Gene expression profiling may be used to stratify patients by disease severity to test the hypothesis that variable disease outcome has a genetic component. In order to define unique expression signatures in African American rheumatoid arthritis (RA) patients with severe erosive disease, we undertook a gene expression study using samples of RNA from peripheral blood mononuclear cells (PBMCs). RNA from baseline PBMC samples of 96 African American RA patients with early RA (<2 years disease duration) was hybridized to cDNA probes of the Illumina Human HT-V3 expression array. Expression analyses were performed using the ca. 25,000 cDNA probes, and then expression levels were compared to the total number of erosions in radiographs of the hands and feet at baseline and 36 months. Using a false discovery rate cutoff of Q = 0.30, 1,138 genes at baseline and 680 genes at 36 months significantly correlated with total erosions. No evidence of a signal differentiating disease progression, or change in erosion scores between baseline and 36 months, was found. Further analyses demonstrated that the differential gene expression signature was localized to the patients with the most erosive disease (>10 erosions). Ingenuity Pathway Analysis demonstrated that genes with fold change greater than 1.5 implicated immune pathways such as CTLA signaling in cytotoxic T lymphocytes. These results demonstrate that CLEAR patients with early RA having the most severe erosive disease, as compared to more mild cases (<10 erosions), may be characterized by a set of differentially expressed genes that represent biological pathways with relevance to autoimmune disease.

Abstract Abstract 1774 Introduction: Chronic Lymphocytic Leukemia (CLL) follows a variable, difficult to predict course. Biomarkers (IGHV mutations, CD38 and ZAP-70) have improved prognostication but accuracy is only ∼80%, not sufficient to initiate preemptive therapy. To address this, we have incorporated another molecular biological parameter, hypervariably expressed genes (HVEGs) from global gene expression profiles (GEPs) [Dozmorov, 2011], along with IGHV mutation status to develop a more robust method of prognostication. Methods: RNA was purified from B cells of 65 CLL patients and 25 normal subjects. GEPs were defined with Illumina HumanHT12 beadchips and analyzed to identify HVEGs fluctuating coordinately in CLL patients but not expressed in normal circulating human B cells. A Cox proportional hazards regression model was used to compare expression levels with clinical outcome. Results: Unmutated CLL (U-CLL) and mutated CLL (M-CLL) samples were sorted based on the averaged normalized gene expression level in the largest HVEG cluster consisting of 45 genes. Samples were split into subgroups based on high and low expression of these genes. Four subgroups were identified: U-CLL with high (U-HVEhi), U-CLL with low (U-HVElo), M-CLL with high (M-HVEhi), and M-CLL with low (M-HVElo) expression of HVEGs. When these subgroups were analyzed for time-to-first treatment (TTFT), the findings were remarkably different. Using a Cox proportional hazards regression model we found that for M-CLL the presence of low levels of HVEGs denoted a subgroup with a prolonged median TTFT compared to M-CLL patients with high levels of HVEGs (23.46 yrs in M-HVElo versus 9.05 yrs in M-HVEhi; P=0.0075). This association was reversed in U-CLL, where low levels of HVEGs pinpointed a subgroup with a shortened median TTFT compared to U-CLL patients with high levels of HVEGs: median TTFT was 8.01 yrs in U-HVEhi and decreased by 50% to 3.12 yrs in U-HVElo (P=0.0151). Compared to the TTFT for M-HVElo, the TTFT for U-HVElo was dramatically shorter (3.12 vs. 23.46 years; P<0.0001). Discussion: Combining the HVEG approach with IGHV mutation status enabled us to define intra-group heterogeneity, and thereby improve prognostication for apparently homogeneous subgroups of U-CLL and M-CLL patients. This combination was superior to IGHV mutations alone in that it pinpointed a subset of M-CLL patients with shorter TTFTs and a subset of U-CLL patients with longer TTFTs, indicating that the combined approach selects those patients that IGHV mutation analysis misclassified. Therefore, combining IGHV mutation status and HVEG expression provides a more precise indicator with potentially valuable clinical implications. The data suggest that the HVEGs are responsible for the different outcomes in the two groups and could provide mechanistic insights into key aspects of CLL B-cell biology as well as therapeutic targets. Disclosures: No relevant conflicts of interest to declare.

