Genome-Wide Expression Profiling of Five Mouse Models Identifies Similarities and Differences with Human Psoriasis

1Psoriasis is a chronic inflammatory disease that leads to widespread development of erythematous plaques with adherent silvery scales. The disease is believed to be primarily mediated by T-cells, which release cytokines that stimulate keratinocyte (KC) hyperproliferation and altered differentiation,. Development of a single suitable animal model would greatly facilitate research on the mechanism(s) of action that drive inflammatory and autoimmune processes associated with psoriasis –. Such an animal model, for example, would permit experiments using genetically uniform subjects within a controlled environment, as well as high-throughput screening of potential therapeutic agents. Most clinical features of psoriasis, however, arise spontaneously only in humans and closely related primate species,. The laboratory mouse offers the most flexible experimental system for development of new psoriasiform phenotypes and previous studies have described transgenic or deletion mutants with skin conditions that resemble human clinical psoriasis –. Given the many disparities between human and mouse skin, it cannot be expected that psoriasiform phenotypes in mice will mirror the human disease in every respect. For instance, relative to human skin, mouse skin has a denser distribution of hair follicles, thinner epidermis, and an underlying cutaneous muscle layer that is generally absent in humans,,. Additionally, mice possess subsets of inflammatory cells that are absent in humans,. Despite these challenges, psoriasis mouse models have already provided mechanistic insights into inflammatory skin diseases –.

2An ideal model would realistically recapitulate a marked epidermal hyperproliferation, thickening and altered differentiation of the epidermis, an inflammatory infiltrate that includes T-cells, altered vascularity, and responsiveness to current anti-psoriatic therapies –. Mouse phenotypes that satisfy a majority of these characteristics include; overexpression of the endothelial-specific receptor tyrosine kinase in basal KCs (K5-Tie2), topical application of the toll-like receptor (TLR) agonist imiquimod (IMQ), overexpression of human amphiregulin in the basal epidermal layer (K14-AREG), basal KC-specific overexpression of a constitutively active mutant of signal transducer and activator of transcription 3 (K5-Stat3C), and overexpression of the latent form of transforming growth factor beta 1 in basal KCs (K5-TGFβ1). The phenotypes of these models recapitulate key features of human psoriasis, but differ with respect to the initiating (biochemical) events. The K14-AREG and K5-Stat3C models involve epidermal overexpression of a growth factor and signaling component, respectively, which directly perturbs KC homeostasis, leading to elevated cytokine or chemokine production and secondary inflammatory responses,. The K5-Tie2 and K5-TGFβ1phenotypes may also arise, in part, from a direct perturbation of KC homeostasis; but in these models, a role has also been postulated for growth factor release and certain concurrent processes (e.g., angiogenesis, oxidative stress accumulation, and/or basement membrane degradation), which may also contribute to KC proliferation and initiation of inflammatory cascades,. By comparison, IMQ-treated mice develop a psoriasiform phenotype that may differ in fundamental ways, since the phenotype arises from direct (over)stimulation of the immune system. IMQ is a TLR7 agonist that drives skin inflammation and immune cell infiltration, followed by KC proliferation and enhanced dermal vascularity. In mice, these effects of IMQ produce red, scaly skin similar to human psoriasis, and indeed, clinical observations have indicated that IMQ can exacerbate psoriasis in patients –.

3The five psoriasiform phenotypes discussed above represent potentially useful tools for studying human psoriasis. However, further characterization of each model at the biochemical level is needed for refinement and development of mouse models with stronger similarity to clinical disease –. Along these lines, it has been challenging to align separate analyses performed by different laboratories, and no side-by-side evaluation has previously assessed each model using a common methodological strategy. Some investigators have closely followed a set of proposed guidelines for validation of psoriasis mouse models, which are based on phenotypic measures (e.g., acanthosis, vascularity, absence of papillomatosis) and experimental demonstration (e.g., T-cell dependence and drug response). This strategy has been valuable, when applied, but is at best semi-quantitative and does not clearly differentiate mouse phenotypes that satisfy most or all of the proposed standards (e.g., K5-Tie2 and K5-Stat3C). For this reason, phenotypic and experimental approaches should be complemented, but not replaced, by additional strategies. Genome-wide transcriptional profiling is an example of one such complementary approach. Microarray analyses have identified dramatic differences between psoriatic and normal skin from patients, which involve altered expression of hundreds of genes –, and several recent large-scale genome-wide association studies have confidently identified 25 psoriasis susceptibility loci –. These findings underscore the polygenic basis of psoriasis and suggest that pathogenesis involves numerous biochemical pathways. An expression profiling approach can provide a “big picture” characterization of this process and support development of quantifiable metrics for evaluating similarity between human psoriasis and mouse phenotypes, allowing investigators to determine whether correspondence between human and mouse model psoriatic phenotypes is larger than expected on the basis of chance alone, and to decompose the global transcriptional correspondence into finer parts and evaluate correspondence with respect to specific pathways and pre-defined gene categories. Furthermore, microarray-based evaluation facilitates objective evaluation of mouse phenotypes, without “dependent variable selection bias” or over-emphasis of characteristics that best correspond between mouse phenotypes and human psoriasis.

