1
|
McDermott GC, DiIorio M, Kawano Y, Jeffway M, MacVicar M, Dahal K, Moon SJ, Seyok T, Coblyn J, Massarotti E, Weinblatt ME, Weisenfeld D, Liao KP. Reasons for multiple biologic and targeted synthetic DMARD switching and characteristics of treatment refractory rheumatoid arthritis. Semin Arthritis Rheum 2024; 66:152421. [PMID: 38457949 PMCID: PMC11088978 DOI: 10.1016/j.semarthrit.2024.152421] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2023] [Revised: 12/26/2023] [Accepted: 02/20/2024] [Indexed: 03/10/2024]
Abstract
OBJECTIVE Switching biologic and targeted synthetic DMARD (b/tsDMARD) medications occurs commonly in RA patients, however data are limited on the reasons for these changes. The objective of the study was to identify and categorize reasons for b/tsDMARD switching and investigate characteristics associated with treatment refractory RA. METHODS In a multi-hospital RA electronic health record (EHR) cohort, we identified RA patients prescribed ≥1 b/tsDMARD between 2001 and 2017. Consistent with the EULAR "difficult to treat" (D2T) RA definition, we further identified patients who discontinued ≥2 b/tsDMARDs with different mechanisms of action. We performed manual chart review to determine reasons for medication discontinuation. We defined "treatment refractory" RA as not achieving low disease activity (<3 tender or swollen joints on <7.5 mg of daily prednisone equivalent) despite treatment with two different b/tsDMARD mechanisms of action. We compared demographic, lifestyle, and clinical factors between treatment refractory RA and b/tsDMARD initiators not meeting D2T criteria. RESULTS We identified 6040 RA patients prescribed ≥1 b/tsDMARD including 404 meeting D2T criteria. The most common reasons for medication discontinuation were inadequate response (43.3 %), loss of efficacy (25.8 %), and non-allergic adverse events (13.7 %). Of patients with D2T RA, 15 % had treatment refractory RA. Treatment refractory RA patients were younger at b/tsDMARD initiation (mean 47.2 vs. 55.2 years, p < 0.001), more commonly female (91.8% vs. 76.1 %, p = 0.006), and ever smokers (68.9% vs. 49.9 %, p = 0.005). No RA clinical factors differentiated treatment refractory RA patients from b/tsDMARD initiators. CONCLUSIONS In a large EHR-based RA cohort, the most common reasons for b/tsDMARD switching were inadequate response, loss of efficacy, and nonallergic adverse events (e.g. infections, leukopenia, psoriasis). Clinical RA factors were insufficient for differentiating b/tsDMARD responders from nonresponders.
Collapse
Affiliation(s)
- Gregory C McDermott
- Division of Rheumatology, Inflammation, and Immunity, Brigham and Women's Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA.
| | - Michael DiIorio
- Division of Rheumatology, Inflammation, and Immunity, Brigham and Women's Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA
| | - Yumeko Kawano
- Division of Rheumatology, Inflammation, and Immunity, Brigham and Women's Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA
| | - Mary Jeffway
- Division of Rheumatology, Inflammation, and Immunity, Brigham and Women's Hospital, Boston, MA, USA
| | - Megan MacVicar
- Division of Rheumatology, Inflammation, and Immunity, Brigham and Women's Hospital, Boston, MA, USA
| | - Kumar Dahal
- Division of Rheumatology, Inflammation, and Immunity, Brigham and Women's Hospital, Boston, MA, USA
| | - Su-Jin Moon
- Division of Rheumatology, Department of Internal Medicine, Yeouido St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Thany Seyok
- Division of Rheumatology, Inflammation, and Immunity, Brigham and Women's Hospital, Boston, MA, USA
| | - Jonathan Coblyn
- Division of Rheumatology, Inflammation, and Immunity, Brigham and Women's Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA
| | - Elena Massarotti
- Division of Rheumatology, Inflammation, and Immunity, Brigham and Women's Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA
| | - Michael E Weinblatt
- Division of Rheumatology, Inflammation, and Immunity, Brigham and Women's Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA
| | - Dana Weisenfeld
- Division of Rheumatology, Inflammation, and Immunity, Brigham and Women's Hospital, Boston, MA, USA
| | - Katherine P Liao
- Division of Rheumatology, Inflammation, and Immunity, Brigham and Women's Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA
| |
Collapse
