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Adeogun G, Camai A, Suh A, Wheless L, Barnado A. Comparison of late-onset and non-late-onset systemic lupus erythematosus individuals in a real-world electronic health record cohort. Lupus 2024; 33:525-531. [PMID: 38454796 PMCID: PMC10954386 DOI: 10.1177/09612033241238052] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Accepted: 02/22/2024] [Indexed: 03/09/2024]
Abstract
Objective: Late-onset systemic lupus erythematosus (LO-SLE) is defined as SLE diagnosed at age 50 years or later. Current studies on LO-SLE are small and have conflicting results.Methods: Using a large, electronic health record (EHR)-based cohort of SLE individuals, we compared demographics, disease characteristics, SLE-specific antibodies, and medication prescribing practices in LO (n = 123) vs. NLO-SLE (n = 402) individuals.Results: The median age (interquartile range) at SLE diagnosis was 60 (56-67) years for LO-SLE and 28 (20-38) years for NLO-SLE. Both groups were predominantly female (85% vs. 91%, p = 0.10). LO-SLE individuals were more likely to be White than NLO-SLE individuals (74% vs. 60%, p = 0.005) and less likely to have positive dsDNA (39% vs. 58%, p = 0.001) and RNP (17% vs. 32%, p = 0.02) with no differences in Smith, SSA, and SSB. Autoantibody positivity declined with increasing age at SLE diagnosis. LO-SLE individuals were less likely to develop SLE nephritis (9% vs. 29%, p < 0.001) and less likely to be prescribed multiple classes of SLE medications including antimalarials (90% vs. 95%, p = 0.04), azathioprine (17% vs. 31%, p = 0.002), mycophenolate mofetil (12% vs. 38%, p < 0.001), and belimumab (2% vs. 8%, p = 0.02).Conclusion: LO-SLE individuals may be less likely to fit an expected course for SLE with less frequent positive autoantibodies at diagnosis and lower rates of nephritis, even after adjusting for race. Understanding how age impacts SLE disease presentation could help reduce diagnostic delays in SLE.
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Affiliation(s)
- Ganiat Adeogun
- Division of Rheumatology & Immunology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Alex Camai
- Division of Rheumatology & Immunology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Ashley Suh
- Division of Rheumatology & Immunology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Lee Wheless
- Research Service, Tennessee Valley Healthcare System Veterans Administration Medical Center, Nashville, TN, USA
- Department of Dermatology, Division of Epidemiology, Vanderbilt University Medical Center, Nashville, TN, USA
| | - April Barnado
- Division of Rheumatology & Immunology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
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Barnado A, Moore RP, Domenico HJ, Green S, Camai A, Suh A, Han B, Walker K, Anderson A, Caruth L, Katta A, McCoy AB, Byrne DW. Identifying antinuclear antibody positive individuals at risk for developing systemic autoimmune disease: development and validation of a real-time risk model. Front Immunol 2024; 15:1384229. [PMID: 38571954 PMCID: PMC10987951 DOI: 10.3389/fimmu.2024.1384229] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2024] [Accepted: 03/08/2024] [Indexed: 04/05/2024] Open
Abstract
Objective Positive antinuclear antibodies (ANAs) cause diagnostic dilemmas for clinicians. Currently, no tools exist to help clinicians interpret the significance of a positive ANA in individuals without diagnosed autoimmune diseases. We developed and validated a risk model to predict risk of developing autoimmune disease in positive ANA individuals. Methods Using a de-identified electronic health record (EHR), we randomly chart reviewed 2,000 positive ANA individuals to determine if a systemic autoimmune disease was diagnosed by a rheumatologist. A priori, we considered demographics, billing codes for autoimmune disease-related symptoms, and laboratory values as variables for the risk model. We performed logistic regression and machine learning models using training and validation samples. Results We assembled training (n = 1030) and validation (n = 449) sets. Positive ANA individuals who were younger, female, had a higher titer ANA, higher platelet count, disease-specific autoantibodies, and more billing codes related to symptoms of autoimmune diseases were all more likely to develop autoimmune diseases. The most important variables included having a disease-specific autoantibody, number of billing codes for autoimmune disease-related symptoms, and platelet count. In the logistic regression model, AUC was 0.83 (95% CI 0.79-0.86) in the training set and 0.75 (95% CI 0.68-0.81) in the validation set. Conclusion We developed and validated a risk model that predicts risk for developing systemic autoimmune diseases and can be deployed easily within the EHR. The model can risk stratify positive ANA individuals to ensure high-risk individuals receive urgent rheumatology referrals while reassuring low-risk individuals and reducing unnecessary referrals.