4In this study, global transcriptional profiling was utilized to evaluate the similarity between human psoriasis and the psoriasis-like phenotypes that develop in five mouse models (K5-Tie2, IMQ, K14-AREG, K5-Stat3C, K5-TGFβ1). A broad comparison is made between each mouse phenotype and clinical psoriasis on the basis of global gene expression patterns, along with more fine-grained comparisons that are specific to key psoriasis-associated biological processes and biochemical pathways. Additionally, for each mouse phenotype, we gauge the intensity of inflammation and composition of inflammatory infiltrate by analysis of leukocyte infiltration signatures embedded within genome-wide transcriptional response patterns. These analyses provide the first transcriptomics-based assessment of correspondence between human psoriasis and multiple mouse phenotypes, and we suggest that similar analytic strategies can be adopted in future work to evaluate existing and new mouse models of psoriasis and other skin diseases.

5Whole-genome microarray analysis was used to identify transcripts altered in human psoriasis and each of five mouse psoriasiform phenotypes (back skin of K5-Tie2 transgenic mice, back skin of IMQ-treated mice, both ear and tail skin of K14-AREG transgenic mice, back skin of K5-Stat3C mice, and back skin of K5-TGFβ1 mice; see representative images of each phenotype in Figure 1). Expression patterns associated with human psoriasis were evaluated by comparing psoriatic skin from patients (n = 58) with normal skin from control subjects with no history of psoriasis (n = 64). Expression patterns associated with mouse phenotypes were evaluated by comparing lesional skin from transgenic or IMQ-treated mice (n = 2–3) with normal skin obtained from control mice (n = 2–3). Of 54,675 transcripts represented on the Affymetrix Human Genome U133 Plus 2.0 Array, approximately 61% (33,322) were matched with at least one transcript derived from an orthologous gene represented on the Affymetrix Mouse Genome 430 2.0 Array. With respect to these human-mouse transcript pairs, fold-change estimates associated with human psoriasis (psoriasis/control) were positively correlated with corresponding estimates in mouse phenotypes (psoriasiform/control) (Figures 2A–2F; 0.18≤ r ≤0.25). A cluster analysis grouped the K5-Tie2, IMQ-treated and K5-TGFβ1 mice apart from the K14-AREG and K5-Stat3C models, with the K14-AREG and K5-Stat3C phenotypes exhibiting slightly greater similarity to the expression pattern of human psoriasis (Figure 2G).

6The global similarity between expression patterns in human psoriasis and mouse phenotypes was statistically significant for each mouse model evaluated. This was demonstrated by five different analytical approaches (Figures 3, 4, S1, S2 and S3). First, we asked whether mouse transcripts orthologous to genes with increased expression in human psoriasis were disproportionately elevated in psoriasiform phenotypes, and conversely, whether mouse orthologues of psoriasis-decreased genes were disproportionately decreased in psoriasiform phenotypes. This expectation was validated in both cases and with respect to each mouse phenotype considered (Figure 3; P<0.001 for each mouse model). Secondly, we evaluated whether overlap among ranked gene lists was statistically significant (Figure 4). Human transcripts were ranked according to the estimated fold-change difference between lesional and normal skin, and likewise for each mouse model, transcripts were ranked according to the estimated fold-change difference between psoriasiform and normal skin. This analysis revealed that ranked transcript lists associated with human psoriasis significantly overlapped with corresponding lists associated with each psoriasiform phenotype, regardless of whether the top N psoriasis-increased or psoriasis-decreased human transcripts were considered (P<0.05; 10≤ N ≤5000; see Figure 4). These conclusions were further supported by three additional statistical methods, including analysis of adjusted residuals (Figure S1), “detection rate” ROC curves (Figure S2), and the gene set enrichment score statistic proposed by Subramanian et al. (i.e., “GSEA analysis”, see Figure S3). We note that, for psoriasis-decreased genes, GSEA-generated p-values were non-significant with respect to the K5-TGFβ1 model (P = 0.318; Figure S3).

