Michaela Oswald

Randomized, Double-Blind, Placebo-Controlled Trial of the Effect of Vitamin D3 on the Interferon Signature in Patients With Systemic Lupus Erythematosus.

Vitamin D modulates the immune response and blocks induction of an interferon (IFN) signature by systemic lupus erythematosus (SLE) sera. This study was undertaken to investigate the effects of vitamin D supplementation on the IFN signature in patients with SLE.

Modular Analysis of Peripheral Blood Gene Expression in Rheumatoid Arthritis Captures Reproducible Gene Expression Changes in Tumor Necrosis Factor Responders

To establish whether the analysis of whole‐blood gene expression is useful in predicting or monitoring response to anti–tumor necrosis factor (anti‐TNF) therapy in patients with rheumatoid arthritis (RA).

Blood pressure regulation by CD4+ lymphocytes expressing choline acetyltransferase

Blood pressure regulation is known to be maintained by a neuro-endocrine circuit, but whether immune cells contribute to blood pressure homeostasis has not been determined. We previously showed that CD4+ T lymphocytes that express choline acetyltransferase (ChAT), which catalyzes the synthesis of the vasorelaxant acetylcholine, relay neural signals. Here we show that these CD4+CD44hiCD62Llo T helper cells by gene expression are a distinct T-cell population defined by ChAT (CD4 TChAT). Mice lacking ChAT expression in CD4+ cells have elevated arterial blood pressure, compared to littermate controls. Jurkat T cells overexpressing ChAT (JTChAT) decreased blood pressure when infused into mice. Co-incubation of JTChAT and endothelial cells increased endothelial cell levels of phosphorylated endothelial nitric oxide synthase, and of nitrates and nitrites in conditioned media, indicating increased release of the potent vasorelaxant nitric oxide. The isolation and characterization of CD4 TChAT cells will enable analysis of the role of these cells in hypotension and hypertension, and may suggest novel therapeutic strategies by targeting cell-mediated vasorelaxation.

Principles for the organization of gene-sets

A gene-set, an important concept in microarray expression analysis and systems biology, is a collection of genes and/or their products (i.e. proteins) that have some features in common. There are many different ways to construct gene-sets, but a systematic organization of these ways is lacking. Gene-sets are mainly organized ad hoc in current public-domain databases, with group header names often determined by practical reasons (such as the types of technology in obtaining the gene-sets or a balanced number of gene-sets under a header). Here we aim at providing a gene-set organization principle according to the level at which genes are connected: homology, physical map proximity, chemical interaction, biological, and phenotypic-medical levels. We also distinguish two types of connections between genes: actual connection versus sharing of a label. Actual connections denote direct biological interactions, whereas shared label connection denotes shared membership in a group. Some extensions of the framework are also addressed such as overlapping of gene-sets, modules, and the incorporation of other non-protein-coding entities such as microRNAs.

Modular Analysis of Peripheral Blood Gene Expression in Rheumatoid Arthritis Captures Reproducible Gene Expression Changes in TNF Responders

To establish whether the analysis of whole‐blood gene expression is useful in predicting or monitoring response to anti–tumor necrosis factor (anti‐TNF) therapy in patients with rheumatoid arthritis (RA).

