Preliminary study to identify the predictive factors for the response to methotrexate therapy in patients with rheumatoid arthritis

[Exploration of Education and Research on Drug Informatics]

I have been exploring methods for education and research on drug information for 43 years. There are various approaches to drug informatics research, which include collecting, evaluating, and analyzing information to solve drug related problems, sometimes producing new information from experiments and clinical research. All are based on information science. Drug informatics is information science from the viewpoint of pharmaceuticals. In addition to basic pharmacology, knowledge and skills such as epidemiology, data science, computer science, mathematical statistics, and communication studies are indispensable for the development of drug informatics.

Assessing prognosis and prediction of treatment response in early rheumatoid arthritis: systematic reviews

BACKGROUND

Rheumatoid arthritis (RA) is a chronic, debilitating disease associated with reduced quality of life and substantial costs. It is unclear which tests and assessment tools allow the best assessment of prognosis in people with early RA and whether or not variables predict the response of patients to different drug treatments.

OBJECTIVE

To systematically review evidence on the use of selected tests and assessment tools in patients with early RA (1) in the evaluation of a prognosis (review 1) and (2) as predictive markers of treatment response (review 2).

DATA SOURCES

Electronic databases (e.g. MEDLINE, EMBASE, The Cochrane Library, Web of Science Conference Proceedings; searched to September 2016), registers, key websites, hand-searching of reference lists of included studies and key systematic reviews and contact with experts.

STUDY SELECTION

Review 1 - primary studies on the development, external validation and impact of clinical prediction models for selected outcomes in adult early RA patients. Review 2 - primary studies on the interaction between selected baseline covariates and treatment (conventional and biological disease-modifying antirheumatic drugs) on salient outcomes in adult early RA patients.

RESULTS

Review 1 - 22 model development studies and one combined model development/external validation study reporting 39 clinical prediction models were included. Five external validation studies evaluating eight clinical prediction models for radiographic joint damage were also included. c-statistics from internal validation ranged from 0.63 to 0.87 for radiographic progression (different definitions, six studies) and 0.78 to 0.82 for the Health Assessment Questionnaire (HAQ). Predictive performance in external validations varied considerably. Three models [(1) Active controlled Study of Patients receiving Infliximab for the treatment of Rheumatoid arthritis of Early onset (ASPIRE) C-reactive protein (ASPIRE CRP), (2) ASPIRE erythrocyte sedimentation rate (ASPIRE ESR) and (3) Behandelings Strategie (BeSt)] were externally validated using the same outcome definition in more than one population. Results of the random-effects meta-analysis suggested substantial uncertainty in the expected predictive performance of models in a new sample of patients. Review 2 - 12 studies were identified. Covariates examined included anti-citrullinated protein/peptide anti-body (ACPA) status, smoking status, erosions, rheumatoid factor status, C-reactive protein level, erythrocyte sedimentation rate, swollen joint count (SJC), body mass index and vascularity of synovium on power Doppler ultrasound (PDUS). Outcomes examined included erosions/radiographic progression, disease activity, physical function and Disease Activity Score-28 remission. There was statistical evidence to suggest that ACPA status, SJC and PDUS status at baseline may be treatment effect modifiers, but not necessarily that they are prognostic of response for all treatments. Most of the results were subject to considerable uncertainty and were not statistically significant.

LIMITATIONS

The meta-analysis in review 1 was limited by the availability of only a small number of external validation studies. Studies rarely investigated the interaction between predictors and treatment.

SUGGESTED RESEARCH PRIORITIES

Collaborative research (including the use of individual participant data) is needed to further develop and externally validate the clinical prediction models. The clinical prediction models should be validated with respect to individual treatments. Future assessments of treatment by covariate interactions should follow good statistical practice.

CONCLUSIONS

Review 1 - uncertainty remains over the optimal prediction model(s) for use in clinical practice. Review 2 - in general, there was insufficient evidence that the effect of treatment depended on baseline characteristics.

STUDY REGISTRATION

This study is registered as PROSPERO CRD42016042402.

FUNDING

The National Institute for Health Research Health Technology Assessment programme.

Genetic and clinical markers for predicting treatment responsiveness in rheumatoid arthritis

Although many drugs and therapeutic strategies have been developed for rheumatoid arthritis (RA) treatment, numerous patients with RA fail to respond to currently available agents. In this review, we provide an overview of the complexity of this autoimmune disease by showing the rapidly increasing number of genes associated with RA.We then systematically review various factors that have a predictive value (predictors) for the response to different drugs in RA treatment, especially recent advances. These predictors include but are certainly not limited to genetic variations, clinical factors, and demographic factors. However, no clinical application is currently available. This review also describes the challenges in treating patients with RA and the need for personalized medicine. At the end of this review, we discuss possible strategies to enhance the prediction of drug responsiveness in patients with RA.

