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Zhang F, Jonsson AH, Nathan A, Millard N, Curtis M, Xiao Q, Gutierrez-Arcelus M, Apruzzese W, Watts GFM, Weisenfeld D, Nayar S, Rangel-Moreno J, Meednu N, Marks KE, Mantel I, Kang JB, Rumker L, Mears J, Slowikowski K, Weinand K, Orange DE, Geraldino-Pardilla L, Deane KD, Tabechian D, Ceponis A, Firestein GS, Maybury M, Sahbudin I, Ben-Artzi A, Mandelin AM, Nerviani A, Lewis MJ, Rivellese F, Pitzalis C, Hughes LB, Horowitz D, DiCarlo E, Gravallese EM, Boyce BF, Moreland LW, Goodman SM, Perlman H, Holers VM, Liao KP, Filer A, Bykerk VP, Wei K, Rao DA, Donlin LT, Anolik JH, Brenner MB, Raychaudhuri S. Deconstruction of rheumatoid arthritis synovium defines inflammatory subtypes. Nature 2023; 623:616-624. [PMID: 37938773 PMCID: PMC10651487 DOI: 10.1038/s41586-023-06708-y] [Citation(s) in RCA: 33] [Impact Index Per Article: 33.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2022] [Accepted: 10/03/2023] [Indexed: 11/09/2023]
Abstract
Rheumatoid arthritis is a prototypical autoimmune disease that causes joint inflammation and destruction1. There is currently no cure for rheumatoid arthritis, and the effectiveness of treatments varies across patients, suggesting an undefined pathogenic diversity1,2. Here, to deconstruct the cell states and pathways that characterize this pathogenic heterogeneity, we profiled the full spectrum of cells in inflamed synovium from patients with rheumatoid arthritis. We used multi-modal single-cell RNA-sequencing and surface protein data coupled with histology of synovial tissue from 79 donors to build single-cell atlas of rheumatoid arthritis synovial tissue that includes more than 314,000 cells. We stratified tissues into six groups, referred to as cell-type abundance phenotypes (CTAPs), each characterized by selectively enriched cell states. These CTAPs demonstrate the diversity of synovial inflammation in rheumatoid arthritis, ranging from samples enriched for T and B cells to those largely lacking lymphocytes. Disease-relevant cell states, cytokines, risk genes, histology and serology metrics are associated with particular CTAPs. CTAPs are dynamic and can predict treatment response, highlighting the clinical utility of classifying rheumatoid arthritis synovial phenotypes. This comprehensive atlas and molecular, tissue-based stratification of rheumatoid arthritis synovial tissue reveal new insights into rheumatoid arthritis pathology and heterogeneity that could inform novel targeted treatments.
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Affiliation(s)
- Fan Zhang
- Division of Rheumatology, Inflammation and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Center for Data Sciences, Brigham and Women's Hospital, Boston, MA, USA
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Rheumatology and the Center for Health Artificial Intelligence, University of Colorado School of Medicine, Aurora, CO, USA
| | - Anna Helena Jonsson
- Division of Rheumatology, Inflammation and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Division of Rheumatology, University of Colorado School of Medicine, Aurora, CO, USA
| | - Aparna Nathan
- Division of Rheumatology, Inflammation and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Center for Data Sciences, Brigham and Women's Hospital, Boston, MA, USA
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Nghia Millard
- Division of Rheumatology, Inflammation and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Center for Data Sciences, Brigham and Women's Hospital, Boston, MA, USA
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Michelle Curtis
- Division of Rheumatology, Inflammation and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Center for Data Sciences, Brigham and Women's Hospital, Boston, MA, USA
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Qian Xiao
- Division of Rheumatology, Inflammation and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Center for Data Sciences, Brigham and Women's Hospital, Boston, MA, USA
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Maria Gutierrez-Arcelus
- Division of Rheumatology, Inflammation and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Center for Data Sciences, Brigham and Women's Hospital, Boston, MA, USA
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Immunology, Department of Pediatrics, Boston Children's Hospital and Harvard Medical School, Boston, MA, USA
| | - William Apruzzese
- Accelerating Medicines Partnership Program: Rheumatoid Arthritis and Systemic Lupus Erythematosus (AMP RA/SLE) Network, Bethesda, MD, USA
| | - Gerald F M Watts
- Division of Rheumatology, Inflammation and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Dana Weisenfeld
- Division of Rheumatology, Inflammation and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Saba Nayar
- Rheumatology Research Group, Institute for Inflammation and Ageing, University of Birmingham, Birmingham, UK
- Birmingham Tissue Analytics, Institute of Translational Medicine, University of Birmingham, Birmingham, UK
| | - Javier Rangel-Moreno
- Division of Allergy, Immunology and Rheumatology, Department of Medicine, University of Rochester Medical Center, Rochester, NY, USA
| | - Nida Meednu
- Division of Allergy, Immunology and Rheumatology, Department of Medicine, University of Rochester Medical Center, Rochester, NY, USA
| | - Kathryne E Marks
- Division of Rheumatology, Inflammation and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Ian Mantel
- Hospital for Special Surgery, New York, NY, USA
- Weill Cornell Medicine, New York, NY, USA
| | - Joyce B Kang
- Division of Rheumatology, Inflammation and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Center for Data Sciences, Brigham and Women's Hospital, Boston, MA, USA
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Laurie Rumker
- Division of Rheumatology, Inflammation and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Center for Data Sciences, Brigham and Women's Hospital, Boston, MA, USA
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Joseph Mears
- Division of Rheumatology, Inflammation and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Center for Data Sciences, Brigham and Women's Hospital, Boston, MA, USA
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Kamil Slowikowski
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Immunology and Inflammatory Diseases, Department of Medicine, Massachusetts General Hospital (MGH), Boston, MA, USA
| | - Kathryn Weinand
- Division of Rheumatology, Inflammation and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Center for Data Sciences, Brigham and Women's Hospital, Boston, MA, USA
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Dana E Orange
- Hospital for Special Surgery, New York, NY, USA
- Laboratory of Molecular Neuro-Oncology, The Rockefeller University, New York, NY, USA
| | - Laura Geraldino-Pardilla
- Division of Rheumatology, Columbia University College of Physicians and Surgeons, New York, NY, USA
| | - Kevin D Deane
- Division of Rheumatology, University of Colorado School of Medicine, Aurora, CO, USA
| | - Darren Tabechian
- Division of Allergy, Immunology and Rheumatology, Department of Medicine, University of Rochester Medical Center, Rochester, NY, USA
| | - Arnoldas Ceponis
- Division of Rheumatology, Allergy and Immunology, University of California, San Diego, La Jolla, CA, USA
| | - Gary S Firestein
- Division of Rheumatology, Allergy and Immunology, University of California, San Diego, La Jolla, CA, USA
| | - Mark Maybury
- Rheumatology Research Group, Institute for Inflammation and Ageing, University of Birmingham, Birmingham, UK
- NIHR Birmingham Biomedical Research Center and Clinical Research Facility, University of Birmingham, Queen Elizabeth Hospital, Birmingham, UK
| | - Ilfita Sahbudin
- Rheumatology Research Group, Institute for Inflammation and Ageing, University of Birmingham, Birmingham, UK
- NIHR Birmingham Biomedical Research Center and Clinical Research Facility, University of Birmingham, Queen Elizabeth Hospital, Birmingham, UK
| | - Ami Ben-Artzi
- Division of Rheumatology, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Arthur M Mandelin
- Division of Rheumatology, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Alessandra Nerviani
- Centre for Experimental Medicine and Rheumatology, EULAR Centre of Excellence, William Harvey Research Institute, Queen Mary University of London, London, UK
- Barts Health NHS Trust, Barts Biomedical Research Centre (BRC), National Institute for Health and Care Research (NIHR), London, UK
| | - Myles J Lewis
- Centre for Experimental Medicine and Rheumatology, EULAR Centre of Excellence, William Harvey Research Institute, Queen Mary University of London, London, UK
