Background

Systemic lupus erythematosus (SLE) is a chronic, multiorgan, autoimmune disease that affects people of all ages and ethnicities.

Objectives

To explore the relationship between age at disease onset and many of the diverse manifestations of SLE. Additionally, to determine the relationship between age of disease onset and genetic risk in patients with SLE.

Methods

The relationship between the age at disease onset and SLE manifestations were explored in a multiracial cohort of 1317 patients. Patients with SLE were genotyped across 19 confirmed genetic susceptibility loci for SLE. Logistic regression was used to determine the relationships between the number of risk alleles present and age of disease onset.

Results

Childhood-onset SLE had higher odds of proteinuria, malar rash, anti-dsDNA antibody, haemolytic anaemia, arthritis and leucopenia (OR=3.03, 2.13, 2.08, 2.50, 1.89, 1.53, respectively; p values <0.0001, 0.0004, 0.0005, 0.0024, 0.0114, 0.045, respectively). In female subjects, the odds of having cellular casts were 2.18 times higher in childhood-onset than in adult-onset SLE (p=0.0027). With age of onset ≥50, the odds of having proteinuria, cellular casts, anti-nRNP antibody, anti-Sm antibody, anti-dsDNA antibody and seizures were reduced. However, late adult-onset patients with SLE have higher odds of developing photosensitivity than early adult-onset patients. Each SLE-susceptibility risk allele carried within the genome of patients with SLE increased the odds of having a childhood-onset disease in a race-specific manner: by an average of 48% in Gullah and 25% in African-Americans, but this was not significant in Hispanic and European-American lupus patients.

Conclusions

The genetic contribution towards predicting early-onset disease in patients with SLE is quantified for the first time. A more severe SLE phenotype is found in patients with early-onset disease in a large multi-racial cohort, independent of gender, race and disease duration.

Background

The World Wide Web plays a critical role in enabling molecular, cell, systems and computational biologists to exchange, search, visualize, integrate, and analyze experimental data. Such efforts can be further enhanced through the development of semantic web concepts. The semantic web idea is to enable machines to understand data through the development of protocol free data exchange formats such as Resource Description Framework (RDF) and the Web Ontology Language (OWL). These standards provide formal descriptors of objects, object properties and their relationships within a specific knowledge domain. However, the overhead of converting datasets typically stored in data tables such as Excel, text or PDF into RDF or OWL formats is not trivial for non-specialists and as such produces a barrier to seamless data exchange between researchers, databases and analysis tools. This problem is particularly of importance in the field of network systems biology where biochemical interactions between genes and their protein products are abstracted to networks.

Results

For the purpose of converting biochemical interactions into the BioPAX format, which is the leading standard developed by the computational systems biology community, we developed an open-source command line tool that takes as input tabular data describing different types of molecular biochemical interactions. The tool converts such interactions into the BioPAX level 3 OWL format. We used the tool to convert several existing and new mammalian networks of protein interactions, signalling pathways, and transcriptional regulatory networks into BioPAX. Some of these networks were deposited into PathwayCommons, a repository for consolidating and organizing biochemical networks.

Conclusions

The software tool Sig2BioPAX is a resource that enables experimental and computational systems biologists to contribute their identified networks and pathways of molecular interactions for integration and reuse with the rest of the research community.

Objective

Interleukin (IL) 21 is a member of the type I cytokine superfamily that exerts a variety of effects on the immune system including B cell activation, plasma cell differentiation, and immunoglobulin production. The expression of IL21R is reduced in B cells from lupus patients, while IL21 serum levels are increased in both lupus patients and some lupus-murine models. We recently reported that polymorphisms within the IL21 gene are associated with increased susceptibility to lupus. Herein, we examined the genetic association between SNPs within IL21R and lupus.

Methods

We genotyped 17 SNPs in the IL21R gene in two large cohorts of lupus patients and ethnically-matched healthy controls. Genotyping was performed with the Illumina BeadStation 500GX instrument using Illumina Infinum II genotyping assays.

Results

We identified and confirmed the association between rs3093301 within the IL21R gene and lupus in two independent European-derived and Hispanic cohorts (meta analysis odds ratio= 1.16, 95% CI= 1.08-1.25, meta analysis p=1.0×10-4).

Conclusion

We identified IL21R as a novel susceptibility gene for lupus.

Objective

Both genetic and epigenetic factors play an important role in the pathogenesis of lupus. Herein, we study methyl-CpG-binding protein 2 (MECP2) polymorphism in a large cohort of lupus patients and controls, and determine functional consequences of the lupus-associated MECP2 haplotype.

Methods

We genotyped 18 SNPs within MECP2, located on chromosome Xq28, in a large cohort of European-derived lupus patients and controls. We studied the functional effects of the lupus-associated MECP2 haplotype by determining gene expression profiles in B cell lines from female lupus patients with and without the lupus-associated MECP2 risk haplotype.