Chromosome conformation signatures define predictive markers of inadequate response to methotrexate in early rheumatoid arthritis

Background

There is a pressing need in rheumatoid arthritis (RA) to identify patients who will not respond to first-line disease-modifying anti-rheumatic drugs (DMARD). We explored whether differences in genomic architecture represented by a chromosome conformation signature (CCS) in blood taken from early RA patients before methotrexate (MTX) treatment could assist in identifying non-response to DMARD and, whether there is an association between such a signature and RA specific expression quantitative trait loci (eQTL).

Methods

We looked for the presence of a CCS in blood from early RA patients commencing MTX using chromosome conformation capture by EpiSwitch™. Using blood samples from MTX responders, non-responders and healthy controls, a custom designed biomarker discovery array was refined to a 5-marker CCS that could discriminate between responders and non-responders to MTX. We cross-validated the predictive power of the CCS by generating 150 randomized groups of 59 early RA patients (30 responders and 29 non-responders) before MTX treatment. The CCS was validated using a blinded, independent cohort of 19 early RA patients (9 responders and 10 non-responders). Last, the loci of the CCS markers were mapped to RA-specific eQTL.

Results

We identified a 5-marker CCS that could identify, at baseline, responders and non-responders to MTX. The CCS consisted of binary chromosome conformations in the genomic regions of IFNAR1, IL-21R, IL-23, CXCL13 and IL-17A. When tested on a cohort of 59 RA patients, the CCS provided a negative predictive value of 90.0% for MTX response. When tested on a blinded independent validation cohort of 19 early RA patients, the signature demonstrated a true negative response rate of 86 and a 90% sensitivity for detection of non-responders to MTX. Only conformations in responders mapped to RA-specific eQTL.

Conclusions

Here we demonstrate that detection of a CCS in blood in early RA is able to predict inadequate response to MTX with a high degree of accuracy. Our results provide a proof of principle that a priori stratification of response to MTX is possible, offering a mechanism to provide alternative treatments for non-responders to MTX earlier in the course of the disease.

Electronic supplementary material

The online version of this article (10.1186/s12967-018-1387-9) contains supplementary material, which is available to authorized users.

Thymidylate synthase genetic polymorphism and plasma total homocysteine level in a group of Turkish patients with rheumatoid arthritis: relationship with disease activity and methotrexate toxicity

BACKGROUND

The polymorphism of thymidylate synthase (TS) gene and homocysteine are reported to have a relationship to methotrexate (MTX) metabolism, with conflicting results. The aim of this study was to determine homocysteine levels and the frequency of TS gene triple repeat (TS3R) and double repeat (TS2R) polymorphisms in a group of Turkish RA patients and evaluate its association with MTX toxicity and disease activity.

METHODS

Sixty-four patients with RA and 31 control subjects with a mean age of 48.7 ± 12.5 and 46.2 ± 13.4 years, were enrolled to the study. Demographic characteristics were obtained and number of patients with MTX-related adverse affects, were recorded in the patient group. The homocysteine levels and TS2R/TS3R polymorphisms of the TS gene were analyzed and the distribution of genotypes according to MTX toxicity and disease activity, were determined.

RESULTS

The demographic properties were similar between the patient and control subjects. Folic acid supplementation with a mean dose of 5mg folic acid/week, was present in all patients. Thirty-six of the 64 patients showed adverse effects to MTX treatment. The frequency of TS2R and TS3R polymorphisms were found to be similar in the patient and control groups. TS2R and TS3R gene polymorphisms were found to be similar in patients with and without MTX-related adverse events. The mean homocysteine level was also similar in patients with and without TS gene polymorphism, but was found to be higher (12.45μmol/L vs 10.7μmol/L) in patients with MTX-related side effects than in patients without side effects. The mean level of homocysteine was correlated with levels of ESR in the patient group.

CONCLUSIONS

In conclusion, homocysteine levels might effect the disease activity and toxicity of MTX but 2R and 3R polymorphisms in the TS gene, were not related with MTX-related toxicity in RA patients receiving folate supplementation. Further studies are needed to illuminate the polymorphisms in other enzymes that might be responsible from the MTX toxicity in patients suffering from RA.

Role of key TYMS polymorphisms on methotrexate therapeutic outcome in portuguese rheumatoid arthritis patients

BACKGROUND

Therapeutic outcome of rheumatoid arthritis (RA) patients treated with methotrexate (MTX) can be modulated by thymidylate synthase (TS) levels, which may be altered by genetic polymorphisms in TS gene (TYMS). This study aims to elucidate the influence of TYMS polymorphisms in MTX therapeutic outcome (regarding both clinical response and toxicity) in Portuguese RA patients.