- Barts Health NHS Trust, Barts Biomedical Research Centre (BRC), National Institute for Health and Care Research (NIHR), London, UK
| | - Felice Rivellese
- Centre for Experimental Medicine and Rheumatology, EULAR Centre of Excellence, William Harvey Research Institute, Queen Mary University of London, London, UK
- Barts Health NHS Trust, Barts Biomedical Research Centre (BRC), National Institute for Health and Care Research (NIHR), London, UK
| | - Costantino Pitzalis
- Centre for Experimental Medicine and Rheumatology, EULAR Centre of Excellence, William Harvey Research Institute, Queen Mary University of London, London, UK
- Barts Health NHS Trust, Barts Biomedical Research Centre (BRC), National Institute for Health and Care Research (NIHR), London, UK
- Department of Biomedical Sciences, Humanitas University and Humanitas Research Hospital, Milan, Italy
| | - Laura B Hughes
- Division of Clinical Immunology and Rheumatology, Department of Medicine, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Diane Horowitz
- Feinstein Institute for Medical Research, Northwell Health, Manhasset, New York, NY, USA
| | - Edward DiCarlo
- Department of Pathology and Laboratory Medicine, Hospital for Special Surgery, New York, NY, USA
| | - Ellen M Gravallese
- Division of Rheumatology, Inflammation and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Brendan F Boyce
- Department of Pathology and Laboratory Medicine, University of Rochester Medical Center, Rochester, NY, USA
| | - Larry W Moreland
- Division of Rheumatology, University of Colorado School of Medicine, Aurora, CO, USA
- Division of Rheumatology and Clinical Immunology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Susan M Goodman
- Hospital for Special Surgery, New York, NY, USA
- Weill Cornell Medicine, New York, NY, USA
| | - Harris Perlman
- Division of Rheumatology, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - V Michael Holers
- Division of Rheumatology, University of Colorado School of Medicine, Aurora, CO, USA
| | - Katherine P Liao
- Division of Rheumatology, Inflammation and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Andrew Filer
- Rheumatology Research Group, Institute for Inflammation and Ageing, University of Birmingham, Birmingham, UK
- Birmingham Tissue Analytics, Institute of Translational Medicine, University of Birmingham, Birmingham, UK
- NIHR Birmingham Biomedical Research Center and Clinical Research Facility, University of Birmingham, Queen Elizabeth Hospital, Birmingham, UK
| | - Vivian P Bykerk
- Hospital for Special Surgery, New York, NY, USA
- Weill Cornell Medicine, New York, NY, USA
| | - Kevin Wei
- Division of Rheumatology, Inflammation and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Deepak A Rao
- Division of Rheumatology, Inflammation and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Laura T Donlin
- Hospital for Special Surgery, New York, NY, USA
- Weill Cornell Medicine, New York, NY, USA
| | - Jennifer H Anolik
- Division of Allergy, Immunology and Rheumatology, Department of Medicine, University of Rochester Medical Center, Rochester, NY, USA
| | - Michael B Brenner
- Division of Rheumatology, Inflammation and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Soumya Raychaudhuri
- Division of Rheumatology, Inflammation and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
- Center for Data Sciences, Brigham and Women's Hospital, Boston, MA, USA.
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.
- Broad Institute of MIT and Harvard, Cambridge, MA, USA.
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Roodenrijs NMT, Welsing PMJ, van Roon J, Schoneveld JLM, van der Goes MC, Nagy G, Townsend MJ, van Laar JM. Mechanisms underlying DMARD inefficacy in difficult-to-treat rheumatoid arthritis: a narrative review with systematic literature search. Rheumatology (Oxford) 2022; 61:3552-3566. [PMID: 35238332 PMCID: PMC9434144 DOI: 10.1093/rheumatology/keac114] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2021] [Revised: 02/07/2022] [Accepted: 02/14/2022] [Indexed: 12/03/2022] Open
Abstract
Management of RA patients has significantly improved over the past decades. However, a substantial proportion of patients is difficult-to-treat (D2T), remaining symptomatic after failing biological and/or targeted synthetic DMARDs. Multiple factors can contribute to D2T RA, including treatment non-adherence, comorbidities and co-existing mimicking diseases (e.g. fibromyalgia). Additionally, currently available biological and/or targeted synthetic DMARDs may be truly ineffective (‘true’ refractory RA) and/or lead to unacceptable side effects. In this narrative review based on a systematic literature search, an overview of underlying (immune) mechanisms is presented. Potential scenarios are discussed including the influence of different levels of gene expression and clinical characteristics. Although the exact underlying mechanisms remain largely unknown, the heterogeneity between individual patients supports the assumption that D2T RA is a syndrome involving different pathogenic mechanisms.
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Affiliation(s)
- Nadia M T Roodenrijs
- Department of Rheumatology & Clinical Immunology, University Medical Center Utrecht, Utrecht University, the Netherlands
| | - Paco M J Welsing
- Department of Rheumatology & Clinical Immunology, University Medical Center Utrecht, Utrecht University, the Netherlands
| | - Joel van Roon
- Department of Rheumatology & Clinical Immunology, University Medical Center Utrecht, Utrecht University, the Netherlands
| | - Jan L M Schoneveld
- Department of Rheumatology, Bravis Hospital, Roosendaal, the Netherlands
| | - Marlies C van der Goes
- Department of Rheumatology & Clinical Immunology, University Medical Center Utrecht, Utrecht University, the Netherlands.,Department of Rheumatology, Meander Medical Center, Amersfoort, the Netherlands
| | - György Nagy
- Department of Rheumatology & Clinical Immunology, Semmelweis University, Budapest, Hungary.,Department of Genetics, Cell and Immunobiology, Semmelweis University, Budapest, Hungary
| | - Michael J Townsend
- Biomarker Discovery OMNI, Genentech Research & Early Development, South San Francisco, USA
| | - Jacob M van Laar
- Department of Rheumatology & Clinical Immunology, University Medical Center Utrecht, Utrecht University, the Netherlands
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Oliver J, Nair N, Orozco G, Smith S, Hyrich KL, Morgan A, Isaacs J, Wilson AG, Barton A, Plant D. Transcriptome-wide study of TNF-inhibitor therapy in rheumatoid arthritis reveals early signature of successful treatment. Arthritis Res Ther 2021; 23:80. [PMID: 33691749 PMCID: PMC7948368 DOI: 10.1186/s13075-021-02451-9] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2020] [Accepted: 02/11/2021] [Indexed: 12/11/2022] Open
Abstract
BACKGROUND Despite the success of TNF-inhibitor therapy in rheumatoid arthritis treatment, up to 40% of patients fail to respond adequately. This study aimed to identify transcriptome-based biomarkers of adalimumab response in rheumatoid arthritis (RA) to aid timely switching in non-responder patients and provide a better mechanistic understanding of the pathways involved in response/non-response. METHODS The Affymetrix Human Transcriptome Array 2.0 (HTA) was used to measure the transcriptome in whole blood at pre-treatment and at 3 months in EULAR good- and non-responders to adalimumab therapy. Differential expression of transcripts was analysed at the transcript level using multiple linear regression. Differentially expressed genes were validated in independent samples using OpenArray™ RT-qPCR. RESULTS In total, 813 transcripts were differentially expressed between pre-treatment and 3 months in adalimumab good-responders. No significant differential expression was observed between good- and non-responders at either time-point and no significant changes were observed in non-responders between time-points. OpenArray™ RT-qPCR was performed for 104 differentially expressed transcripts in good-responders, selected based on magnitude of effect or p value or based on prior association with RA or the immune system, validating differential expression for 17 transcripts. CONCLUSIONS An early transcriptome signature of DAS28 response to adalimumab has been identified and replicated in independent datasets. Whilst treat-to-target approaches encourage early switching in non-responsive patients, registry evidence suggests that this does not always occur. The results herein could guide the development of a blood test to distinguish responders from non-responders at 3 months and support clinical decisions to switch non-responsive patients to an alternative therapy.