|
2
|
Weber B, Weisenfeld D, Massarotti E, Seyok T, Cremone G, Lam E, Golnik C, Brownmiller S, Liu F, Huang S, Todd DJ, Coblyn JS, Weinblatt ME, Cai T, Dahal K, Kohler M, Yinh J, Barrett L, Solomon DH, Plutzky J, Schelbert HR, Campisi R, Bolster MB, Di Carli M, Liao KP. Interplay Between Systemic Inflammation, Myocardial Injury, and Coronary Microvascular Dysfunction in Rheumatoid Arthritis: Results From the LiiRA Study. J Am Heart Assoc 2024; 13:e030387. [PMID: 38686879 DOI: 10.1161/jaha.123.030387] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/11/2023] [Accepted: 01/17/2024] [Indexed: 05/02/2024]
Abstract
BACKGROUND Coronary microvascular dysfunction as measured by myocardial flow reserve (MFR) is associated with increased cardiovascular risk in rheumatoid arthritis (RA). The objective of this study was to determine the association between reducing inflammation with MFR and other measures of cardiovascular risk. METHODS AND RESULTS Patients with RA with active disease about to initiate a tumor necrosis factor inhibitor were enrolled (NCT02714881). All subjects underwent a cardiac perfusion positron emission tomography scan to quantify MFR at baseline before tumor necrosis factor inhibitor initiation, and after tumor necrosis factor inhibitor initiation at 24 weeks. MFR <2.5 in the absence of obstructive coronary artery disease was defined as coronary microvascular dysfunction. Blood samples at baseline and 24 weeks were measured for inflammatory markers (eg, high-sensitivity C-reactive protein [hsCRP], interleukin-1b, and high-sensitivity cardiac troponin T [hs-cTnT]). The primary outcome was mean MFR before and after tumor necrosis factor inhibitor initiation, with Δhs-cTnT as the secondary outcome. Secondary and exploratory analyses included the correlation between ΔhsCRP and other inflammatory markers with MFR and hs-cTnT. We studied 66 subjects, 82% of which were women, mean RA duration 7.4 years. The median atherosclerotic cardiovascular disease risk was 2.5%; 47% had coronary microvascular dysfunction and 23% had detectable hs-cTnT. We observed no change in mean MFR before (2.65) and after treatment (2.64, P=0.6) or hs-cTnT. A correlation was observed between a reduction in hsCRP and interleukin-1b with a reduction in hs-cTnT. CONCLUSIONS In this RA cohort with low prevalence of cardiovascular risk factors, nearly 50% of subjects had coronary microvascular dysfunction at baseline. A reduction in inflammation was not associated with improved MFR. However, a modest reduction in interleukin-1b and no other inflammatory pathways was correlated with a reduction in subclinical myocardial injury. REGISTRATION URL: https://www.clinicaltrials.gov; Unique identifier: NCT02714881.
Collapse
Affiliation(s)
- Brittany Weber
- Division of Cardiovascular Medicine, Department of Medicine, Heart and Vascular Center Brigham and Women's Hospital, Harvard Medical School Boston MA
| | - Dana Weisenfeld
- Division of Rheumatology, Inflammation, and Immunity Brigham and Women's Hospital, Harvard Medical School Boston MA
| | - Elena Massarotti
- Division of Rheumatology, Inflammation, and Immunity Brigham and Women's Hospital, Harvard Medical School Boston MA
| | - Thany Seyok
- Division of Rheumatology, Inflammation, and Immunity Brigham and Women's Hospital, Harvard Medical School Boston MA
| | - Gabrielle Cremone
- Division of Rheumatology, Inflammation, and Immunity Brigham and Women's Hospital, Harvard Medical School Boston MA
| | - Ethan Lam
- Division of Rheumatology, Inflammation, and Immunity Brigham and Women's Hospital, Harvard Medical School Boston MA
| | - Charlotte Golnik
- Division of Rheumatology, Inflammation, and Immunity Brigham and Women's Hospital, Harvard Medical School Boston MA
| | - Seth Brownmiller
- Division of Rheumatology, Inflammation, and Immunity Brigham and Women's Hospital, Harvard Medical School Boston MA
| | - Feng Liu
- Division of Rheumatology, Inflammation, and Immunity Brigham and Women's Hospital, Harvard Medical School Boston MA
| | - Sicong Huang
- Division of Rheumatology, Inflammation, and Immunity Brigham and Women's Hospital, Harvard Medical School Boston MA
| | - Derrick J Todd
- Division of Rheumatology, Inflammation, and Immunity Brigham and Women's Hospital, Harvard Medical School Boston MA
| | - Jonathan S Coblyn
- Division of Rheumatology, Inflammation, and Immunity Brigham and Women's Hospital, Harvard Medical School Boston MA
