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Efficacy of Integrating a Novel 16-Gene Biomarker Panel and Intelligence Classifiers for Differential Diagnosis of Rheumatoid Arthritis and Osteoarthritis.

ABSTRACT: Introducing novel biomarkers for accurately detecting and differentiating rheumatoid arthritis (RA) and osteoarthritis (OA) using clinical samples is essential. In the current study, we searched for a novel data-driven gene signature of synovial tissues to differentiate RA from OA patients. Fifty-three RA, 41 OA, and 25 normal microarray-based transcriptome samples were utilized. The area under the curve random forests (RF) variable importance measurement was applied to seek the most influential differential genes between RA and OA. Five algorithms including RF, k-nearest neighbors (kNN), support vector machines (SVM), naïve-Bayes, and a tree-based method were employed for the classification. We found a 16-gene signature that could effectively differentiate RA from OA, including TMOD1, POP7, SGCA, KLRD1, ALOX5, RAB22A, ANK3, PTPN3, GZMK, CLU, GZMB, FBXL7, TNFRSF4, IL32, MXRA7, and CD8A. The externally validated accuracy of the RF model was 0.96 (sensitivity = 1.00, specificity = 0.90). Likewise, the accuracy of kNN, SVM, naïve-Bayes, and decision tree was 0.96, 0.96, 0.96, and 0.91, respectively. Functional meta-analysis exhibited the differential pathological processes of RA and OA; suggested promising targets for further mechanistic and therapeutic studies. In conclusion, the proposed genetic signature combined with sophisticated classification methods may improve the diagnosis and management of RA patients.

SUBMITTER: Long NP

PROVIDER: S-EPMC6352223 | biostudies-literature | 2019 Jan

REPOSITORIES: biostudies-literature

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Efficacy of Integrating a Novel 16-Gene Biomarker Panel and Intelligence Classifiers for Differential Diagnosis of Rheumatoid Arthritis and Osteoarthritis.

Long Nguyen Phuoc NP Park Seongoh S Anh Nguyen Hoang NH Min Jung Eun JE Yoon Sang Jun SJ Kim Hyung Min HM Nghi Tran Diem TD Lim Dong Kyu DK Park Jeong Hill JH Lim Johan J Kwon Sung Won SW

Journal of clinical medicine 20190106 1

Introducing novel biomarkers for accurately detecting and differentiating rheumatoid arthritis (RA) and osteoarthritis (OA) using clinical samples is essential. In the current study, we searched for a novel data-driven gene signature of synovial tissues to differentiate RA from OA patients. Fifty-three RA, 41 OA, and 25 normal microarray-based transcriptome samples were utilized. The area under the curve random forests (RF) variable importance measurement was applied to seek the most influential ...[more]

PMID: 30621359

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Project description:BACKGROUND:Rheumatoid arthritis and osteoarthritis are two common musculoskeletal disorders that affect the joints. Despite high prevalence rates, etiological factors involved in these disorders remain largely unknown. Dissecting the molecular aspects of these disorders will significantly contribute to improving their diagnosis and clinical management. In order to identify proteins that are differentially expressed between these two conditions, a quantitative proteomic profiling of synovial fluid obtained from rheumatoid arthritis and osteoarthritis patients was carried out by using iTRAQ labeling followed by high resolution mass spectrometry analysis. RESULTS:We have identified 575 proteins out of which 135 proteins were found to be differentially expressed by ?3-fold in the synovial fluid of rheumatoid arthritis and osteoarthritis patients. Proteins not previously reported to be associated with rheumatoid arthritis including, coronin-1A (CORO1A), fibrinogen like-2 (FGL2), and macrophage capping protein (CAPG) were found to be upregulated in rheumatoid arthritis. Proteins such as CD5 molecule-like protein (CD5L), soluble scavenger receptor cysteine-rich domain-containing protein (SSC5D), and TTK protein kinase (TTK) were found to be upregulated in the synovial fluid of osteoarthritis patients. We confirmed the upregulation of CAPG in rheumatoid arthritis synovial fluid by multiple reaction monitoring assay as well as by Western blot. Pathway analysis of differentially expressed proteins revealed a significant enrichment of genes involved in glycolytic pathway in rheumatoid arthritis. CONCLUSIONS:We report here the largest identification of proteins from the synovial fluid of rheumatoid arthritis and osteoarthritis patients using a quantitative proteomics approach. The novel proteins identified from our study needs to be explored further for their role in the disease pathogenesis of rheumatoid arthritis and osteoarthritis.Sartaj Ahmad and Raja Sekhar Nirujogi contributed equally to this article.