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Affiliation(s)
- James Oliver
- Versus Arthritis Centre for Genetics and Genomics, Centre for Musculoskeletal Research, Manchester Academic Health Sciences Centre, The University of Manchester, Manchester, UK
| | - Nisha Nair
- Versus Arthritis Centre for Genetics and Genomics, Centre for Musculoskeletal Research, Manchester Academic Health Sciences Centre, The University of Manchester, Manchester, UK
| | - Gisela Orozco
- Versus Arthritis Centre for Genetics and Genomics, Centre for Musculoskeletal Research, Manchester Academic Health Sciences Centre, The University of Manchester, Manchester, UK
| | - Samantha Smith
- Versus Arthritis Centre for Genetics and Genomics, Centre for Musculoskeletal Research, Manchester Academic Health Sciences Centre, The University of Manchester, Manchester, UK
| | - Kimme L Hyrich
- NIHR Manchester BRC, Manchester University Foundation Trust, Manchester, UK
- Versus Arthritis Centre for Epidemiology, Centre for Musculoskeletal Research, Manchester Academic Health Sciences Centre, The University of Manchester, Manchester, UK
| | - Ann Morgan
- Leeds Institute of Rheumatic and Musculoskeletal Medicine, University of Leeds and NIHR Leeds Musculoskeletal Biomedical Research Unit, Leeds Teaching Hospitals NHS Trust, Leeds, UK
| | - John Isaacs
- Institute of Cellular Medicine, Newcastle University, Newcastle upon Tyne, UK
- National Institute for Health Research Newcastle Biomedical Research Centre at Newcastle upon Tyne Hospitals NHS Foundation Trust and Newcastle University, Newcastle upon Tyne, UK
| | - Anthony G Wilson
- UCD School of Medicine and Medical Science, Conway Institute, University College Dublin, Dublin, Ireland
| | - Anne Barton
- Versus Arthritis Centre for Genetics and Genomics, Centre for Musculoskeletal Research, Manchester Academic Health Sciences Centre, The University of Manchester, Manchester, UK
- NIHR Manchester BRC, Manchester University Foundation Trust, Manchester, UK
| | - Darren Plant
- Versus Arthritis Centre for Genetics and Genomics, Centre for Musculoskeletal Research, Manchester Academic Health Sciences Centre, The University of Manchester, Manchester, UK.
- NIHR Manchester BRC, Manchester University Foundation Trust, Manchester, UK.
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Circulating Free DNA and Its Emerging Role in Autoimmune Diseases. J Pers Med 2021; 11:jpm11020151. [PMID: 33672659 PMCID: PMC7924199 DOI: 10.3390/jpm11020151] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2021] [Revised: 02/06/2021] [Accepted: 02/17/2021] [Indexed: 12/12/2022] Open
Abstract
Liquid biopsies can be used to analyse tissue-derived information, including cell-free DNA (cfDNA), circulating rare cells, and circulating extracellular vesicles in the blood or other bodily fluids, representing a new way to guide therapeutic decisions in cancer. Among the new challenges of liquid biopsy, we found clinical application in nontumour pathologies, including autoimmune diseases. Since the discovery of the presence of high levels of cfDNA in patients with systemic lupus erythaematosus (SLE) in the 1960s, cfDNA research in autoimmune diseases has mainly focused on the overall quantification of cfDNA and its association with disease activity. However, with technological advancements and the increasing understanding of the role of DNA sensing receptors in inflammation and autoimmunity, interest in cfDNA and autoimmune diseases has not expanded until recently. In this review, we provide an overview of the basic biology of cfDNA in the context of autoimmune diseases as a biomarker of disease activity, progression, and prediction of the treatment response. We discuss and integrate available information about these important aspects.
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Contribution of Multiplex Immunoassays to Rheumatoid Arthritis Management: From Biomarker Discovery to Personalized Medicine. J Pers Med 2020; 10:jpm10040202. [PMID: 33142977 PMCID: PMC7712300 DOI: 10.3390/jpm10040202] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2020] [Revised: 10/27/2020] [Accepted: 10/28/2020] [Indexed: 01/18/2023] Open
Abstract
Rheumatoid arthritis (RA) is a multifactorial, inflammatory and progressive autoimmune disease that affects approximately 1% of the population worldwide. RA primarily involves the joints and causes local inflammation and cartilage destruction. Immediate and effective therapies are crucial to control inflammation and prevent deterioration, functional disability and unfavourable progression in RA patients. Thus, early diagnosis is critical to prevent joint damage and physical disability, increasing the chance of achieving remission. A large number of biomarkers have been investigated in RA, although only a few have made it through the discovery and validation phases and reached the clinic. The single biomarker approach mostly used in clinical laboratories is not sufficiently accurate due to its low sensitivity and specificity. Multiplex immunoassays could provide a more complete picture of the disease and the pathways involved. In this review, we discuss the latest proposed protein biomarkers and the advantages of using protein panels for the clinical management of RA. Simultaneous analysis of multiple proteins could yield biomarker signatures of RA subtypes to enable patients to benefit from personalized medicine.
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Latin American Genes: The Great Forgotten in Rheumatoid Arthritis. J Pers Med 2020; 10:jpm10040196. [PMID: 33114702 PMCID: PMC7711650 DOI: 10.3390/jpm10040196] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2020] [Revised: 10/19/2020] [Accepted: 10/24/2020] [Indexed: 11/28/2022] Open
Abstract
The successful implementation of personalized medicine will rely on the integration of information obtained at the level of populations with the specific biological, genetic, and clinical characteristics of an individual. However, because genome-wide association studies tend to focus on populations of European descent, there is a wide gap to bridge between Caucasian and non-Caucasian populations before personalized medicine can be fully implemented, and rheumatoid arthritis (RA) is not an exception. In this review, we discuss advances in our understanding of genetic determinants of RA risk among global populations, with a focus on the Latin American population. Geographically restricted genetic diversity may have important implications for health and disease that will remain unknown until genetic association studies have been extended to include Latin American and other currently under-represented ancestries. The next few years will witness many breakthroughs in personalized medicine, including applications for common diseases and risk stratification instruments for targeted prevention/intervention strategies. Not all of these applications may be extrapolated from the Caucasian experience to Latin American or other under-represented populations.
