Faculty Bibliography

Large meta-analyses of RA susceptibility in European and East Asian populations have identified >100 RA risk loci, but genome-wide studies of RA in African-Americans are absent. To address this disparity, we performed an analysis of 916 African-American RA patients and 1392 controls, and aggregated our data with genotyping data from >100,000 European and Asian RA patients and controls. We identified two novel risk loci that appear to be specific to African-Americans: GPC5 and RBFOX1 (pAA < 5 x 10-9). Most RA risk loci are shared across different ethnicities, but among discordant loci, we observed strong enrichment of variants having large effect sizes. We found strong evidence of effect concordance for only 3 of the 21 largest effect index variants in Europeans. We used the trans-ethnic fine-mapping algorithm PAINTOR3 to prioritize risk variants in >90 RA risk loci. Addition of African-American data to those of European and East Asian descent enabled identification of 7 novel high confidence candidate pathogenic variants (defined by posterior probability > 0.8). In summary, our trans-ethnic analyses are the first to include African-Americans, identified several new RA risk loci, and point to candidate pathogenic variants that may underlie this common autoimmune disease. These findings may lead to better ways to diagnose or stratify treatment approaches in RA.

OBJECTIVE:Immune-mediated inflammatory diseases (IMIDs) are heterogeneous and complex conditions with overlapping clinical symptoms and elevated familial aggregation, which suggests the existence of a shared genetic component. In order to identify this genetic background in a systematic fashion, we performed the first cross-disease genome-wide meta-analysis in systemic seropositive rheumatic diseases, namely, systemic sclerosis, systemic lupus erythematosus, rheumatoid arthritis and idiopathic inflammatory myopathies. METHODS:We meta-analysed ~6.5 million single nucleotide polymorphisms in 11 678 cases and 19 704 non-affected controls of European descent populations. The functional roles of the associated variants were interrogated using publicly available databases. RESULTS:. Additionally, our results were significantly enriched in drugs that are being tested for the treatment of the diseases under study. CONCLUSIONS:that could be further investigated. Our results highlight the potential of drug repositioning among related systemic seropositive rheumatic IMIDs.

OBJECTIVE:Genetic risk scores (GRS) have been developed that differentiate individuals with type 1 diabetes from those with other forms of diabetes and are starting to be used for population screening; however, most studies were conducted in European-ancestry populations. This study identifies novel genetic variants associated with type 1 diabetes risk in African-ancestry participants and develops an African-specific GRS. RESEARCH DESIGN AND METHODS/METHODS:). RESULTS:*03:02) were significantly associated with type 1 diabetes risk. Among European-ancestry defined non-HLA risk loci, six risk loci were significantly associated with type 1 diabetes in subjects of African ancestry. An African-specific GRS provided strong prediction of type 1 diabetes risk (area under the curve 0.871), performing significantly better than a European-based GRS and two polygenic risk scores in independent discovery and validation cohorts. CONCLUSIONS:Genetic risk of type 1 diabetes includes ancestry-specific, disease-associated variants. The GRS developed here provides improved prediction of type 1 diabetes in African-ancestry subjects and a means to identify groups of individuals who would benefit from immune monitoring for early detection of islet autoimmunity.

To define potentially causal variants for autoimmune disease, we fine-mapped^1,2 76 rheumatoid arthritis (11,475 cases, 15,870 controls)³ and type 1 diabetes loci (9,334 cases, 11,111 controls)⁴. After sequencing 799 1-kilobase regulatory (H3K4me3) regions within these loci in 568 individuals, we observed accurate imputation for 89% of common variants. We defined credible sets of ≤5 causal variants at 5 rheumatoid arthritis and 10 type 1 diabetes loci. We identified potentially causal missense variants at DNASE1L3, PTPN22, SH2B3, and TYK2, and noncoding variants at MEG3, CD28-CTLA4, and IL2RA. We also identified potential candidate causal variants at SIRPG and TNFAIP3. Using functional assays, we confirmed allele-specific protein binding and differential enhancer activity for three variants: the CD28-CTLA4 rs117701653 SNP, MEG3 rs34552516 indel, and TNFAIP3 rs35926684 indel.