| | - Michael E Weinblatt
- Division of Rheumatology, Inflammation, and Immunity Brigham and Women's Hospital, Harvard Medical School Boston MA
| | - Tianrun Cai
- Division of Rheumatology, Inflammation, and Immunity Brigham and Women's Hospital, Harvard Medical School Boston MA
| | - Kumar Dahal
- Division of Rheumatology, Inflammation, and Immunity Brigham and Women's Hospital, Harvard Medical School Boston MA
| | - Minna Kohler
- Division of Rheumatology, Allergy and Immunology Massachusetts General Hospital, Harvard Medical School Boston MA
| | - Janeth Yinh
- Division of Rheumatology, Allergy and Immunology Massachusetts General Hospital, Harvard Medical School Boston MA
| | - Leanne Barrett
- Division of Cardiovascular Medicine, Department of Medicine, Heart and Vascular Center Brigham and Women's Hospital, Harvard Medical School Boston MA
| | - Daniel H Solomon
- Division of Rheumatology, Inflammation, and Immunity Brigham and Women's Hospital, Harvard Medical School Boston MA
| | - Jorge Plutzky
- Division of Cardiovascular Medicine, Department of Medicine, Heart and Vascular Center Brigham and Women's Hospital, Harvard Medical School Boston MA
| | | | - Roxana Campisi
- Instituto Argentino de Diagnóstico y Tratamiento S.A. Buenos Aires Argentina
| | - Marcy B Bolster
- Division of Rheumatology, Allergy and Immunology Massachusetts General Hospital, Harvard Medical School Boston MA
| | - Marcelo Di Carli
- Division of Cardiovascular Medicine, Department of Medicine, Heart and Vascular Center Brigham and Women's Hospital, Harvard Medical School Boston MA
| | - Katherine P Liao
- Division of Rheumatology, Inflammation, and Immunity Brigham and Women's Hospital, Harvard Medical School Boston MA
| |
Collapse
|
3
|
Weisenfeld D, Zhang F, Donlin L, Jonsson AH, Apruzzese W, Campbell D, Rao DA, Wei K, Holers VM, Gravallese E, Moreland L, Goodman S, Brenner M, Raychaudhuri S, Filer A, Anolik J, Bykerk V, Liao KP. Associations Between Rheumatoid Arthritis Clinical Factors and Synovial Cell Types and States. Arthritis Rheumatol 2024; 76:356-362. [PMID: 37791989 PMCID: PMC10922423 DOI: 10.1002/art.42726] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2023] [Revised: 08/25/2023] [Accepted: 09/19/2023] [Indexed: 10/05/2023]
Abstract
OBJECTIVE Recent studies have uncovered diverse cell types and states in the rheumatoid arthritis (RA) synovium; however, limited data exist correlating these findings with patient-level clinical information. Using the largest cohort to date with clinical and multicell data, we determined associations between RA clinical factors with cell types and states in the RA synovium. METHODS The Accelerated Medicines Partnership Rheumatoid Arthritis study recruited patients with active RA who were not receiving disease-modifying antirheumatic drugs (DMARDs) or who had an inadequate response to methotrexate (MTX) or tumor necrosis factor inhibitors. RA clinical factors were systematically collected. Biopsies were performed on an inflamed joint, and tissue were disaggregated and processed with a cellular indexing of transcriptomes and epitopes sequencing pipeline from which the following cell type percentages and cell type abundance phenotypes (CTAPs) were derived: endothelial, fibroblast, and myeloid (EFM); fibroblasts; myeloid; T and B cells; T cells and fibroblasts (TF); and T and myeloid cells. Correlations were measured between RA clinical factors, cell type percentage, and CTAPs. RESULTS We studied 72 patients (mean age 57 years, 75% women, 83% seropositive, mean RA duration 6.6 years, mean Disease Activity Score-28 C-reactive Protein 3 [DAS28-CRP3] score 4.8). Higher DAS28-CRP3 correlated with a higher T cell percentage (P < 0.01). Those receiving MTX and not a biologic DMARD (bDMARD) had a higher percentage of B cells versus those receiving no DMARDs (P < 0.01). Most of those receiving bDMARDs were categorized as EFM (57%), whereas none were TF. No significant difference was observed across CTAPs for age, sex, RA disease duration, or DAS28-CRP3. CONCLUSION In this comprehensive screen of clinical factors, we observed differential associations between DMARDs and cell phenotypes, suggesting that RA therapies, more than other clinical factors, may impact cell type/state in the synovium and ultimately influence response to subsequent therapies.