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Affiliation(s)
- April Barnado
- Division of Rheumatology & Immunology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, United States
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Ryan P. Moore
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Henry J. Domenico
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Sarah Green
- Division of Rheumatology & Immunology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Alex Camai
- Division of Rheumatology & Immunology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Ashley Suh
- Division of Rheumatology & Immunology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Bryan Han
- Division of Rheumatology & Immunology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Katherine Walker
- Division of Rheumatology & Immunology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Audrey Anderson
- Division of Rheumatology & Immunology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Lannawill Caruth
- Division of Rheumatology & Immunology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Anish Katta
- Division of Rheumatology & Immunology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Allison B. McCoy
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Daniel W. Byrne
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, United States
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, United States
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Reynolds JA, Li Y, Herlitz L, Mohan C, Putterman C. Novel biomarker discovery through comprehensive proteomic analysis of lupus mouse serum. J Autoimmun 2024; 142:103134. [PMID: 37944214 PMCID: PMC10957328 DOI: 10.1016/j.jaut.2023.103134] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2023] [Revised: 10/11/2023] [Accepted: 10/13/2023] [Indexed: 11/12/2023]
Abstract
OBJECTIVES The difficulty of monitoring organ-specific pathology in systemic lupus erythematosus (SLE) often complicates disease prognostication and treatment. Improved non-invasive biomarkers of active organ pathology, particularly lupus nephritis, would improve patient care. We sought to validate and apply a novel strategy to generate the first comprehensive serum proteome of a lupus mouse model and identify mechanism-linked lupus biomarker candidates for subsequent clinical investigation. METHODS Serum levels of 1308 diverse proteins were measured in eight adult female MRL/lpr lupus mice and eight control MRL/mpj mice. ELISA validation confirmed fold increases. Protein enrichment analysis provided biological relevance to findings. Individual protein levels were correlated with measures of lymphoproliferative, humoral, and renal disease. RESULTS Four hundred and six proteins were increased in MRL/lpr serum, including proteins increased in human SLE such as VCAM-1, L-selectin, TNFRI/II, TWEAK, CXCL13, MCP-1, IP-10, IL-10, and TARC. Newly validated proteins included IL-6, IL-17, and MDC. Results of pathway enrichment analysis, which revealed enhancement of cytokine signaling and immune cell migration, reinforced the similarity of the MRL/lpr disease to human pathology. Fifty-two proteins positively correlated with at least one measure of lupus-like disease. TECK, TSLP, PDGFR-alpha, and MDC were identified as novel candidate biomarkers of renal disease. CONCLUSIONS We successfully validated a novel serum proteomic screening strategy in a spontaneous murine lupus model that highlighted potential new biomarkers. Importantly, we generated a comprehensive snapshot of the serum proteome which will enable identification of other candidates and serve as a reference for future mechanistic and therapeutic studies in lupus.
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Affiliation(s)
- Joshua A Reynolds
- Albert Einstein College of Medicine: 1300 Morris Park Ave, New York, NY, USA
| | - Yaxi Li
- University of Houston: 3517 Cullen Blvd, Houston, TX, USA
| | - Leal Herlitz
- Cleveland Clinic: 9500 Euclid Ave, Cleveland, OH, USA
| | - Chandra Mohan
- University of Houston: 3517 Cullen Blvd, Houston, TX, USA
| | - Chaim Putterman
- Albert Einstein College of Medicine: 1300 Morris Park Ave, New York, NY, USA; Azrieli Faculty of Medicine of Bar-Ilan University: 8 Henrietta Szold St, Zefat, Israel.