7Correspondence between human psoriasis and mouse phenotypes was also evident from inspection of the “trademark” expression patterns of human psoriasis, which we identified as the most consistent and pronounced gene expression differences between psoriatic plaques and normal human skin (Figure 5). In all five mouse phenotypes, there was increased expression of S100a9, Lcn2, S100a8, Sprr1b, Mpzl2, Has3 (Figure 5A), as well as decreased expression of Tppp, Stxbp6, and Cldn23 (Figure 5B), and each of these effects is consistent with characteristic expression patterns in clinical psoriasis. Additionally, we identified a set of 27 mouse genes (with human orthologues) that were significantly increased in all five mouse phenotypes (P<0.05), and in 23 of these cases, the orthologous human gene was elevated in skin from psoriasis patients (Figure S4). Likewise, we identified a set of 44 mouse genes (with human orthologues) that were significantly decreased in all five mouse phenotypes (P<0.05), and in 32 of 44 cases, associated human genes were correspondingly decreased in human psoriasis (Figure S5). There were also examples in which psoriasiform phenotypes failed to recapitulate a robust gene expression indicator of human psoriasis. For instance, expression of protocadherin 21 (PCDH21) is decreased by 68.4% in human psoriasis (FDR-adjusted P = 6.62×10−37), but the mouse ortholog Pcdh21 was in fact elevated 1.5-fold in K5-Tie2 lesions (P = 0.025), 54.2-fold in IMQ lesions (P = 2.43×10−7), 5.2-fold in K14-AREG ear lesions (P = 1.1×10−3), 24.9-fold in K14-AREG tail lesions (P = 1.48×10−6), 7.4-fold in K5-Stat3C lesions (P = 3.73×10−6), and 22.5-fold in K5-TGFβ1 lesions (P = 4.8×10−4) (Figure 5B and Figure S4). Another robust feature of human psoriasis was increased expression of C-type lectin domain family 7 member A (CLEC7A/DECTIN-1), which encodes a membrane receptor that mediates Th1/Th17 immune responses. In human psoriasis, expression of CLEC7A was elevated 8.7-fold (FDR-adjusted P<1.59×10−58), but expression of the mouse ortholog Clec7a was not altered in the K5-Tie2 phenotype (P = 0.843) and was decreased by 43% in the IMQ phenotype (P = 0.046) (Figure 5A).

8Gene Ontology (GO) biological processes significantly overrepresented among transcripts increased or decreased in human psoriasis were identified (P<0.05), representing the most salient features of the human psoriasis gene expression signature (Figures 6 and 7). For each overrepresented process, we identified the associated human genes altered in clinical psoriasis, and determined whether orthologous mouse genes were correspondingly altered in mouse psoriasiform phenotypes. This analysis revealed that many key aspects of the human psoriasis gene expression signature were mirrored by mouse psoriasiform phenotypes. The most striking point of correspondence, shared among the five mouse models, was elevated expression of transcripts involved in epidermal development and keratinization (see Figure 6). For instance, among transcripts increased significantly in human psoriasis, we identified 26 transcripts associated with the “epidermis development” (GO:0008544) gene ontology term (e.g., KRT16, KRT17, ELF3). Based on the human-mouse orthology, there were 28 mouse transcripts associated with these human transcripts, and of these, 92.9% were elevated in K5-Tie2 (26 of 28; P = 1.08×10−7), 89.3% in IMQ (25 of 28; P = 1.52×10−6), 71.4% in K14-AREG ear (20 of 28; P = 6.27×10−3), 92.9% in K14-AREG tail (26 of 28; P = 1.08×10−7), 75% in K5-Stat3C (21 of 28; P = 1.86×10−3), and 82.1% in K5-TGFβ1 (23 of 28; P = 9.00×10−5). Among transcripts decreased in human psoriasis, there was even stronger similarity among mouse models, involving a broad range of biological processes for which expression patterns were correspondent between psoriasiform phenotypes and human (e.g., response to insulin stimulus, development, transcription; see Figure 7).

9These analyses were repeated based upon the KEGG pathways overrepresented among transcripts increased or decreased in human psoriasis (Figures S6 and S7). As an alternative analysis method, we also extracted sets of human-mouse gene pairs with correspondent expression shifts in mouse phenotypes and human psoriasis, and identified GO biological process terms overrepresented within these gene sets. This strategy identified gene categories that, while not necessarily the most salient features of the human psoriasis expression signature, were nonetheless descriptive of points at which human psoriasis and mouse phenotypes correspond (Figure S8 and ).

