GWAS Replication Study Confirms the Association of PDE3A-SLCO1C1 with Anti-TNF Therapy Response in Rheumatoid Arthritis

Overview

Journal Pharmacogenomics

Specialties Genetics
Pharmacology

Date 2013 May 9

PMID 23651021

Citations 40

Authors

Isabel Acosta-Colman

Nuria Palau

Jesus Tornero

Antonio Fernandez-Nebro

Francisco Blanco

Isidoro Gonzalez-Alvaro

Juan D Canete

Joan Maymo

Javier Ballina

Benjamin Fernandez-Gutierrez

Alex Olive

Hector Corominas

Alba Erra

Oriol Canela-Xandri

Arnald Alonso

Maria Lopez Lasanta

Raul Tortosa

Antonio Julia

Sara Marsal

Affiliations

Soon will be listed here.

Abstract

Aim: The present study was undertaken to replicate the association of candidate genes for anti-TNF response in rheumatoid arthritis. Candidate genes were selected from a recent genome-wide association study on anti-TNF response performed in a population from Denmark.

Materials & Methods: Genomic DNA was obtained from 315 Spanish rheumatoid arthritis patients having received an anti-TNF agent as their first biological therapy. SNPs from NR2FR2, MAP2K6, CBLN2 and PDE3A-SLCO1C1 candidate loci were genotyped.

Results: The PDE3A-SLCO1C1 locus rs3794271 SNP showed a highly significant association with anti-TNF treatment response (p = 1.74 × 10⁻⁵). Combining the statistical evidence from the Spanish and Danish rheumatoid arthritis cohorts, the associated rs3794271 SNP reached a genome-wide significance level of association (p = 3.3 × 10⁻¹⁰).

Conclusion: The present findings establish the PDE3A-SLCO1C1 locus as a strong genetic marker of anti-TNF therapy response.

Citing Articles

Microfibrillar-associated protein 4 as a predictive biomarker of treatment response in patients with chronic inflammatory diseases initiating biologics: secondary analyses based on the prospective BELIEVE cohort study.

Sofiudottir B, Munk H, Christensen R, Moller S, Overgaard S, Sorensen G Rheumatol Int. 2024; 44(12):2935-2947.

PMID: 39465398 PMC: 11618207. DOI: 10.1007/s00296-024-05744-9.

Towards Personalized Medicine in Rheumatoid Arthritis.

Sharma S, Bluett J Open Access Rheumatol. 2024; 16:89-114.

PMID: 38779469 PMC: 11110814. DOI: 10.2147/OARRR.S372610.

Prediction of ineffectiveness of biological drugs using machine learning and explainable AI methods: data from the Austrian Biological Registry BioReg.

Ukalovic D, Leeb B, Rintelen B, Eichbauer-Sturm G, Spellitz P, Puchner R Arthritis Res Ther. 2024; 26(1):44.

PMID: 38331930 PMC: 10851538. DOI: 10.1186/s13075-024-03277-x.

Pharmacogenetics of Drug Therapies in Rheumatoid Arthritis.

Aluko A, Ranganathan P Methods Mol Biol. 2022; 2547:527-567.

PMID: 36068476 DOI: 10.1007/978-1-0716-2573-6_19.

-Omic Approaches and Treatment Response in Rheumatoid Arthritis.

Madrid-Paredes A, Martin J, Marquez A Pharmaceutics. 2022; 14(8).

PMID: 36015273 PMC: 9412998. DOI: 10.3390/pharmaceutics14081648.