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      Transcriptional landscape of psoriasis identifies the involvement of IL36 and IL36RN

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          Abstract

          Background

          In present study we performed whole transcriptome analysis in plaque psoriasis patients and compared lesional skin with non-lesional skin and with the skin from healthy controls. We sequenced total RNA from 12 lesional (LP), 12 non-lesional (NLP) and from 12 normal (C) skin biopsies.

          Results

          Compared with previous gene expression profiling studies we had three groups under analysis - LP, NLP and C. Using NLP samples allows to see the transcriptome of visually normal skin from psoriasis patient. In LP skin S100A12, S100A7A, LCE3E, DEFB4A, IL19 were found up regulated. In addition to already these well-described genes, we also found several other genes related to psoriasis. Namely, KLK9, OAS2, OAS3, PLA2G, IL36G, IL36RN were found to be significantly and consistently related to the psoriatic lesions and this finding is supported also by previous studies. The genes up-regulated in the LP samples were related to the innate immunity, IL17 and IL10 networks. In NLP samples innate immunity and IL17 network were activated, but activation of IL10 network was not evident. The transcriptional changes characteristic in the NLP samples can be considered as a molecular signature of “dormant psoriasis”.

          Conclusions

          Taken together, our study described the transcriptome profile characteristic for LP and NLP psoriatic skin. RNA profile of the NLP skin is in between the lesional and healthy skin, with its own specific pattern. We found that both LP and NLP have up-regulated IL17 network, whereas LP skin has up regulated IL10 related cytokines (IL19, IL20, IL24). Moreover, IL36G and IL36RN were identified as strong regulators of skin pathology in both LP and NLP skin samples, with stronger influence in LP samples.

          Electronic supplementary material

          The online version of this article (doi:10.1186/s12864-015-1508-2) contains supplementary material, which is available to authorized users.

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          Most cited references28

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          A Genome-Wide Association Study of Psoriasis and Psoriatic Arthritis Identifies New Disease Loci