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Barnado A, Wheless L, Camai A, Green S, Han B, Katta A, Denny JC, Sawalha AH. Phenotype Risk Score but Not Genetic Risk Score Aids in Identifying Individuals With Systemic Lupus Erythematosus in the Electronic Health Record. Arthritis Rheumatol 2023; 75:1532-1541. [PMID: 37096581 PMCID: PMC10501317 DOI: 10.1002/art.42544] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2022] [Revised: 03/23/2023] [Accepted: 04/17/2023] [Indexed: 04/26/2023]
Abstract
OBJECTIVE Systemic lupus erythematosus (SLE) poses diagnostic challenges. We undertook this study to evaluate the utility of a phenotype risk score (PheRS) and a genetic risk score (GRS) to identify SLE individuals in a real-world setting. METHODS Using a de-identified electronic health record (EHR) database with an associated DNA biobank, we identified 789 SLE cases and 2,261 controls with available MEGAEX genotyping. A PheRS for SLE was developed using billing codes that captured American College of Rheumatology SLE criteria. We developed a GRS with 58 SLE risk single-nucleotide polymorphisms (SNPs). RESULTS SLE cases had a significantly higher PheRS (mean ± SD 7.7 ± 8.0 versus 0.8 ± 2.0 in controls; P < 0.001) and GRS (mean ± SD 12.2 ± 2.3 versus 11.0 ± 2.0 in controls; P < 0.001). Black individuals with SLE had a higher PheRS compared to White individuals (mean ± SD 10.0 ± 10.1 versus 7.1 ± 7.2, respectively; P = 0.002) but a lower GRS (mean ± SD 9.0 ± 1.4 versus 12.3 ± 1.7, respectively; P < 0.001). Models predicting SLE that used only the PheRS had an area under the curve (AUC) of 0.87. Adding the GRS to the PheRS resulted in a minimal difference with an AUC of 0.89. On chart review, controls with the highest PheRS and GRS had undiagnosed SLE. CONCLUSION We developed a SLE PheRS to identify established and undiagnosed SLE individuals. A SLE GRS using known risk SNPs did not add value beyond the PheRS and was of limited utility in Black individuals with SLE. More work is needed to understand the genetic risks of SLE in diverse populations.
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Affiliation(s)
- April Barnado
- Division of Rheumatology & Immunology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN
| | - Lee Wheless
- Department of Dermatology, Division of Epidemiology, Vanderbilt University Medical Center, Nashville, TN
| | - Alex Camai
- Division of Rheumatology & Immunology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN
| | - Sarah Green
- Division of Rheumatology & Immunology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN
| | - Bryan Han
- Division of Rheumatology & Immunology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN
| | - Anish Katta
- Division of Rheumatology & Immunology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN
| | - Joshua C. Denny
- All of Us Research Program, National Institutes of Health, Bethesda, MD
| | - Amr H. Sawalha
- Departments of Pediatrics, Medicine, and Immunology & Lupus Center of Excellence, University of Pittsburgh School of Medicine, Pittsburgh, PA
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Schattner A. Unusual Presentations of Systemic Lupus Erythematosus: A Narrative Review. Am J Med 2022; 135:1178-1187. [PMID: 35671786 DOI: 10.1016/j.amjmed.2022.05.020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/29/2021] [Revised: 05/01/2022] [Accepted: 05/16/2022] [Indexed: 11/01/2022]
Abstract
Systemic lupus erythematosus (SLE) is a chronic systemic autoimmune disease characterized by an almost 10:1 female predominance, the presence of deleterious nuclear autoantibodies, a tendency for flare, and striking protean manifestations. Early diagnosis is associated with less damage accrual, lower costs, and improved quality of life due to timely treatment. However, early disease may not uncommonly show nonspecific presentation, a single classification criterion, or an unusual organ involvement contributing to frequent, often substantial diagnostic delays. We reviewed the literature (1982-2022) to accumulate and classify all reports of rare, atypical, and unusual presentations. These can involve almost every organ and system, and thus, present to physicians in every discipline and setting. Increasing physicians' awareness of the potential of occult SLE to appear in varied, diverse, and unexpected presentations, may encourage the inclusion of SLE in the differential. Informed history and examination focusing on systemic and joint symptoms and mucocutaneous involvement, and basic tests (focusing on leukopenia, thrombocytopenia, and proteinuria; followed by antinuclear antibodies and complement levels) will correctly diagnose most patients on presentation or within the following months and enable timely treatment.
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Affiliation(s)
- Ami Schattner
- The Faculty of Medicine, Hebrew University and Hadassah Medical School, Jerusalem, Israel.
