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Methotrexate Disposition, Anti-Folate Activity, and Metabolomic Profiling to Identify Molecular Markers of Disease Activity and Drug Response in the Collagen-Induced Arthritis Mouse Model.

ABSTRACT: Methotrexate (MTX) is widely used in the treatment of autoimmune arthritis but is limited by its unpredictable and variable response profile. Currently, no biomarkers exist to predict or monitor early therapeutic responses to MTX. Using a collagen-induced arthritis (CIA) mouse model, this study aimed to identify biochemical pathways and biomarkers associated with MTX efficacy in autoimmune arthritis. Following arthritis disease induction, DBA/1J mice were treated with subcutaneous MTX (20 mg/kg/week) and disease activity was assessed based on disease activity scores (DAS) and paw volume (PV) measurements. Red blood cell (RBC) and plasma samples were collected at the end of the study and were assessed for folate and MTX content. Plasma samples were analyzed by semitargeted global metabolomic profiling and analyzed by univariate and multivariate analysis. Treatment with MTX was associated with significant reductions in disease activity based on both DAS (p = 0.0006) and PV (p = 0.0006). MTX therapy resulted in significant reductions in 5-methyltetrahydrofolate (5mTHF) levels in plasma (p = 0.02) and RBCs (p = 0.001). Reductions in both RBC and plasma 5mTHF were associated with lower DAS (p = 0.0007, p = 0.01, respectively) and PV (p = 0.001, p = 0.005, respectively). Increases in RBC MTX were associated with lower DAS (p = 0.003) but not PV (p = 0.23). Metabolomic analysis identified N-methylisoleucine (NMI) and quinolone as metabolites significantly altered in disease mice, which were corrected towards healthy control levels in mice treated with MTX. Reductions in plasma NMI were associated with lower DAS (p = 0.0002) and PV (p = 9.5 × 10^-6). Increases in plasma quinolone were associated with lower DAS (p = 0.02) and PV (p = 0.01). Receiver-operating characteristic curve analysis identified plasma NMI (AUC = 1.00, p = 2.4 × 10^-8), RBC 5mTHF (AUC = 0.99, p = 2.4 × 10^-5), and plasma quinolone (AUC = 0.89, p = 0.01) as top discriminating metabolites of MTX treatment. Our data support a relationship between MTX efficacy and its effect on circulating folates and identified 5mTHF, NMI, and quinolone as potential therapeutic biomarkers of disease activity and MTX response in the CIA mouse model of autoimmune arthritis.

SUBMITTER: Salamoun YM

PROVIDER: S-EPMC8780148 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundRheumatoid arthritis (RA) is a chronic, autoimmune disorder characterized by joint inflammation and pain. In patients with RA, metabolomic approaches, i.e., high-throughput profiling of small-molecule metabolites, on plasma or serum has thus far enabled the discovery of biomarkers for clinical subgroups, risk factors, and predictors of treatment response. Despite these recent advancements, the identification of blood metabolites that reflect quantitative disease activity remains an important challenge in precision medicine for RA. Herein, we use global plasma metabolomic profiling analyses to detect metabolites associated with, and predictive of, quantitative disease activity in patients with RA.MethodsUltra-high-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) was performed on a discovery cohort consisting of 128 plasma samples from 64 RA patients and on a validation cohort of 12 samples from 12 patients. The resulting metabolomic profiles were analyzed with two different strategies to find metabolites associated with RA disease activity defined by the Disease Activity Score-28 using C-reactive protein (DAS28-CRP). More specifically, mixed-effects regression models were used to identify metabolites differentially abundant between two disease activity groups ("lower", DAS28-CRP ≤ 3.2; and "higher", DAS28-CRP > 3.2) and to identify metabolites significantly associated with DAS28-CRP scores. A generalized linear model (GLM) was then constructed for estimating DAS28-CRP using plasma metabolite abundances. Finally, for associating metabolites with CRP (an indicator of inflammation), metabolites differentially abundant between two patient groups ("low-CRP", CRP ≤ 3.0 mg/L; "high-CRP", CRP > 3.0 mg/L) were investigated.ResultsWe identified 33 metabolites differentially abundant between the lower and higher disease activity groups (P < 0.05). Additionally, we identified 51 metabolites associated with DAS28-CRP (P < 0.05). A GLM based upon these 51 metabolites resulted in higher prediction accuracy (mean absolute error [MAE] ± SD: 1.51 ± 1.77) compared to a GLM without feature selection (MAE ± SD: 2.02 ± 2.21). The predictive value of this feature set was further demonstrated on a validation cohort of twelve plasma samples, wherein we observed a stronger correlation between predicted and actual DAS28-CRP (with feature selection: Spearman's ρ = 0.69, 95% CI: [0.18, 0.90]; without feature selection: Spearman's ρ = 0.18, 95% CI: [-0.44, 0.68]). Lastly, among all identified metabolites, the abundances of eight were significantly associated with the CRP patient groups while controlling for potential confounders (P < 0.05).ConclusionsWe demonstrate for the first time the prediction of quantitative disease activity in RA using plasma metabolomes. The metabolites identified herein provide insight into circulating pro-/anti-inflammatory metabolic signatures that reflect disease activity and inflammatory status in RA patients.

Project description:BackgroundThere are currently no validated criteria that entirely explain or predict response to methotrexate (MTX) treatment in rheumatoid arthritis (RA). We tried to identify the connection between three variants (RFC1 G80A (rs1051266), TYMS 2R/3R (rs34743033), and ATIC C347G (rs2372536)) in the folate pathway of MTX metabolism and the response to MTX monotherapy in a cohort of RA cases.MethodsA prospective study on 100 RA patients on MTX monotherapy was performed. Disease activity was measured at the start of treatment and 6 months after treatment with MTX. The patients were then split into two groups: those who responded to the treatment and those who did not. The molecular genetic study for the RFC1 (G80A) variant was employed via the PCR-restriction fragment length polymorphism (PCR-RFLP) technique, the ATIC (C347G) variant was performed using TaqMan allelic discrimination real-time PCR, and the tandem repeat sequences of TYMS (2R/3R) were amplified by conventional PCR and detected by agarose gel electrophoresis.ResultsThe genotype distribution of RFC-1 (G80A) showed significant variations among non-responders and responders in the recessive genetic model. A significant difference was found in TYMS (2R/3R) in the dominant and heterozygous genetic models. However, ATIC (C347G) genotype frequency did not exhibit substantial link with drug response in all genetic models. Furthermore, the genotype and allele rates of the analyzed variants did not show any significant association with adverse events in all genetic models.ConclusionThe 80AA genotype of RFC-1 G80A and the 2R/3R or 3R/3R genotypes of TYMS 2R/3R are more vulnerable to the good consequences of MTX therapy. Key Points • Current recommendations support the gold standard role of MTX as a first-line monotherapy for RA patients. However, up to 40% of RA patients do not respond or exhibit partial response to MTX. • Persistent disease activity due to treatment unresponsiveness will affect the long-term outcomes in RA patients. • We aimed, through molecular genetic study, to identify the connection between three variants in the folate pathway of MTX metabolism and the response to methotrexate monotherapy in a cohort of RA patients.

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Methotrexate Disposition, Anti-Folate Activity, and Metabolomic Profiling to Identify Molecular Markers of Disease Activity and Drug Response in the Collagen-Induced Arthritis Mouse Model.

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