          Introduction Psoriasis (PS) is a chronic inflammatory disease of the skin affecting 2–3% of the population [1]. Approximately 25% of patients also develop psoriatic arthritis (PSA), a common, debilitating auto-immune disease belonging to the family of spondyloarthritides [2],[3]. The recurrence risk (λS) of PSA is high, and estimates of 27–47 have been proposed [4],[5]. This is much higher than the estimated λS of PS which is estimated to be between 4 and 11[6]. PS and PSA are interrelated disorders, and the prevalence of PS is 19 times higher among first degree relatives of probands with PSA compared with the general population [7]. The pathogenesis of PS and PSA is complex, involving both genetic and environmental risk factors. Strong association of PS with the MHC class I region (PSORS1 or psoriasis susceptibility locus 1) was demonstrated in the 1970s [8] and has been confirmed in numerous subsequent studies [9]–[11]. However, the genetics of PSA is not as clear-cut and association with alleles of the HLA class I region is not reported to be as strong with PSA as with PS [7]. Hence, it has not been clear if PSA is a clinical phenotype that is distinct from PS without psoriatic arthritis and if is due to different predisposing genetic factors. A number of regions in the genome have been reported to be associated with PS [1], [12]–[14], and some have been convincingly replicated. This includes the 3'UTR of interleukin 12B (IL12B) [15],[16] and two non-synonymous SNPs of interleukin 23 receptor (IL23R) [16]. One of these (R381Q) was also shown to be associated with Crohn's disease [17]. However, together with the PSORS1 locus, the combined effect of these loci is unable to account entirely for genetic susceptibility to PS. In order to systematically search for other susceptibility loci, we undertook a genome wide association (GWA) scan to identify genetic factors predisposing to PS and PSA. Besides detecting strong association with the HLA class I region in the combined and PSA cohort, and replicating the recently reported associations with IL23R and IL12B, we identified a number of novel associations. These include a region on chromosome 13q13 harboring LHFP and COG6, a region on chromosome 15q21 harboring USP8-SPPL2A-TNFAIP8L3, association with the LCE cluster of genes on chromosome 1q21 from the PSORS4 locus, and a region of chromosome 4q27 recently reported to be associated with several other autoimmune diseases and associated with PSA and potentially PS. Results/Discussion For our “discovery” phase, 223 PS cases (132 cases with PS without arthritis and 91 PS cases with arthritis (PSA) were typed on the Illumina HumanHap300 arrays. We compared case data to publicly available genotype data of 519 European controls from the New York Cancer Project[18] collected with the same platform. The number of cases used for this scan is smaller than that used in many recently described genome wide association scans. However, the 91 cases of PSA had at least one first degree relative with PS and were expected to be enriched for genetic factors. Power calculations based on 223 controls and 519 controls indicated that using a threshold of P 0.8 (European HapMap CEPH (CEU) samples) with the most significant SNP identified in our study. The recombination rate based on the CEU HapMap is shown in light blue along the x axis (scale on the right). The LD relationship of Illumina discovery SNPs derived from CEU HapMap genotypes are shown below the graph. The most highly associated SNPs are indicated with an asterisk. The green arrows indicate the locations of select genes. 10.1371/journal.pgen.1000041.t001 Table 1 Summary of association with previously reported PS susceptibility loci (MHC, IL23R and IL12B) in U.S. PS cohort (810 cases, 1256 controls). Cyto. locn SNP Location (hg18) Gene/region Disc. P Disc. P (adj.) Rep. P Combined P Minor allele Freq. U.S. PS cases Freq. U.S. Controls OR US PS combined (95% C.I.) 6p21 rs10484554 31382534 MHC 8.7×10−12 7.8×10−11 1.82×10−30 1.81×10−39 T 0.32 0.151 2.8 (2.4, 3.3) 6p21 rs2395029 31539759 MHC 1.4×10−7 5.3×10−7 2.51×10−19 2.13×10−26 C 0.12 0.033 4.1 (3.1, 5.3) 1p31 rs11465804 67475114 IL23R 0.4 0.42 ND 0.0072 G 0.044 0.065 0.67 (0.50,0.9) 1p31 rs11209026 67478546 IL23R 0.067 0.081 0.0039 0.00014 T 0.039 0.066 0.56 (0.41,0.76) 1p31 rs12131065 67541594 IL23R 0.0025 0.0039 0.074 0.001 A 0.197 0.243 0.78 (0.66,0.91) 5q33 rs3212217 158687708 IL12B N.D. N.D. 0.012 N.D. G 0.158 0.199 N.D. 5q33 rs6887695 158755223 IL12B N.D. N.D. 0.00005 N.D. C 0.221 0.294 N.D. Cyto. Locn: Cytogenetic location of SNP; Disc P: Trend P values for the GWA scan; Disc. P (adj.): Genomic control adjusted trend P values for the GWA scan; Rep. P: Trend P values obtained with the U.S. PS replication cohort; Combined P: Trend P values for U.S. discovery and replication cohorts combined ; Freq. U.S. PS cases: Frequency of the minor allele in U.S. psoriasis cases; Freq. U.S. Controls: Frequency of minor allele in the control population. OR: Odds Ratio; C.I.: confidence interval; N.D.: Not Done. In the case of the U.K. PSA replication samples, rs10484554 was again highly significant (P = 6.86×10−11) (Table 2), although the frequency of the rs10484554*T allele exhibited population differences when frequencies in the U.K. and U.S. were compared. In the U.K. the rs10484554*T allele was found at a lower frequency in cases and controls (0.19 and 0.07 respectively; OR: 2.4 (95% CI: 1.8–3.1)). 10.1371/journal.pgen.1000041.t002 Table 2 Summary of association with previously reported PS susceptibility loci in U.K. PSA cohort (576 cases, 480 controls). SNP Gene/Region Trend P value Minor allele Freq. UK PSA cases Freq. UK PSA controls OR UK PSA (95% C.I.) rs10484554 MHC 6.86×10−11 T 0.19 0.07 2.4 (1.8, 3.1) rs2395029 MHC 1.86×10−10 C 0.12 0.04 3.2 (2.2, 4.6) rs11209026 IL23R 0.00083 T 0.043 0.079 0.52 (0.35, 0.77) rs12131065 IL23R 0.31 A 0.21 0.23 0.89 (0.72, 1.11) rs3212217 IL12B N.D. G N.D. N.D. N.D. rs6887695 IL12B 0.0013 C 0.213 0.28 0.69 (0.56, 0.85) UK PSA: U.K. Psoriasis cases with arthritis; OR: Odds Ratio; C.I.: confidence interval; N.D.: Not Done. A second SNP from the HLA class I region lying between MICA and MICB (rs2395029) was highly associated with PS and PSA. This SNP results in the G2V polymorphism of the class I gene HCP5 (HLA complex P5) which encodes an endogenous retroviral element. For this SNP, PS was associated with a combined P = 2.13×10−26 in the U.S. cohort and 1.86×10−10 in the U.K. PSA cohort (Table 1, Table 2). The OR of the rs2395029*C allele with both PS and PSA was higher than with any other SNP tested (4.1 and 3.2 with PS and PSA respectively). This allele was found at a frequency of ∼0.12 in cases and 0.04 in controls and did not exhibit the population frequency differences of rs10484554. The LD relationship between rs2395029 and rs10484554 is not strong (r2 = 0.33 in European CEPH HapMap samples and r2 = 0.23 in our U.S. case/control cohort). Conditioning upon rs10484554, the P value for rs2395029 was still significant (P = 7×10−10), hence effects from this SNP are likely to be independent. HCP5 is expressed primarily