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Mikhaylenko DS, Nemtsova MV, Bure IV, Kuznetsova EB, Alekseeva EA, Tarasov VV, Lukashev AN, Beloukhova MI, Deviatkin AA, Zamyatnin AA. Genetic Polymorphisms Associated with Rheumatoid Arthritis Development and Antirheumatic Therapy Response. Int J Mol Sci 2020; 21:E4911. [PMID: 32664585 PMCID: PMC7402327 DOI: 10.3390/ijms21144911] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2020] [Revised: 07/08/2020] [Accepted: 07/09/2020] [Indexed: 12/11/2022] Open
Abstract
Rheumatoid arthritis (RA) is the most common inflammatory arthropathy worldwide. Possible manifestations of RA can be represented by a wide variability of symptoms, clinical forms, and course options. This multifactorial disease is triggered by a genetic predisposition and environmental factors. Both clinical and genealogical studies have demonstrated disease case accumulation in families. Revealing the impact of candidate gene missense variants on the disease course elucidates understanding of RA molecular pathogenesis. A multivariate genomewide association study (GWAS) based analysis identified the genes and signalling pathways involved in the pathogenesis of the disease. However, these identified RA candidate gene variants only explain 30% of familial disease cases. The genetic causes for a significant proportion of familial RA have not been determined until now. Therefore, it is important to identify RA risk groups in different populations, as well as the possible prognostic value of some genetic variants for disease development, progression, and treatment. Our review has two purposes. First, to summarise the data on RA candidate genes and the increased disease risk associated with these alleles in various populations. Second, to describe how the genetic variants can be used in the selection of drugs for the treatment of RA.
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Affiliation(s)
- Dmitry S. Mikhaylenko
- Institute of Molecular Medicine, Sechenov First Moscow State Medical University (Sechenov University), 119991 Moscow, Russia; (M.V.N.); (I.V.B.); (E.B.K.); (E.A.A.); (A.N.L.); (M.I.B.); (A.A.D.)
- Laboratory of Epigenetics, Research Centre for Medical Genetics, 115478 Moscow, Russia
| | - Marina V. Nemtsova
- Institute of Molecular Medicine, Sechenov First Moscow State Medical University (Sechenov University), 119991 Moscow, Russia; (M.V.N.); (I.V.B.); (E.B.K.); (E.A.A.); (A.N.L.); (M.I.B.); (A.A.D.)
- Laboratory of Epigenetics, Research Centre for Medical Genetics, 115478 Moscow, Russia
| | - Irina V. Bure
- Institute of Molecular Medicine, Sechenov First Moscow State Medical University (Sechenov University), 119991 Moscow, Russia; (M.V.N.); (I.V.B.); (E.B.K.); (E.A.A.); (A.N.L.); (M.I.B.); (A.A.D.)
| | - Ekaterina B. Kuznetsova
- Institute of Molecular Medicine, Sechenov First Moscow State Medical University (Sechenov University), 119991 Moscow, Russia; (M.V.N.); (I.V.B.); (E.B.K.); (E.A.A.); (A.N.L.); (M.I.B.); (A.A.D.)
- Laboratory of Epigenetics, Research Centre for Medical Genetics, 115478 Moscow, Russia
| | - Ekaterina A. Alekseeva
- Institute of Molecular Medicine, Sechenov First Moscow State Medical University (Sechenov University), 119991 Moscow, Russia; (M.V.N.); (I.V.B.); (E.B.K.); (E.A.A.); (A.N.L.); (M.I.B.); (A.A.D.)
- Laboratory of Epigenetics, Research Centre for Medical Genetics, 115478 Moscow, Russia
| | - Vadim V. Tarasov
- Department of Pharmacology and Pharmacy, Sechenov First Moscow State Medical University, 119991 Moscow, Russia;
| | - Alexander N. Lukashev
- Institute of Molecular Medicine, Sechenov First Moscow State Medical University (Sechenov University), 119991 Moscow, Russia; (M.V.N.); (I.V.B.); (E.B.K.); (E.A.A.); (A.N.L.); (M.I.B.); (A.A.D.)
- Martsinovsky Institute of Medical Parasitology, Tropical and Vector Borne Diseases, Sechenov First Moscow State Medical University, 119435 Moscow, Russia
| | - Marina I. Beloukhova
- Institute of Molecular Medicine, Sechenov First Moscow State Medical University (Sechenov University), 119991 Moscow, Russia; (M.V.N.); (I.V.B.); (E.B.K.); (E.A.A.); (A.N.L.); (M.I.B.); (A.A.D.)
| | - Andrei A. Deviatkin
- Institute of Molecular Medicine, Sechenov First Moscow State Medical University (Sechenov University), 119991 Moscow, Russia; (M.V.N.); (I.V.B.); (E.B.K.); (E.A.A.); (A.N.L.); (M.I.B.); (A.A.D.)
| | - Andrey A. Zamyatnin
- Institute of Molecular Medicine, Sechenov First Moscow State Medical University (Sechenov University), 119991 Moscow, Russia; (M.V.N.); (I.V.B.); (E.B.K.); (E.A.A.); (A.N.L.); (M.I.B.); (A.A.D.)
- Belozersky Institute of Physico-Chemical Biology, Lomonosov Moscow State University, 119992 Moscow, Russia
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8
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Guan Y, Zhang H, Quang D, Wang Z, Parker SCJ, Pappas DA, Kremer JM, Zhu F. Machine Learning to Predict Anti-Tumor Necrosis Factor Drug Responses of Rheumatoid Arthritis Patients by Integrating Clinical and Genetic Markers. Arthritis Rheumatol 2019; 71:1987-1996. [PMID: 31342661 DOI: 10.1002/art.41056] [Citation(s) in RCA: 73] [Impact Index Per Article: 14.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2018] [Accepted: 07/18/2019] [Indexed: 12/21/2022]
Abstract
OBJECTIVE Accurate prediction of treatment responses in rheumatoid arthritis (RA) patients can provide valuable information on effective drug selection. Anti-tumor necrosis factor (anti-TNF) drugs are an important second-line treatment after methotrexate, the classic first-line treatment for RA. However, patient heterogeneity hinders identification of predictive biomarkers and accurate modeling of anti-TNF drug responses. This study was undertaken to investigate the usefulness of machine learning to assist in developing predictive models for treatment response. METHODS Using data on patient demographics, baseline disease assessment, treatment, and single-nucleotide polymorphism (SNP) array from the Dialogue on Reverse Engineering Assessment and Methods (DREAM): Rheumatoid Arthritis Responder Challenge, we created a Gaussian process regression model to predict changes in the Disease Activity Score in 28 joints (DAS28) for the patients and to classify them into either the responder or the nonresponder group. This model was developed and cross-validated using data from 1,892 RA patients. It was evaluated using an independent data set from 680 patients. We examined the effectiveness of the similarity modeling and the contribution of individual features. RESULTS In the cross-validation tests, our method predicted changes in DAS28 (ΔDAS28), with a correlation coefficient of 0.405. It correctly classified responses from 78% of patients. In the independent test, this method achieved a Pearson's correlation coefficient of 0.393 in predicting ΔDAS28. Gaussian process regression effectively remapped the feature space and identified subpopulations that do not respond well to anti-TNF treatments. Genetic SNP biomarkers showed small contributions in the prediction when added to the clinical models. This was the best-performing model in the DREAM Challenge. CONCLUSION The model described here shows promise in guiding treatment decisions in clinical practice, based primarily on clinical profiles with additional genetic information.