Collapse
Affiliation(s)
- Dana Weisenfeld
- Division of Rheumatology, Inflammation, and Immunity, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | - Fan Zhang
- Division of Rheumatology, Inflammation, and Immunity, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
- Division of Rheumatology, University of Colorado School of Medicine, Aurora, CO, USA
- Center for Health Artificial Intelligence, University of Colorado School of Medicine, Aurora, CO, USA
- Center for Data Sciences, Brigham and Women’s Hospital, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | - Laura Donlin
- Weill Cornell Medicine, New York, NY, USA
- Hospital for Special Surgery, New York, NY, USA
| | - Anna Helena Jonsson
- Division of Rheumatology, Inflammation, and Immunity, Brigham and Women’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
| | - Debbie Campbell
- Division of Allergy, Immunology and Rheumatology, University of Rochester Medical Center, Rochester, NY, USA
| | | | - Deepak A. Rao
- Division of Rheumatology, Inflammation, and Immunity, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | - Kevin Wei
- Division of Rheumatology, Inflammation, and Immunity, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | - V. Michael Holers
- Division of Rheumatology, University of Colorado School of Medicine, Aurora, CO, USA
| | - Ellen Gravallese
- Division of Rheumatology, Inflammation, and Immunity, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | - Larry 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 Goodman
- Weill Cornell Medicine, New York, NY, USA
- Hospital for Special Surgery, New York, NY, USA
| | - Michael Brenner
- Division of Rheumatology, Inflammation, and Immunity, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | - Soumya Raychaudhuri
- Division of Rheumatology, Inflammation, and Immunity, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
- Center for Data Sciences, Brigham and Women’s Hospital, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | - Andrew Filer
- Rheumatology Research Group, Institute for Inflammation and Ageing, NIHR Birmingham Biomedical Research Center and Clinical Research Facility, University of Birmingham, Queen Elizabeth Hospital, Birmingham, UK
- MRC Versus Arthritis Centre for Musculoskeletal Ageing Research and the Research into Inflammatory Arthritis Centre Versus Arthritis, University of Birmingham, Birmingham, UK
| | - Jennifer Anolik
- Division of Allergy, Immunology and Rheumatology, University of Rochester Medical Center, Rochester, NY, USA
| | - Vivian Bykerk
- Weill Cornell Medicine, New York, NY, USA
- Hospital for Special Surgery, New York, NY, USA
| | - Katherine P. Liao
- Division of Rheumatology, Inflammation, and Immunity, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| |
Collapse
|
4
|
Wen J, Hou J, Bonzel CL, Zhao Y, Castro VM, Gainer VS, Weisenfeld D, Cai T, Ho YL, Panickan VA, Costa L, Hong C, Gaziano JM, Liao KP, Lu J, Cho K, Cai T. LATTE: Label-efficient incident phenotyping from longitudinal electronic health records. Patterns (N Y) 2024; 5:100906. [PMID: 38264714 PMCID: PMC10801250 DOI: 10.1016/j.patter.2023.100906] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/27/2023] [Revised: 09/06/2023] [Accepted: 12/01/2023] [Indexed: 01/25/2024]
Abstract
Electronic health record (EHR) data are increasingly used to support real-world evidence studies but are limited by the lack of precise timings of clinical events. Here, we propose a label-efficient incident phenotyping (LATTE) algorithm to accurately annotate the timing of clinical events from longitudinal EHR data. By leveraging the pre-trained semantic embeddings, LATTE selects predictive features and compresses their information into longitudinal visit embeddings through visit attention learning. LATTE models the sequential dependency between the target event and visit embeddings to derive the timings. To improve label efficiency, LATTE constructs longitudinal silver-standard labels from unlabeled patients to perform semi-supervised training. LATTE is evaluated on the onset of type 2 diabetes, heart failure, and relapses of multiple sclerosis. LATTE consistently achieves substantial improvements over benchmark methods while providing high prediction interpretability. The event timings are shown to help discover risk factors of heart failure among patients with rheumatoid arthritis.
Collapse
Affiliation(s)
- Jun Wen
- Harvard Medical School, Boston, MA, USA
- VA Boston Healthcare System, Boston, MA, USA
| | - Jue Hou
- University of Minnesota, Minneapolis, MN, USA
| | - Clara-Lea Bonzel
- Harvard Medical School, Boston, MA, USA
- VA Boston Healthcare System, Boston, MA, USA
| | | | | | | | | | - Tianrun Cai
- VA Boston Healthcare System, Boston, MA, USA
- Mass General Brigham, Boston, MA, USA
| | - Yuk-Lam Ho
- VA Boston Healthcare System, Boston, MA, USA
| | - Vidul A. Panickan
- Harvard Medical School, Boston, MA, USA
- VA Boston Healthcare System, Boston, MA, USA
| | | | | | - J. Michael Gaziano
- Harvard Medical School, Boston, MA, USA
- VA Boston Healthcare System, Boston, MA, USA
- Brigham and Women’s Hospital, Boston, MA, USA
| | - Katherine P. Liao
- Harvard Medical School, Boston, MA, USA
- VA Boston Healthcare System, Boston, MA, USA
- Brigham and Women’s Hospital, Boston, MA, USA
| | - Junwei Lu
- VA Boston Healthcare System, Boston, MA, USA
- Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Kelly Cho
- Harvard Medical School, Boston, MA, USA
- VA Boston Healthcare System, Boston, MA, USA
- Brigham and Women’s Hospital, Boston, MA, USA
| | - Tianxi Cai
- Harvard Medical School, Boston, MA, USA
- VA Boston Healthcare System, Boston, MA, USA
- Harvard T.H. Chan School of Public Health, Boston, MA, USA
| |
Collapse
|
5
|
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: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [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.
