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Serum metabolomic profiling predicts synovial gene expression in rheumatoid arthritis.

ABSTRACT: BACKGROUND:Metabolomics is an emerging field of biomedical research that may offer a better understanding of the mechanisms of underlying conditions including inflammatory arthritis. Perturbations caused by inflamed synovial tissue can lead to correlated changes in concentrations of certain metabolites in the synovium and thereby function as potential biomarkers in blood. Here, we explore the hypothesis of whether characterization of patients' metabolomic profiles in blood, utilizing 1H-nuclear magnetic resonance (NMR), predicts synovial marker profiling in rheumatoid arthritis (RA). METHODS:Nineteen active, seropositive patients with RA, on concomitant methotrexate, were studied. One of the involved joints was a knee or a wrist appropriate for arthroscopy. A Bruker Avance 700 MHz spectrometer was used to acquire NMR spectra of serum samples. Gene expression in synovial tissue obtained by arthroscopy was analyzed by real-time PCR. Data processing and statistical analysis were performed in Python and SPSS. RESULTS:Analysis of the relationships between each synovial marker-metabolite pair using linear regression and controlling for age and gender revealed significant clustering within the data. We observed an association of serine/glycine/phenylalanine metabolism and aminoacyl-tRNA biosynthesis with lymphoid cell gene signature. Alanine/aspartate/glutamate metabolism and choline-derived metabolites correlated with TNF-? synovial expression. Circulating ketone bodies were associated with gene expression of synovial metalloproteinases. Discriminant analysis identified serum metabolites that classified patients according to their synovial marker levels. CONCLUSION:The relationship between serum metabolite profiles and synovial biomarker profiling suggests that NMR may be a promising tool for predicting specific pathogenic pathways in the inflamed synovium of patients with RA.

SUBMITTER: Narasimhan R

PROVIDER: S-EPMC6091066 | biostudies-literature | 2018 Aug

REPOSITORIES: biostudies-literature

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Serum metabolomic profiling predicts synovial gene expression in rheumatoid arthritis.

Narasimhan Rekha R Coras Roxana R Rosenthal Sara B SB Sweeney Shannon R SR Lodi Alessia A Tiziani Stefano S Boyle David D Kavanaugh Arthur A Guma Monica M

Arthritis research & therapy 20180803 1

<h4>Background</h4>Metabolomics is an emerging field of biomedical research that may offer a better understanding of the mechanisms of underlying conditions including inflammatory arthritis. Perturbations caused by inflamed synovial tissue can lead to correlated changes in concentrations of certain metabolites in the synovium and thereby function as potential biomarkers in blood. Here, we explore the hypothesis of whether characterization of patients' metabolomic profiles in blood, utilizing <su ...[more]

PMID: 30075744

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Project description:OBJECTIVE:Currently, there are no reliable biomarkers for predicting therapeutic response in patients with rheumatoid arthritis (RA). The synovium may unlock critical information for determining efficacy, since a reduction in the numbers of sublining synovial macrophages remains the most reproducible biomarker. Thus, a clinically actionable method for the collection of synovial tissue, which can be analyzed using high-throughput strategies, must become a reality. This study was undertaken to assess the feasibility of utilizing synovial biopsies as a precision medicine-based approach for patients with RA. METHODS:Rheumatologists at 6 US academic sites were trained in minimally invasive ultrasound-guided synovial tissue biopsy. Biopsy specimens obtained from patients with RA and synovial tissue from patients with osteoarthritis (OA) were subjected to histologic analysis, fluorescence-activated cell sorting, and RNA sequencing (RNA-seq). An optimized protocol for digesting synovial tissue was developed to generate high-quality RNA-seq libraries from isolated macrophage populations. Associations were determined between macrophage transcriptional profiles and clinical parameters in RA patients. RESULTS:Patients with RA reported minimal adverse effects in response to synovial biopsy. Comparable RNA quality was observed from synovial tissue and isolated macrophages between patients with RA and patients with OA. Whole tissue samples from patients with RA demonstrated a high degree of transcriptional heterogeneity. In contrast, the transcriptional profile of isolated RA synovial macrophages highlighted different subpopulations of patients and identified 6 novel transcriptional modules that were associated with disease activity and therapy. CONCLUSION:Performance of synovial tissue biopsies by rheumatologists in the US is feasible and generates high-quality samples for research. Through the use of cutting-edge technologies to analyze synovial biopsy specimens in conjunction with corresponding clinical information, a precision medicine-based approach for patients with RA is attainable.

Dataset Information

Serum metabolomic profiling predicts synovial gene expression in rheumatoid arthritis.

Publications

Serum metabolomic profiling predicts synovial gene expression in rheumatoid arthritis.

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