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Affiliation(s)
| | | | | | | | | | - Dimitrios A Pappas
- Columbia University College of Physicians and Surgeons, New York, New York, and Corrona LLC, Waltham, Massachusetts
| | - Joel M Kremer
- Corrona LLC, Waltham, Massachusetts, and Albany Medical College and The Center for Rheumatology, Albany, New York
| | - Fan Zhu
- Chinese Academy of Sciences, Chongqing, China
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9
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Evaluation of 12 GWAS-drawn SNPs as biomarkers of rheumatoid arthritis response to TNF inhibitors. A potential SNP association with response to etanercept. PLoS One 2019; 14:e0213073. [PMID: 30818333 PMCID: PMC6395028 DOI: 10.1371/journal.pone.0213073] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2018] [Accepted: 02/14/2019] [Indexed: 12/14/2022] Open
Abstract
Research in rheumatoid arthritis (RA) is increasingly focused on the discovery of biomarkers that could enable personalized treatments. The genetic biomarkers associated with the response to TNF inhibitors (TNFi) are among the most studied. They include 12 SNPs exhibiting promising results in the three largest genome-wide association studies (GWAS). However, they still require further validation. With this aim, we assessed their association with response to TNFi in a replication study, and a meta-analysis summarizing all non-redundant data. The replication involved 755 patients with RA that were treated for the first time with a biologic drug, which was either infliximab (n = 397), etanercept (n = 155) or adalimumab (n = 203). Their DNA samples were successfully genotyped with a single-base extension multiplex method. Lamentably, none of the 12 SNPs was associated with response to the TNFi in the replication study (p > 0.05). However, a drug-stratified exploratory analysis revealed a significant association of the NUBPL rs2378945 SNP with a poor response to etanercept (B = -0.50, 95% CI = -0.82, -0.17, p = 0.003). In addition, the meta-analysis reinforced the previous association of three SNPs: rs2378945, rs12142623, and rs4651370. In contrast, five of the remaining SNPs were less associated than before, and the other four SNPs were no longer associated with the response to treatment. In summary, our results highlight the complexity of the pharmacogenetics of TNFi in RA showing that it could involve a drug-specific component and clarifying the status of the 12 GWAS-drawn SNPs.
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10
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Magill L, Adriani M, Berthou V, Chen K, Gleizes A, Hacein-Bey-Abina S, Hincelin-Mery A, Mariette X, Pallardy M, Spindeldreher S, Szely N, Isenberg DA, Manson JJ, Jury EC, Mauri C. Low Percentage of Signal Regulatory Protein α/β + Memory B Cells in Blood Predicts Development of Anti-drug Antibodies (ADA) in Adalimumab-Treated Rheumatoid Arthritis Patients. Front Immunol 2018; 9:2865. [PMID: 30568660 PMCID: PMC6290031 DOI: 10.3389/fimmu.2018.02865] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2018] [Accepted: 11/21/2018] [Indexed: 12/14/2022] Open
Abstract
An important goal for personalized treatment is predicting response to a particular therapeutic. A drawback of biological treatment is immunogenicity and the development of antibodies directed against the drug [anti-drug antibodies (ADA)], which are associated with a poorer clinical outcome. Here we set out to identify a predictive biomarker that discriminates rheumatoid arthritis (RA) patients who are more likely to develop ADA in response to adalimumab, a human monoclonal antibody against tumor necrosis factor (TNF)α. By taking advantage of an immune-phenotyping platform, LEGENDScreen™, we measured the expression of 332 cell surface markers on B and T cells in a cross-sectional adalimumab-treated RA patient cohort with a defined ADA response. The analysis revealed seven differentially expressed markers (DEMs) between the ADA+ and ADA− patients. Validation of the DEMs in an independent prospective European cohort of adalimumab treated RA patients, revealed a significant and consistent reduced frequency of signal regulatory protein (SIRP)α/β-expressing memory B cells in ADA+ vs. ADA− RA patients. We also assessed the predictive value of SIRPα/β expression in a longitudinal RA cohort prior to the initiation of adalimumab treatment. We show that a frequency of < 9.4% of SIRPα/β-expressing memory B cells predicts patients that will develop ADA, and consequentially fail to respond to treatment, with a receiver operating characteristic (ROC) area under the curve (AUC) score of 0.92. Thus, measuring the frequency of SIRPα/β-expressing memory B cells in patients prior to adalimumab treatment may be clinically useful to identify a subgroup of active RA subjects who are going to develop an ADA response and not gain substantial clinical benefit from this treatment.
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Affiliation(s)
- Laura Magill
- Division of Medicine, Centre for Rheumatology, University College London, London, United Kingdom
| | - Marsilio Adriani
- Division of Medicine, Centre for Rheumatology, University College London, London, United Kingdom
| | | | - Keguan Chen
- Clinical Immunology, GlaxoSmithKline, Philadelphia, PA, United States
| | - Aude Gleizes
- INSERM UMR996, Faculté Pharmacie, Université Paris Sud, Châtenay-Malabry, France.,Clinical Immunology Laboratory, AP-HP, Le Kremlin-Bicêtre Hospital, Paris-Sud University Hospitals, Le Kremlin-Bicêtre, France
| | - Salima Hacein-Bey-Abina
- Clinical Immunology Laboratory, AP-HP, Le Kremlin-Bicêtre Hospital, Paris-Sud University Hospitals, Le Kremlin-Bicêtre, France.,UTCBS, CNRS UMR 8258, INSERM U1022, Faculty of Pharmacy, Paris-Descartes-Sorbonne-Cité University, Paris, France
| | | | - Xavier Mariette
- Centre for Immunology of Viral Infections and Autoimmune Diseases, INSERM UMR1184, AP-HP, Université Paris-Sud, Hôpitaux Universitaires Paris-Sud, Le Krelin-Bicetre, France
| | - Marc Pallardy
- INSERM UMR996, Faculté Pharmacie, Université Paris Sud, Châtenay-Malabry, France
| | | | - Natacha Szely
- INSERM UMR996, Faculté Pharmacie, Université Paris Sud, Châtenay-Malabry, France
| | - David A Isenberg
- Division of Medicine, Centre for Rheumatology, University College London, London, United Kingdom
| | - Jessica J Manson
- Department of Rheumatology, University College London Hospital, London, United Kingdom
| | - Elizabeth C Jury
- Division of Medicine, Centre for Rheumatology, University College London, London, United Kingdom
| | - Claudia Mauri
- Division of Medicine, Centre for Rheumatology, University College London, London, United Kingdom
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11
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Lopez-Rodriguez R, Perez-Pampin E, Marquez A, Blanco FJ, Joven B, Carreira P, Ferrer MA, Caliz R, Valor L, Narvaez J, Cañete JD, Ordoñez MDC, Manrique-Arija S, Vasilopoulos Y, Balsa A, Pascual-Salcedo D, Moreno-Ramos MJ, Alegre-Sancho JJ, Navarro-Sarabia F, Moreira V, Garcia-Portales R, Raya E, Magro-Checa C, Martin J, Gomez-Reino JJ, Gonzalez A. Validation study of genetic biomarkers of response to TNF inhibitors in rheumatoid arthritis. PLoS One 2018; 13:e0196793. [PMID: 29734345 PMCID: PMC5937760 DOI: 10.1371/journal.pone.0196793] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2017] [Accepted: 04/19/2018] [Indexed: 11/19/2022] Open
Abstract
Genetic biomarkers are sought to personalize treatment of patients with rheumatoid arthritis (RA), given their variable response to TNF inhibitors (TNFi). However, no genetic biomaker is yet sufficiently validated. Here, we report a validation study of 18 previously reported genetic biomarkers, including 11 from GWAS of response to TNFi. The validation was attempted in 581 patients with RA that had not been treated with biologic antirheumatic drugs previously. Their response to TNFi was evaluated at 3, 6 and 12 months in two ways: change in the DAS28 measure of disease activity, and according to the EULAR criteria for response to antirheumatic drugs. Association of these parameters with the genotypes, obtained by PCR amplification followed by single-base extension, was tested with regression analysis. These analyses were adjusted for baseline DAS28, sex, and the specific TNFi. However, none of the proposed biomarkers was validated, as none showed association with response to TNFi in our study, even at the time of assessment and with the outcome that showed the most significant result in previous studies. These negative results are notable because this was the first independent validation study for 12 of the biomarkers, and because they indicate that prudence is needed in the interpretation of the proposed biomarkers of response to TNFi even when they are supported by very low p values. The results also emphasize the requirement of independent replication for validation, and the need to search protocols that could increase reproducibility of the biomarkers of response to TNFi.