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Tan G, Baby B, Zhou Y, Wu T. Emerging Molecular Markers Towards Potential Diagnostic Panels for Lupus. Front Immunol 2022; 12:808839. [PMID: 35095896 PMCID: PMC8792845 DOI: 10.3389/fimmu.2021.808839] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2021] [Accepted: 12/22/2021] [Indexed: 11/13/2022] Open
Abstract
Systemic lupus erythematosus (SLE) is a multifactorial autoimmune disease which can affect various tissues and organs, posing significant challenges for clinical diagnosis and treatment. The etiology of SLE is highly complex with contributions from environmental factors, stochastic factors as well as genetic susceptibility. The current criteria for diagnosing SLE is based primarily on a combination of clinical presentations and traditional lab testing. However, these tests have suboptimal sensitivity and specificity. They are unable to indicate disease cause or guide physicians in decision-making for treatment. Therefore, there is an urgent need to develop a more accurate and robust tool for effective clinical management and drug development in lupus patients. It is fortunate that the emerging Omics have empowered scientists in the discovery and identification of potential novel biomarkers of SLE, especially the markers from blood, urine, cerebrospinal fluids (CSF), and other bodily fluids. However, many of these markers have not been carefully validated for clinical use. In addition, it is apparent that individual biomarkers lack sensitivity or specificity. This review summarizes the sensitivity, specificity and diagnostic value of emerging biomarkers from recent studies, and discusses the potential of these markers in the development of biomarker panel based diagnostics or disease monitoring system in SLE.
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Affiliation(s)
- Gongjun Tan
- Department of Clinical Laboratory, Zhuhai Maternal and Child Healthcare Hospital, Zhuhai, China
| | - Binila Baby
- Department of Biomedical Engineering, University of Houston, Houston, TX, United States
| | - Yuqiu Zhou
- Department of Clinical Laboratory, Zhuhai Maternal and Child Healthcare Hospital, Zhuhai, China
| | - Tianfu Wu
- Department of Biomedical Engineering, University of Houston, Houston, TX, United States
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Fritzler MJ, Choi MY, Satoh M, Mahler M. Autoantibody Discovery, Assay Development and Adoption: Death Valley, the Sea of Survival and Beyond. Front Immunol 2021; 12:679613. [PMID: 34122443 PMCID: PMC8191456 DOI: 10.3389/fimmu.2021.679613] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2021] [Accepted: 05/04/2021] [Indexed: 01/08/2023] Open
Abstract
Dating to the discovery of the Lupus Erythematosus (LE) cell in 1948, there has been a dramatic growth in the discovery of unique autoantibodies and their cognate targets, all of which has led to the availability and use of autoantibody testing for a broad spectrum of autoimmune diseases. Most studies of the sensitivity, specificity, commutability, and harmonization of autoantibody testing have focused on widely available, commercially developed and agency-certified autoantibody kits. However, this is only a small part of the spectrum of autoantibody tests that are provided through laboratories world-wide. This manuscript will review the wider spectrum of testing by exploring the innovation pathway that begins with autoantibody discovery followed by assessment of clinical relevance, accuracy, validation, and then consideration of regulatory requirements as an approved diagnostic test. Some tests are offered as "Research Use Only (RUO)", some as "Laboratory Developed Tests (LDT)", some enter Health Technology Assessment (HTA) pathways, while others are relegated to a "death valley" of autoantibody discovery and become "orphan" autoantibodies. Those that achieve regulatory approval are further threatened by the business world's "Darwinian Sea of Survival". As one example of the trappings of autoantibody progression or failure, it is reported that more than 200 different autoantibodies have been described in systemic lupus erythematosus (SLE), a small handful (~10%) of these have achieved regulatory approval and are widely available as commercial diagnostic kits, while a few others may be available as RUO or LDT assays. However, the vast majority (90%) are orphaned and languish in an autoantibody 'death valley'. This review proposes that it is important to keep an inventory of these "orphan autoantibodies" in 'death valley' because, with the increasing availability of multi-analyte arrays and artificial intelligence (MAAI), some can be rescued to achieve a useful role in clinical diagnostic especially in light of patient stratification and precision medicine.
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Affiliation(s)
- Marvin J Fritzler
- Department of Medicine, Cumming School of Medicine, Calgary, AB, Canada
| | - May Y Choi
- Department of Medicine, Cumming School of Medicine, Calgary, AB, Canada
| | - Minoru Satoh
- Department of Clinical Nursing, School of Health Sciences, University of Occupational and Environmental Health, Kitakyushu, Japan
| | - Michael Mahler
- Research and Development, Inova Diagnostics, San Diego, CA, United States
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