in cells of the immune system such as spleen, blood and thymus (http://smd-www.stanford.edu/), consistent with a potential role in autoimmunity. This allele was recently shown to explain 9.6% of the total variation in viral set point following HIV-1 infection[28]. This is of interest, since psoriasis can be triggered by infection with HIV and other viruses. Hence, it is possible that HCP5-C carriers mount a strong immune reaction to viral infection, but that in genetically susceptible individuals, this reaction leads to excessive inflammation in skin and joints. Overall, our observations indicate that MHC class I region SNPs are more highly associated with both PS and PSA than any other SNPs. IL23R associations A recent global association scan using a set of pooled PS samples and controls against a set of 25,215 genecentric SNPs confirmed a previously reported association with IL12B (rs3212227 in its 3′ UTR) [15] and identified a second region of association 60 kb upstream from its mRNA start site (rs6887695) [16]. An analysis of additional genes encoding components of the IL12B pathway lead to the identification of associations with Il23R (R381Q: rs11209026 and L310P: rs7530511) [16]. These SNPs were proposed to mark a common psoriasis-associated haplotype. Rs11209026 is also the SNP within IL23R reported to be associated with Crohn's disease[17]. In our discovery cohort, the most significant association in the IL23R interval was obtained with a different SNP from that described previously as being associated with PS (rs11209026). This SNP, where P = 0.0039 in the discovery cohort (Table 1), has not previously been reported to be associated with PS. The LD relationship between rs12131065 and the previously associated rs11209026 SNP is low (r2 = 0.031 in HapMap CEPH European samples; 0.009 in cases; 0.026 in controls). Conditioning upon rs11209026, the P value for rs11209026 was 0.013. Hence, effects from this SNP may be independent of rs11209026 and its association with PS should be investigated in other cohorts. SNP rs12131065 lies downstream from IL23R (63 kb from rs11209026) and 4.041 kb upstream from the gene for interleukin 12 receptor B2 (IL12RB2) (Figure 3). IL12RB2 is involved in IL12 dependent signaling, is upregulated by gamma interferon in Th1 cells and plays a role in Th1 differentiation[29]. Association with a SNP closer to IL12RB2 than IL23R is of interest since animals where IL12RB2 is inactivated develop autoimmune disease[30]. 10.1371/journal.pgen.1000041.g003 Figure 3 Association localization plots for the ILI23R region on chromosome 1. Symbols are the same as those used in Figure 2. SNPs indicated with an asterisk are rs11465804, rs11209026 (R381Q) and rs12131065. Association with the previously reported IL23R associated SNP rs11209026 in the discovery cohort was not significant (adjusted P = 0.081). Genotyping of rs11209026 and rs12131065 in the U.S. replication cohort yielded combined P values of 1.4×10−4 and 0.001 respectively (Table 1) consistent with replication of this locus with respect to previous studies. In the case of these two SNPs, the protective T and A alleles were found at frequencies of ∼0.04 and 0.2 in cases versus ∼0.07 and ∼0.24 of controls respectively. In the U.K. replication PSA cohort, association with rs11209026 was consistent with replication (P = 8.3×10−4), with the rs11209026*T allele being found at frequencies of ∼0.04 in cases and ∼0.08 in controls (Table 2). IL12B Associations Although the associated IL12B SNPs rs3212227 and rs6887695 were not interrogated by the Illumina screening panel of SNPs used here, typing of these SNPs in our replication U.S. case/control cohorts yielded P values of 0.021 and 5×10−5 and replicated previously reported associations (Table 1). In the U.K. PSA cohort, association with rs6887695 was also consistent with replication (P = 0.0013) (OR: 0.69; 95% CI: 0.56–0.85)) (Table 2). Novel Psoriasis Loci In the discovery cohort, there were four SNPs from 13q13 where P 40 years of age and were ascertained on the basis of not having PS, PSA, or any other inflammatory or autoimmune disease. Table S1 also provides information on how well the cases and controls were matched in terms of age and gender. It can be seen that the gender proportions and ages are similar in cases and controls, for both discovery and replication studies. Genotyping Methods DNA was normalized to a concentration of 100 ng/µl (diluted in 10 mM Tris/1 mM EDTA). Samples were quantitated with a Nanodrop Spectrophotometer (ND-1000). For the discovery phase, approximately 1 µg of genomic DNA was used to genotype each sample on the Illumina HumanHap300v2A Genotyping BeadChip. This was performed at the Robert S. Boas Center for Genomics and Human Genetics at The Feinstein Institute for Medical Research, Manhasset, NY. This assay relies on allele specific primer extension and the use of a single fluorochrome. Samples were processed according to the standard Illumina Infinium II automated protocol. This involved whole genome amplification, fragmentation, precipitation, resuspension in hybridization buffer and hybridization to the Illumina Bead Chips for a minimum of 16 h at 48°C. After hybridization the BeadChips were processed for the single base extension reaction, followed by staining and imaging on an Illumina Bead Array Reader. Normalized bead intensity data were loaded into the Illumina Beadstudio 2.0 software which converted fluorescence intensities into SNP genotypes. Genotyping for all the replication studies was performed with the Sequenom MassArray system (iPlex assay). This involves primer extension chemistry and mass spectrometric analysis described at our web site http://hg.wustl.edu/info/Sequenom_description.html. Quality Control Before analysis, we performed quality filtering of both samples and SNPs to ensure robust association tests. Based on previous criteria [61], we required that all samples used for the discovery phase pass a 93% genotyping call rate threshold, and that all SNPs pass a 95% call rate threshold. In the case of the replication studies, 57 individuals from the total of 2370 individuals in the replication study were removed because of low genotyping (i.e. when over half of the genotypes for a sample were missing). SNPs with 0.8 (European HapMap CEPH (CEU) samples) with the most significant SNP identified in our study. The recombination rate based on the CEU HapMap is shown in light blue along the x axis (scale on the right). The green arrows indicate the locations of select genes. The LD relationship of Illumina discovery SNPs derived from CEU HapMap genotypes are shown below the graph. The most highly associated SNP, rs6701216 is indicated with an asterisk above the LD plot. (9.70 MB TIF) Click here for additional data file. Figure S5 Association localization plots for autoimmune locus on chromosome 4q27 showing P values obtained in discovery sample. Symbols are the same as those used in Figure S4. The asterisk above the LD plot corresponds to rs6840978. (9.59 MB TIF) Click here for additional data file.
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            Psoriasis.