Abstract Abstract 2833 Introduction: In chronic lymphocytic leukemia (CLL), clonally expanded CD5+ B lymphocytes eventually overwhelm healthy immune cells, hindering normal immune function. To determine mechanisms fueling this expansion, gene expression data were gathered by microarray analysis of cells from CLL patients. Samples were grouped based on Ki-67 expression, an indicator of proliferation. To determine mechanisms correlating with B-cell proliferation and impacting on CLL B-cell biology, microarray profiles were compared using Gene Set Enrichment Analysis (GSEA) [Subramanian A, et al. PNAS 2005]. Methods: Samples were analyzed for intracellular expression of Ki-67 by flow cytometry and divided into 2 groups based on Ki-67 expression (cutoff at 5%). RNA was then purified from CD5+CD19+ CLL cells and gene expression microarray assays were performed using Illumina HumanHT12 beadchips. GSEA was carried out using a library of signatures by Dr. Louis Staudt [Shaffer AL, et al. Immunol Rev 2006] containing 305 gene sets encompassing 13, 564 genes biased towards hematopoietic signatures. Results: Of 61 cases, 14 were Ki-67high and 47 were Ki-67low. When time-to-first-treatment (TTFT) was compared between the groups, Ki67high patients had significantly shorter TTFT (2.76 yrs) compared to Ki-67low patients (23.46 yrs; P<0.0001). By GSEA, we determined 255/285 gene sets were upregulated in the Ki-67high group with 50 gene sets significantly enriched at a false discovery rate (FDR) <25%. For the Ki-67low group, 30/285 gene sets were upregulated with only one significant at FDR <25%. IGHV unmutated CLL (U-CLL) was enriched in only one gene set, termed CLLUNMUT-1, while mutated CLL (M-CLL) was only enriched in CLLMUT-1. CD38high and CD38low subsets were similarly enriched in these two gene sets, with 4 additional gene sets in the CD38high group, including MYD88UP-4 and IFN-2. Of the 50 significantly enriched gene sets in the Ki-67high group, 17 relate to signaling pathways, 16 to cellular differentiation, 6 to cellular processes, 4 to transcription factor targets, and the remaining 7 relate to cancer. Of these, the percentage of the signaling component is up 13% from its representation in the original Staudt library. The top 5 gene sets enriched in the Ki-67high group are: upregulated U-CLL compared to M-CLL (CLLUNMUT-1), myeloid tissue compared to other tissues (MYELOID-1), T cell cytokine induced proliferation (TCYTUP-8), BCR crosslinking CLL B cells (CLLBCRUP-1) and BDCA4+ dendritic cells compared to other hematopoietic cells (DC-1). The total number of genes enriched in these 50 sets is 769, with 217 genes shared in two or more gene sets. Twenty genes were enriched in the CLL BCR signature, CLLBCRUP-1 [Herishanu Y, et al. Blood 2011]. Of these, WARS, IRF4, MX1, OAS1, and NAMPT are also enriched in the T cell cytokine induced and T cell activation signatures. Only one gene set was enriched in the Ki-67low group, CLLMUT-1, upregulated in M-CLL compared to U-CLL. CD274 (PD-L1) was consistently elevated in the Ki-67low group in all the patients, irrespective of IGHV mutation status. Discussion: The observed GSEA profiles in Ki-67high patients correlated with gene signatures biased towards BCR signaling, signal transduction, and hematopoietic cancer, consistent with the Ki-67high group containing more (recently) proliferating cells influenced at least in part by BCR signaling. The profiles also suggest that additional cells (T lymphocytes and dendritic cells) may be involved. It is notable these gene sets were not observed for CLL patients subgrouped by IGHV mutation status or by CD38, and that these other subsets did not show as pronounced a distinction by GSEA profiling. Disclosures: No relevant conflicts of interest to declare.

Macrophage cytokine production is inhibited by cholinergic signals transmitted via the vagus nerve, an α7 nicotinic acetylcholine receptor (α7nAChR) dependent pathway termed the “cholinergic anti‐inflammatory pathway” (Nature 420:853–9, 2002). Here we addressed the hypothesis that this pathway is capable of providing short‐term memory by downregulating macrophage responses to endotoxin for up to 48 hr. Vagus nerve stimulation (VNS) (5V, 2 ms, 1Hz, 2.5 min) in rats 24 h prior to endotoxin (LPS) significantly reduced serum TNF (sham =767 pg/ml; VNS =358 pg/ml, p<0.01); this effect persisted for 48 h (sham TNF = 1327; VNS TNF = 824, p<0.05). The molecular mechanism is attributable to α7nAChR signaling, because VNS fails to reduce TNF levels in α7nAChR KO mice. This molecular memory is recapitulated in cultured human macrophages pulsed with acetylcholine (ACh) (60 min pulse 24 h prior to LPS). LPS‐induced TNF release was reduced 54% as compared with vehicle controls (p<0.05); pulsing also significantly suppressed activation of NF‐κB (74%). Ach‐pulsing significantly altered the macrophage transcriptome response to endotoxin, indicating that vagus nerve signals “train” macrophages as a short‐term (48 hr) memory response. Evidence that discrete neural signals can mediate short‐term memory in macrophages via α7nAChR has surprising implications for understanding innate immunity. Supported in part by NIGMS.

