Previous work has demonstrated that Northern and Southern European ancestries are associated with specific systemic lupus erythematosus (SLE) manifestations. In this study, 1855 SLE cases of European descent were genotyped for 4965 single-nucleotide polymorphisms and principal components analysis of genotype information was used to define population substructure. The first principal component (PC1) distinguished Northern from Southern European ancestry, PC2 differentiated Eastern from Western European ancestry and PC3 delineated Ashkenazi Jewish ancestry. Compared with Northern European ancestry, Southern European ancestry was associated with autoantibody production (odds ratio (OR)=1.40, 95% confidence interval (CI) 1.07–1.83) and renal involvement (OR 1.41, 95% CI 1.06–1.87), and was protective for discoid rash (OR=0.51, 95% CI 0.32–0.82) and photosensitivity (OR=0.74, 95% CI 0.56–0.97). Both serositis (OR=1.46, 95% CI 1.12–1.89) and autoantibody production (OR=1.38, 95% CI 1.06–1.80) were associated with Western compared to Eastern European ancestry. Ashkenazi Jewish ancestry was protective against neurologic manifestations of SLE (OR=0.62, 95% CI 0.40–0.94). Homogeneous clusters of cases defined by multiple PCs demonstrated stronger phenotypic associations. Genetic ancestry may contribute to the development of SLE endophenotypes and should be accounted for in genetic studies of disease characteristics.

The current methods for molecular typing of HLA-DR alleles incur a substantial financial burden when performing large population studies. In the current study, we aimed to provide much less expensive typing approach with high predictability for DRB1 genotype. We have used a panel of three microsatellite markers in the class II region (D6S2666, D6S2665 and D6S2446) for genotyping and haplotype reconstruction in a total of 1687 Caucasian (1313 RA patients and 374 controls) and 1364 Korean individuals (744 RA patients and 620 controls), all of whom were previously genotyped for DRB1. We found that a total of 88.4 and 87.4% of all observed three-marker haplotypes could determine the DR type with a positive predictive value >0.8 with high sensitivity and specificity. There was a high degree of haplotype conservation when comparing Caucasian and Asian populations. Interestingly, we found that the majority of DRB1*09 and DRB1*10 alleles share a common three-marker haplotype in both Caucasian and Asian populations. This is unexpected, since these two alleles are found on very different haplotype families. In addition, these two alleles are both associated with rheumatoid arthritis, making the elucidation of these haplotype relationships potentially important for understanding disease susceptibility.

A genetic contribution to the development of systemic lupus erythematosus (SLE) is well established. Several genome-wide linkage scans have identified a number of putative susceptibility loci for SLE, some of which have been replicated in independent samples. This study aimed to identify the regions showing the most consistent evidence for linkage by applying the genome scan meta-analysis (GSMA) method. The study identified two genome-wide suggestive regions on 6p21.1–q15 and 20p11–q13.13 (P-value=0.0056 and P-value=0.0044, respectively) and a region with P-value<0.01 on 16p13–q12.2. The region on chromosome 6 contains the human leukocyte antigen cluster, and the chromosome 16 and 20 regions have been replicated in several cohorts. The potential importance of the identified genomic regions are also highlighted. These results, in conjunction with data emerging from dense single nucleotide polymorphism typing of specific regions or future genome-wide association studies will help guide efforts to identify the actual predisposing genetic variation contributing to this complex genetic disease.

Psoriatic arthritis (PsA) is a systemic inflammatory condition featuring polyarthritis associated with psoriasis. Apart from clinical indicators, few biomarkers exist to aid in the diagnosis and management of PsA. We hypothesized that whole blood gene expression profiling would provide new diagnostic markers and/or insights into pathogenesis of the disease. We compared whole blood gene expression profiles in PsA patients and in age-matched controls. We identified 310 differentially expressed genes, the majority of which are upregulated in PsA patients. The PsA expression profile does not significantly overlap with profiles derived from patients with rheumatoid arthritis or systemic lupus erythematosus. Logistic regression identified two lymphocyte-specific genes (zinc-finger protein 395 and phosphoinositide-3-kinase 2B) that discriminate PsA patients from normal controls. In addition, a highly coregulated cluster of overexpressed genes implicated in protein kinase A regulation strongly correlates with erythrocyte sedimentation rate. Other clusters of coregulated, yet suppressed genes in PsA patient blood include molecules involved in T-cell signaling. Finally, differentially expressed genes in PsA fall into diverse functional categories, but many downregulated genes belong to a CD40 signaling pathway. Together, the data suggest that gene expression profiles of PsA patient blood contain candidate novel disease markers and clues to pathogenesis.