10While key features of human psoriasis were recapitulated by mouse model phenotypes, points of non-correspondence relative to each other and to human psoriasis were also identified. Most notably, there was disparity between the K5-Tie2 and IMQ phenotypes relative to other mouse models, with respect to psoriasis-increased genes with immune-associated gene ontology terms, such as response to virus, response to lipopolysaccharide, response to cytokine stimulus, cellular defense response, innate immune response and positive regulation of αβ T-cell proliferation (Figures 6 and 8). This disparity between K5-Tie2 and IMQ phenotypes relative to other mouse models was also evident based upon inspection of KEGG pathway terms associated with transcripts elevated in human psoriasis (e.g., primary immunodeficiency, natural killer cell mediated cytotoxicity, toll-like receptor signaling pathway, cytokine-cytokine receptor interaction and leukocyte adhesion; see Figure S6). This trend was further illustrated by GO analysis of human-mouse transcript pairs, with conflicting expression patterns in clinical psoriasis and mouse phenotypes (Figures S10 and S11). This analysis revealed that pairs involving a psoriasis-increased transcript in humans and an orthologous transcript decreased in K5-Tie2 or IMQ lesions were often associated with immunity (e.g., response to virus, innate immune response; see Figure S10). The overall pattern is well-illustrated by the 129 transcripts increased in human psoriasis that were associated with the “immune response” (GO:0006955) GO term (see Figure 8). Of the 128 mouse transcripts that could be matched to the 129 psoriasis-upregulated human transcripts mapping to this term, more than 77% (>99/128) were correspondingly elevated in the K14-AREG, K5-Stat3C and K5-TGFβ1 phenotypes, but only 44% (56/128) and 59% (75/128) were correspondingly elevated in the K5-Tie2 and IMQ phenotypes. These observations suggest that, as compared to the IMQ and K5-Tie2 models, the K14-AREG, K5-Stat3C and K5-TGFβ1 phenotypes better recapitulate immune-associated gene expression patterns characteristic of clinical psoriasis.

11Human psoriasis is associated with increased expression of transcripts involved in cellular proliferation and KC differentiation and this was reflected in each mouse gene expression phenotype (Figure 6). However, IMQ-treated mice were less correspondent with this aspect of the human psoriasis expression pattern, while the K5-Tie2 and K5-TGFβ1 models were most similar to the clinical disease in this respect (e.g., see mitosis, DNA replication, DNA replication initiation, KC proliferation, cell division from Figure 6; see cell cycle and DNA replication from Figure S6; see mitotic anaphase from Figure S10). This trend is exemplified by 128 transcripts associated with mouse genes orthologous to the human “mitosis” genes with elevated expression in human psoriasis (e.g., GO:0007067; see Figure S12). Among these transcripts, more than 87% are increased in the K5-Tie2 and K5-TGFβ1 phenotypes (≥112 of 128), while 60.2% (77/128), 43.7% (56/128), 69.5% (89/128) and 64.1% (82/128) are increased in the IMQ, K14-AREG (ear), K14-AREG (tail) and K5-Stat3C phenotypes, respectively.

12We identified strong differences among mouse phenotypes with respect to the immune-associated gene expression patterns characteristic of human psoriasis, with the K14-AREG, K5-Stat3C and K5-TGFβ1 phenotypes exhibiting a closer correspondences to human psoriasis (Figure 8). One possibility is that models differ in terms of the type and abundance of leukocytes present within psoriasiform plaques, leading to dissimilar expression patterns among genes annotated with immune-related GO terms or KEGG pathways. To evaluate this possibility, we characterized each mouse phenotype using a microarray-based immunophenotyping algorithm, which estimates overall inflammation intensity and also identifies leukocyte subsets underlying an inflammation signature within microarray data (Figure 9) (see also Haider et al. for a similar approach). In brief, the algorithm utilizes gene expression profiles of cell populations harvested from mouse tissues (mostly leukocytes; e.g., T-cells, DCs, macrophages), and for each population, a set of “signature transcripts” is identified, which consists of transcripts highly expressed in that population relative to normal mouse skin. If a given leukocyte population is part of the infiltrate in lesional skin, it is expected that signature transcripts associated with that population will be disproportionately elevated in lesional skin relative to normal skin from control mice, and this information is used to establish an “inflammation profile”. In the present context, we have also adapted this approach to estimate an inflammation profile for human psoriasis, based upon expression patterns of human genes orthologous to signature transcripts associated with individual mouse leukocyte populations (Figure 9).