Editorial: The Power of a Modular Approach to Transcriptional Analysis

In this issue of Arthritis & Rheumatology, Chiche and colleagues provide additional insight into the complexity of interferon (IFN) signatures in the peripheral blood of lupus patients (1). Their data illustrate the power of combining correlated gene expression information with biologic associations, in this case based on empirically derived modules of gene expression and their post hoc annotations. These methods are beginning to provide more user-friendly approaches to analyzing and communicating results for monitoring immune function in the context of disease, vaccination, and therapy. Over the last decade, the development of increasingly comprehensive platforms for global analysis of messenger RNA (mRNA) expression at reasonable cost has spawned a huge number of studies that utilize gene expression profiling to understand human disease. A PubMed search for studies using gene expression profiling in humans yields tens of thousands of results, including more than 300 publications on systemic lupus erythematosus (SLE) and 500 publications on rheumatoid arthritis. A substantial fraction of these studies were carried out on mixed cell populations, most commonly peripheral blood mononuclear cells (PBMCs) or whole blood. Early studies documented the importance of fresh preparation of RNA, since thousands of genes can change expression in PBMCs after just a few hours and even more so after overnight shipping (2). This problem has been solved by the use of blood collections using PAXgene or Tempus tubes that immediately stabilize RNA. Nevertheless, the computational challenges of making sense of large-scale analog data related to mRNA transcript levels are substantial. A variety of exploratory statistical approaches to large-scale data have been employed, which are generally agnostic with regard to the biologic functions of the genes being analyzed. As a result, one of the biggest problems in the field has been the lack of validated results. Small sample sizes, together with statistical noise and an inability to combine data across experiments or laboratories because of standardization problems (batch effects), have led to isolated reports of results which could not later be reproduced. Studies of rheumatic diseases in particular have been plagued by this problem. However, an exception to this is the peripheral blood IFN signature in lupus, which has been well replicated in numerous studies since the first observations more than a decade ago (3–5). In 2008, Chaussabel et al reported on an approach to gene expression analysis that was based on an empirical examination of how groups of genes behave across a variety of disease conditions in PBMCs (6). Expression profiling was carried out on 239 patients with 1 of 8 disorders: juvenile rheumatoid arthritis, systemic lupus, type 1 diabetes mellitus, metastatic melanoma, Escherichia coli infection, Staphylococcus aureus infection, influenza A infection, and acute liver transplant rejection. These disorders all involve some degree of inflammation or immune stimulation, and thus, it was reasonable to expect some reflection of these states in the circulating peripheral blood cells. Remarkably, the authors observed clear “modules” of gene expression, most commonly involving hundreds of transcripts moving in a common pattern across samples from the 8 data sets. Upon inspection of the genes in these modular groupings, many modules could be reasonably designated as belonging to known cell types, such as B cells, T cells, myeloid lineage, etc., as well as to known pathways, such as IFN-inducible genes or ribosomeor major histocompatibility complex–related genes. Many modules did not lend themselves to easy categorization and were thus designated “undetermined”; a total of 28 distinct modules were identified. Not surprisingly, the IFN-associated module was strongly up-regulated in the pediatric lupus patients in that study (6). The study by Chiche et al takes advantage of an Peter K. Gregersen, MD, Michaela Oswald, PhD: Feinstein Institute for Medical Research, Manhasset, New York. Address correspondence to Peter K. Gregersen, MD, Robert S. Boas Center for Genomics and Human Genetics, Feinstein Institute for Medical Research, 350 Community Drive, Manhasset, NY 11030. E-mail: peterg@nshs.edu. Submitted for publication February 24, 2014; accepted in revised form March 11, 2014.

Molecular signatures in systemic lupus erythematosus: distinction between disease flare and infection

The clinical scenario of a febrile, acutely ill, immunocompromised patient with immunocompromised lupus remains challenging despite advances in technology and improved understanding of pathogenic mechanisms. Infection is a major contributor to morbidity and mortality in systemic lupus erythematosus (SLE); infection-related hospitalisation rates range from 10% to 35%1–4 and mortality rates range from 29% to 53%.5 ,6 The disease itself and most treatment strategies are immunosuppressive, rendering patients with SLE more susceptible to severe infection with common organisms and opportunistic pathogens. Both infection and lupus flare can incite clinically indistinguishable inflammatory responses. Consequently, appropriate therapy may be delayed or patients are treated for both conditions while awaiting results of time-consuming investigations for bacterial and viral infections. The potential consequences of treating infection with immunosuppression are obvious and may contribute to the high mortality rates. Antibiotics given unnecessarily also have potential toxicities. A biomarker that would accurately and rapidly differentiate between flare and infection would provide an extremely valuable guide to more directed, precise therapy, likely leading to significantly decreased morbidity and mortality. Microarray technology offers an unbiased, systems biology approach to study the expression level of thousands of genes simultaneously and genome-wide transcriptional studies have emerged as a powerful investigational tool to study complex diseases as well as infection.7 The objective of this exploratory study was to use whole blood gene expression profiling to identify specific RNA expression profiles that would differentiate systemic inflammation related to SLE disease flare from infection in acutely ill patients with lupus. We hypothesised that the molecular signature associated with active disease and no infection in patients with SLE will differ from the molecular signature in patients with SLE with infection. Comparison groups consisted of SLE subjects with inactive disease and healthy controls. ### Study design Blood samples for microarray analysis were obtained from two …

Randomized, Double-Blind, Placebo-Controlled Trial of the Effect of Vitamin D3on the Interferon Signature in Patients With Systemic Lupus Erythematosus: TRIAL OF VITAMIN D3IN SLE

Vitamin D modulates the immune response and blocks induction of an interferon (IFN) signature by systemic lupus erythematosus (SLE) sera. This study was undertaken to investigate the effects of vitamin D supplementation on the IFN signature in patients with SLE.

Double-Blind Randomized Placebo-Controlled Trial of the Effect of Vitamin D3 on the Interferon Signature in Patients with Systemic Lupus Erythematosus

Vitamin D modulates the immune response and blocks induction of an interferon (IFN) signature by systemic lupus erythematosus (SLE) sera. This study was undertaken to investigate the effects of vitamin D supplementation on the IFN signature in patients with SLE.

Modular Analysis of Peripheral Blood Gene Expression in Rheumatoid Arthritis Captures Reproducible Gene Expression Changes in Tumor Necrosis Factor Responders: Whole-Blood Gene Expression Analysis and Response to Anti-TNF in RA

To establish whether the analysis of whole‐blood gene expression is useful in predicting or monitoring response to anti–tumor necrosis factor (anti‐TNF) therapy in patients with rheumatoid arthritis (RA).