            Recent breakthroughs in the treatment of psoriasis have led to improved understanding of the pathogenesis of this disease. Activation of T lymphocytes leading to release of cytokines results in proliferation of keratinocytes. Several new biological therapies have been developed, which target specific steps in the pathogenesis of psoriasis. With these new treatments, variable degrees of clearing occur. Initial data suggest improved safety over older agents such as methotrexate and ciclosporin, but long-term data are necessary. Enhancements in topical therapy and phototherapy have also increased the armamentarium of treatments available for this disorder.
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              IL-36R ligands are potent regulators of dendritic and T cells.

              IL-36α (IL-1F6), IL-36β (IL-1F8), and IL-36γ (IL-1F9) are members of the IL-1 family of cytokines. These cytokines bind to IL-36R (IL-1Rrp2) and IL-1RAcP, activating similar intracellular signals as IL-1, whereas IL-36Ra (IL-1F5) acts as an IL-36R antagonist (IL-36Ra). In this study, we show that both murine bone marrow-derived dendritic cells (BMDCs) and CD4(+) T lymphocytes constitutively express IL-36R and respond to IL-36α, IL-36β, and IL-36γ. IL-36 induced the production of proinflammatory cytokines, including IL-12, IL-1β, IL-6, TNF-α, and IL-23 by BMDCs with a more potent stimulatory effect than that of other IL-1 cytokines. In addition, IL-36β enhanced the expression of CD80, CD86, and MHC class II by BMDCs. IL-36 also induced the production of IFN-γ, IL-4, and IL-17 by CD4(+) T cells and cultured splenocytes. These stimulatory effects were antagonized by IL-36Ra when used in 100- to 1000-fold molar excess. The immunization of mice with IL-36β significantly and specifically promoted Th1 responses. Our data thus indicate a critical role of IL-36R ligands in the interface between innate and adaptive immunity, leading to the stimulation of T helper responses.
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                Author and article information