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Affiliation(s)
- Rosario Lopez-Rodriguez
- Experimental and Observational Rheumatology and Rheumatology Unit, Instituto de Investigación Sanitaria, Hospital Clínico Universitario de Santiago, Santiago de Compostela, Spain
| | - Eva Perez-Pampin
- Experimental and Observational Rheumatology and Rheumatology Unit, Instituto de Investigación Sanitaria, Hospital Clínico Universitario de Santiago, Santiago de Compostela, Spain
| | - Ana Marquez
- Instituto de Parasitología y Biomedicina López-Neyra, CSIC, Granada, Spain
| | - Francisco J. Blanco
- Rheumatology Department, Instituto de Investigacion Biomedica–Complejo Hospitalario Universitario A Coruna, Coruna, Spain
| | | | | | - Miguel Angel Ferrer
- Rheumatology Unit, Hospital Universitario Virgen de las Nieves, Granada, Spain
| | - Rafael Caliz
- Rheumatology Unit, Hospital Universitario Virgen de las Nieves, Granada, Spain
| | - Lara Valor
- Rheumatology Unit, Hospital General Universitario Gregorio Marañón, Madrid, Spain
| | - Javier Narvaez
- Department of Rheumatology, Hospital Universitario de Bellvitge, Barcelona, Spain
| | - Juan D. Cañete
- Arthritis Unit, Rheumatology Dpt, Hospital Clinic and IDIBAPS, Barcelona, Spain
| | - Maria del Carmen Ordoñez
- Servicio de Reumatología, HRU Carlos Haya, Universidad de Málaga, Instituto de Investigación Biomédica de Málaga (IBIMA), Málaga Spain
| | - Sara Manrique-Arija
- Servicio de Reumatología, HRU Carlos Haya, Universidad de Málaga, Instituto de Investigación Biomédica de Málaga (IBIMA), Málaga Spain
| | - Yiannis Vasilopoulos
- Department of Biochemistry and Biotechnology, University of Thessaly, Larissa, Greece
| | - Alejandro Balsa
- Rheumatology Unit, Instituto de Investigación Sanitaria del Hospital Universitario La Paz (IdiPAZ), Hospital Universitario La Paz, Madrid, Spain
| | - Dora Pascual-Salcedo
- Department of Immunology, Instituto de Investigación Hospital Universitario La Paz (IdiPAZ), Madrid, Spain
| | | | | | | | - Virginia Moreira
- Rheumatology Unit, Hospital Universitario Virgen Macarena, Sevilla, Spain
| | | | - Enrique Raya
- Department of Rheumatology, Hospital Clínico San Cecilio, Granada, Spain
| | - Cesar Magro-Checa
- Department of Rheumatology, Hospital Clínico San Cecilio, Granada, Spain
- Department of Rheumatology, Leiden University Medical Center, Leiden, The Netherlands
| | - Javier Martin
- Instituto de Parasitología y Biomedicina López-Neyra, CSIC, Granada, Spain
| | - Juan J. Gomez-Reino
- Experimental and Observational Rheumatology and Rheumatology Unit, Instituto de Investigación Sanitaria, Hospital Clínico Universitario de Santiago, Santiago de Compostela, Spain
| | - Antonio Gonzalez
- Experimental and Observational Rheumatology and Rheumatology Unit, Instituto de Investigación Sanitaria, Hospital Clínico Universitario de Santiago, Santiago de Compostela, Spain
- * E-mail:
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12
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Smolen JS, Aletaha D, Barton A, Burmester GR, Emery P, Firestein GS, Kavanaugh A, McInnes IB, Solomon DH, Strand V, Yamamoto K. Rheumatoid arthritis. Nat Rev Dis Primers 2018; 4:18001. [PMID: 29417936 DOI: 10.1038/nrdp.2018.1] [Citation(s) in RCA: 1254] [Impact Index Per Article: 209.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
Rheumatoid arthritis (RA) is a chronic, inflammatory, autoimmune disease that primarily affects the joints and is associated with autoantibodies that target various molecules including modified self-epitopes. The identification of novel autoantibodies has improved diagnostic accuracy, and newly developed classification criteria facilitate the recognition and study of the disease early in its course. New clinical assessment tools are able to better characterize disease activity states, which are correlated with progression of damage and disability, and permit improved follow-up. In addition, better understanding of the pathogenesis of RA through recognition of key cells and cytokines has led to the development of targeted disease-modifying antirheumatic drugs. Altogether, the improved understanding of the pathogenetic processes involved, rational use of established drugs and development of new drugs and reliable assessment tools have drastically altered the lives of individuals with RA over the past 2 decades. Current strategies strive for early referral, early diagnosis and early start of effective therapy aimed at remission or, at the least, low disease activity, with rapid adaptation of treatment if this target is not reached. This treat-to-target approach prevents progression of joint damage and optimizes physical functioning, work and social participation. In this Primer, we discuss the epidemiology, pathophysiology, diagnosis and management of RA.