Collapse
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.
| |
Collapse
|
6
|
Das P, Weisenfeld D, Dahal K, De D, Feathers V, Coblyn JS, Weinblatt ME, Shadick NA, Cai T, Liao KP. Utilizing biologic disease-modifying anti-rheumatic treatment sequences to subphenotype rheumatoid arthritis. Arthritis Res Ther 2023; 25:93. [PMID: 37269020 DOI: 10.1186/s13075-023-03072-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2022] [Accepted: 05/20/2023] [Indexed: 06/04/2023] Open
Abstract
BACKGROUND Many patients with rheumatoid arthritis (RA) require a trial of multiple biologic disease-modifying anti-rheumatic drugs (bDMARDs) to control their disease. With the availability of several bDMARD options, the history of bDMARDs may provide an alternative approach to understanding subphenotypes of RA. The objective of this study was to determine whether there exist distinct clusters of RA patients based on bDMARD prescription history to subphenotype RA. METHODS We studied patients from a validated electronic health record-based RA cohort with data from January 1, 2008, through July 31, 2019; all subjects prescribed ≥ 1 bDMARD or targeted synthetic (ts) DMARD were included. To determine whether subjects had similar b/tsDMARD sequences, the sequences were considered as a Markov chain over the state-space of 5 classes of b/tsDMARDs. The maximum likelihood estimator (MLE)-based approach was used to estimate the Markov chain parameters to determine the clusters. The EHR data of study subjects were further linked with a registry containing prospectively collected data for RA disease activity, i.e., clinical disease activity index (CDAI). As a proof of concept, we tested whether the clusters derived from b/tsDMARD sequences correlated with clinical measures, specifically differing trajectories of CDAI. RESULTS We studied 2172 RA subjects, mean age 52 years, RA duration 3.4 years, and 62% seropositive. We observed 550 unique b/tsDMARD sequences and identified 4 main clusters: (1) TNFi persisters (65.7%), (2) TNFi and abatacept therapy (8.0%), (3) on rituximab or multiple b/tsDMARDs (12.7%), (4) prescribed multiple therapies with tocilizumab predominant (13.6%). Compared to the other groups, TNFi persisters had the most favorable trajectory of CDAI over time. CONCLUSION We observed that RA subjects can be clustered based on the sequence of b/tsDMARD prescriptions over time and that the clusters were correlated with differing trajectories of disease activity over time. This study highlights an alternative approach to consider subphenotyping of patients with RA for studies aimed at understanding treatment response.
Collapse
Affiliation(s)
- Priyam Das
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Department of Biostatistics, Virginia Commonwealth University, Richmond, VA, USA
| | - Dana Weisenfeld
- Division of Rheumatology, Inflammation, and Immunity, Brigham and Women's Hospital, 60 Fenwood Road, Boston, MA, 02115, USA
| | - Kumar Dahal
- Division of Rheumatology, Inflammation, and Immunity, Brigham and Women's Hospital, 60 Fenwood Road, Boston, MA, 02115, USA
| | - Debsurya De
- Indian Statistical Institute, Kolkata, India
| | - Vivi Feathers
- Division of Rheumatology, Inflammation, and Immunity, Brigham and Women's Hospital, 60 Fenwood Road, Boston, MA, 02115, USA
| | - Jonathan S Coblyn
- Division of Rheumatology, Inflammation, and Immunity, Brigham and Women's Hospital, 60 Fenwood Road, Boston, MA, 02115, USA
| | - Michael E Weinblatt
- Division of Rheumatology, Inflammation, and Immunity, Brigham and Women's Hospital, 60 Fenwood Road, Boston, MA, 02115, USA
| | - Nancy A Shadick
- Division of Rheumatology, Inflammation, and Immunity, Brigham and Women's Hospital, 60 Fenwood Road, Boston, MA, 02115, USA
| | - Tianxi Cai
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Katherine P Liao
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.