Results

We confirm, replicate, and extend the genetic association between lupus and genetic markers within MECP2 in a large independent cohort of European-derived lupus patients and controls (OR= 1.35, p= 6.65×10−11). MECP2 is a dichotomous transcriptional regulator that either activates or represses gene expression. We identified 128 genes that are differentially expressed in lupus patients with the disease-associated MECP2 haplotype; most (~81%) are upregulated. Genes that were upregulated have significantly more CpG islands in their promoter regions compared to downregulated genes. Gene ontology analysis using the differentially expressed genes revealed significant association with epigenetic regulatory mechanisms suggesting that these genes are targets for MECP2 regulation in B cells. Further, at least 13 of the 104 upregulated genes are interferon-regulated genes. The disease-risk MECP2 haplotype is associated with increased expression of the MECP2 transcriptional co-activator CREB1, and decreased expression of the co-repressor HDAC1.

Conclusion

Polymorphism in the MECP2 locus is associated with lupus and, at least in part, contributes to the interferon signature observed in lupus patients.

Introduction

Behçet's disease is a chronic systemic inflammatory disease that remains incompletely understood. Herein, we perform the first genome-wide association study in Behçet's disease.

Methods

Using DNA pooling technology and the Affymetrix 500K arrays, we identified possible candidate gene associations with Behçet's disease in a cohort of 152 Behçet's disease patients and 172 healthy ethnically matched controls. Genetic loci that were identified in the pooling study were genotyped in patients and controls using TaqMan genotyping technology.

Results

We identified genetic associations between Behçet's disease and single-nucleotide polymorphisms (SNPs) in KIAA1529, CPVL, LOC100129342, UBASH3B, and UBAC2 (odds ratio = 2.04, 2.26, 1.84, 1.71, and 1.61, respectively; P value = 4.2 × 10-5, 1.0 × 10-4, 3.0 × 10-4, 1.5 × 10-3, and 5.8 × 10-3, respectively). Among the associated SNPs, the Behçet's disease-risk allele in rs2061634 leads to substitution of serine to cysteine at amino acid position 995 (S995C) in the KIAA1529 protein.

Conclusions

Using an unbiased whole-genome genetic association approach, we identified novel candidate genetic loci that are associated with increased susceptibility for Behçet's disease. These findings will help to better understand the pathogenesis of Behçet's disease and identify novel targets for therapeutic intervention.

Background

Studies of cellular signaling indicate that signal transduction pathways combine to form large networks of interactions. Viewing protein-protein and ligand-protein interactions as graphs (networks), where biomolecules are represented as nodes and their interactions are represented as links, is a promising approach for integrating experimental results from different sources to achieve a systematic understanding of the molecular mechanisms driving cell phenotype. The emergence of large-scale signaling networks provides an opportunity for topological statistical analysis while visualization of such networks represents a challenge.

Results

SNAVI is Windows-based desktop application that implements standard network analysis methods to compute the clustering, connectivity distribution, and detection of network motifs, as well as provides means to visualize networks and network motifs. SNAVI is capable of generating linked web pages from network datasets loaded in text format. SNAVI can also create networks from lists of gene or protein names.

Conclusion

SNAVI is a useful tool for analyzing, visualizing and sharing cell signaling data. SNAVI is open source free software. The installation may be downloaded from: . The source code can be accessed from:

In learning models of strategic game play, an agent constructs a valuation (action value) over possible future choices as a function of past actions and rewards. Choices are then stochastic functions of these action values. Our goal is to uncover a neural signal that correlates with the action value posited by behavioral learning models. We measured activity from neurons in the superior colliculus (SC), a midbrain region involved in planning saccadic eye movements, while monkeys performed two saccade tasks. In the strategic task, monkeys competed against a computer in a saccade version of the mixed-strategy game ”matching-pennies”. In the instructed task, saccades were elicited through explicit instruction rather than free choices. In both tasks neuronal activity and behavior were shaped by past actions and rewards with more recent events exerting a larger influence. Further, SC activity predicted upcoming choices during the strategic task and upcoming reaction times during the instructed task. Finally, we found that neuronal activity in both tasks correlated with an established learning model, the Experience Weighted Attraction model of action valuation (Camerer and Ho, 1999). Collectively, our results provide evidence that action values hypothesized by learning models are represented in the motor planning regions of the brain in a manner that could be used to select strategic actions.

Systemic lupus erythematosus (SLE) is a predominantly female autoimmune disease that affects multiple organ systems. Herein, we report on an X-chromosome gene association with SLE. Methyl-CpG-binding protein 2 (MECP2) is located on chromosome Xq28 and encodes for a protein that plays a critical role in epigenetic transcriptional regulation of methylation-sensitive genes. Utilizing a candidate gene association approach, we genotyped 21 SNPs within and around MECP2 in SLE patients and controls. We identify and replicate association between SLE and the genomic element containing MECP2 in two independent SLE cohorts from two ethnically divergent populations. These findings are potentially related to the overexpression of methylation-sensitive genes in SLE.