13The immunophenotype of human psoriatic plaques was consistent with elevated abundance of Th1 T-cell, CD4+ T-cell, CD8+ T-cell, DC and macrophage signatures (P<0.05; see Figure 9), which was an expected based upon prior clinical studies of psoriatic lesions. Most of these trends, however, were absent from the IMQ phenotype, and in general, the intensity of inflammation was low in IMQ-generated lesions, with significant evidence for invasion by macrophages and granulocytes (P<0.05), but no other leukocyte subsets (Figure 9). To some degree, inflammation intensity was also relatively low in lesions from K5-Tie2 mice, and surprisingly, there was no significant evidence for macrophage or DC infiltration, although there was evidence for infiltration by CD4+ and regulatory T-cells (P<0.05; Figure 9). Inflammation intensity was strongest in the K14-AREG, K5-Stat3C and K5-TGFβ1 models, with the strongest patterns associated with K14-AREG lesions (ear and tail), for which there was significant evidence of infiltration by CD4+ T-cells, Th1 T-cells, Th17 T-cells, CD8+ T-cells, regulatory T-cells, NK cells, DCs, macrophages and monocytes (P<0.05; Figure 9). The immunophenotypes of K5-Stat3C and K5-TGFβ1 models were comparable in most respects, although for K5-TGFβ1 lesions, there was stronger indication of T-cell infiltration, with significant CD4+ T-cell, CD8+ T-cell, helper T-cell and regulatory T-cell signatures (P<0.05; Figure 9). Taken together, these analyses support a ranking of mouse phenotypes with regard to overall inflammation intensity, with the strongest inflammation signature in K14-AREG lesions, moderately strong inflammation in K5-Stat3C and K5-TGFβ1 lesions, weak-to-moderate inflammation in K5-Tie2 lesions, and weak inflammation in the phenotype generated by topical application of IMQ.

14The above results indicated that mouse models differed with respect to immune-associated gene expression patterns (Figures 6 and S6) and also with respect to their microarray-based inflammation profiles (Figure 9). We therefore evaluated the expression of selected cytokines and chemokines thought to contribute to initiation or maintenance of the inflammatory cascade in human psoriasis (e.g., TNF, IL22, IL6, CXCL1) (Figure S13). This analysis pointed to key expression responses that were more prominent in the K14-AREG (ear and tail), K5-Stat3C and K5-TGFβ1 models as compared to the K5-Tie2 and IMQ models, such as increased expression of tumor necrosis factor-α (Tnf), interferon (IFN)-γ (Ifng), interleukin (IL)-6 (Il6) CXC-chemokine ligand 10 (Cxcl10), and integrin β2 (Itgb2) (Figure S13). For instance, we noted little change in Tnf expression for K5-Tie2 or IMQ lesions (6% increase for K5-Tie2 and 13% decrease for IMQ; P>0.43), while expression of Tnf was elevated 31% in K14-AREG ear lesions (P = 0.063), 48% in K14-AREG tail lesions (P = 0.047), 34% in K5-Stat3C lesions (P = 0.042) and 116% in K5-TGFβ1 lesions (P = 0.01). These results are consistent with decreased accumulation of key cytokines in psoriasiform lesions of K5-Tie2 and IMQ mice, which may account for lower intensity inflammation within these models (Figure 9).

15Gene expression shifts in both human psoriasis and mouse psoriasiform phenotypes are, in part, a consequence of KC responses to the local cytokine and chemokine environment. While mouse phenotypes differed with respect to localized abundance of mRNAs encoding key cytokines and chemokines (Figure S13), these disparities at the RNA level may or may not influence steady-state cytokine abundance or KC responses. We therefore identified sets of genes associated with such in vitro KC responses to cytokine treatment and evaluated how these gene sets were altered in both psoriatic skin from humans and lesional skin from mouse model phenotypes (Figure 10). This indicated that K14-AREG (ear), K14-AREG (tail), K5-Stat3C and K5-TGFβ1 phenotypes exhibited increased expression of transcripts that are induced by in vitro treatment of KCs with TNF-α, IFN-α and IFN-γ, while such responses were not observed with respect to the K5-Tie2 and IMQ phenotypes (Figure 10). Additionally, as transcriptional markers of KC differentiation, we identified gene sets associated with calcium supplementation of cultured KCs, and these gene sets were more strongly elevated in K5-Tie2 and K5-TGFβ1 lesions (Figure 10).