METHODS

Clinicopathological data from 233 Caucasian RA patients treated with MTX were collected, outcomes were defined and patients were genotyped for the following TYMS polymorphisms: 1) 28 base pairs (bp) variable number tandem repeat (rs34743033); 2) single nucleotide polymorphism C>G (rs2853542); and 3) 6 bp sequence deletion (1494del6, rs34489327). Chi-square and binary logistic regression analyses were performed, using genotype and haplotype-based approaches.

RESULTS

Considering TYMS genotypes, 3R3R (p = 0.005, OR = 2.34), 3RC3RG (p = 0.016, OR = 3.52) and 6bp- carriers (p = 0.011, OR = 1.96) were associated with non-response to MTX. Multivariate analysis confirmed the increased risk for non-response to MTX in 6bp- carriers (p = 0.016, OR = 2.74). Data demonstrated that TYMS polymorphisms were in linkage disequilibrium (p<0.00001). Haplotype multivariate analysis revealed that haplotypes harboring both 3R and 6bp- alleles were associated with non-response to MTX. Regarding MTX-related toxicity, no statistically significant differences were observed in relation to TYMS genotypes and haplotypes.

CONCLUSION

Our study reveals that TYMS polymorphisms could be important to help predicting clinical response to MTX in RA patients. Despite the potential of these findings, translation into clinical practice needs larger studies to confirm these evidences.

Methotrexate pharmacogenetics in rheumatoid arthritis: a status report

Methotrexate (MTX), an antifolate drug, is the first-line disease-modifying agent for the treatment of rheumatoid arthritis (RA) worldwide. MTX has excellent long-term efficacy, tolerability and safety. Early initiation of MTX in patients with RA controls joint destruction and slows progression of disease. However, the clinical response to MTX and frequency of adverse effects from the drug exhibit marked interpatient variability. Over the past decade, there has been a quest to identify genetic markers that reliably predict MTX efficacy and toxicity and help optimize MTX therapy in RA; that is, the field of MTX pharmacogenetics. This review will summarize key pharmacogenetic studies examining SNPs in the genes encoding enzymes in the MTX cellular pathway and their association with MTX response in RA. As evident from this review, MTX pharmacogenetics in RA remains a muddled field, mostly due to inconsistent results from several small underpowered studies.

Old drugs, old problems: where do we stand in prediction of rheumatoid arthritis responsiveness to methotrexate and other synthetic DMARDs?

Methotrexate (MTX) is the central drug in the management of rheumatoid arthritis (RA) and other immune mediated inflammatory diseases. It is widely used either in monotherapy or in association with other synthetic and biologic disease modifying anti-rheumatic drugs (DMARDs). Although comprehensive clinical experience exists for MTX and synthetic DMARDs, to date it has not been possible to preview correctly whether or not a patient will respond to treatment with these drugs. Predicting response to MTX and other DMARDs would allow the selection of patients based on their likelihood of response, thus enabling individualized therapy and avoiding unnecessary adverse effects and elevated costs. However, studies analyzing this issue have struggled to obtain consistent, replicable results and no factor has yet been recognized to individually distinguish responders from nonresponders at treatment start. Variables possibly influencing drug effectiveness may be disease-, patient- or treatment-related, clinical or biological (genetic and nongenetic). In this review we summarize current evidence on predictors of response to MTX and other synthetic DMARDs, discuss possible causes for the heterogeneity observed and address its translation into daily clinical practice.

(1)H NMR-based metabolomic analysis for identifying serum biomarkers to evaluate methotrexate treatment in patients with early rheumatoid arthritis

To identify the major serum biomarkers predicting the response to methotrexate (MTX) treatment in patients with early rheumatoid arthritis (RA), we evaluated the relationships between the individual response to MTX and various associated factors utilizing the (1)H nuclear magnetic resonance ((1)H NMR)-based metabolomic method. Thirty-eight early RA patients were enrolled in this cohort study, and they received MTX (10 mg/week) orally as monotherapy for 24 weeks. According to the American College of Rheumatology criteria for improvement, clinical evaluation following MTX treatment was carried out at baseline and at the end of 24 weeks. Furthermore, collected serum samples were analyzed using 600 M (1)H NMR for spectral binning. The obtained data were processed by both the unsupervised principal component analysis (PCA) and the supervised partial least squares discriminant analysis (PLS-DA). Lastly, multivariate analyses were performed to recognize the spectral pattern of endogenous metabolites related to MTX treatment. Differential clustering of (1)H NMR spectra identified by PCA was found between the effective (n=25) and non-effective (n=13) group of RA patients receiving MTX treatment. Multivariate statistical analysis showed a difference in metabolic profiles between the two groups using PLS-DA (R(2)=0.802, Q(2)=0.643). In targeted profiling, 11 endogenous metabolites of the effective group showed a significant difference when compared with those of the non-effective group (p<0.05). Serum metabolites correlated with MTX treatment in patients with early RA were identified, which may be the major predictive factors for evaluating the response to MTX treatment in patients with early RA. Furthermore, our results highlight the usefulness of (1)H NMR-based metabolomics as a feasible and efficient prognostic tool for predicting therapeutic efficacy to MTX treatment.