- Division of Rheumatology, Inflammation, and Immunity, Brigham and Women's Hospital, 60 Fenwood Road, Boston, MA, 02115, USA.
| |
Collapse
|
7
|
Zhang HG, McDermott G, Seyok T, Huang S, Dahal K, L'Yi S, Lea-Bonzel C, Stratton J, Weisenfeld D, Monach P, Raychaudhuri S, Yu KH, Cai T, Cui J, Hong C, Cai T, Liao KP. Identifying shared genetic architecture between rheumatoid arthritis and other conditions: a phenome-wide association study with genetic risk scores. EBioMedicine 2023; 92:104581. [PMID: 37121095 PMCID: PMC10173154 DOI: 10.1016/j.ebiom.2023.104581] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2022] [Revised: 03/19/2023] [Accepted: 04/05/2023] [Indexed: 05/02/2023] Open
Abstract
BACKGROUND Rheumatoid arthritis (RA) shares genetic variants with other autoimmune conditions, but existing studies test the association between RA variants with a pre-defined set of phenotypes. The objective of this study was to perform a large-scale, systemic screen to determine phenotypes that share genetic architecture with RA to inform our understanding of shared pathways. METHODS In the UK Biobank (UKB), we constructed RA genetic risk scores (GRS) incorporating human leukocyte antigen (HLA) and non-HLA risk alleles. Phenotypes were defined using groupings of International Classification of Diseases (ICD) codes. Patients with an RA code were excluded to mitigate the possibility of associations being driven by the diagnosis or management of RA. We performed a phenome-wide association study, testing the association between the RA GRS with phenotypes using multivariate generalized estimating equations that adjusted for age, sex, and first five principal components. Statistical significance was defined using Bonferroni correction. Results were replicated in an independent cohort and replicated phenotypes were validated using medical record review of patients. FINDINGS We studied n = 316,166 subjects from UKB without evidence of RA and screened for association between the RA GRS and n = 1317 phenotypes. In the UKB, 20 phenotypes were significantly associated with the RA GRS, of which 13 (65%) were immune mediated conditions including polymyalgia rheumatica, granulomatosis with polyangiitis (GPA), type 1 diabetes, and multiple sclerosis. We further identified a novel association in Celiac disease where the HLA and non-HLA alleles had strong associations in opposite directions. Strikingly, we observed that the non-HLA GRS was exclusively associated with greater risk of the validated conditions, suggesting shared underlying pathways outside the HLA region. INTERPRETATION This study replicated and identified novel autoimmune phenotypes verified by medical record review that share immune pathways with RA and may inform opportunities for shared treatment targets, as well as risk assessment for conditions with a paucity of genomic data, such as GPA. FUNDING This research was funded by the US National Institutes of Health (P30AR072577, R21AR078339, R35GM142879, T32AR007530) and the Harold and DuVal Bowen Fund.
Collapse
Affiliation(s)
- Harrison G Zhang
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA; Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Greg McDermott
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Thany Seyok
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Sicong Huang
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Kumar Dahal
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Sehi L'Yi
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Clara Lea-Bonzel
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Jacklyn Stratton
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Dana Weisenfeld
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Paul Monach
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA; VA Boston Healthcare System, Boston, MA, USA
| | - Soumya Raychaudhuri
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA; Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA; Center for Data Science, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA; Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA; Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Kun-Hsing Yu
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Tianrun Cai
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Jing Cui
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Chuan Hong
- Department of Biostatistics and Bioinformatics, Duke University, Durham, NC, USA
| | - Tianxi Cai
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA; VA Boston Healthcare System, Boston, MA, USA; Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Katherine P Liao
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA; Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA; VA Boston Healthcare System, Boston, MA, USA.