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Affiliation(s)
- Josef S Smolen
- Division of Rheumatology, Department of Medicine 3, Medical University of Vienna, Waehringer Guertel 18-20, 1090 Vienna, Austria
| | - Daniel Aletaha
- Division of Rheumatology, Department of Medicine 3, Medical University of Vienna, Waehringer Guertel 18-20, 1090 Vienna, Austria
| | - Anne Barton
- Arthritis Research UK Centre for Genetics and Genomics and NIHR Manchester Biomedical Research Centre, Manchester Academic Health Sciences Centre, The University of Manchester and Central Manchester Foundation Trust, Manchester, UK
| | - Gerd R Burmester
- Department of Rheumatology and Clinical Immunology, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Paul Emery
- Leeds Institute of Rheumatic and Musculoskeletal Medicine, University of Leeds, Chapel Allerton Hospital, Leeds, UK.,NIHR Leeds Biomedical Research Centre, Leeds Teaching Hospitals NHS Trust, Leeds, UK
| | - Gary S Firestein
- Division of Rheumatology, Allergy and Immunology, University of California-San Diego School of Medicine, La Jolla, CA, USA
| | - Arthur Kavanaugh
- Division of Rheumatology, Allergy and Immunology, University of California-San Diego School of Medicine, La Jolla, CA, USA
| | - Iain B McInnes
- Institute of Infection Immunity and Inflammation, University of Glasgow, Glasgow, UK
| | - Daniel H Solomon
- Division of Rheumatology, Brigham and Women's Hospital, Boston, MA, USA
| | - Vibeke Strand
- Division of Immunology and Rheumatology, Stanford University, Palo Alto, CA, USA
| | - Kazuhiko Yamamoto
- Laboratory for Autoimmune Diseases, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
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13
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Romão VC, Vital EM, Fonseca JE, Buch MH. Right drug, right patient, right time: aspiration or future promise for biologics in rheumatoid arthritis? Arthritis Res Ther 2017; 19:239. [PMID: 29065909 PMCID: PMC5655983 DOI: 10.1186/s13075-017-1445-3] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022] Open
Abstract
Individualising biologic disease-modifying anti-rheumatic drugs (bDMARDs) to maximise outcomes and deliver safe and cost-effective care is a key goal in the management of rheumatoid arthritis (RA). Investigation to identify predictive tools of bDMARD response is a highly active and prolific area of research. In addition to clinical phenotyping, cellular and molecular characterisation of synovial tissue and blood in patients with RA, using different technologies, can facilitate predictive testing. This narrative review will summarise the literature for the available bDMARD classes and focus on where progress has been made. We will also look ahead and consider the increasing use of 'omics' technologies, the potential they hold as well as the challenges, and what is needed in the future to fully realise our ambition of personalised bDMARD treatment.
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Affiliation(s)
- Vasco C. Romão
- Rheumatology Research Unit, Instituto de Medicina Molecular, Faculdade de Medicina, Universidade de Lisboa, Av. Professor Egas Moniz, 1649-028 Lisboa, Portugal
- Department of Rheumatology, Hospital de Santa Maria, Centro Hospitalar Lisboa Norte, Av. Professor Egas Moniz, 1649-035 Lisboa, Portugal
| | - Edward M. Vital
- Leeds Institute of Rheumatic and Musculoskeletal Medicine, University of Leeds, Leeds, UK
- NIHR Leeds Musculoskeletal Biomedical Research Unit, Leeds Teaching Hospitals NHS Trust, Leeds, UK
| | - João Eurico Fonseca
- Rheumatology Research Unit, Instituto de Medicina Molecular, Faculdade de Medicina, Universidade de Lisboa, Av. Professor Egas Moniz, 1649-028 Lisboa, Portugal
- Department of Rheumatology, Hospital de Santa Maria, Centro Hospitalar Lisboa Norte, Av. Professor Egas Moniz, 1649-035 Lisboa, Portugal
| | - Maya H. Buch
- Leeds Institute of Rheumatic and Musculoskeletal Medicine, University of Leeds, Leeds, UK
- NIHR Leeds Musculoskeletal Biomedical Research Unit, Leeds Teaching Hospitals NHS Trust, Leeds, UK
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14
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Nair N, Wilson AG, Barton A. DNA methylation as a marker of response in rheumatoid arthritis. Pharmacogenomics 2017; 18:1323-1332. [PMID: 28836487 DOI: 10.2217/pgs-2016-0195] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022] Open
Abstract
Rheumatoid arthritis (RA) is a complex disease affecting approximately 0.5-1% of the population. While there are effective biologic therapies, in up to 40% of patients, disease activity remains inadequately controlled. Therefore, identifying factors that predict, prior to the initiation of therapy, which patients are likely to respond best to which treatment is a research priority and DNA methylation is increasingly being explored as a potential theranostic biomarker. DNA methylation is thought to play a role in RA disease pathogenesis and in mediating the relationship between genetic variants and patient outcomes. The role of DNA methylation has been most extensively explored in cancer medicine, where it has been shown to be predictive of treatment response. Studies in RA, however, are in their infancy and, while showing promise, further investigation in well-powered studies is warranted.
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Affiliation(s)
- Nisha Nair
- Arthritis Research UK Centre for Genetics & Genomics, Centre for Musculoskeletal Research, University of Manchester, Manchester, UK
| | - Anthony G Wilson
- University College Dublin School of Medicine & Medical Science & Conway Institute, Dublin, Ireland
| | - Anne Barton
- Arthritis Research UK Centre for Genetics & Genomics, Centre for Musculoskeletal Research, University of Manchester, Manchester, UK.,NIHR Manchester Musculoskeletal BRU, Central Manchester Foundation Trust, Manchester Academic Health Sciences Centre, Manchester, UK
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15
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Genomics and epigenomics in rheumatic diseases: what do they provide in terms of diagnosis and disease management? Clin Rheumatol 2017; 36:1935-1947. [PMID: 28725948 DOI: 10.1007/s10067-017-3744-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2017] [Revised: 06/28/2017] [Accepted: 06/28/2017] [Indexed: 12/28/2022]
Abstract
Most rheumatic diseases are complex or multifactorial entities with pathogeneses that interact with both multiple genetic factors and a high number of diverse environmental factors. Knowledge of the human genome sequence and its diversity among populations has provided a crucial step forward in our understanding of genetic diseases, identifying many genetic loci or genes associated with diverse phenotypes. In general, susceptibility to autoimmunity is associated with multiple risk factors, but the mechanism of the environmental component influence is poorly understood. Studies in twins have demonstrated that genetics do not explain the totality of the pathogenesis of rheumatic diseases. One method of modulating gene expression through environmental effects is via epigenetic modifications. These techniques open a new field for identifying useful new biomarkers and therapeutic targets. In this context, the development of "-omics" techniques is an opportunity to progress in our knowledge of complex diseases, impacting the discovery of new potential biomarkers suitable for their introduction into clinical practice. In this review, we focus on the recent advances in the fields of genomics and epigenomics in rheumatic diseases and their potential to be useful for the diagnosis, follow-up, and treatment of these diseases. The ultimate aim of genomic studies in any human disease is to understand its pathogenesis, thereby enabling the prediction of the evolution of the disease to establish new treatments and address the development of personalized therapies.
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16
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Affiliation(s)
- Joel M Kremer
- Pfaff Family Professor of Medicine, Albany Medical College; Director of Research, The Center for Rheumatology, Albany, New York, USA.
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17
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Eyre S, Orozco G, Worthington J. The genetics revolution in rheumatology: large scale genomic arrays and genetic mapping. Nat Rev Rheumatol 2017; 13:421-432. [PMID: 28569263 DOI: 10.1038/nrrheum.2017.80] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Susceptibility to rheumatic diseases, such as osteoarthritis, rheumatoid arthritis, ankylosing spondylitis, systemic lupus erythematosus, juvenile idiopathic arthritis and psoriatic arthritis, includes a large genetic component. Understanding how an individual's genetic background influences disease onset and outcome can lead to a better understanding of disease biology, improved diagnosis and treatment, and, ultimately, to disease prevention or cure. The past decade has seen great progress in the identification of genetic variants that influence the risk of rheumatic diseases. The challenging task of unravelling the function of these variants is ongoing. In this Review, the major insights from genetic studies, gained from advances in technology, bioinformatics and study design, are discussed in the context of rheumatic disease. In addition, pivotal genetic studies in the main rheumatic diseases are highlighted, with insights into how these studies have changed the way we view these conditions in terms of disease overlap, pathways of disease and potential new therapeutic targets. Finally, the limitations of genetic studies, gaps in our knowledge and ways in which current genetic knowledge can be fully translated into clinical benefit are examined.