BACKGROUND:Detailed molecular analyses of cells from rheumatoid arthritis (RA) synovium hold promise in identifying cellular phenotypes that drive tissue pathology and joint damage. The Accelerating Medicines Partnership RA/SLE Network aims to deconstruct autoimmune pathology by examining cells within target tissues through multiple high-dimensional assays. Robust standardized protocols need to be developed before cellular phenotypes at a single cell level can be effectively compared across patient samples. METHODS:Multiple clinical sites collected cryopreserved synovial tissue fragments from arthroplasty and synovial biopsy in a 10% DMSO solution. Mechanical and enzymatic dissociation parameters were optimized for viable cell extraction and surface protein preservation for cell sorting and mass cytometry, as well as for reproducibility in RNA sequencing (RNA-seq). Cryopreserved synovial samples were collectively analyzed at a central processing site by a custom-designed and validated 35-marker mass cytometry panel. In parallel, each sample was flow sorted into fibroblast, T-cell, B-cell, and macrophage suspensions for bulk population RNA-seq and plate-based single-cell CEL-Seq2 RNA-seq. RESULTS:T-cell activation states. Bulk RNA-seq of sorted cell populations demonstrated robust separation of synovial lymphocytes, fibroblasts, and macrophages. Single-cell RNA-seq produced transcriptomes of over 1000 genes/cell, including transcripts encoding characteristic lineage markers identified. CONCLUSIONS:We have established a robust protocol to acquire viable cells from cryopreserved synovial tissue with intact transcriptomes and cell surface phenotypes. A centralized pipeline to generate multiple high-dimensional analyses of synovial tissue samples collected across a collaborative network was developed. Integrated analysis of such datasets from large patient cohorts may help define molecular heterogeneity within RA pathology and identify new therapeutic targets and biomarkers.

BACKGROUND:Systemic lupus erythematosus (SLE) is an autoimmune disease with genetic, hormonal, and environmental influences. In Western Europe and North America, individuals of West African descent have a 3-4 fold greater incidence of SLE than Caucasians. Paradoxically, West Africans in sub-Saharan Africa appear to have a low incidence of SLE, and some studies suggest a milder disease with less nephritis. In this study, we analyzed sera from African American female SLE patients and four other cohorts, one with SLE and others with varying degrees of risk for SLE in order to identify serologic factors that might correlate with risk of or protection against SLE. METHODS:Our cohorts included West African women with previous malaria infection assumed to be protected from development of SLE, clinically unaffected sisters of SLE patients with high risk of developing SLE, healthy African American women with intermediate risk, healthy Caucasian women with low risk of developing SLE, and women with a diagnosis of SLE. We developed a lupus risk index (LRI) based on titers of IgM and IgG anti-double stranded DNA antibodies and levels of C1q. RESULTS:The risk index was highest in SLE patients; second highest in unaffected sisters of SLE patients; third highest in healthy African-American women and lowest in healthy Caucasian women and malaria-exposed West African women. CONCLUSION/CONCLUSIONS:This risk index may be useful in early interventions to prevent SLE. In addition, it suggests new therapeutic approaches for the treatment of SLE.

BACKGROUND:Endometriosis is a chronic and underdiagnosed disease which affects 5-10% of women of childbearing age and is characterized by growth of endometrial tissue outside of the uterus, most often in the peritoneal cavity. Delay in diagnosis is a major problem for management of this disorder, and treatment is often not initiated until the disease has progressed for many years. Although the exact etiology of endometriosis remains unknown, retrograde menstruation is recognized as a common underlying factor leading to the deposit of menstrual effluent (ME) into the peritoneal cavity. Differences in the cellular biology and genetics of the cells within ME are therefore likely to explain why endometriosis develops in only a subset of women. METHODS:Patients with and without endometriosis were consented to provide ME. ME was analyzed by flow cytometry for CD45- and CD45+ cell populations or used to isolate stromal fibroblast cells. ME-derived stromal fibroblast cells were assessed using decidualization assays following the addition of cAMP and IGFBP-1 concentrations in the culture supernatants were measured by ELISA. In addition, RNA was collected and analyzed by RNA-Seq and qPCR for markers of decidualization and to identify differentially expressed genes in ME-derived stromal fibroblast cells obtained from controls and subjects with endometriosis (±cAMP). RESULTS:Flow cytometry analysis of cell subsets within the CD45+ fraction of ME revealed a significant decrease in the number of uterine NK cells in endometriosis patients compared with controls (p < 0.01). No other significant differences within either the CD45+ or CD45- cell populations were observed. Most strikingly, ME-derived stromal fibroblast cells cultured from endometriosis subjects showed impaired decidualization potential compared with controls. Highly significant differences in decidualization response were detected by measuring IGFBP-1 production at multiple time points after cAMP stimulation (p = 0.0025 at 6 h; p = 0.0045 at 24 h; p = 0.0125 at 48 h). RNA-Seq and qPCR analyses were used to identify genes differentially expressed by ME-derived stromal fibroblast cells obtained from endometriosis and control subjects. CONCLUSIONS:Menstrual effluent can be useful for investigating the pathobiology of endometriosis and for developing a non-invasive diagnostic for endometriosis which may lead to earlier and more effective treatments for this common disorder.

