Transcriptional landscape of epithelial and immune cell populations revealed through FACS-seq of healthy human skin.

Human skin consists of multiple cell types, including epithelial, immune, and stromal cells. Transcriptomic analyses have previously been performed from bulk skin samples or from epithelial and immune cells expanded in cell culture. However, transcriptomic analysis of bulk skin tends to drown out expression signals from relatively rare cells while cell culture methods may significantly alter cellular phenotypes and gene expression profiles. To identify distinct transcriptomic profiles of multiple cell populations without substantially altering cell phenotypes, we employed a fluorescence activated cell sorting method to isolate keratinocytes, dendritic cells, CD4+ T effector cells, and CD8+ T effector cells from healthy skin samples, followed by RNA-seq of each cell population. Principal components analysis revealed distinct clustering of cell types across samples, while differential expression and coexpression network analyses revealed transcriptional profiles of individual cell populations distinct from bulk skin, most strikingly in the least abundant CD8+ T effector population. Our work provides a high resolution view of cutaneous cellular gene expression and suggests that transcriptomic profiling of bulk skin may inadequately capture the contribution of less abundant cell types

Large-Scale Imputation of KIR Copy Number and HLA Alleles in North American and European Psoriasis Case-Control Cohorts Reveals Association of Inhibitory KIR2DL2 With Psoriasis

Killer cell immunoglobulin-like receptors (KIR) regulate immune responses in NK and CD8+ T cells via interaction with HLA ligands. KIR genes, including KIR2DS1, KIR3DL1, and KIR3DS1 have previously been implicated in psoriasis susceptibility. However, these previous studies were constrained to small sample sizes, in part due to the time and expense required for direct genotyping of KIR genes. Here, we implemented KIR*IMP to impute KIR copy number from single-nucleotide polymorphisms (SNPs) on chromosome 19 in the discovery cohort (n=11,912) from the PAGE consortium, University of California San Francisco, and the University of Dundee, and in a replication cohort (n=66,357) from Kaiser Permanente Northern California. Stratified multivariate logistic regression that accounted for patient ancestry and high-risk HLA alleles revealed that KIR2DL2 copy number was significantly associated with psoriasis in the discovery cohort (p ≤ 0.05). The KIR2DL2 copy number association was replicated in the Kaiser Permanente replication cohort. This is the first reported association of KIR2DL2 copy number with psoriasis and highlights the importance of KIR genetics in the pathogenesis of psoriasis

Cross-Tissue Transcriptomic Analysis Leveraging Machine Learning Approaches Identifies New Biomarkers for Rheumatoid Arthritis

There is an urgent need to identify biomarkers for diagnosis and disease activity monitoring in rheumatoid arthritis (RA). We leveraged publicly available microarray gene expression data in the NCBI GEO database for whole blood (N=1,885) and synovial (N=284) tissues from RA patients and healthy controls. We developed a robust machine learning feature selection pipeline with validation on five independent datasets culminating in 13 genes: TNFAIP6, S100A8, TNFSF10, DRAM1, LY96, QPCT, KYNU, ENTPD1, CLIC1, ATP6V0E1, HSP90AB1, NCL and CIRBP which define the RA score and demonstrate its clinical utility: the score tracks the disease activity DAS28 (p = 7e-9), distinguishes osteoarthritis (OA) from RA (OR 0.57, p = 8e-10) and polyJIA from healthy controls (OR 1.15, p = 2e-4) and monitors treatment effect in RA (p = 2e-4). Finally, the immunoblotting analysis of six proteins on an independent cohort confirmed two proteins, TNFAIP6/TSG6 and HSP90AB1/HSP90

Specificity of the STAT4 Genetic Association for Severe Disease Manifestations of Systemic Lupus Erythematosus

Systemic lupus erythematosus (SLE) is a genetically complex disease with heterogeneous clinical manifestations. A polymorphism in the STAT4 gene has recently been established as a risk factor for SLE, but the relationship with specific SLE subphenotypes has not been studied. We studied 137 SNPs in the STAT4 region genotyped in 4 independent SLE case series (total n = 1398) and 2560 healthy controls, along with clinical data for the cases. Using conditional testing, we confirmed the most significant STAT4 haplotype for SLE risk. We then studied a SNP marking this haplotype for association with specific SLE subphenotypes, including autoantibody production, nephritis, arthritis, mucocutaneous manifestations, and age at diagnosis. To prevent possible type-I errors from population stratification, we reanalyzed the data using a subset of subjects determined to be most homogeneous based on principal components analysis of genome-wide data. We confirmed that four SNPs in very high LD (r2 = 0.94 to 0.99) were most strongly associated with SLE, and there was no compelling evidence for additional SLE risk loci in the STAT4 region. SNP rs7574865 marking this haplotype had a minor allele frequency (MAF) = 31.1% in SLE cases compared with 22.5% in controls (OR = 1.56, p = 10−16). This SNP was more strongly associated with SLE characterized by double-stranded DNA autoantibodies (MAF = 35.1%, OR = 1.86, p<10−19), nephritis (MAF = 34.3%, OR = 1.80, p<10−11), and age at diagnosis<30 years (MAF = 33.8%, OR = 1.77, p<10−13). An association with severe nephritis was even more striking (MAF = 39.2%, OR = 2.35, p<10−4 in the homogeneous subset of subjects). In contrast, STAT4 was less strongly associated with oral ulcers, a manifestation associated with milder disease. We conclude that this common polymorphism of STAT4 contributes to the phenotypic heterogeneity of SLE, predisposing specifically to more severe disease

