Divergent Gene Activation in Peripheral Blood and Tissues of Patients with Rheumatoid Arthritis, Psoriatic Arthritis and Psoriasis following Infliximab Therapy

<div><p>Objective</p><p>The immune inflammatory disorders rheumatoid arthritis (RA), psoriatic arthritis (PsA) and psoriasis (Ps) share common pathologic features and show responsiveness to anti-tumor necrosis factor (TNF) agents yet they are phenotypically distinct. The aim of this study was to examine if anti-TNF therapy is associated with divergent gene expression profiles in circulating cells and target tissues of patients with these diseases.</p><p>Methods</p><p>Peripheral blood CD14⁺ and CD14⁻ cells were isolated from 9 RA, 12 PsA and 10 Ps patients before and after infliximab (IFX) treatment. Paired synovial (n = 3, RA, PsA) and skin biopsies (n = 5, Ps) were also collected. Gene expression was analyzed by microarrays.</p><p>Results</p><p>26 out of 31 subjects responded to IFX. The transcriptional response of CD14⁺ cells to IFX was unique for the three diseases, with little overlap (<25%) in significantly changed gene lists (with PsA having the largest number of changed genes). In Ps, altered gene expression was more pronounced in lesional skin (relative to paired, healthy skin) compared to blood (relative to healthy controls). Marked suppression of up-regulated genes in affected skin was noted 2 weeks after therapy but the expression patterns differed from uninvolved skin. Divergent patterns of expression were noted between the blood cells and skin or synovial tissues in individual patients. Functions that promote cell differentiation, proliferation and apoptosis in all three diseases were enriched. RA was enriched in functions in CD14⁻ cells, PsA in CD14⁺ cells and Ps in both CD14⁺ and CD14⁻ cells, however, the specific functions showed little overlap in the 3 disorders.</p><p>Conclusion</p><p>Divergent patterns of altered gene expression are observed in RA, PsA and Ps patients in blood cells and target organs in IFX responders. Differential gene expression profiles in the blood do not correlate with those in target organs.</p></div

Venn/hive plots showing genes that changed following IFX treatment in three diseases in CD14⁺ cells.

<p>The three shaded bars emanating from the center each represent a list of significant probe sets where their members are distributed along the bar sorted by fold-change (indicated by color). The numbers of probe sets up- and down-regulated are shown on the red and blue portions of the bars, respectively. For example, in PsA,148 genes were up-regulated and 91 down-regulated following IFX therapy. Arcs that connect pairs of shaded bars represent genes that are common between two comparisons (in the same fashion, the intersect of two circles in a Venn diagram); the gray numbers indicate the numbers of arcs. Probe sets that are common to all three lists are represented by green arcs (15 probe sets representing eight genes). Probe set lists were obtained using a general linear model with p<.05, with the requirement that the log₂ signal was required to be >5 for at least one of the sample groups and the absolute fold change was required to be greater than 1.5. Only annotated probe sets are depicted. For this figure, the larger fold change was used for the two time points after baseline.</p

Numbers of significant genes in PBMC comparisons.

<p>Numbers reflect total number of genes as well as the number up- and down-regulated. These numbers were derived from a slightly larger number of probe sets. Unannotated probe sets are not included in this tabulation. BL = baseline, HC = healthy control (n = 19), Dx = disease. Numbers are based on general linear model with p<.05 and fold change at least 1.5.</p><p>Numbers of significant genes in PBMC comparisons.</p

Patient demographics.

<p>Patient demographics.</p

Numbers of significant genes in biopsy comparisons.

<p>Numbers reflect total number of genes as well as the number up- and down-regulated. These numbers were derived from a slightly larger number of probe sets. Unannotated probe sets are not included in this tabulation. BL = baseline, L = lesional, NL = non-lesional. Numbers are based on paired t-test with p<.01 and fold change at least 1.5.</p><p>Numbers of significant genes in biopsy comparisons.</p

Upstream regulator analysis using Ingenuity Pathway Analysis.

<p>Upstream regulators predicted based on genes that were significantly different for lesional skin before and after treatment with IFX (n = 379). Subset of “significant” transcription factors are shown that had an overlap p-value <.0001 (negative log of 4) and a reported activation z-score, indicating that many of the targets were enriched in the gene list. Except for STAT3 which was down-regulated, none of these were in the gene list. The further the activation z-score is from zero, the more likely that the direction of change of the target genes are consistent with the regulator being in either an “activated” or “inhibited” state. Bias terms over 25 are shown, indicating that the regulation of the targets in the data set as well as all of those for the regulator are skewed towards a particular direction <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0110657#pone.0110657-Systems1" target="_blank">[26]</a>. Six additional upstream regulators, E2F4, E2F1, PBRM1, NFYB, MYBL2 and NFkB, had low overlap p-values, but there wasn’t sufficient data about known relationships with targets to predict an activation state. Although no upstream regulator was predicted to be activated or inhibited for the IFX-response in CD14⁺ or CD14⁻ cells, some still had low overlap p-values.</p><p>Upstream regulator analysis using Ingenuity Pathway Analysis.</p