B Cell Receptor Signaling-Based Index as a Biomarker for the Loss of Peripheral Immune Tolerance in Autoreactive B Cells in Rheumatoid Arthritis

<div><p>This study examines the loss of peripherally induced B cell immune tolerance in Rheumatoid arthritis (RA) and establishes a novel signaling-based measure of activation in a subset of autoreactive B cells - the <i>Induced tolerance status index</i> (ITSI). Naturally occurring naïve autoreactive B cells can escape the “classical” tolerogenic mechanisms of clonal deletion and receptor editing, but remain peripherally tolerized through B cell receptor (BCR) signaling inhibition (postdevelopmental “receptor tuning” or anergy). ITSI is a statistical index that numerically determines the level of homology between activation patterns of BCR signaling intermediaries in B cells that are either tolerized or activated by auto antigen exposure, and thus quantifies the level of peripheral immune tolerance. The index is based on the logistic regression analysis of phosphorylation levels in a panel of BCR signaling proteins. Our results demonstrate a new approach to identifying autoreactive B cells based on their BCR signaling features.</p></div

Phosphorylation levels of major BCR signal transduction proteins and total tyrosine phosphorylation levels (pTyr) in CD27⁻IgD⁺IgM^low/− B cells of RA patients (red) and healthy control subjects (blue) at baseline and in response to anti-BCR stimulation <i>in vitro</i>.

<p>Phosphorylation levels of major BCR signal transduction proteins and total tyrosine phosphorylation levels (pTyr) in CD27⁻IgD⁺IgM^low/− B cells of RA patients (red) and healthy control subjects (blue) at baseline and in response to anti-BCR stimulation <i>in vitro</i>.</p

Induced tolerance status index (ITSI) discriminates between autoreactive B_ND cells from healthy controls and RA subjects based on BCR phosphoprotein activation patterns.

<p>Induced tolerance status index (ITSI) discriminates between autoreactive B_ND cells from healthy controls and RA subjects based on BCR phosphoprotein activation patterns.</p

Strategies for BCR phosphoprotein data analysis in autoreactive B_ND cells.

<p>Strategies for BCR phosphoprotein data analysis in autoreactive B_ND cells.</p

BCR signaling pathways associated with the loss of peripheral induced tolerance in autoreactive B_ND cells of RA patients [2]. (A)

<p>Unmanipulated B_ND cells: increased baseline activity Blnk, SHP and Jnk. <b>(B)</b> Response to BCR engagement in B_ND cells: decreased phosphorylation of Blnk, Syk, SHP2, CD19 and increased activation of Erk1/2, Jnk.</p

Normal (tolerance in healthy controls) and pathological (broken tolerance in RA) BCR signaling in autoreactive B cells with induced peripheral immune tolerance.

<p>Normal (tolerance in healthy controls) and pathological (broken tolerance in RA) BCR signaling in autoreactive B cells with induced peripheral immune tolerance.</p

Image_1_On the Use of Diversity Measures in Longitudinal Sequencing Studies of Microbial Communities.TIFF

<p>Identification of the majority of organisms present in human-associated microbial communities is feasible with the advent of high throughput sequencing technology. As substantial variability in microbiota communities is seen across subjects, the use of longitudinal study designs is important to better understand variation of the microbiome within individual subjects. Complex study designs with longitudinal sample collection require analytic approaches to account for this additional source of variability. A common approach to assessing community changes is to evaluate the change in alpha diversity (the variety and abundance of organisms in a community) over time. However, there are several commonly used alpha diversity measures and the use of different measures can result in different estimates of magnitude of change and different inferences. It has recently been proposed that diversity profile curves are useful for clarifying these differences, and may provide a more complete picture of the community structure. However, it is unclear how to utilize these curves when interest is in evaluating changes in community structure over time. We propose the use of a bi-exponential function in a longitudinal model that accounts for repeated measures on each subject to compare diversity profiles over time. Furthermore, it is possible that no change in alpha diversity (single community/sample) may be observed despite the presence of a highly divergent community composition. Thus, it is also important to use a beta diversity measure (similarity between multiple communities/samples) that captures changes in community composition. Ecological methods developed to evaluate temporal turnover have currently only been applied to investigate changes of a single community over time. We illustrate the extension of this approach to multiple communities of interest (i.e., subjects) by modeling the beta diversity measure over time. With this approach, a rate of change in community composition is estimated. There is a need for the extension and development of analytic methods for longitudinal microbiota studies. In this paper, we discuss different approaches to model alpha and beta diversity indices in longitudinal microbiota studies and provide both a review of current approaches and a proposal for new methods.</p

Median (25th, 75th Percentile)^* levels of adiponectin and inflammatory markers by high-risk autoantibody profile (HRP) phenotype in 257 serum/plasma samples from clinic visits of 144 FDRs from the studies of the Etiology of rheumatoid arthritis (SERA) cohort.

<p>Median (25th, 75th Percentile)^{<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0199578#t002fn001" target="_blank">*</a>} levels of adiponectin and inflammatory markers by high-risk autoantibody profile (HRP) phenotype in 257 serum/plasma samples from clinic visits of 144 FDRs from the studies of the Etiology of rheumatoid arthritis (SERA) cohort.</p

Association between adiponectin and markers of inflammation in 257 serum/plasma samples from clinic visits of 144 FDRs from the studies of the Etiology of rheumatoid arthritis (SERA) cohort.

<p>Association between adiponectin and markers of inflammation in 257 serum/plasma samples from clinic visits of 144 FDRs from the studies of the Etiology of rheumatoid arthritis (SERA) cohort.</p

Modification of the association between adiponectin and inflammatory markers (A through H) by HRP status using linear mixed models in the studies of the Etiology of rheumatoid arthritis.

<p>This figure presents the interaction between adiponectin and High-Risk profile autoantibody (HRP) status in 257 serum and plasma samples from clinic visits of 144 first degree-relatives of RA patients in the Studies of the Etiology of Rheumatoid Arthritis. All analyses were adjusted for age, sex, ethnicity, BMI, pack-years of smoking, and current use of cholesterol-lowering medications.</p