                Contributors
                maris.keerman@kliinikum.ee
                sulev.koks@ut.ee
                ene.reiamnn@ut.ee
                ele.prans@ut.ee
                kristi.adram@kliinikum.ee
                kylli.kingo@kliinikum.ee
                Journal
                BMC Genomics
                BMC Genomics
                BMC Genomics
                BioMed Central (London )
                1471-2164
                19 April 2015
                19 April 2015
                2015
                : 16
                : 1
                : 322
                Affiliations
                [ ]Department of Dermatology, University of Tartu, Tartu, Estonia
                [ ]Department of Dermatology, Tartu University Hospital, Tartu, Estonia
                [ ]Department of Pathophysiology, Centre of Translational Medicine, University of Tartu, 19 Ravila Street, 50411 Tartu, Estonia
                [ ]Department of Reproductive Biology, Estonian University of Life Sciences, Tartu, Estonia
                Article
                1508
                10.1186/s12864-015-1508-2
                4405864
                25897967
                7ed401ad-07e8-4397-a779-dad53136327e
                © Keermann et al.; licensee BioMed Central. 2015

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 28 September 2014
                : 30 March 2015
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2015

                Genetics
                psoriasis,transcriptome,gene expression profiling,high-throughput nucleotide sequencing,functional genomics

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