The prediction of response (or non-response) to anti-TNF treatment for rheumatoid arthritis (RA) is a pressing clinical problem. We conducted a genome-wide association study using the Illumina HapMap300 SNP chip on 89 RA patients prospectively followed after beginning anti-TNF therapy as part of Autoimmune Biomarkers Collaborative Network (ABCoN [Autoimmune Bio-markers Collaborative Network]) patient cohort. Response to therapy was determined by the change in Disease Activity Score (DAS28) observed after 14 wks. We used a two-part analysis that treated the change in DAS28 as a continuous trait and then incorporated it into a dichotomous trait of “good responder” and “nonresponder” by European League Against Rheumatism (EULAR) criteria.We corrected for multiple tests by permutation, and adjusted for potential population stratification using EIGENSTRAT. Multiple single nucleotide polymorphism (SNP) markers showed significant associations near or within loci including: the v-maf musculoaponeurotic fibrosarcoma oncogene homolog B (MAFB) gene on chromosome 20; the type I interferon gene IFNk on chromosome 9; and in a locus on chromosome 7 that includes the paraoxonase I (PON1) gene. An SNP in the IL10 promoter (rs1800896) that was previously reported as associated with anti-TNF response was weakly associated with response in this cohort. Replications of these results in independent and larger data sets clearly are required. We provide a reference list of candidate SNPs (P < 0.01) that can be investigated in future pharmacogenomic studies.

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.

46,XY gonadal dysgenesis was transmitted as an autosomal-dominant trait in a large family with multiple affected members. Expressivity of the trait was highly variable, ranging from pure to partial gonadal dysgenesis associated with normal female genitalia or sexual ambiguity, to mild hypospadias in otherwise normal males. The phenotypic features of this trait appeared to be confined to the genitourinary system. Multipoint parametric analysis using markers D5S664, D5S633, and D5D2102 yielded an LOD score of 4.47, assuming sex-limited, autosomal-dominant inheritance with a penetrance of 0.6. Because mutation in testis-determining genes leads to gonadal dysgenesis in 46,XY individuals, we postulate that the gene mapped by this study normally plays a role in gonadal differentiation.

OBJECTIVE A number of non-HLA loci that have shown evidence (P < 0.05) for linkage with rheumatoid arthritis (RA) have been previously identified. The present study attempts to confirm these findings. METHODS We performed a second genome-wide screen of 256 new multicase RA families recruited from across the United States by the North American Rheumatoid Arthritis Consortium. Affected sibling pair analysis on the new data set was performed using SIBPAL. We subsequently combined our first and second data sets in an attempt to enhance the evidence for linkages in a larger sample size. We also evaluated the impact of covariates on the support for linkage, using LODPAL. RESULTS Evidence of linkage at 1p13 (D1S1631), 6p21.3 (the HLA complex), and 18q21 (D18S858) (P < 0.05) was replicated in this independent data set. In addition, there was new evidence for linkage at 9p22 (D9S1121 [P = 0.001]) and 10q21 (D10S1221 [P = 0.0002] and D10S1225 [P = 0.0038]) in the current data set. The combined analysis of both data sets (512 families) showed evidence for linkage at the level of P < 0.005 at 1p13 (D1S1631), 1q43 (D1S235), 6q21 (D6S2410), 10q21 (D10S1221), 12q12 (D12S398), 17p13 (D17S1298), and 18q21 (D18S858). Linkage at HLA was also confirmed (P < 5 x 10(-12)). Inclusion of DRB1*04 as a covariate significantly increased the probability of linkage on chromosome 6. In addition, some linkages on chromosome 1 showed improved significance when modeling DRB1*04 or rheumatoid factor positivity as covariates. CONCLUSION These results provide a rational basis for pursuing high-density linkage and association studies of RA in several regions outside of the HLA region, particularly on chromosomes 1p, 1q, and 18q.

Rheumatoid arthritis (RA) is an inflammatory disease with a complex genetic component. An association between RA and the human leukocyte antigen (HLA) complex has long been observed in many different populations, and most studies have focused on a direct role for the HLA-DRB1 "shared epitope" in disease susceptibility. We have performed an extensive haplotype analysis, using 54 markers distributed across the entire HLA complex, in a set of 469 multicase families with RA. The results show that, in addition to associations with the DRB1 alleles, at least two additional genetic effects are present within the major histocompatibility complex. One of these lies within a 497-kb region in the central portion of the HLA complex, an interval that excludes DRB1. This genetic risk factor is present on a segment of a highly conserved ancestral A1-B8-DRB1*03 (8.1) haplotype. Additional risk genes may also be present in the HLA class I region in a subset of DRB1*0404 haplotypes. These data emphasize the importance of defining haplotypes when trying to understand the HLA associations with disease, and they clearly demonstrate that such associations with RA are complex and cannot be completely explained by the DRB1 locus.