Liver stiffness correlates with methotrexate cumulative dose in patients with rheumatoid arthritis

BACKGROUND

Liver stiffness values were recently proposed to identify patients with methotrexate-induced liver fibrosis. Aim of this study was to assess the clinical and laboratory determinants of the association between liver stiffness, measured by transient elastography, and methotrexate treatment in patients with rheumatoid arthritis in the absence of other factors contributing to liver damage and fibrosis.

METHODS

100 patients with rheumatoid arthritis, with a cumulative methotrexate dose ranging from 1530 to 13,000 mg over a mean period of 7.07±3.89 yrs, were retrospectively evaluated.

RESULTS

The average liver stiffness value in the whole population was 4.93±1.8 kPa, excluding the presence of significant fibrosis. At univariate analysis, a significant correlation was found between liver stiffness and methotrexate cumulative dose, duration of treatment, alanine transaminases levels, body mass index, gamma glutamyl-transpeptidase and the presence of steatosis. At multivariate analysis, a significant association was detected only between liver stiffness and methotrexate cumulative dose. Out of 11 patients with liver stiffness >7.0 kPa, five were subjected to liver biopsy and mild or moderate perisinusoidal fibrosis was detected in two patients with a cumulative dose >4000 mg and liver stiffness >9 kPa.

CONCLUSIONS

Chronic methotrexate treatment induces a progressive increase in liver stiffness corresponding to mild or moderate perisinusoidal fibrosis for values >9 kPa.

Genetic polymorphisms in metabolic and cellular transport pathway of methotrexate impact clinical outcome of methotrexate monotherapy in Japanese patients with rheumatoid arthritis

The aim of this study was to investigate the impact of genetic polymorphisms in the metabolic and cellular transport pathway of methotrexate (MTX) on the clinical outcome of MTX monotherapy in Japanese rheumatoid arthritis (RA) patients. Fifty-five patients were treated with MTX monotherapy at a dose of 4-10 mg/week. The total concentration of MTX-polyglutamates (MTX-PGs) was measured at steady-state in red blood cells (RBCs) by high performance liquid chromatography. The genotype at 16 polymorphic sites in 11 genes (ABCB1, ABCG2, ABCC2, RFC1, PCFT, SLCO1B1, MTHFR, GGH, ATIC, MTR, and MTRR) was analyzed. No significant association between the total concentration of MTX-PGs in RBCs and clinical outcome was found. However, patients with the ABCB1 3435TT genotype had a significantly lower mean disease activity score (DAS) 28 than did patients with the ABCB1 3435CC genotype (p = 0.02). Similarly, patients with the ABCB1 2677AA/AT/TT genotypes had a significantly lower mean DAS28 than did patients with the ABCB1 2677GG/GA/GT genotypes (p = 0.04). The patients with the MTHFR 1298AA genotype had a significantly lower mean DAS28 than those with the MTHFR 1298AC/CC genotypes (p = 0.04). In conclusion, the ABCB1 3435C>T, ABCB1 2677G>A/T, and MTHFR 1298A>C polymorphisms influenced the efficacy of MTX monotherapy.

MTHFR gene polymorphisms and outcome of methotrexate treatment in patients with rheumatoid arthritis: analysis of key polymorphisms and meta-analysis of C677T and A1298C polymorphisms

Association of two key variants mapping to the MTHFR gene (C677T (rs1801133) and A1298C (rs1801131)) with response to methotrexate (MTX) remains controversial. We investigated these and other markers spanning the gene as predictors of MTX efficacy and adverse events in a UK rheumatoid arthritis (RA) patient cohort and performed a meta-analysis of the two key variants using all published data. The tagging single nucleotide polymorphisms (SNPs) were genotyped in 309 patients with well-defined outcomes to MTX treatment and 17 studies were included in the meta-analysis. No association of the SNPs tested was detected with MTX efficacy or toxicity in our UK cohort. After combining our data with previous studies by meta-analysis, the random effects pooled odds ratios (OR) for both C677T and A1298C showed no association with efficacy or toxicity for either of the SNPs (efficacy: OR=1.05 (95% confidence interval (CI) 0.83-1.32) and OR=0.81 (95% CI 0.53-1.24), respectively; toxicity: OR=1.38 (95% CI 0.90-2.12) and OR=1.19 (95% CI 0.80-1.78), respectively). The available evidence suggests that the MTHFR C677T and A1298C gene polymorphisms are not reliable predictors of response to MTX treatment in RA patients.