Project description:ObjectiveExaggerated neutrophil activation and formation of neutrophil extracellular traps (NETs) are linked to inflammation and autoimmunity, including rheumatoid arthritis (RA). However, whether NETs are present in the circulation of RA patients and contribute to inflammation and disease progression has not been carefully addressed. We undertook this study to assess markers of neutrophil activation and NET formation in plasma samples, investigating whether they add clinical value in improving the determination of prognosis and monitoring in RA patients.MethodsMarkers of neutrophil activation (calprotectin) and cell death (NETs) were analyzed, using enzyme-linked immunosorbent assay, in serum and plasma obtained from patients in 3 cross-sectional RA cohorts and sex-matched healthy controls. A longitudinal inception cohort (n = 247), seen for a median follow-up of 8 years, was used for predictive analyses.ResultsMarkers of neutrophil activation and cell death were increased in RA patients compared to healthy individuals (P < 0.0001). Calprotectin levels correlated with the Clinical Disease Activity Index (r = 0.53, P < 0.0001) and could be used to distinguish between patients with disease in remission and those with active disease, an observation not seen when examining C-reactive protein levels. A biomarker panel consisting of anti-citrullinated protein antibody and calprotectin could predict erosive disease (odds ratio [OR] 7.5, P < 0.0001) and joint space narrowing (OR 4.9, P = 0.001). NET levels were associated with markers of inflammation (P = 0.0002). Furthermore, NETs and a "neutrophil activation signature" biomarker panel had good predictive value in identifying patients who were developing extraarticular nodules (OR 5.6, P = 0.006).ConclusionNeutrophils undergo marked activation and cell death in RA. Neutrophil biomarkers can provide added clinical value in the monitoring and prognosis of RA patients and may allow for early preventive treatment intervention.

Project description:Biologic drug therapies represent a huge advance in the treatment of rheumatoid arthritis (RA). However, very good disease control is achieved in only 30% of patients, making identification of biomarkers of response a research priority. We undertook this study to test our hypothesis that differential DNA methylation patterns may provide biomarkers predictive of response to tumor necrosis factor inhibitor (TNFi) therapy in patients with RA.An epigenome-wide association study was performed on pretreatment whole blood DNA from patients with RA. Patients who displayed good response (n?=?36) or no response (n?=?36) to etanercept therapy at 3 months were selected. Differentially methylated positions were identified using linear regression. Variance of methylation at differentially methylated positions was assessed for correlation with cis-acting single-nucleotide polymorphisms (SNPs). A replication experiment for prioritized SNPs was performed in an independent cohort of 1,204 RA patients.Five positions that were differentially methylated between responder groups were identified, with a false discovery rate of <5%. The top 2 differentially methylated positions mapped to exon 7 of the LRPAP1 gene on chromosome 4 (cg04857395, P?=?1.39 × 10(-8) and cg26401028, P?=?1.69 × 10(-8) ). The A allele of the SNP rs3468 was correlated with higher levels of methylation for both of the top 2 differentially methylated positions (P?=?2.63 × 10(-7) and P?=?1.05 × 10(-6) , respectively). Furthermore, the A allele of rs3468 was correlated with European League Against Rheumatism nonresponse in the discovery cohort (P?=?0.03; n?=?56) and in the independent replication cohort (P?=?0.003; n?=?1,204).We identify DNA methylation as a potential biomarker of response to TNFi therapy, and we report the association between response and the LRPAP1 gene, which encodes a chaperone of low-density lipoprotein receptor-related protein 1. Additional replication experiments in independent sample collections are now needed.

Project description:IntroductionThe risk of cardiovascular disease (CVD) in patients with rheumatoid arthritis (RA) is 1.5-2 times higher than the general population. The fundamental risk factor for CVD is age, related to alterations at the arterial level. The aim of the study was to compare vascular age (VA) in RA patients under a strict treat-to-target (T2T) strategy with Osteoarthritis (OA) patients without strict follow up and to assess the influence of inflammaging (chronic, sterile, low-grade inflammation related to aging) and metabolic markers on VA.Materials and methodsThis was an analytical cross-sectional study. Patients with RA (under a strict a T2T strategy) and OA patients without strict clinical follow-up were included. Patients with a history of uncontrolled hypertension, CVD, and/or current smoking were excluded. Sociodemographic, physical activity, and toxic exposure data were obtained. Waist-hip ratio and body mass index (BMI) were measured. DAS-28 (RA) and inflammatory markers, lipid profile, and glycaemia were analyzed. Pulse wave velocity (PWV) was measured (oscillometric method, Arteriograph-TensioMed®). VA was calculated based on PWV. Eleven components of inflammaging [six interleukins, three metalloproteinases (MMP), and two tissue inhibitors of metalloproteinases (TIMP)] were evaluated (Luminex® system). Univariate and bivariate analyzes (Mann Whitney U and chi-square) and correlations (Spearmans Rho) were done to compare the two groups.ResultsA total of 106 patients (74% women) were included, 52/RA and 54/OA. The mean age was 57 (Interquartile range - IQR 9 years). The BMI, waist circumference, and weight were higher in patients with OA (p < 0.001). RA patients had low disease activity (DAS-28-CRP). There were no differences in VA, inflammaging nor in PWV between the two groups. VA had a positive, but weak correlation, with age and LDL. In group of RA, VA was higher in those who did not receive methotrexate (p = 0.013). LDL levels correlated with MMP1, TIMP1, and TIMP2.ConclusionsWhen comparing RA patients with low levels of disease activity with OA patients with poor metabolic control, there are no differences in VA. Furthermore, methotrexate also influences VA in RA patients. This shows that implemented therapies may have an impact on not only the inflammatory state of the joint but also CVD risk.

Dataset Information

Efficacy of Integrating a Novel 16-Gene Biomarker Panel and Intelligence Classifiers for Differential Diagnosis of Rheumatoid Arthritis and Osteoarthritis.

Publications

Efficacy of Integrating a Novel 16-Gene Biomarker Panel and Intelligence Classifiers for Differential Diagnosis of Rheumatoid Arthritis and Osteoarthritis.

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