| |
Collapse
|
8
|
Ashburner JM, Chang Y, Wang X, Khurshid S, Anderson CD, Dahal K, Weisenfeld D, Cai T, Liao KP, Wagholikar KB, Murphy SN, Atlas SJ, Lubitz SA, Singer DE. Natural Language Processing to Improve Prediction of Incident Atrial Fibrillation Using Electronic Health Records. J Am Heart Assoc 2022; 11:e026014. [PMID: 35904194 PMCID: PMC9375475 DOI: 10.1161/jaha.122.026014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Background Models predicting atrial fibrillation (AF) risk, such as Cohorts for Heart and Aging Research in Genomic Epidemiology AF (CHARGE-AF), have not performed as well in electronic health records. Natural language processing (NLP) may improve models by using narrative electronic health record text. Methods and Results From a primary care network, we included patients aged ≥65 years with visits between 2003 and 2013 in development (n=32 960) and internal validation cohorts (n=13 992). An external validation cohort from a separate network from 2015 to 2020 included 39 051 patients. Model features were defined using electronic health record codified data and narrative data with NLP. We developed 2 models to predict 5-year AF incidence using (1) codified+NLP data and (2) codified data only and evaluated model performance. The analysis included 2839 incident AF cases in the development cohort and 1057 and 2226 cases in internal and external validation cohorts, respectively. The C-statistic was greater (P<0.001) in codified+NLP model (0.744 [95% CI, 0.735-0.753]) compared with codified-only (0.730 [95% CI, 0.720-0.739]) in the development cohort. In internal validation, the C-statistic of codified+NLP was modestly higher (0.735 [95% CI, 0.720-0.749]) compared with codified-only (0.729 [95% CI, 0.715-0.744]; P=0.06) and CHARGE-AF (0.717 [95% CI, 0.703-0.731]; P=0.002). Codified+NLP and codified-only were well calibrated, whereas CHARGE-AF underestimated AF risk. In external validation, the C-statistic of codified+NLP (0.750 [95% CI, 0.740-0.760]) remained higher (P<0.001) than codified-only (0.738 [95% CI, 0.727-0.748]) and CHARGE-AF (0.735 [95% CI, 0.725-0.746]). Conclusions Estimation of 5-year risk of AF can be modestly improved using NLP to incorporate narrative electronic health record data.
Collapse
Affiliation(s)
- Jeffrey M Ashburner
- Division of General Internal Medicine Massachusetts General Hospital Boston MA.,Harvard Medical School Boston MA
| | - Yuchiao Chang
- Division of General Internal Medicine Massachusetts General Hospital Boston MA.,Harvard Medical School Boston MA
| | - Xin Wang
- Cardiovascular Research Center Massachusetts General Hospital Boston MA
| | - Shaan Khurshid
- Cardiovascular Research Center Massachusetts General Hospital Boston MA.,Division of Cardiology Massachusetts General Hospital Boston MA
| | | | - Kumar Dahal
- Department of Rheumatology, Inflammation, and Immunity Brigham and Women's Hospital Boston MA
| | - Dana Weisenfeld
- Department of Rheumatology, Inflammation, and Immunity Brigham and Women's Hospital Boston MA
| | - Tianrun Cai
- Harvard Medical School Boston MA.,Department of Rheumatology, Inflammation, and Immunity Brigham and Women's Hospital Boston MA
| | - Katherine P Liao
- Harvard Medical School Boston MA.,Department of Rheumatology, Inflammation, and Immunity Brigham and Women's Hospital Boston MA
| | - Kavishwar B Wagholikar
- Harvard Medical School Boston MA.,Laboratory of Computer Science Massachusetts General Hospital Boston MA
| | - Shawn N Murphy
- Harvard Medical School Boston MA.,Research Information Science and Computing Mass General Brigham Somerville MA
| | - Steven J Atlas
- Division of General Internal Medicine Massachusetts General Hospital Boston MA.,Harvard Medical School Boston MA
| | - Steven A Lubitz
- Cardiovascular Research Center Massachusetts General Hospital Boston MA.,Cardiac Arrhythmia Service Massachusetts General Hospital Boston MA
| | - Daniel E Singer
- Division of General Internal Medicine Massachusetts General Hospital Boston MA.,Harvard Medical School Boston MA
| |
Collapse
|
9
|
Weber B, Weisenfeld D, Seyok T, Huang S, Massarotti E, Barrett L, Bibbo C, Solomon DH, Plutzky J, Bolster M, Di Carli M, Liao KP. Relationship Between Risk of Atherosclerotic Cardiovascular Disease, Inflammation, and Coronary Microvascular Dysfunction in Rheumatoid Arthritis. J Am Heart Assoc 2022; 11:e025467. [PMID: 35657008 PMCID: PMC9238711 DOI: 10.1161/jaha.121.025467] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Affiliation(s)
- Brittany Weber
- Heart and Vascular Center Division of Cardiovascular Medicine Department of Medicine Brigham and Women's HospitalHarvard Medical School Boston MA
| | - Dana Weisenfeld
- Division of Rheumatology, Inflammation, and Immunity Brigham and Women's Hospital Harvard Medical School Boston MA
| | - Thany Seyok
- Division of Rheumatology, Inflammation, and Immunity Brigham and Women's Hospital Harvard Medical School Boston MA
| | - Sicong Huang
- Division of Rheumatology, Inflammation, and Immunity Brigham and Women's Hospital Harvard Medical School Boston MA
| | - Elena Massarotti
- Division of Rheumatology, Inflammation, and Immunity Brigham and Women's Hospital Harvard Medical School Boston MA