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Affiliation(s)
- Stephen Eyre
- Arthritis Research UK Centre for Genetics and Genomics, School of Biological Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Stopford Building, Oxford Road, Manchester M13 9PT, UK
| | - Gisela Orozco
- Arthritis Research UK Centre for Genetics and Genomics, School of Biological Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Stopford Building, Oxford Road, Manchester M13 9PT, UK
| | - Jane Worthington
- Arthritis Research UK Centre for Genetics and Genomics, School of Biological Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Stopford Building, Oxford Road, Manchester M13 9PT, UK.,NIHR Manchester Musculoskeletal Biomedical Research Unit, Manchester Academic Health Sciences Centre, Central Manchester Foundation Trust, Grafton Street. Manchester M13 9NT, UK
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18
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Conigliaro P, Ciccacci C, Politi C, Triggianese P, Rufini S, Kroegler B, Perricone C, Latini A, Novelli G, Borgiani P, Perricone R. Polymorphisms in STAT4, PTPN2, PSORS1C1 and TRAF3IP2 Genes Are Associated with the Response to TNF Inhibitors in Patients with Rheumatoid Arthritis. PLoS One 2017; 12:e0169956. [PMID: 28107378 PMCID: PMC5249113 DOI: 10.1371/journal.pone.0169956] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2016] [Accepted: 12/27/2016] [Indexed: 11/29/2022] Open
Abstract
Objective Rheumatoid Arthritis (RA) is a progressive autoimmune disease characterized by chronic joint inflammation and structural damage. Remission or at least low disease activity (LDA) represent potentially desirable goals of RA treatment. Single nucleotide polymorphisms (SNPs) in several genes might be useful for prediction of response to therapy. We aimed at exploring 4 SNPs in candidate genes (STAT4, PTPN2, PSORS1C1 and TRAF3IP2) in order to investigate their potential role in the response to therapy with tumor necrosis factor inhibitors (TNF-i) in RA patients. Methods In 171 RA patients we investigated the following SNPs: rs7574865 (STAT4), rs2233945 (PSORS1C1), rs7234029 (PTPN2) and rs33980500 (TRAF3IP2). Remission, LDA, and EULAR response were registered at 6 months and 2 years after initiation of first line TNF-i [Adalimumab (ADA) and Etanercept (ETN)]. Results STAT4 variant allele was associated with the absence of a good/moderate EULAR response at 2 years of treatment in the whole RA group and in ETN treated patients. The PTPN2 SNP was associated with no good/moderate EULAR response at 6 months in ADA treated patients. Patients carrying PSORS1C1 variant allele did not reach LDA at 6 months in both the whole RA group and ETN treated patients. TRAF3IP2 variant allele was associated with the lack of LDA and remission achievement at 6 months in all RA cohort while an association with no EULAR response at 2 years of treatment occurred only in ETN treated patients. Conclusions For the first time, we reported that SNPs in STAT4, PTPN2, PSORS1C1, and TRAF3IP2 are associated with response to TNF-i treatment in RA patients; however, these findings should be validated in a larger population.
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Affiliation(s)
- Paola Conigliaro
- Clinic of Rheumatology, Allergology and Clinical Immunology, Department of “Medicina dei Sistemi”, University of Rome Tor Vergata, Rome, Italy
| | - Cinzia Ciccacci
- Department of Biomedicine and Prevention, Genetics Section, University of Rome Tor Vergata, Rome, Italy
| | - Cristina Politi
- Department of Biomedicine and Prevention, Genetics Section, University of Rome Tor Vergata, Rome, Italy
| | - Paola Triggianese
- Clinic of Rheumatology, Allergology and Clinical Immunology, Department of “Medicina dei Sistemi”, University of Rome Tor Vergata, Rome, Italy
- * E-mail:
| | - Sara Rufini
- Department of Biomedicine and Prevention, Genetics Section, University of Rome Tor Vergata, Rome, Italy
| | - Barbara Kroegler
- Clinic of Rheumatology, Allergology and Clinical Immunology, Department of “Medicina dei Sistemi”, University of Rome Tor Vergata, Rome, Italy
| | - Carlo Perricone
- Reumatologia, Dipartimento di Medicina Interna e Specialità Mediche, Sapienza Università di Roma, Rome, Italy
| | - Andrea Latini
- Department of Biomedicine and Prevention, Genetics Section, University of Rome Tor Vergata, Rome, Italy
| | - Giuseppe Novelli
- Department of Biomedicine and Prevention, Genetics Section, University of Rome Tor Vergata, Rome, Italy
| | - Paola Borgiani
- Department of Biomedicine and Prevention, Genetics Section, University of Rome Tor Vergata, Rome, Italy
| | - Roberto Perricone
- Clinic of Rheumatology, Allergology and Clinical Immunology, Department of “Medicina dei Sistemi”, University of Rome Tor Vergata, Rome, Italy
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Pouillon L, Bossuyt P, Peyrin-Biroulet L. Considerations, challenges and future of anti-TNF therapy in treating inflammatory bowel disease. Expert Opin Biol Ther 2016; 16:1277-90. [PMID: 27329436 DOI: 10.1080/14712598.2016.1203897] [Citation(s) in RCA: 37] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
INTRODUCTION Crohn's disease (CD) and ulcerative colitis (UC) are chronic disabling conditions. Monoclonal antibody therapy directed against tumor necrosis factor-alpha (anti-TNF) has revolutionized the care of patients with inflammatory bowel disease (IBD). AREAS COVERED Considerations before starting anti-TNF therapy are highlighted: the best time to start with anti-TNF therapy, either alone or in combination with an immunomodulator, the choice of an anti-TNF agent and the contra-indications to anti-TNF therapy. Primary nonresponse and secondary loss of response are discussed. De-escalating therapy, the role of therapeutic drug monitoring and the use of biosimilars, are handled. Finally, the future directions of anti-TNF therapy are emphasized. EXPERT OPINION Anti-TNF therapy remains the cornerstone in the treatment of IBD. When initiating long-term therapy, safety and cost issues are of great importance. The therapeutic armamentarium in the treatment of IBD is rapidly growing. Therefore, the challenge is to optimize the use and refine the exact position of anti-TNF therapy in the near future, with personalized medicine as the ultimate goal.
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Affiliation(s)
- Lieven Pouillon
- a Department of Hepato-Gastroenterology , University Hospitals Leuven, Uz Gasthuisberg , Leuven , Belgium
| | - Peter Bossuyt
- b Imelda GI Clinical Research Centre , Imeldaziekenhuis Bonheiden , Bonheiden , Belgium
| | - Laurent Peyrin-Biroulet
- c Inserm U954 and Department of Gastroenterology , Nancy University Hospital, Université de Lorraine , Vandœuvre-lès-Nancy , France
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Affiliation(s)
- Hannah Wilson
- Future Medicine Ltd, Unitec House, 2 Albert Place, Finchley Central, N3 1QB, London, UK
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