 2: Table S2. The differentially expressed genes in adalimumab good-responders (baseline versus 3-months) as analysed using Ingenuity Pathway Analysis (IPA) software. The -log(p-value) for each pathway association, the ratio of the number of differentially expressed genes within each pathway, and a list of the differentially expressed genes (molecules) within each pathway are shown.

Published
2021
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