Pharmacogenomics of Methotrexate Membrane Transport Pathway: Can Clinical Response to Methotrexate in Rheumatoid Arthritis Be Predicted?

• Type: Another Publication in an International Scientific Journal
• Date: 2015

Authors

Lima, A (Author) Other; José Bernardes (Author) FMUP; Azevedo, R (Author) Other; Rui Medeiros (Author) ICBAS; Seabra, V (Author) Other

Journal

Title: International Journal Of Molecular Sciences

Vol. 16

Pages: 13760-13780

ISSN: 1661-6596

Publisher: MDPI

Indexing

ISI Web of Knowledge - 31 Citations

Scopus - 34 Citations

Other information

Authenticus ID: P-00G-CPW

DOI: 10.3390/ijms160613760

Abstract (EN): Background: Methotrexate (MTX) is widely used for rheumatoid arthritis (RA) treatment. Single nucleotide polymorphisms (SNPs) could be used as predictors of patients' therapeutic outcome variability. Therefore, this study aims to evaluate the influence of SNPs in genes encoding for MTX membrane transport proteins in order to predict clinical response to MTX. Methods: Clinicopathological data from 233 RA patients treated with MTX were collected, clinical response defined, and patients genotyped for 23 SNPs. Genotype and haplotype analyses were performed using multivariate methods and a genetic risk index (GRI) for non-response was created. Results: Increased risk for non-response was associated to SLC22A11 rs11231809 T carriers; ABCC1 rs246240 G carriers; ABCC1 rs3784864 G carriers; CGG haplotype for ABCC1 rs35592, rs2074087 and rs3784864; and CGG haplotype for ABCC1 rs35592, rs246240 and rs3784864. GRI demonstrated that patients with Index 3 were 16-fold more likely to be non-responders than those with Index 1. Conclusions: This study revealed that SLC22A11 and ABCC1 may be important to identify those patients who will not benefit from MTX treatment, highlighting the relevance in translating these results to clinical practice. However, further validation by independent studies is needed to develop the field of personalized medicine to predict clinical response to MTX treatment.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 21