Methotrexate: Implications of pharmacogenetics in the treatment of patients with Rheumatoid Arthritis.

BACKGROUND: Methotrexate (MTX) is an anti-folate drug with anti-proliferative and anti-inflammatory effects. MTX proved to be the most highly effective, fast-acting disease modifying anti-rheumatic drug (DMARD), being widely used for the treatment of rheumatoid arthritis (RA). This review aims to describe the main genetic variants identified concerning proteins that play a role in methotrexate's kinetics and efficiency profile. METHODS: A literature review was conducted since January of 2000 until December 2020, by searching the PubMed and Embase bibliographic databases, employing the following MeSH terms: methotrexate, pharmacogenetics, pharmacokinetics, and rheumatoid arthritis. The search was limited to articles in English language. Two independent reviewers screened the titles and abstracts followed by a full-text review to assess papers regarding their eligibility. A total of 48 articles matched the research criteria and were analyzed. RESULTS: Reduced folate carrier 1 (RFC1), a constitutively expressed folate transport protein that has high affinity for MTX is responsible, almost exclusively, for the transport of folate and MTX into the cell. The most studied variant of the gene is the 80G>A variant, mapped within exon 2, on chromosome 21. It seems to improve RA responses to MTX, clinical efficacy with long disease remission. ABC transporters are involved in the efflux of MTX from cells. An increased expression and function of these transporters should decrease MTX concentrations in target cells, resulting in lack of therapeutic response. ABCB1 3435 C/T is a high frequency polymorphism, significantly associated with RA good responses, symptom remission and reduced adverse events, due to MTX treatment. Thymidylate synthase (TYMS) is involved in thymidine synthesis. MTX decreases TYMS activity by inhibition and decreasing the access to tetrahydrofolate (THF) cofactors. The most common genetic variant of the TYMS gene consists of a 28 bp tandem repeat, with double and triple number of repeats (2R and 3R). The 3R allele genotype was associated with decreased efficacy and increased toxicity. The 5,10-methylenetetrahydrofolate reductase (MTHFR) enzyme is indirectly inhibited by MTX. The most common SNPs of the MTHFR gene are C677T and A1298C. Both are associated with a decreased efficacy and an increased toxicity of MTX. CONCLUSION: MTX response is affected by many gene variants; the effect of each variant separately is likely to be small. Additionally, gene-gene interaction seems to enhance the potential role of linkage disequilibrium. This shows the emerging need for a better gene characterization and to improve the knowledge about variants distribution according to ethnicity, to explain different responses to MTX at an individual level.

Outcomes of COVID-19 in patients with primary systemic vasculitis or polymyalgia rheumatica from the COVID-19 Global Rheumatology Alliance physician registry: a retrospective cohort study.

