Pharmacogenetics of TNF inhibitor response in rheumatoid arthritis utilizing the two-component disease activity score.
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ABSTRACT:
SUBMITTER: Gilani SS
PROVIDER: S-EPMC7649675 | biostudies-literature | 2020 Nov
REPOSITORIES: biostudies-literature
Publications
Pharmacogenetics of TNF inhibitor response in rheumatoid arthritis utilizing the two-component disease activity score.
Gilani Syed Sa SS Nair Nisha N Plant Darren D Hyrich Kimme K Morgan Ann W AW Morris Andrew P AP Wilson Anthony G AG Isaacs John D JD Barton Anne A Bluett James J
Pharmacogenomics 20201030 16
<b>Aim:</b> TNF inhibitor drugs are a treatment option for rheumatoid arthritis, but response is not universal. Response is typically measured using the composite 4-component (4C) disease activity score 28 (DAS28) which contains more subjective measures. This study used a validated 2-component (2C) DAS28 score to determine whether SNPs associated with response were replicated in the UK population. <b>Materials & methods:</b> A literature review identified TNF inhibitor response SNPs. Linear regr ...[more]
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Project description:In 15 patients with rheumatoid arthritis the baseline expression (t=0) of type I IFN-regulated genes was determined in peripheral blood cells (PAXgene) using cDNA-microarrays and compared to levels one month after (t=1) anti-TNF treatment (infliximab). Therefore, we used 43K cDNA microarrays from the Stanford Functional Genomics Facility (http://microarray.org/sfgf/) printed on aminosilane-coated slides containing ~20.000 unique genes. Only one batch of arrays was used for all experiments. First DNA spots were UV-cross linked to the slide using 150-300 mJoules. Sample preparation and microarray hybridization were performed as described previously (1,2). Data storage and filtering was performed using the Stanford Microarray Database (http://genome-www5.stanford.edu//) as described previously. 1. van der Pouw Kraan TC, Wijbrandts CA, van Baarsen LG, Voskuyl AE, Rustenburg F, Baggen JM et al.: Rheumatoid arthritis subtypes identified by genomic profiling of peripheral blood cells: assignment of a type I interferon signature in a subpopulation of patients. Ann Rheum Dis 2007, 66: 1008-1014. 2. van der Pouw Kraan TC, van Baarsen LG, Rustenburg F, Baltus B, Fero M, Verweij CL: Gene expression profiling in rheumatology. Methods Mol Med 2007, 136: 305-327. Abbreviations: - Bnrs are the different patients analyzed - PAX or Paxgene indicates the total RNA was isolated from peripheral blood obtained in PAXgene tubes - CRS: common reference sample: We made a common reference that consisted of a mixture of mRNAs isolated from 11 different cell lines (Perou CM, Jeffrey SS, van de RM et al. Distinctive gene expression patterns in human mammary epithelial cells and breast cancers. Proc Natl Acad Sci U S A. 1999; 96:9212-9217) supplemented with RNA from rheumatoid synovial tissue, fibroblasts, and activated peripheral blood mononuclear cells (PBMCs). - PMT: photomultiplier tube: the sensitivity/intensity of the scanner can be adjusted to prevent spot saturation. Compound Based Treatment: anti-TNF (infliximab)
2010-01-28 | GSE19821 | GEO
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Project description:Genetic biomarkers are sought to personalize treatment of patients with rheumatoid arthritis (RA), given their variable response to TNF inhibitors (TNFi). However, no genetic biomaker is yet sufficiently validated. Here, we report a validation study of 18 previously reported genetic biomarkers, including 11 from GWAS of response to TNFi. The validation was attempted in 581 patients with RA that had not been treated with biologic antirheumatic drugs previously. Their response to TNFi was evaluated at 3, 6 and 12 months in two ways: change in the DAS28 measure of disease activity, and according to the EULAR criteria for response to antirheumatic drugs. Association of these parameters with the genotypes, obtained by PCR amplification followed by single-base extension, was tested with regression analysis. These analyses were adjusted for baseline DAS28, sex, and the specific TNFi. However, none of the proposed biomarkers was validated, as none showed association with response to TNFi in our study, even at the time of assessment and with the outcome that showed the most significant result in previous studies. These negative results are notable because this was the first independent validation study for 12 of the biomarkers, and because they indicate that prudence is needed in the interpretation of the proposed biomarkers of response to TNFi even when they are supported by very low p values. The results also emphasize the requirement of independent replication for validation, and the need to search protocols that could increase reproducibility of the biomarkers of response to TNFi.
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