16The development of a “high-fidelity” mouse model of psoriasis would provide a valuable experimental system for investigating mechanisms of psoriasis pathogenesis and anti-psoriatic therapies. Despite differences that exist between humans and mice, mouse disease models have made important contributions to the investigation of major disease processes, including for example, heart disease, Alzheimer's disease, diabetes, cancer, as well as autoimmune syndromes such as lupus erythematosus and rheumatoid arthritis,. Because the primary disease symptoms of psoriasis occur at the skin surface, direct comparisons can be made between affected skin from patients and putative mouse models. We have followed this approach and have applied functional genomics methods to compare global transcriptional signatures of psoriasis phenotypes in humans and five psoriasis mouse models. With respect to an unbiased choice of psoriasis-associated GO and KEGG pathway terms, we identified specific similarities and differences between human psoriasis and each mouse model, and we suggest that these differences can be translated into strengths and weaknesses of each mouse model. For each model, gene expression patterns associated with epidermis development and keratinization mirrored those of clinical psoriasis. However, we noted divergence among models with respect to immune-associated gene expression, with a heightened inflammatory signature in lesions from K14-AREG, K5-Stat3C and K5-TGFβ1 mice, along with stronger elevation of mRNAs coding key cytokines and chemokines (e.g., Tnf, Ifng, IL-6) and more pronounced TNF-α and IFN-γ-driven expression patterns. Nevertheless, at a global level, there is strong and statistically significant similarity between expression patterns in clinical psoriasis and those of each mouse model evaluated by our study.

17Psoriasis results from an interaction between activated immunocytes and KCs, in which KCs exhibit abnormal maturation and proliferation in response to a complex cytokine network that mediates disease maintenance and progression. The key role of the immune response and inflammatory process has been convincingly supported by the identification of major histocompatibility complex and cytokine-associated loci in genome-wide association analyses, the effectiveness of immunosuppressant therapies in treatment of the disease, and the observation that psoriasis can be transferred between donor and recipient with bone marrow transplantation. For these reasons, a consensus point among investigators is that a realistic psoriasis mouse model should exhibit an inflammatory infiltrate resembling that found in clinical psoriasis, including T-cells, DCs and neutrophils, and that the psoriasiform phenotype should be both T-cell dependent and responsive to drug treatments targeting the immune system –. It was therefore significant, in the present study, to observe that gene expression signatures of mouse psoriasiform phenotypes diverged with respect to immune-associated transcripts, with three phenotypes more closely mirroring clinical psoriasis (i.e., K14-AREG, K5-Stat3C and K5-TGFβ1) as compared to two others (i.e., K5-Tie2 and IMQ). This disparity likely involves differences in the relative abundance of certain immune cell subsets within lesional skin of psoriasiform phenotypes, which would have consequent effects on the cytokine and chemokine milieu and development of the inflammatory cascade. For instance, the K14-AREG, K5-Stat3C and K5-TGFβ1 phenotypes showed a stronger inflammation signature overall, with significant evidence for infiltration by T-cells, monocytes, DC and macrophages (sure 9). These phenotypes contrast with that of the K5-Tie2 model, where our immunophenotyping algorithm supported increased expression of transcripts associated with CD4+ T-cells, but did not provide evidence for increased expression of transcripts highly expressed in cells from the monocyte-DC/macrophage lineage (Figure 9). Similarly, for IMQ-generated lesions, evidence of macrophage infiltration was obtained, but there was little or no indication of T-cell infiltration (Figure 9). Previously, immunohistochemical methods have detected increased abundance of CD8+ T cells, F4/80+ macrophages and CD11b and CD11c+ myeloid cells in K5-Tie2 lesions,, as well as increased abundance of CD4+ and CD8+ T-cells in IMQ-generated lesions. In these cases, however, the number of infiltrating immunocytes may not be sufficient to have a discernable impact on gene expression patterns, and this is likely to at least partially account for the observed disparity among models with respect to immune-associated transcripts (Figure 8).