BACKGROUND: Patients with primary systemic vasculitis or polymyalgia rheumatica might be at a high risk for poor COVID-19 outcomes due to the treatments used, the potential organ damage cause by primary systemic vasculitis, and the demographic factors associated with these conditions. We therefore aimed to investigate factors associated with COVID-19 outcomes in patients with primary systemic vasculitis or polymyalgia rheumatica. METHODS: In this retrospective cohort study, adult patients (aged ≥18 years) diagnosed with COVID-19 between March 12, 2020, and April 12, 2021, who had a history of primary systemic vasculitis (antineutrophil cytoplasmic antibody [ANCA]-associated vasculitis, giant cell arteritis, Behçet's syndrome, or other vasculitis) or polymyalgia rheumatica, and were reported to the COVID-19 Global Rheumatology Alliance registry were included. To assess COVID-19 outcomes in patients, we used an ordinal COVID-19 severity scale, defined as: (1) no hospitalisation; (2) hospitalisation without supplemental oxygen; (3) hospitalisation with any supplemental oxygen or ventilation; or (4) death. Multivariable ordinal logistic regression analyses were used to estimate odds ratios (ORs), adjusting for age, sex, time period, number of comorbidities, smoking status, obesity, glucocorticoid use, disease activity, region, and medication category. Analyses were also stratified by type of rheumatic disease. FINDINGS: Of 1202 eligible patients identified in the registry, 733 (61·0%) were women and 469 (39·0%) were men, and their mean age was 63·8 years (SD 17·1). A total of 374 (31·1%) patients had polymyalgia rheumatica, 353 (29·4%) had ANCA-associated vasculitis, 183 (15·2%) had giant cell arteritis, 112 (9·3%) had Behçet's syndrome, and 180 (15·0%) had other vasculitis. Of 1020 (84·9%) patients with outcome data, 512 (50·2%) were not hospitalised, 114 (11·2%) were hospitalised and did not receive supplemental oxygen, 239 (23·4%) were hospitalised and received ventilation or supplemental oxygen, and 155 (15·2%) died. A higher odds of poor COVID-19 outcomes were observed in patients who were older (per each additional decade of life OR 1·44 [95% CI 1·31-1·57]), were male compared with female (1·38 [1·05-1·80]), had more comorbidities (per each additional comorbidity 1·39 [1·23-1·58]), were taking 10 mg/day or more of prednisolone compared with none (2·14 [1·50-3·04]), or had moderate, or high or severe disease activity compared with those who had disease remission or low disease activity (2·12 [1·49-3·02]). Risk factors varied among different disease subtypes. INTERPRETATION: Among patients with primary systemic vasculitis and polymyalgia rheumatica, severe COVID-19 outcomes were associated with variable and largely unmodifiable risk factors, such as age, sex, and number of comorbidities, as well as treatments, including high-dose glucocorticoids. Our results could be used to inform mitigation strategies for patients with these diseases. FUNDING: American College of Rheumatology and the European Alliance of Associations for Rheumatology.

Remission and low disease activity matrix tools: results in real-world rheumatoid arthritis patients under anti-TNF therapy.

BACKGROUND: Remission/ low disease activity (LDA) are the main treatment goals in rheumatoid arthritis (RA) patients. Two tools showing the ability to predict golimumab treatment outcomes in patients with RA were published. OBJECTIVES: To estimate the real-world accuracy of two quantitative tools created to predict RA remission and low disease activity. METHODS: Multicenter, observational study, using data from the Rheumatic Diseases Portuguese Register (Reuma.pt), including biologic naïve RA patients who started an anti-TNF as first-line biologic and with at least 6 months of follow-up. The accuracy of two matrices tools was assessed by likelihood-ratios (LR), sensitivity (SN), specificity (SP), positive predictive value (PPV), negative predictive value (NPV) and area under the ROC curve (AUC). RESULTS: 674 RA patients under first-line anti-TNF (266 etanercept, 186 infliximab, 131 adalimumab, 85 golimumab, 6 certolizumab pegol) were included. The median (IQR) age was 53.4 (44.7-61.1) years and the median disease duration was 7.7 (3.7-14.6) years. The majority were female (72%). Most patients were RF and/or ACPA positive (75.5%) and had erosive disease (54.9%); 58.6% had comorbidities. At 6-months, 157 (23.3%) patients achieved remission (DAS28 ESR < 2.6) and 269 (39.9%) LDA (DAS28 ESR ≤ 3.2). Area under the curve for remission in this real-world sample was 0.756 [IC 95% (0.713-0.799)] and for LDA was 0.724 [IC 95% (0.686 -0.763)]. The highest LR (8.23) for remission state was obtained at a cut-off ≥ 67%, with high specificity (SP) (99.6%) but low sensitivity (SN) (3.2%). A better balance of SN and SP (65.6% and 73.9%, respectively) was observed for a cut-off >30%, with a LR of 2.51, PPV of 43.3% and NPV of 87.6%. CONCLUSION: In this population, the accuracy of the prediction tool was good for remission and LDA. Our results corroborate the idea that these matrix tools could be helpful to select patients for anti-TNF therapy.