Gene-level analysis of ImmunoChip or genome-wide association studies (GWAS) data has not been previously reported for systemic sclerosis (SSc, scleroderma). The objective of this study was to analyze genetic susceptibility loci in SSc at the gene level and to determine if the detected associations were shared in African-American and White populations, using data from ImmunoChip and GWAS genotyping studies. The White sample included 1833 cases and 3466 controls (956 cases and 2741 controls from the US and 877 cases and 725 controls from Spain) and the African American sample, 291 cases and 260 controls. In both Whites and African Americans, we performed a gene-level analysis that integrates association statistics in a gene possibly harboring multiple SNPs with weak effect on disease risk, using Versatile Gene-based Association Study (VEGAS) software. The SNP-level analysis was performed using PLINK v.1.07. We identified 4 novel candidate genes (STAT1, FCGR2C, NIPSNAP3B, and SCT) significantly associated and 4 genes (SERBP1, PINX1, TMEM175 and EXOC2) suggestively associated with SSc in the gene level analysis in White patients. As an exploratory analysis we compared the results on Whites with those from African Americans. Of previously established susceptibility genes identified in Whites, only TNFAIP3 was significant at the nominal level (p = 6.13x10-3) in African Americans in the gene-level analysis of the ImmunoChip data. Among the top suggestive novel genes identified in Whites based on the ImmunoChip data, FCGR2C and PINX1 were only nominally significant in African Americans (p = 0.016 and p = 0.028, respectively), while among the top novel genes identified in the gene-level analysis in African Americans, UNC5C (p = 5.57x10-4) and CLEC16A (p = 0.0463) were also nominally significant in Whites. We also present the gene-level analysis of SSc clinical and autoantibody phenotypes among Whites. Our findings need to be validated by independent studies, particularly due to the limited sample size of African Americans.

Interferon regulatory factor 5 (IRF5) is widely recognized as a risk locus for systemic lupus erythematosus (SLE). Risk gene and IRF5 activation is triggered through toll-like receptor signaling. In myeloid cells, this leads to production of type I interferon and inflammatory cytokines, with enhanced production in cells of individuals harboring IRF5 risk alleles. Mouse models have also demonstrated the importance of IRF5 in B cell function, particularly plasma cell differentiation and isotype switching. Here, we evaluated the major SLE risk haplotype of IRF5 on the functional attributes of freshly isolated B cells from human subjects who do not have evidence of SLE or other forms of autoimmunity. We took this approach to avoid the complications of studying genotype-phenotype relationships in B cells that have been chronically exposed to an inflammatory disease environment before isolation. We focused on B cell endophenotypes that included gene expression, antibody secretion, class switching, and apoptotic susceptibility. We performed IRF5 overexpression studies, genetic reporter assays and electro-mobility shift assays on B and myeloid cell lines. Somewhat surprisingly, the results of our analyses indicate that IRF5 risk genotypes do not have a B cell intrinsic effect on these B cell functions. By contrast, we confirmed that the IRF5 risk and non-risk haplotypes exert differential effects in myeloid cells, including an increased susceptibility to apoptosis conferred by the risk haplotype. We also demonstrated an increased binding of the transcription factor specificity protein 1 to an insertion/deletion present in the risk haplotype. Our findings raise the specter that genetic risk alleles can have complex and unexpected lineage-specific effects, and these must be carefully considered when guiding or developing therapies based on understanding disease risk haplotypes.