Autoantibodies are clinically relevant biomarkers for numerous autoimmune disorders. The genetic basis of autoantibody production in systemic lupus erythematosus (SLE) and other autoimmune diseases is poorly understood. In this study, we characterized autoantibody profiles in 1506 individuals from 229 multiplex SLE pedigrees. There was strong familial aggregation of antinuclear antibodies (ANAs), anti-double-stranded DNA (dsDNA), anti-La/SSB, anti-Ro/SSA, anti-Sm, anti-nRNP (nuclear ribonucleoprotein), IgM antiphospholipid (aPL) antibodies (Abs) and rheumatoid factor (RF) across these families enriched for lupus. We performed genome-wide linkage analyses in an effort to map genes that contribute to the production of the following autoantibodies: Ro/SSA, La/SSB, nRNP, Sm, dsDNA, RF, nuclear and phospholipids. Using an approach to minimize false positives and adjust for multiple comparisons, evidence for linkage was found to anti-La/SSB Abs on chromosome 3q21 (adjusted P =1.9 × 10 −6 ), to anti-nRNP and/or anti-Sm Abs on chromosome 3q27 (adjusted P =3.5 × 10 −6 ), to anti-Ro/SSA and/or anti-La/SSB Abs on chromosome 4q34–q35 (adjusted P =3.4 × 10 −4 ) and to anti-IgM aPL Abs on chromosome 13q14 (adjusted P =2.3 × 10 −4 ). These results support the hypothesis that autoantibody production is a genetically complex trait. Identification of the causative alleles will advance our understanding of critical molecular mechanisms that underlie SLE and perhaps other autoimmune diseases.

We carried out gene expression profiling of peripheral blood mononuclear cells (PBMCs) in 29 patients with active rheumatoid arthritis (RA) and 21 control subjects using Affymetrix U95Av2 arrays. Using cluster analysis, we observed a significant alteration in the expression pattern of 81 genes (P<0.001) in the PBMCs of RA patients compared with controls. Many of these genes correlated with differences in monocyte counts between the two study populations, and we show that a large fraction of these genes are specifically expressed at high levels in monocytes. In addition, a logistic regression analysis was performed to identify genes that performed best in the categorization of RA and control samples. Glutaminyl cyclase, IL1RA, S100A12 (also known as calgranulin or EN-RAGE) and Grb2-associated binding protein (GAB2) were among the top discriminators. Along with previous data, the overexpression of S100A12 in RA patients emphasizes the likely importance of RAGE pathways in disease pathogenesis. The altered expression of GAB2, an intracellular adaptor molecule involved in regulating phosphatase function, is of particular interest given the recent identification of the intracellular phosphatase PTPN22 as a risk gene for RA. These data suggest that a detailed study of gene expression patterns in peripheral blood can provide insight into disease pathogenesis. However, it is also clear that substantially larger sample sizes will be required in order to evaluate fully gene expression profiling as a means of identifying disease subsets, or defining biomarkers of outcome and response to therapy in RA.

Monitoring of gene and protein expression in peripheral blood cells has significant potential for improving the diagnosis and therapy of many human diseases. As genomic-scale microarray and proteomic technologies are applied to peripheral blood, it is important to consider the variables that may affect interpretation of data. Here we report experiments performed to identify genes that are particularly sensitive to ex vivo handling prior to RNA extraction for gene expression microarrays or quantitative real-time RT-PCR assays. We examined Affymetrix gene expression in samples from eight normal individuals where blood was processed for RNA either immediately after blood draw or the next day following overnight incubation. These studies identified hundreds of genes that are sensitive to ex vivo handling of blood, and suggest that this is an important variable to consider when designing and interpreting human PBMC experiments.

Systemic lupus erythematosus (SLE) is a chronic, autoimmune disorder influenced by multiple genetic and environmental factors. Linkage of SLE to chromosome 16q12–13 (LOD score=3.85) was first identified in pedigrees collected at the University of Minnesota, and has been replicated in several independent SLE collections. We performed fine mapping using microsatellites to further refine the susceptibility region(s), and the best evidence for linkage was identified at marker D16S3396 (LOD=2.28, P=0.0006). Evidence of association was suggested in the analysis of all families (D16S3094, P=0.0516) and improved to the level of significance (P=0.0106) when only the Caucasian families were analyzed. Subsets of pedigrees were then selected on the basis of clinical manifestations, and these subsets showed evidence for association with several markers: GATA143D05 (renal, P=0.0064), D16S3035 (renal, P=0.0418), D16S3117 (renal, P=0.0366), D16S3071 (malar rash, P=0.03638; neuropsychiatric, P=0.0349; oral ulcers, P=0.0459), D16S3094 (hematologic, P=0.0226), and D16S3089 (arthritis, P=0.0141). Together, these data provide further evidence that an important susceptibility gene(s) for SLE is located at 16q12.