18The environment of cytokines and chemokines in mouse psoriasiform lesions is largely shaped by early-stage inflammation responses. Along these lines, mouse phenotypes also differed in their relative expression level of the proinflammatory cytokines TNF-α, IFN-γ and IL-6, where in each case expression was more strongly elevated in K14-AREG, K5-Stat3C and K5-TGFβ1 lesions as compared to K5-Tie2 or IMQ lesions (Figure S13). Moreover, in vitro KC transcriptional responses to TNF-α, IFN-γ and IFN-α stimulation were not discernable with respect to the K5-Tie2 or IMQ expression signatures, but were discernable with respect to K14-AREG, K5-Stat3C and K5-TGFβ1 expression signatures (Figure 10). TNF-α is generated by NK-T and αβ-T-cells, macrophages and KCs, and is known to reinforce inflammatory processes. In psoriasis, the pathogenic role of TNF-α has been demonstrated by the effective treatment of patients with anti-TNF therapies. TNF-α is also a key component of local cytokine networks, and indeed, the quantitatively lower increase in TNF-α expression that we observed in K5-Tie2 and IMQ-generated lesions may explain the similar trends observed for IFN-γ and IL-6. In particular, a previous study using peripheral blood mononuclear cells has shown that TNF blockade suppresses IFN-γ expression, while in turn, IFN-γ blockade suppresses IL-6 expression. Our findings thus suggest that psoriasis mouse models can be differentiated with respect to a TNF-α/IFN-γ/IL-6 axis, which ultimately, may be reflective of disparities in the abundance of certain TNF-generating immunocytes (e.g., macrophages, DCs or T-cells).

19KC proliferation and consequent hyperplasia of the epidermal layer is a hallmark feature of clinical psoriasis. It is therefore noteworthy that our analysis detected differences among models related to mitosis-associated gene expression patterns. Mitosis-associated transcripts were most strongly elevated in K5-TGFβ1 lesions, and a comparable trend was evident for K5-Tie2 lesions, and in this regard, the K5-TGFβ1 and K5-Tie2 models were generally most similar to the mitotic gene expression signature of clinical psoriasis (see Figure S12). This trend was supported, for example, by expression patterns of many transcripts involved in DNA replication and the transitions between mitotic phases, including cyclin A2 (Ccna2), cyclin F (Ccnf) and budding uninhibited by benzimidazoles 1 homolog (Bub1b) (Figure S12).

20The psoriasis phenotypes evaluated in this study were generated on outbred, inbred and hybrid genetic backgrounds, including outbred CD1 mice (K5-Tie2), the inbred strain C57BL/6 (IMQ), as well as hybrid FVB/NCrIBR (K14-AREG), FVB/NHsd (K5-Stat3C), and ICR/B6D2 mice (K5-TGFβ1). While our analysis has identified disparities among models, it is possible that these disparities are, in part, driven by characteristics of individual mouse strains, which might in turn modulate the direct effects of manipulations we have considered. For this reason, we suggest that any psoriasis mouse model should be considered jointly with the genetic background with which it is associated (e.g., the “K5-Tie2/CD1 model”, the “B6/IMQ model”, etc.). Along these lines, an important avenue for future investigation is to evaluate background-dependence of manipulations that give rise to psoriasis-like phenotypes in mouse.

21The approach used in this study to evaluate psoriasis mouse models represents a general strategy that can be applied to score alternative mouse phenotypes with resemblance to specific human diseases. Potentially, the same methodology could be applied to determine whether psoriasiform phenotypes we evaluated are equally or better-suited as models for other inflammatory skin conditions, such as atopic dermatitis or allergic contact dermatitis. The microarray-based analytical approach we have implemented does not replace conventional validation criteria for psoriasis mouse models, but extends these criteria by providing a quantitative “yardstick” that can be used to clearly judge progress towards more realistic mouse phenotypes. This can guide development of new psoriasis mouse models by identifying combinations of genetic manipulations that complement each other well and also provide guidance to scientists in choosing the most appropriate mouse model to use when testing specific mechanistic and therapeutic hypotheses. Ultimately, this may lead to development of psoriasis mouse models with stronger biochemical similarity to the human disease.

22This study was conducted in compliance with good clinical practice and according to the Declaration of Helsinki principles. Informed written consent was obtained from all human subjects, under protocols approved by the institutional review board of the University of Michigan (HUM00037994). All animal protocols were approved by animal welfare committees at each participating institution; Case Western Reserve University Institutional Animal Care and Use Committee (IACUC, #2009-0193), Erasmus Medical Center Animal Ethics Committee (Advies DEC Nr. EUR 1846 (EMCnr. 128-09-09), Institutional Animal Care and Use Committee of the University of Texas, Austin (AUP-2010-00029), Institutional Animal Care and Use Committee of the University of Colorado (B-850008(08)2E and the Institutional Animal Care and Use Committee of Mayo Clinic (A1009-Rochester).