| | - Leanne Barrett
- Division of Rheumatology, Inflammation, and Immunity Brigham and Women's Hospital Harvard Medical School Boston MA
| | - Courtney Bibbo
- Division of Rheumatology, Inflammation, and Immunity Brigham and Women's Hospital Harvard Medical School Boston MA
| | - Daniel H Solomon
- Division of Rheumatology, Inflammation, and Immunity Brigham and Women's Hospital Harvard Medical School Boston MA
| | - Jorge Plutzky
- Heart and Vascular Center Division of Cardiovascular Medicine Department of Medicine Brigham and Women's HospitalHarvard Medical School Boston MA
| | - Marcy Bolster
- Division of Rheumatology, Allergy and Immunology Massachusetts General HospitalHarvard Medical School Boston MA
| | - Marcelo Di Carli
- Heart and Vascular Center Division of Cardiovascular Medicine Department of Medicine Brigham and Women's HospitalHarvard Medical School Boston MA.,Cardiovascular Imaging Program Division of Nuclear Medicine and Molecular Imaging Department of Radiology Brigham and Women's HospitalHarvard Medical School Boston MA
| | - Katherine P Liao
- Division of Rheumatology, Inflammation, and Immunity Brigham and Women's Hospital Harvard Medical School Boston MA
| |
Collapse
|
10
|
Weber B, He Z, Yang N, Playford MP, Weisenfeld D, Iannaccone C, Coblyn J, Weinblatt M, Shadick N, Di Carli M, Mehta NN, Plutzky J, Liao KP. Divergence of Cardiovascular Biomarkers of Lipids and Subclinical Myocardial Injury Among Rheumatoid Arthritis Patients With Increased Inflammation. Arthritis Rheumatol 2021; 73:970-979. [PMID: 33615723 DOI: 10.1002/art.41613] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2020] [Accepted: 12/03/2020] [Indexed: 11/10/2022]
Abstract
OBJECTIVE Patients with rheumatoid arthritis (RA) are 1.5 times more likely to develop cardiovascular disease (CVD) attributed to chronic inflammation. A decrease in inflammation in patients with RA is associated with increased low-density lipoprotein (LDL) cholesterol. This study was undertaken to prospectively evaluate the changes in lipid levels among RA patients experiencing changes in inflammation and determine the association with concomitant temporal patterns in markers of myocardial injury. METHODS A total of 196 patients were evaluated in a longitudinal RA cohort, with blood samples and high-sensitivity C-reactive protein (hsCRP) levels measured annually. Patients were stratified based on whether they experienced either a significant increase in inflammation (an increase in hsCRP of ≥10 mg/liter between any 2 time points 1 year apart; designated the increased inflammation cohort [n = 103]) or decrease in inflammation (a decrease in hsCRP of ≥10 mg/liter between any 2 time points 1 year apart; designated the decreased inflammation cohort [n = 93]). Routine and advanced lipids, markers of inflammation (interleukin-6, hsCRP, soluble tumor necrosis factor receptor II), and markers of subclinical myocardial injury (high-sensitivity cardiac troponin T [hs-cTnT], N-terminal pro-brain natriuretic peptide) were measured. RESULTS Among the patients in the increased inflammation cohort, the mean age was 59 years, 81% were women, and the mean RA disease duration was 17.9 years. The average increase in hsCRP levels was 36 mg/liter, and this increase was associated with significant reductions in LDL cholesterol, triglycerides, total cholesterol, apolipoprotein (Apo B), and Apo A-I levels. In the increased inflammation cohort at baseline, 45.6% of patients (47 of 103) had detectable circulating hs-cTnT, which further increased during inflammation (P = 0.02). In the decreased inflammation cohort, hs-cTnT levels remained stable despite a reduction in inflammation over follow-up. In both cohorts, hs-cTnT levels were associated with the overall estimated risk of CVD. CONCLUSION Among RA patients who experienced an increase in inflammation, a significant decrease in routinely measured lipids, including LDL cholesterol, and an increase in markers of subclinical myocardial injury were observed. These findings highlight the divergence in biomarkers of CVD risk and suggest a role in future studies examining the benefit of including hs-cTnT for CVD risk stratification in RA.
Collapse
Affiliation(s)
- Brittany Weber
- Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts
| | - Zeling He
- Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts
| | - Nicole Yang
- Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts
| | | | - Dana Weisenfeld
- Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts
| | | | - Jonathan Coblyn
- Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts
| | - Michael Weinblatt
- Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts
| | - Nancy Shadick
- Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts
| | - Marcelo Di Carli
- Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts
| | - Nehal N Mehta
- National Heart, Lung, and Blood Institute, NIH, Bethesda, Maryland
| | - Jorge Plutzky
- Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts
| | - Katherine P Liao
- Brigham and Women's Hospital, Harvard Medical School, and VA Boston Healthcare System, Boston, Massachusetts
| |
Collapse
|