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      Clinical Pharmacogenetic Models of Treatment Response to Methotrexate Monotherapy in Slovenian and Serbian Rheumatoid Arthritis Patients: Differences in Patient's Management May Preclude Generalization of the Models

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          Abstract

          Objectives: Methotrexate (MTX) is the first line treatment for rheumatoid arthritis (RA), but nevertheless 30% of patients experience MTX inefficacy. Our aim was to develop a clinical pharmacogenetic model to predict which RA patients will not respond to MTX monotherapy. We also assessed whether this model can be generalized to other populations by validating it on a group of Serbian RA patients.

          Methods: In 110 RA Slovenian patients, data on clinical factors and 34 polymorphisms in MTX pathway were analyzed by Least Absolute Shrinkage and Selection Operator (LASSO) penalized regression to select variables associated with the disease activity as measured by Disease Activity Score (DAS28) score after 6 months of MTX monotherapy. A clinical pharmacogenetic index was constructed from penalized regression coefficients with absolute value above 0.05. This index was cross-validated and also independently validated on 133 Serbian RA patients.

          Results: A clinical pharmacogenetic index for prediction of DAS28 after 6 months of MTX monotherapy in Slovenian RA patients consisted of DAS28 score at diagnosis, presence of erosions, MTX dose, Solute Carrier Family 19 Member 1 ( SLC19A1) rs1051266, Solute Carrier Organic Anion Transporter Family Member 1B1 ( SLCO1B1) rs2306283, Thymidylate Synthase ( TYMS), and Adenosine Monophosphate Deaminase 1 ( AMPD1) rs17602729. It correctly classified 69% of Slovenian patients as responders or nonresponders and explained 30% of variability in DAS28 after 6 months of MTX monotherapy. Testing for validity in another population showed that it classified correctly only 22.5% of Serbian RA patients.

          Conclusions: We developed a clinical pharmacogenetic model for DAS28 after 6 months of MTX monotherapy in Slovenian RA patients by combining clinical and genetic variables. The clinical pharmacogenetic index developed for Slovenian patients did not perform well on Serbian patients, presumably due to the differences in patients' characteristics and clinical management between the two groups.

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          Most cited references31

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          The American Rheumatism Association 1987 revised criteria for the classification of rheumatoid arthritis.

          The revised criteria for the classification of rheumatoid arthritis (RA) were formulated from a computerized analysis of 262 contemporary, consecutively studied patients with RA and 262 control subjects with rheumatic diseases other than RA (non-RA). The new criteria are as follows: 1) morning stiffness in and around joints lasting at least 1 hour before maximal improvement; 2) soft tissue swelling (arthritis) of 3 or more joint areas observed by a physician; 3) swelling (arthritis) of the proximal interphalangeal, metacarpophalangeal, or wrist joints; 4) symmetric swelling (arthritis); 5) rheumatoid nodules; 6) the presence of rheumatoid factor; and 7) radiographic erosions and/or periarticular osteopenia in hand and/or wrist joints. Criteria 1 through 4 must have been present for at least 6 weeks. Rheumatoid arthritis is defined by the presence of 4 or more criteria, and no further qualifications (classic, definite, or probable) or list of exclusions are required. In addition, a "classification tree" schema is presented which performs equally as well as the traditional (4 of 7) format. The new criteria demonstrated 91-94% sensitivity and 89% specificity for RA when compared with non-RA rheumatic disease control subjects.
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            FASTSNP: an always up-to-date and extendable service for SNP function analysis and prioritization

            Single nucleotide polymorphism (SNP) prioritization based on the phenotypic risk is essential for association studies. Assessment of the risk requires access to a variety of heterogeneous biological databases and analytical tools. FASTSNP (function analysis and selection tool for single nucleotide polymorphisms) is a web server that allows users to efficiently identify and prioritize high-risk SNPs according to their phenotypic risks and putative functional effects. A unique feature of FASTSNP is that the functional effect information used for SNP prioritization is always up-to-date, because FASTSNP extracts the information from 11 external web servers at query time using a team of web wrapper agents. Moreover, FASTSNP is extendable by simply deploying more Web wrapper agents. To validate the results of our prioritization, we analyzed 1569 SNPs from the SNP500Cancer database. The results show that SNPs with a high predicted risk exhibit low allele frequencies for the minor alleles, consistent with a well-known finding that a strong selective pressure exists for functional polymorphisms. We have been using FASTSNP for 2 years and FASTSNP enables us to discover a novel promoter polymorphism. FASTSNP is available at .
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              The Disease Activity Score and the EULAR response criteria.

              The Disease Activity Score (DAS), its modified version the DAS28, and the DAS-based European League Against Rheumatism (EULAR) response criteria are well-known measures of disease activity in rheumatoid arthritis (RA). The DAS is a clinical index of RA disease activity that combines information from swollen joints, tender joints, the acute phase response, and general health. The EULAR response criteria classify individual patients as non-, moderate, or good responders, depending on the extent of change and the level of disease activity reached. The DAS, DAS28, and EULAR response criteria have been validated extensively. For daily practice, it has been shown that a tight control strategy, including measurement of disease activity using the DAS and planned adjustment of antirheumatic medication, is an effective strategy for RA. This article summarizes the development and validation of the DAS and DAS28 and their use in clinical trials and practice for the clinician.
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                Author and article information

                Contributors
                Journal
                Front Pharmacol
                Front Pharmacol
                Front. Pharmacol.
                Frontiers in Pharmacology
                Frontiers Media S.A.
                1663-9812
                25 January 2018
                2018
                : 9
                : 20
                Affiliations
                [1] 1Pharmacogenetics Laboratory, Faculty of Medicine, Institute of Biochemistry, University of Ljubljana , Ljubljana, Slovenia
                [2] 2Department of Rheumatology, University Medical Centre Ljubljana , Ljubljana, Slovenia
                [3] 3Faculty of Medicine, University of Ljubljana , Ljubljana, Slovenia
                [4] 4Faculty of Medicine, Institute of Human Genetics, University of Belgrade , Belgrade, Serbia
                [5] 5Faculty of Medicine, Institute of Rheumatology, University of Belgrade , Belgrade, Serbia
                Author notes

                Edited by: Laure Elens, Université catholique de Louvain, Belgium

                Reviewed by: Chakradhara Rao Satyanarayana Uppugunduri, Université de Genève, Switzerland; Murray Barclay, Canterbury District Health Board, New Zealand

                *Correspondence: Vita Dolžan vita.dolzan@ 123456mf.uni-lj.si

                This article was submitted to Pharmacogenetics and Pharmacogenomics, a section of the journal Frontiers in Pharmacology

                Article
                10.3389/fphar.2018.00020
                5788961
                29422864
                68e58fa9-7ca2-46e2-9d17-8ceab2212d28
                Copyright © 2018 Jenko, Tomšič, Jekić, Milić, Dolžan and Praprotnik.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 24 June 2017
                : 08 January 2018
                Page count
                Figures: 0, Tables: 3, Equations: 0, References: 42, Pages: 8, Words: 6574
                Funding
                Funded by: Javna Agencija za Raziskovalno Dejavnost RS 10.13039/501100004329
                Award ID: P1-0170
                Funded by: Ministarstvo Prosvete, Nauke i Tehnološkog Razvoja 10.13039/501100004564
                Award ID: grant 175091
                Categories
                Pharmacology
                Original Research

                Pharmacology & Pharmaceutical medicine
                rheumatoid arthritis,pharmacogenetics,methotrexate,polymorphism,predictive model

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