23The patient population and sample processing methods for the collection of human microarray data has been described in a recent report. In brief, the study involved 58 psoriasis patients (ages 21- 69) and 64 normal healthy control subjects (ages 18 - 45) recruited from areas surrounding Detroit, Michigan. The 58 psoriasis patients were chosen on the basis of having one or more psoriatic plaques not limited to the scalp region. If the patient had only one plaque, the single plaque was large in size (greater than 1% of total body area). No systemic anti-psoriatic treatments were used for 2 weeks prior to biopsy, and no topical treatments were used for 1 week prior to biopsy. In control subjects, biopsies were always taken from the buttocks or upper thighs. RNA samples were hybridized to the Affymetrix Human Genome U133 Plus 2.0 Array, which includes probesets corresponding to 54675 human transcripts. All the microarray data are MIAME compliant. Raw microarray data from the psoriasis cohort has been deposited in the NCBI Gene Expression Omnibus (GEO, http://www.ncbi.nlm.nih.gov/geo) and is accessible through GEO Series accession number GSE13355.

24Generation of transgenic mice bearing psoriasiform phenotypes has been described in previous reports –. The K5-Tie2 mice were generated by crossing a KC-specific K5-tTA driver line (Tg(KRT5-tTA)1216Glk) with a TetOSTek/Tie2 responder line (Tg(TetOS-Tek)1Dmt) that had been generated on an outbred CD1 background,. The generation of K14-AREG (FVB/NCrIBR-Tg(KRT14-AREG)3Pwc), K5-Stat3C (FVB-Tg(KRT5-Stat3*A661C*N663C)1Jdg) and K5-TGFb1 ((ICRxB6D2)F1-Tg(KRT5-TGF-B1)F2020Xjw) transgenic mice is described in the reports of Cook et al., Sano et al. and Li et al., respectively. For all experiments involving transgenic mice, experimental and control animals were genotyped at weaning using PCR, and development of psoriasiform lesions was spontaneous and not induced by wounding (e.g., tape stripping). For the IMQ-generated phenotype, the treatment protocol was to apply a daily topical dose of 62.5 mg IMQ cream (5% Aldara; 3M Pharmaceuticals) to the shaved back region of 8–10 week old C57BL/6 mice. This treatment was carried out for six consecutive days, and during this time, control animals were treated with a vehicle cream (Vaseline Lanette cream; Fagron). In all experiments, adult mice were euthanized at 10–20 weeks of age at which time ear, tail or back skin samples were flash frozen and stored at −80°C prior to the isolation of total RNA. We have evaluated back skin samples from the K5-Tie2, IMQ, K5-Stat3C and K5-TGFβ1. In K14-AREG mice, however, we have focused on tail and ear skin phenotypes to be consistent with previous studies, and because focusing on hairless regions prevented analyses from being influenced by K14-driven overexpression of AREG in the outer root sheath. For all samples, total RNA was extracted using the RNeasy mini kit (Qiagen, Valencia, CA), and after further processing, cDNA was hybridized to Affymetrix 430 2.0 arrays (45,101 probesets).

25The human and mouse datasets were normalized using the Robust Multichip Average (RMA) algorithm. Following RMA normalization, human data were further processed to calculate expression scores adjusted for gender and batch effects as described by Gudjonsson et al. (51). Analyses were based upon a between-chip mapping of transcripts represented on the Human Genome U133 Plus 2.0 and transcripts on the Affymetrix Mouse Genome 430 2.0 array. This map was downloaded as a single CSV file from the NetAffx analysis center in July 2009, and is based upon reference-sequence similarity from the HomoloGene database.

26Differential expression of transcripts between human psoriatic skin samples and control skin samples was evaluated using the Limma linear modeling package, with P-value adjustment using the Benjamini-Hochberg method. All p-values generated from differential expression analyses were derived from two-tailed hypothesis tests. The over-representation of KEGG and gene ontology terms was evaluated based upon the conditional hypergeometric test procedure implemented in the GOstats package, which is available as part of the R Bioconductor software suite. Among transcripts increased or decreased in human psoriasis, a large number of Gene Ontology biological process or KEGG pathway terms were significantly over-represented. Of these, we have focused on that were most frequently associated with the transcripts significantly altered in human psoriasis (i.e., at least 10–12 transcripts per term in Figures 6 and 7; at least 3 transcripts per term in Figures S6 and S7). Correspondence between human-mouse expression patterns with respect to particular Gene Ontology or KEGG pathways was evaluated based upon two-tailed hypothesis tests (i.e., t-tests), which evaluated whether, among transcripts associated with a given term, the mean log2-transformed expression difference between psoriasiform and normal mice was greater or less than zero.