Differential genetic associations for systemic lupus erythematosus based on anti-dsDNA autoantibody production

Systemic lupus erythematosus (SLE) is a clinically heterogeneous, systemic autoimmune disease characterized by autoantibody formation. Previously published genome-wide association studies (GWAS) have investigated SLE as a single phenotype. Therefore, we conducted a GWAS to identify genetic factors associated with anti-dsDNA autoantibody production, a SLE-related autoantibody with diagnostic and clinical importance. Using two independent datasets, over 400,000 single nucleotide polymorphisms (SNPs) were studied in a total of 1,717 SLE cases and 4,813 healthy controls. Anti-dsDNA autoantibody positive (anti-dsDNA +, n = 811) and anti-dsDNA autoantibody negative (anti-dsDNA -, n = 906) SLE cases were compared to healthy controls and to each other to identify SNPs associated specifically with these SLE subtypes. SNPs in the previously identified SLE susceptibility loci STAT4, IRF5, ITGAM, and the major histocompatibility complex were strongly associated with anti-dsDNA + SLE. Far fewer and weaker associations were observed for anti-dsDNA - SLE. For example, rs7574865 in STAT4 had an OR for anti-dsDNA + SLE of 1.77 (95% CI 1.57-1.99, p = 2.0E-20) compared to an OR for anti-dsDNA - SLE of 1.26 (95% CI 1.12-1.41, p = 2.4E-04), with pheterogeneity<0.0005. SNPs in the SLE susceptibility loci BANK1, KIAA1542, and UBE2L3 showed evidence of association with anti-dsDNA + SLE and were not associated with anti-dsDNA - SLE. In conclusion, we identified differential genetic associations with SLE based on anti-dsDNA autoantibody production. Many previously identified SLE susceptibility loci may confer disease risk through their role in autoantibody production and be more accurately described as autoantibody propensity loci. Lack of strong SNP associations may suggest that other types of genetic variation or non-genetic factors such as environmental exposures have a greater impact on susceptibility to anti-dsDNA - SLE

High-Density SNP Screening of the Major Histocompatibility Complex in Systemic Lupus Erythematosus Demonstrates Strong Evidence for Independent Susceptibility Regions

A substantial genetic contribution to systemic lupus erythematosus (SLE) risk is conferred by major histocompatibility complex (MHC) gene(s) on chromosome 6p21. Previous studies in SLE have lacked statistical power and genetic resolution to fully define MHC influences. We characterized 1,610 Caucasian SLE cases and 1,470 parents for 1,974 MHC SNPs, the highly polymorphic HLA-DRB1 locus, and a panel of ancestry informative markers. Single-marker analyses revealed strong signals for SNPs within several MHC regions, as well as with HLA-DRB1 (global p = 9.99×10−16). The most strongly associated DRB1 alleles were: *0301 (odds ratio, OR = 2.21, p = 2.53×10−12), *1401 (OR = 0.50, p = 0.0002), and *1501 (OR = 1.39, p = 0.0032). The MHC region SNP demonstrating the strongest evidence of association with SLE was rs3117103, with OR = 2.44 and p = 2.80×10−13. Conditional haplotype and stepwise logistic regression analyses identified strong evidence for association between SLE and the extended class I, class I, class III, class II, and the extended class II MHC regions. Sequential removal of SLE–associated DRB1 haplotypes revealed independent effects due to variation within OR2H2 (extended class I, rs362521, p = 0.006), CREBL1 (class III, rs8283, p = 0.01), and DQB2 (class II, rs7769979, p = 0.003, and rs10947345, p = 0.0004). Further, conditional haplotype analyses demonstrated that variation within MICB (class I, rs3828903, p = 0.006) also contributes to SLE risk independent of HLA-DRB1*0301. Our results for the first time delineate with high resolution several MHC regions with independent contributions to SLE risk. We provide a list of candidate variants based on biologic and functional considerations that may be causally related to SLE risk and warrant further investigation